diff --git a/Workyard/07DA001_discharge_daily_withoutmissing.csv b/Workyard/07DA001_discharge_daily_withoutmissing.csv
new file mode 100644
index 00000000..f253723b
--- /dev/null
+++ b/Workyard/07DA001_discharge_daily_withoutmissing.csv
@@ -0,0 +1,24744 @@
+Daily Discharge (m3/s) (PARAM = 1) and Daily Water Level (m) (PARAM = 2)
+ ID,PARAM,Date,Value,SYM
+07DA001,1,1957/10/01,467,
+07DA001,1,1957/10/02,467,
+07DA001,1,1957/10/03,467,
+07DA001,1,1957/10/04,476,
+07DA001,1,1957/10/05,487,
+07DA001,1,1957/10/06,496,
+07DA001,1,1957/10/07,501,
+07DA001,1,1957/10/08,535,
+07DA001,1,1957/10/09,541,
+07DA001,1,1957/10/10,544,
+07DA001,1,1957/10/11,524,
+07DA001,1,1957/10/12,510,
+07DA001,1,1957/10/13,510,
+07DA001,1,1957/10/14,521,
+07DA001,1,1957/10/15,530,
+07DA001,1,1957/10/16,544,
+07DA001,1,1957/10/17,561,
+07DA001,1,1957/10/18,586,
+07DA001,1,1957/10/19,626,
+07DA001,1,1957/10/20,685,
+07DA001,1,1957/10/21,728,
+07DA001,1,1957/10/22,688,B
+07DA001,1,1957/10/23,651,B
+07DA001,1,1957/10/24,623,B
+07DA001,1,1957/10/25,572,B
+07DA001,1,1957/10/26,538,B
+07DA001,1,1957/10/27,498,B
+07DA001,1,1957/10/28,413,B
+07DA001,1,1957/10/29,394,B
+07DA001,1,1957/10/30,394,B
+07DA001,1,1957/10/31,416,B
+07DA001,1,1957/11/01,481,B
+07DA001,1,1957/11/02,530,B
+07DA001,1,1957/11/03,538,B
+07DA001,1,1957/11/04,541,B
+07DA001,1,1957/11/05,547,B
+07DA001,1,1957/11/06,575,B
+07DA001,1,1957/11/07,572,B
+07DA001,1,1957/11/08,538,B
+07DA001,1,1957/11/09,513,B
+07DA001,1,1957/11/10,484,B
+07DA001,1,1957/11/11,470,B
+07DA001,1,1957/11/12,462,B
+07DA001,1,1957/11/13,445,B
+07DA001,1,1957/11/14,439,B
+07DA001,1,1957/11/15,411,B
+07DA001,1,1957/11/16,419,B
+07DA001,1,1957/11/17,462,B
+07DA001,1,1957/11/18,436,B
+07DA001,1,1957/11/19,396,B
+07DA001,1,1957/11/20,402,B
+07DA001,1,1957/11/21,362,B
+07DA001,1,1957/11/22,331,B
+07DA001,1,1957/11/23,323,B
+07DA001,1,1957/11/24,292,B
+07DA001,1,1957/11/25,294,B
+07DA001,1,1957/11/26,354,B
+07DA001,1,1957/11/27,377,B
+07DA001,1,1957/11/28,337,B
+07DA001,1,1957/11/29,385,B
+07DA001,1,1957/11/30,422,B
+07DA001,1,1957/12/01,464,B
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+07DA001,1,1957/12/06,300,B
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+07DA001,1,1957/12/08,311,B
+07DA001,1,1957/12/09,252,B
+07DA001,1,1957/12/10,244,B
+07DA001,1,1957/12/11,179,B
+07DA001,1,1957/12/12,292,B
+07DA001,1,1957/12/13,328,B
+07DA001,1,1957/12/14,323,B
+07DA001,1,1957/12/15,297,B
+07DA001,1,1957/12/16,255,B
+07DA001,1,1957/12/17,283,B
+07DA001,1,1957/12/18,297,B
+07DA001,1,1957/12/19,283,B
+07DA001,1,1957/12/20,283,B
+07DA001,1,1957/12/21,278,B
+07DA001,1,1957/12/22,255,B
+07DA001,1,1957/12/23,258,B
+07DA001,1,1957/12/24,263,B
+07DA001,1,1957/12/25,246,B
+07DA001,1,1957/12/26,244,B
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+07DA001,1,1957/12/28,241,B
+07DA001,1,1957/12/29,238,B
+07DA001,1,1957/12/30,244,B
+07DA001,1,1957/12/31,235,B
+07DA001,1,1958/01/01,246,B
+07DA001,1,1958/01/02,244,B
+07DA001,1,1958/01/03,238,B
+07DA001,1,1958/01/04,241,B
+07DA001,1,1958/01/05,232,B
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+07DA001,1,1958/01/07,227,B
+07DA001,1,1958/01/08,229,B
+07DA001,1,1958/01/09,218,B
+07DA001,1,1958/01/10,215,B
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+07DA001,1,1958/01/18,212,B
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+07DA001,1,1958/01/21,207,B
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+07DA001,1,1958/03/25,173,B
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+07DA001,1,1958/04/20,1980,B
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+07DA001,1,1958/04/27,1500,
+07DA001,1,1958/04/28,1410,
+07DA001,1,1958/04/29,1350,
+07DA001,1,1958/04/30,1250,A
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diff --git a/Workyard/Algorithm.ipynb b/Workyard/Algorithm.ipynb
new file mode 100644
index 00000000..f556ac71
--- /dev/null
+++ b/Workyard/Algorithm.ipynb
@@ -0,0 +1,894 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d3382417-3993-4e5d-8390-0c6cc4197326",
+   "metadata": {},
+   "source": [
+    "## Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "bb67d97e-8317-4b2f-be8e-c8ac9f45f196",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "862f09e2-4350-4eb5-8bdc-d865a99076eb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "4c68de36-ea9f-43be-aa9e-13fdd7b4a3ab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining time period & q_critical\n",
+    "\n",
+    "experiment_start_date = \"2014-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2014-12-31T00:00:00Z\"\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "hysets_id = \"hysets_07DA001\"\n",
+    "basin_size = 132572"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "c2d00787-45c7-4f63-8641-5f1f5f67127e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Loading in data\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"ERA5-1970-2024\"\n",
+    "forcing_path_ERA5.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "calibration_temp = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"calibration_temp\"\n",
+    "calibration_temp.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "b40fb132-370d-4584-b198-4a789d02abc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>20367</th>\n",
+       "      <td>2014-01-01</td>\n",
+       "      <td>177.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20368</th>\n",
+       "      <td>2014-01-02</td>\n",
+       "      <td>188.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20369</th>\n",
+       "      <td>2014-01-03</td>\n",
+       "      <td>198.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20370</th>\n",
+       "      <td>2014-01-04</td>\n",
+       "      <td>204.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20371</th>\n",
+       "      <td>2014-01-05</td>\n",
+       "      <td>208.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Date  discharge_m3s\n",
+       "20367 2014-01-01          177.0\n",
+       "20368 2014-01-02          188.0\n",
+       "20369 2014-01-03          198.0\n",
+       "20370 2014-01-04          204.0\n",
+       "20371 2014-01-05          208.0"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "q_obs = q_obs[\n",
+    "    (q_obs[\"Date\"] >= start_date) &\n",
+    "    (q_obs[\"Date\"] <= end_date)\n",
+    "].copy()\n",
+    "\n",
+    "q_obs.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "eb8f1766-b180-4486-9cec-6539c086eb7f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"], label=\"Observed discharge\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.axhline(\n",
+    "    y=q_critical,\n",
+    "    linestyle=\":\",\n",
+    "    label=f\"Critical discharge ({q_critical} m³/s)\",\n",
+    "    color='black'\n",
+    ")\n",
+    "\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "07a239a5-398f-4ad2-9a33-f2d199485309",
+   "metadata": {},
+   "source": [
+    "# Finding range"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9c87425e-c0d7-49ad-aab7-57bb5df5af0d",
+   "metadata": {},
+   "source": [
+    "## Start of range (freshet)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "504d4401-3712-406b-b9ef-884db8702c28",
+   "metadata": {},
+   "source": [
+    "### Idea 1: Rate of change\n",
+    "\n",
+    "gemiddelde dQ over 5 dagen periode moet groter zijn dan 15 m^3/s increase per dag voor consecutive dagen \n",
+    "& Q > Q_kritisch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "204f6612-01b4-43c5-aff4-d345817047d9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Define dQ\n",
+    "\n",
+    "# dQ = Q_today - Q_yesterday\n",
+    "\n",
+    "# dQ over 5 dagen periode moet groter zijn dan x m^3/s increase per dag voor consecutive dagen \n",
+    "# & Q > q_kritisch\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dc8791fb-3dac-425a-b5bd-45cdb8a0331f",
+   "metadata": {},
+   "source": [
+    "### Idea 2: Q_critical "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "727e107a-465a-4947-ba90-494ec323a262",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>first_above_critical_date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>2014-04-23</td>\n",
+       "      <td>506.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   year first_above_critical_date  discharge_m3s\n",
+       "0  2014                2014-04-23          506.0"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create pd for identified critical dates\n",
+    "\n",
+    "freshet_start_date = []\n",
+    "\n",
+    "for year, group in q_obs.groupby(q_obs[\"Date\"].dt.year):\n",
+    "\n",
+    "    # Set start date to March 1\n",
+    "    start_date_algorithm = pd.to_datetime(f\"{year}-03-01\")\n",
+    "    season_data = group[group[\"Date\"] >= start_date_algorithm].copy()\n",
+    "    \n",
+    "    # Identify first day where q > q_critical\n",
+    "    \n",
+    "    above_critical = season_data[\n",
+    "        season_data[\"discharge_m3s\"] > q_critical\n",
+    "    ]\n",
+    "    \n",
+    "    if len(above_critical) > 0:\n",
+    "        first_day = above_critical.iloc[0]\n",
+    "        \n",
+    "        freshet_start_date.append({\n",
+    "            \"year\": year,\n",
+    "            \"first_above_critical_date\": first_day[\"Date\"],\n",
+    "            \"discharge_m3s\": first_day[\"discharge_m3s\"]\n",
+    "        })\n",
+    "    else:\n",
+    "        freshet_start_date.append({\n",
+    "            \"year\": year,\n",
+    "            \"first_above_critical_date\": pd.NaT,\n",
+    "            \"discharge_m3s\": None\n",
+    "        })\n",
+    "\n",
+    "freshet_start_date = pd.DataFrame(freshet_start_date)\n",
+    "\n",
+    "freshet_start_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "e20e293c-245d-47da-9b45-1c9675f989f4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"], label='Observed discharge')\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.axhline(\n",
+    "    y=q_critical,\n",
+    "    linestyle=\":\",\n",
+    "    label=f\"Critical discharge ({q_critical} m³/s)\",\n",
+    "    color='black'\n",
+    "    )\n",
+    "\n",
+    "for date in freshet_start_date[\"first_above_critical_date\"].dropna():\n",
+    "    plt.axvline(\n",
+    "        x=date,\n",
+    "        linestyle=':',\n",
+    "        color='orange',\n",
+    "        label='Start navigable season'\n",
+    "    )\n",
+    "        \n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "39bd4c7f-1a15-464d-bddd-6c3e05088566",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Convert date to day of year\n",
+    "freshet_start_date[\"day_of_year\"] = (freshet_start_date[\"first_above_critical_date\"].dt.dayofyear)\n",
+    "\n",
+    "# Make plot \n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.scatter(freshet_start_date[\"day_of_year\"], freshet_start_date[\"year\"], marker=\"o\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Year\")\n",
+    "plt.title(\"First date discharge exceeds critical threshold between 1970-2024\")\n",
+    "plt.grid(True)\n",
+    "\n",
+    "# Convert day of year to day in months (on the axis)\n",
+    "plt.xticks(\n",
+    "    [60, 65, 70, 75, 80, 85, 90,\n",
+    "     95, 100, 105, 110, 115, 120,\n",
+    "     125, 130, 135, 140, 145, 150],\n",
+    "    [\"Mar 1\", \"Mar 6\", \"Mar 11\", \"Mar 16\", \"Mar 21\", \"Mar 26\", \"Mar 31\",\n",
+    "     \"Apr 5\", \"Apr 10\", \"Apr 15\", \"Apr 20\", \"Apr 25\", \"Apr 30\",\n",
+    "     \"May 5\", \"May 10\", \"May 15\", \"May 20\", \"May 25\", \"May 30\"],\n",
+    ")\n",
+    "\n",
+    "# Automate x-axis range to fit data\n",
+    "plt.xlim((freshet_start_date[\"day_of_year\"].min()-1), (freshet_start_date[\"day_of_year\"].max()+1))\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "1bf87b1f-7a42-4819-af63-2dc95649c8fb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Creating bar graph\n",
+    "\n",
+    "# Choose bin size\n",
+    "bin_size = 5   # use 10 for 10-day periods\n",
+    "\n",
+    "# Convert date to day of year\n",
+    "freshet_start_date[\"day_of_year\"] = freshet_start_date[\"first_above_critical_date\"].dt.dayofyear\n",
+    "\n",
+    "# Create bins\n",
+    "freshet_start_date[\"date_bin\"] = (freshet_start_date[\"day_of_year\"] // bin_size) * bin_size\n",
+    "\n",
+    "# Count how many years fall in each bin\n",
+    "freshet_counts = freshet_start_date.groupby(\"date_bin\").size()\n",
+    "\n",
+    "# Plot bar chart\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.bar(freshet_counts.index, freshet_counts.values, width=bin_size)\n",
+    "\n",
+    "# Convert x-axis from day-of-year to calendar dates\n",
+    "tick_days = freshet_counts.index\n",
+    "tick_labels = [\n",
+    "    (pd.to_datetime(\"2001-01-01\") + pd.to_timedelta(day - 1, unit=\"D\")).strftime(\"%b %d\")\n",
+    "    for day in tick_days\n",
+    "]\n",
+    "\n",
+    "plt.xticks(tick_days, tick_labels, rotation=45)\n",
+    "\n",
+    "plt.xlabel(\"Date period\")\n",
+    "plt.ylabel(\"Number of years\")\n",
+    "plt.title(\"First date discharge exceeds critical threshold\")\n",
+    "plt.grid(axis=\"y\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d32414f7-d742-48cb-9d94-50441c3f550c",
+   "metadata": {},
+   "source": [
+    "## End of range (river freeze-up)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f912ae02-7887-4bf3-af61-0ccc4c154fef",
+   "metadata": {},
+   "source": [
+    "### Idea 1: Critical when AFDD = x\n",
+    "\n",
+    "AFDD is Accumulated Freeze Degree Days. It calculates the accumulative temperature under 0. \n",
+    "Example: If 3 days have a mean temperature of -5 C per day, the AFDD would be 15. \n",
+    "\n",
+    "A study shows the LAR forms an ice sheet when AFDD reaches (approx) 50 degrees. https://www.iahr.org/library/infor?pid=26767 (Figure 6)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7aa6524c-9140-4756-bfc9-c67947740a8e",
+   "metadata": {},
+   "source": [
+    "### Load ERA5-forcings & TAS data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "9e315bb0-0085-43e0-b0a0-0d23d6bc4ba0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate ERA5 data\n",
+    "\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "#     directory=forcing_path_ERA5\n",
+    "# )\n",
+    "\n",
+    "# Load ERA5 data\n",
+    "\n",
+    "# load_location = forcing_path_ERA5 / \"work\" / \"diagnostic\" / \"script\" \n",
+    "# ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=load_location)\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "e90fb4e3-9f06-405c-bc08-fcbc28c0ef7c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Exract tas file from Era5\n",
+    "tas_file = Path(ERA5_forcing.directory) / ERA5_forcing.filenames[\"tas\"]\n",
+    "\n",
+    "# Extract tas data from tas file\n",
+    "temp_data = xr.open_dataset(tas_file)[\"tas\"]\n",
+    "\n",
+    "# Convert to panda\n",
+    "temp_data = temp_data.to_series()\n",
+    "temp_data.index = pd.to_datetime(temp_data.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Convert Kelvin to Celsius:\n",
+    "temp_data = temp_data - 273.15\n",
+    "\n",
+    "# Create dataframe with Date, Temp & year as columns\n",
+    "temp_data = pd.DataFrame({\n",
+    "    \"Date\": temp_data.index,\n",
+    "    \"Temp\": temp_data.values,\n",
+    "    \"year\": temp_data.index.year\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "54ebf5d5-9ad6-4a37-8301-f204b1059c06",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">   year AFDD_critical_date       AFDD       Temp\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41.426453</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-13.859253</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "   year AFDD_critical_date       AFDD       Temp\n",
+       "\u001b[1;36m0\u001b[0m  \u001b[1;36m2014\u001b[0m         \u001b[1;36m2014\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m10\u001b[0m  \u001b[1;36m41.426453\u001b[0m \u001b[1;36m-13.859253\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>AFDD_critical_date</th>\n",
+       "      <th>AFDD</th>\n",
+       "      <th>Temp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>2014-11-10</td>\n",
+       "      <td>41.426453</td>\n",
+       "      <td>-13.859253</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   year AFDD_critical_date       AFDD       Temp\n",
+       "0  2014         2014-11-10  41.426453 -13.859253"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "AFDD_critical = 30\n",
+    "AFDD_critical_dates = []\n",
+    "\n",
+    "# min_subzero_days = 5\n",
+    "# consec_days = 7\n",
+    "\n",
+    "start_year = start_date.year\n",
+    "end_year = end_date.year\n",
+    "\n",
+    "for year in range(start_year, end_year + 1):\n",
+    "\n",
+    "    # Set start date to 1 August\n",
+    "    year_data = temp_data[\n",
+    "        (temp_data[\"year\"] == year) &\n",
+    "        (temp_data[\"Date\"] >= pd.to_datetime(f\"{year}-10-01\"))\n",
+    "    ]\n",
+    "\n",
+    "    AFDD = 0\n",
+    "    \n",
+    "    # Isolate datasets of date & temperature data to each year \n",
+    "    for i in range(len(year_data)):\n",
+    "        temp = year_data.iloc[i][\"Temp\"]\n",
+    "        date = year_data.iloc[i][\"Date\"]\n",
+    "\n",
+    "        # Cumulative AFDD\n",
+    "        if temp < 0:\n",
+    "            AFDD += -temp\n",
+    "\n",
+    "        # Append when AFDD is critical\n",
+    "        if AFDD >= AFDD_critical:\n",
+    "            AFDD_critical_dates.append({\n",
+    "                \"year\": year,\n",
+    "                \"AFDD_critical_date\": date,\n",
+    "                \"AFDD\": AFDD,\n",
+    "                \"Temp\": temp\n",
+    "            })\n",
+    "\n",
+    "            break \n",
+    "\n",
+    "AFDD_critical_dates = pd.DataFrame(AFDD_critical_dates)\n",
+    "\n",
+    "print(AFDD_critical_dates)\n",
+    "\n",
+    "        # # Criteria 1: 5 of 7 consecutive days must be sub-zero\n",
+    "        # if i >= consec_days - 1:\n",
+    "        #     last_7_days = year_data.iloc[i - consec_days + 1 : i + 1]\n",
+    "        #     subzero_days = 0\n",
+    "\n",
+    "        #     for j in range(len(last_7_days)):\n",
+    "        #         if last_7_days.iloc[j][\"Temp\"] < 0:\n",
+    "        #             subzero_days += 1\n",
+    "\n",
+    "        #      if AFDD >= AFDD_critical and subzero_days >= required_subzero_days:\n",
+    "        #         AFDD_critical_dates.append({\n",
+    "        #             \"year\": year,\n",
+    "        #             \"AFDD_critical_date\": date,\n",
+    "        #             \"AFDD\": AFDD,\n",
+    "        #             \"Subzero days in 7 day period\": subzero_days\n",
+    "        #     })\n",
+    "        #     break\n",
+    "\n",
+    "AFDD_critical_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "861083f4-0521-4186-a73d-9c2aca2befa3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Convert date to day of year\n",
+    "AFDD_critical_dates[\"day_of_year\"] = (AFDD_critical_dates[\"AFDD_critical_date\"].dt.dayofyear)\n",
+    "\n",
+    "# Make plot \n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.scatter(AFDD_critical_dates[\"day_of_year\"], AFDD_critical_dates[\"year\"], marker=\"o\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Year\")\n",
+    "plt.title(f\"Date of river freeze-up (AFDD >= {AFDD_critical}) between 1970-2024\")\n",
+    "plt.grid(True)\n",
+    "\n",
+    "# Convert day of year to day in months (on the axis)\n",
+    "plt.xticks(\n",
+    "    [274, 279, 284, 289, 294, 299, 304,\n",
+    "     309, 314, 319, 324, 329, 334, 339,\n",
+    "     344, 349, 354, 359, 364, 366],\n",
+    "    [\"Oct 1\", \"Oct 6\", \"Oct 11\", \"Oct 16\", \"Oct 21\", \"Oct 26\", \"Oct 31\",\n",
+    "     \"Nov 5\", \"Nov 10\", \"Nov 15\", \"Nov 20\", \"Nov 25\", \"Nov 30\", \"Dec 5\",\n",
+    "     \"Dec 10\", \"Dec 15\", \"Dec 20\", \"Dec 25\", \"Dec 30\", \"Dec 31\"],\n",
+    ")\n",
+    "\n",
+    "# Prevent y-axis from showing decimal years\n",
+    "# plt.yticks(range(start_year, end_year + 1))\n",
+    "\n",
+    "# Automate x-axis range to fit data\n",
+    "plt.xlim((AFDD_critical_dates[\"day_of_year\"].min()-1), (AFDD_critical_dates[\"day_of_year\"].max()+1))\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "7995d878-10ac-4e6e-aa0f-b8e281d5aaf6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot temp for 1 year for fun:\n",
+    "selected_year = 2014\n",
+    "year_data = temp_data[temp_data[\"year\"] == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.title(f\"Temperature time series showing date of river freeze-up (AFDD >= {AFDD_critical}) for 2014\")\n",
+    "plt.scatter(year_data[\"Date\"], year_data[\"Temp\"], marker=\"o\")\n",
+    "plt.axhline(\n",
+    "    y=0,\n",
+    "    linestyle=\":\",\n",
+    "    color=\"black\",\n",
+    "    label=\"0°C\"\n",
+    ")\n",
+    "\n",
+    "# Extract & plot critical AFDD date for selected year\n",
+    "AFDD_critical_date = AFDD_critical_dates.loc[AFDD_critical_dates[\"year\"] == selected_year, \"AFDD_critical_date\"].iloc[0]\n",
+    "plt.axvline(\n",
+    "    x=AFDD_critical_date,\n",
+    "    linestyle=\":\",\n",
+    "    color=\"orange\",\n",
+    "    label=\"River freeze-up\"\n",
+    ")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Temperature (°C)\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5b3a1903-f809-45da-ad01-13313da0afea",
+   "metadata": {},
+   "source": [
+    "### Idea 2: Critical when q_critical < 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6e7f55d8-67b3-4721-912b-511875ecdbb4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a0f3c170-d57e-4d00-80c0-1bc1f090b940",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f655679f-10de-42bf-88b9-ef58385bd62c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c6b724d3-19f0-4ec3-9bb6-1828e22b320d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "078fc0ee-197a-45de-87b5-9a00eec5801f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fabbb9d8-1446-474d-b329-83c221d3f018",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Bonus trial notebooks/Calibration file deletion.ipynb b/Workyard/Bonus trial notebooks/Calibration file deletion.ipynb
new file mode 100644
index 00000000..4c358f2b
--- /dev/null
+++ b/Workyard/Bonus trial notebooks/Calibration file deletion.ipynb	
@@ -0,0 +1,135 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "180f6063-930f-49dd-86b3-9bab1c4d82af",
+   "metadata": {},
+   "source": [
+    "## Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "5037dc08-d28b-4299-b220-454411e406a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print\n",
+    "\n",
+    "from ipywidgets import IntProgress\n",
+    "from IPython.display import display\n",
+    "import shutil"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "c2bdabd1-470a-450e-bbd2-5a49b57e18f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "6acd5b8a-f2fb-45ee-8b14-aa0c7f14ad04",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[3;92mTrue\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[PosixPath('/home/maxime/BEP-maxime/Workyard/calibration_temp/test .txt'),\n",
+       " PosixPath('/home/maxime/BEP-maxime/Workyard/calibration_temp/.ipynb_checkpoints')]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "calibration_temp = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"calibration_temp\"\n",
+    "\n",
+    "print(calibration_temp.exists())\n",
+    "\n",
+    "list(calibration_temp.iterdir())[:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "03635a99-3dbb-4216-b27e-bfdc27f8ed21",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# if calibration_temp.exists() and calibration_temp.is_dir():\n",
+    "#     for item in calibration_temp.iterdir():\n",
+    "#         if item.is_dir():\n",
+    "#             shutil.rmtree(item)\n",
+    "#         else:\n",
+    "#             item.unlink()\n",
+    "# else:\n",
+    "#     print(\"Folder does not exist or is not a folder.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "14ad44ce-1fcf-4b6c-9525-9e5e49d04e34",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Bonus trial notebooks/Step2_Calibration_trial.ipynb b/Workyard/Bonus trial notebooks/Step2_Calibration_trial.ipynb
new file mode 100644
index 00000000..f19a8b8f
--- /dev/null
+++ b/Workyard/Bonus trial notebooks/Step2_Calibration_trial.ipynb	
@@ -0,0 +1,4767 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fbc7f454-3d60-492d-aa6c-0ce21a0dfc77",
+   "metadata": {},
+   "source": [
+    "## Startup\n",
+    "\n",
+    "\n",
+    "80/20 rule:\n",
+    "80% calibration (2000-2020)\n",
+    "20% validation (2020-2025)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "95a06f73-282f-4c7c-8333-f002e73e205a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print\n",
+    "\n",
+    "from ipywidgets import IntProgress\n",
+    "from IPython.display import display"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8b61a012-64eb-48b2-ba78-f641a1a581a3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a860a623-f634-4b50-822c-51e09ab4e594",
+   "metadata": {},
+   "source": [
+    "### Defining variables & pathways"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "7d407089-bbfc-40d7-983f-efbc4a7ccaf5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Naming region \n",
+    "\n",
+    "hysets_id = \"hysets_07DA001\"\n",
+    "basin_size = 132572"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "970798cd-b737-44f3-8edd-de3352b86efd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "experiment_start_date = \"2000-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2005-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "c3b02d32-4be2-47a7-8935-8284af182d66",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcing_trial\" / hysets_id / \"ERA5\"\n",
+    "forcing_path_ERA5.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "calibration_temp = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"calibration_temp\"\n",
+    "calibration_temp.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd4ec71b-d4f6-4a1c-be9a-f8d3b89059d1",
+   "metadata": {},
+   "source": [
+    "### Load & prepare discharge data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "d590f365-72ad-4473-9996-88820ea52c18",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "1cec4b74-037a-4d48-8769-e0b57a7683aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= start_date) & (q_obs[\"Date\"] <= end_date)].copy()\n",
+    "\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7c47f7f-18ff-4441-b1d4-975e46e1719b",
+   "metadata": {},
+   "source": [
+    "### Generate ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "eb582ebf-8fbc-4542-b785-cee2f332bdd5",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'ewatercycle' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Generate ERA5 data\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m ERA5_forcing \u001b[38;5;241m=\u001b[39m \u001b[43mewatercycle\u001b[49m\u001b[38;5;241m.\u001b[39mforcing\u001b[38;5;241m.\u001b[39msources[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mLumpedMakkinkForcing\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mgenerate(\n\u001b[1;32m      4\u001b[0m     dataset\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mERA5\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m      5\u001b[0m     start_time\u001b[38;5;241m=\u001b[39mexperiment_start_date,\n\u001b[1;32m      6\u001b[0m     end_time\u001b[38;5;241m=\u001b[39mexperiment_end_date,\n\u001b[1;32m      7\u001b[0m     shape\u001b[38;5;241m=\u001b[39mshape_file,\n\u001b[1;32m      8\u001b[0m )\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'ewatercycle' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "    dataset=\"ERA5\",\n",
+    "    start_time=experiment_start_date,\n",
+    "    end_time=experiment_end_date,\n",
+    "    shape=shape_file,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6fc290da-fa08-48f0-83e3-a39e8f5c36ef",
+   "metadata": {},
+   "source": [
+    "## Calibration Methods"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9b95e67e-780e-4a4d-a2f1-4cf9de2b0512",
+   "metadata": {},
+   "source": [
+    "### Method 1: RMSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "3da0e944-b4bf-49c6-a986-a94fc14e0bfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def RMSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return np.sqrt(np.mean((obs - sim)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba51d28d-1fdb-46af-8f8e-5dcf904aba7f",
+   "metadata": {},
+   "source": [
+    "### Method 2: NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "9ff8dc21-0959-49a4-9d4b-496726c90f88",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def NSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return 1 - np.sum((obs - sim) ** 2) / np.sum((obs - np.mean(obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "93f96591-ceb4-4671-9a48-04a0ddbfaf5a",
+   "metadata": {},
+   "source": [
+    "### Method 3: Log_NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "826cfb65-21ba-4901-aafe-37738913c0ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def log_NSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "645d5bb0-de70-4b97-9aa0-93094c91ebe6",
+   "metadata": {},
+   "source": [
+    "## Calibration start"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "0f58e61f-7178-44f8-8e5e-e1fa402813c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create function to run the model\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Create model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Create config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=calibration_temp\n",
+    "    )\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs \n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m, \n",
+    "        index=time, \n",
+    "        name=\"Modelled discharge\"\n",
+    "    )\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "210b14c5-80b4-4b84-9e1d-09d2c0968c23",
+   "metadata": {},
+   "source": [
+    "### Define Parameters & Storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "42429a8f-42c3-4864-b351-cb8e80404a5b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.04132074e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.86890731e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.00329377e+02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.57156950e+00</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.93221286e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8.51057360e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.11747433e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.11115492e-02</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.50756202e-01</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[1;36m7.04132074e+00\u001b[0m \u001b[1;36m3.86890731e-01\u001b[0m \u001b[1;36m2.00329377e+02\u001b[0m \u001b[1;36m1.57156950e+00\u001b[0m\n",
+       " \u001b[1;36m2.93221286e-01\u001b[0m \u001b[1;36m8.51057360e+00\u001b[0m \u001b[1;36m3.11747433e-01\u001b[0m \u001b[1;36m2.11115492e-02\u001b[0m\n",
+       " \u001b[1;36m9.50756202e-01\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Define initial storages\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])\n",
+    "\n",
+    "# # Define parameters\n",
+    "# par_names = [\"Imax\",\n",
+    "#                \"Ce\",\n",
+    "#                \"Sumax\",\n",
+    "#                \"Beta\",\n",
+    "#                \"Pmax\",\n",
+    "#                \"Tlag\",\n",
+    "#                \"Kf\",\n",
+    "#                \"Ks\",\n",
+    "#                \"FM\"\n",
+    "#                ]\n",
+    "# p_min = np.array([0,   0.1,  10,  0.1, 0.001, 0,   0.001, 0.0001, 0.01])\n",
+    "# p_max = np.array([10,  2.0, 500,  5.0, 0.3,   10,  0.1,   0.01,   0.5])\n",
+    "\n",
+    "# Define parameters\n",
+    "parameter_ranges = {\n",
+    "    \"Imax\":  (2.5, 8.5),            # Maximum interception storage\n",
+    "    \"Ce\":    (0.38, 0.5),       # Evaporation correction factor\n",
+    "    \"Sumax\": (140, 275),         # Maximum soil moisture storage\n",
+    "    \"Beta\":  (1.5, 2.3),          # Soil runoff parameter\n",
+    "    \"Pmax\":  (0.2, 1.4),            # Maximum percolation rate\n",
+    "    \"Tlag\":  (5.8, 8.7),           # Time lag\n",
+    "    \"Kf\":    (0.02, 0.35),       # Fast reservoir recession coefficient\n",
+    "    \"Ks\":    (0.001, 0.1),     # Slow reservoir recession coefficient\n",
+    "    \"FM\":    (0.35, 1),          # Snowmelt factor\n",
+    "}\n",
+    "\n",
+    "# parameter_ranges = {\n",
+    "#     \"Imax\":  (3, 8.5),\n",
+    "#     \"Ce\":    (0.35, 0.48),\n",
+    "#     \"Sumax\": (140, 280),\n",
+    "#     \"Beta\":  (1.5, 2.2),\n",
+    "#     \"Pmax\":  (0.15, 1.2),\n",
+    "#     \"Tlag\":  (6, 9),\n",
+    "#     \"Kf\":    (0.04, 0.30),\n",
+    "#     \"Ks\":    (0.025, 0.07),\n",
+    "#     \"FM\":    (0.35, 1.1),\n",
+    "# }\n",
+    "\n",
+    "# Convert to arrays\n",
+    "parameter_names = list(parameter_ranges.keys())\n",
+    "\n",
+    "p_min = np.array([parameter_ranges[name][0] for name in parameter_names])\n",
+    "p_max = np.array([parameter_ranges[name][1] for name in parameter_names])\n",
+    "\n",
+    "# Create samples\n",
+    "N = 300\n",
+    "par_samples = np.random.rand(N, len(parameter_ranges))                  # Generates values between 0-1\n",
+    "parameter_sets = p_min + par_samples * (p_max - p_min)                  # Fits value to parameter range\n",
+    "\n",
+    "print(parameter_sets[:][0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e93b5d4-0a92-4d09-b135-07101e614d9e",
+   "metadata": {},
+   "source": [
+    "## LoopdiLoop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "577e23e5-8db6-45a1-b91b-aae3a46b6c12",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d5d2bf84579442978bea3ee6ec8bd1a0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "IntProgress(value=0, max=300)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m6\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m7\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m8\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m9\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m10\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m11\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m12\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m13\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m14\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m15\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m16\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m17\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m18\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m19\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m20\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">21</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m21\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m22\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">23</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m23\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m24\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m25\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">26</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m26\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m27\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m28\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">29</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m29\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m30\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m31\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m32\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m33\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m34\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">35</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m35\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m36\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">37</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m37\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">38</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m38\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">39</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m39\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">40</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m40\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m41\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">42</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m42\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">43</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m43\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">44</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m44\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">45</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m45\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">46</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m46\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">47</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m47\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m48\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m49\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">50</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m50\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">51</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m51\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m52\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">53</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m53\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">54</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m54\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">55</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m55\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">56</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m56\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">57</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m57\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">58</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m58\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">59</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m59\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">60</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m60\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">61</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m61\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">62</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m62\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">63</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m63\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m64\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">65</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m65\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">66</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m66\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">67</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m67\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">68</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m68\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">69</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m69\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">70</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m70\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m71\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">72</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m72\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">73</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m73\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m74\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">75</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m75\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">76</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m76\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">77</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m77\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">78</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m78\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">79</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m79\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">80</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m80\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">81</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m81\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">82</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m82\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">83</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m83\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">84</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m84\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">85</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m85\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">86</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m86\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">87</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m87\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">88</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m88\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">89</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m89\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">90</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m90\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m91\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">92</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m92\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">93</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m93\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">94</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m94\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">95</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m95\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">96</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m96\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">97</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m97\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">98</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m98\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">99</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m99\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">100</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m100\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">101</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m101\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">102</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m102\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">103</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m103\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">104</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m104\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">105</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m105\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">106</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m106\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">107</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m107\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">108</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m108\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">109</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m109\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">110</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m110\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">111</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m111\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">112</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m112\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">113</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m113\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">114</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m114\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">115</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m115\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">116</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m116\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">117</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m117\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">118</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m118\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">119</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m119\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">120</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m120\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">121</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m121\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">122</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m122\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">123</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m123\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">124</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m124\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">125</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m125\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">126</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m126\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">127</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m127\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">128</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m128\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">129</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m129\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">130</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m130\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">131</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m131\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">132</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m132\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">133</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m133\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">134</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m134\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">135</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m135\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">136</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m136\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">137</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m137\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">138</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m138\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">139</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m139\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">140</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m140\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">141</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m141\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">142</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m142\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">143</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m143\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">144</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m144\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">145</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m145\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">146</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m146\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">147</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m147\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">148</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m148\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">149</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m149\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">150</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m150\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">151</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m151\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">152</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m152\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">153</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m153\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">154</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m154\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">155</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m155\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">156</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m156\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">157</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m157\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">158</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m158\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">159</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m159\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">160</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m160\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">161</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m161\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">162</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m162\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">163</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m163\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">164</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m164\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">165</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m165\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">166</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m166\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">167</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m167\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">168</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m168\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">169</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m169\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">170</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m170\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">171</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m171\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">172</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m172\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">173</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m173\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m174\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">175</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m175\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">176</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m176\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">177</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m177\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">178</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m178\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m179\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">180</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m180\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">181</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m181\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">182</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m182\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m183\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">184</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m184\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">185</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m185\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">186</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m186\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">187</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m187\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">188</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m188\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">189</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m189\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">190</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m190\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">191</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m191\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">192</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m192\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">193</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m193\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">194</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m194\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">195</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m195\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">196</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m196\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">197</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m197\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">198</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m198\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">199</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m199\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">200</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m200\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">201</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m201\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">202</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m202\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">203</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m203\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">204</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m204\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">205</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m205\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">206</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m206\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">207</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m207\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">208</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m208\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">209</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m209\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">210</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m210\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">211</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m211\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">212</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m212\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">213</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m213\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">214</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m214\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">215</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m215\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">216</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m216\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">217</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m217\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m218\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">219</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m219\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">220</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m220\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">221</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m221\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">222</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m222\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">223</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m223\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">224</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m224\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">225</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m225\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">226</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m226\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">227</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m227\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">228</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m228\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">229</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m229\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">230</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m230\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">231</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m231\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m232\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">233</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m233\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">234</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m234\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">235</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m235\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">236</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m236\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">237</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m237\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">238</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m238\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">239</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m239\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">240</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m240\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">241</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m241\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">242</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m242\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">243</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m243\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">244</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m244\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">245</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m245\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">246</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m246\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">247</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m247\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">248</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m248\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">249</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m249\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">250</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m250\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">251</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m251\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">252</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m252\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">253</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m253\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">254</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m254\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">255</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m255\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">256</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m256\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">257</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m257\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">258</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m258\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">259</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m259\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">260</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m260\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">261</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m261\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">262</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m262\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">263</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m263\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">264</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m264\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">265</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m265\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">266</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m266\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">267</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m267\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">268</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m268\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">269</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m269\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">270</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m270\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">271</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m271\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">272</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m272\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">273</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m273\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">274</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m274\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">275</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m275\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">276</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m276\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">277</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m277\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">278</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m278\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">279</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m279\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">280</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m280\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">281</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m281\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">282</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m282\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">283</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m283\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">284</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m284\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">285</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m285\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">286</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m286\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">287</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m287\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">288</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m288\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">289</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m289\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">290</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m290\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">291</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m291\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">292</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m292\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">293</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m293\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">294</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m294\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m295\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m296\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m297\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m298\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m299\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m300\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = []\n",
+    "\n",
+    "# Progress bar for visualization\n",
+    "f = IntProgress(min=0, max=N)\n",
+    "display(f)\n",
+    "\n",
+    "for i in range(N):\n",
+    "    print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "    simulated = run_hbv(\n",
+    "        parameters=parameter_sets[i], \n",
+    "        initial_storages=s_0, \n",
+    "        forcing=ERA5_forcing\n",
+    "    )\n",
+    "\n",
+    "    # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "    simulated_daily = simulated\n",
+    "    observed_daily = observed_output\n",
+    "\n",
+    "    simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "    \n",
+    "    # Align simulated and observed data\n",
+    "    combined_data = pd.DataFrame(\n",
+    "        {\"Modelled discharge\": simulated_daily, \n",
+    "        \"Observed discharge\": observed_daily}\n",
+    "    ).dropna()\n",
+    "\n",
+    "    # Skip first year as warm-up\n",
+    "    combined_data = combined_data[combined_data.index >= \"2001-01-01\"]\n",
+    "    \n",
+    "    # Append results\n",
+    "    if combined_data.empty:\n",
+    "        print(f\"No overlapping data for parameter set {i+1}\")\n",
+    "        nse = np.nan\n",
+    "        log_nse = np.nan\n",
+    "    else:\n",
+    "        nse = NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "        log_nse = log_NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "        \n",
+    "    results.append({\n",
+    "        \"run\": i,\n",
+    "        \"NSE\": nse,\n",
+    "        \"log_NSE\": log_nse,\n",
+    "        \"parameters\": parameter_sets[i]\n",
+    "    })"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d7b5f35-f872-4ef5-8ced-c92cdd81c8f8",
+   "metadata": {},
+   "source": [
+    "### Display results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "4c69f827-adda-4ec9-8863-abf0ba31e0d2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">     run       NSE   log_NSE\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.439754</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.709099</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.699835</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.776052</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.782790</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.795898</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.408743</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.376669</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.382206</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.721494</span>\n",
+       "..   <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.705821</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.809451</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.666569</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.698280</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.481626</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.689337</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.472785</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.363001</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.230548</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.231731</span>\n",
+       "\n",
+       "<span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span> rows x <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span> columns<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "     run       NSE   log_NSE\n",
+       "\u001b[1;36m0\u001b[0m      \u001b[1;36m0\u001b[0m  \u001b[1;36m0.439754\u001b[0m  \u001b[1;36m0.709099\u001b[0m\n",
+       "\u001b[1;36m1\u001b[0m      \u001b[1;36m1\u001b[0m  \u001b[1;36m0.699835\u001b[0m  \u001b[1;36m0.776052\u001b[0m\n",
+       "\u001b[1;36m2\u001b[0m      \u001b[1;36m2\u001b[0m  \u001b[1;36m0.782790\u001b[0m  \u001b[1;36m0.795898\u001b[0m\n",
+       "\u001b[1;36m3\u001b[0m      \u001b[1;36m3\u001b[0m  \u001b[1;36m0.408743\u001b[0m  \u001b[1;36m0.376669\u001b[0m\n",
+       "\u001b[1;36m4\u001b[0m      \u001b[1;36m4\u001b[0m  \u001b[1;36m0.382206\u001b[0m  \u001b[1;36m0.721494\u001b[0m\n",
+       "..   \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m\n",
+       "\u001b[1;36m295\u001b[0m  \u001b[1;36m295\u001b[0m  \u001b[1;36m0.705821\u001b[0m  \u001b[1;36m0.809451\u001b[0m\n",
+       "\u001b[1;36m296\u001b[0m  \u001b[1;36m296\u001b[0m  \u001b[1;36m0.666569\u001b[0m  \u001b[1;36m0.698280\u001b[0m\n",
+       "\u001b[1;36m297\u001b[0m  \u001b[1;36m297\u001b[0m  \u001b[1;36m0.481626\u001b[0m  \u001b[1;36m0.689337\u001b[0m\n",
+       "\u001b[1;36m298\u001b[0m  \u001b[1;36m298\u001b[0m  \u001b[1;36m0.472785\u001b[0m  \u001b[1;36m0.363001\u001b[0m\n",
+       "\u001b[1;36m299\u001b[0m  \u001b[1;36m299\u001b[0m  \u001b[1;36m0.230548\u001b[0m  \u001b[1;36m0.231731\u001b[0m\n",
+       "\n",
+       "\u001b[1m[\u001b[0m\u001b[1;36m300\u001b[0m rows x \u001b[1;36m3\u001b[0m columns\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span> with NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8095358934408565</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m179\u001b[0m with NSE: \u001b[1;36m0.8095358934408565\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.279135309789487</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.48082432749007864</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174.127749336179</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9527195686909842</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3305087197271726</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.199192091400492</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.07683628832422615</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.004363984839521473</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.40766060413663546</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.279135309789487\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.48082432749007864\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m174.127749336179\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.9527195686909842\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.3305087197271726\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.199192091400492\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.07683628832422615\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.004363984839521473\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.40766060413663546\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span> with log_NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8717169479201906</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m179\u001b[0m with log_NSE: \u001b[1;36m0.8717169479201906\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.279135309789487</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.48082432749007864</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174.127749336179</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9527195686909842</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3305087197271726</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.199192091400492</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.07683628832422615</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.004363984839521473</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.40766060413663546</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.279135309789487\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.48082432749007864\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m174.127749336179\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.9527195686909842\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.3305087197271726\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.199192091400492\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.07683628832422615\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.004363984839521473\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.40766060413663546\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = pd.DataFrame(results)\n",
+    "\n",
+    "print(results[[\"run\", \"NSE\", \"log_NSE\"]])\n",
+    "\n",
+    "# Best NSE\n",
+    "best_run_nse = results[\"NSE\"].idxmax()\n",
+    "best_result_nse = results.loc[best_run_nse]\n",
+    "\n",
+    "best_parameters_nse = best_result_nse[\"parameters\"]\n",
+    "best_nse = best_result_nse[\"NSE\"]\n",
+    "\n",
+    "print(f'Best run: {best_run_nse} with NSE: {best_nse}, with parameters:')\n",
+    "print(list(zip(parameter_names, best_parameters_nse)))\n",
+    "\n",
+    "# Best log_NSE\n",
+    "best_run_log_nse = results[\"log_NSE\"].idxmax()\n",
+    "best_result_log_nse = results.loc[best_run_log_nse]\n",
+    "\n",
+    "best_parameters_log_nse = best_result_log_nse[\"parameters\"]\n",
+    "best_log_nse = best_result_log_nse[\"log_NSE\"]\n",
+    "\n",
+    "print(f'Best run: {best_run_log_nse} with log_NSE: {best_log_nse}, with parameters:')\n",
+    "print(list(zip(parameter_names, best_parameters_log_nse)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "68ac955d-5bc7-4c75-a862-0a6ddec6b96a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.2391126094287115</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4059034482695777</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">154.67204503110761</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.754032781455765</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.39617478157458713</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8.374403905226643</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1561690712250938</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.01336758499776439</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4720208296914324</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.2391126094287115\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.4059034482695777\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m154.67204503110761\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.754032781455765\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.39617478157458713\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m8.374403905226643\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.1561690712250938\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.01336758499776439\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.4720208296914324\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Manual check for other runs\n",
+    "\n",
+    "selected_run = results.loc[295]\n",
+    "print(list(zip(parameter_names, selected_run[\"parameters\"])))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "dc27944c-bad7-49ac-acb0-d050c6471452",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">RMSE for best NSE parameter set: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52.624</span> m³/s\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "RMSE for best NSE parameter set: \u001b[1;36m52.624\u001b[0m m³/s\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">RMSE for best log_NSE parameter set: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">62.495</span> m³/s\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "RMSE for best log_NSE parameter set: \u001b[1;36m62.495\u001b[0m m³/s\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Calculate RMSE for best parameter sets NSE and log_NSE\n",
+    "\n",
+    "rmse_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "rmse_log_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "print(f\"RMSE for best NSE parameter set: {rmse_nse:.3f} m³/s\")\n",
+    "print(f\"RMSE for best log_NSE parameter set: {rmse_log_nse:.3f} m³/s\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "aeb2ea7e-9826-450f-880e-e1e5e72c9dba",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "simulated_calibrated_nse = run_hbv(\n",
+    "    parameters=best_parameters_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "simulated_calibrated_log_nse = run_hbv(\n",
+    "    parameters=best_parameters_log_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "# Align dates\n",
+    "simulated_plot_nse = simulated_calibrated_nse\n",
+    "simulated_plot_log_nse = simulated_calibrated_log_nse\n",
+    "observed_plot = observed_output\n",
+    "\n",
+    "simulated_plot_nse.index = pd.to_datetime(simulated_plot_nse.index).tz_localize(None).normalize()\n",
+    "simulated_plot_log_nse.index = pd.to_datetime(simulated_plot_log_nse.index).tz_localize(None).normalize()\n",
+    "observed_plot.index = pd.to_datetime(observed_plot.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Combine modelled and observed data\n",
+    "plot_data = pd.DataFrame({\n",
+    "    \"Modelled discharge NSE\": simulated_plot_nse,\n",
+    "    \"Modelled discharge log_NSE\": simulated_plot_log_nse,\n",
+    "    \"Observed discharge\": observed_plot\n",
+    "}).dropna()\n",
+    "\n",
+    "# Calculate NSE for plotted data\n",
+    "plot_nse = NSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "plot_log_nse = log_NSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\")\n",
+    "plt.plot(plot_data.index, plot_data[\"Modelled discharge NSE\"], label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data.index, plot_data[\"Modelled discharge log_NSE\"], label=\"Modelled discharge log_NSE\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001, NSE = {best_nse:.3f}, log NSE = {best_log_nse:.3f}\")\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f'Critical discharge ({q_critical} m³/s', color='black')\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dde634ea-53bd-4c41-ba13-8ec762014b89",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Bonus trial notebooks/Step2_Trial_model_LAR.ipynb b/Workyard/Bonus trial notebooks/Step2_Trial_model_LAR.ipynb
new file mode 100644
index 00000000..9071a3ff
--- /dev/null
+++ b/Workyard/Bonus trial notebooks/Step2_Trial_model_LAR.ipynb	
@@ -0,0 +1,867 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bdb4216e-a341-4c2b-a410-35170773a9a7",
+   "metadata": {},
+   "source": [
+    "## Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "id": "d197b8f0-0f85-4a41-b2fb-1b2a8cf3f9f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "id": "dd7b7d3f-1489-4723-bb51-f3cffcb7a85c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "1c8aee93-b2d6-4291-89ae-1d29e69268cd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining basin size\n",
+    "\n",
+    "basin_size = 132572"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "id": "d7dce039-d1f3-44a0-b646-98c32ecffb28",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "experiment_start_date = \"1999-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2019-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "d330bf37-7419-4287-81af-3d09e4c7a30e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "id": "12cc30f9-29ad-4b43-b3dd-9cd5612ff4e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Create pathways for ERA 5 forcings\n",
+    "\n",
+    "# forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5-2019-2024\"\n",
+    "\n",
+    "# discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"hbv_config\"\n",
+    "# hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "id": "46ea8b1e-fb73-49ed-855c-4d95cd932748",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "id": "8bb224ad-d23c-475f-b6af-4a6023a17044",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>14888</th>\n",
+       "      <td>1999-01-01</td>\n",
+       "      <td>104.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14889</th>\n",
+       "      <td>1999-01-02</td>\n",
+       "      <td>103.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14890</th>\n",
+       "      <td>1999-01-03</td>\n",
+       "      <td>101.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14891</th>\n",
+       "      <td>1999-01-04</td>\n",
+       "      <td>103.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14892</th>\n",
+       "      <td>1999-01-05</td>\n",
+       "      <td>105.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Date  discharge_m3s\n",
+       "14888 1999-01-01          104.0\n",
+       "14889 1999-01-02          103.0\n",
+       "14890 1999-01-03          101.0\n",
+       "14891 1999-01-04          103.0\n",
+       "14892 1999-01-05          105.0"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "q_obs = q_obs[\n",
+    "    (q_obs[\"Date\"] >= start_date) &\n",
+    "    (q_obs[\"Date\"] <= end_date)\n",
+    "].copy()\n",
+    "\n",
+    "q_obs.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "id": "7f6f57aa-9f39-4524-ba3a-34f55035ebab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"])\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "id": "77e79b20-3e4d-405a-bd88-16bdc50bdb39",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1999-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1999-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2019-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "ca2be146-1112-4806-a44f-d57ebd4442c9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.991929</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.44128</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183.49046</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.62907</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.572658</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.215476</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0654684</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00259304</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.14274</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.991929\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.44128\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m183.49046\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.62907\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.572658\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.215476\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.0654684\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.00259304\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.14274\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "# par_0 = [4.45787, 0.42307, 201.57602, 2.36497, 0.26755, 8.62964, 0.083568, 0.0037073, 0.29645]\n",
+    "# par_0 = [2.79874, 0.49211, 255.96478, 1.782968, 0.503199, 6.095956, 0.33279, 0.10539, 0.63857]\n",
+    "# par_0 = [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606]         # 0.725 val, 0.x cal - Fav run 2\n",
+    "# par_0 = [6.28908, 0.423917, 173.56627, 1.63144, 0.402586, 6.56151, 0.0456809, 0.00313744, 0.516696]                 # 0.702 val, 0.x cal\n",
+    "# par_0 = [6.4919, 0.386877, 221.78625, 1.388269, 0.276453, 4.9870704, 0.04126777, 0.05640195, 1.148877]              # 0.668 val, 0.x cal\n",
+    "# par_0 = [7.502398, 0.38028, 194.1899, 1.680197, 0.47956, 4.8566806, 0.041745354, 0.02833896, 1.051862]              # 0.677 val, 0.x cal\n",
+    "# par_0 = [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392]                        # 0.781 val, 0.776 cal\n",
+    "# par_0 = [6.16512, 0.4369419, 151.2515900, 1.727835, 0.3771705, 6.19265974, 0.06959136, 0.001310818, 0.8130732]      # 0.664 val, 0.791 cal\n",
+    "# par_0 = [5.7107, 0.441634, 172.81305, 1.87367, 0.588802, 5.498147, 0.060305, 0.019666, 1.2011814]                    # x val, 0.73 cal         Start of 5+ months exclusion\n",
+    "# par_0 = [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504]                    # 0.82 val, 0.818 cal - Fav run 1      \n",
+    "# par_0 = [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]                    #  val,  0.77 cal    \n",
+    "# par_0 = [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857]                           # 0.78 val, 0.71 cal - potential inclusion\n",
+    "par_0 = [6.991929, 0.44128, 183.49046, 1.62907, 0.572658, 5.215476, 0.0654684, 0.00259304, 1.14274]                   # 0,69 c, 0.73 v - 6 months excluded N = 600 #1\n",
+    "# par_0 = [5.882658, 0.472413, 194.30386, 1.78162, 0.460818, 5.215365, 0.0641993, 0.159898, 1.091972]                   # 0,637 c, 0,65 v - 6 months excluded N = 600 #2\n",
+    "# par_0 = [6.991929, 0.44128, 183.49046, 1.62907, 0.572658, 5.215476, 0.0654684, 0.00259304, 1.14274]                   # c, v - 6 months excluded N = 600 #3\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"          # Snowmelt factor\n",
+    "               ]\n",
+    "\n",
+    "# Initial: par_0 = [5.085, 0.55, 100.373, 1.612, 0.545, 3.801, 0.196, 0.00, 0.185]\n",
+    "\n",
+    "print(list(zip(par_names, par_0)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "d5e5bcb4-bf90-470b-90ed-4a0b9d80c35d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5bbaae8e-18fa-4383-9973-5a2560840699",
+   "metadata": {},
+   "source": [
+    "## Setup model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "055bdbc8-af1f-41ac-ad1d-b4da4d6785f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create model object\n",
+    "\n",
+    "model = ewatercycle.models.HBV(forcing=ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "id": "44092959-524a-4330-a274-77cfad0eacd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create config file\n",
+    "\n",
+    "config_file, _ = model.setup(parameters=par_0, initial_storages=s_0, cfg_dir=hbv_config)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "079368de-30cf-491f-8cc9-2021f6a4bfa6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Initialising model\n",
+    "\n",
+    "model.initialize(config_file)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "327222c7-bd08-4992-826e-07f40f61b783",
+   "metadata": {},
+   "source": [
+    "## Running the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "id": "93b4084b-21e5-4009-9fc7-122b7b739a86",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define outputs\n",
+    "\n",
+    "Q_m = []\n",
+    "time = []\n",
+    "\n",
+    "while model.time < model.end_time:\n",
+    "    model.update()\n",
+    "    Q_m.append(model.get_value(\"Q\")[0])\n",
+    "    time.append(pd.Timestamp(model.time_as_datetime))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "id": "f1bb58f8-3dee-43eb-abc8-4af333b5d064",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.finalize()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "39872047-cba7-47c4-b2f8-6ed47c56fdc6",
+   "metadata": {},
+   "source": [
+    "## Process results "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "id": "715c5274-8ab4-45d0-b154-bb0cf30b52bd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Make Series for model output and q_obs\n",
+    "model_output_mmday = pd.Series(data=Q_m, name=\"Modelled discharge\", index=time)\n",
+    "model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "# Date_obs = q_obs[\"Date\"]\n",
+    "# discharge_m3s_obs = q_obs[\"discharge_m3s\"]\n",
+    "\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])\n",
+    "\n",
+    "# q_obs.set_index(\"Date\")[\"discharge_m3s\"]\n",
+    "# observed_output.name = \"Observed discharge\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "id": "9ee05f10-c416-4238-be5f-0dd3901ba3ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for year range\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "observed_output.plot(label=\"Observed discharge\")\n",
+    "model_output_m3s.plot(label=\"Modelled discharge\")\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f'Critical discharge ({q_critical} m³/s)', color='black')\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Modelled vs observed discharge at 07DA001\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.xlim(\"2020-01-01\", \"2024-12-31\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "id": "494883ac-e9f0-4806-93d9-bb6a52372309",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for 1 year\n",
+    "\n",
+    "selected_year = 2024\n",
+    "\n",
+    "observed_plot = observed_output\n",
+    "modelled_plot = model_output_m3s\n",
+    "\n",
+    "observed_plot.index = pd.to_datetime(observed_plot.index).tz_localize(None).normalize()\n",
+    "modelled_plot.index = pd.to_datetime(modelled_plot.index).tz_localize(None).normalize()\n",
+    "\n",
+    "plot_data = pd.DataFrame({\n",
+    "    \"Modelled discharge\": modelled_plot,\n",
+    "    \"Observed discharge\": observed_plot\n",
+    "}).dropna()\n",
+    "\n",
+    "plot_data_year = plot_data[plot_data.index.year == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Observed discharge\"],label=\"Observed discharge\")\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge\"],label=\"Modelled discharge\")\n",
+    "\n",
+    "plt.axhline(y=q_critical,linestyle=\":\",color=\"black\",label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001 in {selected_year}\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e2e1edf-f9a2-4d42-8de0-13e5dfc29fd5",
+   "metadata": {},
+   "source": [
+    "### "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b4a1bc95-7122-4372-8b79-991d1344452c",
+   "metadata": {},
+   "source": [
+    "### Log NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "id": "0c3e7e10-16ba-46cf-96a6-9bb2d01f8287",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate log NSE\n",
+    "\n",
+    "def log_NSE(sim, obs):\n",
+    "    \n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "id": "6bcc0656-5f3a-450a-b758-e4c93e9feb07",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call log NSE for relevant timeperiod\n",
+    "\n",
+    "def lognse_for_period(sim, obs, lognse_start, lognse_end):\n",
+    "\n",
+    "    simulated_daily = sim\n",
+    "    observed_daily = obs\n",
+    "\n",
+    "    simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    combined_data = pd.DataFrame({\n",
+    "        \"Modelled discharge\": simulated_daily,\n",
+    "        \"Observed discharge\": observed_daily\n",
+    "    }).dropna()\n",
+    "\n",
+    "    lognse_start = pd.to_datetime(lognse_start).tz_localize(None).normalize()\n",
+    "    lognse_end = pd.to_datetime(lognse_end).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Set time period - Skip 1st year\n",
+    "    combined_data = combined_data[\n",
+    "        (combined_data.index >= lognse_start) &\n",
+    "        (combined_data.index <= lognse_end)\n",
+    "    ]\n",
+    "\n",
+    "    # Exclude winter months\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])\n",
+    "    ]\n",
+    "\n",
+    "    if combined_data.empty:\n",
+    "        print(\"No data left after filtering.\")\n",
+    "        return np.nan\n",
+    "\n",
+    "    log_nse = log_NSE(\n",
+    "        combined_data[\"Modelled discharge\"],\n",
+    "        combined_data[\"Observed discharge\"]\n",
+    "    )\n",
+    "\n",
+    "    return log_nse"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "id": "aa07b0d5-9144-48bf-9ca6-a43812e30020",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">log NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.6899179967067883</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "log NSE: \u001b[1;36m0.6899179967067883\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Return log NSE\n",
+    "evaluation_start = pd.to_datetime(f\"{start_date.year + 1}-01-01\")\n",
+    "\n",
+    "lognse_value = lognse_for_period(\n",
+    "    model_output_m3s,\n",
+    "    observed_output,\n",
+    "    evaluation_start,\n",
+    "    end_date\n",
+    ")\n",
+    "\n",
+    "print(\"log NSE:\", lognse_value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56592f44-6174-48c3-a724-2ed1036228ff",
+   "metadata": {},
+   "source": [
+    "### Days calc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "id": "2d2cda32-61ff-4710-998b-4c4a5205cefc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def days_counter(sim, obs, start_date, end_date):\n",
+    "\n",
+    "    # Combine dataset in Dataframe\n",
+    "    combined_data = pd.DataFrame({\n",
+    "        \"Modelled discharge\": sim,\n",
+    "        \"Observed discharge\": obs\n",
+    "    }).dropna()\n",
+    "\n",
+    "    # Make list of years\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    # Loop through each year\n",
+    "    for i in range(len(years)):\n",
+    "\n",
+    "        year = years[i]\n",
+    "\n",
+    "        # Define start month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "\n",
+    "        year_data = combined_data[\n",
+    "            (combined_data.index >= year_start) &\n",
+    "            (combined_data.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = 0\n",
+    "\n",
+    "        # Loop through each  year to identify lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "            modelled_q = year_data.iloc[j][\"Modelled discharge\"]\n",
+    "\n",
+    "            # Check if that day is low flow and accumulate\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "            if modelled_q < q_critical:\n",
+    "                modelled_lowflow_days += 1\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    # average_error = round(lowflow_days[\"%error\"].abs().mean(), 1)\n",
+    "\n",
+    "    return lowflow_days\n",
+    "    \n",
+    "    # , print(f\"average error = {average_error}%\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "id": "c04c46cc-b80a-40ec-b741-e78fa5168dcd",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: []\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Define period (based on algorithm date > q_critical & freeze-up date output) & prepare\n",
+    "day_calc_start = pd.to_datetime(f\"{start_date.year + 1}-01-01\")\n",
+    "q_critical = 500\n",
+    "\n",
+    "lowflow_days = days_counter(\n",
+    "    sim=model_output_m3s,\n",
+    "    obs=observed_output,\n",
+    "    start_date=day_calc_start,\n",
+    "    end_date=end_date\n",
+    ")\n",
+    "\n",
+    "lowflow_days\n",
+    "\n",
+    "# NOTE TO CHANGE TIME RANGE -> EDIT DEF days_counter FUNCTION UNDER # Define start month day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3d9701be-4df6-41b8-904e-cb4cda096e80",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/CMIP6_Forcings_Generation.ipynb b/Workyard/CMIP6_Forcings_Generation.ipynb
new file mode 100644
index 00000000..2fe6549a
--- /dev/null
+++ b/Workyard/CMIP6_Forcings_Generation.ipynb
@@ -0,0 +1,758 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e91181a8-c60f-456f-80cc-3923bf7c6a43",
+   "metadata": {},
+   "source": [
+    "# CMIP6 Data generation & merging \n",
+    "\n",
+    "CMIP6 data will be generated from 1995-2014, loaded and merged into one file\n",
+    "\n",
+    "**Note: Depending on if you want to run historical, or an ssp, changes you need to make are:**\n",
+    "1. Cell 5: Select scenario\n",
+    "2. Cell 6: Define period"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "680410be-715a-4678-a4e3-c1141939241e",
+   "metadata": {},
+   "source": [
+    "## Start-up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "7ef3318e-968e-418e-bf4c-a8936aade9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# general python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "#niceties\n",
+    "from rich import print\n",
+    "\n",
+    "import yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "f7ff029b-ee4b-4fe2-b5d5-bf768b626989",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "df3c38b4-7757-475c-a670-e7a06cc53955",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choose what you want to run:\n",
+    "\n",
+    "Scenario = \"historical\"    # Options: historical, ssp119, ssp126, ssp245, ssp,370, ssp585"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74c8c15e-8cab-4e1a-b6eb-c9c165d8c051",
+   "metadata": {},
+   "source": [
+    "### Define range & forcing paths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b2343410-2713-4089-ae42-dad37b457c41",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6-1995-1999</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/\u001b[0m\u001b[95mCMIP6-1995-1999\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2000</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2000\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2014\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining period range\n",
+    "\n",
+    "# For CMIP trial:\n",
+    "periods = [\n",
+    "    [1995, 2000, 2005, 2010],\n",
+    "    [1999, 2004, 2009, 2014]\n",
+    "]\n",
+    "\n",
+    "folder_names = []\n",
+    "forcing_paths = {}\n",
+    "\n",
+    "# Generate file names & paths\n",
+    "for i in range(len(periods[0])):\n",
+    "    start_year = periods[0][i]\n",
+    "    end_year = periods[1][i]\n",
+    "    \n",
+    "    folder_name = f'CMIP6-{start_year}-{end_year}'                        \n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / folder_name\n",
+    "\n",
+    "    folder_names.append(folder_name)\n",
+    "    forcing_paths[folder_name] = forcing_path\n",
+    "\n",
+    "    forcing_path.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "# Call path test\n",
+    "print(forcing_paths[folder_names[0]])\n",
+    "\n",
+    "print(periods[0][1])\n",
+    "\n",
+    "print(periods[1][-1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "619dd21a-0646-4bae-a71b-935f1fca8c04",
+   "metadata": {},
+   "source": [
+    "### Generate CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "cbc7b2b6-88ee-4e7f-b37c-39eaf878c075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1995</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1999</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping CMIP6-\u001b[1;36m1995\u001b[0m-\u001b[1;36m1999\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2000</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2004</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping CMIP6-\u001b[1;36m2000\u001b[0m-\u001b[1;36m2004\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2005</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2009</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping CMIP6-\u001b[1;36m2005\u001b[0m-\u001b[1;36m2009\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2010</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping CMIP6-\u001b[1;36m2010\u001b[0m-\u001b[1;36m2014\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Shapefile path\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\"\n",
+    "\n",
+    "# Choose CMIP6 dataset\n",
+    "CMIP_dataset = {'dataset': 'MPI-ESM1-2-HR', 'project': 'CMIP6', 'grid' : 'gn', 'exp': Scenario, 'ensemble': 'r1i1p1f1'}\n",
+    "\n",
+    "\n",
+    "# Generate forcing data\n",
+    "# for i in range(1):\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Change start year to start time so ERA5 can interpret it\n",
+    "    start_time_CMIP = f'{periods[0][i]}-01-01T00:00:00Z'\n",
+    "    end_time_CMIP = f'{periods[1][i]}-12-31T00:00:00Z'\n",
+    "\n",
+    "    # Skip if folder is not empty to prevent errors\n",
+    "    if any(forcing_paths[folder_names[i]].iterdir()):\n",
+    "        print(f\"Skipping {folder_names[i]} because the folder is not empty.\")\n",
+    "        continue\n",
+    "\n",
+    "    # Load forcings\n",
+    "    CMIP_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "        dataset=CMIP_dataset,\n",
+    "        start_time=start_time_CMIP,\n",
+    "        end_time=end_time_CMIP,\n",
+    "        shape=shape_file,\n",
+    "        directory=forcing_paths[folder_names[i]]\n",
+    "    )\n",
+    "\n",
+    "    # I need info because my patience is limited\n",
+    "    print(f\"Finished {folder_names[i]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91242ae4-3d21-4d18-815f-5cc986d5961e",
+   "metadata": {},
+   "source": [
+    "### Load CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "f8e8ac64-fee5-4602-a1f1-90b8fb14c2b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-1995-1999'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2000-2004'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2005-2009'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2010-2014'</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[32m'CMIP6-1995-1999'\u001b[0m, \u001b[32m'CMIP6-2000-2004'\u001b[0m, \u001b[32m'CMIP6-2005-2009'\u001b[0m, \u001b[32m'CMIP6-2010-2014'\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "LumpedMakkinkForcing(start_time='1995-01-01T00:00:00Z', end_time='1999-12-31T00:00:00Z', directory=PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script'), shape=PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script/07DA001_basin.shp'), filenames={'pr': 'CMIP6_MPI-ESM1-2-HR_day_historical_r1i1p1f1_pr_gn_1995-1999.nc', 'tas': 'CMIP6_MPI-ESM1-2-HR_day_historical_r1i1p1f1_tas_gn_1995-1999.nc', 'rsds': 'CMIP6_MPI-ESM1-2-HR_day_historical_r1i1p1f1_rsds_gn_1995-1999.nc', 'evspsblpot': 'Derived_Makkink_evspsblpot.nc'})"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "CMIP_forcings = {}\n",
+    "\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Create new path to find relevant files in the folder\n",
+    "    directory_new = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\"\n",
+    "    \n",
+    "    # Load forcings\n",
+    "    CMIP_forcings[folder_names[i]] = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=directory_new)\n",
+    "\n",
+    "# Test to see if it works\n",
+    "print(folder_names)\n",
+    "CMIP_forcings[folder_names[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8eddb25-06e3-4702-87e8-258aeda27a15",
+   "metadata": {},
+   "source": [
+    "### Merge CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "1cb12aa2-4b4c-4108-a5c9-2d8156cdecfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to seperate files based on file names and combine same file names from different folders\n",
+    "def combine_variable(var_name):\n",
+    "    datasets = []\n",
+    "\n",
+    "    for i in range(len(folder_names)):\n",
+    "\n",
+    "        if var_name == \"evspsblpot\":\n",
+    "            file_name = \"Derived_Makkink_evspsblpot.nc\"\n",
+    "        else:\n",
+    "            file_name = f\"CMIP6_MPI-ESM1-2-HR_day_{Scenario}_r1i1p1f1_{var_name}_gn_{periods[0][i]}-{periods[1][i]}.nc\"\n",
+    "\n",
+    "        directory = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\" / file_name\n",
+    "\n",
+    "        print(f\"Loading {directory}\")\n",
+    "\n",
+    "        datasets.append(xr.open_dataset(directory))\n",
+    "\n",
+    "    combined = xr.concat(datasets, dim=\"time\")\n",
+    "    return combined"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "b21fe2e4-478a-4e0b-9f1f-a40316e22018",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_pr_gn_1995-1999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_pr_gn_1995-1999.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2000-2004/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_pr_gn_2000-2004.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2000-2004/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_pr_gn_2000-2004.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2005-2009/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_pr_gn_2005-2009.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2005-2009/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_pr_gn_2005-2009.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2010-2014/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_pr_gn_2010-2014.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2010-2014/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_pr_gn_2010-2014.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_tas_gn_1995-1999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_tas_gn_1995-1999.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2000-2004/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_tas_gn_2000-2004.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2000-2004/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_tas_gn_2000-2004.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2005-2009/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_tas_gn_2005-2009.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2005-2009/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_tas_gn_2005-2009.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2010-2014/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_tas_gn_2010-2014.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2010-2014/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_tas_gn_2010-2014.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_rsds_gn_1995-1999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_rsds_gn_1995-1999.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2000-2004/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_rsds_gn_2000-2004.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2000-2004/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_rsds_gn_2000-2004.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2005-2009/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_rsds_gn_2005-2009.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2005-2009/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_rsds_gn_2005-2009.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2010-2014/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">HR_day_historical_r1i1p1f1_rsds_gn_2010-2014.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2010-2014/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-\u001b[0m\n",
+       "\u001b[95mHR_day_historical_r1i1p1f1_rsds_gn_2010-2014.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_e</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">vspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-1999/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_e\u001b[0m\n",
+       "\u001b[95mvspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2000-2004/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_e</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">vspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2000-2004/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_e\u001b[0m\n",
+       "\u001b[95mvspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2005-2009/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_e</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">vspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2005-2009/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_e\u001b[0m\n",
+       "\u001b[95mvspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2010-2014/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_e</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">vspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-2010-2014/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_e\u001b[0m\n",
+       "\u001b[95mvspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Running function for various file name types\n",
+    "combined_variables = {}\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "combined_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f'CMIP6-{periods[0][0]}-{periods[1][-1]}'\n",
+    "# combined_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / f'ERA5-{periods[0][0]}-{periods[1][-1]}'\n",
+    "combined_path.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "    combined_variables[var_names[i]] = combine_variable(var_names[i])\n",
+    "    combined_variables[var_names[i]].to_netcdf(combined_path / f'combined_ERA5_{periods[0][0]}_{periods[1][-1]}_{var_names[i]}.nc')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a439e818-0aa8-4e92-a189-fde70016a911",
+   "metadata": {},
+   "source": [
+    "### Create YAML file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "e60b3316-e100-4af9-a36d-fad721ef6e02",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create yaml\n",
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{periods[0][0]}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{periods[1][-1]}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_CMIP6_{periods[0][0]}_{periods[1][-1]}_pr.nc\",\n",
+    "        \"tas\": f\"combined_CMIP6_{periods[0][0]}_{periods[1][-1]}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_CMIP6_{periods[0][0]}_{periods[1][-1]}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_CMIP6_{periods[0][0]}_{periods[1][-1]}_evspsblpot.nc\"\n",
+    "    }}\n",
+    "\n",
+    "# Save the YAML file\n",
+    "yaml_file_path = combined_path / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "10ff50bf-b6e7-4033-9682-3e25d01ecd26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1995-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-2014'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1995_2014_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1995_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1995_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1995_2014_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1995-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-2014'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_1995_2014_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_1995_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_1995_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_1995_2014_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "CMIP6_combined_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=combined_path)\n",
+    "print(CMIP6_combined_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "83a89024-510b-442f-adeb-8f9e0d07a77f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/CMIP_Projections.ipynb b/Workyard/CMIP_Projections.ipynb
new file mode 100644
index 00000000..726701b4
--- /dev/null
+++ b/Workyard/CMIP_Projections.ipynb
@@ -0,0 +1,2106 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9ca8fd44-6292-4af4-9100-d3256fccd960",
+   "metadata": {},
+   "source": [
+    "# Ensemble validation\n",
+    "\n",
+    "The 5 parameter sets calculkated in Calibration_HBV.ipynb will be used for a validation period, in which the log NSE will be calculated, a mean will be calculated and total low flow days during the navigation season.\n",
+    "\n",
+    "The structure of this notebook is as follows:\n",
+    "\n",
+    "### 1. Startup\n",
+    "### 2. Model Setup\n",
+    "### 3. Running model\n",
+    "### 4. LNSE calculation\n",
+    "### 5. Display results\n",
+    "### 6. Lowflow calculation\n",
+    "### 7. Cumsum distribution"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdb4216e-a341-4c2b-a410-35170773a9a7",
+   "metadata": {},
+   "source": [
+    "## 1. Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "d197b8f0-0f85-4a41-b2fb-1b2a8cf3f9f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "dd7b7d3f-1489-4723-bb51-f3cffcb7a85c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "1c8aee93-b2d6-4291-89ae-1d29e69268cd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "d7dce039-d1f3-44a0-b646-98c32ecffb28",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "# experiment_start_date = \"2019-01-01T00:00:00Z\"\n",
+    "# experiment_end_date = \"2024-12-31T00:00:00Z\"\n",
+    "\n",
+    "start_year = 1995\n",
+    "end_year = 2014\n",
+    "\n",
+    "validation_start = f\"{start_year}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{end_year}-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "d330bf37-7419-4287-81af-3d09e4c7a30e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / f\"ERA5-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_CMIP = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"historical\" / f\"CMIP6-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_QDM = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"historical\" / f\"CMIP6-QDM-{start_year}-{end_year}\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "id": "15ea4507-f559-4ef8-9756-60b8502064d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Create pathways for ERA 5 forcings\n",
+    "\n",
+    "# forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"forcings\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "# discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "# hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "46ea8b1e-fb73-49ed-855c-4d95cd932748",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "8bb224ad-d23c-475f-b6af-4a6023a17044",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs to relevant dates\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= validation_start_date) & (q_obs[\"Date\"] <= validation_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "fc27f6f8-e7ff-4be6-b073-05006d25426a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date\n",
+       "1995-01-01    197.0\n",
+       "1995-01-02    196.0\n",
+       "1995-01-03    194.0\n",
+       "1995-01-04    191.0\n",
+       "1995-01-05    186.0\n",
+       "Name: Observed discharge, dtype: float64"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "observed_output.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "7f6f57aa-9f39-4524-ba3a-34f55035ebab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"])\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a48b5085-6478-4cf2-bd02-75b75f82e90f",
+   "metadata": {},
+   "source": [
+    "### Generate/Load CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "id": "77e79b20-3e4d-405a-bd88-16bdc50bdb39",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1995-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-2014'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1995_2014_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1995_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1995_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1995_2014_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1995-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-2014'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1995_2014_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1995_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1995_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1995_2014_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate data\n",
+    "# CMIP_dataset = {'dataset': 'MPI-ESM1-2-HR', 'project': 'CMIP6', 'grid' : 'gn', 'exp': 'historical', 'ensemble': 'r1i1p1f1'}\n",
+    "\n",
+    "# CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].generate(\n",
+    "#     dataset=CMIP_dataset,\n",
+    "#    start_time=validation_start,\n",
+    "#    end_time=validation_end,\n",
+    "#    shape=shape_file,\n",
+    "# )\n",
+    "# CMIP_forcing_QDM = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].generate(\n",
+    "#     dataset=CMIP_dataset,\n",
+    "#    start_time=validation_start,\n",
+    "#    end_time=validation_end,\n",
+    "#    shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_CMIP)\n",
+    "\n",
+    "# QDM_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_QDM)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "09f9dfb3-40c9-4689-98b8-fd1ea8fd72d1",
+   "metadata": {},
+   "source": [
+    "### Load parameter sets & initial storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "id": "ca2be146-1112-4806-a44f-d57ebd4442c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "# par_0 = [4.45787, 0.42307, 201.57602, 2.36497, 0.26755, 8.62964, 0.083568, 0.0037073, 0.29645]\n",
+    "# par_0 = [2.79874, 0.49211, 255.96478, 1.782968, 0.503199, 6.095956, 0.33279, 0.10539, 0.63857]\n",
+    "# par_0 = [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606]         # 0.725 val, 0.x cal - Fav run 2\n",
+    "# par_0 = [6.28908, 0.423917, 173.56627, 1.63144, 0.402586, 6.56151, 0.0456809, 0.00313744, 0.516696]                 # 0.702 val, 0.x cal\n",
+    "# par_0 = [6.4919, 0.386877, 221.78625, 1.388269, 0.276453, 4.9870704, 0.04126777, 0.05640195, 1.148877]              # 0.668 val, 0.x cal\n",
+    "# par_0 = [7.502398, 0.38028, 194.1899, 1.680197, 0.47956, 4.8566806, 0.041745354, 0.02833896, 1.051862]              # 0.677 val, 0.x cal\n",
+    "# par_0 = [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392]                        # 0.781 val, 0.776 cal\n",
+    "# par_0 = [6.16512, 0.4369419, 151.2515900, 1.727835, 0.3771705, 6.19265974, 0.06959136, 0.001310818, 0.8130732]      # 0.664 val, 0.791 cal\n",
+    "# par_0 = [5.7107, 0.441634, 172.81305, 1.87367, 0.588802, 5.498147, 0.060305, 0.019666, 1.2011814]                    # x val, 0.73 cal         Start of 5+ months exclusion\n",
+    "# par_0 = [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504]                    # 0.82 val, 0.818 cal - Fav run 1      \n",
+    "# par_0 = [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]                    #  val,  0.77 cal    \n",
+    "# par_0 = [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857]                           # 0.78 val, 0.71 cal - potential inclusion\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]\n",
+    "]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"          # Snowmelt factor\n",
+    "               ]\n",
+    "\n",
+    "# Initial: par_0 = [5.085, 0.55, 100.373, 1.612, 0.545, 3.801, 0.196, 0.00, 0.185]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "id": "d5e5bcb4-bf90-470b-90ed-4a0b9d80c35d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "06c977b4-ba9d-4e82-8415-42180eac9f01",
+   "metadata": {},
+   "source": [
+    "## 2. Model setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "id": "055bdbc8-af1f-41ac-ad1d-b4da4d6785f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config\n",
+    "    )\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\"\n",
+    "    )\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "id": "0eef7e02-1e23-4d1a-99a3-56c2d3b5f62f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1995-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-2014'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1995_2014_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1995_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1995_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1995_2014_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1995-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1995-2014'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_1995_2014_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_1995_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_1995_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_1995_2014_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(CMIP_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "650daf1f-e90f-4b5b-aac5-eca8965de7cf",
+   "metadata": {},
+   "source": [
+    "## 3. Running model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "44092959-524a-4330-a274-77cfad0eacd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing\n",
+    "        )\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Filter observed data by day\n",
+    "    observed_daily = observed_output\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "    ensemble_data['Observed discharge'] = observed_daily\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "id": "079368de-30cf-491f-8cc9-2021f6a4bfa6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set 1</th>\n",
+       "      <th>Set 2</th>\n",
+       "      <th>Set 3</th>\n",
+       "      <th>Set 4</th>\n",
+       "      <th>Set 5</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Observed discharge</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1995-01-02</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>196.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1995-01-03</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>194.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1995-01-04</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>191.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1995-01-05</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>186.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1995-01-06</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>180.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Set 1  Set 2  Set 3  Set 4  Set 5  Mean  Observed discharge\n",
+       "1995-01-02    0.0    0.0    0.0    0.0    0.0   0.0               196.0\n",
+       "1995-01-03    0.0    0.0    0.0    0.0    0.0   0.0               194.0\n",
+       "1995-01-04    0.0    0.0    0.0    0.0    0.0   0.0               191.0\n",
+       "1995-01-05    0.0    0.0    0.0    0.0    0.0   0.0               186.0\n",
+       "1995-01-06    0.0    0.0    0.0    0.0    0.0   0.0               180.0"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ensemble_data_ERA5 = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "ensemble_data_CMIP = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=CMIP_forcing\n",
+    ")\n",
+    "\n",
+    "# ensemble_data_QDM = run_hbv_ensemble(\n",
+    "#     par_ensemble=par_ensemble,\n",
+    "#     initial_storages=s_0,\n",
+    "#     forcing=QDM_forcing\n",
+    "# )\n",
+    "\n",
+    "ensemble_data_ERA5.head()\n",
+    "ensemble_data_CMIP.head()\n",
+    "# ensemble_data_QDM.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "96d6162f-f432-4dfc-9194-f522a2e6a6da",
+   "metadata": {},
+   "source": [
+    "## 4. LNSE Calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "37567a9e-dff3-4c80-84e0-572a6ed72b68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate log NSE\n",
+    "\n",
+    "def LNSE(sim, obs):\n",
+    "    \n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "id": "dc7850a4-dc30-4aa7-8719-4f810760c320",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call log NSE for relevant timeperiod\n",
+    "\n",
+    "def lnse_ensemble(ensemble_data, lnse_start, lnse_end):\n",
+    "\n",
+    "    # Select evaluation period - skip first year for storages to fill\n",
+    "    combined_data = ensemble_data[\n",
+    "        (ensemble_data.index >= lnse_start) &\n",
+    "        (ensemble_data.index <= lnse_end)\n",
+    "    ].dropna()\n",
+    "\n",
+    "    # Exclude winter months\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])\n",
+    "    ]\n",
+    "\n",
+    "    lnse_results = []\n",
+    "\n",
+    "    # Calculate LNSE for all sets\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        lnse_value = LNSE(\n",
+    "            combined_data[f\"Set {i+1}\"],\n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "\n",
+    "        # Append LNSE\n",
+    "        lnse_results.append({\n",
+    "            \"Set\": f\"Set {i+1}\",\n",
+    "            \"LNSE\": lnse_value\n",
+    "        })\n",
+    "\n",
+    "    # Calculate LNSE of ensemble mean\n",
+    "    mean_lnse = LNSE(\n",
+    "        combined_data[\"Mean\"],\n",
+    "        combined_data[\"Observed discharge\"]\n",
+    "    )\n",
+    "\n",
+    "    # Append LNSE\n",
+    "    lnse_results.append({\n",
+    "        \"Set\": \"Ensemble mean\",\n",
+    "        \"LNSE\": mean_lnse\n",
+    "    })\n",
+    "\n",
+    "    lnse_results = pd.DataFrame(lnse_results)\n",
+    "\n",
+    "    return lnse_results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "id": "80962ebd-6ad7-48ce-b378-acd68ed03a1e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set</th>\n",
+       "      <th>LNSE</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Set 1</td>\n",
+       "      <td>-0.221387</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Set 2</td>\n",
+       "      <td>-0.100210</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Set 3</td>\n",
+       "      <td>-0.154252</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Set 4</td>\n",
+       "      <td>-0.250239</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Set 5</td>\n",
+       "      <td>-0.164213</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Ensemble mean</td>\n",
+       "      <td>-0.141139</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             Set      LNSE\n",
+       "0          Set 1 -0.221387\n",
+       "1          Set 2 -0.100210\n",
+       "2          Set 3 -0.154252\n",
+       "3          Set 4 -0.250239\n",
+       "4          Set 5 -0.164213\n",
+       "5  Ensemble mean -0.141139"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lnse_results_ERA5 = lnse_ensemble(\n",
+    "    ensemble_data=ensemble_data_ERA5,\n",
+    "    lnse_start=evaluation_start,\n",
+    "    lnse_end=validation_end_date\n",
+    ")\n",
+    "\n",
+    "lnse_results_CMIP = lnse_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    lnse_start=evaluation_start,\n",
+    "    lnse_end=validation_end_date\n",
+    ")\n",
+    "\n",
+    "# lnse_results_QDM = lnse_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     lnse_start=evaluation_start,\n",
+    "#     lnse_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "lnse_results_CMIP\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9b6a719-39c6-4872-87ff-cdb65d853e42",
+   "metadata": {},
+   "source": [
+    "## 5. Display results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "id": "f519854a-a994-44fd-a428-4d0c6daa98e1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_ensemble(ensemble_data, plot_start, plot_end):\n",
+    "\n",
+    "    plot_start = pd.to_datetime(plot_start)\n",
+    "    plot_end = pd.to_datetime(plot_end)\n",
+    "\n",
+    "    # Filter data to start & end time\n",
+    "    plot_data = ensemble_data[\n",
+    "        (ensemble_data.index >= plot_start) &\n",
+    "        (ensemble_data.index <= plot_end)\n",
+    "    ].dropna()\n",
+    "\n",
+    "    # Define figure\n",
+    "    plt.figure()\n",
+    "    plt.figure(figsize=(20, 8))\n",
+    "\n",
+    "    # Plot sets, observed data, ensemble mean and axhline, respectively\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        plt.plot(plot_data.index, plot_data[f\"Set {i+1}\"], color=\"orange\", alpha=0.3, label=\"Parameter sets\" if i == 0 else None)\n",
+    "\n",
+    "    plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\", linewidth=3)\n",
+    "    plt.plot(plot_data.index, plot_data[\"Mean\"], label=\"Ensemble mean\", linewidth=3)\n",
+    "    plt.axhline(y=q_critical, linestyle=\":\", color=\"black\", label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "    # Extras\n",
+    "    plt.xlabel(\"Date\")\n",
+    "    plt.ylabel(\"Discharge (m³/s)\")\n",
+    "    plt.title(\"Observed vs modelled ensemble discharge at 07DA001\")\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "id": "f1bb58f8-3dee-43eb-abc8-4af333b5d064",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for full evaluation period\n",
+    "\n",
+    "plot_ensemble_ERA5 = plot_ensemble(\n",
+    "    ensemble_data=ensemble_data_ERA5,\n",
+    "    plot_start=evaluation_start,\n",
+    "    plot_end=validation_end_date\n",
+    ")\n",
+    "\n",
+    "plot_ensemble_CMIP = plot_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    plot_start=evaluation_start,\n",
+    "    plot_end=validation_end_date\n",
+    ")\n",
+    "\n",
+    "# plot_ensemble_QDM = plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     plot_start=evaluation_start,\n",
+    "#     plot_end=validation_end_date\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "id": "b835010a-b272-46b7-9c20-b0db1a99506b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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fGjFixDmTN4sXL9Yrr7yihIQE7d27V++9957sdrtiY2Pl5+ensWPH6oknntB7772nv//+W+vWrdPcuXPPe+5OdevW1fLly7VmzRpt375dw4cPV2Ji4nm3Gz58uP7880+NHTtWO3fu1CeffKL58+dLOlN1c75riIvnsYqY/Kxatcrtuclk0uTJkzV58uQCt/Hz89Ps2bM1e/bsAseEh4frgw8+uERRAgAAAOVY1nHHsjgSMX6nEzHZJyS7TfLyPvd4AAAAFKt69epp48aNmjx5sm677TYdP35c0dHR6tOnjyZNmqTwcPf/JxwzZow2bdqkKVOmKDg4WC+99JJrwvmwsDA999xzevTRR2Wz2dS4cWN98803rrlc5s2bp6lTp2rMmDE6ePCgIiIi1LZtW/Xo0aNQcbZu3VobNmxwm4heckxa/8MPP+jpp5/WtddeK8MwdPnll+u2225zjZk3b57uu+8+dejQQVFRUZo6daomTJhwzmOOGTNGhw4d0uDBg+Xl5aUhQ4bo5ptvVkpKSr7jw8LC9MUXX2jy5MnKzMxUvXr19NFHH+nKK6+UJE2YMEE+Pj6aOHGi/v33X8XExOj+++8/77k7TZgwQbt371ZcXJwCAgI0bNgw9enTp8B4nGrXrq3PPvtMY8aM0csvv6y2bdvq6aef1gMPPOCaI70w1xAXx2TkbgiHfKWmpio0NFQpKSkKCQnxdDilhtVq1ZIlS9SjR48yOZEaUN5wTwJlB/crSiVbtnToW8fjqt0dc7pcaokrpJwMKfLqM4mZUo77FSi7uH+BsqOs36+ZmZnavXu3ateu7VatAZRG06ZN0xtvvKH9+/df0PZ2u12pqakKCQmRl1epbrp1SZzr/i5s3qBUVcQAAAAA8CDn/DDm4OJJwkiO9mQ5+xztycpIIgYAAAAoy15//XW1bt1aERER+vnnn/Xiiy9q1KhRng6rQiERAwAAAMDBmYixVCq+Y/hGSun7pMyjUmjxHQYAAACAw65duzR16lQlJSWpRo0aGjNmjMaNG+fpsCoUEjEAAAAAHLJPOJbFMT+Mk2+kY2lNdbRC87YU37EAAAAAaObMmZo5c6anw6jQyn8DNwAAAACFY01zLM3FOCeit++Z/WcdK77jAAAAAEApQSIGAAAAgGTPkezZjsc+AcV7LGdVTNbR4j0OAAAAAJQCJGIAAAAASLZTjqWX2fFTnPwqO5YkYgAAAABUACRiAAAAAEg5pxMxxV0NIznmoDF5STkZUk568R8PAAAAADyIRAwAAACAMxUx3iWQiPHykSyVHI+zjhf/8QAAAADAg0jEAAAAAHBUp0glUxEjOapiJCk7qWSOBwAAAAAeQiIGAAAAQMlWxEiS7+lETBaJGAAAABTNnj17ZDKZlJCQUOCYVatWyWQyKTk5ucTiAgpCIgYAAABAyc4RI51pTZaTLtmySuaYAAAAcDN48GCZTKY8P927d/d0aEC54uPpAAAAAACUAiVdEeNllszBkvWklH1C8o8umeMCAAAUN7tdyvBw1a9/uORVuO/gd+/eXfPmzXNb5+vrWxxRARUWFTEAAABARWfLluw5jsfe/iV3XGdVDPPEAACA8iQjSXrxcs/+FCER5Ovrq+joaLefSpUquV43mUx6++23dfPNNysgIED16tXTokWLXK+fOHFCd9xxhypXrix/f3/Vq1fPLbFz8OBB3XbbbapUqZIiIiLUu3dv7dmzx/X64MGD1adPH02fPl1RUVEKCwvTlClTlJOTo8cff1zh4eG67LLL9M477+SJ/c8//1S7du3k5+enK6+8UqtWrTrnua5Zs0bXXXed/P39Vb16dT300ENKT08vcPzkyZPVrFkzvfPOO6pRo4aCgoL0wAMPyGaz6YUXXlB0dLSqVKmiadOmuW2XkpKiYcOGqUqVKgoJCdH111+v3377zfX633//rd69eysqKkpBQUFq3bq1VqxY4baPWrVqafr06RoyZIiCg4NVo0YN/d///d85zw+lF4kYAAAAoKJzVcP4Sl7eJXdcy+l5YrJPlNwxAQAAUGRTpkxR//79tWXLFvXo0UN33HGHkpIcyZ4JEybojz/+0NKlS7V9+3bNmTNHkZGRkqRTp06pU6dOCgoK0o8//qiffvpJQUFB6t69u7Kzs137//777/Xvv//qxx9/1H//+19NnjxZPXv2VKVKlfTLL7/o/vvv1/3336/9+/e7xfX4449rzJgx+vXXX9WuXTvddNNNOn78eL7nsHXrVsXFxalv377asmWLPv74Y/30008aNWrUOc/977//1tKlSxUfH6+PPvpI77zzjm688UYdOHBAP/zwg55//nmNHz9e69atkyQZhqEbb7xRiYmJWrJkiTZt2qQWLVqoc+fOrmuWlpamHj16aMWKFfr1118VFxenXr16ad++fW7Hfumll9SqVSv9+uuvGjFihB544AH9+eefRfjNobQgEQMAAABUdDkl3JbMydeZiEmWDHvJHhsAAACSpMWLFysoKMjt55lnnnEbM3jwYA0YMEB169bV9OnTlZ6ervXr10uS9u3bp+bNm6tVq1aqVauWunTpol69ekmSFi5cKC8vL7399ttq3LixGjZsqHnz5mnfvn1u1Svh4eF65ZVXFBsbqyFDhig2NlanTp3SU089pXr16mncuHGyWCz6+eef3eIaNWqUbrnlFjVs2FBz5sxRaGio5s6dm+95vvjiixo4cKBGjx6tevXqqV27dnrllVf03nvvKTMzs8DrY7fb9c477+iKK65Qr1691KlTJ+3YsUOzZs1SbGys7rnnHsXGxrrOZ+XKldq6das+/fRTtWrVSvXq1dOMGTMUFhamzz77TJLUtGlTDR8+XI0bN1a9evU0depU1alTx63SSJJ69OihESNGqG7duho7dqwiIyPPW/WD0ok5YgAAAICKzlkR41PCiRifQMnLItmzHckYZ2IGAAAAJaZTp06aM2eO27rwcPf/L2vSpInrcWBgoIKDg3XkyBFJ0gMPPKBbbrlFmzdvVrdu3dSnTx+1a9dOkrRp0yb99ddfCg4OdttfZmam/v77b9fzK6+8Ul5nzWkTFRWlRo0auZ57e3srIiLCdUyntm3buh77+PioVatW2r59e77n6YxlwYIFrnWGYchut2v37t1q2LBhvtvVqlXLLf6oqCh5e3vnidcZ26ZNm5SWlqaIiAi3/WRkZLjOOT09XVOmTNHixYv177//KicnRxkZGXkqYs6+7iaTSdHR0XmuAcoGEjEAAABAReepihjJkXzJSHS0JyMRAwAAygP/cOnxv88/rrhjKKTAwEDVrVv3nGPMZrPbc5PJJLvdUdF8ww03aO/evfrf//6nFStWqHPnzho5cqRmzJghu92uli1buiU/nCpXrnzO/Z/rmOdiMpnyXW+32zV8+HA99NBDeV6rUaNGgfsramx2u10xMTH5Vq6EhYVJcrRU+/bbbzVjxgzVrVtX/v7+uvXWW93atRV07MJcA5Q+JGIAAACAis5TFTGSY56YjEQpO0nS5SV/fAAAgEvNy0sKjPR0FCWqcuXKGjx4sAYPHqxrr71Wjz/+uGbMmKEWLVro448/dk1af6mtW7dO1113nSQpJydHmzZtKnDOlxYtWmjbtm3nTTpdrBYtWigxMVE+Pj6qVatWvmNWr16twYMH6+abb5bkmDNmz549xRoXPIs5YgAAAICKzpMVMZZKjmVWUskfGwAAAMrKylJiYqLbz7Fjxwq9/cSJE/X111/rr7/+0rZt27R48WJXm6877rhDkZGR6t27t1avXq3du3frhx9+0MMPP6wDBw5cdOyvvfaavvzyS/35558aOXKkTpw4oSFDhuQ7duzYsVq7dq1GjhyphIQE7dq1S4sWLdKDDz540XGcrUuXLmrbtq369Omjb7/9Vnv27NGaNWs0fvx4bdy4UZJUt25dffHFF0pISNBvv/2mgQMHUulSzpGIAQAAACoyw5BsGY7HHqmICZNMXo55YnLSS/74AAAAFVx8fLxiYmLcfq655ppCb2+xWDRu3Dg1adJE1113nby9vbVw4UJJUkBAgH788UfVqFFDffv2VcOGDTVkyBBlZGRckgqZ5557Ts8//7yaNm2q1atX6+uvv1ZkZP7VSE2aNNEPP/ygXbt26dprr1Xz5s01YcIExcTEXHQcZzOZTFqyZImuu+46DRkyRPXr19ftt9+uPXv2KCoqSpI0c+ZMVapUSe3atVOvXr0UFxenFi1aXNI4ULqYDMMwPB1EWZCamqrQ0FClpKQUSxldWWW1WrVkyRL16NEjT89CACWPexIoO7hfUWrYMqVDyyWTSap6o2NZ0o7+7KiIqdRMCqxe8sc/D+5XoOzi/gXKjrJ+v2ZmZmr37t2qXbu2/Pz8PB0OUKzsdrtSU1MVEhIiL6/yX+txrvu7sHmD8n+VAAAAABTM1ZbM3zNJGOlMe7Js2pMBAAAAKH9IxAAAAAAVmc2D88M4WcIdy+wTnosBAAAAAIoJiRgAAACgInNWxHhifhgnZ0WM9aRkt3ouDgAAAAAoBiRiAAAAgIqsNFTEePtKPoGOx1m0JwMAAABQvpCIAQAAACqy0lARI0m+zvZkJGIAAAAAlC8kYgAAAICKzFUR4+/ZOCwkYgAAAACUTyRiAAAAgIrKsEu2TMdjj1fERDiW2cmOuAAAAACgnCARAwAAAFRUtgzJMCSTl+Tt59lYfAIdc8UYdkcyBgAAAADKCRIxAAAAQEVVWuaHcXK2J8s67tk4AAAAAOASIhEDAAAAVFS2DMfSu5QkYnyZJwYAAKCsWLVqlUwmk5KTk885rlatWpo1a9YlO27Hjh01evToIm0zefJkNWvWzPV88ODB6tOnzyWJx2Qy6auvvrok+ypJgwYN0vTp0z0dhkdlZWWpRo0a2rRpU7Efi0QMAAAAUFGVuooY5zwxSY6WaQAAACh2iYmJevDBB1WnTh35+vqqevXq6tWrl7777rtzbteuXTsdOnRIoaGhkqT58+crLCwsz7gNGzZo2LBhxRH6BXv55Zc1f/58T4fhMVu2bNH//vc/Pfjgg651gwcPlslkcvu5+uqr3bbLysrSgw8+qCpVqqhatWrq3bu3Dhw44DbmxIkTGjRokEJDQxUaGqpBgwadN1l3IWbNmqUbbrhBXbt21dChQ2Xk+vfD4MGD9eSTT55zH76+vnrsscc0duzYSx5fbiRiAAAAgIrKdjoRU1oqYswhkpePZM+Rck56OhoAAIByb8+ePWrZsqW+//57vfDCC9q6davi4+PVqVMnjRw5ssDtrFarLBaLoqOjZTKZznmMypUrKyCglPz/5mmhoaH5Jo1Ki+zs7GLd/6uvvqp+/fopODjYbX337t116NAh18+SJUvcXh89erS+/PJLffjhh1q6dKnS09PVs2dP2Ww215iBAwcqISFB8fHxio+PV0JCggYNGnTJz2H06NGqVq2a/v77b3344Yc6efLMvx/sdrv+97//qXfv3ufdzx133KHVq1dr+/btlzzGs5GIAQAAACoqV2syf8/G4WQySZZKjsfMEwMAAMqB9PR0paenu31bPzs7W+np6crKysp3rN1ud62zWq1KT09XZmZmocYW1YgRI2QymbR+/Xrdeuutql+/vq688ko9+uijWrdunWucyWTSG2+8od69eyswMFBTp051a022atUq3XPPPUpJSXFVU0yePFlS3tZkycnJGjZsmKKiouTn56dGjRpp8eLFkqTjx49rwIABuuyyyxQQEKDGjRvro48+KvJ5Pffcc4qKilJwcLDuvffePNcvd2uyzz77TI0bN5a/v78iIiLUpUsXpaenu15/5513dOWVV8rX11cxMTEaNWqU2/6OHTumm2++WQEBAapXr54WLVrkes1ms+nee+9V7dq15e/vr9jYWL388sv5xvPss8+qatWqql+/viRpzZo1atasmfz8/NSqVSt99dVXMplMSkhIcG37xx9/qEePHgoKClJUVJQGDRqkY8eOFXht7Ha7Pv30U9100015XvP19VV0dLTrJzw83PVaSkqK5s6dq5deekldunRRkyZN9N5772nr1q1asWKFJGn79u2Kj4/X22+/rbZt26pt27Z66623tHjxYu3YsaPAmGrVqqWpU6fqrrvuUlBQkGrWrKmvv/5aR48eVe/evRUUFKTGjRtr48aNbtu9/fbb+vXXX/X444+7JZV+/vlneXl56aqrrlJ2drZGjRqlmJgY+fn5qVatWnr22WddYyMiItSuXbsLep8VBYkYAAAAoKKynf4HqbefZ+M429ntyQAAAMq4oKAgBQUFuX0w/uKLLyooKCjPh/lVqlRRUFCQ9u3b51r32muvKSgoSPfee6/b2Fq1aikoKMjtW/xFbbWVlJSk+Ph4jRw5UoGBgXlez10xMmnSJPXu3Vtbt27VkCFD3F5r166dZs2apZCQEFc1xWOPPZZnn3a7XTfccIPWrFmjDz74QH/88Yeee+45eXt7S5IyMzPVsmVLLV68WL///ruGDRumQYMG6Zdffin0eX3yySeaNGmSpk2bpo0bNyomJkavv/56geMPHTqkAQMGaMiQIdq+fbtWrVqlvn37upJnc+bM0ciRIzVs2DBt3bpVixYtUt26dd32MWXKFPXv319btmxRjx49dMcddygpKcl1zpdddpk++eQT/fHHH5o4caKeeuopffLJJ277+O6777R9+3YtX75cixcv1smTJ9WrVy81btxYmzdv1jPPPJOnhdahQ4fUoUMHNWvWTBs3blR8fLwOHz6s/v37F3i+W7ZsUXJyslq1apXntVWrVqlKlSqqX7++hg4dqiNHjrhe27Rpk6xWq7p16+ZaV7VqVTVq1Ehr1qyRJK1du1ahoaG66qqrXGOuvvpqhYaGusYUZObMmWrfvr1+/fVX3XjjjRo0aJDuuusu3Xnnndq8ebPq1q2ru+66y/V7cSbX/Pz89O677+q3335z7WvRokXq1auXvLy89Morr2jRokX65JNPtGPHDn3wwQeqVauW27HbtGmj1atXnzO+i+VTrHsHAAAAUDoZxlmJmFJSESNJvqe/dZdFIgYAAKA4/fXXXzIMQw0aNCjU+IEDB7olYHbv3u16bLFYFBoaKpPJpOjo6AL3sWLFCq1fv17bt293VX3UqVPH9Xq1atXcEjgPPvig4uPj9emnn7p9uH8us2bN0pAhQ3TfffdJkqZOnaoVK1bkqYpxOnTokHJyctS3b1/VrFlTktS4cWPX61OnTtWYMWP08MMPu9a1bt3abR+DBw/WgAEDJEnTp0/X7NmztX79enXv3l1ms1lTpkxxja1du7bWrFmjTz75xC1hEhgYqLffflsWi0WS9MYbb8hkMumtt96Sn5+frrjiCh08eFBDhw51bTNnzhy1aNFC06dPd6175513VL16de3cudN1jc+2Z88eeXt7q0qVKm7rb7jhBvXr1081a9bU7t27NWHCBF1//fXatGmTfH19lZiYKIvFokqVKrlVYkVFRSkxMVGSY76h3PuVHElG55iC9OjRQ8OHD5ckTZw4UXPmzFHr1q3Vr18/SdLYsWPVtm1bHT58WNHR0erfv79SUlJ0/PhxdenSRY0aNXLta9GiRZoxY4Ykad++fapXr56uueYamUwm1+/4bNWqVdOePXvOGd/FIhEDAAAAVET2bMk4/Q8ob1/PxnI2c5hk8nIkiXLSJZ+8384EAAAoK9LS0iTJbY6Uxx9/XKNHj5aPj/tHs87qA3//M1+SGTlypIYOHeqqGHFyfmh89tjBgwcXKTZnZcH55nhxyq+CoqgSEhJ02WWX5ZsgkBxtvJ577jl9/PHHOnjwoLKyspSVlZVvxU5Btm/frvvvv99tXdu2bbVy5cp8xzdt2lSdO3dW48aNFRcXp27duunWW29VpUqVdOTIEf3777/q3LnzOY/ZpEkT1+PAwEAFBwe7VZO88cYbevvtt7V3715lZGQoOztbzZo1c9tH48aNXUkYSdqxY4eaNGkiP78z1ett2rRx22bTpk1auXKlgoKC8sT0999/53udMzIy5Ovrm+f3ftttt7keN2rUSK1atVLNmjX1v//9T3379i3w3A3DcNtXfu+n3GPyc/Y1jIqKkuSeEHOuO3LkiKKjo93av51t+/btOnDggLp06SLJcV907dpVsbGx6t69u3r27OlW1SM57qNTp06dM76LRWsyAAAAoCJyVcP4OhIfpYWXt2QJczymKgYAAJRxgYGBCgwMdPsQ2mKxKDAwUL6+vvmO9fI68/9mZrNZgYGBbh/Gn2tsUdSrV08mk6nQk5QXJRlSkLMTR/l56aWXNHPmTD3xxBP6/vvvlZCQoLi4uGKdvN7b21vLly/X0qVLdcUVV2j27NmKjY3V7t27zxuvU+5rbzKZXFUjn3zyiR555BENGTJEy5YtU0JCgu65554855T7+uaXvDh7riHJ0fasV69eSkhIcPvZtWuXrrvuunxjjYyM1KlTp857TWNiYlSzZk3t2rVLkhQdHa3s7GydOHHCbdyRI0dcSZLo6GgdPnw4z76OHj3qGlOQs6+h87zzW3d2NU5+Fi1apK5du7p+dy1atNDu3bv1zDPPKCMjQ/3799ett97qtk1SUpIqV658zv1erFL0Ly4AAAAAJaY0zg/jZDndnox5YgAAAIpNeHi44uLi9Nprr7lNTO+UnJxcpP1ZLBbZbLZzjmnSpIkOHDignTt35vv66tWr1bt3b915551q2rSp6tSp40oEFFbDhg21bt06t3W5n+dmMpnUvn17TZkyRb/++qssFou+/PJLBQcHq1atWvruu++KFMPZVq9erXbt2mnEiBFq3ry56tatq7///vu82zVo0EBbtmxRVlaWa13uyepbtGihbdu2qVatWqpbt67bT0GJM2clzh9//HHO4x8/flz79+9XTEyMJKlly5Yym81avny5a8yhQ4f0+++/q127dpIclUcpKSlav369a8wvv/yilJQU15ji9vXXX+umm25yWxcSEqLbbrtNb731lj7++GN9/vnnrjl8JOn3339X8+bNizUuEjEAAABARWTLcCxL0/wwTs5ETNZxz8YBAABQzr3++uuy2Wxq06aNPv/8c+3atUvbt2/XK6+8orZt2xZpX7Vq1VJaWpq+++47HTt2LN9WTx06dNB1112nW265RcuXL9fu3bu1dOlSxcfHS5Lq1q2r5cuXa82aNdq+fbuGDx9+3rlFcnv44Yf1zjvv6J133tHOnTs1adIkbdu2rcDxv/zyi6ZPn66NGzdq3759+uKLL3T06FE1bNhQkjR58mS99NJLeuWVV7Rr1y5t3rxZs2fPLnQ8devW1caNG/Xtt99q586dmjBhgjZs2HDe7QYOHCi73a5hw4Zp+/bt+vbbb13znjirQ0aOHKmkpCQNGDBA69ev1z///KNly5ZpyJAhBSbFKleurBYtWuinn35yrUtLS9Njjz2mtWvXas+ePVq1apV69eqlyMhI3XzzzZKk0NBQ3XvvvRozZoy+++47bdmyRXfddZcaN27sagPWsGFDde/eXUOHDtW6deu0bt06DR06VD179lRsbGyhr9mFOnLkiDZs2KCePXu61s2cOVMLFy7Un3/+qZ07d+rTTz9VdHS0wsLCXGNWr16dp13ZpUYiBgAAAKiISnNFjO/pRExOumTLOvdYAAAAXLDatWtr8+bN6tSpk8aMGaNGjRqpa9eu+u677zRnzpwi7atdu3a6//77ddttt6ly5cp64YUX8h33+eefq3Xr1howYICuuOIKPfHEE66kwYQJE9SiRQvFxcWpY8eOio6OVp8+fYoUx2233aaJEydq7Nixatmypfbu3asHHnigwPEhISH68ccf1aNHD9WvX1/jx4/XSy+9pBtuuEGSdPfdd2vWrFl6/fXXdeWVV6pnz55FqtK5//771bdvX91222266qqrdPz4cY0YMeK824WEhOibb75RQkKCmjVrpqeffloTJ06UJFeruqpVq+rnn3+WzWZTXFycGjVqpIcfflihoaFubetyGzZsmBYsWOB67u3tra1bt6p3796qX7++7r77btWvX19r165VcHCwa9zMmTPVp08f3X777erevbv8/f31zTffuM1htGDBAjVu3FjdunVTt27d1KRJE73//vuFvl4X45tvvtFVV12lKlWquNYFBQXp+eefV6tWrdS6dWvt2bNHS5YscV2ftWvXKiUlJU+7skvNZORuLId8paamKjQ0VCkpKQoJCfF0OKWG1WrVkiVL1KNHjyL3oQRw6XFPAmUH9ys87kSClL5fCmkghdTzdDR5Hf5BsqZKEa0k/xiPhsL9CpRd3L9A2VHW79fMzEzt3r1btWvXzjOfC3CpLFiwQPfcc49SUlIKPX9NfjIzMxUbG6uFCxcWufJJcszTkpqaqpCQkHMmfEraTTfdpGuuuUZPPPFEobfp16+fmjdvrqeeeqrAMee6vwubN/ApdEQAAAAAyg9nRYxPKWxNJjmqYqypUlaSxxMxAAAAgCe89957qlOnjqpVq6bffvtNY8eOVf/+/S8qCSM5Kmree+89HTt27BJFWjpcc801GjBgQKHHZ2VlqWnTpnrkkUeKMSoHEjEAAABAReScI8arlH5j0xIuaY+UzTwxAAAAqJgSExM1ceJEJSYmKiYmRv369dO0adMuyb47dOhwSfZTmhSlEkaSfH19NX78+GKKxh2JGAAAAKAiKs1zxEiSb4RjaU2V7DmSF/90AQAAQMXyxBNPFDm5gNKp9DRwAwAAAFAy7DmOH6n0JmK8/SSfAMkwpOwTno4GAAAAAC4YiRgAAACgonFWw3iZS3eliSXcscyiPRkAACgbDMPwdAgALrFLcV+TiAEAAAAqGuf8MKW1GsbJ93QiJjvJs3EAAACch7e3tyQpOzvbw5EAuNROnTolSTKbzRe8j1L89TcAAAAAxaK0zw/jZDk9T0z2CcmwSya+RwYAAEonHx8fBQQE6OjRozKbzfLy4v9bUH7Z7XZlZ2crMzOzXL/XDcPQqVOndOTIEYWFhbkSrheCRAwAAABQ0bgSMf6ejeN8zEGSl0WyZ0vWFMlSydMRAQAA5MtkMikmJka7d+/W3r17PR0OUKwMw1BGRob8/f1lMpk8HU6xCwsLU3R09EXtg0QMAAAAUNGUldZkkqM9WUaiY54YEjEAAKAUs1gsqlevHu3JUO5ZrVb9+OOPuu666y6qXVdZYDabL6oSxolEDAAAAFDRlJXWZJJkcSZikqRgTwcDAABwbl5eXvLzKwP/jwVcBG9vb+Xk5MjPz6/cJ2IulfLbwA0AAABA/lwVMaW8NZkk+TrniUmSDMOzsQAAAADABSARAwAAAFQ0Zakixhwimbwlu1XKSfN0NAAAAABQZCRiAAAAgIrEsEv2033LvcpAIsbkdWZumKzjno0FAAAAAC4AiRgAAACgInFWw5i8JG+LZ2MpLN9wxzI7ybNxAAAAAMAFIBEDAAAAVCSutmRlYH4YJ8tZ88QAAAAAQBlDIgYAAACoSGwZjmVZmB/GyRLmWOZkSLYsj4YCAAAAAEXl0UTMnDlz1KRJE4WEhCgkJERt27bV0qVLXa8PHjxYJpPJ7efqq69220dWVpYefPBBRUZGKjAwUDfddJMOHDjgNubEiRMaNGiQQkNDFRoaqkGDBik5ObkkThEAAAAoXVwVMWUoEePlI5mDHI+tKZ6NBQAAAACKyKOJmMsuu0zPPfecNm7cqI0bN+r6669X7969tW3bNteY7t2769ChQ66fJUuWuO1j9OjR+vLLL7Vw4UL99NNPSktLU8+ePWWz2VxjBg4cqISEBMXHxys+Pl4JCQkaNGhQiZ0nAAAAUGqUxdZkkmQOdSyzScQAAAAAKFt8PHnwXr16uT2fNm2a5syZo3Xr1unKK6+UJPn6+io6Ojrf7VNSUjR37ly9//776tKliyTpgw8+UPXq1bVixQrFxcVp+/btio+P17p163TVVVdJkt566y21bdtWO3bsUGxsbDGeIQAAAFDKlMXWZNLpRMxBKmIAAAAAlDkeTcSczWaz6dNPP1V6erratm3rWr9q1SpVqVJFYWFh6tChg6ZNm6YqVapIkjZt2iSr1apu3bq5xletWlWNGjXSmjVrFBcXp7Vr1yo0NNSVhJGkq6++WqGhoVqzZk2BiZisrCxlZZ3pP52amipJslqtslqtl/TcyzLnteCaAKUD9yRQdnC/wlNM2WmSLUeG3VsqS+8/k79MthwpM0lGCcfN/QqUXdy/QNnB/QqUHdyvZxT2Gng8EbN161a1bdtWmZmZCgoK0pdffqkrrrhCknTDDTeoX79+qlmzpnbv3q0JEybo+uuv16ZNm+Tr66vExERZLBZVqlTJbZ9RUVFKTEyUJCUmJroSN2erUqWKa0x+nn32WU2ZMiXP+mXLlikgIOBiTrlcWr58uadDAHAW7kmg7OB+RUmrbPtNXkaWkrxPyWoK8nQ4hWYyrKpi+1WSdMT7pAxTyf9ThvsVKLu4f4Gyg/sVKDu4X6VTp04VapzHEzGxsbFKSEhQcnKyPv/8c91999364YcfdMUVV+i2225zjWvUqJFatWqlmjVr6n//+5/69u1b4D4Nw5DJZHI9P/txQWNyGzdunB599FHX89TUVFWvXl3dunVTSEhIUU+z3LJarVq+fLm6du0qs9ns6XCACo97Eig7uF/hEYYh0yFDkiEjqkuZa09mOhwk2TJkRLSVfCNK7Ljcr0DZxf0LlB3cr0DZwf16hrOT1vl4PBFjsVhUt25dSVKrVq20YcMGvfzyy3rzzTfzjI2JiVHNmjW1a9cuSVJ0dLSys7N14sQJt6qYI0eOqF27dq4xhw8fzrOvo0ePKioqqsC4fH195evrm2e92Wyu8G+u/HBdgNKFexIoO7hfUaJsmZK3t2QySb5BjmVZ4h8hZSRKOiWZ859HsjhxvwJlF/cvUHZwvwJlB/erCn3+XsUcR5EZhuE2N8vZjh8/rv379ysmJkaS1LJlS5nNZrcSqEOHDun33393JWLatm2rlJQUrV+/3jXml19+UUpKimsMAAAAUCHYMh1LL9+yl4SRJHOoY5md4tk4AAAAAKAIPFoR89RTT+mGG25Q9erVdfLkSS1cuFCrVq1SfHy80tLSNHnyZN1yyy2KiYnRnj179NRTTykyMlI333yzJCk0NFT33nuvxowZo4iICIWHh+uxxx5T48aN1aVLF0lSw4YN1b17dw0dOtRVZTNs2DD17NlTsbGxHjt3AAAAoMQ5EzFlrCWZi/l0i2Br4cr/AQAAAKA08Ggi5vDhwxo0aJAOHTqk0NBQNWnSRPHx8eratasyMjK0detWvffee0pOTlZMTIw6deqkjz/+WMHBwa59zJw5Uz4+Purfv78yMjLUuXNnzZ8/X97e3q4xCxYs0EMPPaRu3bpJkm666Sa9+uqrJX6+AAAAgEfZMhxLb3/PxnGhLGGOZc5JyW6TvLzPORwAAAAASgOPJmLmzp1b4Gv+/v769ttvz7sPPz8/zZ49W7Nnzy5wTHh4uD744IMLihEAAAAoN8p6RYy3n+RlkezZjmSMMzEDAAAAAKVYqZsjBgAAAEAxKesVMZJkOT1PjJV5YgAAAACUDSRiAAAAgIrClYgpoxUxkmQ+nYjJJhEDAAAAoGwgEQMAAABUFK7WZGW4IsZMRQwAAACAsoVEDAAAAFARGEb5SMS4WpOlOs4JAAAAAEo5EjEAAABARWDPkgy7ZDKV7dZk3gGSl4/jXHLSPB0NAAAAAJwXiRgAAACgIjh7fhiTybOxXAyTSTKHOB7TngwAAABAGUAiBgAAAKgIykNbMifnPDHZJGIAAAAAlH4kYgAAAICK4OyKmLLOmYihIgYAAABAGUAiBgAAAKgIcpyJmPJQEeNsTZbq2TgAAAAAoBBIxAAAAAAVga0cJWJ8ghxzxditki3L09EAAAAAwDmRiAEAAAAqgvKUiPHylrwDHI+tJz0bCwAAAACcB4kYAAAAoCIoT4kYSTIHO5Y5JGIAAAAAlG4kYgAAAIDyzrCfaeFVXhIxPqcTMVTEAAAAACjlSMQAAAAA5Z0t07E0eUneFs/GcqlQEQMAAACgjCARAwAAAJR35a0tmST5BDmWVMQAAAAAKOVIxAAAAADlXXlNxJhMkt16pu0aAAAAAJRCJGIAAACA8i7ndCLGpxwlYry8Je8Ax2OqYgAAAACUYiRiAAAAgPLOWRHj5efZOC415okBAAAAUAaQiAEAAADKO1umY+kT4Nk4LjWf04kYKmIAAAAAlGIkYgAAAIDyzjVHDBUxAAAAAFDSSMQAAAAA5Z0rEVOO5oiRJJ8gx5KKGAAAAAClGIkYAAAAoDyz50h2q+NxeUzEmEyO87NleToaAAAAAMgXiRgAAACgPHPOD+Nllrx8PBvLpeblLXmfnveGqhgAAAAApRSJGAAAAKA8K6/zwzgxTwwAAACAUo5EDAAAAFCeldf5YZx8TidiqIgBAAAAUEqRiAEAAADKs/KeiKEiBgAAAEApRyIGAAAAKM/KeyLGJ8ixpCIGAAAAQClFIgYAAAAoz3JOJ2J8ynEixmSS7FbJluXpaAAAAAAgDxIxAAAAQHlW3itivLwl7wDHY6piAAAAAJRCJGIAAACA8syViPHzbBzFiXliAAAAAJRiJGIAAACA8sqWLRl2x+PyWhEjST6nEzFUxAAAAAAohUjEAAAAAOWVqxrGVzKV4//1pyIGAAAAQClWjv81BgAAAFRw5X1+GCczFTEAAAAASi8SMQAAAEB5VRHmh5EknyDJZJLsVsmW6eloAAAAAMANiRgAAACgvMo55Vj6BHo2juJm8jpzjlTFAAAAAChlSMQAAAAA5VVOmmNZ3hMxkmQOcSytqZ6NAwAAAAByIREDAAAAlFc56Y6ldwVIxPicnicmh4oYAAAAAKULiRgAAACgPDIMyVZBWpNJkvl0IoaKGAAAAAClDIkYAAAAoDyynXIkY0xekrefp6Mpfq7WZGmO8wYAAACAUoJEDAAAAFAeOduS+QRKJpNnYykJ3gGOpJNhO1MJBAAAAAClAIkYAAAAoDw6OxFTEZhMZ7UnY54YAAAAAKUHiRgAAACgPKpoiRhJ8mGeGAAAAAClD4kYAAAAoDxyJWKCPBtHSXLOE5NDRQwAAACA0oNEDAAAAFAeVcSKGDMVMQAAAABKHxIxAAAAQHlj2M9MWF+hEjHOiph0xzUAAAAAgFKARAwAAABQ3tgyJMOQTN6Sl6+noyk53n6Sl9lx7jlpno4GAAAAACSRiAEAAADKn7PbkplMno2lpLnakzFPDAAAAIDSgUQMAAAAUN5UxPlhnHyYJwYAAABA6UIiBgAAAChvKnIixjlPDBUxAAAAAEoJEjEAAABAeeOcH6VCJmJOV8TkkIgBAAAAUDqQiAEAAADKm5xTjmVFTMQ4W5PlnJLsOZ6NBQAAAABEIgYAAAAoXwy7ZKvAiRhvi+Tt53hMVQwAAACAUoBEDAAAAFCe2DIkw5BM3mcSEhWNsz0Z88QAAAAAKAVIxAAAAADlibUCzw/j5GxPZk31bBwAAAAAIMnH0wEAAAAAuIRs6Y5lBUrEHE/L0qodR5WWdXpOmGyrzJnS1bWPqU6YR0MDAAAAABIxAAAAQLmSU7ESMSfSs9Vr9k/6NyUz1ytesqxO00dDj6llrUiPxAYAAAAAEq3JAAAAgPKlgiViVu44kk8SxiHbZtJn6/8p4YgAAAAAwB2JGAAAAKA8cSVigjwbRwk5cjLrnK8fTE4voUgAAAAAIH8kYgAAAIDywrBLtgzHY58Az8ZSQk5mWs/5+rG0cydqAAAAAKC4kYgBAAAAyoucU5JhSF4+krefp6MpEakZOW7Pq4X5uz0/mmZzXBMAAAAA8BCPJmLmzJmjJk2aKCQkRCEhIWrbtq2WLl3qet0wDE2ePFlVq1aVv7+/OnbsqG3btrntIysrSw8++KAiIyMVGBiom266SQcOHHAbc+LECQ0aNEihoaEKDQ3VoEGDlJycXBKnCAAAAJQcZ1sy74pRDSNJqbkqYupUdp8bJynDkC07tSRDAgAAAAA3Hk3EXHbZZXruuee0ceNGbdy4Uddff7169+7tSra88MIL+u9//6tXX31VGzZsUHR0tLp27aqTJ0+69jF69Gh9+eWXWrhwoX766SelpaWpZ8+estlsrjEDBw5UQkKC4uPjFR8fr4SEBA0aNKjEzxcAAAAoVtbTCQdzsGfjKEEnM90rYupEuidibIZJJ5KPlGRIAAAAAODGx5MH79Wrl9vzadOmac6cOVq3bp2uuOIKzZo1S08//bT69u0rSXr33XcVFRWlDz/8UMOHD1dKSormzp2r999/X126dJEkffDBB6pevbpWrFihuLg4bd++XfHx8Vq3bp2uuuoqSdJbb72ltm3baseOHYqNjS3ZkwYAAACKS87pLyyZQzwbRwlKzXCviKmVKxEjSceSkxQZVVIRAQAAAIA7jyZizmaz2fTpp58qPT1dbdu21e7du5WYmKhu3bq5xvj6+qpDhw5as2aNhg8frk2bNslqtbqNqVq1qho1aqQ1a9YoLi5Oa9euVWhoqCsJI0lXX321QkNDtWbNmgITMVlZWcrKOjOxZ2qq49uFVqtVVuu5JwStSJzXgmsClA7ck0DZwf2K4mDKSJJsOTLkL1WQ91buREyon7cqBZh14tSZ9YeTjuvyi7ge3K9A2cX9C5Qd3K9A2cH9ekZhr4HHEzFbt25V27ZtlZmZqaCgIH355Ze64oortGbNGklSVJT7V9eioqK0d+9eSVJiYqIsFosqVaqUZ0xiYqJrTJUqVfIct0qVKq4x+Xn22Wc1ZcqUPOuXLVumgICK03O7sJYvX+7pEACchXsSKDu4X3HJGHZF2TZJMnTUO0d2k8XTEZWII8nekkyu539uTZCv4eW2bv2WHUo9nCa7yfeijsX9CpRd3L9A2cH9CpQd3K/SqVOnCjXO44mY2NhYJSQkKDk5WZ9//rnuvvtu/fDDD67XTSaT23jDMPKsyy33mPzGn28/48aN06OPPup6npqaqurVq6tbt24KCak4rR7Ox2q1avny5eratavMZrOnwwEqPO5JoOzgfsUlZ02V6agkL7OM6DhPR1Nintr0naQz80N2vrattmb/pcR/klzrgqPrqHunppJ/tQs6BvcrUHZx/wJlB/crUHZwv57h7KR1Ph5PxFgsFtWtW1eS1KpVK23YsEEvv/yyxo4dK8lR0RITE+Maf+TIEVeVTHR0tLKzs3XixAm3qpgjR46oXbt2rjGHDx/Oc9yjR4/mqbY5m6+vr3x9835jzmw2V/g3V364LkDpwj0JlB3cr7hkrBmSt4/kW0mqIO+pHJtd6dk2t3WVgvxUJcTPbV1SprfM9pMXfV24X4Gyi/sXKDu4X4Gyg/tVhT5/r2KOo8gMw1BWVpZq166t6Ohot/Km7Oxs/fDDD64kS8uWLWU2m93GHDp0SL///rtrTNu2bZWSkqL169e7xvzyyy9KSUlxjQEAAADKPOtJx9Jccaq307Jy8qwL8TMrMsj9C1XHTknKSsozFgAAAABKgkcrYp566indcMMNql69uk6ePKmFCxdq1apVio+Pl8lk0ujRozV9+nTVq1dP9erV0/Tp0xUQEKCBAwdKkkJDQ3XvvfdqzJgxioiIUHh4uB577DE1btxYXbp0kSQ1bNhQ3bt319ChQ/Xmm29KkoYNG6aePXsqNjbWY+cOAAAAXFLW0yXxFSgRczIzn0SMv48qB7snYo6ekuP62K2SV8X+xh4AAACAkufRRMzhw4c1aNAgHTp0SKGhoWrSpIni4+PVtWtXSdITTzyhjIwMjRgxQidOnNBVV12lZcuWKTg42LWPmTNnysfHR/3791dGRoY6d+6s+fPny9vb2zVmwYIFeuihh9StWzdJ0k033aRXX321ZE8WAAAAKE7ORIxP8LnHlSMpGVa3595eJvmbvfNUxBzN8JJkk7JPSH5VSjBCAAAAAPBwImbu3LnnfN1kMmny5MmaPHlygWP8/Pw0e/ZszZ49u8Ax4eHh+uCDDy40TAAAAKB0s1slW6bjcQWqiEnNdE/EhPj5yGQyKTLI4rb+WIbJ8SDzMIkYAAAAACWu1M0RAwAAAKCIXNUw/pKXR79rVaJytyYL9nO0HcvdmizplF02u6RTByR73nZmAAAAAFCcSMQAAAAAZZ31pGPpU3GqYSQpNVdrshB/RxKqcq7WZHZDSrIGOJIwGf+WWHwAAAAAIJGIAQAAAMo+Z0VMBWpLJuWtiAk5XRETHmiRyeQ+9pgR7XiQvqcEIgMAAACAM0jEAAAAAGWdKxET7Nk4SljuOWKC/RwVMT7eXgoPcJ8n5mhOuGTykrJTHD8AAAAAUEJIxAAAAABlXc7p1mQVrCImNSP/ihhJiszVnuzYKZvkH+N4QlUMAAAAgBJEIgYAAAAoy3JOOeY+MXlJPoGejqZEncxTEXMmEVM52D0Rc/RklhRYy/Hk1EHHNQMAAACAEkAiBgAAACjLrKerYXyCHMmYCiR3a7IQfx/X48gg99Zkx9KyJN9wyRwkGTbp1IESiREAAAAAKta/1AAAAIDyxjU/TMVqSyZJJzMLbk2Wb0WMJAXWdCzT9xZrbAAAAADgRCIGAAAAKMtynImYYM/G4QG5K2KC/c6uiMk1R0xatuNBQHVH5ZA1Vco6XuwxAgAAAACJGAAAAKAsc7Ymq4AVMakZuSpi/AuuiDmWdroixsvsSMZI0onfJLutWGMEAAAAABIxAAAAQFll2KWcNMfjCpiIOVmEihhXazJJCm0oeftJOenSyZ3FGiMAAAAAkIgBAAAAyirrSckwHFUe3n6ejqZEGYah1HPMEZM7EZN0Kls5NrvjiZdZCmvseJz2t5SdXJyhAgAAAKjgSMQAAAAAZZU1xbE0h3o2Dg/IsNpksxtu60LP0ZrMMKSk9OwzK/yjpYBqjhdOJDiqiwAAAACgGJCIAQAAAMoqZyWHpeIlYnLPDyO5tyYLD7TIy+T++tG0LPcVoY0kL4ujsujkruIIEwAAAABIxAAAAABllqsiJsyjYXhCaq75YSQpyPdMIsbby6TwQPeqmGNp2e4beFvOtCg7ucsxZwwAAAAAXGIkYgAAAICyyLBL1lTH4wpYEXMyVyIm0OItH2/3f95EBlncnh89masiRpICqkp+VRwtyk7+fcnjBAAAAAASMQAAAEBZlJPmSMZ4mSWfQE9HU+JytyYLOWt+GKfc88Qcy92azCm4rmN5ar9ky85/DAAAAABcIBIxAAAAQFnknB/GXPGqYaS8rclC/PJJxAS5J2LyrYiRJN8IyRLmSGyl77lEEQIAAACAA4kYAAAAoCxyzg9TAduSSVJqpntFTLCfT54xkYWtiJGkoMsdy7Tdkt120fEBAAAAgBOJGAAAAKAsclXEhHkyCo9JzchVEZNfa7KgIiRi/GMknwDJni1lHLgkMQIAAACARCIGAAAAKHsMu2RNdTy+RBUxWTk2zVqxU49/+psS9idfkn0Wp5OFqoixuD0vsDWZJJlMUlCd0zv/WzKMi44RAAAAACQp779WAAAAAJRuOWmOZIyXWfIJvCS7HPvZFn2V8K8kKX5bolY+1lGRuSpKSpPCzBGTO/5jadnn3mlAdSl1h5STLmUelvyjLzpOAAAAAKAiBgAAAOVTzinJdp4P3ssqV1uyS1MNs2lvkisJIzmqTb7dlnhJ9l1cclfEhPjn/Y5Z5VxzxCSlZ8tqsxe8Uy8fKbCW43Ha3xcbIgAAAABIIhEDAACA8sh6Ujq8UkpcLp34TbKmeTqiS8ua4lhegrZkhmFo+pI/86xf90/SRe+7OOWeIya4EBUxkiMZc05BtRxtyrKSHJUxAAAAAHCRSMQAAACg/Dl10NG6y7BL6fscSZlj68vPB+uXsCLm222J2rT3RJ716/45LqMUz5NSmNZklQIs8vYyua075zwxkuTtJ1nCHY+zjl1UjAAAAAAgkYgBAABAeZR5uq1WcN0z83xkHpaOb/RcTJeKYZesqY7HlrCL2pXVZtfz8Tvyfe3oySztPlZ6E1e5W5MF++VtTebtZVJ4oMVt3dG08yRiJMm3smOZefSC4wMAAAAAJxIxAAAAKF9y0h2tyUwmRyImorUU1UkyeTsSGGX9w/WcNEcyxssseQdc1K4+Wr/vnMmW0tyeLHdrshD/vBUxklQ5V3uyY+eriJEkv0jHMuuYVIqrggAAAACUDSRiAAAAUL5knK6G8Y10JCskyRwkBdZ0PD75l2fiulTObktmMp1z6LmczLTq5RW7zjlm3T/HL3j/xS13RUxIPhUxkhQZ7J6IKVRFjDnM8d6xW8/MxwMAAAAAF4hEDAAAAMoXZ1syv2j39UF1Tk/CfkzKLsMfrjsTA5aLmx/m7dW7dTzXxPU3N6/m9ry0zhOTnWNXhtXmti44nzliJCkqVyImMSXz/AcwmSTfCMfjsl5BBQAAAMDjSMQAAACg/LBlSVmn22n550rE+PhL/qcTDWlluCrm7IqYC3QqO0fvrt3jtq5Lwyg9eH1dt3VHSuk8MSczrXnWhfjnXxFTNczf7fnBExmFO4hznpgsEjEAAAAALg6JGAAAAJQfmYcdS0uY5O2X9/Xgyx3LjEOOuWTKGsPumOdGcpzjBfpkw34ln3JPZjweF6vakYGqkquCpDTOE5O7LZkkhRRQEVMtdyImuZCJGL/TiZjsE5I97/EAAAAAoLBIxAAAAKD8yDjkWOZuS+ZkDpH8qjgmYE/7p+TiulRy0hzJGC8fyTvgwnZhs+vtn3a7revcoIpio4NlMpl0dZ0It9dK4zwxqbkqYizeXvL1yf+fNtUqXWAixifQUUVl2KXs0peMAgAAAFB2kIgBAABA+WDPccz/Ikn+MQWPCz7dfit9n6OVWVlydlsyk+mCdrH090QdyNWea9h1dVyPcydiftld+uaJyV0RE+LvI1MB1yN3a7KTmTl5EjkFoj0ZAAAAgEuARAwAAADKh8wjjuoFn0DJHFTwON8IR1svwy6l/V1i4V0S1hTH8gLbkhmGof/70b0SqGn1MLWpHe56fnWdcLfXD6dmac/xUxd0vOKSmuGeSAkuoC2ZJMWE5m1R929hq2JOJ2JMzgQfAAAAAFwAEjEAAAAoHzITHctzVcM4hcQ6lmn/OOYAKSuyTydizKEXtPnaf45r68EUt3XDr6vjVk1SOzJQlfPME1O62pPlrmgJ8fMpcKyf2VuRQe7nU/hETKRjmXNSXkZ2kWIEAAAAACcSMQAAACj7DLuUedjx2L+A+WHO5ldFCrjMMVfMiQTH9qWdYVx0RUzuapiaEQGKu9L9epWFeWJytyY7V0WMlM88MScKmYjxtkgWR9LLYqQWPkAAAAAAOAuJGAAAAJR9OWmOOWK8zJI5rHDbhDWSvH0la5qUuqNYw7skck46EkZePpJ3QJE335F4Uqt2uM91ct81teXtlXduldztydb9U7rmicndmizEv+CKGEmqFubenuxgcmbhD3a6PZkviRgAAAAAF4hEDAAAAMo+a5pj6RNU+EnsvcxSWBPH47S/S3+LsrPbkhX2HM/yVcJBt+fhgRbd2rJ6vmNzV8QcTs3S3lI0T0xqroqYkPNVxITlqogpbGsyyZWIsYhEDAAAAIALQyIGAAAAZV/O6USMOaho2/lHu7coyyk9yYY8rMmO5QW2Jduf5H5uvZtVlb/FO9+xdSIDFRlkcVv324HkCzpuccg9R0zwOeaIkaSquRIxhZ4jRpIslSSZHHPE2IpQSQMAAAAAp5GIAQAAQNmXc1ZFTFGd3aIs8Tvp0HIpaZOUtkeyZV3SMC/K2RUxF+DEKffJ5nNXiZzNZDKp6WVhbusS9idf0HGLQ2rGRVbEFHaOGEny8pbMwY7HzmQYAAAAABQBiRgAAACUfTnpjuWFJGK8zFJEa0flg8nkqHo49a+UvFVKXC4d+0U6dVCy2y5tzEVhGJL1dCLmAitiktLdq0gqBVgKGOnQtLr7cX4rRYmYkxdZEXP4ZKasNnuhj2c4k1/ZyYXeBgAAAACczv0vFgAAAKAscFXEBF7Y9pZKUpVrHMkWa7KUlSRlHnbMG5N5xPHj7SdVvkbyKbiSpNjknJQMu+TlI3kHXNAuTqS7V8SEBxYtEfP7v6my2uwye3v+u1x55ojxP3dFzGWV3H9nhiElpmSqenghr6U5TJJkcibDAAAAAKAIPP+vKAAAAOBi2DIle46jmuVCEzFOXt6Sb4QUUs+RmIm+Xgqp70jC2DKl1O2XJuaiOrstmclU5M0Nw1BSrtZklc6XiLnMvQVado5dOxJPFvnYxSF3Rcz5WpOF+psVkGs+nINFmicmzLGkNRkAAACAC0AiBgAAAGWb9XQ1jHeAZLrE/3vrEyiFxEoRbRzPTx10VMmUNGcC4ALnhzmVbVN2jnsrrvDztCYLC7CoVoR7xUhpmScmNaNorclMJtPFzRPjEyzJS7Jbz7TBAwAAAIBCIhEDAABQgX3/52E9+kmC3l2zR1k5HpwD5WK42pJdwPwwhWUJlQJrOB4nb3P0tipJ2Rc7P0x2nnWVAs9dRSKVznli7HZDJ7OK1ppMyjtPzL9FqYgxeclqOp2UYp4YAAAAAEVEIgYAAKCC2rQ3SUPf26QvNh/UpEXbdMucNfrnaJqnwyo6Z4WCuRgTMZIU0sAxR0v2CSnjYPEe62yGIVlTHY8vsCLmRK62ZGZvk4J8zz9dZNPLwtye/3Yg+YKOfymlZ+fkyYOdryJGkqrlmiemSK3JJFlNp9vekYgBAAAAUEQkYgAAACqo//vxH9nsZz7R/v1gqnrO/kmfbzpQMgHYMqXk3yXrRc47UhIVMZLk7SsF13M8Ttku2UuogijnpGTYHEmgC5wDJ3dFTKUAi0yFmGsmd0XMriNpSstVjVLSUjPzHr8wFTF5WpMVNRGj09eeeWIAAAAAFBGJGAAAgAroyMlMfbf9SJ71p7JtGvPpb3ry8y0yirP9lmGXjm+Q0nZLJxIubl+uRMyFJSmKJKiO5BPgSCKl/VX8x5POtCUzh0qFSJ7kJ3dFTHjgueeHcbqyaoh8vM4c0zCkrQdSLiiGS+Vkpvv8MCaTFGQpREXMxSZiXBUxKSXfmg4AAABAmUYiBgAAoAL6fNNB5dgL/jB54Yb9+iqhGNtvpfxxpsVTdrKUefTC9mO3STmnHI+LuyJGkkxeUugVjscn/3ZM3l7cnBUYF9iWTJKS0t3jrBRQuESMn9lbDWKC3dZ5uj1ZaoZ7RUyQr4+8vM6foMpvjpiiJBtt8pNMPo7qpJyLrOICAAAAUKGQiAEAAKhgDMPQxxv2ua2LCvHNM+7LX/8tngAyDjkqYSTJN9yxPLnrwvZlOz0/jJfZ0TqsJPjHSOZgxwfyGYnFfzxnRYwl7IJ3cSL9wipipHzmidmffMFxXAopGe5JpRC/87clk/LOEZNptedp2XZOJtOZ3wHzxAAAAAAoAhIxAAAAFcwvu5O05/gpt3WvDWyhCT2vcB/3z3FlWi/xPCg56WdakQXXlcJbOqpMso5LWUkXtj+pZKphzuZfzbHMKMaqIcnRAsua6nh8MRUxuVqTVQosXPJCyjtPjKcTMckXeC5Rwb7yzlU5829yZpGObTh/ByRiAAAAABQBiRgAAIAKZuF692qYulWC1LJmJd3a4jKd/Tl1Vo5dG/ZcQHKkIIZdOr5Rsuc4KmFCYiVvPyngMsfrF1IVYz09P4y5hBMxAVUdy6xjkq0IVRVFlZPuqLwxeV/UHDh5KmIK2ZpMkprlSsT8m5KpI6lFS2BcSsmn3CtiwvwLdy4+3l6KDvFzW1fUeWJkDnMsne3iAAAAAKAQSMQAAABUICmnrFryu3s7rdtbV5fJZFJogDlP9cPqXccu3cEzEh3VHV6WM5UwkqMyxmSSMo+cacNVWDmnEzHeF56kuCA+gZIl1FGxknmo+I5jPX09zCGOa3SBcrfgqlSE1mSXVw5SoMXbbd1vB4r4e7qEkjPczyUsoPDVPVXDLjIR42xNZk11JBYBAAAAoBBIxAAAAFQgXyUcVHbOmQ+Qzd4m3dy8muv5tfUqu43/cefRS3dwZ4st/2hHJYyTT6Dkf7rCpKhVMTkeqoiRzsR8qpjm0pHOaksWclG7OXHqwueI8fYyqfFl7m3RPNme7ETuipgiJGKqhbnPE/NvURMx3v6ORKJhnEmSAQAAAMB5kIgBAACoIAzD0Ee52pJ1uyJaEUFnJrm/rl6k2+t/Jp68dG2oXEmT4LyvBddzLDMOSdaTRd9nSc8RI51JxGQfl2xZxXMMZyLGcuHzw0hSUrp78qIoiRgpn3liDiRfVDwXIyVXIqZSEdqsVc2ViDl4ooiJGOlMVQzzxAAAAAAoJBIxAAAAFcS2f1P1Z6J7kuP2NtXdnjetHqZgXx+3dZesPdm5kibmYEeljCSl78v7en5smY75Zkymi5o/5YL5BEiWSo7qiIxiqoo5uzXZBbLbjf9n777j3Kjv/I+/Rl1a7Wr7rsu694qNDaaZEmNsWggJJCEh4S7hUoA7LqTnckcul5ByScgvueRypJBACKQRIBAHm2aMbYyNe+9lvb1odyWt6vz++EorjbRF2tWubfx5Ph77kGY0mhlpJbD03s/nk1ERk0t4AXDB2GLD8vaT7URj+qDPaSjSH4vHmUNFTElaRYxXghghhBBCCCHE8JMgRgghhBDiPPHWsVbD8phiJ5dNNlbAWM0mLp1SZlj3+sE8tCfTdTV4HvquXnHFQ6Huhuz2mdif2ZWcNzPSXPGqmOEIYqLBZKWNZfBBTGd3JCM0ybUi5oJxxYblju4Ibx5tGfQ5DUX7ma6IsRary3B77vcVQgghhBBCnJckiBFCCCGEOE/sreswLF88qRSTKXMAfPqcmHWHmokNtfoh4lPDzTWzmrPRG3u5ClQivuzak/VU2JyBapiERHuyYKuq0MmnnvkwbjCZB72b1rQKEsi9ImaUx8nMUcYw6K876gZ9TkPRnvZ4cpkRMzYtiGnxhegOR3M7gURFTLhLVWQJIYQQQgghxAAkiBFCCCGEOE+ktyWbNar3KoulaUFMc1eIvfUdvW6btZ75MG7VSqw3JosKYwAC9QPvM3wG58MkmB1gL1XX810Vk4e2ZACtPmNw4bSacdpyD3Zumj/KsPy3nXWEo7EhndtgtAeMFTG5BDHpFTEAte05VsWY7WCJ70fakwkhhBBCCCGycEaDmIceeojFixdTWFhIZWUlt9xyC/v37zdsc9ddd6FpmuFnyZIlhm2CwSD33Xcf5eXlFBQUcPPNN3Pq1CnDNm1tbdx55514PB48Hg933nkn7e3tw/0QhRBCCCHOCpFojP1pQUx6hUPCuDIX48tchnVrDwxxTkyiwmWg0CQxJyab9mSp4c6ZlKiK8ec7iElUxHiGtJu2tCAm17ZkCTfNG23crz/MG4fyND8oS8FIFH/IWMFSnEN1T4HdkhHcnM41iAFpTyaEEEIIIYTIyRkNYl577TXuueceNm7cyOrVq4lEIixfvhyfz2fYbsWKFdTV1fX8vPDCC4bb77//fp5++mmefPJJ1q1bR1dXFzfeeCPRaPJD2h133MG2bdtYtWoVq1atYtu2bdx5550j8jiFEEIIIc60Yy0+ghFj9cKM6sI+t79iqnF2zJDnxPS0Eev7mAA4qtRlqC05H2XAfZ4lQUyoDSKD+FK/L/mqiElr5VVSkH0FSaqaUhfza4oN657bPrLtybxp82EAip25PZ7RHmNVzMnWQfzOEu3JpCJGCCGEEEIIkQXLmTz4qlWrDMu/+tWvqKysZMuWLSxdurRnvd1up7q6utd9eL1efvGLX/DYY4+xbNkyAB5//HFqampYs2YN1113HXv37mXVqlVs3LiRiy++GIBHHnmESy65hP379zN9+vRheoRCCCGEEGeHPXXGapjKQjtlbnuf218xtYLHN57oWd58rA1/KILLNsh/PmZbvWJ2qC+5Q+2qKqZgXO/b6TGIxr9AP5MzYkC1qrKXqjkx3fXgnjj0fcaialYODDmISa+IyXU+TKqb5o1i+8n2nuUXd9cTjMzBbhn8DJtctPUSxHhyDGLGlbrYkzIv6Xirr5+t+yAVMUIIIYQQQogcnNEgJp3Xq/7qr7S01LD+1VdfpbKykuLiYq688kq+8Y1vUFlZCcCWLVsIh8MsX768Z/vRo0czZ84c1q9fz3XXXceGDRvweDw9IQzAkiVL8Hg8rF+/vtcgJhgMEgwm/wqzo0N9WAuHw4TDmR8Az1eJ50KeEyHODvKeFOLcMdLv1z217YblGdXufo+9eFwRZpNGNKYDEIrGWLuvgXfNrBzU8bXudtAj6LodBnrMllK0QDN01aLbRvW+TcSHFgmDZkKPmSF2hv+7ZylH8zdC50l0+9ih7y/Urh6fyT7kx9fc2W1YLnZaBv26u25WBd94YS+6elnQGYzw8p56lg3ydZGr5k6/YbnQYUGPRQnHon3cI9PYEodh+VhT14DPR8b7VStAi0Yg2oke9IFp8OGWEGJ4yb+PhTh3yPtViHOHvF+Tsn0OzpogRtd1PvOZz3D55ZczZ86cnvUrV67ktttuY/z48Rw9epSvfvWrXHPNNWzZsgW73U59fT02m42SkhLD/qqqqqivV0Ne6+vre4KbVJWVlT3bpHvooYf42te+lrH+xRdfxOVy9XKP89vq1avP9CkIIVLIe1KIc8dIvV/X7jWR2pXW6mvKaPeablyBmaOdWs/yD55/m+DR3Iezm/QQFdFtgEaDGdD6745r0f2URXehY6LRXAdaZrWFTe+gJLqPqOakeWSKMfpl1oOUR7cDGo3mRnRtcO2/EpyxJopiRwlpHtrMQ/tws+OQ8XfvbTzNCy+c6vsOA5jkNnM45XXxyN/fJtTL68IUC+EJnCBoKcJvKx/w956N7S0akPyF2/TwgK/jdB0Nxn3sOtaQ9T5S36/l0d2Y9QBt5g5CWnFO5yCEGHny72Mhzh3yfhXi3CHvV/D7/QNvxFkUxNx7773s2LGDdevWGda///3v77k+Z84cFi1axPjx43n++ee59dZb+9yfrutoWvIDYur1vrZJ9aUvfYnPfOYzPcsdHR3U1NSwfPlyioqG1h7inSQcDrN69WquvfZarNahfeEghBg6eU8Kce4Y6ffrN3e/BiSrfW+4bD7Xz+uj2iSuo+IUX312T8/yfq+JCQsuZdaoHP8tFGxCa7GAxY1eeVVWd9EaSiAaQC9dnJwbk8p/Aq3dDfZK9LKLcjufYaI1lUPYi148D1x9tFTLlncnmq8M3T0ZimYOaVfP/nYrNCVn/CyYNZXrr5486P21lZ3gwb/u61ne22HhqmVXGdrWacffwPzMp9A6TwOg2wrQK2ahV80mduE/QuWsQR3bt+UUHEi+JkeXe7j++iU57cNzuIXfH9nSs9wetbBy5fI+PxdAH+/XtlFogVr0wmlQOC23ByKEGDHy72Mhzh3yfhXi3CHv16REJ62BnBVBzH333cezzz7L2rVrGTu2/1YOo0aNYvz48Rw8eBCA6upqQqEQbW1thqqYxsZGLr300p5tGhoaMvbV1NREVVUvH+xRc2ns9sy+6Var9bx/cfVGnhchzi7ynhTi3DES79c2X4iGDuPg+7ljSwY87m2Lx/HwS4doSZkx8uiGk/zg/RfkdgLBIJgt4CiGbB+reyx0HYVIC1h7+/dhOL7Pouz3OdzcNdDhg3AzWAcfdACgB9Tjc5YN+fG1ByKG5fIi55BeczdeMJb/fH4f8a51BMIxXj/cxo3zRqvZNq9/D159SM3xidNCPrTat6D2Lcxv/xre878w/wM5H7sjaKy8KSmw5/xYJlcag0RfMEpnSKfMPXB7McP71VUBoQaI+c6e16AQok/y72Mhzh3yfhXi3CHvV7J+/Dn3Bzh27BiPPfYYX//61/nSl77E97//fV555RW6u7sHvnMaXde59957+fOf/8zLL7/MxIkDDzZtaWnh5MmTjBql/oLzwgsvxGq1Gsqg6urq2LVrV08Qc8kll+D1etm0aVPPNm+++SZer7dnGyGEEEKId6q99ca/0LFZTEwsH3jAvcNq5qOXTjCse277aU63B3I7gXCnurQUZn+fRBVMdwM9A0lSRePl32ZnbucynJzV6jLYDLFI/9v2R9chHP+dWYdeid2WEqQBlLqGNs+k3G3nsinlhnXPbjsNXY3w2HvglW8YQphMOvzl07Dv+ZyP3e43tmkrdub+oW+Ux4HFZKx+Od6aXTsBA1uxugy3535fIYQQQgghxHkl6yDmiSeeYMmSJUyaNInPfe5z/OUvf+H111/n5z//OStWrKCqqopPf/rTHD9+POuD33PPPTz++OM88cQTFBYWUl9fT319PYGA+nDf1dXFZz/7WTZs2MCxY8d49dVXuemmmygvL+c973kPAB6Ph4997GM88MADvPTSS2zdupUPf/jDzJ07l2XLlgEwc+ZMVqxYwd13383GjRvZuHEjd999NzfeeCPTp0/P5fkSQgghhDjn7K3rNCxPq3JjMWf3z8A7l4zHaU3O04jEdH657mhuJxDpUpdWd/b3sZeByQLRYO9fdEfjYZD5LJrdZy1Uj1GPqQBpsKJ+FeRoJrDk8Jz1odVvDGJKCob+F2s3zRttWD65fwvR/10KR1/Lbgd6FP7wD3B0bU7H9QbSHosr98diMZuoKTW+bk60DCKIsXpA09RrNJJjOCmEEEIIIYQ4r2T1CXzhwoV8//vf58Mf/jDHjh2jvr6eLVu2sG7dOvbs2UNHRwfPPPMMsViMRYsW8Yc//CGrg//0pz/F6/Vy1VVXMWrUqJ6fp556CgCz2czOnTt597vfzbRp0/joRz/KtGnT2LBhA4WFyb+o/MEPfsAtt9zC7bffzmWXXYbL5eK5557DbE5+afDb3/6WuXPnsnz5cpYvX868efN47LHHcnmuhBBCCCHOSXvrjBUxM6uzr7IoKbBx+yJja7DfbTqBN5DDAPlEEJNLqKCZwFGprgd6CTUi8S/OLWdREAPgiM/d6a4f/D5Sq2H6mVuSjUg0lvG7Ki0YWkUMwHVzqrFZ1EeJedphnrD8J+auOuNGmgmu+Tf41z3woT/BBR823h4Nwu8+CKe2kK02n/GxeAZZ3TMuLYg5PpggRjMlK5akKkYIIYQQQgjRj6xmxHz961/nhhtu6PN2u93OVVddxVVXXcV//dd/cfRodn8lqffWZiKF0+nk73//+4D7cTgc/OhHP+JHP/pRn9uUlpby+OOPZ3VeQgghhBDvJBlBzKjc2l19/IpJPLbxeM9MEF8oyhNvnuBTV2UxByUWVl+4Q+7VHY5q8J9WoYZnRnK9HoNovC3u2VQRA6o9WedBFR7FomAyD3yfdCGvusxDWzJvIJzR2W2orckAPE4r18+ppmHHah6xfg+3ltamuHA0vO8XMD7eBtgzBqa8SwVLW1P+GCrUBb99L3xiLRSPG/C47XmoiAEYX5YWxLT6BrUfrMXq9xVqB+eowe1DCCGEEEII8Y6XVUVMfyFMuvLychYvXjzoExJCCCGEEPkTicY42NBlWJdrEFNT6mLlXOOXzL964yjBSHTgO/fMh3GqVmO5cFSqL+7DnRBJ+aI80ZZMM4N56KFCXtmK1WPVoxBsGtw+eipiPEM+nba0tmQAxXkIYgA+Vb2fR63fyQxhxi6GT76eDGESNA1u+iHMerdxfaAN/vRxiA48VydjRswgg5j0iphBtSaD5JyYUPvg7i+EEEIIIYQ4L2Q9Iybh7bffZufOnT3LzzzzDLfccgtf/vKXCYUyP+gJIYQQQogz50izj1DUODh95qjCPrbu2yeWTjIsN3YGeXlv48B3HExbsgSTFWxl6nrqzJWztS1ZgqNaXQbq+t+uL5GU1mRD1JrWyqvQbulpKTYkm3/FtNc+hV0z7n9/wSL4yDNQUN77/UxmuPURmHyNcf3JN+HVhwY8bGYQM7hQaXxZgWH5eOsQg5hwOxmlR0IIIYQQQggRl/OnsE984hMcOHAAgCNHjvCBD3wAl8vFH/7wBz7/+c/n/QSFEEIIIcTgpbclG+VxDOrL63lji7loQqlh3V93ZBE09FTE5B7+AOCsUpepc2Ki8S/Nz7a2ZAnOlDkxsSyqhlLFwsnB79ZBPmcpWn1prbyGOh9G1+Hlb8Bf70fTjQHf89GLuK3jfjpivR9jb10Hj288zpG2MNz2ayiZYNzg9e/Bkdf6PXx6hU+xMz+tyZo6g/hDA1fkZLAUqsqsWMRYtSWEEEIIIYQQKXIOYg4cOMAFF1wAwB/+8AeWLl3KE088waOPPsqf/vSnfJ+fEEIIIYQYgj1DnA+T6j0LxxiWX9rXgC84wJfXiYoY6yAqYgAc8SAm1KJCCkgGFWdrRYytVJ1bLKLCmFwYWrkNLmRIlR5cDCmIiYbhmXth7XcybnoychX3hf+ZjrCJZ7edNtwWisT45gt7WfnD1/m3v+xixQ9f59Xj3fDeX6a1q9Phz/8EvpZeD98djhKMGMOfwVbEpLcmAzg+mPZkmga2eAu5cPugzkUIIYQQQgjxzpdzEKPrOrGY+gC0Zs0arr/+egBqampobm7O79kJIYQQQogh2VvXaVgeTFuyhBWzq7GYtJ7l7nCMNXsb+rkHQ2tNBmApUJUhug7d8VZoPRUxzsHtc7hpGrjGquv+k7ndNzEfxjL0tmSQWRFTOsiZKui6muOy7fGMm54v+TBfjNxNLP7R4qm3ko/5WLOP9/3vev5v7ZGedaFIjE89/jZbY5PgXf9u3FlXPfzlUxAzBi7Q+7ybkkE+HofVTFWR3bBuUEEMgLVYXcqcGCGEEEIIIUQfcg5iFi1axH/913/x2GOP8dprr3HDDTcAcPToUaqqqvJ+gkIIIYQQYvD2pVXEzKge/Bf8JQU2Lp9qnP3x3PZ+2pPFoinzXIbQZisxcyVRXXK2z4gBcNWoy+6mZAVPNsL5mw8DvQQxBfY+thzAGz+EPX8xrtNMcMP3cV33H0AyoNtZ6+XTv93CP/9uKzf8v9fZccqbsbtAOMo/PPoWh6bcBZPfZbzx4N9h3fcy7pM+H0bToNAx+Kqh8aXGOTEnWgfZWiwxJybUNuhzEUIIIYQQQryz5RzEPPzww7z99tvce++9fOUrX2HKlCkA/PGPf+TSSy/N+wkKIYQQQojBaekK0tgZNKwbSmsygJvmjTYsv3agEW/aF+Q9ovEvtk1WMA+hJVZiTkx3I+ixs39GDKiQyF6mrvtPZX+/SLyCKQ/zYQDaMoKYQQQXR1+Hl75mXGdxwPsfh8UfY+m0CqqLHIabX9hZz7PbT+ML9T0jp90f5s5fbqb+moehoNJ448vfgENrDKvSK2I8TivmlAqtXI1LmxMz6IoYW4m6DHtznwkkhBBCCCGEOC9kHcQcOHAAgHnz5rFz5068Xi//8R//0XP7d7/7XX7961/n/wyFEEIIIcSgHG4y/oW/3WJiYnlBH1tn59rZVdjMyX9ChqM6f9/TxxyUfM1ysRaD2a5mrgQaIRrMz36HW6IqJpf2ZPmuiBnqjJjOevjjP6oArIcGH/gtzFCV8WaTxu2Lxg64q0kVBSyZVGpYV+ft5s6njhK65WeqwqZHvBVa27GeNemBX7FzaDN0JqQFMSdaBxnEWFxgdqj2bTInRgghhBBCCNGLrIOYBQsWMHPmTL7whS+wYcOGjNsdDgdW69AHigohhBBCiPyo8xpbYo0pcQ6pggCgyGHlqukVhnV/3dFHe7JYPDAxOXq/PVuaBo54VYz/RHyflrwMsx9WzlGgmSHig2DrwNtHAips0kxqNk4eZFTE5DLcPhqGP9wFvkbj+qu/DFOWGVbdeckEKgv7bnt2+6Kx/PW+y/nlXYu5oKbYcNvBxi6e7ZiWOS8m0AZPfRjC6nXclh7E5PJYejGuzPgcD7oiBpJVMdn8noUQQgghhBDnHUu2G7a0tLB69WqeeeYZ3vOe96DrOjfeeCPvfve7Wb58OQ7HED9gCyGEEEKIvKr3dhuWR3ny8++1m+aP5sU9DT3LbxxqpqUrSJk77Yv4aPz45kHOJUnlqAbfCfAfV8HO2dyWLMFkAddo8J1UVTH20v63T1TDWNxp1SGDN6SKmFe+CSfS/gBryrVwxWczNq0otPPnT1/Kql31hrk0NrPGlZOcLKgIQsdmiAb41W1jee9jYY6kVGytP9TM+26/H2q3wN7nkjuu3wnPPwC3/IT2gPGxFLuGFsSNLzW+hmrbA4SjMazmQTz39lII1MmcGCGEEEIIIUSvsv6U4XA4uOmmm/j5z39OXV0dTz/9NBUVFXzxi1+krKyMd7/73fzyl7+ksbFx4J0JIYQQQohhV5cWxFQXOfOy33fNrMRpNfcsR2M6f9vVS3uyniAmDwGQvVxVl4S8EPGf/W3JEhLtyQKnB54f0tOWLD/zYQDafMYqktJsgxh/K2z4H+M6zzi49f/A1PtHiLElLj5+xSQ+v2KG+rmqlPtnH2WBfTt07IPuJgh3URLaxz/MM95345EWdIB3/wTKpxlv3PZb2P0X2tMqYkqGWBEzPq01WTSmc7o90MfWA7DFQ7ZQq2pRJoQQQgghhBApBvWndpqmcemll/Ktb32LPXv2sG3bNpYuXcqjjz5KTU0N//M//zPwToQQQgghxLAarooYl83Cu2Yah6s/t/105oaJ1mT5CGJMZnBUQCykvuw25ydUGna2UhUaxSLQ3UcLt4RIp7rM03yYYCRKVzBiWJd1eLHjqeQsHlDVPbf/GlwDVPUkhLzQshliYdVCzlkNxXOgeDZoZpZUdRo2P+3t5mRrABxF8P7HweY27u+v/0rEa3z+PEOcEVPsslHkMDYIGHR7MmuRCgpjYdWKTgghhBBCCCFS5KXnwdSpU3nggQdYu3Ytp0+fZvny5fnYrRBCCCGEGIK6jrSKmDwFMaDak6XadKyVxrTj9VTEDHVGTIJzlAp3Qu3nTkWMpiWrYnzH+9+2pyImP0FMegUJZFkRo+uw5VHjupk3w5iF2R04EoCWTaBHVXg2ajmULQb3RHBPgsqlTKnyUOY0Vo5sPNKirlRMhxu+b9xnoJV3n/w2kLzPUCtiAManz4lpHWQQo5nAVqyuh2ROjBBCCCGEEMIo6yDmz3/+Mx/5yEdYtWoVCxcu5E9/+lOv25WVlTF16tS8naAQQgghhBiceq+xzVK+KmIArpxWQaE9WU2g6/DSvrQWtfmcEQPgqIJoCKL+1O/jz34F49QX9cFWFSL1Ro9BpEtdz1MQkzqrBVQmlFUVyclN0LTPuO7Cu7I7aCyiQphot2qxVnph5rwbqxut8nIuHm+setl4tCW5MO92Ff6kmO/fyO3mV3uWhzojBmBcWnuyEy1DqGbpaU8mc2KEEEIIIYQQRlkHMT/5yU947rnnMJvNfOtb3+JrX/vacJ6XEEIIIYQYgnA0RmNn0LAunxUxDquZK6dXGNat2dOQXND1/LYmA9XiyhQPdSId+dnnSDA7wBmvIOo63Ps2kS71nJmseXu+2tKCmGKnFbNJG/iO6dUwpZNgwhUD30+PQetmVdljtkPZxerx9EYzsWT6BMOqNw83oSfmq2ga3PgDKDC2wPt3y2OM1VTgl48gZnypMYgZdGsyAFuJupSKGCGEEEIIIUSarIMYk8nE7Nmzufbaa1m+fDklJSXDeV5CCCGEEGIImjqDGTPDR3nyO1fl2llVhuV1h5rxh+IzSWKh5NByU54qYmJRsMarKPqqLDlbFU5Wl4E61borXZ7bkgG0+o1BTEk2bckC7bD7aeO6hR8BUxYfGzr2QXeTmpVSdjFY+n+9LZlUZliu9YY41ZAya6igHG7+f4Zt3Fo3D1l+DqgZL0M1vmwYgphwl6rcEkIIIYQQQoi4rIOY8vJyfvOb3/QsR6PRYTkhIYQQQggxdHVpbcnsFhMleaggSHXVtEpDhUUwEmPdwWa1kNqWTMuiCiMbUb/6slszQ7gzeYxzgbUI7OUqnOo6knl7TxBTmLdDplfElGYTXOz8gzEoMlnggg8NfL9APXTGq31KF4DNM+Bdpla6M2bWbNi13RiyTV8JC+40bHOFeReLtH15eT2nz4g50epPVuXkymxLCQqlPZkQQgghhBAiKesg5uc//zmTJk0CIBQK8YMf/GDYTkoIIYQQQgxNndcYUozyONDyFYjEeVxWLppQali3Zm+8PVlPEJO/dmhE/GCygT1eSRGoz9++R0KiKsZ/AmJh423hTnWZz4oYn/EYA1bE6Dps/pVx3YwbwF3Z+/YJER+0bVXX3ZPAOSqr89M0jSWTjK+fN0/FoHljMpgCuO6bxAqN+/y05VmKnfmviAmEozSltfTLSc+cGGlPJoQQQgghhEjKOohxuZIfUmw2G4sXLx6WExJCCCGEEENXnxbE5HM+TKplae3JXtrbSDSWMh/GlMfjRuOVGq6x6jJQl799jwRHpap4iUXAf9J42zC0Jmvz51gRU7sFGncb1y38aP/3iUWhZbN6TPZS8MzM6RwvnmhsT7bxtEmFVE0bkuGUo4iOhZ82bHeNeRslnftyOlZvqgod2CzGj0RHm32D36HMiRFCCCGEEEL0IusgJqG7u5vvfve7XH/99SxatIiFCxcafoQQQgghxJmXWRGT3/kwCctmGqslWnwhtp1sN7Ymy5dofH6HMx7EhFrOvVkcblVhTteR5AydWDj5fFny15qs1ZfjjJgtjxqXi8fBpKv7v493lwqRTDYovRC03D5eZMyJ6dA5GShUM4aaN6hqG6B20u206Mbnxr3phzkdqzcmk8akcmN7soONXYPfYU9FTDvoscHvRwghhBBCCPGOYsn1Dv/4j//I6tWred/73sdFF12U9xYXQgghhBBi6EaqImZ8WQHTqtwcaEh+eb1mbwMXXhwPAfLdmgzAUa5CmXAHdDdAQU3+jjHcXGPBu1fNYQmcBteYZDWMxaVmsuRJRkVMQT8zVWIx2Pe8cd3Cj4Kpn2DFd0L9AJQuHNTvOjEnJjU02tg+gZqi4+p5ad4AFZfTFrLwfGQln7f+vmc7bc8z0HwQyqfmfNxU06oK2Vff2bN8oKGzn60HYHWDyarCtbA3WSEjhBBCCCGEOK/l/Env+eef54UXXuCyyy4bjvMRQgghhBB5UOcNGJZHDVMQA7BsZpUxiNnTwBcWx9va5jOISVTEmJ1qDkm4A7rrz60gRjOBeyJ07IfOQ+AcPSxtyaCXipj+WpPVb4dAWjutubf1vX2oHdp3qutFM8BRMahzNJk0Lp5Yyt92Jef9bDzq5baFS6DpDVUR0/IW7b6JPB69lk9anqNIS7y2dVj3MNzyP4M6dsL06kLYnlzeXz+EIAZUVUx3A4TaJIgRQgghhBBCAINoTTZmzBgKC/PXMkEIIYQQQuRfRkVM0TAGMWlzYg42dnGsOR6amPLYmixREWNxgbNaXe9uVPNJhlssAtEhDHFP5Z6oKl8SQVJPRUx+/43d5kuviOkniDn8inG5dDKUjO9922gQWt5Srbec1VA4ZUjnmd6e7M2jLaqlXfnFqrok1E5by1E6KOCx6LXGO+94EtrT5u3kaFqV8Xk/0NCJnmgbNxj2eHuyYMsQzkoIIYQQQgjxTpJzEPO9732PL3zhCxw/fnw4zkcIIYQQQgxRNKbT0GkMDYZrRgzABWOLKXcbv+RfcyhetZCviphYRLV7AjC7VPWIpUCFAd0N+TlGOl2H7iZofRvqXoT61dB1dOj7NVmhYKK63nEAQsNUEePPYUbMkbQgZnIfs2H0GLRuUTNtrG4oWQBDbFWcHsScagtwstWvfr+li0DT8Ha2A/DLyEq69ZQWa7EIrP9/Qzr+tCq3YbnNH6apawihmz1eHRRsTs4BEkIIIYQQQpzXcg5iFi1aRHd3N5MmTaKwsJDS0lLDjxBCCCGEOLOau4JEY8YvgIdrRgyo9lLvmmGsillzJF6lkq8gJtGWzGRNzlFxjlaXgbr8HCNB11Xg0vASNG8Efy3oUbW+fZcKZmLRoR2jcHK8KsYL/vicFWv+KmICoSjdYeOw+NK+WpOF/HBio3HdpD6CGO9eVelhskDp4rzMtJla6abEZZxf8+bReJs0RzkUz6UtoMKeFjz8LnqNcQfbfgch36CPX1PiwmE1fiw6UN/Vx9ZZsBbF58REINw++P0IIYQQQggh3jFy/uT0wQ9+kNraWr75zW9SVVWFNsS/gBNCCCGEEPlVl9aWzGrWKOuvGiIPls2q4qnNyRZRm05DfRdU56s1WWpbsgTXaOg8qCpiYpH8DLoPeaF9h5qBAuoLddcYcI1VMz+8e1QwE+6EskWqamMwElUx3l1q4H3JPLC4B75fltKrYaCfipgT6yGasr1mholXZG4XbIGuI/GdLVAVMXmg5sSUsWp3ypyYIy2878KxaqFgPO3Ro4AKW34euZ6PWlZjIh40hTphz7NwwQcHffxpVYXsOOXtWXegoZPLp5YPan9oGtjLVUDY3SRzYoQQQgghhBC5BzHr169nw4YNzJ8/fzjORwghhBBCDFG9N2BYripyYDIN7x/PXD6lnAKbGV9IVYrEdI0/7Tdzz4y+j1vnDfD6/gYWjCtlavUAbbmiiVZnKUFMoj1ZxKfCGNeYwT+AiA+6joHvqKp8MVnVEPqCcaDFqyVsJWD1qNZc4Q5oXAdVV4N5kCGXe1K8zZdfzV3J4x84tXYZgxiLSaPI0cc//dPnw4xdBA6PcZ0eUwEVgHtCckZPniyZVJoRxKTyRgtIBDG1VHCyZAnj29YnN9j6+KCDGKDXIGZIHBUqiAk2AdOGti8hhBBCCCHEOS/n1mQzZswgEAgMvKEQQgghhDgjTrcbK2JGDWNbsgSnzcxN80cb1j21RycW631GRm17gGu/9yqf//NuVvzwdTYfGGD2Sm8VMZDSnux0biccCYB3n2o9dnoV1L+sqj10XVXaVF2lAgct7Z/L9jKoXKqqQWIh6DyQ23FTmW1qfwCh1sHvpxe9zYfps5I9PYjprS1Z1xEId4HZrgKqXOgxVRnSvguaNqh9xSKGTZZMzpwTc6rN37Pc5g8bbj9Wc7PxGMfXQeuR3M4rxfQqY1u4/UMNYhJzYkJtGY9VCCGEEEIIcf7JOYj51re+xQMPPMCrr75KS0sLHR0dhh8hhBBCCHFm1XekBzHOETnu+xfXGJZPeHU2pFU2JPxy3VG6Qqq1VFSH77+4G5o3qZZfvUnMiDGnBTGueBDT3ZjdF96xsGov1vByvK1Zk1qnmVTFS/nFUHph/7NtzA7wzFXXfcdUQDFYtmJ1bD0GgYbB7ydNm88YxPQ5H6azARp3G9dNTgtiIgHoiAdOnlmqWigbET+0bFZBV/NGNXcn2Aztu6F+jQrCokEAplUWZs6JOZIMp9rTgqWuypngTGv5te2J7M6rF9OqjUHMgfpOdL33EDErFpf60fW8h2xCCCGEEEKIc0/OQcyKFSvYsGED73rXu6isrKSkpISSkhKKi4spKZH+x0IIIYQQZ1r6jJiRqIgBuKCmOKOy4Mm3Tva67esHGg3LG2uhsaUBGl/rPZBIVMSY00KlRHsyPabak/Wn8zDUv6Qu9ZiqRimZpypcRq+EysvBUdn/PhIc5eCoUl+0d+zN7j69iQbUfiwu6Nw/+P2kafWlV8T0EZ4cedW4bCuEMRca13l3gR5Vz5drbHYnEPFD83rVnkuPqvCqYJwKciwFKvzqPKgCma5jPXNiUqW2J2tPq4jxmDth9i3GY257AmLR7M4vzbQq47wbXyhKbfsQuwDY4zNmupuGth8hhBBCCCHEOS/nGTGvvPLKwBsJIYQQQogzJn1GTPUIBTGapvH+xTX851/39Kz7+6562nwhw6D4em83Bxp9hvvGdI2/HS/go7O6oGMfOKuMO0/MiElvTQaqPVnnQdWerK85Mb4TqhIGVHjjmZl96NIXzywINkKgHrqbVTiTCz2mZtM4qlVVTMirQqj0xz4IbWkVJKUFfVTEHEn7t/3EK8CcEtoEGtTj0zQonpvdwSMBFcJEAqqFW8lCsKXMnHFPUqFZ5yHVuqt9J4RauXhisXFOzFEVxOi6TnvAGMQU24EpF8PmXyVXdtSqxzNlWXbnmaK6yEGhw0Jnd7Kq6kBDJ2NLenm9ZcteoV53webB70MIIYQQQgjxjpBzEHPllVcOx3kIIYQQQog8OVMVMQDvWTCGb/1tD6F4YUIoGuPprbX84+UTe7Z5/WDvFQLPHbbx0dlmCHeoKgJHfM5GLKx+ILM1Gaj2ZJ0Hk+3JTL38E7crPoOmcIqacdLXvJRcWN1QMB66joF3N9iX5rbfcKeqqLEUQEGNqtTpPJCXICajIqa31mS63v98GF1XjwvAPRmsxmqnXqWGMJYCKL8ks82bpoGzWv10HlYVRf5alhS3GTY72Rqgtj1AocNCNG3WkMepgdsNVbOhIaW12tbHBxXEaJrG9KpCNh9PnsP++i6umTGE30WiIibcoVqwme2D35cQQgghhBDinJZVa7ITJ07ktNPa2tpBnYwQQgghhBiaWEynIW1GTPUIzYgBNRR+xRRjEPLkWycM8zbS25IlbD7ezulovKKl63DyhkQ1jMkGJnPmHQdqTxZsVV+Ga2YVxOQjhEkonK5mpoQ7wH8qt/uG4/MVrYUq6NDMEGpXgdIQZVUR07QPuuqN6yZfk7webFEVOyYrFE4d+KDRbmjeoNqSWQqg4tL+Z+0AFE6GcrXddI+f4rTN3zzSwo6T3oy7lZTEXyfTlhpv2Pc8+Ac3kyVjTkxDH/OKsmW2JSuBpCpGCCGEEEKI81pWQczixYu5++672bRpU5/beL1eHnnkEebMmcOf//znvJ2gEEIIIYTIXosvRDhqrB4YyYoYgA/MNi4faOhi68l2QAVF6w71PTPj+SMOFZR0N6lWXZCcD9NbW7IE52h1GTideZvvmLp0jcl+0Hy2zLZkSNGxT4VB2YrEv+i3FqlqCfeE+H6GPismq4qY9GoYTw2UTU4u++PzfZyje68yShULQ/ObKrixuLILYRLspVC5FJOzgotHG1+76w+38J2/7zOsqyl1UlA2Xb1Oxs9Xv4OEaAh2/jG746ZJn2+0v36IQQwkq2KCMidGCCGEEEKI81lWQczevXvxeDysWLGCqqoqbrjhBu6++27uu+8+PvzhD7Nw4UIqKyt59NFH+e53v8t999033OcthBBCCCF6UZ/Wlsxs0ih3j2BLJF1nyegw44qMX6j/7k1VYb37dAet/r4Hqj+3qykZqiSqYqJZBDGu+H0S7ckSokE1MB6gYEK2jyI37olgcaqKEN/x7O/XUxFTFN9P/qpi2nzGmSq9VsQcftm4POmqZLVQLJLyvNX0fzA9Bi2b1eMx23tvRzYQsx3KLmbJFGMrsL9srWXHKWNFzD8tnYxmdYGjChxumHyFcV9v/1q1VcvRtLQg5lBTV0ZLtJzZ4+31pCJGCCGEEEKI81pWQUxpaSn//d//zenTp/npT3/KtGnTaG5u5uDBgwB86EMfYsuWLbzxxhusXLlyWE9YCCGEEEL0rc4bMCxXFdoxm/LYimsgsRAmdN4/y/gF9tNbaznW7GPtAWMrLJvZ+M/RHae8HAvF204FTqtZI4mKmN7mwyT01Z7Md0Kts5UYB8bnk2ZKVsV0HoRY30GTQWprMlBhRMF4db3jwJBOqTWtNVlJehATCcLxN4zrJqfMhwnUgR5Vz6mtpO8D6Tq0bVVBg8kCZRf3H5j1R9NYMnO68TTTgpBJ5QV8YHE8GEoEa1MuNu6nYRfUvp3z4adVuQ3LoUiM4y2+nPdjYCtVr49IQFULCSGEEEIIIc5LA/QYMHI4HNx6663ceuutw3U+QgghhBBiCOoz5sOMbFsyour4t82x8cO3YoSiqlVXJKbz3Rf30+LtMGx+26KxrNpVT0tKK63n93Zyz9wK1Z6s60hyRox5gFk3ztEqCAmcVm3IdB388QqVRNuv4eKqUceOBNQx3ZP63z4aUtU6AJaUSozCKaqVWqhNPX5HRc6nous6bWmtyUrTW5Od3ARhf8oKDSZelVxMtCVzDVAN490N/tMqbChdPOSwa3pVIcUuK+3+cK+3f2HlDKyJ8M5erkKfUTPAMwa8KXMq334Uxl6Y07HL3HbK3Taau5LP3YGGTiZVuPu51wBMZhXGBJtVlZN74uD3JYQQQgghhDhnZVURI4QQQgghzg11aa3JRnkGCC/yLabChcoiJx+9dLzhpud31PHWCWNVwNXTK1k5t9qw7rntp1WbLlCtvhKVIwNVWqS3J+tuUMGIyZZsdzZcNBMUTlPXOw8NXBWT+phS56+Y7clKj87BVcV0BiMZlSQlBWmzcY6kzYcZNQ8KytT1iB+CLeq6a2w/BzoEXUfjB7gAHOWDOt9UJpPGRRNKe71t0Rgry2ekHEPTVAWRZoLp1xg33vkn6DaGftlIb0+2v74r531kcMbbrfU2v0gIIYQQQghxXpAgRgghhBDiHaSu3dia7ExVxGBycO/VU/E4jQFANCUfsJg0lkwu46Z5xpBkX30nB7wO1W5Mj0LXMXVDf63JQG1vdSfbk/ni9ysYp76sH26usSpYiQaTx+5LJG0+TKrCyep8g62qKiZH6dUw0MuMmMNpQcyklLZk/lPq0l6uZt/0xn8KvHvV9eLZqgIpT5ZMKut1/ZeWBNFaNqrfb4Ir/rudfJGar5MQ9sGuP+Z87PQg5kBDZ877yOAYpS6Drcn3hxBCCCGEEOK8IkGMEEIIIcQ7SGZFzBkKYsx2PC4r9149pc9NLxxfgttuYfGEUqqK7IbbVu9pUG2cYhHorgP0gVuTQfJL764jyRCjYHzf2+dTRlVMpO9tw/Ev+HsLYsyO5DkPoiqmNS2IsVtMOK0pIYW/FU5vNd5pckpFSaItWUEfbcm6m6Btm7peOHngNmw56i2IuX5WKReOsaqWbR37kzeYbeAcBQUlMOlS4522PJrzsadXp1XE5COIsTjBHq/yCdQNfX9CCCGEEEKIc44EMUIIIYQQ7yDpM2JGvDVZTxCjAqCPXDqesSW9n8PSaWr+icmksWxmleG2Aw2d4BwDxFSFSbRbzdsYSKI9WedhVU1jLx388PjBcI1VA+5joWTbrt70tCYr7P32wikpVTHNOZ1Cmz9tPkyBDU3TkiuOvgakliY5YdwSdT3YqlqTmSzJUCtVqB1a3lLzd1xjoGhmTueWjRnVhdSUJl8zFpPG566fp9qfgQq5Up+TRGg1NS2IqdueGTgNIL0i5mizj2BkgDZz2XDGn0tpTyaEEEIIIcR5SYIYIYQQQoh3CF3XMypiRrw1WXxGTCKIsVvMfO666b1uesXU5LyP9C/AjzT54oPO49URYW92x0+0Jwt3qNDAVpLT6Q+ZpkFRvCqm61Dvrah0vf+KGEiritnf+zZ9aPUZB92XuAZoSzb+UrDEK5IS1TDO0ZnBVzQILZtUwOWoUMFIasCTJyaTxn+/bz5TK92ML3Px4zsWMrG8AJzVyeekbSvE4o/TXqZ+56NnQ2FaeLTl1zkde1qV27AcjekcbMjHnJh4QCjtyYQQQgghhDgvDSqIeeyxx7jssssYPXo0x48fB+Dhhx/mmWeeyevJCSGEEEKI7LX7w4QiMcO6MzcjJtlq7KZ5o5kzxhg4lLiszB7t6VmeVFFguP1IUxe6ridbOkV8EDHOv+mTczREfRBqHfkgBlQlj61YtSbz7sm8PepXYYZmUtUzfRlkVUz6jBjDfBhdhyNpQczkq5O3JVpnucb2suPtKoyxFkLpomGdu3PxpDJWf+ZKXvvc1ayYU528wTNbPWfRbnU+CQUTwGSCGVcbd7TzDxDMPkgpdFgZV2qsoNp9OssQsD9mR0p7MqmKEUIIIYQQ4nyT86enn/70p3zmM5/h+uuvp729nWhUleoXFxfz8MMP5/v8hBBCCCFEltJbUgGUpQ9pH25prclAVTh85fpZpNZOvPuCMZhNyTWTKoyVCL5QlMbOoKq4sBapYMd3PLtzsFeq0CbUDmb3gJvnnaZB8Tx16a9NzqpJSLQlsxb2X1FidkDBOHU9h1kxrWmvg5LU10DrEWg/YbzDpHh4EWpTVSYmK9hKjdv4TkJ3gwpfSheq1mVngskMpReq5y1QB774Y3GNBc0MUy42BkShLtjxZE6HmDvGY1jeVdsx1LNWElUxfglihBBCCCGEON/kHMT86Ec/4pFHHuErX/kKZnOyXcGiRYvYuXNnXk9OCCGEEEJkr6PbOBzebjHhsGYxVyVfdD2jNVnCJZNK+PGKGFfU6Nx1SQ0PLJ9muH1UkQOH1fhP08NNXSpQsVeAyQb+E6AbK356pQFmuwoLInmoZhgMm0dVaQC07zSe90BtyVIVTo1XxbSoypgsZFTEuKzJhfRqmIJKqJqtrnc3qEtHpTEgivjBu0tdL5qe3XkPJ5sHimao6949yfDINRoKymDCEuP2rzwEgbasdz87rXprZ22eXkOJOTGhtuyru4QQQgghhBDvCDkHMUePHmXBggUZ6+12Oz6fLy8nJYQQQgghcucNGGeDFDmtfWw5TGIhFcaAoTUZABE/N0yBx24x8eC751HoMJ6byaQxsdxYvXKkyafaeNlLVPVINAiB+oHPI9SmKjrMBWe2+qBougqEIj41YD4hMe8mm0DD7Ei2Ces6nNVhW339VMSkz4eZfHUydOkJYlJagek6tG1TbdbspeCenNU5DDv3ZPWaiIWhM/68JIKvmVcZt/U3w0tfz3rXc0YbK2L21nUQiWYRAA7E7FDzbEDakwkhhBBCCHGeyTmImThxItu2bctY/7e//Y1Zs2bl45yEEEIIIcQgpAcxnhEPYhLVMPbMlltRv7q0GOdvpMqcE+NT1RiYwD1FrcymPVmoXQUxVjcEmyCa2bJtRJisaqYJQOdBFchAsiLGkmVlSSL8CNQn99GP9CCmZ0ZMNAJHXzdunGhLFvGr89I0cFQkb/cdVdU4mhlKLui/ldpI0rRkVUzXEdUSz1asqmVGz4Kp1xi33/xLqH07q13PHm38vQQjMY405+kPzhLtySSIEUIIIYQQ4ryScxDzuc99jnvuuYennnoKXdfZtGkT3/jGN/jyl7/M5z73ueE4RyGEEEIIkYWOMx3ERONBTHo1DCQDhH6G008uTw9iOtRQe1DVJZoGweZkkNGXULsKfBzVqiXYmfzS2zVGBRt6TFWWRMPJ5yLbFl9Wt2oXBip0GEDGjBhXPIg5/TYE09psTbpKXSaqYWylKkACVW3i3aeuF8/u93d3RjirwVaiXiOdB9W6RFXMRR8Aa2rop8PzD0AsOuBuy9x2RnuMrfV2nx7gNZf1OY9Sr+NQezxkFEIIIYQQQpwPcg5i/uEf/oH/+I//4POf/zx+v5877riD//3f/+WHP/whH/jAB4bjHIUQQgghRBYyWpM5RnigerRbXZp7C2LiXzqb+6uI6aU1GaiWTtYCcFSpZd+xvs8hlhJ0eOIVE/5TA5z4MCueq+bVBFuhdYtaZ3aA2db//VIlqmJ8Jwes8EmfEVOWqIg59JJxw4qZUBSfW5IIYpwpbcn8J1XIYS2EgvHZn+tI8sxUl77j6vfuHK2ea6cLLr3HuO3pt+HtX2e129ljjO3Jdtd15ONs1XvDXq6u9/c6FkIIIYQQQryj5BzEANx9990cP36cxsZG6uvrOXnyJB/72MfyfW5CCCGEECIHZ7wiJja0ipj01mSn2rsJRkm2MyuYqC59J1Xg0ptQe/I4BePj1QdtWbX0GjaWAiier657d6lzzHXgvaNctd3So/22Z4vGdNrTXgclBTY162XHU8aNJ8fbksUiqv0YJMMuXYeuY+p6osrkbGQvi1cc6dCxX4UwiZk6c5ZB+TTj9msehAMvDrjb9Dkxu0/nKYiBlNfxcfXcCyGEEEIIId7xBhXEJJSXl1NZWZmvcxFCCCGEEEPQ0X2WtCYzO3q5LTEjpu8gZmJaa7KYDsfbAbNTrXCUqwBDj4LvRO87CbWpS1txfDh6vPrgTFfFuEaDe4KqDOo60ntYNZCeqpijqtVZL7yBMLpuXFdaYIMTG6DtqPGGOe9Vl8EmtT9LQfL3E2xW4VVqsHG2KopXxfhrIdyRrN4JNcOKh4zbdnvhidvgiQ9Aa99t3uaMMQZle+s6iel9bJwrR6VqNxeLZDfzSAghhBBCCHHOy7lfxYIFC9B6GdKpaRoOh4MpU6Zw1113cfXVV+flBIUQQgghRHYyWpOdqYqY9NZkup5SEdN3a7JCh5XKQjuNncGedUfaYdqElPu4J0LbdhVGuCdlDo9PVMTYStSlqwa6m1QQUzQ998eUT57Z0PAa6BHVlqpkfub598c5SoVL0W4VOhTUZGzS6stsW1bsssLLvzWuLJ8OYy5U1xNtyRLVMABd8dDGVaPCmLOZzaOCLv9pNdOm/CKwl6pWcJU1KnDa9SfjfQ78DQ6/DKPmq/ZshaOgbArMvhUKypib1prMF4rS3J2n89U0Faq1bVehnHsiaEP6+zghhBBCCCHEWS7nf/GvWLGCI0eOUFBQwNVXX81VV12F2+3m8OHDLF68mLq6OpYtW8YzzzwzHOcrhBBCCCH6kB7EjHxFTPyb6vRqj1hQVVxoWrK6pQ/p7ckOt2EMb5xjwGSDSCAZIKQKt6tLW7G6dFSDZlaVKMHWrB/K8NDUDBPNDLEQePfkeHeTCp8Aug73ukmb3xjEuO0W7NEA7H7auOEFd6jfh65DIC2IifiTz+3Z3JYsVdEM9Xi6G9TvOfE8dR6CFd+A8Zdn3icahFObYM8z8Ob/wgufhR9fCDv/SGWhnYpC4+v4pC+H0GwgrrHJUC1wOn/7FUIIIYQQQpyVcg5impubeeCBB3j99df53ve+x/e//33Wrl3LZz/7WXw+Hy+++CL/9m//xte//vXhOF8hhBBCCNGHs6YiJj2IicTbkpmdA/7l/6QKt2H5SLtmbGdmMidbT3WltZaKBNSX65oGVk9ye2d8IP2Zbk8W9YPJqqohzA51/rm2pioYpypUwp3Q3Zhxc3pFTEmBFfY+C+GUGTmaCeZ/QF0Pt6tQyGRVVSSQHCLvqFAttM4FlgJwjVPXO/aq37mjQgWAgWPw0efglp9CQUX/+wm0wZ8+Bk99mEurjPNbTnXlMYjRTKoSBqCz91BNCCGEEEII8c6RcxDz+9//ng9+8IMZ6z/wgQ/w+9//HoAPfvCD7N+/f+hnJ4QQQgghstYRMH5xfNbMiOlpS9b3fJiESWlzYo609XI/9wQVtgRb1EyQhMR8GGuRMfBJzDgJnO5ztsqISJyre3xyrkn7TtU6LVsmazJwSA+igLa0IKbUZYOtaW3JpiyDwmp1vacapkI9Z7GU+TuJofLniqJp6jEEW1VIVTxPVR8FmyFQq6qA7tsCSz6t1vdn31/5Vv3dXGba2bPqpK+f7QejYHw8VOvoNVQTQgghhBBCvHPkHMQ4HA7Wr1+fsX79+vU4HOpDdywWw24fxABSIYQQQggxaBkVMY4RDGL0GMTix0+fEZMIYsx9z4dJmNxLRYyu2YwbmR3JKpfUMKKnLVmJcXt7ubpPLNx7O7NsxKLQcRqaDkDtFji6Fry1ue0jEcRYi6BoqgqIdB1aN6sKl2wlZuN0NxmDKKA1rTXZNFsLHF9nvP8FH0peT7TFciSCmVr1PFlcaqj8ucTsSFaZePeqCqzEXCDvboiGwOGBFQ/BZ/bC+38L1/83XP4ZmPyujN05Ix38zPoDqlAt7U75NHRdz9/5poZqUhUjhBBCCCHEO1rOkzfvu+8+PvnJT7JlyxYWL16Mpmls2rSJn//853z5y18G4O9//zsLFizI+8kKIYQQQojexWI6Hd1ncEZMohpGM6kvmA23xVuTWQYOYtJnxHiD0OoPU+ZOC3fck9Rwdn8tFM0Csw1C7eo2a7FxW00D1xj1ZbfvRDLEydaBF+EvnwR/S+Zt06+Hm38EBeUD7yc1iAEoma+em2ArtGyCisszQ6zeWJxq1oy/Vj2m0uS/u9MrYpaFXjLe11kC01eq66E2FZJp5uR8mESrtIIJ6nk717inqMcQ7lAhk3uiakkX7lBhTOK5KqyCmTca77v7aXj+s+BvTu5O6+bL1if4l/C9BKIap9oDTKpMCwaHdL6TwHc0XrXTAM6q/O1bCCGEEEIIcdbIuSLm3/7t33jkkUfYtGkT//zP/8x9993Hpk2beOSRR/jKV74CwCc/+Umee+65vJ+sEEIIIYToXVcoQvof63tcIxjExLrVZW9BQg6tycaWuLCZjf9EPdLcS08oWwnYilUlju+4qixJBDG24sztE3Nluhszqkj6dfhleOpDvYcwAPtfgJ9eBkdeHXhfPUFMfH6NZoLSxep5ifih5a3sW6clhtEHatXA97hWXzKM04hxccffjfebextY4r8j30l16RylWmRF/Oo51LRkO7dzjdmmwhiAjn3qsmS+uvSfgvbdhufLYPZ74J43Veu2FO82r2eJaQ8Au0/nULmUDYsz2QKubWvf5yaEEEIIIYQ4p+UUxEQiEb72ta+xdOlSNmzYQGtrK62trWzYsIE77rijZzun09nTpkwIIYQQQgw/rz+csa7IkXPx8+AlKmJMvQUxiYqYgYMYs0ljfJmxcuZIU1fvGyfaUPmOqdZeelRVd1h6GTBvKQDXaHW989CA5wHA8Q3w5IdUS6v+dNXDb26BNQ9CNPP3AKh2X4nnIVERAyo4KLtIVRGF2qBtW3bnZisGe5kKoLqO9qxuS2lNttK0ieJQvfF+F8T/za7Hkm3JXDXqMrFsK8uuMuds5Z6ozj/iV8+NrRgK4+FM1xGofwnatqvnu7s5WVnUdQwcRfCe/wNHsWGXD1p+jYUIe07nEOJlyzMTbB71GmndQkaiKoQQQgghhDjn5RTEWCwWvvvd7xKNRofrfIQQQgghxCCkz4cxmzTc9hEMYmLxIMac9sc4sTDE4uFAFjNiILM92ZGmPqakO0erL9yj3dAVn7FhLey7pVbhVHUZOJ2s0unL6W3wxO0Q9mfeZrarAMVAh3U/gF9eB61HM++TmAFjcWa2brO6oXSROm9/LXTs7//cEtyT1aXvOMQiALTGW5NN0U7xHev/GbevnA2jLlDXuxvU78bsUIEOpAQzo7M7/tnKZEnOhunYq6qgPDNV4GUvjVdRnYDGddC8AVrfBu8eaN8J9ashdBKu/KxhlzNMJ/mIeTW764YhiNFMUHqhOu9ga/a/fyGEEEIIIcQ5I+fWZMuWLePVV1/Ny8EfeughFi9eTGFhIZWVldxyyy3s32/84KHrOg8++CCjR4/G6XRy1VVXsXv3bsM2wWCQ++67j/LycgoKCrj55ps5deqUYZu2tjbuvPNOPB4PHo+HO++8k/b29rw8DiGEEEKIM60jLYgpcljQRnLGR18VMYkqEJNNfdGchUkVxoqWw30FMZpJzTKBZBuq3qphEqxFahaKrvdfFdN0AB57DwTTvnSf8174t0b4aiP86+5eB7xTuwX+9wrY8Qfj+kRbMktR5n0AHOVQPC/+WA6oQGYgjkoV4sTC4D8BqIqYIrp4xPo93Fpam6tL7kmGVP74v5VdY9W6iB9CXnXdUT3wsc92BeOhoEb9rlu3qOffWQUVl6kfR5V6TVrdYC9XM4RsnnhIcxLGjIPyyYZd3m/5I3W1x9GHo2LFUgDF8RZqnQehuyn/xxBCCCGEEEKcMTkHMStXruRLX/oSn/3sZ/nd737Hs88+a/jJxWuvvcY999zDxo0bWb16NZFIhOXLl+PzJT9sf+c73+H73/8+P/7xj3nrrbeorq7m2muvpbMz2Z/5/vvv5+mnn+bJJ59k3bp1dHV1ceONNxoqd+644w62bdvGqlWrWLVqFdu2bePOO+/M9eELIYQQQpyVOrqNQYzHOYLzYSA52yK9pVU0+7ZkCZPK0ypimvtoTQbqC3fNpAadR7pURUx/iuJVMf6TEAlk3h7shCfvgECrcf20lfCenyXnq7gr4UN/hOXfyKxwCXXCnz8Of7obTm9VYUDYq26z9hHEABSMA9c46GiAA3+CE+ugYbcKhjobMltWaVpyVkzXEYhFafd182Prj5hoajBuO+8DybZk0ZCqiIHkLJh3SluyVMXzVLVPLAItm5KvUXsplF8Eo6+Dqquh4hIoXQiVS6HychXKmC1wyYcMuyvSAnwi/DjNXQO0qhss1+jkLKPWt1XbNCGEEEIIIcQ7Qs79Kj71qU8B8P3vfz/jNk3TcmpbtmrVKsPyr371KyorK9myZQtLly5F13UefvhhvvKVr3DrrbcC8Otf/5qqqiqeeOIJPvGJT+D1evnFL37BY489xrJlarDm448/Tk1NDWvWrOG6665j7969rFq1io0bN3LxxRcD8Mgjj3DJJZewf/9+pk+fnuvTIIQQQghxVklvTVY00kFMrK+KmPgf2Fiya0sGMKnU+E/UEy1+wtEYVnMvf0NktqsWZW07VLjQX0UMgK1EfTkfbFHtzIrnJG/TdXjmXmg5aLzPxKVw26NgTntOTSa49F6YcBn88WPQeth4+87fq5/SSTBhERRXgqcdXPFqlI5aaD+hfrwn1WXHaaCPigt3FYy5EMYshFELoHImuMeA5SAEO4nseIxvRn/LUvNO4/1GL4CbHk5WwwRq1WO1eZLB1TulLVkqzQRli6FpHYS7VBhTPF+FYanVYroOkU4V2Fg9KpTxnwY9RmzqFZgOvt6z6S2mdWw9sp+K+fOG55w9s1VoF2qHlo1QNBMKJw94NyGEEEIIIcTZLecgJhaLDcd5AOD1qr8ULC0tBeDo0aPU19ezfPnynm3sdjtXXnkl69ev5xOf+ARbtmwhHA4bthk9ejRz5sxh/fr1XHfddWzYsAGPx9MTwgAsWbIEj8fD+vXrew1igsEgwWCwZ7mjQ7WTCIfDhMN9DGE9DyWeC3lOhDg7yHtSiHNHvt+vrV1Bw3Kh3TKi/y3QQj6IRtB1M6Qet7sdLRpBx2Zc349xhcbtIjGdo40dTCzvo6rGPhZT2AfhLmJRBj6OcwKavwE6DqM7JvRUgJg2/Qzznr8YNtWr5xF5328Ac9/7rZgDH3sJ89+/jGnHE5m3tx5RP0PV1QD7X1A/ifOzF6GXjENrOYQl3M0NZuNdoq4KYu/9NWDpOX+t45j6Xdmq1bqIDy3QAmjolvKsf0/njKIFaM1vQKAFAi+DZgFbKbrFhRbuUMGHHv9jMs0EVg+6rQQNB1z4PoIHN+FEvb8sWgzL278iPOs7w3e+xYuhfQdaoBZad6AHmsEzL+vWfkIII/n3sRDnDnm/CnHukPdrUrbPwVnzr3ld1/nMZz7D5Zdfzpw56i8T6+vrAaiqqjJsW1VVxfHjx3u2sdlslJSUZGyTuH99fT2VlZUZx6ysrOzZJt1DDz3E1772tYz1L774Ii5X9n/Reb5YvXr1mT4FIUQKeU8Kce7I1/t16wkTqV1n/e1NvPDCC33fIc/Ko9sx60FazX7CWrIqpSS6D5vegdfUQrfpcD97SHLGGii0VNIZSVag/GHVWuaU9l4pYtaDTAyfxKx3U3v0T3SZxw54jNLoXqy6j27tMF7TJEp9B7ns4EOGbULmAl4r/Sj+NWuzOm/MKxgz3sP8k49ijfXS9mwYaMEOtPpdvd4W0s2sH/0JvOu2AdvUKeoByqM7AY0mc5SYtpeCWB3u2ElCWhFt5hGcKzSCLLofd+wUNr0TjcwKfh0LumbCpCfbjml6FJMWwWtZzLLIup71U078nlV/vZSYyTas5+yMNVEUOwFsJqKtoc00nZg2wpVuQryDyL+PhTh3yPtViHOHvF/B7/dntd2gghifz8drr73GiRMnCIWMPZL/+Z//eTC75N5772XHjh2sW7cu47b0QbO6rg84fDZ9m962728/X/rSl/jMZz7Ts9zR0UFNTQ3Lly+nqKif3t7nmXA4zOrVq7n22muxWuWDoRBnmrwnhTh35Pv9uum5vVB7smd52sRxXH/9rCHvN1taHaDH0CuvMbQh0xrsEA2gl18KttLsdubdzbTjJ9mS8vcyJRNmcP3lE3vfvrsBrb4LAqeZUjIBvWoZRLrRDr8MYT/Y3GB3g60QvWwK2AsheDFay0Y1nL2lHvMrP8/4gt703ke4aury3o/Zp+uh41NEt/wC056/oLUfz/H+im62gx5Fi0UGdf9u3cp/ap/ga++/33hD21a0gB0cVeiliwHQml6HcBW6Z25yRsk7la5DpEO1posGVJsyWwmYC1S7sogfQq2qGiXYBCEvfwiOgwPJzyiFehcra/zo828Z/vMNtaK1blGt/ywF6KUX59TmTwgh/z4W4lwi71chzh3yfk1KdNIaSM5BzNatW7n++uvx+/34fD5KS0tpbm7G5XJRWVk5qCDmvvvu49lnn2Xt2rWMHZv8C8bq6mpAVbSMGjWqZ31jY2NPlUx1dTWhUIi2tjZDVUxjYyOXXnppzzYNDWkDS4GmpqaMapsEu92O3Z45qNRqtZ73L67eyPMixNlF3pNCnDvy9X7tDBpDhJIC+8j9dyAWVvNSMKnAwxTvj6XHQIuowecOT+aMlT6FmFqqGYKYo82Bvh9PdxCc5aB3gxaD1p3wx09B84HMbTUzjLsEpi0Hpxs2/gQaD2Vud8Vnscy6IcvzTVM2Hpb/J1z7NTi9Fd7+OZzYCNEI6BpEw2oeibsSisdD8Tj146npua45i9W+2rZB5zHwe6HbAnU7oPZtaNwDoa6MQ2+NTWF1dCHPxS7BUjbJ+Jx1HIBQA1isUDwDrFY1wyfmU+sKx+XwOzqH2crBVd77bVYPOD1QNB6a3wSzheqqGGv3zjXM3jFv/jnahR8xzpoZDtYqsF8JzRtVSNS+CcqXJGf7CCGyJv8+FuLcIe9XIc4d8n4l68efcxDzr//6r9x000389Kc/pbi4mI0bN2K1Wvnwhz/Mv/zLv+S0L13Xue+++3j66ad59dVXmTjR+FeOEydOpLq6mtWrV7NgwQIAQqEQr732Gt/+9rcBuPDCC7FaraxevZrbb78dgLq6Onbt2sV3vqN6N19yySV4vV42bdrERRddBMCbb76J1+vtCWuEEEIIIc5lHd3GvrQe5wj+Yzgan09jsiRDGFAVB7quwg+zI4f9+ZhSogPJL7kPNmaGDj0inWrbwqnQUQcvfAG8tb1vq0fh+Dr105eJV8LVX87+fPuiaTBmIdg/AgtWQsl8KBiX2z48c9XgdpMZKkbBBR9S63UdvKegaR+0HAZnMV/cWsaT+5LV6ssrUion/LXQsV9dL54H9nh1UqBOXdrLwTy8rbbOKZoJyhZB0zqmV4f4anS5IYjR6neocG38JcN/LpYCqLhMhTHhTmh6Q4UxtuLhP7YQQgghhBAiL0wDb2K0bds2HnjgAcxmM2azmWAwSE1NDd/5znf48pdz+8B6zz338Pjjj/PEE09QWFhIfX099fX1BAKqp7amadx///1885vf5Omnn2bXrl3cdddduFwu7rjjDgA8Hg8f+9jHeOCBB3jppZfYunUrH/7wh5k7dy7Lli0DYObMmaxYsYK7776bjRs3snHjRu6++25uvPFGpk+fnutTIIQQQghx1vEGjEFMkXMERwHGEkFMWjVxJD4nxeLMfl+6DhE/U9K6mB1u7ELXe58RQzge0phK4IWH+g5hslE+EZZ9BgKnk+c/VKF2dWn15H5fkxlKFqhQJ1CnAhVQy8U1MPVaWPJJgrNv47kjxqqoZaOboeMgdDepyhqAwsnGMMgfb2fnHJ37ub3TmaxQdhGjigt4yzyP47G0mZObfjZy52J2qDDGVqIq0Fo3q4ozIYQQQgghxDkh5yDGarX2zFWpqqrixIkTgApEEtez9dOf/hSv18tVV13FqFGjen6eeuqpnm0+//nPc//99/PpT3+aRYsWUVtby4svvkhhYbIc/wc/+AG33HILt99+O5dddhkul4vnnnsOszn5F5m//e1vmTt3LsuXL2f58uXMmzePxx57LNeHL4QQQghxVkoPYs5IRUx61UusO74+hyAmGgA9xpRS4z9TO4MRGjuDvd8n0gn+dvj9J8B72nibs1S1/3KVqcqcvnjGwBV3w03/AXqnCi7q10DDK9C+W4UZg/niO+JTX5xrpsG3k7J5oHCaut6+E6LdGZtsPNKKL5QMYjTg6vFR6NinKin0GDiroWhm8k7BVhViaWZwjsrYpwAsBWjlFzGlVOM30WuNt+15dmihX65MVlUJY3aokLDryMgdWwghhBBCCDEkOf+p5IIFC9i8eTPTpk3j6quv5t///d9pbm7mscceY+7cuTntq8+/akyhaRoPPvggDz74YJ/bOBwOfvSjH/GjH/2oz21KS0t5/PHHczo/IYQQQohzRceZDGJ6Ape0iphEYJBeKdOfiA+A0SVOnNYQgXAyXDjU2EVVUVrYE+2GSAhe/B60HDXeVjoJ7noBiuIhQ8gHR9fCgb/DwRehoxbKpsDln4F5t6sqk1AbBJvVMPdwuwoqwl3qS2+zHcoWq6qEbIW86tJapMKYwSqcAt31an9tO6D8IsPNa/YY5yEuGFdMxdgJ0LFXfWlv80DJQuNME3/8j6hco9WX/KJ39lKmVhXxh4areMDyR1xaPBDUo7D5F/Cufx+5czFZwDMTWrdC50FwjZOWckIIIYQQQpwDcv40+M1vfpNRo9SH2a9//euUlZXxqU99isbGRv7v//4v7ycohBBCCCH6p+s6HYGIYd2ZmRHTRxCTy3yYeBBjsriZXFlguOlgQ2fm9uFOOLQOmtNCmKIqeO8PkiEMgK0Apq+Emx6Gf90NXzwB926GBR9SQ+pNFnBUqC+6Ky+HUdepOSEF41QIEw1C0wYV0mQr3B4/dnH29+mNZoKSC9RldwP4TvbcpOs6a/Yag5hls6rANQaqroHyi6H8UuP8nlgY/PHqoYLxQzu388C0MaPpoIA/Ry833rDl1xDpo1JruDjHqGAvFoHOAyN7bCGEEEIIIcSg5BzELFq0iKuvvhqAiooKXnjhBTo6Onj77beZP39+3k9QCCGEEEL0rzscIxQ1ts0qcoxkRUz+gxgsBUytNLbyOtTUlbl9sA3eftq4zjMWbvgyaN0Qi2beB1RliMNjrBBJZ7Kqll0l81WgYS9XVRDNG6G7MbvH01MRM4j5MOmsRckWZd7dPc/v7tMd1HmN7cqunVmlrmgmcFSqkCmVv1Y9FmthbhU+56lp1cUA/Dp6nfEGfzPsfW5kT0bTwDNbXfcdS75nhBBCCCGEEGetIfRHEEIIIYQQZ4P0+TBwlsyIGWIQM6XSbbjpUGMvQczW30FXk3HdDT8AzzhV9RE4lf2x+2OyqMoSR5Wat9LyFgTq+r+PruevIiahcIraVyys5thARjXM+DJXxnOXwXdcXRaMy895vcNNrVLP50F9LG/GZhhvfOsXI39CjvL4a1EH756RP74QQgghhBAiJzkHMQ0NDdx5552MHj0ai8WC2Ww2/AghhBBCiJHV0Z0ZxBQ6ch4FOHjRPmbExAYRxESTQczkivQgJu0v/0N+2PQr47pxl8DUa8E9QS13HVFfVueDZlKtylyjVRjT+jaEO/rePupX7aM0E1gK+94up3PQoGRBvEVZE/hOZLYlm1mF1l+lT6hdnbdmAldNfs7rHa6swIbbql5Hj0WuNd54Yj00nIEwxDNLvR4C9RBsHfnjCyGEEEIIIbKW8yf0u+66ixMnTvDVr36VUaNG9f8hTwghhBBCDLv0ihi33YLFPIKFz721JtP1ZEBjyjKI0XWI+NV1SwFTq4zt1pq7grT7QxS74sPJN/0f+NuM+7jmq+rLadc46DgA4S415N45irzQTGrofSyqZrW0bYeKy3tvcRZqV5fWAVqg5crqVnNs2ndTd2oXu2qNQdOyRFuyvvhOqEvnKNV+bSREu6Fjv2qJppnAZFPHNtnBWQWO6swg7ywzyqlzMKzx99himnQPFZo3eePmX8IN/z2yJ2R1q9e577h6bisuGdnjCyGEEEIIIbKWcxCzbt06Xn/9dS644IJhOB0hhBBCCJErr98YxIxoWzJdh1hIXU/9Ij0WSlaiZPsFe7RbVZpoJjA7GV+qYzVrhKPJoOFQYxeLJpRCtxfeeNh4/8nvggmXqesmC7gnqjCm82D+ghiIV6XMg4ZXVdjSdQQKJ2dulwhi8tWWLFXBRAjUsWZnK6lF7h6nlUUT+pn5EotAoDa+j/H5P6+M40Wh6zB0HlIzaUBdxlJes90NoO0EWyk4R4OzOrcqqhEyygUHOyCMhaeiV3Gv5ZnkjdufhGUPgn2AlnD5VjgV/Ccg2KxCR+sIH18IIYQQQgiRlZz/VLKmpgY9X+0dhBBCCCHEkKW3JisaySAmNXBJrYhJbVemZflPzkh8BozFBZqGxWxiQlmBYZOeOTEb/gcC6dUw/2ZcLpgImhlCXuhuzO4csmV2qNZQoKoRehuYHo5XTFg9+T02xMOgC1hz1PjcXj29Amt/1VD+UyqMsRSAvSz/55Uq5IXGV9Tzo0fBVgIVl0LVVVBxGZRdpCp7bMXqNRRsgfadULcamt6ArqPJ19FZYJQr+Rnod5FriJFS5RTqhJ1/GPmTsjjVrBgA37GRP74QQgghhBAiKzkHMQ8//DBf/OIXOXbs2DCcjhBCCCGEyFV6a7KikZwPk2hLZrYb229FBzMfJt6WzJwMX9KHzh9q7FLVMBt/arzvzJtgzELjOrMtOSum82D255GtgnFgL1chQ9t24226ngxihqMiBuiK2tlQa2x5tmxWP23Jwp3Jwe6J52W4RPzQ8iZEAiosKF0IlZer8MdaCPZS1ZKscApUXgHV71LBli1ezRNshfZdUL8GWrf2P4tnhKQGMbVU8Gr0AuMGm3+Rv3lEuSiYoC79J1UFkhBCCCGEEOKsk9Wn9JKSEsMsGJ/Px+TJk3G5XFitxr+4bG2VQZFCCCGEECMpPYgZ0dZk0V7mwwDEcpwPA8mqEksyiJla6eZvKZscbOyCLY9CMPWLeQ2u/krv+3RPUpUVwVZVcZHvKpCS+apFWbBFzV4pGKfWR3yq8kQzg2V42kVtPtZKKKVtm8UES8f1MYsmFoGWt1RoZC9X1ULDJRZWIUw0CNYiVf1iGuBjh8Wl2rsVTlbhTXcd+E9DqE1V8fhPgaMCCqepEOcMqHYal38TXcY15q3JFfU74dRmqFk8sidmL1fvmYgPAqdGpuWcEEIIIYQQIidZBTEPP/zwMJ+GEEIIIYQYrDMbxKS0IOt1/dCCmMlpFTHHGtqgLa0aZtoyqJzZ+z7NDhWOdB1TVTH5DmIsLvDMgPbd4N2t2kSZ7RBuV7fbPMZKoTzactzYmm1+pU6Rbys47ZlhRdtW9fyaHVB64bCdE3pMBT7hLnWs8osHDmHSWZwqQHNPis/gOQyBOuhuUrNQShaAa8ywnH5/nBYY5XFQ51Wv7bWx+fhsxRQkZgEBvPXIyAcxmqYqnNp3q9e5BDFCCCGEEEKcdbL6VPTRj350uM9DCCGEEEIMUkcgYlge0SAm1kdFTJ6CmPTWZIu7XgJrnfF+l97T/37dk8F3XH2RH2pLtr/Kl4KJqmIj5FWtv0oXqOsA1uL8HitFehCzqMYFuk9Vo3hmqUocS4E6t0C9mtVTtli1bBsubdtUdZDJokKYXH7/vbEVq+Ao4oeOvapKpvVtNZvIPYxVPX2YVunuCWJimNhSeBlLW55PbrDrT/CufwfP2JE9MVcNePepFm7B1jNWNSSEEEIIIYToXc4zYl544QX+/ve/Z6x/8cUX+dvf/tbLPYQQQgghxHDKmBFzJlqTpX/hnmsQo+u9V8RUuHuKNzRi/JP5r8b7Vc+AcZf3v2+LC1zxL8bbd6uqjXzSNCiep677T6kgIrUiZhhEojG2nWw3rFs4fYZqUxWLQNsOaFqvBt9796oNiucM27waADoOgr9WPR+li1RbsnyxuKBkYTJ8ad8FHQfyt/8sTa0yBoNPW24Cc8rftsUimfOLRoLJmqwS8h0b+eMLIYQQQggh+pVzEPPFL36RaDRzCGQsFuOLX/xiXk5KCCGEEEJkr+NMtiZLVMQMtTVZtFsFJJoJzMlhHA6rmZoSFwBXmbYzzVRrvN8F71FfQg+kcJqq0gi1qS/x881WrNpDAbRth2C8WmWYKmL21XfiDxn/TX7hhDJV8VI4Rc1TsbiSLcgKxg1vy6pAPXTsU9eL56nj55umqTCpaJpa7tivqkBG0LS0Cq3N3nKYMM+40ZZfQ7d3BM8qrmCCugzUJQNSIYQQQgghxFkh5yDm4MGDzJo1K2P9jBkzOHToUF5OSgghhBBCZK+j+yyYETPU1mSJahizM2N+SaI92ScsadUwxWNg8tLs9m9xqRZXoNqUdR3L7n65KJoBJpuaYxKoVcFPSnVPPqW3JZtQ5qLcbVfH9MyE8iVQ/S4YfT2MuhZK5g/LeQAQ7lQzaEBVrBSMU9d1XbWD6zqqKpFa3lJVOh0Hk6+PwSiargIZUHN/AvVDO/8cTK82BjEn20N0zroVSHnNhjphy6Mjdk49bB7Vdk+PSVWMEEIIIYQQZ5mcgxiPx8ORI0cy1h86dIiCguH5oCmEEEIIIfqW2Zosx+HoQ9HbjBg9pmZ4AJiyrYjJbEuWMKXSzXztEEtMe403zLsht/ZXjkoVUgB4d6kWYun0mGov1rgWav+qLtt3q9kk0VDPZr5ghEONnYaf7qgJimdDpAsCp9VjTwuV8mVzWhBz4fg+ZoJopqHPaelPLKwCllgE7GVqNg2o57F1CzRvVBVIXUdUYBJsUZUz9WvUbf5atY9cuSeCe5K63rZtaMFODqZUuLGZjR+hdlovh7HTjRtu/F+IhBhxieek64hUxQghhBBCCHEWyflT+s0338z999/P008/zeTJkwEVwjzwwAPcfPPNeT9BIYQQQgjRv/QgZmQrYnqZEZNYp5myaxsGKfNh3Bk3Tal0s8DynHFlQRlMvhSshbmdb+EUNdDcXwstm6FwMmgWda7RblUtk/qlfsirfgA0M5RfzBPbfPz7M7uIxHTjKdnMfO/2C1jhMqkgItiU27nl4O2MIKZk2I7VJ11XYUvEBxanmgujmVQo07JJhS6aCRxVqiLJHG+V5q9Vt3U3qR9NA1up2s5RobYzZfExxTMTQi3q99P6NpRfMmzBV4LNYmLGqEJ2nEq2HtvV6uLS+bfAqW8lN+w8Dbv+BBd8cFjPJ4NzlKqMCXlVtVCickgIIYQQQghxRuVcEfPd736XgoICZsyYwcSJE5k4cSIzZ86krKyM//7v/x6OcxRCCCGEEH0IR2MZs0JGLIiJRZLVDKlBTCzRlsye/RfjPUGMK+OmueYTrDS/Zdx89vVqSHovwc2AiuerL6tjITXIvn2nmuvSsV+FMGaHajNWdRWULlSzXywFoEeJNG3iW3/bmxHCAPhCUT7/x+0EtHJAU9VCvuO5n98A6rwBatsDhnWLJpyBIMa7Kx6kmKHsIjDbVAjXvF4FLSYLlF0MZYtUpYx7gppTU3EpVF8DhVPB6laBTrAFvHug4TU4/Tc4vUpdb9uefG2k00yq3ZzJou7fOTJtkmeP9hiWd9X5YcpKqBhn3HD9j9RjG0maBkXxqi/fcYj4R/b4QgghhBBCiF7lXBHj8XhYv349q1evZvv27TidTubNm8fSpVn25xZCCCGEEHnTEchs61TkGKEgpmc+jMVYwdCzPoeWWP1VxOz5kWHZq7torrqCyQCWHCtiAExmFRB0HVHnqkfVDxq4RoNztPqSH1TFjWsMxKLQspG2tlY6uvv+W6aO7gh/O6xz6/ga9Vjad4OtTAUOeZI+H6bIYWFKRf72n5WuI8k5O6ULVYu4aLeaARPxqRCu7GIVePXGUgCeGeon4oPuRuhugFC7CvcSP+EO8J8E5xgompbZus5SAMVzoXUrdO5X7dHsfbRpy5M5Y4zt8Had9oJ7Icy/Gdb8OHlD42449BJMXTas55PBUaF+uptUuFi6YGSPL4QQQgghhMgwqAbimqaxfPlyli9fDkB7e3s+z0kIIYQQQmQpvS0ZQNFIVcQkApf0GSR9re+LrvddEXN6K9aDfzOs+r/IjczscDF5lE1VYQyG2Z6cF5MNk6r66GpZB/RfZfDkHo1b50wFi0N9Gd72NlRcngx3hmjzMWMQs3B8CSbT8LbkMgjUq4AJVKWLszrZjiziU7/D8iW9zvvplaUgPvNlolqORSAaUPvynVABjf8UBGqhYAJ4ZhsrrVxj1fPsP6We68ors2+JNwhz0ipijjb76Iq5cE+/Ad58Ejqbkze+/HWYfA2Y8vO7z1rRzORzUjg5t1lKQgghhBBCiLzL+RPBt7/9bZ566qme5dtvv52ysjLGjBnD9u3b83pyQgghhBCif+lBjN1iwmE1j8zBo/H2WGZn2vocg5hYUM1U0TQ1HyTVK980LLbqbh6NXsfeZi2vVSZZMVnpcs02rLKaNf7njoWGdZtOaxz2FUHJBSoQCHlVZUKevH0ibT7MuBFsS5aYxwKqzVjhZBWktW1Vt5lsalZLtiFMb0wWVYnkrIbyi6DyCjU/Rteh66hqiZaueK46ZiSg2pkNo+nVhZhTgi9dh711HarV2vybjBvXbYM9fxnW8+mVzaOqu0C13xNCCCGEEEKcUTkHMT/72c+oqakBYPXq1axevZq//e1vrFy5ks997nN5P0EhhBBCCNG3ju6IYXnE5sNA/ipiwl3x7V3GSoeTb8HBFw2b/ixyEz6c7G1mcG3JhqgzbPzns9umce2sKsoKjJU5v98VVY+/5IL4HQ9BdzO5isV0nt1+msc2HqfNF8IfirD7dIdhmwtHaj5MNKiqXvSoan2VGATfsVdVyWgmFZz0MudnSGzFar+l8cCr61hmsGWyqNs1EwTqhmU2T4LDamZqpTEE3FXrVc/J7JugsMJ4h5f+E6KZlWvDrmiGej91NybbyAkhhBBCCCHOiJyDmLq6up4g5q9//Su33347y5cv5/Of/zxvvfXWAPcWQgghhBD5lF4RM2JtySB/FTHReKuv9CqKV75hWGzWi/hN9FoA9rYw8hUxQFda8FVojWKLtPDeC8ca1v9pRxuhSExVdRTEh7i3bslpeLqu63z2j9v5599t5at/2cWy77/GT145TDSWHABvNmlcUFM86MeTw8moqpdot3reSy9UoYfvBHQeVtuUXAC2YQyFXGNU5QtAxwE1pyaVrViFDwDtuyDcOWynMmeMsT3Zrtp4OFY0DS76oHHjtqOw5dFhO5c+WQqgIN7urX0ntGxWc3eEEEIIIYQQIy7nIKakpISTJ08CsGrVKpYtU8MndV0nGo3m9+yEEEIIIUS/0oOYs6IiJhZfb8oyiInEK2JSg5jj6+HIK4bNfhq5iQBqn3VdGu2htABoBHQFjUGM2wa0beP2hdWG9c2+MC/va1ALnjmqVVQspCpKYsZ99OXZ7af589u1PcstvhA/fuWQYZtZo4pw2QY19jE3XYfVzBHNDKWLVMu1QB2071C3F01XQclwc09ICVt2g+9k2u2TVGWKHlPBV2x4Pp/MTQtidp/2qiuuMTD5cqiYaLzDa9+G4PAFQ33yzFI/mqZ+X42vQaht4PsJIYQQQggh8irnIObWW2/ljjvu4Nprr6WlpYWVK1cCsG3bNqZMmZL3ExRCCCGEEH3rOKNBTJ4qYiI+dZkIYnQd1jxo2ER3V/F7rjOs29uSw7nmSUYQYzdDtJsp1sMsHmt8vL/bFA8JTGYou0g9H+FOFRDoOv2p93bz1b/0MgslzYXjR6AtWbAVOvap68Vz1PwW/+nk43CNVZUgI6VoqppNAyoICnmTt2kalCwAsz3+XA9PFcicMUWG5YONXXSHo6pKyD0JLvqQ8Q6+JtjwP3k/jwFpmnquKi5XLeMiAWhcB41rVVVRuGPgfQghhBBCCCGGLOcg5gc/+AH33nsvs2bNYvXq1bjdqiVEXV0dn/70p/N+gkIIIYQQom/pQUyRYwSqIxJ6C1xikWTFR9ZBTFprsl1/gpNvGjbRrniAcVWlhnV7G7pzPeMh60xvTVbg6ak2eP/0LsNtaw82UdueCKscULZYfVHf3QjePX0eQ9d1PvfH7Rnzf3oz7EFMLAxtb8cDlzGqzZr/dMq6sck5OCPJM0u1feupfEl5rsx2KFmoqne6G6FpXTLsy5OZo4oM44yiMZ29dfFQwz0RxsyDmguMd3rj/0FnfV7PI2u2Yqhcqn5fmqbCq4790PCa+smhZZ4QQgghhBAidzkHMVarlc9+9rP88Ic/ZMGCBT3r77//fj7+8Y/n9eSEEEIIIUT/zlhrMj2mWm2BsSImFlSXJov6GXA/urEiJhyA1f9h3KZkIlx4FzNHGasQer74HkEZFTEuJxROB2JcX7aDQluy0kXX4am3Ulpn2YpVtQao+SZ9DFB//M0TvH6w2bBu3lgPNkvmP92HPYhp266qKCwFUDwP/LXJEKagRoUwqYnESCq5ACxO9fpJtEhLcJRDxWXxKqQuaHwdupsz9xGLQKAe2nZA85vQ+raaL9NxQLVi64PLZmFyhXFG0a7T8dejyaIqhBa/H0h5bsI+eOYeiMUG93iHymSF0gVQvVw9d85qFQyGO1RYJdUxQgghhBBCDJus/mTy2WefZeXKlVitVp599tl+t7355pvzcmJCCCGEEGJgZyyISVTDaGb1BW9CJKUCJBuxIOhR9WW+2Qlr/xs6Thm3Wf5fYLFnBjH1I//FcWe38fl22y1QOAV8x3CZQ7x7QguPHyjvuf3nrx/hvQvHML4sXu3jGq2Cg459aoC6yabWxR1r9vHN5/cajlFVZOexf7yY2vYA9/3ubQ43qeDq1gVjGF08jHNygq1qroimQemFEKhVgQWoypjieWcuhIF4sHAhNL2hAiJ7GRSMT95u80DlFWpIfagNmjeoahmTXb0+9ahar/cTjBROhqKZvd40Z3QRhxqTVVC7a1NapBWMh8rpMPVyOPh6cv2hNbDxJ3DpvYN91ENntqkQraBGvY+b34yHMW9A6WIVYgkhhBBCCCHyKqsg5pZbbqG+vp7KykpuueWWPrfTNI1odHgGYgohhBBCiEwdacFA0YgFMX0ELj0VMTnOhzG7VNumdT8w3j7hCphxAwAzqwsNNx1o6CISjWEx51zkPWhdae3C3A6LCiMKxoHZwQendRqCGH8oygO/385Tn7gEsykeWhRNhVi3qohp26oCBUcFAF//6x4CYeO/p7/zvvl4XFY8LivP//MVrDvYTFTXuXp65bA+1p65MK5x0F2vqkQA3BPAM+fMhjAJthIomgHevaqSxVYC1pTAzuyAiktVZY//FESD6ie1+sPiAkclWD2qFVssBFG/asHWeVhV1BTOzTj0nDEe/rLtdM/yrtOps2pMUDQdLvog1O4Cf1vytjUPwoTLYHSyu8AZk3h+Wt6CYAu0vAmlC8E56kyfmRBCCCGEEO8oWX1qjcViVFZW9lzv60dCGCGEEEKIkZVeETNyQUxiPkxaRUZPQGPPbj+pbcle+k8Ip8yq0Eyw4ls9X/inV8SEIjGONud39sdA0luTFdrjf9cU7oTCacwe5eKO2bphm83H2/j560eMO/LMUZUwekx9CR5q40BDJy/tazRs9qGLx3HltIqeZYfVzLJZVVw3u7rXVmV5092kvphHU8FFIoQpmg7Fc8+OECbBPVkFKXoMWjYlX5sJmkm15Bq1XM1JKb9YteYqmQ/V10D1u9RjKhinKmA8M1WlTenC+EyfBrTmNzDrQcNuZ4/2GJb313cSiqRU1zjHQNEYuPITGFqUxcLwh7sg2JnXp2HQTFYoX6LCFz2m2rPleaaOEEIIIYQQ57uR+/NBIYQQQgiRd2euNVkfFTHR+JfV6QFNXxJf+DafgO2/M9628CNQPadnscRlpbrAuMmeEZ4T05leEZMIYkKt8eqCK/jK5TCuyBjGfO/FA+xLbaWmaWpejKNCtchqfpP/e3W/4T4lLitfvr73tljDrmMfoKvfc3d8wHzJPDX75GyTeC4tBao1XvNGiIYytzPbVbsyR2W8Ndc4dZ++uMYk58xEOimN7U3ORQJmjzEGg+GozoGGlHBF01RbszFzYP5Nxn23HYNn71Gzds4GmkmFT44KFca07zzTZySEEEIIIcQ7Sk5BTCwW45e//CU33ngjc+bMYe7cudx888385je/QT9bPkQIIYQQQpxHOgLGYGDEZ8SkBy6xxPocK2I2/dq43l4EV/9b2jH9zCw3/ptzb93IVhWkV8S4HVb1GKJB9WV24WQKKubwvWU6GslzDUVjfOap7caKCc2kZnLYSqjvCPPM9gbDvu+8ZAIF9qw6CedXoB5C7RBoUDOANBOULTLOXznbmG1QfokKTcKdqjImFhn4fqDCkEAD+E5mBji2YjVnxlKASQ+hte/ouanIYWVCmcuw+a7UOTEAziqwl8KFt0LVDONtu5+BP37IWAV2JmlavNrJpCqi/KcHvo8QQgghhBAiK1kHMbquc/PNN/Pxj3+c2tpa5s6dy+zZszl+/Dh33XUX73nPe4bzPIUQQgghRJpINJYxI+bMV8T0EdD0JeKDtlNw5HXj+qWfBXeFcV24kxllxlV7R7giJiOIsVviLbxQX9prJnBPYPHMmfxT2giQPXUd/L+XDhpXmsxQfjG/2mknnJLR2C0mPnrJGQg+dB069kPYC3pEta0qnntuzAyxOFWLLZMVQm3QullVd/Ql2q1artWvUcFN2zaoX61ac3U3J6tVzA70koWASVUH+Y737GL2GGN7sp3pQQyo589sgyv/CWxpFTi7n4ffvhu8B1WAlH6+0SAEW1Uw0t2sXmvBVogNU0toSwEUTlHXvbuzD7OEEEIIIYQQ/cr6T+weffRR1q5dy0svvcTVV19tuO3ll1/mlltu4Te/+Q0f+chH8n6SQgghhBAikzcQzuhsVFZgG5mD9wQufQQxphwqYnY8b1znLIHFH+9l2654RUxy3saIBzFprckKHRYI1qkFW0pKVDiFf73OxKvH97C/NXm+P3n1ENfMrGThuJKedZ0heGKX8Qv49y0cTZk7y+cwnwJ1EGyCrmPgma3adxWMG/nzGCxroZoB07RBhRf1a8CV0oYs2g3dDfHHmRK2mGzxapoO8NeqH5sHypaoEMXqodM0Rm3bvlv9rq1u5oz28PyOup7Dbzne1ss5FYFnlgpZlt4NL/0/Y+BybBM8eScsux8cheo8NZN6b/QVhJgdUDxneAIy9xTwn4KIHzoPqHMXQgghhBBCDEnWFTG/+93v+PKXv5wRwgBcc801fPGLX+S3v/1tXk9OCCGEEEL0rc2fOQej2DXSQYyzj/VpAU1f++hqgsPrjesv6qVyACDcyaxy46rGziAtXcHMbYdJZ28VMaFWtWA3lus4iifxvfdOw2JKpmUxHT77++0EQsmKht9tOkFnMLmsofPxOd7hq3roT8c+6DwE9nJwlKlqjnONrQTKFqv2eNGgejz1L6ufutXQtkOFNLqufmelC2HUtVB1JVQuBfcEMFkg5IXWt3pCE79WDfb4TJ/WLaDHuGhiieHQ++o7aezozjwn90RwVMGERXDdFzJb99Xthd/9M7z2Mzi5BYLtyRDG4lRhjrVQ/Zjt6r3Tshla3lJzcfLJZE7+3ruOqEodIYQQQgghxJBkHcTs2LGDFStW9Hn7ypUr2b59e15OSgghhBBCDKzVZ2xLVmi3YLPkNAJwcPRY74FLNJT8S/9sgpiID3b93Rg4WBwqiOl1+y4mFIPdohlW76sfmS+Kg5GoccYL4LZEVOWApqkAIM2cydO4/8rRhnVHmn18e9U+AEKRGL9cd8xw+3WTNSa6vD1f9o+Y7ibw7lG/W9dYKF2kKjPORY4KqF6mZts4KtW6xDwiWwl4ZkL1NVBxKbjGJB+nzaNCiIrLVYuzYKtqWabroGnoxfNV9Uy4Azr2MX9ssaqKSrH2YHPv51RygQpRxs6GW76r5iCligThwGvw1/+EJz8Df/kaPP/f8ML3YO2jcGg7+E1QvBiKpqlzDtRD46v5n+fiqARntXrc7bvyu28hhBBCCCHOQ1m3JmttbaWqqqrP26uqqmhr66UUXwghhBBCDItWn7EipmTE2pLFK1A0k/pSOiGWaEtmy+4LfF897HvJuO6CD0FBeea2ug7hTiwmmF7lZkdtMnzZW9fBZVN6uU+e+YKZFSqFpi6IAlaPqqLoxSeXXcCag51sO9XVs+7R9ccAWHuwifq0Cop/unoOaLtUC6227eoLfM0YPg0L7x7oblSVG+UXgcU18H3OZppJte5yjlJVI+F2FcJkExJaC1UQ1bJRtSnT47OXzA71+2jZBJ2HsThHcdnkclbtru+56+sHm3jfhWMz92m2QckCaN4IJaVw20/h6X8FX2Pmtr4m9ZNq95+T1ydcAcsfBFt8hkzb26CZwdn357Wceeao10OwWR3DXpq/fQshhBBCCHGeyfpP3KLRKBZL37mN2WwmEpFhjkIIIYQQIyW9NdnIBTHxVkhmhzEgSLRIsjgz79ObrU9AODWE0OCSe/o4pl+1hNJMzBhlHJC+Z4TmxKTPhwFw066upLUlS2Uxm/je+y/EYTX+0/vR9cc40uQzrFs8oYSFU8bHq1E0NavDu3vI5z6gcGe88kFXM0ESVSTvFBanCmSyCWESHOVQPB8AresQzlg8GHFWQUGNut62nSumGn/36w42E4ulDW/q2WcFFE2PX9fhth/BjBtyrzw69jr8+lboiqrqJV2H1s0QbMltP/2xONW+AboO52+/QgghhBBCnIeyrojRdZ277roLu733oaHB4Mj15hZCCCGEEJkVMaUu68gcuK85MD0VMdm0JQvB278zrpt1M5RN7n37xJwKayEzRxlbOu2tG5nWZJ1BYys4kwZOPT4fxtZ/tcDkCjdfXDGDB5/b0+9291w9RV1xVqnqida3oeuoqjIqmjbocx+Qd7+qfrCVqCHwQimoUSFg2x6KYsch7AVrOXhmq+cr3MnS0V2Gu7T4Quyp62DOGE/v+yyaptqete8CSxiW/Qus/Dbs/CNs/S20HMzu3IJeePy98O6fwJgJqk1ZyyYovwRsxUN62D3ck8F3Qu073KkqhYQQQgghhBA5yzqI+ehHPzrgNh/5yEeGdDJCCCGEECJ7bWeqNVkicDGnVb5EUiplBrLnL+BL++v9y/6l7+3D8aoXS2YQc6ixk3A0htU8vPNM0iti3HYLWmLuSD8VMQkfuWQCq/c28MahzKqFcaVOPn3VFK6anlKJ4hoDsZD6wr5jv2oV5uql5dVQRUOqtRUxFRI4KvJ/jHNZ0XQItAIxtLa3wXGNClI8c6B1CzXm40wodXCsNVnd9frB5r6DGAD3RPX+aX1bBTpRP8y/CS76GLSegI5aCPshHIBgJzTuhbptUL8LYimBYDQEf/44LHsQpl0MoRbV+qz8EjXvZqisblVJFKiDzkNQumDo+xRCCCGEEOI8lHUQ86tf/Wo4z0MIIYQQQuSo1Z9eETNCQUxfgUtfAU1v9v/NuDz+chhzYd/bJ4IYaxEzq41BTDiqs7++s/8vvvOgK2gMYgrtpp5zwjRwNZLJpPH92y/gnx7bwvaT7RQ5zNw4Jcqt02NcOFZHKy/JvJN7oqpA6jyk5sVY3PmrdkjoOqK+aDe7oGRhfvf9DqEXzyemvQgRH3h3qTkxrtEQqIVAPVfURDnWmtx+7YEmPnVVH9VdCc5qqLgUmt+EcBd49wJ7VeBWWgwxpwriosUwtgZMN0A0Ai/9EI5uMO5rzYNg+i+YcgGE2qFpnaracU8Y+oMvnKJeH4FaiMzIvvWgEEIIIYQQokfWQYwQQgghhDi7nPmKmLQgpq+WZRn3j8KRV4zr5t3e/30iidZkRXgcVsaVujjR6u+5eccp74gHMW5bfA5IFtUwCVVFDv70yUvo7I7gdliwxrqg5S2I+NWX5yUL1Bf0qYpmqLZQ3Q1q28orcpt10h89ptpZ6REonKGqH0Qmk5V20yRAA99JsFeoiqXiuRBsYenYII9tT1ZkbT7eij8UwWUb4OOWrRiqrobAafX7DTar10LEn7ltNKour/4UOAthz4vG21f/B4x6Ggqr1L7ad6oKmeL5YOrlPKJBFdqgq5Z05t5bUGMrBnu5Oreuw9K6TgghhBBCiEGQIEYIIYQQ4hzV6jfOLCkdqSCmpyIm7S/jsw1i6rZBoM24bvI1fW8fi6pKBOiZUTG/ptgQxGw/2c4dF48b4MSHpjO9NZkl/sX4APNh0lnMpmRoZi6CiiugdYv6orvlLdUerHAaaJraRtOgdKEKasKdapuKy3If8N4b/ynwH1cVPWUXJY8pMoS1IvTCyeA/Cu07VHhhcYFnFkvGbMdigkgsvm1U580jrVw9o7L/nQKYbapyxT0BYhH1OoiFwGSnO2ZhZ10Qj9PKtEq7aksW9sKlHwV3GWxKmbOkR+GPH4dPrFXhYMde8J+GUBtYCkEzq9eMHlUBTLTbeB5WN9jKwDkaHOXG2wqnqPPynVCvTfMI/bdGCCGEEEKId4jhbaQthBBCCCGGTUZFzEi1JuuzIqaPgCbd4ZeNy+XToLim7+0jXaDrKiyIH3P+WGP1y/ZT7QOc9NBltCazxYOYHCpiemW2QfnFqg0ZQMcBaN2sAqgEkwXKFqvnINSu2pQNlR6D5g1qzoirBlzDG2S9I7ingb1UBSatW9RzWDCOQk81C6t1w6ZrDzblvn+ThZi9ijcbCvjiCw0s/s5mbvv5Vpb/aBO/eLNFvdbck6BqKSy8HRa8x3h/XyP84S71u6y4TLURiwTUHJpAHfhVK7WeEMbqVq31QLVH8x1XrwnvXvWeS3BUqJkzehR8R3N/XEIIIYQQQpznpCJGCCGEEOIc1ZoWxIxIRYyup1S+pAQusYj6gYErYg6ntSXrrxoGDPNhEi6oKTZscqChE18wQoF9+P5525VeEWNDfZHdV0unXGgm1fLJ6lHVFoF6iG1UVSqJ+TOWAihdBC0bVSWLtQgKB5hD0p+u49B5GDQrlC0Bk3noj+OdTtPUHJ3G11Qg1r4TSuZD8XyuGP8ym04nw7PXDzbnvPuNR1r4wp92cLwlszXZ91/cz4cuHofDala/+8qlcFkhNB2CUzuTG57cCKv/HVY8BJVXxitsIipE0aPqtWb1xGcbxd8vsTAEW6G7XlW9dB5SlTclC5PVL+4pKnzyHYfCqfmpyBJCCCGEEOI8If96FkIIIYQ4BwUj0YwKjdKCgQfGD1ksqMIYTQNTSgCRCGdMlt7nUSR0d8DJN43rBgpiUubDJMwe7cFsSrbRiumwq9abzSMYtIyKGCs5tyUbUEENlF+iwpdgKzStV7M8Ehzlagg7gHePqnQYjFgYWt5UVUzucVA0Zejnfr6wOKH0QnXdd0L9mG1cMXu6YbNDjV2cbg9kvdtgJMq9T2ztNYQB8IWibDzSklxhskD5Ylj5n+BOayW28SfwykOgWdTcn4Ia1fqscLKqvLKXGt+nJis4q1SoVHqhamPW3QRNayEUf185q1XIGg2qoFAIIYQQQgiRNQlihBBCCCHOQe1p82FghFqT9QQuduM8kWzbkh1bl6ycAfUF8ITL+79PT0VMYc8qp83M9KpCw2bD3Z4sY0aMjaG3JeuNvRQqLlWVNuEOaHojOZcH1BfpBfE2Yq1bVEupXHUeUrNhzA4oXZysuhHZcVRA0Qx1vX0nhNqYO2kCxQ7jx6vXDmTfnmzjkVaau4L9bvPS3l6Ct1FLYcWXwZz2O3ztW/D0JyESyrxPf1yjofIKVYEVCahWZeEuVQGTeN35jue2TyGEEEIIIc5zEsQIIYQQQpyD0tuSaRoUJrhDpgAA8kBJREFUj2QQkx64RPuYG5MufT5MzWKwFfR/n3BmRQzA/LT2ZNtPDndFjDH8ctt0Ndx8OFiLUmZ8+KA5LYwpnpucVdKySVW4ZCsSUDNmwl1QMH5o7c3OZ0VTVZWIHoOWzZj1EJdNrTRs8sjaI0Sisax2t2ZPg2G5otDOFVONlS5r9jag68ZZNJgsMOMDcNk/Zu50x5Pw+K3QdAAC7aqaTddVZVrzITj2BpzeZpxHBCr0rLwCbCUp1VNBNXtG01S7s4gvq8clhBBCCCGEkCBGCCGEEOKc1JYWxBQ7rYZWXcOmp/IlLXDJOoh5ybg8ZVn/28fCyX1bjBUwF9R4DMvbTrb3v68hSm9N5nZYVVAyXCwFUH6ZmkMTCajZMNH4710zqXkxiaCm5S1jpVF/Ovapoe2WQhXoDPQ7E30rWaB+P9FuaN3MDXOrDTcfafbx1OaTA+5G13XW7DUGMf9w2QT+46ZZhnV13m52n+7I3IGlAC79HFz6UWOlGsCx1+F/FsO3x8N/lsE3quFbNfDjC+HR6+H/roSH58Ir34S2lEoXk1XNKLK4IOJXrzGTDezxsEmqYoQQQgghhMiaBDFCCCGEEOegVr8xiCkpGIFqGOinIiaL1mStR6H1iHHdQEFMoi2ZxZUxeya9Iqa2PUBTZ/+tnYaiK601WaHLNWzH6mFxQtkSFZaEu+LVL/HqBbNdfVGumSHYAs1p82R6E2qDzoMQbldtpgplNsyQmCzJ1m7BVlaMaWDOGGPl1g9e3JsR4qXbfbqDOm+3Yd21M6uYXOFmQpnxdZYe2PRwVMAl/wLXfgYs9t630aMQ6c5c31ELr30bfjgfHrsVGvep9WYblF2sHl+oDdq2qqoYAN9JVQ0khBBCCCGEGJAEMUIIIYQQ56D0ipjSkWhLBkOriDnyinHZ6YGquf0fryeIKcy4aWplIS6b2bBuxzDOielMr4hxuoftWAYWJ5QvSX4Z3rol+QW4tUjNkzHZ1FD1pjf6bhkVqIfmjRA4rVqqFU5RlRRiaKzu+IB7DVOgli9faQximn1RHnlpW7+7SA9Xxpe5mFLpRtM03jWzqt9tDQonw7yPwE1fBVdxLo8iTldVa7+4VrUtA/X4yharKqxAHYTb1Ps8FlLLQgghhBBCiAFJECOEEEIIcQ5q9RlngpzxiphYfL2pnyDmUFpbsnEXgWmAf472MR8GwGzSmDPG2J5s+zC2J0uviHEXZJ7TsLEWQvnFqvqlu0HNeEnMCrEVQ+Xl8RZSPhXGBOqSc2N0HToOqNZSEZ9aXzBeqmHyyVGh2rwBl5ae4OopxtfGIxsaaGyq7fPu6eHKsplVaPEWY8vSgphdtR3UeQP0yT0Bpt0G7/46TL4ELP38t6GvyplgBzz2Htj3vFq2l0HJfHW981Dy/SjtyYQQQgghhMiKZeBNhBBCCCHE2abNf6YqYvzqMr3yJTFIvq+ZKdEIHF1rXDfxioGPl6iIsWZWxABcUFPMpqOtPcvbTnkH3ucgZcyIGckgBtTg9NILofUt8J8CdDWjRNNUZUvFZdD8pnrOWjar9dYi0CyqdRmoOTKF08BRqQIckT8F41X7uK4jfPGiDl47DLF4VuYPw8N/38o33xNVLeFS1HkD7Ko1zn1JDV8WTSjB47TiDSTD1zV7G7lzyfi+z8VZDRNvgsIqVbkSCUJ3J3R3QTSsqtFcHnCUQstx2P08HHoDQv7kPqJBeOrDcNMPYeFHwDVWvY58J9SlHlWX4c4+359CCCGEEEIIRSpihBBCCCHOQa2+MzAjRo8lK2JSW1rpMfVlL/RdEVO7Rf2VfarJVw98zEjfFTEA88cWG5a3n2xHT1SK5FE0puMPRQ3rCl39zMMZLs4qKFmoQhZ/rbFNmdmh2pS5J6nfj66rdmXBFtVWylas1pss4Jk58ud+PvDMAkcV00tj3Jb2FD+1G7bs2Q7efclqJlSoYtiF08qiCSU9y1aziaunVxi2WbOnn/ZkCbYSqFyqzqlkDlRfBOOXwuRrYcIKqLkRqq+B2f8A7/sd3LcRJqeFo3oMnr0PNj0SP7nZqvJKjyZb4PlODHwuQgghhBBCnOckiBFCCCGEOAdlVMQUWIf/oNGA+gJZM6tB8T3r4+GMZlLDvXtTu9m4XDIWiif2f7yIX1VwaKY+Z5nMrzG2JvMGwhxv8fe67VD0Nmzd7ThDxeWu0VC6KDmzo+UtiMVDIpMVimerL9hHXQulC6FoGhTNgHC8Wqh4jlTDDBdNU1VLjkr+9aIYqS+RqK7xj3/VOHDsILS9DVH1Hk4PVa6eXoHVbPyYtmyWsT3ZhsMtvb4mM1icam6MZ4Z6XZTMVy3UXGOMVW0mKxSOhzv+AnNvzdzP374AR15VIV6iCkuPQbAVArWGYEkIIYQQQgiRSYIYIYQQQohzUEZFzEi0JovEAw6Ly7i+r7kxqRp2G5crJg88KD4xH8biVqFDL8YUOyl3Gx/79lPt/e93EHoNYuxnsMuvsxrKLorPjGmE5vXqS/FUZof6wt1Vo+Z66Lpqi1XQT0srMXQmM5QtprpyDP+0wBhQeIMaH3nWRG3DaWh4ia6mvWw43GzYJj10AVg6rQKrWetZDkVjvH6gKf/nbrbArb+ESz5lXK9H4Q//AG3HwV4K7ilgK1It8sKdEGzufX9CCCGEEEIIQIIYIYQQQohzUpsvvSJmBIKYnvkw6UFMfD5M+tyYVA27jMvlk/oMV3oMMB8GQNO0jPZk206297/fQejqzgxiCmxneNyiowLKL1ZVCqF2aHpDzYaJ+FToEglAdxO0blat42zFPQPlxTDTTFCygPuuGsdV441hTL0P7nzWwlunIjy58RChaPJ2q1lj6WSPqpYJtan2cx0HKOo+wJIa43t89Z76YTp3Da77Flz+L8b1gVZ48kNqjkzRNNX6zFYEvuPxmUVCCCGEEEKIvpzhT49CCCGEEGIwWv1nYEbMgBUxfQQx0Qg07jOuq5iRxfH6nw+TML+mmJf2JedsbB+OICYYNiy77WZMJq2PrUeQvQyqroaO/eA/qVqVddcDJlXFkGCyJduZiZGhaVjL5vGT22x86LFDbG1Ivl6OtMW47c+Zv4slo2MUtb3c6+6WjYPXjyXv88re00TabFiKJvcfgg7WNQ9Cwx44uDq5rmEnPHsvvPcXUHKBCoq8e9Trr3ieqgYSQgghhBBCZJBPYkIIIYQQ55hAKEp3OGZYVzoircniw7lzbU3WegSiQeO6qlkDHy8x0ySLICbVrtMd2c3PyEFHWkWM2z4CM3myZXao2R+VS8FRqaph9KgKXaxu1casfImaFyJGnKt8Br/6hyVMLRv4o9eyyal/JxefwxILgh7hXROM92/rhrcPHoH6NeDdl/85LSYTvPeXUJo2y2nXn+DNn6n3ZfE8NS+q6zAETuf3+EIIIYQQQryDSBAjhBBCCHGOafEFM9aNSEVMT2uytNkuA7UmS29L5iqBwjH9HysWhXCXuj5AEHNBTTGWlOqUUCTGS3sb+rlH7tJbk7kdZ2FhubVItSqruhqqr4HR16vrZYvB5jnTZ3deKy4u5zf/dBVjPH0HeA6LxnUzSsBersINdBWmmeygWRhbFGNmuTFsWXPCqQKYzoPQ8hbEwr3vfLAcRXDHH8GW9p5f8yC0HlUtyhyjVBjb8lZ+jy2EEEIIIcQ7iAQxQgghhBDnmDaf8ctWs0mjaCSCgcG2JmvYbVwurQFLQe/b9hwrPh/GbB+w7ZLHaeWyKeWGdc9tz+9f56dX2LjtZ2EQk2B1q+dXOwtap4keozxOfnv3ZVw8sZQCmwmXVcNlBZdVZ1qpzveWRam2NKrB99Gg+v3ZisE9CYpmQOFkrp1mDNTWHImqFmGaCboboPH1ZICZL+VT4NZfGNdFAvDX+0GzQMVlal37Dgh15PfYQgghhBBCvEOc0SBm7dq13HTTTYwePRpN0/jLX/5iuP2uu+5C0zTDz5IlSwzbBINB7rvvPsrLyykoKODmm2/m1CnjsMi2tjbuvPNOPB4PHo+HO++8k/b29mF+dEIIIYQQwyNjPozLhjbcX7rHwsm/tjenBTGxAVqTZQQx4wYOYkKJtmTZVXLcNH+0Yfm1A014/fmrDkiviCk8GytixFlvQnkBT33iEnb/50r2fP169nztOvZ8aQEvfnIaN1w4C4rnqmCl/BIYtQIqr4Di2VA0FTyzWLZwrmF/R1ojHD51VM3/sThV+8Cm18F3PL+tymashAs/alx35FXY9gQUTQdnlWqH17g2f8cUQgghhBDiHeSMBjE+n4/58+fz4x//uM9tVqxYQV1dXc/PCy+8YLj9/vvv5+mnn+bJJ59k3bp1dHV1ceONNxKNJoeT3nHHHWzbto1Vq1axatUqtm3bxp133jlsj0sIIYQQYji1+YxBTGnBCMwrSVTDmO3Ggdy6PriKmPQwJ104tyBm+ewqbObkP23DUZ2/76nP6r7Z6AwEDMtndUWMOHeYLOAao1p8FU4G9wQoqAFHubotzZzRHqqK7IZ1a/Z7wbsTiheAvQxiEWjbAY2vQqCPFn2xCHQ3QccBaN8NXUcgUAehdtUWsDfX/he4q4zr/v5l8DVBxRVquWM3BFtyegqEEEIIIYQ4H5zRT5ArV65k5cqV/W5jt9uprq7u9Tav18svfvELHnvsMZYtWwbA448/Tk1NDWvWrOG6665j7969rFq1io0bN3LxxRcD8Mgjj3DJJZewf/9+pk+fnt8HJYQQQggxzFozgpgRmA8T8anL9EqWWFCFMZqmZlmk6/aC94RxXfkUY5jTm0QQk+VskyKHlaumV/DinuQXz89tP83ti2qyuv9Auvw+w7IEMeJMMJk03jWziifeTL6n1hyz8ImFAWjdDGWLINyhApZwF7RsAluJClB1HYip4DTc2c9BrCoYKpigWp4lOIrgph/C7z6QXNfdDi98Dt77M7BXQLAJWjbDqOXSGk8IIYQQQogUZ/0nyFdffZXKykqKi4u58sor+cY3vkFlZSUAW7ZsIRwOs3z58p7tR48ezZw5c1i/fj3XXXcdGzZswOPx9IQwAEuWLMHj8bB+/fo+g5hgMEgwmByE29Gh+h2Hw2HC4TwPwTyHJZ4LeU6EODvIe1KIc8dQ3q/Nnd2G5WKndfjf90EvWjSCrlsh9VihTrRoBMwO9Egk427a6R2Gf3DqJjPR4ono/Z2vHkPrbgM9ho7TeLx+rJxdaQhi1h9uob7dR1kegqqOtCDGZTPJf2vPI2fT/1+vnlZmCGK21MVo6C6gzOqFhjfQSy6Esiug6yCa7xgEmpJ3DneoHz2MhgndZAWzC91ehmZxx0OaALRsh/aD6EUzwJnS9m/SMswzbsS076/JdXv+QmT2+6BkDlrjK+gdh9BdE6Fg4vA/GUJk4Wx6/woh+ifvVyHOHfJ+Tcr2OTirg5iVK1dy2223MX78eI4ePcpXv/pVrrnmGrZs2YLdbqe+vh6bzUZJSYnhflVVVdTXq1YU9fX1PcFNqsrKyp5tevPQQw/xta99LWP9iy++iMs1QCuN89Dq1avP9CkIIVLIe1KIc8dg3q/bj5hI7TDb2VzHCy/U5vGsMhXFjuGMNeIz1dFlqutZb4+1URw7SFhz02oOZdxvQtMa5qcs+23FbNq0kw5z3wPFLbqfsugudMw0mrWs/7I+HAWbyUwopraPxnS+99RLXF499FkZx0/5gGR1Tv3JY7zwwpEh71ecW86G/7+GY8bXeUyH//dKB9eVHcSme4FNBLVigloRERxYdT8OvQ0HLZj1IDomIjjQtdSPgoeIYcWvVaBjooBGTHoIWEtI89Bumtyzvc2ygmXml7BGk+36up99gPXTH6A81oZDP4J3dyPN5rnEtBFomyhEls6G968QIjvyfhXi3CHvV/D7/Vltd1YHMe9///t7rs+ZM4dFixYxfvx4nn/+eW699dY+76fr/5+9+46Tq673P/6aXrb3kt57QgiQAoQWqhRFBRtgQ7wqV8R27eDPC1evDcFruRZU5KKooCItdAJphIT0QnrZzfY6O/38/vju7O6Z3U02ybYk7+fjsY+Z+c53zjkzu3Nm9nzO5/OxbA1re2pemz4n3Ve+8hXuvPPOjttNTU2MGjWKyy67jOzs7GN9KqesWCzG0qVLufTSS/F49I+WyFDTe1Lk5HEi79enHnkLDndmfsyZOpGrlkzs7020cdSuhEg1Vu4cCHYp99W6G0djDvjLsPLndXuc88nn4UDn7UD5ZM676HLIPML2hvbjaPCDtwCrcOExbefLofX8a2PnyTZ7rULuuersY1pGTx498AzUd96eO3MqV5079oSXKyeH4fb5+kzTOpZuqeq4Xe0bwcKrr4SGt3C0pQdls4H23i4ON1agFFwZ4AqYvk6xRhytuzt7PTk9WNmXQ6INR8tOsBLgzsTKPwfc5oQ0x9gkPPHvHWvIjBzmktI41ohLTb+ajDFY2WMhdw4iQ224vX9FpHd6v4qcPPR+7ZSqpHU0wzoQk66srIwxY8awY8cOAEpLS4lGo9TX19uyYqqqqli0aFHHnMOHuzeprK6upqSkpNt4is/nw+frXufc4/Gc9n9cPdHrIjK86D0pcvI4nvdrQ5s99bkwyz8I7/kouNzgz4Gu63IkzLgvyz6eUr3FdtNZMAanL6fnuSlWyCwzUHDkeT24du4IWyBm9d56akMJSnP8x7Qcm3gbaW15yAn6tJ89DQ2Xz9fLZpTaAjHL3q4l4XDjLz4Hog0Qrjb9WqKmxB+eLNPzJTgSnOn/ApZB7mRoq4Dmt03psuZNkDEKSs6DujUmSFO/AgrPMT1n5t0Ma/4XKjZ0LMW17Idw0+8gazxEaiBSAdZE8OYOxksiclTD5f0rIken96vIyUPvV/r8/J1HnzJ81NbWsn//fsrKygCYN28eHo/HlgJVUVHBxo0bOwIxCxcupLGxkVWrVnXMWblyJY2NjR1zRERERE4m9a32QEx+P/RAOSLLgkR7urU7w35fqjyRq4dARzIJVZvtY/mjui8jXazRXHpzjjyvBxdMLiLL13mg2bLgXxsqjvCIPog305JW9jfTd1KdzySnmIunFtsq9oWiCZbvqjU3vLmQPQmKFkHZFVB6MZRcCJljewjCtHM4ITgCis+HrEmmHGDrfqhfC7kzzXsxGYXq16Gt0tx/+XftywjVwPonTNDH4QSS0LDBvAlFRERERE5zQxqIaWlpYd26daxbtw6A3bt3s27dOvbt20dLSwtf+MIXWL58OXv27OGll17immuuobCwkHe9610A5OTk8LGPfYzPf/7zPP/886xdu5YPfehDzJo1iyVLlgAwbdo0rrjiCm699VZWrFjBihUruPXWW7n66quZMmXKUD11ERERkeNWF7KnZ+QNdCAm0WYOpjqc4EzLGE6VM+opENOwF6JpvWDyR3eUN+qRZZkz8gE8x14O1u9xcekMe9bzP9adYP+cWDMtaRkxmX4FYmToFGT6mDfa3ifzoeV7sdKDHk7X0QOfXTmckDMVCheZ92k8ZDJiAiPAX2Kya+rWQLgGxp4LE5fYH7/6t9DWCoFyiDWb7JzW3cf3JEVERERETiFDGoh54403mDt3LnPnzgXgzjvvZO7cuXzzm9/E5XKxYcMGrrvuOiZPnswtt9zC5MmTWb58OVlZWR3L+NGPfsQ73/lObrjhBs4991yCwSD//Oc/cblcHXP++Mc/MmvWLC677DIuu+wyZs+ezR/+8IdBf74iIiIiJ8qyLOrT6mTlBwc4EBNvz4ZxBSC9x15HICbQ/XGHN9lv+zIhsxicR0jdToQgGTcHhN2Zx7W518wpt91+60AjWyv7Vre3R7GmboGYLGXEyBC7dLo94Pj81ir++uYJBh1TfPlQvBiC5SY42rgZnN4uwZjVEG2Ey+9tz35pFw/Dun+a93jq/du4xQRkREREREROY0P6H+SFF17Y/aytLp555pmjLsPv93P//fdz//339zonPz+fhx566Li2UURERGQ4aY7EiSft35/yMga4Jm9vZcks68ilydIDMfmjwXOU4Eq0vSyZJ9t+gPcYnD+xkOIsH1XNkY6xR1bt565rZxzX8pI9BGKUESND7YazRvHLV3ZR2yUwe/c/NrFwQgEjcnsIjB4rpwfy54EnxwRTQvvNdU+WyXapXQlF58IZH4C1Xf7X2vQvmLwICseANx8itSaLpnjxkYOwIiIiIiKnsJOqR4yIiIjI6S49GwYGoUdMKiMmvaRYMmLOjnc4esmI2Wi/nT/qyGXJoLM/jOfY+8OkuF1O3nvWSNvYY2sPEo4ljn1hlkUo1IKFPRNIPWJkqOVleLnn+lm2seZInC8++hbJZD/2ZcmaCIXzTRAl1gjJmHkfJyJQswIu/A/wdH3/W7D6T6ZHlK+gs8RZ/Vv9t00iIiIiIicZBWJERERETiJ1aYEYn9tJwOPqZXY/SWXEuNKCKPHWzvH0kmXQc0bM0fpVpAIx3uMPxIDJFuiqsS3GM5sqj31BiRAtkWS34SyfzuyXoXf5jFLefaY96Pj6zlp+v3xP/67IXwzF54M7YMoROlwmCy4egug+WPhp+/wDb8G+N6GtEvLPNPuHtgpo6eftEhERERE5SSgQIyIiInISSQ/E5Gd4cfQUBOlPqYBLehClt3GAaAjqdtnH8kd2D+aki7X3cvFkH/t2djGmIINFEwpsY39avf/YFxRr7laWDCDDN8DBL5E++ta10ynPsZcGvPepreysbunfFbkzoOAccLpNaTJXhrkeqYPZ15j+T12tfBjCtSZokz3NjDVugnB1/26XiIiIiMhJQIEYERERkZNIeiAmLzjAZcmg99JkHYGYHoIr1VuAruWRHJA38sgZMYmwKXfkcID7xAIxADeebc+KeX1nLXtrW49tIbFmmtMCMQGPC7dLX6NleMj2e/jv986xjUXiSe7881vEE92zuU6IJxvyzzLv0Wht5/s5vB8u/Lx9btNh2PQstOyGzPEQKDWlDGtXmUwZEREREZHTiP6DFBERETmJ1Ie6Z8QMqGQcku3rTM9mSZUs6ym4UrPDfju7GNy+Iwdiou1lydyZ4DzxjJPLZ5SSG7SXEDvmrJh494yYTL/6w8jwcu7EQj68aKxt7K39DfzspZ39vzJ/EeTONtejjZ39ocrGQukM+9y1j0PtJtNPKn8eBMpMMKbuDQgd7P9tExEREREZphSIERERETmJ1LXGbLfzBjoQkwq2OL2mDFFXHT1iegiu1L5tv51T1t5Xwtf7ujrKkp1Yf5gUv8fFu+aOsI09uubAsWUJxJq6BWKyfArEyPDz5SumMr7Q/l687/kdbDzY2P8ryxgNWRPN9UQYnB6wYrDoI/Z5sTZY/WeTFeNwmmBMcCRYFtS9Ca17+3/bRERERESGIQViRERERE4i9ek9YoID3DS+t7JkcOQeMekZMTmlR86GAYg1mEtv/wRiAN539mjb7ermCC9u62OPCisJ8ZZupcmUESPDUcDr4gc3zMHZpWVUPGlx55/XEY4l+n+F2VPBV4gpQWgBDsgvhUnn2+dtewl2LTXZdQ4H5J0BGWPMffXroW4tJO0BZhERERGRU40CMSIiIiInkbq00mQDnhHTWx+YRNQcWO3pPoDatJJIOWU9z+sq1n7mfj9lxABMKc1i7uhc29gfVvTxLPx4K1gWLXF7mbRMZcTIMDV3dB6fvmiibWz74RZ+tHR7/6/M4YD8M02WWzLeme0273pwd90vWfDCT6BuY+fj8mZD9hRzPXQAql6GcE3/b6OIiIiIyDChQIyIiIjISSQ9I6ZgsEqTpZcfS6QCNAFTcqirZBLqegrEHCEjJhGBeJu53o+BGID3nT3KdvuV7dVsrWw6+gNjzQC0xO2vsQIxMpzdfvEkZpRn28Z++eouVu2uO+ZlVTaGCUXjvU9w+SDvTHM9EQaXHzKLYNZl9nnN1fDUVyHZJTMnezIULjL7hXgb1CyHho3KjhERERGRU5ICMSIiIiInkdq0QExucKAzYnopTXak/jDNhyAWso8dLRDTkQ2T2b0XzQm6ds4I8tMCVr98ZdfRH9jes6Ylbi//ptJkMpx53U5+eMMZeF2d/+pZFnzh0bdojRwhqNJFVXOYjz24mgX3Ps+cu59l6ebDvU/2F5qgCpiAqtMDc98NRWPs83a+Bqv/xz7my4fixZ2lylp2Q+Xz0LLLlAYcLMmEeb+3HYaWPdC0HaL1g7d+ERERETnlKRAjIiIichKpagrbbhdl+QZ2hb31gemtZBlA7dv2224/BHPBdYTSZNEGc+nJPY6NPLKA18VNC+wHhf+x7hAVjW1HfmDcZMQ0x+yBlyxlxMgwN6U0i89fNtk2tq8uxH8+ueWoj315ezVX3fcqz2+tAiCWsPjiX946cmZM1uTOfjFW3ARTz/8YePz2eUu/071/lNNtSpUVLgBPtsmIadgEh1+Ctso+PNsTFGuCw8/D4ZehdhU0bICmbVD9mgkMiYiIiIj0AwViRERERE4SrZE4rVF70+2SbH8vs/uBlewsTdZrIKaHLJf0A605paYXxJEyYlKBGG/u8WzpUd28cAw+d+dX33jS4rev7Tnyg1KlyWJpPWKUESMngY+fP56zx+bZxh5euY8Xt1X1OD8aT3LPk1u45TerqGmxZ941hGI8+saB3leW6hfjDpr0m2QC8sbAOdfZ58XD8KcPQltD92X4i0x2TN4cU/Is3gq1q6FmRef+pr/FQ1CzsjOTx5sDgVKzLZZlSqXVrx/c7BwREREROSUpECMiIiJykqhqjnQbKx7IjJhEmzkY6XCBM2098V4CNAC16f1h2gMxrkDv6+ooTda//WFSCjJ9vPeskbaxh1fuoyncSz+KZKLj4G/aMWkyfZ4eHiAyvLicDn7w3jMIeu2BxC//ZT0NIfsfdSSe4GO/W33Ekn2/WraLRNI6wgp9UDDfBDScbtMzZsoVMG6OfV71NvjdNRDqoWeNwwEZo6HkYsiaZPpPhatNdkzjVnuPmROViJogTyIMniwovcQEggrONtk5OdPNvNa97fOiR16eiIiIiMgRKBAjIiIicpJIL0uW4XWRMZBlsrqWH3M4ermvp0BMekZMmSlLlr6MlETY/DgcAxaIAfj4eeNtm9ASifN/K/f1PDneYi6dXlqi9rPhlREjJ4vRBUG+9o5ptrGq5gj/8dcNROPm7zqRtLjzT2/x6o6aIy5rf10bT288SqkwT6YJZDic5j1vxWDhLZCVb59Xud4EY1qqe16O0w05U6HkQvAXm4yU5h1QvQziRykp2BfJONSuNPsxd8AEXpxpAdasCVBwjtmWSK0pW6bMGBERERE5TgrEiIiIiJwk0jNiigeyLBn0HmxJxiDZfnZ4T31f0nvE5JT13EsmJVWWzJ0FTlfv807Q2MIMrphRahv77Wt7Og5I27T3h8GTRXPY3hsjW4EYOYl84JzRXDC5yDb29KZK3vPz19lT08q3/rGRf22osN3vdTn55tXTmTPSHhj95Ss7sawjZMUA+Aog7wwTWHX6weODxR8Cf9p+5PBG+N3V0HyE4I47Awrnm+COy2f6uVS/CpEesmn6yrKgbo3Z7zi9ULAAXP72uyxW76njJ8/v4NE39pPwFUPRuSZIE62Hpq3Hv14REREROa0pECMiIiJykkgPxBQNZFky6D0QkypL5vKZs8Vt90WgIS3LJKf0yP1hUmXJvAOXDZPyicXjbbcrm8I8umZ/D9vUeyAmcyCzkET6mcPh4HvvmU1OwJ7xsf5AI5f+6GUeWmF/v2Z4XTxy2wI+et44bk17v7x1oJGVu/sQBAmOMKW9HE5wZ0JWMZz/Hghk2edVb4VfXgS7Xj7y8gKlUHQ+eLJNP5ea5RA6Qs+aI2neAeEqU3KxcD54Mtlb28qPlm7ngv9+iff+fDk/XLqdL/5lPfc+ucWsM++M9sfuhLajZAWJiIiIiPRAgRgRERGRk0RVs7002YD2h4EugZjMXsZ7CK7U7e5evudogZhURown93i28pjMHZ3HOWPtZZL+68mtHGxIK3cUawJgbZW7233pB7RFhruSbD8/unEOXpf9379Ywp7d4nU5+eXNZ3Hm6DwArphRyqh8e2+nI/WRscma0JnJEhwBOcVw7nUQzLbPaz4Ev78Oln4T4kfow+IOmOyUQKnZx9SthaYdvc/vSaQWmreb63mzwZvLD57dxgX//RL3Pb+DfXUh2/TfvLabt6uazToz24NS9es6g9EiIiIiIn2kQIyIiIjISaK6Ka00WdYglSZLLz/W2zh0L0sWzANvsOe5KalAjDf3eLbymH3m4om2282ROF989C2SXRuRx5uxLLj3eXsPi2y/m5kjBj5zR6S/XTy1hMc+vYjxRT0HRR0O+NGNZ3DuxMKOMbfLycfPs2fFvLC1ih2Hm/u20lQmizcXsqdDbhksuASCaZkxWPDaffDrJVC5sfflOd2QfxZktb+Hm7ZCYx/LhSUiUPemKU2WMQqCI9l0qJH7X3ibDNqY6DjAWY6tLHGu4V3OV5nt2EnSgv96qn35OdPM80jGTGkz9YsRERERkWOgQIyIiIjISaJ7j5gBzIixkpBoP+vbk5YRkxrvKculNu0M9Zyy3ueCabydjJqjwJ7snuf0s8WTi3j3mSNtY6/vrOX3y/eYG8k4xNt4bg+s2ms/4Hz7xZPwewauj43IQJpRnsMTt5/HDWeN7Hbft6+byTtml3Ubf+9ZI8kN2rPAfr1sd99X6smE4vNN8CNnNhTOhrMXQkFR97kVb8Evzod/fhZaqrvfD2ZfkTPNlD4DU2qsYdORt8GyoH4tJMLgyYKcWQD88uWdfM79KG/5buU535f4i+/b/Mr7A37k/Rn/8H2Du92/5cUtFazYVWvKrOWf1d4vpgEat/T9NRARERGR054CMSIiIiIniUEtTZZoMwcvHU5wpq3nSKXJ0jNiskvMZW8ZMbEGc+nJNusaJN+6djrlOfaMonuf2srO6haINxNPwn+9bt+ekXkBbl40ZtC2UWQgBL1uvveeOfzk/XMZnR+kIMPLd945k5sW9Py3HfS6uTntvqc3VRJPHENGiNNjypQVngP5s2HEEph7DkyYYAIrXVlJWPMg/GQuLPux6TvVk6wJkGsCKrTsgvr1Zp+VzkpC0xYIV5u+MPnzwOniQH2I8k2/5LPux3A7en4ut7iX8r+eH/DjJ9aYjDl3oLNfTMsus0wRERERkT5QIEZERETkJNEtI2YgS5N1DbakHyjtuK+H4EpNWiAmpwxcfnD2kkUSbTSXnsEt95Xt9/Df751jG4vEk3z6j2/y4uaDPLwRdtbbH/PFy6fgcysbRk4N184p55UvXcSab1zKh3oJwqTceM5o2+2GUIw1e+t7mX0EgVIovghKLoARV8PUc+GM6RDoYV8WbYbnvgU/Pw92v9Lz8jLHQl77+7h1Lxx+0Vymyoa1HYbDL0HzTnM7d5bJiAFW//1nfNn9f0fd5Itd6/hmzRd4ftXazueQOdZcr18HiSP0tRERERERaadAjIiIiMhJIBJP0BCK2cYGtDRZb1kvyYQp7wPg6kNGTE5p72XJoDMjZpD6w3R17sRCPrxorG1sa2UzH3lkL998xf41edaIHK6ZXT6IWycyfIzIDTC9zF468Lkth49vYU4X5EyFUe+E8R+Bie+EeXNhVAk4e/j3tGY7/O4a+Out0FLV/f6M0e1ZLh6z36pfD5XPQfXrULvKjLl8JpMlYxQArZuXcvXu/+y+LLcPMguxnG7b8HTnXs54+t1ED7f3i8mebkquJcLQ8NbxvQ4iIiIiclpRIEZERETkJFDd3L08z4CWJustEJPqD+P0gMtrv6+tHkI19rGjBWKiDebSk3u8W3pCvnzFVMYXHmH72n3lqqk4nY6jzhM5VS2ZXmK7vXTzYayeSoH1lTsIBWfC1H+H6XfClLPgrNlQlNfz/A1/hgfOgref635fsBxKl0DuDJOBl4hApL2vS9ZEKLm4IwhDxVt4/nozHkfCtoj6KZfCDXfBu76B4+pvEm3PnEkpoo7W338AoiETTMo70yy/rRJa9x3/6yAiIiIipwUFYkREREROAullybxuJzkBTy+z+0FvgZgjlSWr3Wm/7XBCdnHvgZh4CJIxMy/toOdgCXhdPPCBMynL6b3M20VTilg0oXAQt0pk+Ll0mj0Qs6c2xM7q1hNfsMsP5ZfBWQ/A2KthziKYOxOyetgnhBvhjzfAmt91v8/phszxUHqJyX7JHA8lF0LONHMfQLgJ65EP4E0FlNu9kHkFeUu+aPZDbRXgqsWz5MMcdJbZ5uW17oSnvmhueHMge6q53rARYi0n9jqIiIiIyClNgRgRERGRk0BVkz0QU5Tpw5Heu6U/pQIu6eXHegvQQPeyZNml5gCoO7PndXRkw2SbYMwQmV6ezdOfXcz/u24GZ4yy96rxe5x85appQ7RlIsPHzBHZlKSVQzzu8mQ98efD1M/BxI/DuCtgwRKYNhvc9jJhWAn457/D89+GnjJyHE6T/ZI7o/t+6pmv4mg8YBv6Z2IBRRd9ECJVJjMvaxJ483D4Heyd/yk2J9P656x9CNa195bJHA++QrNNdashGT+x10BERERETlkKxIiIiIicBKqaw7bb6QdE+5VldZYg6600WU/9YWp22G/nlPa8jJRYo7n05PR8/yDKCXq4aeFYHv/4NF74YJLPLXDzgfmj+ePHFzC5ZGiydUSGE4fDwZK0rJjnNvdjIAZM4LbkQhj5Dii/FKYtgSUfhtLR3ee++gP4260Qj/Zt2dufgbV/sA2tSk7hzyWfYVaJwwSEsydD8Xkw6t0QKGdeUQ13Jm+nxUrLmPvX56B6GzgckH+myeqJtUD9uuN51iIiIiJyGlAgRkREROQkkJ4RU5zVeymtE5YImWCMw2kOMHZ1TBkx7QdtXT2UMYPOQIw397g3td/FmhifB589L4973jWLeWN66VchchpK7xOzZl89tS3d+1edEIcT8uaa8mJ5Z0DBVLjwVph2bve5Gx6FP98M8aNsQ6gO/v4p21CzFeDO2Kf46FxMAKhwPmRPgUApZI6G8svxZY+lrDjAV2Mfty8v1gZ/vsn0i3H5oOCs9n4xFdCcth8UEREREUGBGBEREZGTQnpGTPFAZsR0Dbaklz+Lt3Tely49EJNbBu6AaWzdk47SZEOfEdMh1mwuPdlDux0iw9DC8QUEvZ3vZ8uCF7ZW9f+KHA5TWix3hgmMBEfA2TfCOdd33ydtfwr+dBPEwj0vC0wps9Ya29D/i3+IguIiLhwNZE/rHnTOHA+F53D+GC//SC7i4fjF9vurt8Ez/2Gue/Mgd6a53rgFwtXH/pxFRERE5JSmQIyIiIjISaCqOT0jZpACMV0lYxBvM9c9aeW6kkmo3Wkfyy7tuYQZQDxkludwdl/WUIqnAjHDaJtEhgm/x8XiSUW2sX7tE5Mua6LJinH5TP+W6ZfBxZ8Cl8c+b8cz8MgHugdjLAte+xFs+adt+PnEXB7nQr5/SRKHLw8y0vrApOTMYPHUkQDcHb+ZLcm0EmlrfgdbnjDXM8ZARvv9dWtMqTIRERERkXYKxIiIiIicBAa1NFlvgZhUtog7AM60A6FNBzuDNCm5ZX3oD5NlgjHDRUyBGJEjSS9P9sr2GsKxxMCtMGMU5J9tyoe5M2HiRXDFF8Httc/b+Tw8eCW8/bwJDIfq4P9ugKV32abVW5n8R+zjfGmhxaQCB+TN7p5lk+JwMGHiWZRlQgQvn479OyErLQj+909Bc4W5njvLZMckY1CzvHNfKiIiIiKnvWH0X6+IiIiI9CY9I6ZosEqTdRVrah/vIUhRs81+2xOEQG7vgZhoKhAzjMqSJcLtWToOc8BXRLq5aEoRzi5xi7ZYguU7awd2pYESE+QA8z6dcBlc+RVwp+0HD74JD10PP5kNPz0Ltj/bbVHfiH2E8SPy+egcIHPCUcsQOlxeFk80+6ldVjnfjt9knxBuhL/c3NlXq+AcE8hNhNuDMaHjfdYiIiIicgpRIEZERERkmIsnktS2DkFpsvSyYqlATE8HLqu322/njWwPaBwtI2YYBWI6Mn4yhleWjsgwUpDpY96YPNvYUxsrBn7FGaMhc5y53lYBk6+Bd3wNPD1kBzbsh9buwaGfxa/hRfcivn9JAqfbD1mT+7Tq86eN67j+SOIilibPsk/Yuwpe/ra57vJC4ULwZJoswZrl3bMFRUREROS0o/8wRURERIa52tYolmUfG7DSZJYFifYzuNODKPEjNLJPz4jJLe15GSmpQIx3GAViUs+vp4wfEemwZJq9PNkT6ytoicQHfsU5M8BfBFYCWvfCpHfBO74KgSPvR+qsTG6N3sl34+/nm+c7GJUNZE8Bp6tPqz13YhGdSUAOvhT9OFFfrn3Sq/fDjsfNdZfPBGPcGSYjRmXKRERERE57CsSIiIiIDHPp/WFcTgcFGd5eZp+gRKizxI4rLdjTkRHTQ6AiPSMmp8xc9hSISYQhEWnPmDlyWaBBdaSMHxHp8M65I2zlyULRBE+8dWjgV+xwQP689gBHG4QPweQb4MYfwrkfgfxR3R7ySmIWl0e+y9LkWVwzPYsbpsbN44Mj+7zavAwvs0d2BnvqyeZvIz5vn5SIwd/vhMoV5rbL3x6MCZogTNUyiAxwCTcRERERGbYUiBEREREZ5qqaw7bbhZlenM5emkufqHiXbJiuDazjbZCM994/pVtGTDm4Az2X+Er1h3Fn9vmM9EGRKk3WU6BJRDqUZPu5eGqxbeyR1fsHZ+VODxScDQ4XhKtN8LjkfJj5DnjXPbRc+jWWus9neWI6X419jFtiX6aaPM6fWMAPLmo1u7XsKcdcfvD8SUW223+onwNzb7RPaqmFv98B9ZvNbXcAis4Fby4ko1CzAloH6XUSERERkWFFgRgRERGRYa6qOb0/zACVJQOIt5jL9EyWVLaIO6v7AczWWgilnemdW957w/vh2B/Gsrr0iFEgRuRobjx7tO32uv0NbK1sGpyVe7Igd4a53rTFlAIrvQQK5vH1HWdwa8u/8f7Y13k4cQkWTuaMzOFn12bjdcRNxlug/JhXef6kQtvtTRUt1FzwfSibaZ9YsQWWfgsaNpr9issPhYsgWA5WEurXQeNmutWbFBEREZFTmgIxIiIiIsNcemmy4izfwK0s3kt/mCOVJatJK0vm8kBWce/9YaIN5tKbe7xb2f8SbabvhMPZ+3aLSIeLphR12xf9abCyYgAyxkCgzAQ06t4EK8n6ugwe3xqzTRtflMFvbp5DZmyPGcieYs/266O5o/PI8Noz+F57uxo+8FfItGfLsPlZePNBqF0JyZjJ/Ms7E7Inm/ubd3beJyIiIiKnBQViRERERIa59NJkxdkDGYjpJSMm1ci+p/4p6WXJckaYA4+9BTSGY0ZMR8ZP5nEdpBU53bhdTt57lr3PymNrDxKOJQZvI/LmmPJf8Vas+vXc8+QW291Zfje//+g5FCR2mUCrNxcCpce1Kq/bycIJBbaxZzfsgaxSeP+fwJXWt2vZb2Db01C9zPSIcThMECj/zM6yalWvdmbiiYiIiMgpTYEYERERkWEuvTRZ0YCWJms1l67eMmJ6CMRUp2XE5Jb3vAyARAQS4d6XNVTUH0bkmN1w1ijb7YZQjGc2VQ7eBjg9JtPE4eDFLQdZsavOdvdnLprASGsbtO4zA9nTTmh1F6X1xXlhZxuh1noYMQ+uuc8+OZmA538CO14yAZfQQTMeHGH6xrQHkKheBm2D+JqJiIiIyJBQIEZERERkmOveI2aAMmIsyzS+Bns2i5XskinTU2my9IyY0u7LSOnIhskEp/vEtrc/HSnjR0R6NKYgg3Mn2rNEBrU8GYAvn3jmVO593Z7JNiLXzy2TKiB0wGSj5M4Cf2EvC+mbK2aU4nJ2rqct7uD5dRvNjTM+APP/zf6AVDDm7ZdN+bTaNyARBW8OFC0GXwEk41C7Gpq2qW+MiIiIyClMgRgRERGRYa6qyV6arCR7gDJiEm3mQKDDaRpMp8RbzLjTY87iTtctI6bUHPh0B7vPjQ7DsmTQ2bdmuG2XyDB349mjbbdf31nL2n31g7oNf9nmZUedPRDz+bMj+JMNZr9VsAAyx57wegoyfSxKK0/2z02NnfuPy++BuR+0P8hKwos/h63PQNshqHrJZMC4vFC4ADLHmXlN26HuDROYEREREZFTjgIxIiIiIsNYMmlRPVgZMamyZO4Me5+UjrJkPWTDRFuhcZ99LHcEuAImoJNuOPaHScY6n7s3d0g3ReRkc9n0EnKDHtvYjb9YwW9f2401CBkeoWicHy61B4OnF1q8c3LCZN4Vn3/CmTBdXTOn3Hb7pT3QVN3em8bphGsegDNvsj/ISsKyP8CK30CkzmTA1K01fWtyZ0LeGWZ/2VbZ2VNGRERERE4pCsSIiIiIDGP1oSjxpP1gZnH2IARiuoodoWxXzY60AYcpTdZTWTIYnoGY1Nns7gxz9ryI9Jnf4+rWKyaaSHL3Pzdz6+/foLYl0ssj+8f9L7zdrXzjV6+ajjNnKhSd1/u+6DhdPqMUj6szUB1NOnh2c40JsIAJxlz9E5h3S/cHb3wRnrsPGndC6144/KIJvmSMgqJFJhMx1gxVyzoD4CIiIiJySlAgRkRERGQYSz/A6HBAYeZgB2JSGTF9CMRkl4LbB+7M7nOTMYi396DxDsNAjLJhRI7LHUsmccao3G7jz22pYuG9L/CpP65h6ebDROPJfl3vmr31/OLlnbaxxZOLOG/6eMieNCCB1ZyAhwsmF9vGnnjbAY0bO3u8OJ1w9X1w1ke6L+DAZnj251CxGsLV7dkxb4Irw2TveHMgGYXq1yE6uCXeRERERGTgKBAjIiIiMoylB2Lyg148rgH6Cne0QIy7h9JkNdvst/NG9bwMGL6ZJ7EGc6lAjMhxCXrd/Pm2hdx6/rhu90UTSZ7cUMmtv3+DBfc+z69e3UUyeeIly0LROJ//8zq6LsrjcvDVq6ae8LKP5po5Zbbby/Y7qGtshND+zkGHA97xI7j0ru5lGhsr4LnfwO4V0LILWvaY3jHReihcCL58E7iuWQGR2oF+OiIiIiIyCBSIERERERnGqprCtttFA9UfBiDeYi5dXYIoyRgk2rehp4yY6rRATG77AcqeAjGpsmTDKRsGOgNEntyh3AqRk5rX7eRr75jObz9yNgUZ3h7n1LVG+c6/tnDLb1dR1RzucU5PDtSH+M2y3Ty9sZJwLAHAfz21lT21Idu8O5ZMZmppD/upfrZkWgl+T+e/0vEkPL0TaNxi9pkpDgec+zn44J/BlxbIjobgld/D5hXQtB1Ch6D2DWhYD7lzwVcIybgJxoSrB/w5iYiIiMjAUiBGREREZBhLz4gpzvYPzIosCxJt5nrXIEpHNkwAnO7uj6uxN8kmu7j7MjqWNQz7wyTC5sfhGF7bJXKSumhKMU/dcT7XnVGOt5fsvVd31HDVfa/y8vYjBxgsy+KhFXu55Acv8+0nNvPJh9Zw9nee41N/XMPvl++1zZ07OpfbFo/vt+dxJBk+N5dMLbGN/XOn25QUa9rW/QETL4VPvAwF3TOGWP8kLH8CQjXQvMNkx9S8BtmTwV8CVtKUL0v1oBERERGRk5ICMSIiIiLDWHV6IGagMmISbeaAn8NpGkandARiejjLPBGHWnt/BnLK2pcR7D4/OgwDMR3l0jLB6RrSTRE5VRRn+bnvfXNZ9bVL+M47ZzJvTF63OTUtUW75zSo++uBq/vnWoY5Ml5SGUJR/e+hNvv74RiJdess0R+I8uaHSNtfvcfKD987BPVBlG3uQXp5sxf4kVa1A6x6INXd/QMEE+MSrMHlJ9/sOboBnfg6huAnGhA6YTBhfIfiLwUpA7aqelysiIiIiJ4UeTmsUERERkeEivXzPgAViuvaHcTg6x1MH/noqS1a/216GByC3vPsywMxLrWM4BWI6yqXlDulmiJyKcoNePrRgDB9aMIblO2u5409rOdxkDy6/sLWKF7ZWkeVzM398Pm6nCaa8daCBisa+lS/7ypXTGF+U2e/bfyQXTikm0+emJRIHwAL+tjObT85ugoaNULSw+4N8WfD+v8Cr98KL/22C3ykt1fDkf8Oim6Hca/aXVhwCI83+N9ZkgjNF54K7h0C3iIiIiAxryogRERERGcbSD0SWDFRpsq6BmK46yon1oT9MMB/8mT3P7VrizNVz/4ghof4wIoNi4YQCnvrsYi6ZWtzj/c2ROM9tqeLpTZU8vamyxyBMenwX4LyJhdy0YEx/b+5R+T0uLptuL0/24LoY0aQTIjXQuq/nBzocsPir8ME/QSDXfl8iCq/+Ct56FSwnNO2A1r2AZTIVE2ETjElEelqyiIiIiAxjCsSIiIiIDGMVDfaDkWU5gxiIsZKdARRvD1ksNWmBmLxR7cvI6j53OPaHgc5AjDJiRAZcfoaXX91yFnddM50Mb99LAeYFPfzq5rN4/T8u5stXTGVKSRY+t5NFEwr40Y1n4HT2EKEZBDcttAeAKpsi/GN/qbnRsPHIpcQmXga3vQyl07vft/UFWPZ/4M6H5m0QPtxZOjLeCrUru2cjioiIiMiwpkCMiIiIyDAVTyS7lSYrzw0M0Mp6CMTEW8zBP6ene6YMQM0O++3ccnPp6SEQMxz7w8RDprm2w9lzFo+I9DuHw8GHzx3Hyq8t4fvvncO5Ewt6zHRJWTA+n6c+u5gl00soywnwbxdO4JnPLWbbd67k4VsXUDRQ5Rr7YO7oPM4Zl28b+99VLVi+QtPXpW4NJBO9PBrIHQsffxHmvLv7fQfWw/O/AHcpNO+EaJ3ZHyfjZn9au9pe2kxEREREhjX1iBEREREZpg43R0ha9rEBC8Qk2gMxri4Bl46yXb0ET9JLk2UXts/vKSOmfVnDKfOk4/llm2CMiAyaTJ+b98wbyXvmjaSisY3ntlRR1xLtuN/hgDNH57FwQgGuIcp46YvbFo9n1e66jtvbDrfwUvUZXJTXYjJiGjdA3hm9L8Dth3f9BkacCc/cbcqTpRzeCs/+BC79DLTsgYzR7SXK2iBSawI9+Wf1XLNNRERERIYVBWJEREREhqlDDW222z63k7ygp/9XZFkmOwTsmS8djex7CMQkk1Cz3T6WUw4OF7jSGkknExBrMdeHU0ZMKjg0nLZJ5DRUlhMYkj4v/eGiKcVMLM7k7aqWjrFfLtvPRbecCTXLoXU/+AohOPLICzrnM1A0DR65GSKdy6J2Fzz1A7jiTmg7CP5ScHo7988N6yFvzgA8MxERERHpTzr1T0RERGSYSg/ElOcGcAzEmc+Jts7+A64uPWiOVE6sfjdEW+xjeSNMNkz6NqYOGLr84Bq6MkLdqD+MiJwgp9PBJ84fbxtbvquWDdVuyJpsBurXd+5vjmTcJXDz3yCYZx9vPAjP3mfKlEWqIREyAfRIDbTug/p1KlMmIiIiMswpECMiIiIyTFU02vvDlOX4e5l5gjr6wwQ7gyiW1SUjJrf7Yw6ttd8O5puDhz2WJRuG/WGO9vxERPrournlFKf1qvnFKzshaxL4i0y/mJoVEGs6+sJGzIdb/gFZJfbx+n2w9H7wlpvlxJsBC8IVJuumZiUkY/33pERERESkXykQIyIiIjJMVaRlxJTlDFB/mI5ATGaXsWZzhrXT3b3UGEDFOvvt4kkmiOM+QiCmpxJnQyXeappeO1w9b7OISB/53C4+fO5Y29iTGyrYVdNqerh480yQpGZF5/72SEpmw4f/Cbnl9vHq7fDCz8E/0gSTow3g8Jn+MeHDUP0axNt6WqKIiIiIDDEFYkRERESGqUNpGTHluQOcEdM14NK1LFlP5dAOrbPfLmjv79BTRsyRSpwNlVR/GG8vz09E5Bh8cP4YMryujttJC771j01YDhcUzgdPNiQipm9MX4IlBVPgpschs8g+fnAdvPIgBEaaIHK4wux3m7dD22GoftVcioiIiMiwokCMiIiIyDBV0TjIGTGeLhkxHYGK3O7zLQsq1tvH8ke0LyM7bW6yvYQOwysQE6k1l968I88TEemDnICHmxeNtY29uqOGJzdUgtMDhQvMPjbeBjWv9z0Y88E/QSBt37nrVVj+JxOMCY6G0H5wuKH5bWjZa8qU1a6GRLjn5YqIiIjIoBvSQMwrr7zCNddcQ3l5OQ6Hg8cff9x2v2VZ3HXXXZSXlxMIBLjwwgvZtGmTbU4kEuH222+nsLCQjIwMrr32Wg4cOGCbU19fz0033UROTg45OTncdNNNNDQ0DPCzExERETkxFQ1pPWIGKiMmcZSMmHR1uyDSaB8rHGsONrrStjHWZAI3Ti+4ByiQdDzCVebSV3TkeSIiffSZiyZSmm3fB377iU20ROLg8kHhQtOLKx7qezCmbB7c+CB400pEbvkXvPEPyJoIOTPMfjYZMRkyjRuhcRscfhFadpmA+DGqa43y7KZK9teFjvmxIiIiItLdkAZiWltbmTNnDg888ECP93/ve9/jhz/8IQ888ACrV6+mtLSUSy+9lObm5o45d9xxB4899hiPPPIIy5Yto6WlhauvvppEItEx5wMf+ADr1q3j6aef5umnn2bdunXcdNNNA/78RERERI5XOJagtjVqGxuROwCBDMsyBwWhs0eMZXU2le4pEJPeHyZYAMH8nsuSDcf+MLEmc6a4wwW+gqHeGhE5RWT43Hzzmum2scNNEX68dLu54fJD4SJwZ7QHY17r3P8eydiL4d3/A26ffXzdw7Dm71B0PhTMg+Co9izEFmhYB/VvmeyYwy9A6z6zbz+KWCLJL17eybn/9QKf+MMaFv/3i3z1sQ3UpX0eiYiIiMixcQ/lyq+88kquvPLKHu+zLIsf//jHfO1rX+P6668H4He/+x0lJSU8/PDD3HbbbTQ2NvLrX/+aP/zhDyxZsgSAhx56iFGjRvHcc89x+eWXs2XLFp5++mlWrFjB/PnzAfjf//1fFi5cyLZt25gyZcrgPFkRERGRY1DR2L2kTFnOAGTEJNrMgTuHszObJd4MVgKcbnPAMF16f5jiyabPSk9N76MN5tKT248bfYJS/RN8heZ5i4j0kytnlrJ4chGvbK/uGPvt63t497yRTCvLNpmBRYug+nVTFrLm9fZMmR72tV1NeRdc2wCPfwGS8c7x5Q+APwcWfxEyx0HjZmjeBeHD0FYJoQMQKINQBQRHQPZkCJT3uO9bs7eerz22ga2VnSc+WhY8vHIfT7x1iDsvncyHFozB7dJ+U0RERORYDWkg5kh2795NZWUll112WceYz+fjggsu4PXXX+e2225jzZo1xGIx25zy8nJmzpzJ66+/zuWXX87y5cvJycnpCMIALFiwgJycHF5//fVeAzGRSIRIJNJxu6nJnBUai8WIxWL9/XRPWqnXQq+JyPCg96TIyeNo79f9tc2225k+N37XALy/Iw04EnFwZ2LF2w/uhWrMmCunc6wL16G1trTqZMFYkok4lsMPadvnaKuFRBzLEex231BxtB4y2+TOGzbbJMObPl/lWHzzqilctauWaNyUBEskLb78l7f4w0fPIuh1Ay7IPRtH7QqINEPlK1gFfQjGTP0gzktrcT77nzi6lht78T9JNBwgefm9UHgxZE7D0bgZmrbiiFRDywHTO8ZXhNW4AwLlWJnjITgGXD7CsQTffWY7D63c3+uqm8Jx7vrnZh5ZvZ+ffeAMRuYNo1KTR6H3r8jJQ+9XkZOH3q+d+voaDNtATGVlJQAlJSW28ZKSEvbu3dsxx+v1kpeX121O6vGVlZUUFxd3W35xcXHHnJ7ce++93H333d3Gn332WYLBYA+POL0tXbp0qDdBRLrQe1Lk5NHb+3VVlQNwddzOdMZ48skn+339geRhspN7iThyaXCZEjlZyb0Ek4cJOUtpdtbbH2BZXLl/Dd4uQ9tqWml84w3qXC3EHFu6zE1SkngTSFLjipFwpJXVGQIOK05xYi1gtW/T5qHeJDmJ6PNV+uriUidPH+gMWa8/2MQ7f/w8n5iaINj+X7jTipGX3IrbaiPJSupcU0k4jhLgsMYzdeSVTNn/L9uwa+3vaNi+nNXjbifSXlLSaxWSlQiRlazFZzXgtfbjZDVxh58QBUSd+WwLj+GnO0dzqM3Tp+e1tbKZ6+5/hU9MTTAqs++vx3Cg96/IyUPvV5GTh96vEAr1rafesA3EpDgcDttty7K6jaVLn9PT/KMt5ytf+Qp33nlnx+2mpiZGjRrFZZddRnZ2dl83/5QXi8VYunQpl156KR5P3768i8jA0XtS5ORxtPfr7pd2wc63O25PHlnIVVfN6/8NadyEo7UIK2OcafgMOGpeg2g9Vt5cCIywz6/fg2ed/YvmpHMugMwCrNLLwNklRBNrxFENOD1YpZf3/7Yfj7ZDOOqdJgOo+MKh3ho5SejzVY7VJbEEmx94nX11bR1ju5sd/OFAHr+5ZR4FGe37ysQVOOpWmt5VTh9WwYKe+211lbycxMtfx/X6b2zDBa3buXzvvSTe/SDWiDM774g2QPN2HA3rcUSqIFKDFW3ikf25fGfLWMIJF+mmFAf43JJJ/GtjFf9cbz+BsSnm4H+2+bjvxtlcOLnomF6XoaD3r8jJQ+9XkZOH3q+dUpW0jmbYBmJKS0sBk9FSVlbWMV5VVdWRJVNaWko0GqW+vt6WFVNVVcWiRYs65hw+fLjb8qurq7tl23Tl8/nw+bqftenxeE77P66e6HURGV70nhQ5efT2fj3cbG+MPCIvOEDv6yi43ODPBY/HNARIhsxYoNCMdVW90X47kI87uxjcfvClldWJti/HV9B9OUOlpd5sU+aI4bNNctLQ56v0lcfj4WcfmseHfrWS+lBnuYrNFc186Ddv8Mub5jG+KNPsh0rOh5rlEGsiUbeKeJdgjNPhwNOtJ4sHLv4O+LPg5Z9BovPzwtF8CPeDl8PcD8HF34CsEvAUQUYRFM6F0H6shi38x9I2/rSj+wmGfleCO2fu5SMzW/H4d3DFReO4+YzRfOWpGt6u7gzCh6IJPvnHdfy/62bygfmj+/fFGyB6/4qcPPR+FTl56P1Kn5//sO2yN27cOEpLS23pTdFolJdffrkjyDJv3jw8Ho9tTkVFBRs3buyYs3DhQhobG1m1alXHnJUrV9LY2NgxR0RERGS4qWhss90uyxmgevyJVnOZ6k0QbwErAU53z/0KDq2z3y6ZBg4HuHs4gzvaYC69uf20sSfIsiBcZa77upeuFRHpTzPKc/jTbQspyrKf4Pd2VQuX/PBlPv67N3h9Zw07aiL8YksZNz7uYer/xJly92tM+frT7T9P8aFfrWRrZdqZlu4MWPB5uO7/QUZB2potWPsHuP9MePWHEGv/PHEHIXsKD+6b02MQZmpOM09c9CqfGLsWT9MGOPwi7HmEsyMP8dclG1g4ImGbn0hafPWxDfx5de+9ZURERETEGNKMmJaWFt5+u7Pkxu7du1m3bh35+fmMHj2aO+64g3vuuYdJkyYxadIk7rnnHoLBIB/4wAcAyMnJ4WMf+xif//znKSgoID8/ny984QvMmjWLJUuWADBt2jSuuOIKbr31Vn7xi18A8IlPfIKrr76aKVOmDP6TFhEREemDioaw7XZZjr//V2JZEG8/wzkVdIk1mktPtgmwdNuwdfbbxRPb5/cQiIk1mMvhEoiJNUEiYoJMvvyh3hoROQ1MLsni0dsW8sFfreRgQ2eA3bLguS2HeW5LevUG+343acGyt2t4509f4553zeL6M0d23unNgek3Q1YxPPNfULnNvqhoCzx/N6z8OSy6HeZ9hA3VCe59amu37bxlfhlfuXgm/tgEaKuASBVEqqGtEsJV5FiH+N05O/jy2rN5bI898PMff1tPXoaXS6f3XnFCRERE5HQ3pIGYN954g4suuqjjdqonyy233MKDDz7Il770Jdra2vjUpz5FfX098+fP59lnnyUrq/Mf/R/96Ee43W5uuOEG2trauOSSS3jwwQdxuTrr3P7xj3/k3//937nssssAuPbaa3nggQcG6VmKiIiIHLtDaRkxI3IHICMm0QZWEhxOcLUvP5XF4sntPt+yumfEFLSXpPGknV1tJSHW3H5fTj9t8AnqyIYpNM9ZRGQQjC3M4NFPLuRDv1rJrprW41pGOJbkzj+/xeo99Xzrmun4Pe3/77qDMPpquC4P1vwR1v0D4hH7g1sOw7NfJ/nqD1kZv4KsxPnU0rlf/sn753LtnPL2W2M6HxdrgZZd0LgZwlV4m9/mh7OWUu5fwE+3ju2YlrTgMw+/ye8/eg7zx6dn54iIiIgIDHEg5sILL8SyrF7vdzgc3HXXXdx11129zvH7/dx///3cf//9vc7Jz8/noYceOpFNFRERERk0zeEYzeG4baxsIAIx8VRZsmBn9ksqI8bbQ/CkYS+EG+xjee0H79IzYmJNJhjj9JrlDweR9kCMX2XJRGRwlecGeOzT5/LTF9/m/1bt67aP76v/W7WPF7dWcf6kQhZOKGDhhAJTurJkMSzMhMmL4Y1HYfurgP1/bWdbHR/nYW7x/YkXknP5U+JCJp/7zi5BmDSeTMibDTnToe0gNG7F0bSNLzrfJJmM8rPtkzumRuJJPv67N/jTbQuZXt697JmIiIjI6W5IAzEiIiIi0l1FY7jb2ICUJksFYlztZcksC6Kp0mS53eenZ8ME8iGQ2XOPmI7+MMMkGyYZg2i9ua7+MCIyBHICHr561TQ+e8kk/vrmAX772h52t2fIlOX4uWhqMRdPKWZCcSaOSA1WwwZ+vRYe2mgvV1bZFObRNQd4dM0BAMYVZrBgfAELJ4zgnJIiii4oxTX9Ulj9Jzi4sdt2eBwJLne9weWuN7A2/hoazoaRZ8PIs6BkFmQU2ktTOt2QMQYC5RAohYzRfClzC7XhXfx53/iOac2RODf8YjlfvWoa7z9nFI6eyluKiIiInKYUiBEREREZZg412MuS5Wd4O8vQ9KeOjJj2QEy8BawEOFydY12l94cpmdYZhHGmfa2MHSGgMxTCh02gyZMF7gHILhIR6aMMn5ubF47lQ/PHsLmiCb/HxYSijLTARQbkWHwnZwNnlcNXXnTRFkv2uLzdNa3srmnl/1btA8xuOds3iVzfVyiO7+A2x99Z4lrb42MdbfWw41nzk+LNhLxxkD8WRpwFk6+Aoing9EDeHAiMwOHJ4p5L91L/r0MsrezMqGmJxPnqYxt4Yv0h/uv62YwuGCYZkSIiIiJDTMWxRURERIaZ9IyYAcmGge6BmK5lyXo6kzk9I6ZoQvv8vO5zOzJick9wI/tJ635zGeilBI+IyCBzOh3MHJHDxOLMnrNHMsdCxijeOdniHzc6mVme1X1ODywLGsNJ9jY6WB2fzMdjX+QdkXv4a+I82izv0RcQbYHDG2DLP+G5b8H/zIf75sBTXzafA/5CKL4Ad8EZ3H91DucU1nVbxOs7a7n8x6/wq1d3EU/0HEASEREROZ0oECMiIiIyzFSkZcSU5QxQBkciLRBzpLJkyQQcXGMfKxhpLtMDMckExJvb7+thWYMtHoJIjbkeHDW02yIicixyZoEnm0m5Uf75PhdPf/Y8vnXNdC6dXkK2v+8FLjZZY/l87FMsiP6Ul0Z9FIonHdt2NOyFlT+HX14Aj38aQvWQfyb+0nP47buyee+46m4PaYsl+M6/tnDdT19j3f6GY1ufiIiIyClGpclEREREhplDaRkx5bkDkBFjWSZAAV0yYhrMZU99XSo3QKTJPtZbICbeZJbv8oFrgLJ5jkXI9FHAV6iyZCJycnG6IH8eVL+KI1rH1KxDTD13Gh85dxyJpMWWiiZe31nD8p21rNpdR2s00W0RLqeDeWPyuHhyPpeNjTM+UAjxi6GlBg6/DdVvQ9UuqNlt+mkdzbqHYOs/4aKvw1kfJWNULv997WquXr+Vr6wo4VCbvbTlpkNNvOt/XuOmBWP44uVTyPJ7+uvVERERETlpKBAjIiIiMsxUNA5CRkwiDFYSHE5wBUzgpCMjpodAzN7X7Lfzx0Eg2/QMSO8nkypLNhz6w1gWhEzfBDJGD+22iIgcD08m5M6BujXQ/DZ48yFQgqu9tNnMETl8YvEE4okk1S0RGkIx6kNRGkIx/B4n88bkkxPoGvyYAZE6yDgAeeNh4kKzr0wmobUOmg9DUxXU7IH9a81YunAjPPVFWP8I3PgQFF/ABXMDPFO0nP9a5eOPeybYplsW/H75Xp7fUsUPbpjDgvEFA/qSiYiIiAw3CsSIiIiIDDOHGgYhIybeYi7dQdMPJtYCVgIcLnBndp+/Jy0QM+IMc+nN695PpqM/TA8BncEWqYV4mwkY+UuHemtERI5PsByiddCyG+rXgmex2X934XY5KcsJ9C1478s3P2DKScYazU9OmwnUJ8KQCEEsBHX7YM9q2Pg0xOyfTxxcA7+8EN73MIxYRJY7k//0LeVdo1/la+vmsK0p2z69oY33/+8Kbj1/PHdeOhm/x3UCL4qIiIjIyUOBGBEREZFhxLIsDqX1iCnPHYiMmPayZK4eypKlB1aSSdj3un2sbFr7/LSyZGAO5sHwyIhJZcMEyk2JHxGRk1XOdBPojtab7Jiic01W44lyuuyBma7ibVBQC6PPg+mXw4o/wM60z4OWw/Dbq+Dan8Cc94Eni7Ocf+eJ/GX8avto7ts+g3C883PFsuCXr+zi5W3V3Pf+M5hamo2IiIjIqa4fvrWJiIiISH+pD8WIxJO2sbKcAciIiaUyYtoDMUcqS1a9Bdrq7WPFY81leiAmGYdYc/t9Q5wRk4xBW4W5rrJkInKyczhNvxinxwRkGjcN/DrdAQiOhLwzYPx74Or/gnd8HbJL7PMSEXjsNlj6LcgcD2Pfjyd7HP827SBLL3qa+WXxbovedriZax94jT8s34NlWQP/XERERESGkAIxIiIiIsNIejaMwwEl2QMQiEllxLjTM2Jyu89NL0uWOxr8wZ7nx5rMpctvfoZS2yHTB8eT1fPzEhE52bgDkH+mud6yB0IHB2/dLi/kzYE5n4D33AflM7vPee3H8MTnwFcC4z8MmWMYlevh/855nK8tCOFNS0yMxpN84++b+ORDa2gIRQfjWYiIiIgMCQViRERERIaRikZ7/f3iLB8e1wB8ZYu3mkt3hqkTkwqg9JQRs3eZ/fbIee1zs8yZ2V0dKaAz2Frby5IpG0ZETiX+YsiaZK7Xv9W5/x4s3hwYdQW856cw47Lu96/5LTz+b6Y85fiPQXAkTm8Bt5Y8yT/e1cC0ou6fac9sOsxV973KnprWgd9+ERERkSGgQIyIiIjIMFLRaM+I6VPT5WNlWfZATLzVlBRzuMCd2X3u3rR+AOUzzGVP/WGiDeZyqPvDxJrNtjgcEBgxtNsiItLfsqeArxCsBFQvH/xgjMMB+WfAld+D8z/WvVfN+kfgLx8BVxAm3ArBEeArYmr8BR6/5jAfOaN7z65DjWHu+NM6kkmVKRMREZFTjwIxIiIiIsPIoQZ7Rkx57kCUJQubkl0OJ7gCEEv1h8k2B9e6qtkOrdX2seLx5vJIgZih7g/Tsttc+kvB5RvabRER6W8OBxScZbIPk1Gofn3wgzEAmeNg0Zfhks+CMy24suUf8OebwOmH8R/tCMb4GlbwrXkH+PU1LvKDbttD1u1v4G9rB7HcmoiIiMggUSBGREREZBjZV2cvyzIidwAyYjqyYYLmYF5H8CS3+9w9aWXJskeAvz04lB6IScY6lz2UGTHJGIQOmOuZ44ZuO0REBpLTA4ULzL44GTPBmGjj4G9HoATOuQMu+wK40spVbn/aZMa4gzD2QyYY48mDhvVcUrSbp96XZGy+/YSD7z69lZZIfPC2X0RERGQQKBAjIiIiMozsqQnZbo8pyOj/lSTagyWu9mV3ZMT01B8mrSzZ6HOAJDjd3cuYRevNpTvDNHUeKq37TLkeTzb4CoZuO0REBlp6MKZmOYSGIKPEmwtn/htc+R/gTstC3PoE/O1W8xkz+r2QORY8mdC8k5LkNr61yP65V90c4f4XdgzapouIiIgMBgViRERERIYJy7LYW2vPiBlXOACBmK79YSyrMxCTXk7MsmDva/ax8lntc/O6lzGL1JrLoQx+WBa07jHXlQ0jIqcDp9sEY3z5JhhT9ybUrIR429Ef25+8eTDro3DVV8GTVlZz02Pw90+BrwjKr4CsieDyQ1sVF+Vv5eIxSdv03yzbza7qlkHceBEREZGBpUCMiIiIyDBR3RKhNZqwjY0pCPb/iroGYhIhSMbB4QJ3ln1e3S5orrCPlUw0lz32h6lrvy+/f7f3WIQPQzxkzhIPjBi67RARGUxONxQuhOyppv9XuAoOvwgtu0xPsMHiy4cZN8HlX+qeGbP+T/DEHRAcDUXnQc4UcLgh3so3ztiOx2l1TI0lLL7zry2Dt90iIiIiA0yBGBEREZFhYm+tvTyL1+WkLGcge8RkdPaH8WR3z3BJz4bJKIZge4ZOt/4wic5lDWVGTMtuc5kxpnvjaBGRU5nDCdmToPgCExCxEtCwCSqfN/vGwQrI+Apg5s1w2ee794x58/ew9BuQNQny5kLuNLAcjMtO8NEph21TX9haxYvbqgZnm0VEREQGmAIxIiIiIsPEnhp7WbLRBUFcTkcvs4+TZdkDMb2VJQPYkxaIGbMAEm0mYJOe9RJrMAf5XH7TlHkoxJohUmO2L2Ps0GyDiMhQ82RC4SLIm2P2yYkwNGw0AZnmt83tgeYvgpkfgiV3mGydrl6/H5b9EHJmmAyevOlAks/MS1Doj9mm/uCZbViWhYiIiMjJToEYERERkWFiT1p/mLEDUZYsETYBE4cTXAGINZlxTw/9YXa/bB8rn2kuvXndD6wNh/4wqWwYfym4ByCTSETkZOFwQMZoKL0E8mabfWIiDI1boGIp1KyA0AFIRAZuG4IjYNYH4ZLbzWdOV89/G974jQkWZYyFnGlk+eBL59gzQzceauL5N98yJTRFRERETmLuo08RERERkcGwJ6002diCjP5fSUc2TNAcqIu2Z8R4su3zqrd17w9TOtlc+oq7L3eo+8MkY+agIkDmuKHZBhGR4cbhNKUag6PMPjK0HyJ1EK42P2B6anmywJ0JTp/pGeZ0mf4tnuz20pXHeQ5n5jiY+T6IhuDlX9jv+9fnwZcNs94NdQ7AyfXT2vj5Wwl2NXaWlrzvhbe5JG8jjryZ5rn01KNMREREZJhTIEZERERkmNiblhEzpnAgAjEt5tKVYc6OTkZNQCY9ELPrRfvt7JEQ8IMVB3+h/T4raQ7swdBlxLTuM/0QPNlDm5UjIjIcOZwmQyZjNMRDJijTdsiUdEzGzD48tR/v6bHeXBMAyRh37BmHOVPhjA9ApBVWPNTlDgse+4QJ+sx4FzRtwd28k9vPgc8t7Zy1oTbAC1v3csmI7eDJMFmPOdNNnxlv7jG+ECIiIiJDQ4EYERERkWHAsiz21KRnxAxAabJUIMaT2ZkN487sfrbzrpfst8ctMkEYpwc8ufb7Yk0mCOL0mGUNNsuC1j3murJhRESOzB2E7MnmJ5kwnwupn2TM7M+thAnURxvNZSpQ07LHPC5z/LFlyeTOhnkfMsGYtY91jltJ+OvHTTBm+nXgCnLN5I38ZJXF7sbOHmk/3jKZi8fuxBFvMH1umt82nzcZoyFnFmSM6rnX2ZHEW6HtMESqzLJcAfPjDppynY5+7tEmIiIipzUFYkRERESGgdrWKC0Rew38gSlN1h6IcWf23h8mEYM9y+xjI2abS19h94NTXfvDDMWBq/Bhc4a30wOBEYO/fhGRk5XTZQIYRwpixFshWm8yDyO1ps9M6IAJrvj6WI7S4YSCs2B+GGJtsPHpzvusBPzlo/De38G0q3G7Atx+zpvcuTTZMWVDtZMXrXdz8bgoNG2D5h2mJGbjZnPbVwjBkZA1wWTMePPNc+sq1gSNO6Fpa/vnRqtZN4DLC74S8Bd1lmTLmW5ui4iIiPQDBWJEREREhoH0smQel4Py3AFoON81EBOuMtfTD8AdWA3RFvtYyXgg2fNBqaHuD9Oy21xmjOl+4E1ERE6MO8P8BEdC634T/Ig1Q/Vr7SXCJvRtOU4PFC6ARVGTibO5S/2xZBwe/TBc9wDMeR/XLr6Yn7zxEnvqO09Q+PGzm7jo1mk4yi6F0ktMJmT9OggdhEi1Ca40bjZBGU+WCai4vDgSMDr2LM7tb4Ij2WWDHODOAm8WJJMmoN+y05Tu9JdAzQrwF5vn6MnqhxdSRERETmcKxIiIiIgMA7vTypKNyg/icvZzdkkyAfE2c92dCbFUabL0/jAv2W+XzAS3BRbgSwvEWJY9I2awxZohUmMycTLGDv76RUROJxmjTJCiaXNnUCYZM31g+sIdgML5sChugh9bn++8LxmDx26DirdwX/r/uH3JDD7/6Fsdd68/nODxlet519QN5rMoOAJGvgtiDdC6F5q2m8+jcCWE9nc8zpFMEEhWg5VrTibImmJKq/kKTZZMpMo8LlINiSg4XOa6JxvCmOtZUyB7Ur+8hCIiInJ6UiBGREREZBhIz4gZNxBlyRLt63B6TOAi3h78Sc+I2fmi/faYc0zAxZ1haud3leop4HCZg1aDLZUN4y899gbSIiJy7FxeyDvDBPQbt5gyYcko5M7qW3lKby4UngPnJUyPmG1pnzkr/gcqN3Dd9b/h/oIge2o7T1T46otOphcmmVJQZbI6HU6TtRIoh5yZJmgSOtDeAy0OyThWPEKty8eECR/GlTkSorVmTu3OztJkYLI6Y40mqAPg9JnPFctlypnFGs3zduowioiIiBw7fYMQERERGQZ219gDMWMGIhATay835skymSRgDjI5PZ1zwo1wcI39cSNmmsueypJ1ZMPkH1vj5v6QjJmDaQCZ4wZ33SIip7usieD0QsN6E7ywYpA3t2+fBf4iyJ8H51ng8sDmZ+3373kV9/8u5ieTbuPdteOJtR+6aIvDJ5/N4O+3lJFtVZrPtbZK8+NwmaBM5jjwFpiAicOJFYvR8Najps/N4W2QiHSuJ1VyzeGCRBskwiYg07wdWnZBvASCo8ABtFWYkw8KzjaPExERETkGCsSIiIiIDAN7a+2lycYVBnuZeQI6+sNkdJYl86Rlw+xZZj9D2OWF/HIg3r0sGQxtf5jWfWZbPdlDUxZNROR0lzHaBPPr3oTQIcBpskb6khkTHAHJCCy6GQrGwOsPQiLWeX9zBbPX3cWqrBL+O3Q1f0ksJoqH3bVtfP7pVn7xoQtxJprNetsOQbzVBEvaKjqX4XDgSFgUJDbhaA2Ay22CR8ERJgDjze2+XckYBMqgbo35nIk1QOYkcPvNSQxVr5ogUk8nJ4iIiIj0QoEYERERkSFmWRZ7agchI6YjENOlP0x6ObH0smSjzgFH3BxU6ynYMVT9YSzLNGoGZcOIiAylQBnknwV1q02WostnGtz3ReZ4k6EyBcgbCS88AC3Vtil5scPc4/k1/+F+mJeTc3gucSYvbT6D+1/I4d8vmYgjZ6rpURNtNAGZtkOdpTctC6w44MQKlEPW2PYAioOaHavZ9vT/UFC3jhguqlyl1HvLaA6MpLr0fPILz2acu4Ci5E4O7qlgd2wke5p8xJNxbpyxkvnTppqsIBEREZE+UCBGREREZIjVtUZpDsdtY2MHOhDTdshcT8+I2fWS/faoeebSm2cvYQbmoFci3N4fJre/t/bI2irMgTanFwIjBnfdIiJiFygxmTB1a6F5p+mvkjWhb4/NmYap/QVc+y149UHY/0a3admONq5xreAa1wrilpM3XpnCI5sWc+E1N1M2fqbpd+bNMcuzkiZj0kpgRduoclmQdybEW4gt/wWNr/2GwtbtFHZdQeJtaAPaIFr7Ex6Iv4vbEtcSZ1q3bXl8u8VPQ1u4cnYj5J4BTtcxvVwiIiJy+lEgRkRERGSI7UkrS+ZxOSjP9ff/ilI9YlzBzh4xXTNiGg9A7Q77Y8qnmsueypKFK82lv2jwD0K1vG0uM8fpAJiIyHAQHGmyWxo3mx+Xz4z1Rc5UcAfBsR4u+yxU74e1f4f9K3uc7nYkWeDYwoL6LfD7X1AXHEv2nGtxT73KZHI6Xe29ajzgdpEVPkjr3/6djG1/w5MM2wMwPfA6Etzp+QtXuFbzxdhtbLLG2u5PWg7+/Vn4lecQF0xsMaXKPJl9e64iIiJyWlIgRkRERGSI7U0rSzYqL4jb1c+N7xNhc3awwwEkzdnCTo858JWSXpYskAdZOWZ+T7Xw21KBmNL+3dajCdeYbByHCzLGDu66RUSkd1kTzOdNyy6oXwdOP/iPFvZolzEaXAGoewOKR8MVn4P6elj9EOx97YgPzQ/tgeU/geU/IerNI14+j7ZogkgkjBWq46K2bcf1dKY79/J379d5IPFO7otfj0XnZ3Ms6eC2p+D31zZxTvwVyJ0FGaOOaz0iIiJy6lMgRkRERGSI7alJ7w8T7GXmCUhlw7gzes6Gge5lycYsAJKm/Fd66bF4G8SaTGDHX9L/23skqWyYjNHg8g7uukVE5MhypkMyAqGDJqhSdF7fs0X8RVB0rilxFmuC3CwTkHH+P9i3DnY8S+LtF3ElI70uwhutx7vnOfrySXrQKmRr/gWMK8/F0VyFp6WC8ro3cZLsmON2JLnD/TfmZTXwi4yPs+xA5+PDcQcf/Sc8/M4Es611EKmG3Nng1KEWERERsdO3AxEREZEhll6abGzhAPeHiTWZ6137w1gW7H7F/pgRs8ylv7g9k6aLVFkyb97gBkOijRCuNtuTOX7w1isiIn3jcJh+MfEQROuhdpUJxvT1s8KTDcWLoe0gNG01gf/EISgvg/FfwHXVtwnt3cSWV/7KmJpXKHQ0HdPmxSwXzyTP5s2ci7j+omlcUpKWgVq9C175JdQfsA2f3/YC541w86WMW3h0W+dnYkvMwYf/CX9/b5xRHDTPOXdO3zOBRERE5LSgQIyIiIjIEEsvTTa2YIADMdF6c71rRkzVFmitsj+mZJy57CnjZajKkrXsNJeBcntZNRERGT4cTig4G6qXQbzVZMYULmjv29KXxztMf5lAObTshtbdJiDTVglUEizwMO/Gf2N93Zf4yXNvUFL5Mhc732Sac3+vi6y2cnjcuYTDoy/m3Mk5fGMMODxByJpkPg+t9rKdOdOgYBys/Rus+4cp65narLef5bsjG4mM/xT/2OXpGK8LO/j4v1z89foImX6gZrnJ2syZbsqAioiIyGlPgRgRERGRIWRZFrvTSpMNbEZMBrTuNde9XTJi0suS5YyEQGZ76bG0/jDJGERrzfXAIAZi4iFoO2SuZ00cvPWKiMixc/mg4BwTjInUQsN6kylzLBxO03cma4LJ5myrNBmZ0UaI1jM7s57Z7yymKnIzz+y9jZ9tPkhWxQoKaMTp9pCVESA7GKAhmuScxQv4WIkLpwPzWZg1CYIjugeH/IUmABQshuKJ8Nx9kIh23O08sJIfF7eQGPFZ/nWws+Tatjondzzn4xdXRHG5nNC6D8KHIWcmBMuP/3UUERGRU4ICMSIiIiJDqKEtRlM4bhsbOxA9YlKBGJwmkOJwmuyYlN0v2+ePOssEYbz53c/mDVeZUmaeTHMwa7C07DLr9Rd1728jIiLDjycL8ueZ8mSt+82++3jLSnqyzU/2ZEiETZCjrRIiNRT72rhpchs3TQ7QFruItqSbPF8SB0niiThvvPEGM4osnJ4M8/jAiO4lN7tyB00GT2AE+DLg6e9BtLOMqLNqE/fn/idNeXfyan3nyQrP7XHyvVU+vrIg3B68saBujTkBInemeT1ERETktNTHvGARERERGQjp/WHcTgcjcgP9u5JkwpR0MTfMhSer8yzgRAz2vGZ/TPlUc9lTWbLwEJQlS4Q7M3kylQ0jInLS8BebEl0AjZtNn68T5fJDxhgonA9ll5vLzPHgySbggXxfHEfq8w6IOwJYeXOh5CJT8uxIQZiuMkbBtA/ANd+EYK7tLmfDXh50fIdz/PZyaL9408FvNviwnH5Tli0ZhkgNVL1snn/SfvKFiIiInB6UESMiIiIyhPalBWJG5Qdxu/r5XJlEe+kzpxcS7QGZrhklB9+EaLP9MUVjzGV6IMZKmowYGNyyZM1vm3X78tUAWUTkZJM53pQWa91vMkSKz++/jEqn2wR7/MXmdiIKyQg43OBwYSUsal3Oo2fB9CZQApPeDW4/PHUPNHX2U3OFqnnY8x0+FPscKxJTO8a//aqTF/c4ufeiTEZmRkxAxuWD5p0QOmACU8GRJ/rMRURE5CSijBgRERGRIbS9qsV2e8xAlCWLtQdZPJmmrj6Ap0t/mPSyZIWTIZBlDpJ5Mu33RWrN2bwuH3hy+39bexJv68yGyZoyOOsUEZH+lTsbvHmmPGbt6oHLDHF5TdanO2Cup/eAOR7+Yhh3NVxzN+SPtt3ljjXzR9+9vNf1km381f1w+f+5+P1GH2EyzPNOhCARgbq1UP1a52eyiIiInPIUiBEREREZQpsr7Jko08oGoPdJvD0jxp0J8SZzvWsgZldaIGbkbHOZOru4q46yZCXHd2bx8Wje0Z4NU6BsGBGRk5XDCQVnmbJisWaoe9P0/TpZ+Itg1GVwzbegdKrtLlcyxn97fsk33b/HRaJjvDVm8c1XnJz5ayefXhrkX7sChMIhk7ETqYPqV6FhownSiIiIyClNpclEREREhohlweaKJtvYzPKcXmafgHh71o3T29krJlWaLNoK+1fa55e292DpqSxZW0X7fYNUliwegtA+cz176pHniojI8ObyQ8HZJhskfBgaN5km9icLfyGUXwRXuuH5+2Dfm7a7P+p+mlmeg9za9hkayOoYD8XgX287+NfbLryuDBaMsLh4dIyLxzoYbe02n625M0n6Stlc0cSKXbUs31lLVXOEMQVB5o7OY+7oXGaUZ+Nzuwb7WYuIiEg/UCBGREREZIg0RqGu1X4W7IzyAciISZUmS5157M4wNfUB9i23n4nrcEHxeHPpK7AvJ1xlSqq4fObM4MHQvN1st7/I9IcREZGTmzcX8uaaXjEtu8EdND1kTha+AihdDJe5YcVDsPEp291nWxt4OfPrfCr0cV5Lzur28GjCwSv7HLyyz8ddy8DttAi4I/jca4gknDRH7FlCGw428sR6cxKEz+3k+jNH8vnLJlOY6Ru45ygiIiL9TqXJRERERIbIgZC9tFemz83o/H7uEWNZnaXJrPZyKZ4uwZ70smSl08EbNIGP9Lr6re2ZKcFR/VNz/2jiraapMUC2esOIiJwyguWmYT1Aw6bObMuThS8fihbBoltg8Sc6T25olxOv5o/ee/mfgj/hd0SPuKh40kFz1EFNyNEtCJMuEk/yf6v2cdH3X+LXy3YTSyRP+KmIiIjI4FBGjIiIiMgQOdhqvz29LBuns5/7riTCJgDjcEKy/WCQrT/MS/b5I2aYy/SyZIkwRKrM9Qx7o+IB07StPRum2DR4FhGRU0fWBNO8vmWP6RdTtOjk2tf78qFwEUxzQW45PHcfhOptU65q/TuXlW9j6eh/4+EDhbx+ABLWiX/ON4fj/L8nNvPQir3MKM8mL+glN+hhckkWl04vwe9R+TIREZHhRoEYERERkSFyoNV+MGb6gJQla+9B486AeHuJslRGTKgOKjfY55dMMJf+Yvt4634TFPEVmGUNtGgDhA6a6+oNIyJyasqZaXqXhQ9D9XLInweBkqM/brjw5kDReeD0wHXfhlf+Fw6ut01x127lyro7ufKcj9B42fm8esDFC3udvLzPRW0o0eNix2RbLBoJkwostjVmsbYSdlS3dlQYTdld08ruGvtZHeMKM/jee2Zz9liV8xQRERlOFIgRERERGSLpgZiB6Q/TaC7dmRCuNNe97Rkxu18BuhzVcfuheKIJ1Lj8neOWBaH2smSDlQ3TuMlcBkd2bq+IiJxaHA7IPxPq3oBwNdSthtxZkDFmcNYfbYTmHZCMQDLeXsLTMuvPnGC272jcwfZgzCq44guweSms+hMkupQksxKw8lfk7HiBqy/4JFdPKidpJdkXKaLFO5FwwkG4+RDxln1MyksyIjPRZd3N4PJT4ZzJd1+s4/F1h464ObtrWrnhF8u5ZeFYvnj5FDJ8OuwjIiIyHKhHjIiIiMgQaGyLURdJD8QMQMAhFYhxuE1AxentDLKklyUrnwUuT/dsmEgNxEPmjF9/Wf9vY7q2SojUmXJqyoYRETm1Od1QcA5kjDKfU/XroXEL3dI/+pOVNOUvq181/WkidSaDNN5qPu8at0D1Moi19PE5eKBwoXkOMy6Hd34bCid0n1e3Cx77Eqx+DGe8jbH+amZ61nJWuYPzZs/iwnMuZkRREThcmMM1DsCCRJiy2Hp+vCTGX26dy8wRRz5xw7Lgwdf3cMV9r7D+QMMxvjgiIiIyEHRqhIiIiMgQ2FLRbLvtdTmZVJLZ/yvqCMS0B326Zpfsftk+t2yKuUwPxKSyYYIjwDnAdeetJDRuNtczJ4A7MLDrExGRoedwQt4Z4AqaAEnz2xCphqzJpmdZXzJT+iraCPXrOkt3BspM9qXDZX7iLeZzKNoAVS+bEwIyxx99GxxOk93jzTfXr/kGbHga3vwrJGP2uW/9FXa9Bud+FEZOh5rX29czAQoXQOgANGxsf5xltsuKQ/gwZ/lr+PvNk3mtcjJbD7fQEIpRH4rx1v4GNlc02Vazv66ND/zvSn59y1nMH1/QX6+giIiIHAcFYkRERESGQPrBksmlmXhc/ZysnIia2vtgAhzQ2R+mYb85M7ersinmzOSuzZITUZOhAoNTKqZ1rzkj2eWDrIkDvz4RERk+siebUl/1603ApHa1+dzKmmROEnCewCGMVBZM847ODNHcWRAst8/z5Zt11b8F4SoTlIk3Q+6cvgWEMseaz9G6N+CMq2HMXHj9D1Cx0T6vuRKevgcmXwznvBesLRCphby5JjDkK4LGjRA61F4yzQVOJyTjuJq3sDg3m8XjZnd8ZieSFr9ZtpvvP7uNSDzZsZqWSJybf7OKX9w0jwunpJ1oISIiIoNGpclEREREhsDmtIyYGWUDWJbMnQGJkLnuSfWHScuG8WdDwRhz4MfR5Sti2wFz8Mqb2xnEGSjJmDlIBpA95cQOuImIyMkpOBJKl5jgi9NtMlfq1sChp+DwSyZA0rrXjPexfJnbasVRswyatpvHBMqg5MLuQZgUlx8K50PebBN8ad3f2busL7w5ULzYLD9vBFz5JTjvVvD0kOW5/QX429dh3zoT+Kl62ZRKc/kgfx4UnN1eUjRp+tg4PeZxsSaoWgZ1ayERxuV0cOvi8Tx9x2LmjcmzrSIST3Lr79/gqQ0VfX8OIiIi0q/0362IiIjIENh0yJ4Rc7R678clFYjxZJuDO9AZiEnvDzNilgnApJcla91rLjNG9//2pWvaboIxniwIDsL6RERkeHJ5IWcqZE2All2mVFc8BLFm89PaXjLT4TInCqROFnBnmc8QMNmVsSYIVVGQ2AyxAHiCPWfB9CZjjFlH3Vpo2W36reX0sXeZ02MCKf4yaFgPUy+AkTNh+f/B3hX2uaFaePb7MPUSOOdGe6myQCn4Ckzfmta9nWXOUuXKQgdMn5usiZA5gXGFGTx863xuf3gtz24+3LGKWMLi0w+/yYcWjOHfL5lEYaav2yZblkVlU5itFc1UNYfJ8nvIDXrIDXgpyvJRlNX9MSIiItI3CsSIiIiIDLK2aIJdNa22senlA5gR4/SasiYOl8mOsSzY/Yp9bulkc9k1EBOpM42KHS4IjOj/7bNtawu07jbXc6b3bz8AERE5OTk9JkMyewokIhCtN71bovUQazAZIpFa85OS+vxoz5ZxJOKAZQIihXNNpsmxCI40n6H1601ZM4cLsicdw+PLTbmz+rfM7SWfhj2L4LXfQLjBPnfr83BwI5z/MbP9qVJlLq/JzskYBQ0bTNm21Oe6w5Qro2mbCdTkTMMXGMFPP3gmX3z0LR5fd6hj8UkLfr98L3978yCfvGA808uz2V0TYk9NK29XtbClsomGUFo/my5G5wdZNKGAhRMKWDC+gJJs/zG8kCIiIqc3BWJEREREBtnWyiaSXaqpOBwwrSyr/1cUbUytwVx4sszKqrZAy2H73PIZ5mxiV5eDKqH2M46D5QNfJqxxkzno5C/pnpUjIiLi8pnskECpuW1ZEG9pD8o0df6kMkacbvBkY+GnwdWElT8PXJ7jW3fGGBPsaNwMTVvB6YLM8cew7e2lzlr3mc+7cWdC6URY/gjsSjsxovkwPHkPzLwCzrrBPKf8eSaY482DovNNwKVpq3muVtIsPxmHRNhk73h348mZwQ9vOIMMn5s/rtxnW0VLJM73n91+zC/DvroQ++pCPLJ6PwCFmV6mlmYzrSyLs8fmc8m0ElxOnUghIiLSEwViRERERAZZelmy8YUZBL39/LUsGTNlWcwNc9FbWbKsEsguMUGQro8PtZ9FO9BlwsJV5sfhhNwZA7suERE5NTgc5gQDT9qJDImwCdK42/uxxGJEHAdOfH1ZE0wWStM2aNhkypQda9nOjNHgK4T6deb2RbfC2Hmw7JcQtWfKsvFpOLABFn8CkpHOUmUOB2SONX1umraY/jWJcHvWa5bpCRdtgOrXcAbK+M47plCW4+cnL7xNNJ488dehi5qWKMvermHZ2zX876u7mTcmj59+4ExKc5QpIyIiks559CkiIiIi0p/SAzEzBqQsWfs63AFzgAZM82CAXS/b55ZNMwd2umaitB0yB5w8WeYs3IFiJaFho7meOc6UThMRETleLn9nEKa/ZU82ARkwpcZCB499Ge4gFC40Jx44XTB+HrznezB6fve5DQfhn3fD6j9D3QaoXQWJqLnP5YO8M6DoXJPRaiUg3myWmfosbavAUf0ynzmjhRfvmM/1Z47oU+XPDK+L6WXZjCvMIC/ooa9JLmv21vOOn7zKsh01fXuAiIjIaUQZMSIiIiKDbPOhRtvtGeXZ/b+SVH8YT44p2wLmQE0iDnuW2eeWTzN1+L15nWOte83lsZ7te6xadpvMHZcPsiYP7LpEREROVM50E/Ro2QP1a9v7qJUe2zIcDlPazFcIdW9CELj00/D2InjtZxAPd861krDu77B/HVzwSXupMjCXxYvby5Vtaw/URMEVMEGZWAuEDjDCcZAfXjqajy08hx+9sIeVu+twOx2MLcxgXEEGYwszmFKaxbTSbEbmBXB2ib4kkhbbKptZvquW5TtrWbm7luZwvMenVtsa5abfrORzSybzmYsm2pYjIiJyOlMgRkRERGQQxRNJtlY228YGJCMm1R/GFYBEpTno486Gg2sgal8/5TPAX9TZ4DjaaH4cTgiM7P9tS0lEoLm9Rn32tIHvQyMiItIfcmaaYEzrfqhbA3lzTT+1Y+XJNj1fGjeZQMqkeVD+I3j5F3BonX1u7V54/Bsw7z0wuw1yp3eWKkuVKwuOgOYd5iSHRBskAG+uCebEmqB1LzOc+/nVdWOxMmfjcPv6tJkup4Pp5dlML8/mY+eNI5m02FcXYktFE1sqm/nbmwc4UN/WMd+y4IdLt7Otspkf3jgHn9t17K+NiIjIKUalyUREREQG0c7qViJpNdoHNCPGar/tzjBnxqaXJcsfDcFc8HUpSxZqb+obKAWXt/+3LaVpm2ku7M2F4AAGfERERPqTwwG5c0zgw0qaYEzL7uNbltMFebOh4CyTnZqRBVd9Ec779+4nKCTjsPoReOL/wb4X20uVRbosy2Mydkou6gwMRRtM5qm/2GTJWklo2YXj8PPQuMX++L5ucnsmzZWzyrjz0sn86/bzWTKtuNu8f22o4KMPrqYl0nP2jIiIyOlkWAdi7rrrLhwOh+2ntLQz5deyLO666y7Ky8sJBAJceOGFbNq0ybaMSCTC7bffTmFhIRkZGVx77bUcONAPjfpEREREjsOKXbW222U5fvIy+jnYkUxAvMVctxLmMlV2bHd6f5ip5jLVHyaZ6Kx5HxzAsmSx5s6AT84M+lS0XkREZLhwOEwmTOZYc7thIzRuPf7lBcqg+IL2kmMWTD0HbvwZFE/rPvfwdnjsa/Dmw1D5AoQO2e93B035suLzzOe/lYBwFSTD5iSLVE+Z5reh8jlo2ADx0HFvek7Qwy9vOosvXzG1Wz+Z196u5f2/XEFNy7EHfERERE4lwzoQAzBjxgwqKio6fjZs2NBx3/e+9z1++MMf8sADD7B69WpKS0u59NJLaW7uLLdxxx138Nhjj/HII4+wbNkyWlpauPrqq0kkEkPxdEREROQ099yWw7bb88fm9TLzBMSbTF0Qlw+S7aVCPLkQDcH+lfa55TPBm2PmAoQrIBkzB3F8hf2/bSmNW8w2Bko769yLiIicTBwOyJ0F2e0nNTTvgLq15qSG4+EOQOEiyJ5slp0RgOvuhgWfBNIiHPEIvP4gPHE37PyHycpJRO1zvHkmGJM/z3yuJyLQVglWDALlnWXLWvbA4RfMtsfSypf2kdPp4N8unMDvPzqfDK+9FNmGg4289+fL2VvbelzLFhERORUM+0LcbrfblgWTYlkWP/7xj/na177G9ddfD8Dvfvc7SkpKePjhh7nttttobGzk17/+NX/4wx9YsmQJAA899BCjRo3iueee4/LLLz/m7WltbSUrKwtH+1mb0WiUWCyG2+3G5/PZ5gEEAgGcThPvisViRKNRXC4Xfr//uOaGQiEsy8Lv9+NymS838XicSCSC0+kkEAgc19y2tjaSySQ+nw+32/xZJBIJwuHwEeemJBIJotEoDoeDYDDYMR4Oh0kkEni9Xjwej225fZmbTCZpazMHkDIyMjrmRiIR4vE4Ho8Hr9d7zHMtyyIUMmf8BIPBbr/PY5nbl999f/yd9PT77I+/k9Tv80T/TtJ/n8cy91h+9yf6d9L193mifye9/T6P9++kv/YRqdco9foM5T7ieH732kdoH3Eq7yNaInFW7OzMiLESMRaNySASifTvPqK1hmgojCuQjd9qMBO9eYS2vYjVFsHvNvXecTiJF00iEs/E2dZmfp+tJkslRBFWKDQw+4i2anwth3B73JA9TfsI7SOG/T4i9XuzLKvjdT9Vv0cMp/819D1C+4j+2keEw+GO1/5Iv8/j/jvJngQuH1b9W4Rq3oaGw2SMOg88md3nHu13H4sRc43EnZWFr3UTJMIwazGtJXNg6b0EW/d2zk1YxPZuxn3gK/jmXgVn3QhF82lNZtp/98FyYu4Cog27cLXuwk8bxNvAnUGrowRiLQSczThDByB0gJi7kKhvFK5A4TH/7s+bVMgjn1jIzb94hdrWKA63B4fTxe6aVq77ySv8+L0zmD+hSPsI7SNsv8+ucxOJBK2trfh8vlPme8TpdDxC3yNOn31E6vfW2+/zVPoe0dff/VFZw9i3vvUtKxgMWmVlZdbYsWOtG2+80dq5c6dlWZa1c+dOC7DefPNN22OuvfZa6+abb7Ysy7Kef/55C7Dq6upsc2bPnm1985vfPOK6w+Gw1djY2PGzf/9+C1Nl3Tp48KAVjUataDRq3X333RZgffSjH+0Yi0ajVjAYtABr+/btHWPf//73LcB63/veZ5tbWFhoAdbatWs7xn72s59ZgHXNNdfY5o4ZM8YCrNdff71j7MEHH7QA65JLLrHNnTZtmgVYS5cu7Rh79NFHLcBauHChbe68efMswHr88cc7xp588kkLsGbPnm2bu3jxYguwHn74Yau1tdV6/PHHreeee84CrIkTJ9rmXnnllRZg/epXv+oYW7VqlQVY5eXltrnXX3+9BVj33Xdfx9imTZsswMrJybHNvemmmyzAuvfeezvGdu/ebQGW2+22zf3kJz9pAdbXv/71jrGqqqqO32dra2vH+J133mkB1p133tkx1tra2jG3qqqqY/zrX/+6BVif/OQnbetzu90WYO3evbtj7N5777UA66abbrLNzcnJsQBr06ZNHWP33XefBVjXX3+9bW55ebkFWKtWreoY+9WvfmUB1pVXXmmbO3HiRAuwXnrppY6xhx9+2AKsxYsX2+bOnj3bAqwnn3yyY+zxxx+3AGvevHm2uQsXLrQA69FHH+0YW7p0qQVY06ZNs8295JJLLMB68MEHO8Zef/11C7DGjBljm3vNNddYgPWzn/2sY2zt2rUWYBUWFtrmvu9977MA6/vf/37H2Pbt2y3ACgaDtrkf/ehHLcC6++67O8YOHjzY8fvsOvf222+3AOvLX/5yx1h9fX3H3Pr6+o7xL3/5yxZg3X777bZlDId9xOjRoy3AeuWVV4bFPiI19tJLL2kfoX2E9hHtc0fe/kdrzJefsMZ8+Qkrb/GHBmYf8YOvmn3EFYut2J6/WbG9j1vRSNgaU2z+plZ9PMOyvpVtJR840/rdjz/buY8I1Zn5ex6zpk2bOqD7iP/76ResaPUa7SO0jzgp9hGp77x79uw5pb9HDLf/NVJj2kdoH3Ei+4irr77aAqwHHnhgwPYRqbGDu9Z3/D5je/9uRRt3n9g+ItxixSpft2J7/tYxt+L3H7esb2Vb1reyre9c5LMA6+NzPeZz/XvjrPjLX7OCAf8R9hE3WtG6rVZs3xNWbM/frML8bLOPWPaYFT28wort+Zv1s3v/zQKsay8/14o27rGikfAx7yMmTjbfI0ref0/H956id33NAqzJs+y/e+0jtI9I7SNaW1s7ntup9D2iYx9xih+P0PeI02sfkfp+3Nraekp/j+jLPqKmpsYCrMbGxiPGG4Z1Rsz8+fP5/e9/z+TJkzl8+DDf+c53WLRoEZs2baKyshKAkpIS22NKSkrYu3cvAJWVlXi9XvLy8rrNST2+N/feey933313j/c999xz5OTkALB9+3YA9u/fz5NPPtkxJ1X67MUXX+zYxs2bNwNw6NAh29xo1KQPv/rqqx3bnirBdvjwYdvcVJTztddeo6qqCoC33noLgJqaGtvclhZTG37FihUdUcw1a9YAUF9fb5vb2Gga+r7xxhsdY+vWrQOgqanJNre21pzJu3bt2o4I4erVqwETLe06t+s2psZ37doFmIhi17mp38mmTZs6xg8dMrVuY7GYbW6qz8/WrVs7xlPbZVmWbW7qNd2xY0fHeOq1AXjqqac6op+pbdu1a1fH3Hi8s7Hgs88+S2ZmZsfyUsvvuj7LsgB44YUXKCgo6NjO1HZ3nRuLxQB4+eWXO5aX6nNUWVlpmxsOhwFYtmxZx+uS+t1XVVXZ5qZ+38uXL6ehoQEwv6/U69R1blNTEwCrVq3q+FtM/R00Njba5tbX1wPm7ygVBU79rba0tNjm1tTUdGxjbm6u7TULhUK2uYcPH+5YVmp83z5zRnY0GrXNTT33zZs3d4ynHp9IJGxz9+/fD5j3aWo89bcO2Obu3r0bgJ07d3aMp15zgGeeeaYjgr9z586Ox3RdRspQ7iNSEfmVK1dSV1cHDI99xJYtWwDtI1LrB+0jTud9RFcFPqin//cRu3aYuXW1tbzxxhvEHFnUuSAZtdd/P+jIY9cu81rW1NTw6tN/JJisIOLIpaXF/J309z6ivvZw++u0m6eX7SLp2K99hPYRw34fsXTpUsC81imn4veI4fq/hvYR2kecyD4i9XfS9X0/GN8j3li9ElhJm6OQPbvN7/6Y9xFPPwdAIFndMXdNLJfi8Z9mxoE/AQfpytFai+uF+03ZMuC1F//B5pKJHc/JPMcKnnxlKw4rQdA63PE3uHn1k7QcHkOYfHbsNa9vQ101a5b+kqTDS8hRTNsx7CMibebvpMAH6QXJ9taFuO1/nuYdo5O4ndpHaB9h30eknErfI06X4xH6HmGcLvuI1PfjpUuXntLfI/qyj0j97R+Nw0r9Bk4Cra2tTJgwgS996UssWLCAc889l0OHDlFWVtYx59Zbb2X//v08/fTTPPzww3zkIx8hErE3hbv00kuZMGECP//5z3tdVyQSsT2uqamJUaNGsXfvXkpLS5Xm1z7XsiyWLl3KxRdfTCKRUJpfL7/P/vg7UZrfsc89HVOBGxsbef7557nqqqs6xpUKrH2E9hHDYx/R1NzCRT98lcaYs2PuO0eG+dqNiwkEAv23j7CSxPc/QTQaxRksJUADVsY4cBUR+/40LIuO0mTxq75KbOT5RILTcTog2PQ6JCNY+WcRSmb3/z7CShLe+wzJeCveghm486Yd8+9e+wjtI4aqNNnSpUtZsmRJxz+lp+L3iOH2v4a+R2gf0R/7iObmZpYuXcoVV1zRMT7g3yMsiwzrII5mc1AnEncRy5iCJ2vk8f/uGypwNLxF0BPD4XBg+UYQX/MPEst/hocYPndnD5nWqIXl8uA782qY/3HIn0ss6ex5H9HcAC27CCYrcTqS5ndv+Ym4inE5LQLJKkiaYyOhcIykrwx/wRRc/rwj/j5Tfydxh5sv/m0TL26rwUomsOIxcDhwenxMLMrg29dOZ2aJ/6j7CMuyONDQxqodh9lf10ptOElVS4LDzWGSiQRZHoucgJeivCxG5QU5Y1QOE/O9eJxoH3ES7SNisRhPP/00559/vkqT6XtEn36f+h4xtKXJli5dyqWXXkosFjtlv0f05Xff1NREYWEhjY2NZGdn05uTKhADJogyceJEvvjFLzJhwgTefPNN5s6d23H/ddddR25uLr/73e944YUXuOSSS6irq7NlxcyZM4d3vvOdvWa89KSpqYmcnJyjvqCnm1TU96qrrur4YxSRoaP3pMjw9caeOt7z8+W2sW/OjXPT9f38fg1XQc1KcPnNT7QB8s+Et1+Dv93aOc8TgJt+BoVnQ3AktFVA7RvmMaVLTJPg/tayCxo2mXWUXAxO19EfIzIM6PNV5OQ1pO/fSB3Ur4N4e05IsBxyZoLLd8SH9SqZgMZN0GrOoMabC4ksePabsPvlnh+TUQBn3wjzboXMcb1/vidj0LLbfFYnTcAZdxAyx4PDBa17INp5Nj++AsgYA4EycDiPuNmJpMV3n97KL1/Z1eP97503kv+4cioFmfbXpSEU5a9vHmT5zlrW7a+npiXa4+N743Y6mFaWTVmOn4DXhd/tIuB1MaYgyLSybKaVZpMT7P43YVkWhxrDvLW/gdZInAnFmUwtzSLoHdZFZU4J+rwVOXno/dqpr3GDk+pTJBKJsGXLFs4//3zGjRtHaWkpS5cu7QjERKNRXn75Zb773e8CMG/ePDweD0uXLuWGG24AoKKigo0bN/K9731vyJ6HiIiInH6e21Jluz25OJMCf0P/ryjcvh5fEbS1lyzx5sHOF+3zyqaC023mAbSa9GqCowYmCJOMQZMpj0D2FAVhRETk1OfLh5ILzedfy9sQOgThasidaU6COFZOF+TNBn8R1L9lTrZwNMG7fgh718EzX4WWw/bHtNbCS/8D65+ARbfCnA+Dp4eDRE4PZE82gZfWPSYgEw9Bw0ZzAkXWBMiaCqF9EK6ESK35cXrNc8kYA57MHjfb5XTw1aumMaEog68/vpFYwn4+8KNrDvD3dYe4ZFox75o7gtEFQf6wfC9/ffMA4Vjy2F+ndvGkxYaDjWw42NjrnLIcP8VZPnKCXvKCHtqiCdbtb6Cq2V5ZxeGAMflBxhZmEPC48Lf/jMwLsHhSETPKs3E6B+D7k4iInDKGdSDmC1/4Atdccw2jR4+mqqqK73znOzQ1NXHLLbfgcDi44447uOeee5g0aRKTJk3innvuIRgM8oEPfACAnJwcPvaxj/H5z3+egoIC8vPz+cIXvsCsWbNYsmTJED87EREROZ08v8V+YOTiqUUQa+j/FYXb1+MOgJU0B0hcAdj5gn3eiFnmTFqXD+JtnQGcjFH9v00AzTtMMMaTZYI9IiIipwOHE3KmmsyR+nUQa4K6tRA6CLmzzef1sQqUgScXGtabz++mLVBSCre9BMt+Aqt+Yb4DdFW3D574Bqz9M1z0RRh/dc8nRTjdkDURMsaZoEvz25AIm4xWp9sEXAoWQbTanMSRCJugTcsuE3jKGAP+sh6XfePZo5lelsNXH9vQLTgSTSR5amMlT208cj/f/lbRGKaiMXzUeZYFe2pD7Knt3gfgv5/ZRlGWj4umFHHB5GIWjM/vlt0jIiIyrAMxBw4c4P3vfz81NTUUFRWxYMECVqxYwZgxYwD40pe+RFtbG5/61Keor69n/vz5PPvss2RlZXUs40c/+hFut5sbbriBtrY2LrnkEh588MGOunIiIiIiA21fbYgdVS22sYunFFGxcUf/rijWbM5edThNGREw2TDVW6El7cDGiJngLzbXQ6aZKL5CcGfQ7+IhU+4EIGf6wGTciIiIDGfeHCg+H5p3QvN2E0Cpesl8LmaMOfbluQNQOB9a90PjRojWQ2wtLPowzHk/LP067H6l++MOboCHboHJF8Al34KSM3tevtNlSplljIHQAWjZCbEWs/0tuyBQDvlnQTLaniVz2JRii9SBcyMER0BghAnOdDFrZA6Pf/pcfr98Dz94djstkXjP6+9FfoaXGeXZjMwLUJodoDTHh9PhoCEUo6EtSnVzhA0Hm9hW2URyEAvxVzdH+PMbB/jzG6ZJ99TSLBaML2D+uHzmjs6jNMd/lCWIiMipblgHYh555JEj3u9wOLjrrru46667ep3j9/u5//77uf/++/t560RERET65rm0bJiCDC+zR+ZQsbGfV5TKhvEVmjNuwWS9bHrOPi+jAHLKTCDGsswBFICM0f28Qe2atpozc32FncEfERGR043DCdmTTEZLw1vtPWTWQ1sl5M0xJcCOVcao9lJl6833gOYdprfLDb+CA+th6TehanPagyzY/hK8vQymXw4Xfh0Kp/e+zRmjTTZruMoEYSI1JqMndND0iskcb3rfhA5AaK/JtG3ZY37cQROQCY4wWbGYUmUfOXccV84s47tPb+Vf6yuIJnouQeZ2OrhyVhkXTy3izNF5jM7vbEZ9JK2ROOsPNLK5oonWSJy2WIJwLEFDKMa2ymbermrpdZ0pOQEXBUEve+rajjmos7Wyma2VzTz4+h7AlECbOzqXheMLuGhqMSPzgrb5yaRFJJ7E53aqxJmIyClqWAdiRERERE4Fz29NL0tWjGsg/slOBWL8JeZACbT3h0kvS9beKNiTC5Fqc8DE6TEHhvpbtNEcqAFz1q+IiMjpzpMJhYugdTc0bjEBjsMvmVJlwfJjX57LD4XnQFuF6ekSD0HtKsgvg1ufgw1/gxf/E5or7I9LxmHjv2DzMzDjKrjoW5A/sed1OBwQKDE/0UbzPaPtYGevGHeGyZ4pPB/iTSYoE64029K8w/x4sjszZdwBSnP8/OjGM7jrmhk8seEQf3vzIGv21gOQG/TwwfmjuWnB2OPKJsnwuVk4oYCFEwrsd8SaoO0wsdBhdlU1sLveoiEM9WFoiDhIJGFaocXcEhiXm8ThiNEWgx11sLXOSW2bg3DcIhy3aArD8oOwp/Ho3+kqGsNUbKjkyQ2V8PdNTC7ycs6YXGrbHOyuDbGntrWjH47X5cTvcZKX4WXWiBzmjs5j7uhcZpRn43OruouIyMlKgRgRERGRAbSruoWVu+psY5dMK+n/FSVjpiwJgDcf4hvMdWcA9r5mnztiljl71uHoLEsWHGnOeu1vje1n4QZHmLIsIiIiYj6DM8eDrwjq15rgRt0aE7zInWVOkDhWgTKzvObt7YGSChPkmXwuzHgDVv4Mlv0YovZyqSTjsOEfsOlfMOPa9oDMuN7X482B/LmQmGZKj7buhXir+cxv2mo+8zPHmcBS+LAJ2ISrTBCksckEn7y55sQRfwk5wRw+OH8MH5w/hgP1IQ41hJk9Mge/px+DDuEqEwyKmO9kHmBKPkwpzjAnpzjcpqyrw2m+UyVjpuxaMkbAG2N2icXskp4zaHY3WLyw18XL++CNQxah2NE3Z3t1lO3VVT3eF00kiSaSNIXj7K0N8cR6E0ALeFxcPbuM988fzdxRuX3KDBIRkeFDgRgRERGRARKOJfjMw2uJd6ln4XU5OX9SIdDPhcvDVabMmCcLku1NZ90ZcHAtxLo2lnXAiBngL4VE1JRDgYEpS9Z22JQvcTghe1r/L19ERORk58mCovM6s0ZC7VkmeWeYkyaOldNtMlCDI6Fhgwk8NGwCz36Y/zE488Pw8nfhzd+Z7wFdJROw4THY9A+YcR1c+A0oGN/7ulx+yJkGWZNNsKVltwm2tO43P94cyBgLeWcCSRMYCh0wzy/aYH6atpnl+IvBX8LInKJuZbuOm2WZwFbzDhPoAvOdxFfUsT7cgb4tKxk3wRmSgLO9350DHC7GjXDxsZkOPgbEEknWH2hg+c5aVu6uY93+BprDx9YHpzdtsQSPrjnAo2sOMLU0i3fNHcGkkkzGFWYyMi+AxzUAJ9SIiEi/USBGREREZIDc++QWNlc02cbed84oMnxuYrE+nC55LLqWJYs2mOveXNj0hH1e4VgIZJuDO6EDpneLN8eUC+lPVhIaN5nrmeP7fqBDRETkdONwQvYUExyoW2uyS2pWmKyS7GngPI7MEE+2KX8W2m8yVWJNUP0aBErhsrvgvDtMdkyvAZm/maDM5CVw7udh9IL24EMPnC5zQkfGaJOd27IH2g6Z4Ef0LbP+4AjTZ6ZoESQi5ntL+DCEqyERhtZ95sfhND3lfIXmu4o7q/f19iYZN/3vWnab0mhgsl0yx5rvJMfTi8fpNj9H4XE5mTcmn3lj8vkMpvfLrpoW3tzbwPJdtby0rYr6vqTMHMXWymbufWprx22X08HYgiDTyrLbf7KYVpZNabZfmTMiIsOEAjEiIiIiA+DpjRX8bvle29ik4kz+48qp/b8yyzIZMWACMc07zPXe+sN4C0zJk46yZKP6f5tadpkDSS4/ZE3q/+WLiIicarx5UHwBNG1ub3a/2/Ryy5trTq44Vg6HCY74S03JsNA+kwkbPmz6uVzxn3D+nfDafbDmQYiH0xZgwfal5qdsNpz7OZh2LbiOcCjJmwf5eZCYYb5ntO4xwZCWPebHk2W+dwTKzbZZSZMhkwrMxEPmO024ChoBpxd8+aavnTcXPDng8nZfb7zNBIGidWa9yfYsFKfHBLQy2kutRapM4CdVesxKgCtgsohTP07fsQd/euF0OphYnMXE4ixuOHsUiaTFWwcaeGlrFfvr2yjO8jGuMIOxhRmUZvmIRZoIt9bSFqpjV3UzaythbaXpUWPR+zYlkhY7q1vZWd3aUcoMTK+dqaUmKDOhKJPxqXVl+3EORL9CERHplQIxIiIiIv1sf12IL/5lvW3M73Hy0w+eSdA7AF+/ovXmgILTYw6ApDJi4sChdfa5I2aaRruxJnOmqsNpmub2p0S4MxiUM61PZ5CKiIgIJrskd5YJntSvg1gLVC8z5b+yJh5fPzeXF/Jmm2yQxs0m4NGyx2TGZk6Ey++B8z4Hr/0E3viNCWqkq1gPf/kIZJfDgk/DmTeD/wjZtC4vZE0w64zUmOBIWwXEms02NG4231kCZSYok1sEzDT3h6vMY6J1JljSVtlZShXM9x2nu7OvS6LNZNl05ck06/aPgFg9NG4wy7B67vNi43B2BmVcAbMep7u9b08qeGGZE2Gw7NcdLjPP4TGX7qAtA8fldHDm6DzOHJ3Xy8ozgXIAzknGeF+4GiJVVNUe5tGNUR7Z7GB/U98DKA2hGCt21bEirV+h3+NkckkW00pN9sykkiwKMr3kBb3kBDz9259HREQABWJERERE+tWB+hAfeXB1t3rgd187g8klWQOz0o6yZMUQbzYHLRxO2P0atl40Li+UTDYHd1p2mbFAac9nlp6Ixi3mTFRvXv8HeURERE4H/iIoudD0eQkdNL1Uwochb87xlxP1ZELhOSYDpXFze4+WrSZrJXsKXP6fcO5nYfkDJkMm0tR9GU2H4Nmvwcv/BXPeD/M+AiXTe1+nw2Gei7/InDTSVmGCMpG69gyW+vagTG5nUCZrgvmxku29ZOoh1mBOIIm3tmezxLqvx5Ntvnv4S0z2b9sBqH7FPCbFm2PKnTm95sfhhETIzImHzHUraQJCsebje53TOT0mE8idCb4Cs219Kdnq9ECwHILlFOfBp8e08G9Lalm2vYJ/bWpgR22cPQ1QFz72zJZwLMn6A42sP9DY4/1etxO/20nA68LvcVGQ4WVqquxZe4ZNhk+HFEVEjoX2miIiIiL9ZOP/b+/O4+yo63z/v6rqrL2nu7N0ks5GAgQCBAg7iiggMAo6d9TrgoOj3h8uo47jODo6V9Q7MnoVtxkXRlHGwXG54uAoKMywibITIAlJIJCQrTuddHo/fdb6/v741tm6T3d6Jd2d9/PxqMepU1Wnqs7pru5T9a7P97uvh3f98DEO9pXflXnVaYt584ZpaP4Lih3Rgr3wMBiEMtH58OwPy5ddegrEGu2dmYl9dtpUN0uW7rJ32AI0rJuypj1ERESOOW4YGs+w/9+7N9lQouMBW8VSu2ZifceADQPmX2j7cendZgOIrqehb4dd76Wfg1f+DWz8ETz8HejZPXwdqT549CY7tJ4LG94FJ70BwqP0v+KGi33J5JJBpct+W/mS7rZDz1YblsQW2fcdbbRDnp+xrzU5e9OHydkbSsL1NlQxvg16Ou4tVva4IahaaptjKw2xDm6HfY9B4jAku2GwG7IpiFZBtBoiVRCO2qbYXNcOfg7SA5AZhNQAJHsg0Q0Dh2GwC9IJu45sCnIZiMRs5VCszvbRN28JNK+CReugtjV4j81j+1mGa3DDNbzyjOW88ozgs8j00tN7mBcOdLGtrZdtHUm2HoJtndCXnvh3sHTWJ5316Q1uLHqpM8GTu7uLP0oHjl9Yy+nL5nH6sgYuWN3Mkgb1BygiMhoFMSIiIiJT4N7tHXzg1idJpHNl01c2V/MPb1w3fR2lDu6zzZa4IVsRc+gRO92Jwwv3li+78hx7wp88YKtmvJgNbKaKMdC92Y5Xt06sPXsREREpV7XEhifdm21FSd/zNsBoOBVizRNbp+PY9cZbbEVM7/O2KqTrKeh7zgYy574Pzv7/YOuvbJXMvicqr2vPw3b47Sdg/dvhzGuh+Qj9w3kxqFlhh1zK3lSS2A/pTlv5ku6xVUBezH6/iQSBTKg6aCKshPFtU2bJAzbcySWL26g9DqqWF4OOxGHY/At46lbYv3Fin914pAegv7PCDAcaFsPik2H5mbDylVC91H5P86JjW7cbhmgT9fObOGM+nLEO+1lk+zGpbvZ2drG1rYet7QmeO5RlZzfs6oFEZvLfSX0D29r72Nbex78/uhvHgUvWLuQvLljJuasap+97r4jILKYgRkRERGSSfv3Mfj78k6fI+aZs+poFNfzgXWdRGwuP8MpJ8nP2TlawF0yMbytSAHY/Vd5shxuCZettU2S9z9lpVa1TW7HSt8PezeqGoG7t1K1XRETkWOfFoGmDDRq6N9nQ5NBDtumqupPG1tRVJY5r+1KpWmYDmb4XSipknrffL05+A5z8RtjziA1ktv6asqZP8wa77PyH/glWvALWvw3WXgXRmiO8t6itVqleDrm0DWWSByB50IYqA7vtAEG/KzXl318yvbY6pvSzql1t31M+gBnohP/63/DMz+w2jjoD3fvs8OxdEP4qLD0Vlm+A1RdD3Ur7nS08zmZtHRfCdTjhOlprltG6HC6DoHqmD5Pp5WB3N8+397K1Y5CtHVm2HjLs7YPe1MS/ExoDdz97gLufPcDaljquu2gVV522WIGMiEgJBTEiIiIik7C7M8Hf/r9nhoUw565q5LvXbKA+Pk0hDMDATtvsRigO1Svt3bFgm/TY9uPyZZeeArEGcGOQOminVU9hs2TpLujbbscbThn73ZwiIiIydvFFtjqmdxsMvGSrSAYP2MCk9jh7IX4i3JANL6pX2kCmvzSQec42h7b0LHjLv0HXS/DkLfDkj2Cgo/L6dv3eDr/5GJx0FZz6FhvOeEe4DOVFis2X5StdUoeC/mS6baCQv+mk7HUxW00SW2j7o8l/DsbYCpg7Pw6JSpUpM0QmCTsftcMDN8GSdbDyLFh1ITSsKTbTNuGfbxiijTjRRhbUwIKlcAHYz8dPQTZBNjNAb/8AXf399A8OkkwlSabTJNI+u3pgW6fD1kPwQhfkzMgBy9a2Xj78k6f4+eN7ueFPT6G1sWpi+ywiMscoiBERERGZoJxv+NjPn2ZgSHNkb1i/mC/+2alEQxNsu31MG0/bO1UB6k60d3wmg/5hnGrY8d/ly688G+ILbf8txhSb95gKfhYOP2nXW7XEtsMuIiIi08MN25seqpfb6pjUYRvMJHbb7wTxxROveHU9G+hUr4DES7baNTtot9O73W6zbiW85n/Dqz4J234DT/wAXryv8voyA/D0v9uher6tkDn5jbD8/CP3i+K4tlmy2AL73Pi2+iXf9Fi+KsersjehDNW7H37z17D9jpG3UTUPGlcE/bg0QChi+30Z7IZkr21aLJeGbLpYdROJ275wwlH7GKuyfcFEYxAKQSgMXti+v9RAMAxCog+6D0BPp30vI/GzsOcpO/z++9Bykg1lVpwNDSshMs+GcZGG4c20jZfj2BDLixGKNtJYA41Dl8mlwU/a34PcIMnkAJv3dbNxbz8b92f4/Z7K/dE8uOMQr/3qffztxQu4+MRFdGWidCUNvjGsW1zPgrpif0LJTI57tnVw1+Y2dux2ecJs47gFtaxoruaUJfU0Vkcm9z5FRGYABTEiIiIiE3Tzgzt5dNfhsmn/44ylfPlNp05/Uwx9z9kT9Ug9xJcEd40GlS57N9n21vPcECw7A6ILofdZO61q2dTtS/cme9dsqMpeGBIREZHpF66D+RdAYh/0PGv/Fx9+EiIv2ObKJtp/DNgQoWaV7V8lsRv6X7Tr73veVstULbHzT36DHTpfgCd+CBv/DQYPV17nwEF4/Pt2iDfC6ktgzaVw3GuguunI++S4Y+t/zhhbsXPX30Oqt8J7C8Fxr7D92Sw/C3KDkO2HTJ+tDsEJKk8cG1QYY79zmbTtY8/uTH5lQaBUUqniuLYy2A2qg/2M3UamDzJdkOyGzl1wYBe074SuA6O8Fx/2b7bDH34Ajctg8Uk2nFl0AlQvsN8Fw/UQbrDjkw1nhvIidgjXARCrgQ3NsOE0wM/SP9DNL57YzQ8eOciurmzZSxMZw2fuOsBn7hr+Hlc1RTn/uCZyePzmmTZ6k/nXumx+eHdhubDn8BcXruSvLz2BiOvbIC6XtOFQLmU/X5MFk7OD44LjBUMIvLj9jupV2dBpDN/RO3qT/PjR3VRHQrz93GVURXT5VEQmT39JRERERCbguQN9/N/fbS+b1toY57NXnzz9IUym3zYbAvZCi+NA8pC9SOBFYfvd5csvORliQRvj2YQ9QY8vnpp9SeyzVTaOA/NOn/qTfxERERld1RKILbJhSf8O29H9oYdsE111J9gKiolyPahZaStkku12G6nDMLDHDtFmG8g0roLLPg+v/rStknn6J7Djv+yF8UoGD8Omn9kBB5acaUOZNZdCy+ngTrAJrsMvwq8+ZJtFq+S4V8CffB1CWfteujeNY+WubeIV7PctL26HcK3ttyZUbS/2u+GRL/bn0pDtg3SvrTjqfQ56XoR9z8H+F6Bj9+jVMod322Hzb+3zukUwfyU0rQwel0NVsw2swkFAMxWVMyNxQ9TUNvPnr2rmmlca7nq2nc/+57O09SSP+NIXO1O82Ln/iMtlcobv3v8iD297kW9c5rO8QvHTmDmu/VmFayFUa8OlcK39OQY/s75khj/7zkPsPpwA4LaN+7j1PeccsSonnfUJuQ6uq35xRKQyBTEiIiIi45TO+vzVT58inSueKDsOfPnPTqMmOs1fr7IJ6AqaAYstLN7tmm+WzK21Fz5KrTzbNuuRDE52q5YcuTmQsUh12rbjAWqPt82diYiIyMvP9aBuje1bpe95e8NG8qAdYguCQKZh4ut3HIi32CHdZUOMwbZiHy6harvtqlZY96d26DsAm35uw5a2p0dZuYF9j9vhvhtskLDiwuIw/8QjVzEc2AJP/Rge+75tQmuoeD1c9llYdQEMPG+rKMBehI82BUFKja2cMAbwg0dDoTIGJ6iwiFbuq8X4tkIj3W8rYArVNUF1hhu2F/+jTXaoXQkLLrLNra18wVYtd2+Dfdth3wvQ8RLkssO3U6q33Q4vPJT/QUH9ImheCU0roLHVVtHUtRRDmXxA401tc1+u63D5uhYuWN3MDXdu48eP7D7yi8bh6QPwJz9x+IdXu1x9UtyGYl4sCL5CwWfs2Z9DvjomX42UTdjHfPN2mSGVUo5nfxfCdXzz/kQhhAHb583b/uVh/u0959BcU94HYs43/GZTG//ywIts2d9DyHVZWB+lpS7O0sY4V65r4TVrF0z/TVoiMisoiBEREREZp+/e/wJb9pefwL3nwpWcs2oMzWpMxsAe6NlsK1/cMNSfVJyXD2L2bYVsyV2IrgfLzrTNkvUEd31WL5/8vqS7oPNRe5IbW2A7CRYREZGjy4tCwzpbpdL3nK1aTXbYIbYAalfbEGAyIvOg8UwbeAzshIGXIDsAPVttPzKxhfa7Rs0COP+Ddjj8Imz+JWz+OXRsHX39iUPw7H/YASA+Dxaug/kn2FCmdpHt3D6TCJa9ffSgZ+1r4bVfhNRu6AuqmcO19iaSeMv4+9Mxvq1OziWC5saCC/vZ/tGrWfK8aNCMWAPEF9nmxJrOsEN2EJZvg+7N0L0d2nfYSpn2nZDNjGXnoKfNDi/8sTg5Xl8MZfKPDUsh3mRDtNLBq55USFMbC/OFN57Cn5zSwv/5zVa2ttnvzGHPoaEqwmA6R3+qcsB0dmuc5twB3PrF7O7OsvVAkkzJR9qfcfjw7wybBhbyd1euHV/1iTHFJuKy+Z9bX/Bzy0G6mxcPdPODR4PQrcS29j7e+p3f8+N3raO+dh4H+nM8uOMQ373/BXZ1FkObdM5nz+FB9hwe5NFdcNuT+zhvVROfueokTlxUN/Z9FZE5SUGMiIiIyDgc6k/x7ftfKJu2ZkENf33ZCdOzwVzKXtwY2AmJoKIl2mibAQtV2eeZPnunn+PC8/eWv37xSVDVaO/KNH5wJ+QkTwTT3XDoYRsIxeZD01kT7xRYREREpl6oCuattzdK9D1fHshEGuz02MLJ/f8Oxe1NIbXHw+B+G8iku22lzGCb3YeqZVDdapsue+Vf26F7Nzz3O9j+a3jpIcimRt/OYJdtamyk5sZGUtMMV9wAqy6Cro22OsKN2KAqvti+dz8DqR7I9tp9zw1iL8I7xc/G+EHAElS85EZpdstxbZWGF7ePGPDz1RlBs2S5FOQO2Jtoerfb8CO+GKoW2+9ojafbIZuE5c/am3B6n4fDbXBwDxzca8f9EZp9q/gZ9sC+Hti3uXx6vB7qFkLdAttPT3WjHWoXQN0SqF5of46h6qApr1obJI3BBaubufPDr6AnkSHkOVRFPBzHIZvz2bK/l4de7OTRnYfJ+oZzVjZy9frFLKwJc8cdd3DllecTDofZvK+Hv/z3jew8NFC27u89uJPDA2m++GenEvbG2Iyd4wTvpQpYWJxujP2unenl83duJ+MnKr78+UMpLrzxcVK58R0zD73YyZVf/z3XnLucv7r0eBqqprYSSURmDwUxIiIiIuPwz/fuIJEunvi6Dtz45vXEwpNo6ivTZy9Y5JJgMkEzCil7p6Vfcseg40DtCfZu1tILJ/lqGD8Czw/pH2bF2VC1FBJ77PPJVsNkeoshTLQJGs+q3DyHiIiIHH2h6mIg0/8iDOy2gUPnY3ZezQrbnNhk+hBxQ7ZZsupl9nvCwG4b/GQT0LvNVqFE5xf7smlYBme/1w7ZFOx8ALbdDi/eB117puBNO3DqVfDaGyF7yFbwgq3kadpgA5JcEnq2FG9yGfcmvGIFSbi+Yl8jFfm5YuiTOmSDseyADcv6nrfrqFpqh1CspFImBf3PQ9+O4Oacg9DbCd0d0H0Aujrs87FU5JQa7LHDgecqz/fCxXAmP9TMh3kroWU9zFsD0XlB6FRZfVX571bIczmttYHTWhu47qLjyuZlMuVVP+uW1PPrv7yQ/337Fn7x5N6yebdt3EdXIs0/v/0MqiKTuLzpOBCu4Z4XBrj3hfIQJuw5ZHKm8Hy8IUyeb+CWh17iN5va+PzV67jilJaJ76+IzFoKYkRERETGaG9XglsfLm/v+o2nL+WUpRPoNdTPEPcP4Bx8EPz+0ZcNxe1diCO1754PYrb8rrxddMeFFRvsRYLsgL1QEl88/n3NG2yDrqdsCBOZB01nT01fMyIiIjK9QtXQcIqtXunfafuQyQ5A9xZblVHVam/WCNdObjvhOltxUrcWkm22SiZ1uFiN47i2EifeYptKC0VhzaV2AOjcAc/fYatf9j4J/YfGvu2qeXDCq+GMd8His+Dwk7Y/O4CalcUmXft2QO9ztkoFbIVEvt+UUHWwsnz/MACu3W/HtYGVVzXmqpBhXM9+h4rMs/vkZ+33uMH99vPJ9Nkm3nq2QrTZBjLxFvs5NayzA0Cqy362iT32tanDkO6D3kM2nOnqgL7D0HMIcmNp0mwEuQz0HrBDJdFqmNcK84+DllNh6dmw4FT7fdWdmkuO1dEQX3nzaZyzqpFP3raJnF8MRu7dfpB3fO8RvnvNBubXTvBngu3/8fO/Lm8yb0FtlFvfcw7v+dfHeamzcpVM3ikL4H1n+LTUQHs/7O6FW55x2N9fHtwc6k/zvluf5Mq19Xzu9Wtorp835X31iMjMpSBGREREZIy+/l/Pk84V7zQMew4fuWQCfaMk9uIcepI6/yXIzIdQ2F6UCNfZJjPcSPFEP1Q1esVJujs4+U7Axp+Uz1t1LtQugfRh+zy+eGInxcZA71boC5pkizbZ5sim6ARbREREXiZeFOpPtBUyg3ttKJPps4/9O+0F9OplwXeGyVTJeMXKjkw/DO6DxD4b/uSbLnMcGzbEFgahTDU0rYamD8G5H7LfPw5uhn2PQscWOPg8dL0EmUH7PkIRG1DULYSTroIT/xSiDTB4AA7cb5sCczyYd5qtxkn3QNeTdn/ANvVav8720XK0uCG7b1VLbEX0YJsNV1KHbcVM6hB0b7J9ycSX2O9gbshWoUTnQeN6u55cEpKHgs95T1BpkwiqbQ7ZQKb3EPQehp5OGOiamv1PDUD7Njts+o2dFqmC+atg4VpYvB5az4HGE+xNRZNoCu/NG1qZXxPlfbc+QbKk45gnd3dzxdd/z41vPo1XHj9/Quv+/oM7hzV/9reXn8iahbX85H+dyzXff5QdHeU3TsXDHmetbOS9r1jJhaubcfx0Wf8z79zQx7cf7uO7T+SGVdLcsbWHh3Y+xtcuNVy0MhT0zRN87/fidsiPT+Y4FJEZRWfPIiIiImOwo6NvWJMIbz9nOa2NVWNfifFt56sDL4HJkXXimLqToG7FxO+s7A06nX3uIUj1lcxwYP3V9uJGfxCgTKRZslwKDj9RvKO09jh7l6v6hBEREZm9XM9+L6heDsmDtkImecDe4JHutpUy8RYbykQaJ/d/P1wD4RNsZW+6J6j+aLeBSPKgHcA2bxWbb8OZaLN9vuAUO+T5GRuw5KtUcOyFasex31m6N9tACWzA0nimvcidPAiHH7cVKF7UVsdULZ34e5oObrjYxFs2YYOrxB4bpiSCIMtx7c8jNt+GMuH6Yr801UvtwDm2CbRMD2S6g4Cm3YY6ftJWT6d7bUDT3wWJPhhMQHIABvsg0WsfMUfY4RGkE7Yvmn2b4cmf22lV84KqmZNh8Rmw9FyoW1bs73CMLj5hPre+ewN/ccuTJAaTrHDaWeIcYvFgJ0//64+oW5jmlCV1eKGo/R33Iravm8aVMG+FbVItWlO2zjs2tfHlu7aXTTt9WQNvPH0JAC31cX79lxfy0IudwfMYLXVx6uIhnNLjwosG3+ebAYjPg4/+Kbzpoj6u/9Vm/nv74bJtdCUd/tcdcNfbsiyv7wF6Kr9pN1wezBTGY+DG7DbVTLDIrKAgRkRERGQMvnLXc5S0hEBVxOMDF68e+wqyCXsBIG1PskztGjpdB2pW2fa3JyLdFTRjMQhP/bJ83sqzoHGp7XPG+PZiRKVmzY60/s7H7V2Wbsi2MR9Xm9YiIiJzSmy+HXIp27dLYrcNSRJ77RCqsk2XVS0pabprgiL1dqhfG1THtAcBUJf9vjGwxw5gA5xoEDiEau223fDwCoFUpw2SBttsFQ3Y71f1a+0F6sQ+27Sq8W3A07Rh5lcZhKqgbo0d0l32PSQP2O+T+UoZsO8vXGe/44XrbdNyoTobQkQb7VCzyi6bS9twJt1tA5p0L2R7bP8zfrrYT6HJQjYJiS4Y6LZVL4kBSCaCoKYHutvt68Yq0QUvPW4HbrHT6hfB/DWw6CRoWG6bOKteQtw/AP07wHNt02iJg9C1E7p3Q9cezuzay6M1e/FMGyFy5dvpDIbRzFtpm1FrOY0n0q189r+z5PzyqqjrX38yrlsMWWJhj4tPWDD291uitamW7117Lr96ej+f+dUWuhPFpuJSOYf/81gz//KWlbZvyGwCcoPB+KD9ufjBzyXTO/JGvGhJMBMLAptY+TDTf+dFjgEKYkRERESO4Jm93dy5ub1s2l9csHLsbVGnDtuOYv2MbXas8QzwGsB5YXI7lq+Gef4xSHaXz1v/Bog02RN3sE2QjEf/LtuJrfHthZDGs+yjiIiIzE1e1Fa+1h5nL/4P7LbVK9mE/c7Ru91e9I+32KbLJvu9IFRd3J6fs02p5kOGdLcNgzL9xQoXxw3CmKgNC/IXqP10cZ2ReVB3vG3qDKD/RVvdA1C1GOadPvuqB/J9yrDOhlfJDlvhk+6y7z1fxVQqVG1DmXBdcfCqiqFbnvEhG3zOhSAgaNKsYbAYbBm//DPPJmz/PT0d0LUfDu+Hzt0wOEpYMFRPux12/L4wKQxc4ng4mxzABF315Ia9dOK9wWBDna6d8OztnAk8EoF2M48t/go2mxW0rj2X02p6wNRPWQW44zhcvX4J5x/XzMf/39Pcu/1gYd7d2zp5YM9xvPL4lcNf6OfszyM3aId8UJNN2OqmXNL+jHIpO4xUVQO2mb6yYCZqz0u8qB33IsG0qPqAFJkmCmJERERERmGM4f8M6byzPh7mva9cNbYVJDtsVYnJ2bsVGzdAKA6ZSXScCkHHtwft3YhP/b/yeSvOgqZldtzP2AslsUVjW6+fg55NxbtR4y22Ekb9wYiIiBw78hf/69fZMGZwnw1IMr126N1uL/QXQpnayW3P9cpDAj8zJJTps9+lMn1AX/lrnaA/mpoVNnDI69kKfTvseM1KqD959jetGqq276UmuGifTRQrXPI/m1zKBin5iqO8fJAVqoZQTUkzV3FbKZRv4i3P+PZCf3agGNLk15vtt8FWvkjET9swZ+AwdO6xoUznHji0CzLJcb1F1+Qm3CraRC1yuljkdfEaNsLzv4Sv/y3EGmzlzKJToWW9HW9aPamQYn5tlK/9z9N59Zfvo3OgGCB+7tfPcueHX0HYGxISuh64tSMfX8bYzz4XhDL5cKZsGAwqnXLFn9+ROF5JQBMENoXxaFCZVtKvpc4TRMZER4qIiIjIKH79TBuP7ipv0/l9rzqO+vgYyvsT+6Froz2RjS2wIcxU3WGWr4Z54QlIlO8f66+yJ0WZ4K64mtVju/CQTUDnY/Yk3nFsXzC1x03N/oqIiMjs43pQ3WoHP2Mv7A/uD0KZPjv0Pmcv7scWBE2JNU/++44bDkKeoElUY+wF5UyfrcxwQvbirxN0dF56Idj40P1M8aaSuhNtE19zUSjo4J3FxWm5VNBpfBDM5H9O+SAr0zfi6oZfYI8UBy9umz/LV1EYP1h/t71ByIvaptAaV8OaYD9ySejrtIFMfujcbfvqmSpVjSTii3i0q5Zd6XpyeLj4ePicMt9jfW0PTtcu6Gsb33qT3bDzATvkhatg4bpC02YsOhUWrIXQ2Gt06uNh/ua1J/CJ2zYVpu3o6OdfH3qJd19YoSpmNI5T0jdN/cjL5UO1QjATVND46eAxVZxm/CC0SQCJMe6HO+R3ZsjvzrDfq3DxGBY5hug3XkRERGQEiXSWL9xRXg2zdF6ca89fceQX9++C7uAEq2qJrSqZqqYwUp32Akj7c/DQzeXzWtdD80p7R2iqM2jXfcmR15nsgMNPljSfdibEmqdmf0VERGT2c8PloUzygL3pJHXQ3mXfv9MOhQ7lF9gKl9IqlYlynJLQYRR+zvbJl+ywr2k4FaqXTX77s8mQTuOBIMhK2kqWbF9JXySDxb5IoNj0GGOpmnCLTaDFF9txYyDXb4OZdJfdj6Z6aFoFJxD0RQMc3geHdsLBHdDdBv0HIdE9+rZqF0D9EluVsuhUmH8CzGsBz6UqN8iSA3186CcD9JZ2XdMG1yyM8erT6ljREOZf/+sZBnY/w8nOLk52X+Ik5yWqnHH0dZNJwN5H7ZDnhmHBibDoNPvYfLzdx4bl4FW+7PqmDa3c+shuNu0rNiX2tf96jqvXL6a5ZlINr1XmuGM7fsCGZKVBTWG8NLhJF/uvMX550DOu/XKCQKY0nMmPB5U2pdPLpgXjs62pQTmmKYgRERERGcF37nuBtp7yE4pP/8lJxMKj3OXpZ20Ak9hrn9essM16TFVTGNmEvcuzczfcdaPtTLXU+qvtBY98swM1x41+gmIM9D1frLCJzLOd2HqxqdlfERERmXvcsG0OrGqp/e6TOmTDj9TB8g7le7DfKaJNNpyJNkKodnqaCMv0QdfTNgBwPHtTSXzh1G9nNnIc2wRZKA7MHz7f+MX+dgqP6RGep+3P2PglFTb7i+sKBZUz+e+gJmsDoHRXcZn5K+2w9tW2bxInDDmfTG8HzzzxGKeuP5NwOGovtEfrbQCDsU2kZXrs91yThMTOwirX1MK/XAnX3O6Q9ou/Xz96KsmPnsp/X24CLi7Mc/G57uQsHzsljduxCdqegbanIDlKXytD+Rlo32SHUl4EGldB8xpoWmMDmuY10LQaL97A9VedxP/49kOFxfuSWf7vb7fzxT87dezbng5uUKkSqh7b8n52yO/IkcYzYDL2HMQYO+5Poslmxw2CGs8+FqrlvPLKuSMuk5/nzf4mDGXGUhAjk5PYS5XfDgO7IBwB3OCPoAs4wWN+mjPKfGfIciIiIkfXnsMJvvPAi2XTLljdxGtPHuWEPtMLh5+wbWQ7jm0Ko3b11O1Uuhs6H4XuPfC7L0G6v3z+ia+GhWtsmDLwkr3wMdpdoH7WNp2Wbz+8ZkXQfrruLBMREZExckMQX2QHKOlQvsNW5+aSkNhnh/zy4fpgqINIPXjVE2/OLJeyN5QkdtsLu24Yms8JOriXMXHckkqaMcg3FZftD8KYnmDotxU22UGgpH8aL2Z/Hk4YMPY7aLYv6H8mDdiKHKcqTiZehVNbXVJNMgB9zw3fBy9qQz1MUNWT5JyWJDe+Gj74X0e+ochzDJ883/Du9SEcLw5LXw+Rd0K4AQb74cCz0PY0tAfhTF/7kVZZLpeGg9vsMFT1As5sWs1PF9bx4KEa9pgF7DYLuOfxbv54Wgvnr6kQls1U+eCG+Phe5+eCECZbDGP8jA3u/KHTKy0TNG9nfDBp8KfwPTluEMgMHUaaHgxuaZhTadlgWum1UZ13HVMUxMikOAMvUuvvxunZPGLJ5cRWPCSsqRjYlIY5TjDulE8b+rwwzS3Oy08rW2bI60db59D1lI0zvnkKoUREZox/+M1W0tniN3rPdfjM60/GqfS32s/AwG7o3WZPBryYvQsz2jh1OzTYDp2Pw75N8MdbhjffsOJcOP/P7UWQ1CE7rWbVyF/uswkb6mT67DINp9qmRkREREQmo7RDeeMHzVTlh66ggqbTDqW8mO1EvtChfDB4VeUhjclXRvTa9Q28VLwoG18E9SeN/W5+mZjSpuJiC4rT/WwxlEl3F8OZXLJ440+eFwu+K3vgBtd80glyTtz+zD3X/v644WBb1eDGguqdLOT67O+WyRXX6UZ43YnQkYLP/X7k3Z8X9fmniw9ywYJD0Ovb7YWD3z0vZvelsRYWvQ4i77AhUioZhDJPB5UzT0PXzpE3MpqBDhjo4BzgnCHdTiZvjeA3r8RtXGmbN5u3wg4NrVC3BOLz5sa1I9cDPJhod1LGFAMZkysZr/C8dHphfMjz0n6L8s2tMYlKnfEohDRucRx3lOljWW7IzfGl11ePdI1V4dC0URAjk2KiC0g6TZj44uI/SUzJHy3f/nHEL5lWaf7QFefnH6MqhjuUPy9dZsTXjBYIMfz50HnTPW3ovh217U3XtNLnIjKb/OTR3fx2S/nJ4jXnLuf4hbXlC+ZP/hP7iv+3Ygtg3um2OYIjcEwu6OQ0Db177J1hbhgI2b8fqS5IHraPux+B7fdCb8fwFS3dAK/6X+CFAdfeXehFoXp55Q2nOm2o46eDtrvP0l2jIiIiMvUc1/Y5l+93zhhbCZHuCb4DBY9+ptjHRP6GkqHyTQz5mfKL7wCRBhvARJum9e3IEbgh+zMo/TmMFs4M61MkRI5wUCkVtz9vk7U3ECUP2OWHXkNyI8VtRpvAq+IvlobYcFo3P3t8D9va+tjW3kt/yv7OnNoS459fX0NrVRyy84P+TRJ2nxJtkBuwF7PLwsCY3U59HTRfDme82VZyZX04sMWGMge2QOfzcOg5GOxiomKk4dB2O1QSrrKBTP0SqFsaPC4uGV8CsSnolynQnUhTGwvjuTPs2objYPuJCR952bEyfhDilAyFoKfCvLEOfrbkGmiF65355WaSYcFMyXjd2mIFpIyLghiZnFAVWSduSzfD0SHJ6pBUtqz0bkgpHkwgxDHFx9Jxc4TnI04burwp2YfxrLNkeRjy+gqhUyWm9PXj/JnIzPQyBUdOLkdj7lmcQw0QCo3rtcNCpLkYxlVaptL7nsppCuNmvnx7xUEnlN9/qJ3P37W/bJF5cZe/OtvYvl+yg/ZkLZso/8IcrrN3fla1jv5zNwb6d+Fsv531bb/F+/evQ8cOSPWP/JrRLFgLl/wlhDx7EWIw2PeG04JmAobo3wk9W+x+ROqh6Wz1ByMiIiIvD8ex35nCQy4U59L2Anh2ILhIH4xnB4p3qvtZIBh33OJ6ovMh3qLv3TPVOMOZiOmFZDtkRrhkWQhemu1jqKbiz/7UpQ2curTBbs437O0aJJHJcvyCWtx8qJBL2u2nu+0NVpmeYvNX2X77+5fqtN/7vRh4cVud48WDIQpVdXDihXDqn9jm9kK1MNhdDGUOPW+Hzufh8M7JX3DPJOy6Op8feZloLdQsgtpFULMweFwQTFtYfIw1DPvsUtkcj+48zD3bOrh3Wwe7OhPMqwrz1rOX8c7zVrCo3p43pLM+T+3pZkdHP7mSa10OEAt7xMIu8bAXjBef18bCNFVHij+DmaRwjXIKw51KTP56Yv56Z67keT70GTq9wryKr88/H+F6amHa0PlD9zGYVun3daaFRrOIghiZFGdgFzX+XpzeZyffNNmYQpxRpg1tY9ENlU8bVzg0jf8QzGghTf6fl6kwjwrLDpk3rvUNnVey/sK+VZr/Mk0buo9D92mqp417P8ep7P0MWe1UymUJm35b9p/Tn/gZZcJB1UjzR1imYhUcFV5Tuvworx9xm2NZpkIYNexvIIx4rA8LuoaMjxp6lc7Ldz4atC2cSwUdRabsePAl0xj45uNw4yPDS7E/cV6W+uxOGJqVOC7EF9u+VcZSUZI8BE//AB66mVD3fkbpvWVsGlfBZR+yIYwXhXSvnV6zcnjntH4Oup8uts9etSQIaybaHoCIiIjIFPEidqj0fWpo00P5agUFL7PXCOGMGeykx+3C1J9im6wq/LyrSkKQ8d9A5LoOy5qqhs/wYuX9G+WbvcuHQ+kgLMqlbZ84+ZuxUoftOE7JvsVt02mhOEQaoaYe5p0Pa18L4Vq7TC4DXbtsQNO104537SJzaCem6yUiTnb4Pk5Eqs8Oo4U1YI+5mgVQPR+/qpmtvVEeOeDSnq2mjzpWmVoanDo6B2u55b5ebnrgBS49aRF9ySyPv3SYZGZiLdmEPYcFtTFa6mPEIx6D6RzJbI5UxmdhXYxzVzVy3nFNnLq0gbBXfm5mjGFXZ4KHX+ykP5nlxJZaLlzdXLn56JnKcYJrkDPoPGxoODTsRvmS6aGao7uvs5iu0smkmNgiBp35mPiSkqbJSg7QsoS20gFcurIZ1BzZ0HYSK1bxDG2H8UjhUIVpo4VDbklnXjLzzNDgyGQzdLs9mMYNtiJmQkHYaNubzL6P9TN7GT6/iu97vPs5Ti9XGDfLZXKwvx/290Fbvx0OJpxRP/KcgWQWBrOQykIyB4MZ+5jMDh9iIVhUAy01sLAajHHoSjkcTDhs7hi+oQ+eV8ubN9QHzWF49uTKKzkZHMvfaT8HW38MD3wDDlTobHS85q+FU98ArWsgFNwVaIBcpz3Rq1tbvnx2wDZFlum1/+PqT7L9x4iIiIjMdG4Ie/lqjB3Jy+zkhiDSSNJtss3rhqe5KqESxyk2R8YSO60snOmzTetl+mwFj5+y37NzQTiTTdjAEDfo8yhmwxkvZs8fYk0QaYKla2Hl2bZ6xosRdhxu+cOLfPs/H2SZ00Grc5Blbgdn1vVw7rw+Qj0vQX8HU34CmUtDz17o2YsLnAyc7DBiQUjKhOl8vpYuU0sndRwO13LY1NFtauihmh5TPeTRTs8MufycyRn2dQ+yr3tw2Dae7+jnwR22ecKqiMfK5mrmVUWorwrjOg6P7zpMW095k3arF9TwrgtW8KenLyUemUHhxmwyE8OhOUhBjEyY7xuoPZ5eb4dtC3+8/yQLTXmVlNZVKrcbsdRuhLBn1HWMFg6ZIfs2g9poHKmCp1Kw4042MBopdBrSlNyxbtid+EdtT8plMqTceRBbdHS+uB5rpj04GiE0GktgNGrl2xiWqViJV+n1Iy1Tab+KlSvGGPb2+Dy5P80zbWleOJxlV1eWPd1ZctMcUA1k4IUuO5QbvuG/vfxE3veq4ya3wcEuuP29sO3uib3eDduTuFg9rLwQ1r0eGluKTZBVLbbNIPRstX+jG88sVrkYAwO7oHebvaPQi0LjhqBjVBERERERGVVZOFPCzxVDmcLjAGS6g2bWBm2TxuluO46BHgDHVqK4UdvMWqgKIvO4ZtU87ly2mId3N/GoWQs+cBiW+HG+9fYzOK2lCvraoHcf9OyD3r0lj8H44OFp/SiiTobFHGaxM77tJEyUHqrpNtX05oOaktCmn7gdTPGxjzj96Tgv7Y/zLDEMI1+L2tHRz6d+uZn/+7vtvPcVq/hfr1w1rJJGZCZQECMT9syXLmXe4B7W4bHnmc9gvAiOG4aQ7SzLuGEcL4wTihAKRwiFo0QiUbxwBC8cIRSK4IWjhCMRHC9iOxj2IvYuiMLzoOMtL2KbPiuMV5jnRYLn4fJ1DSlPNMbQl8pyoCfJ4YE03YMZuhNpehIZEuksyYwdMjmfiOcQD7vEQlAdcVnWEGFlY4TWeWGiHlMbDs2WaiEYuYpnXJVAUxUOzZQERI5JZc1vHdU9mRX2dw9y7/YO7t9+kCd3d3GoP320d2lUn7/6ZK45b8XkVrLnEfj5n0NvW8XZ/dFFxNe+Bq/lBGheBrEaykKy/P84nKCt6gE7PR/CVC+3/x96ttrn9SfZihiwJ33dz9gmFcCGL41nqj8YEREREZHJcoP+GSMN5dONbytjsgO2r6NMvx3SnbYfmmwiaOZs0IY3qUMwsBsX+NJpUa7YfyoD2WJVwr7uQd707Qf5+1fFeMeGZpzmJdByKoQrVOZnBqF3vx36D0Bfe/C434Y4fe0wcBCSvdP96ZSpclJUkaJlnAFOqb6SkGaAWNnzfmxwM5CK0/5fUb7xWB1vPmcFrQuaIVIDkWqI1NrxaPAYikzhOxQZGwUxMmGN6XaWOe32SS4YZqAcHr7jksMjazwyxiWDRzUuMeOxADsvg2eXCZ5n8cgZl2x+PJi3DY8tuEQiUeKxKNWxKDVVMWriMeqq49TGY7ihsA2BXC94HPo8GLzw8Gn55QoBBMXAoTR4cN3iRWDHATc/TnG6i33MVx5VrAQaSzg0tDmlGRQMFZqRqxTsjNIf0JiriY4QOjlqQk5kJMYYNu/r5c7NbdyzrYNt7X1He5fGJOK53PCnp/A/zlw68ZX4OXjwRrjvBjs+VH0r2bPewTPtg5x9+vpiP2umvMyeXGb4/9dIg+2c1I3Yapdswk6vXQ3VK2yHook9MLDHTnfDUL8WqpYpvBYRERERmU6OC+EaOwxlDOSSxf5mMgO2f9cgpFkW6+YHr36J9z/QyqFksYWLtO/w9/ek+N2WLXz+rF2srE2CE7bVNOFaCNXZoCEUDM0tsHClPV8oG+w5R0dXN5+45R66DuxmgdNNk9NLI700Ob0siyU4pzlFTa4bEodhsMfeEHaU1TqD1DI4thsgE8C9R1jG8SActS0PhEuGUNw+RqrsvNIhXPoYh3A8mBeMh6uCx6AJ60iVneaGX5abivcctn3n7OkapDuRpithbzz3jSEW8ohFPGIhj4V1UU5sqeOkllpWNFUTUvXQy0ZBjEyYOwP+EI+FRw7P5AgT7O8IfT6PWw4YCIbOSazn5ZAPDPKhj+PZIKcw7hX7pCkEQUOnB2GDWxI+uC7loVF+/tDnTvm00lCpNFAqLBvsMyXj+emF5Uq34VXeftk+V9q/oe/BC7YzgV+M0kCoEOh4lAU1FcdHmjaG5UVmIGMMT+3p5s7N7dyxqY29XcPb/R2L2miIRfUxFtXHWFgXIxIa+XfedbBfLMMe8YhHNOQSD75k2mlu4YtnNOTSn8zS3pukrSdJe0+SsOfQUBVhXlWEhqow61sbWNwQn+hHAPs3wq//yj4OFamB894Dx50Ofo5Q+yM2SPHqg7+JEQoVgG4oaK4gBk60ePKUS9gql1RH0IGpC7XHAz60/5c9ucurWmqrZDy1qS4iIiIiclQ5jr1oH4oDlZsKPnt1mt+c2sUHf/osj+1JlM178EADr73jVD5w8n6uW7uPqOmBTE/lbbnhoPmzqD0XcMPgxdjRW821v4mwtzcKrClrnfndZzfw1lcvIhaJghPcVIwH2ZQNZBKd0B9U2Qx0QOIQDByCZE8w9EKq3w7Z1JR8ZNPG5CCdsMN0cz3b0kGopDWgUEmLPmUtA+Vb/Yna56FIMC1Sso4IhKL0Zz2e7YTNh2DTQZ/2AYeUCZMmRBr7mDF2PBVMyxAiV9IPTDTkcsLCak5cWMPallrWttSyekENTdUxHNfTjXxTTEGMTJhrspMLMuTlk69gmSXh2VFXCHEqBFCVQp2yIKjS8iXTKi7rjXE9Q5bJ/8MuDGFcHFZ17cB9are9SyP/D98taa7PC9sLuqXN+xWa+QsGt+TRDSq39A9YRuD7hid3d3HHpnZ+u7mN/UM6TxxNY3WE9a0NnLy4jlXzq1nRVM3K5moaqmZhqfhgN9z7D/DY9ypXDS4+Dc5/i+38sm8bZJLE/QMw8BL0J6nUR01lJXdQRRqgajn0PV8yOwzxFqheBpF5k3pLIiIiIiLyMvIiLGxeyI+vm8+Xf7ed7z7wYtnstO/y1U1L+Y99q/nExY1ctiKDkwv6qMn0QrYf/JS9YcvPQrYX0lnA8NCBOq578Hh6hrQQXR/J8c8XH+TCpfuhc0dwDSAYnJLO212gPgrzVoGzJrjWESq5WTdUvKksl7bnR8luG9Dkw5pUX/A8CG3yYUgmGQyDkB6c+UHOePg58Afte5tCNcDZwQDAGE+hc8YhS4g0IdsK0CGP9KEQ2c0eGUIcxOOAE8LzPLxQiKzjkTY21EmZEGkiNF5wLSddePWUvp9jgYIYmTD/qm+ybf/TvLjzBeY1LSSV8Ummc2SzGfxcDj+XhVyWbNYOuWyGXDYbVKdkCTn2MUyOEFkiZAmRI+zYaeHgeYicnVdYvuQ1zgxtD01mN+NDzgdmX3DlAacA7PrZ1K54xOCoQuVUaRN7+XHHC/p5ChWDncKXO68YCpU121c6PmQ5r2Qdw5YdOh4u3/aoyyt0GgtjDC8cHOChFzt5+IVOHnqxk8MDY+vvpT4e5qLj53PR8fPZsGIeyxqrcGbz520M7H0cttwGz/zM3hU2lOPCuktg1fGQa4esAcfBMTnCJHFM1jZd4AVl68an0KRkLhWcSKXttrygzN2rsq8J1RTubiNcC/ElEFugqjkRERERkVks7Ll88sq1nL2ykU//x2bahtzstvNwkv/vF/vZsHwen7zyDM5cXnIDVi5tq+hzg5BNYLID3PJoJ5+/L0FuyL1frbVZfnjZQY6rS0EuB7l+G+AYH0w2WCp/Y2g+nAkXq/ULz8PDz0EcIB6BeDPQPPKbzW/Lz9pHk4VsBrKDQVAzCJlEENIkg+cpG9Zk03Y8k8bPpNjf49M9kCNOinjQN02cFFEnO/L2jzGeY/DIEB16zWvoabkPjHCav/HQhdOxa3OeghiZsKVnXkk2vh0Ge1mzZgGeGwLC4MQp3q1b2h+HbY4qY1yS2RCDOY+k79GTDtGd8uhKefSkPZJZj8GcQzLnksg49KQ9upIOXSmXvpRDMgeDWYdkFnK+oTqUo8bLURvKUhPKUe1lqfZyVHlZasM56iM+9eEcDZEs8yI+zbEcTbEc86K+DXL8oC8UPz+eA98fcXoqk6MnmaNnMEd/0qcv6TOQzpFI5TC+jxeERx5+IUgqPHfy07OEyC9rH8Pk8Bz73GbSPi4GL5hvXz9D+mWRY08hnDpGDOvLaejzCgGSV9IfVGmJcSEICo8e/hxhvVnHI5FxSPouaeOSyrmkcfFCEaKRKJFolEgkSjRqh3A4OqGAKZvzSWZ9kpkc3YkMPYNpugYydPSl2N7ey9a2Pra299KXHPsX2eVNVVyxroVL1i5gfWvDzG2DNjMI/R2QTdq+WfwM5LL2RCY/nkkUO77sa4Odv4ee3SOvs24hnH4xNC6wJxZu3IYnkQaMW82BUBPHLb8Kr7qlcjvSecYEJyWlfXhhAxhXX+dEREREROai16xdyDmrmvjq3c/xgz/sxB8SpDz+Uhf/49t/5LKTFvKBi1dzWmtDsaULGkhmcnzql5v5xZPDm+A6bUk133vLSuZX5Wzo4SeDx5S9IcyU3vwcXB8b2tewnwGTstMdBwgVrwMW+kXJXx8s7aPXBeOAY4J1uTbcyTtSdUfhvCgbXLPL4pocS/0MvYdcbniyjkfao/RlbEVPiGwhlKkqBDTJwvjiaD9nzuvCy6VxcxlMLstAyieT9ok6aWJkiJKmxk3RHE5SH0pSFTQA5vo5nOBm9LG3cjC7pYx35IVkGJ25y+TEWhh0mjHxVtu+YT4+LaTgwy/6hYEwhtrCFBMM2WAonZ4frfSHbOg0pyTwccCJBX/US0Oh/CPFP/6F1+X7IRm6bNB/STAexWEBsKCscy0XYwxdg7Czx2dXl09bnx3a+33a+nK09/kcHpzshWxTCGfcIOgpjttHDx/PKQZBQ8Oc4rjBdYauo8Lyjl943UjbDJHDDZYr24+ybdp1FbczyvLBusKOT9jJEXLsciEnRyi/f8F7dIxfeHTwcY1dtxtMd51j45+gTLF8GfcMEgLqgmGiMkH8m8Uj53i2DNnY8uOM8Ugbjwx2egaPrAmRwcPFoxmPejzOCF6fCeWXC8qZS16TxaOuOsrxC2tZu7iORQ1VON5W6HDhoFPsjynf51Ph729pP1JBCOV4xSCprCm+Iw0lfV5lU7Y948QhO/S1Qc8+6NtvA5X+Djske6fkZwXYAOzki2HlCRBrtPsSboRIvZ1ftRgTP45u736oXgHh8Kirs5/JEZYREREREZE5pyYa4u9fdxJvPH0Jn/6PzTy1p3vYMnc9e4C7nj3Ahaubufb8FQyks2xt6+PebR1sP9A3bPlL1i7kG29dT1VklEvDfrYYyvgp2xdlYTxfuZ8PbcZzvcu3N0CDPcfx4kFFTUmLGoXgJn9zd74lDseOO06wTT+4aa04ftICn++t9THGZ19Phm0daTYfSPP7nSk2tmXKw6z8+CDcPNaWw4a0mlYbztJanaKpJk1TJEVzZJDGUJJqN0W1k6bKSRMljedn8UwW18+QzfokM4ZUxpDO2PFkBtIZP2gZKGMHJz+eJUKGMFkiTpZoMC3qZKj1MlR7tsLFM1kcPwinplHKV6QwEfrUZHJiC0i58yC2ELz8H0FTkkznQxaKj8bYXCMfrhi/mNcU/nCb4msL6zDBKkr/YpYEJ5RsyxibquMEYYxTXL7wmvw4wesZMj0/ToXXDA+YHKDRg8ZGOLNyn2skcw4HBhza+h3a+x3aBqC93w5dSehJGrqS0J00pCv+zXQI4gZg2N/+orFmD8dERmFKQqliKFQWBjnFSiYXE4RNubJlPadkfOi8kgCsNJwqVjwF63fKw6z8PlRaR6EKitJ9K+5rxe3nl3NM5e0H+xZWk37HrHBQfQdUzLKntN+vNLAnGI41revhrDdAXYs9kcgNQqjWnkREG6H+JNt3S2b2NX8oIiIiIiJHx7ol9dz2vvP59aY2/u/vtrHn8PDk4MEdh3hwR4Xmkkt86NWr+cglx+O6RzgBzN/kFqo+8s75mfJmlf100LJA6ZApH8+/biL9Gedv3itrLi1oVcKxg+OFWNocYumCEJecEuIjToiupOH+Hb38v40dPPjC4fFvt4K+TIhnu0PAGD6nKbCkJsuly1Nc3JrknEUpYl7ptVcoXJfNBS385DLFm01zWTvd5IJpwbK+rXDK5Qzdg4ZDA3A4AX0p25pQ1MkRdWwXEZFIDavWnfOyvNe5RkGMTI4TwlBy9/G4EvDJyifeJY+FEMgvCXBK0/Fgml/6uvz8kmXJzy99Xck6zdA/cqW7ZYJk3gwLb2I4LAeWVztQUykcss+NcUhkHbrTtsm2gaCUMr++nO+QDJpvG8y69GcculIe3SmX7pRbHE+6HE659KWnpxmgqGcIl6zaAIkMmCm9mjtZTiE6GdFYAqk5FVqZQuA0LAjKhzclVVXD5pVULhXnD5kXVDC5lcKkIc3tlb62tDm/sJMrNNuXD5by/UOFnHzTf9mgOT/bh1R+u/nx0r6mbKA2p36QMpPUt8Dxr4ZV50LtPMBANmFPKsIN9i6u+pNs9cts7hNHRERERESOGtd1uOq0xbz25IX828O7+eY9z9OdGFuQUR3x+Mqb13P5ukXTsGNBEMIozS2Xyjdr5lcKa7JBH5nZYlBjMiXj+et44w9x5gFvWARvuAIe2Qc3PuLwyP7Rz89cB+bFXToTR6+59mXzIlyxtoEr19Zy6qIITqGJuPww9Plo00e+LuIBTcEwosbToWopGd1YOG4KYmRSTPN5dIS6MC1XFJtVMSVhRuGxtFJmhPGyYKTC9FGXL90OJfNLq2mGTCsLbyo8Lywz4U9nyLpK9mXoNobMc4yhGkO1MSwZ+prCfpZug+D9D92ufZ7IQHvCo30gxIFEiJwpfT0l6zA4GGKeIe7liIVyxDyfWMgn5uaI5x+9HBHP4OIPWY/tRqQv49GVDtOdCjGYdW1glHNJZG0/QN3BvK50iO5UiO7gsSsdIpGdnnYma8I5GqI+86L2sT7qUxWy7zUWMkS8CsUAZRdLRxgPlgm7EA8ZYiGIekFrSxVf55RMckZYJv9QWpFVnB92HWJhiHkQDx5jITvukuXJpzZx/EmnkPFDpHLlGVLOOKRyDsmsQzLrBo/YvpcyDsmssSFfFpJZyPrF7Rrs88EsJLOGRHbo/+/yT9A3kMrZZQczhowPsZBDPOQQC0HYc4KPr/KXnoyPLc/N2qHQRU2Qc6ZzhlR2fMGKg2/7Y6oU8DglIVChoqjYf1N4SPBTGC8JfkJkg9f6hJ18CJTvF6o8ZAoN2Y/CMOJ+ZPEcv+J+RFTlNA2coL+efPNowbgbgnhdMNRCvAaWrIMFa4t9teSS9m+1F7cBTKQB5p0+eh8wIiIiIiIiYxQNebz7wpW8ecNSbn1kN9/7/U4O9Y/Ybgorm6u56ZozWbOwdsRlXlaOC17UDuPl54IQJlse0PiZILzJ2sfS8QrTzlli+MkbDQ/tM/zuBYe+dPEaSzwMS2sNa5vh+EaIh3329MJDe+GhfQ6bOmB3D6T96bnJrqnK49wVVZy3vIbzVtSyqjmO43qVm23Lj5dNH2W/CtdYRwtt8tdbS+cFz8OTaTD92KYgRqaeE/TBMloFwmxSsYm0cQQ9R3zdCOMjbvtI4wybV2UMqzCsGmn949rG8PWXtsfpGZ8GoGHo8mXhEUPW5WMbWkuRykHPIHSloC+dDwSc4OK/DQySWYdkBsqvwRuqQoZ5Mb8kcDE0RHM0RHOEXVO2bDF8Gvp86Hs9wv4P/UyHLm9Gej50vaWfa+mkIcuMVI3lOJB1yPk5Vod3sJocXtiD8JD2pgpN+ZU+H1qVVdr/UYWm+krXUTbdHeE1FeaPeVsu5dst31ffOKSyDomcQ08yaOIvZR9tc38OXUnoTRXDplQuRNYPEQ/ZACsWguowzItBfcwwL2anlX7kGZ9COJXIOPSk7HY6g+10B0NPamJfwprihkU10FIN86sMDdHg9zjm29/hiM+8aJb6WI7qkE/MtaGM/Z3JkcvmSGbskEplSWZ90pks6YxPKmvIZH0yWcjlDK7J4ZgcrrFBTszNEXGyhceIY4OiCDmirg2W8mXKxcdcsbKwUMpc8rdg6HJ+/otb6bGQD86HHHOlz4euy9j3a6fliusdq3AcotUQq4F4PVTV2fFYNcTiEItBJAqh/P+vSkGfA6EqCNXYEv1wDbixYJZrmyFzPPBiNpipXQM1x6kKRkREREREplxtLMx1Fx3Hteev4OdP7OWWP+5i56EBFtRGOXFRLWtb6jh1aT2vPnEhkdD0tJbysnM9wJv8ZUc/h2OynN+S5fwzKgQ2hXNOO7RWZ2ldlOPNZ9rnuVyW/b1ZdnVlaevN0p306Ro0dCcNfWl7/SCVtTezZoectlaFoSEKDTE7zK8ytNRASw0sqoYF1T6O0wP02Bd0jfO9Ffq9Lglr8n1kF/rJLh13Rp5eOs0NMbVtmh9bFMSIHEn+4q/+zoxd2cXW8YROPlFggTEsGK2iaIwBVMXxsYRMk1nPWN9zpWbuhlY7jVIuWuFDBwwmm6PHyWLqT4FQqMJ6TOXHSsscMQQq3dehzystV/LNw4ywTMVtjBBiGRsHxTHEMTRFHIgMrTgqDXFg+IFcoT+owvKlrx9hfaZ8eznj0JdybGCYcxjMOMU7ZBwHDHhuMQCKeYaaiGuDn2FBkwvO2P5Ne9jWaCu2SJsPL4bdzVKpTHmk6fnXB9NnksKxRDA45fMMtkQtHA6Wy2HDlJitWPFi4EZKOocMMyxoHBYWuvY1jgcmG2wr6BDRDe7oql4GdSdO7A4vERERERGRcYiFPa45dznXnLsc3zdH7v9FioEOEztn84DWhdA6dEb+HLzS4GeHnJ/7w8/DGTptpOmllSslrQTl94H8ufwUazwdwjOksmqWURAjIlPPGXoBWyZsnMGPyaTpDKUxCy8uBjHjCrQMI1ZzDVt+6LSxvO4ITQSOtp5xh1MvPw9oiEzklUN/nsE0k2VYxZLj2kXLQoKSgIBgXiEkKpmeX74wzy0ERJXXV/qa/DIuFKpkhoY0+WnZ8vfhOHb5UatCSn/mJX17mRyFL5DDvqQOrYYZ4ffD8Yphixu1j14sCGGi5ftVWEW+4scHZ8jvp8najihNcsh2XIjOh/oTVa4tIiIiIiJHhUKYo8xxgpsqX+bL7iWt1ZQHO6bkXHpocGOGT6vUDUTpMl7Vy/u+5hAFMSIiM9l4K7JMhKwTtxeB8/02zTVlodIYw6ARgx5/9MeK/VJVeCwLncb4WHFdHPlnXdaEFyNmDzOKoSQkKi2JLilzLgRGpeXSzujzcOzn5gTbyFddlYWVwWfruLb5NAf73E/ZZsTS3ZN7b24YYgsgtghi84OKGhEREREREZGXkePYmxDxAJ2XzkQKYkREZHYpC6fmSF9UecPCopEexxsWjbZspaBotBCpwjoq7t/Q95YPSWZY02Zgv6yG4vbOnnxTZU7Itn+bb1O3NAzyokGFTTRoI1dEREREREREZGS6eiAiIjJTFEKmWd6J4miB0linVQyKJhgQ4QTNkoXBCdsgxYtDqMo+qopFRERERERERKaRghgRERGZWnMlUBIRERERERERmQK6QiIiIiIiIiIiIiIiIjJNFMSIiIiIiIiIiIiIiIhMEwUxIiIiIiIiIiIiIiIi00RBjIiIiIiIiIiIiIiIyDRRECMiIiIiIiIiIiIiIjJNFMSIiIiIiIiIiIiIiIhMEwUxIiIiIiIiIiIiIiIi00RBjIiIiIiIiIiIiIiIyDQ5poKYb33rW6xcuZJYLMaZZ57J73//+6O9SyIiIiIiIiIiIiIiMocdM0HMT3/6Uz7ykY/wqU99io0bN/KKV7yCK664gt27dx/tXRMRERERERERERERkTnqmAlibrzxRt797nfznve8h7Vr1/K1r32N1tZWvv3tbx/tXRMRERERERERERERkTkqdLR34OWQTqd54okn+MQnPlE2/bLLLuOPf/xjxdekUilSqVTheW9vLwCZTIZMJjN9OzvL5D8LfSYiM4OOSZHZQ8eryOyh41Vk9tLxKzJ76HgVmT10vBaN9TNwjDFmmvflqNu/fz9LlizhD3/4A+eff35h+he+8AVuueUWtm/fPuw1119/PZ/97GeHTf/xj39MVVXVtO6viIiIiIiIiIiIiIjMbIlEgre97W309PRQV1c34nLHREVMnuM4Zc+NMcOm5X3yk5/kox/9aOF5b28vra2tXHbZZaN+oMeaTCbD3XffzaWXXko4HD7auyNyzNMxKTJ76HgVmT10vIrMXjp+RWYPHa8is4eO16J8S1pHckwEMc3NzXieR3t7e9n0jo4OFi5cWPE10WiUaDQ6bHo4HD7mf7kq0eciMrPomBSZPXS8isweOl5FZi8dvyKzh45XkdlDxytjfv/uNO/HjBCJRDjzzDO5++67y6bffffdZU2ViYiIiIiIiIiIiIiITKVjoiIG4KMf/SjXXHMNGzZs4LzzzuOmm25i9+7dXHfddUd710REREREREREREREZI46ZoKYt7zlLXR2dvK5z32OtrY21q1bxx133MHy5cuP9q6JiIiIiIiIiIiIiMgcdcwEMQDvf//7ef/733+0d0NERERERERERERERI4Rx0QfMSIiIiIiIiIiIiIiIkeDghgREREREREREREREZFpoiBGRERERERERERERERkmiiIERERERERERERERERmSYKYkRERERERERERERERKaJghgREREREREREREREZFpEjraOzBbGGMA6O3tPcp7MrNkMhkSiQS9vb2Ew+GjvTsixzwdkyKzh45XkdlDx6vI7KXjV2T20PEqMnvoeC3K5wX5/GAkCmLGqK+vD4DW1tajvCciIiIiIiIiIiIiIjJT9PX1UV9fP+J8xxwpqhEAfN9n//791NbW4jjO0d6dGaO3t5fW1lb27NlDXV3d0d4dkWOejkmR2UPHq8jsoeNVZPbS8Ssye+h4FZk9dLwWGWPo6+tj8eLFuO7IPcGoImaMXNdl6dKlR3s3Zqy6urpj/qATmUl0TIrMHjpeRWYPHa8is5eOX5HZQ8eryOyh49UarRImb+SIRkRERERERERERERERCZFQYyIiIiIiIiIiIiIiMg0URAjkxKNRvnMZz5DNBo92rsiIuiYFJlNdLyKzB46XkVmLx2/IrOHjleR2UPH6/g5xhhztHdCRERERERERERERERkLlJFjIiIiIiIiIiIiIiIyDRRECMiIiIiIiIiIiIiIjJNFMSIiIiIiIiIiIiIiIhMEwUxIiIiIiIiIiIiIiIi00RBzBx0ww03cNZZZ1FbW8uCBQt4wxvewPbt28uWMcZw/fXXs3jxYuLxOK961avYsmVL2TI33XQTr3rVq6irq8NxHLq7u4dt66qrrmLZsmXEYjFaWlq45ppr2L9//xH3cdOmTVx00UXE43GWLFnC5z73OYwxhfltbW287W1v44QTTsB1XT7ykY9M6LMQmQnmwjH54IMPcsEFF9DU1EQ8HufEE0/kq1/96sQ+EJEZbC4cr/fddx+O4wwbtm3bNrEPRWSGmgvH67XXXlvxeD355JMn9qGIzBJz4fgF+Od//mfWrl1LPB7nhBNO4F//9V/H/2GIzHAz/XhNJpNce+21nHLKKYRCId7whjcMW0bXmORY8XIer3mpVIr169fjOA5PPfXUEffxWL4mrCBmDrr//vv5wAc+wMMPP8zdd99NNpvlsssuY2BgoLDMl770JW688Ub+6Z/+iccee4xFixZx6aWX0tfXV1gmkUhw+eWX83d/93cjbuviiy/mZz/7Gdu3b+cXv/gFL7zwAn/2Z3826v719vZy6aWXsnjxYh577DG++c1v8uUvf5kbb7yxsEwqlWL+/Pl86lOf4rTTTpvEpyFy9M2FY7K6upoPfvCDPPDAA2zdupVPf/rTfPrTn+amm26axCcjMvPMheM1b/v27bS1tRWGNWvWTOATEZm55sLx+vWvf73sON2zZw+NjY286U1vmsQnIzLzzYXj99vf/jaf/OQnuf7669myZQuf/exn+cAHPsB//ud/TuKTEZl5ZvrxmsvliMfjfOhDH+KSSy6puIyuMcmx4uU8XvM+/vGPs3jx4jHt3zF/TdjInNfR0WEAc//99xtjjPF93yxatMj84z/+Y2GZZDJp6uvrzXe+851hr7/33nsNYLq6uo64rdtvv904jmPS6fSIy3zrW98y9fX1JplMFqbdcMMNZvHixcb3/WHLX3TRRebDH/7wEbctMlvM9mMy741vfKN5xzveccR9EJnNZuPxOp5tiswls/F4HeqXv/ylcRzH7Nq164j7IDKXzMbj97zzzjMf+9jHyl734Q9/2FxwwQVH3AeR2WymHa+l/vzP/9xcffXVoy6ja0xyLJnu4/WOO+4wJ554otmyZYsBzMaNG0fdn2P9mrAqYo4BPT09ADQ2NgKwc+dO2tvbueyyywrLRKNRLrroIv74xz9OeDuHDx/m1ltv5fzzzyccDo+43EMPPcRFF11ENBotTHvta1/L/v372bVr14S3LzJbzIVjcuPGjfzxj3/koosumvD+icwGs/l4Pf3002lpaeE1r3kN995774T3TWS2mM3Ha973v/99LrnkEpYvXz7h/ROZjWbj8ZtKpYjFYmWvi8fjPProo2QymQnvo8hMN9OOVxEZ2XQerwcOHOC9730vP/rRj6iqqhrTa471a8IKYuY4Ywwf/ehHufDCC1m3bh0A7e3tACxcuLBs2YULFxbmjcff/u3fUl1dTVNTE7t37+b2228fdfn29vaK2y7dN5G5arYfk0uXLiUajbJhwwY+8IEP8J73vGfc+ycyW8zW47WlpYWbbrqJX/ziF9x2222ccMIJvOY1r+GBBx4Y9/6JzBaz9Xgt1dbWxp133qn/rXLMma3H72tf+1q+973v8cQTT2CM4fHHH+fmm28mk8lw6NChce+jyGwwE49XEalsOo9XYwzXXnst1113HRs2bBjz6471a8IKYua4D37wgzzzzDP8+7//+7B5juOUPTfGDJs2Fn/zN3/Dxo0bueuuu/A8j3e+852FTpZOPvlkampqqKmp4Yorrhh125Wmi8w1s/2Y/P3vf8/jjz/Od77zHb72ta9VfB8ic8VsPV5POOEE3vve93LGGWdw3nnn8a1vfYs/+ZM/4ctf/vK4909ktpitx2upH/7whzQ0NFTsZFhkLputx+/f//3fc8UVV3DuuecSDoe5+uqrufbaawHwPG/c+ygyG8zU41VEhpvO4/Wb3/wmvb29fPKTnxxxGV0THi50tHdAps9f/uVf8qtf/YoHHniApUuXFqYvWrQIsEljS0tLYXpHR8ewVHIsmpubaW5u5vjjj2ft2rW0trby8MMPc95553HHHXcUyrLj8Xhh+0NTzo6ODmB4Iisyl8yFY3LlypUAnHLKKRw4cIDrr7+et771rePeR5GZbi4cr6XOPfdc/u3f/m3c+ycyG8yF49UYw80338w111xDJBIZ976JzFaz+fiNx+PcfPPNfPe73+XAgQOFitTa2lqam5vHvY8iM91MPV5FZLjpPl7vueceHn744bImxgA2bNjA29/+dm655RZdE65AFTFzkDGGD37wg9x2223cc889hQuneStXrmTRokXcfffdhWnpdJr777+f888/f9LbBtteLsDy5ctZvXo1q1evZsmSJQCcd955PPDAA6TT6cLr7rrrLhYvXsyKFSsmtX2RmWiuHpPGmMJ6ReaKuXq8bty4seyLtshcMJeO1/vvv58dO3bw7ne/e1L7JTJbzKXjNxwOs3TpUjzP4yc/+Qmve93rcF1dapG5Y6YfryJS9HIdr9/4xjd4+umneeqpp3jqqae44447APjpT3/KP/zDPwC6JlyRkTnnfe97n6mvrzf33XefaWtrKwyJRKKwzD/+4z+a+vp6c9ttt5lNmzaZt771raalpcX09vYWlmlrazMbN240//Iv/2IA88ADD5iNGzeazs5OY4wxjzzyiPnmN79pNm7caHbt2mXuuecec+GFF5rjjjvOJJPJEfevu7vbLFy40Lz1rW81mzZtMrfddpupq6szX/7yl8uW27hxo9m4caM588wzzdve9jazceNGs2XLlin+tESm31w4Jv/pn/7J/OpXvzLPPfecee6558zNN99s6urqzKc+9alp+MREjp65cLx+9atfNb/85S/Nc889ZzZv3mw+8YlPGMD84he/mIZPTOTomQvHa9473vEOc84550zhpyMys82F43f79u3mRz/6kXnuuefMI488Yt7ylreYxsZGs3Pnzqn/wESOopl+vBpjzJYtW8zGjRvN61//evOqV72qcD2plK4xybHg5Tpeh9q5c6cBhh13Qx3r14QVxMxBQMXhBz/4QWEZ3/fNZz7zGbNo0SITjUbNK1/5SrNp06ay9XzmM58ZdT3PPPOMufjii01jY6OJRqNmxYoV5rrrrjN79+494j4+88wz5hWveIWJRqNm0aJF5vrrrze+7x/xfSxfvnyyH4/Iy24uHJPf+MY3zMknn2yqqqpMXV2dOf300823vvUtk8vlpuQzEpkp5sLx+sUvftEcd9xxJhaLmXnz5pkLL7zQ/OY3v5mSz0dkJpkLx6sx9oQ0Ho+bm266adKfichsMReO32effdasX7/exONxU1dXZ66++mqzbdu2Kfl8RGaS2XC8Ll++vOK6j/Q+dI1J5pqX63gdaqxBjDHH9jVhx5igzk9ERERERERERERERESmlBouFRERERERERERERERmSYKYkRERERERERERERERKaJghgREREREREREREREZFpoiBGRERERERERERERERkmiiIERERERERERERERERmSYKYkRERERERERERERERKaJghgREREREREREREREZFpoiBGRERERERERERERERkmiiIERERERERERERERERmSYKYkRERERE5Jhz7bXX4jgOjuMQDodZuHAhl156KTfffDO+7495PT/84Q9paGiYvh0VEREREZFZT0GMiIiIiIgcky6//HLa2trYtWsXd955JxdffDEf/vCHed3rXkc2mz3auyciIiIiInOEghgRERERETkmRaNRFi1axJIlSzjjjDP4u7/7O26//XbuvPNOfvjDHwJw4403csopp1BdXU1rayvvf//76e/vB+C+++7jXe96Fz09PYXqmuuvvx6AdDrNxz/+cZYsWUJ1dTXnnHMO991339F5oyIiIiIiclQpiBEREREREQm8+tWv5rTTTuO2224DwHVdvvGNb7B582ZuueUW7rnnHj7+8Y8DcP755/O1r32Nuro62traaGtr42Mf+xgA73rXu/jDH/7AT37yE5555hne9KY3cfnll/P8888ftfcmIiIiIiJHh2OMMUd7J0RERERERF5O1157Ld3d3fzHf/zHsHn/83/+T5555hmeffbZYfN+/vOf8773vY9Dhw4Bto+Yj3zkI3R3dxeWeeGFF1izZg179+5l8eLFhemXXHIJZ599Nl/4whem/P2IiIiIiMjMFTraOyAiIiIiIjKTGGNwHAeAe++9ly984Qs8++yz9Pb2ks1mSSaTDAwMUF1dXfH1Tz75JMYYjj/++LLpqVSKpqamad9/ERERERGZWRTEiIiIiIiIlNi6dSsrV67kpZde4sorr+S6667j85//PI2NjTz44IO8+93vJpPJjPh63/fxPI8nnngCz/PK5tXU1Ez37ouIiIiIyAyjIEZERERERCRwzz33sGnTJv7qr/6Kxx9/nGw2y1e+8hVc13av+bOf/axs+UgkQi6XK5t2+umnk8vl6Ojo4BWveMXLtu8iIiIiIjIzKYgREREREZFjUiqVor29nVwux4EDB/jtb3/LDTfcwOte9zre+c53smnTJrLZLN/85jd5/etfzx/+8Ae+853vlK1jxYoV9Pf389///d+cdtppVFVVcfzxx/P2t7+dd77znXzlK1/h9NNP59ChQ9xzzz2ccsopXHnllUfpHYuIiIiIyNHgHu0dEBERERERORp++9vf0tLSwooVK7j88su59957+cY3vsHtt9+O53msX7+eG2+8kS9+8YusW7eOW2+9lRtuuKFsHeeffz7XXXcdb3nLW5g/fz5f+tKXAPjBD37AO9/5Tv76r/+aE044gauuuopHHnmE1tbWo/FWRURERETkKHKMMeZo74SIiIiIiIiIiIiIiMhcpIoYERERERERERERERGRaaIgRkREREREREREREREZJooiBEREREREREREREREZkmCmJERERERERERERERESmiYIYERERERERERERERGRaaIgRkREREREREREREREZJooiBEREREREREREREREZkmCmJERERERERERERERESmiYIYERERERERERERERGRaaIgRkREREREREREREREZJooiBEREREREREREREREZkm/z9hKoPYYyzjEAAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2013\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data_ERA5,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    ")\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    ")\n",
+    "\n",
+    "# plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "#     plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d017577d-79da-4a97-9522-81f4c307f3aa",
+   "metadata": {},
+   "source": [
+    "## 6. Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "dcc14e37-5aea-4b00-ae71-32b68ee03d4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_counter_ensemble(ensemble_data, start_date, end_date):\n",
+    "    \n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "    \n",
+    "        year = years[i]\n",
+    "    \n",
+    "        # Define start and end month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "    \n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        # Set zeros to count from\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = []\n",
+    "        modelmean_lowflow_days = 0\n",
+    "\n",
+    "        # Count observed lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "        # Count model mean lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "            modelmean_q = year_data.iloc[j][\"Mean\"]\n",
+    "\n",
+    "            if modelmean_q < q_critical:\n",
+    "                modelmean_lowflow_days += 1\n",
+    "\n",
+    "        # Count modelled lowflow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "        \n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"observed\": observed_lowflow_days,\n",
+    "            \"modelmean\": modelmean_lowflow_days,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)\n",
+    "        })\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    days_sum = lowflow_days[[\"observed\", \"modelmean\", \"set_1\", \"set_2\", \"set_3\", \"set_4\", \"set_5\", \"set_avg\"]].sum()\n",
+    "\n",
+    "    print(days_sum)\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "7460b853-5619-44c9-ac89-3c6fc099bde6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">observed     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">532.0</span>\n",
+       "modelmean    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">538.0</span>\n",
+       "set_1        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">711.0</span>\n",
+       "set_2        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">464.0</span>\n",
+       "set_3        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">546.0</span>\n",
+       "set_4        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">558.0</span>\n",
+       "set_5        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">376.0</span>\n",
+       "set_avg      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">532.0</span>\n",
+       "dtype: float64\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "observed     \u001b[1;36m532.0\u001b[0m\n",
+       "modelmean    \u001b[1;36m538.0\u001b[0m\n",
+       "set_1        \u001b[1;36m711.0\u001b[0m\n",
+       "set_2        \u001b[1;36m464.0\u001b[0m\n",
+       "set_3        \u001b[1;36m546.0\u001b[0m\n",
+       "set_4        \u001b[1;36m558.0\u001b[0m\n",
+       "set_5        \u001b[1;36m376.0\u001b[0m\n",
+       "set_avg      \u001b[1;36m532.0\u001b[0m\n",
+       "dtype: float64\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>observed</th>\n",
+       "      <th>modelmean</th>\n",
+       "      <th>set_1</th>\n",
+       "      <th>set_2</th>\n",
+       "      <th>set_3</th>\n",
+       "      <th>set_4</th>\n",
+       "      <th>set_5</th>\n",
+       "      <th>set_avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1996</td>\n",
+       "      <td>0</td>\n",
+       "      <td>110</td>\n",
+       "      <td>111</td>\n",
+       "      <td>100</td>\n",
+       "      <td>99</td>\n",
+       "      <td>101</td>\n",
+       "      <td>113</td>\n",
+       "      <td>105.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1997</td>\n",
+       "      <td>0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>52</td>\n",
+       "      <td>34</td>\n",
+       "      <td>36</td>\n",
+       "      <td>39</td>\n",
+       "      <td>35</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1998</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1999</td>\n",
+       "      <td>35</td>\n",
+       "      <td>20</td>\n",
+       "      <td>39</td>\n",
+       "      <td>7</td>\n",
+       "      <td>21</td>\n",
+       "      <td>24</td>\n",
+       "      <td>2</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2000</td>\n",
+       "      <td>20</td>\n",
+       "      <td>29</td>\n",
+       "      <td>36</td>\n",
+       "      <td>26</td>\n",
+       "      <td>29</td>\n",
+       "      <td>29</td>\n",
+       "      <td>22</td>\n",
+       "      <td>28.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2001</td>\n",
+       "      <td>60</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2002</td>\n",
+       "      <td>52</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2003</td>\n",
+       "      <td>51</td>\n",
+       "      <td>6</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2004</td>\n",
+       "      <td>5</td>\n",
+       "      <td>23</td>\n",
+       "      <td>41</td>\n",
+       "      <td>17</td>\n",
+       "      <td>27</td>\n",
+       "      <td>31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2005</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2006</td>\n",
+       "      <td>42</td>\n",
+       "      <td>24</td>\n",
+       "      <td>40</td>\n",
+       "      <td>20</td>\n",
+       "      <td>31</td>\n",
+       "      <td>29</td>\n",
+       "      <td>0</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2007</td>\n",
+       "      <td>25</td>\n",
+       "      <td>26</td>\n",
+       "      <td>42</td>\n",
+       "      <td>15</td>\n",
+       "      <td>29</td>\n",
+       "      <td>31</td>\n",
+       "      <td>7</td>\n",
+       "      <td>25.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>37</td>\n",
+       "      <td>21</td>\n",
+       "      <td>38</td>\n",
+       "      <td>18</td>\n",
+       "      <td>23</td>\n",
+       "      <td>23</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2009</td>\n",
+       "      <td>42</td>\n",
+       "      <td>13</td>\n",
+       "      <td>23</td>\n",
+       "      <td>8</td>\n",
+       "      <td>14</td>\n",
+       "      <td>16</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2010</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2011</td>\n",
+       "      <td>36</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2012</td>\n",
+       "      <td>13</td>\n",
+       "      <td>91</td>\n",
+       "      <td>91</td>\n",
+       "      <td>88</td>\n",
+       "      <td>90</td>\n",
+       "      <td>91</td>\n",
+       "      <td>64</td>\n",
+       "      <td>85.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2013</td>\n",
+       "      <td>21</td>\n",
+       "      <td>131</td>\n",
+       "      <td>130</td>\n",
+       "      <td>131</td>\n",
+       "      <td>132</td>\n",
+       "      <td>133</td>\n",
+       "      <td>127</td>\n",
+       "      <td>131.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>43</td>\n",
+       "      <td>0</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    year  observed  modelmean  set_1  set_2  set_3  set_4  set_5  set_avg\n",
+       "0   1996         0        110    111    100     99    101    113    105.0\n",
+       "1   1997         0         38     52     34     36     39     35     39.0\n",
+       "2   1998        44          6     11      0      5      2      0      4.0\n",
+       "3   1999        35         20     39      7     21     24      2     19.0\n",
+       "4   2000        20         29     36     26     29     29     22     28.0\n",
+       "5   2001        60          0      0      0      0      0      0      0.0\n",
+       "6   2002        52          0      8      0      0      0      0      2.0\n",
+       "7   2003        51          6     21      0      7      9      0      7.0\n",
+       "8   2004         5         23     41     17     27     31      0     23.0\n",
+       "9   2005         0          0      0      0      0      0      0      0.0\n",
+       "10  2006        42         24     40     20     31     29      0     24.0\n",
+       "11  2007        25         26     42     15     29     31      7     25.0\n",
+       "12  2008        37         21     38     18     23     23      6     22.0\n",
+       "13  2009        42         13     23      8     14     16      0     12.0\n",
+       "14  2010         6          0      0      0      0      0      0      0.0\n",
+       "15  2011        36          0      7      0      3      0      0      2.0\n",
+       "16  2012        13         91     91     88     90     91     64     85.0\n",
+       "17  2013        21        131    130    131    132    133    127    131.0\n",
+       "18  2014        43          0     21      0      0      0      0      4.0"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# lowflow_ERA5 = lowflow_counter_ensemble(\n",
+    "#     ensemble_data=ensemble_data_ERA5,\n",
+    "#     start_date=evaluation_start,\n",
+    "#     end_date=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "lowflow_CMIP = lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date\n",
+    ")\n",
+    "\n",
+    "# lowflow_counter_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     start_date=evaluation_start,\n",
+    "#     end_date=validation_end_date\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d98001e7-ada9-4415-ae0b-ed7cb8888319",
+   "metadata": {},
+   "source": [
+    "## 7. Cumsum"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 155,
+   "id": "1e9e205d-08bf-4f19-9b12-a0141a4fad99",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def rank(lowflow_ERA5, lowflow_CMIP):\n",
+    "\n",
+    "    # Combine tables\n",
+    "    rank_table = pd.DataFrame({\n",
+    "        \"Observed\": np.sort(lowflow_ERA5[\"observed\"]),\n",
+    "        \"ERA5\": np.sort(lowflow_ERA5[\"set_avg\"]),\n",
+    "        \"CMIP6\": np.sort(lowflow_CMIP[\"set_avg\"])\n",
+    "    })\n",
+    "    \n",
+    "    rank_table.insert(0, \"rank\", range(1, len(rank_table) + 1))\n",
+    "\n",
+    "    return rank_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 156,
+   "id": "02d8a545-838c-4da5-9935-22f34d49f4ee",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>rank</th>\n",
+       "      <th>Observed</th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>13</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>20</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>21</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>12.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>35</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>11</td>\n",
+       "      <td>36</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>22.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12</td>\n",
+       "      <td>37</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>13</td>\n",
+       "      <td>42</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>14</td>\n",
+       "      <td>42</td>\n",
+       "      <td>41.0</td>\n",
+       "      <td>25.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>15</td>\n",
+       "      <td>43</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>28.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>16</td>\n",
+       "      <td>44</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>17</td>\n",
+       "      <td>51</td>\n",
+       "      <td>58.0</td>\n",
+       "      <td>85.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>18</td>\n",
+       "      <td>52</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>105.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>19</td>\n",
+       "      <td>60</td>\n",
+       "      <td>102.0</td>\n",
+       "      <td>131.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    rank  Observed   ERA5  CMIP6\n",
+       "0      1         0    0.0    0.0\n",
+       "1      2         0    0.0    0.0\n",
+       "2      3         0    0.0    0.0\n",
+       "3      4         5    1.0    2.0\n",
+       "4      5         6    2.0    2.0\n",
+       "5      6        13    5.0    4.0\n",
+       "6      7        20   10.0    4.0\n",
+       "7      8        21   17.0    7.0\n",
+       "8      9        25   19.0   12.0\n",
+       "9     10        35   22.0   19.0\n",
+       "10    11        36   32.0   22.0\n",
+       "11    12        37   34.0   23.0\n",
+       "12    13        42   36.0   24.0\n",
+       "13    14        42   41.0   25.0\n",
+       "14    15        43   45.0   28.0\n",
+       "15    16        44   54.0   39.0\n",
+       "16    17        51   58.0   85.0\n",
+       "17    18        52   59.0  105.0\n",
+       "18    19        60  102.0  131.0"
+      ]
+     },
+     "execution_count": 156,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rank_table = rank(lowflow_ERA5, lowflow_CMIP)\n",
+    "\n",
+    "rank_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 160,
+   "id": "f87182f3-7a63-4856-9594-f53b5dd421b8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Observed_cumsum</th>\n",
+       "      <th>ERA5_cumsum</th>\n",
+       "      <th>CMIP6_cumsum</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>5</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>11</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>24</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>8.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>44</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>12.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>65</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>90</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>31.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>125</td>\n",
+       "      <td>76.0</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>161</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>72.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>198</td>\n",
+       "      <td>142.0</td>\n",
+       "      <td>95.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>240</td>\n",
+       "      <td>178.0</td>\n",
+       "      <td>119.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>282</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>144.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>325</td>\n",
+       "      <td>264.0</td>\n",
+       "      <td>172.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>369</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>211.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>420</td>\n",
+       "      <td>376.0</td>\n",
+       "      <td>296.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>472</td>\n",
+       "      <td>435.0</td>\n",
+       "      <td>401.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>532</td>\n",
+       "      <td>537.0</td>\n",
+       "      <td>532.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Observed_cumsum  ERA5_cumsum  CMIP6_cumsum\n",
+       "0                 0          0.0           0.0\n",
+       "1                 0          0.0           0.0\n",
+       "2                 0          0.0           0.0\n",
+       "3                 5          1.0           2.0\n",
+       "4                11          3.0           4.0\n",
+       "5                24          8.0           8.0\n",
+       "6                44         18.0          12.0\n",
+       "7                65         35.0          19.0\n",
+       "8                90         54.0          31.0\n",
+       "9               125         76.0          50.0\n",
+       "10              161        108.0          72.0\n",
+       "11              198        142.0          95.0\n",
+       "12              240        178.0         119.0\n",
+       "13              282        219.0         144.0\n",
+       "14              325        264.0         172.0\n",
+       "15              369        318.0         211.0\n",
+       "16              420        376.0         296.0\n",
+       "17              472        435.0         401.0\n",
+       "18              532        537.0         532.0"
+      ]
+     },
+     "execution_count": 160,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cumsum_table = pd.DataFrame({\n",
+    "    \"Observed_cumsum\": rank_table[\"Observed\"].cumsum(),\n",
+    "     \"ERA5_cumsum\": rank_table[\"ERA5\"].cumsum(),\n",
+    "    \"CMIP6_cumsum\": rank_table[\"CMIP6\"].cumsum()\n",
+    "})\n",
+    "\n",
+    "cumsum_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 153,
+   "id": "78105310-3388-48fa-9471-54003b019753",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_cumsum(rank_table):\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    # Plot cumsum for all columns, skipping rank column\n",
+    "    for i in range(1, len(rank_table.columns)):\n",
+    "        plt.plot(\n",
+    "            rank_table[\"rank\"],\n",
+    "            rank_table[rank_table.columns[i]].cumsum(),\n",
+    "            marker=\"o\",\n",
+    "            label=rank_table.columns[i]\n",
+    "        )\n",
+    "\n",
+    "    # Plotting\n",
+    "    plt.xlabel(\"Ranked years\")\n",
+    "    plt.ylabel(\"Cumulative low flow days\")\n",
+    "    plt.xticks(rank_table[\"rank\"])\n",
+    "    plt.title(\"Cumulative annual low flow days\")\n",
+    "    # plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 154,
+   "id": "b3fa8488-2d3f-4dbd-b82c-e3f8c5bb04d8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_cumsum(rank_table)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b2bf2bc7-1bc9-462a-a4f9-2e04b1f0ed7c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cee6e4aa-f4be-45c7-9d7a-d70782c60ad4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Calibration_HBV.ipynb b/Workyard/Calibration_HBV.ipynb
new file mode 100644
index 00000000..2395973d
--- /dev/null
+++ b/Workyard/Calibration_HBV.ipynb
@@ -0,0 +1,11052 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fbc7f454-3d60-492d-aa6c-0ce21a0dfc77",
+   "metadata": {},
+   "source": [
+    "## Startup\n",
+    "\n",
+    "\n",
+    "80/20 rule:\n",
+    "80% calibration (2000-2020)\n",
+    "20% validation (2020-2025)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "95a06f73-282f-4c7c-8333-f002e73e205a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print\n",
+    "\n",
+    "from ipywidgets import IntProgress\n",
+    "from IPython.display import display"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "8b61a012-64eb-48b2-ba78-f641a1a581a3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a860a623-f634-4b50-822c-51e09ab4e594",
+   "metadata": {},
+   "source": [
+    "### Defining variables & pathways"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "970798cd-b737-44f3-8edd-de3352b86efd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period & basin si\n",
+    "\n",
+    "experiment_start_date = \"2000-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2005-12-31T00:00:00Z\"\n",
+    "\n",
+    "calibration_start = \"1999-01-01T00:00:00Z\"\n",
+    "calibration_end = \"2019-12-31T00:00:00Z\"\n",
+    "\n",
+    "# validation_start = \"\"\n",
+    "# validation_end = \"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "c3b02d32-4be2-47a7-8935-8284af182d66",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "basin_size = 132572\n",
+    "\n",
+    "calibration_temp = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"calibration_temp\"\n",
+    "calibration_temp.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd4ec71b-d4f6-4a1c-be9a-f8d3b89059d1",
+   "metadata": {},
+   "source": [
+    "### Load & prepare discharge data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "d590f365-72ad-4473-9996-88820ea52c18",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "1cec4b74-037a-4d48-8769-e0b57a7683aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "# start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "# end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# q_obs = q_obs[(q_obs[\"Date\"] >= start_date) & (q_obs[\"Date\"] <= end_date)]\n",
+    "# observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7c47f7f-18ff-4441-b1d4-975e46e1719b",
+   "metadata": {},
+   "source": [
+    "### Generate or Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "eb582ebf-8fbc-4542-b785-cee2f332bdd5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1999-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1999-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2019-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load ERA5 data\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6fc290da-fa08-48f0-83e3-a39e8f5c36ef",
+   "metadata": {},
+   "source": [
+    "## Calibration Methods"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9b95e67e-780e-4a4d-a2f1-4cf9de2b0512",
+   "metadata": {},
+   "source": [
+    "### Method 1: RMSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "3da0e944-b4bf-49c6-a986-a94fc14e0bfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def RMSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return np.sqrt(np.mean((obs - sim)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba51d28d-1fdb-46af-8f8e-5dcf904aba7f",
+   "metadata": {},
+   "source": [
+    "### Method 2: NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "9ff8dc21-0959-49a4-9d4b-496726c90f88",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def NSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return 1 - np.sum((obs - sim) ** 2) / np.sum((obs - np.mean(obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "93f96591-ceb4-4671-9a48-04a0ddbfaf5a",
+   "metadata": {},
+   "source": [
+    "### Method 3: Log_NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "826cfb65-21ba-4901-aafe-37738913c0ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def log_NSE(sim, obs):\n",
+    "    # Convert for easy calculations\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8dc2e27c-2caa-493a-8ad0-3a8540ff4a18",
+   "metadata": {},
+   "source": [
+    "### Define Parameters & Storages and Times"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "2ed6540e-ec2f-4f80-975f-66fee4b2a75a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define initial storages\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])\n",
+    "\n",
+    "# Define parameters (range)\n",
+    "parameter_ranges = {\n",
+    "    \"Imax\":  (5.5, 8),            # Maximum interception storage\n",
+    "    \"Ce\":    (0.35, 0.6),       # Evaporation correction factor\n",
+    "    \"Sumax\": (150, 220),         # Maximum soil moisture storage\n",
+    "    \"Beta\":  (1.6, 2),          # Soil runoff parameter\n",
+    "    \"Pmax\":  (0.1, 0.6),            # Maximum percolation rate\n",
+    "    \"Tlag\":  (5.2, 7),           # Time lag\n",
+    "    \"Kf\":    (0.01, 0.1),       # Fast reservoir recession coefficient\n",
+    "    \"Ks\":    (0.001, 0.1),     # Slow reservoir recession coefficient\n",
+    "    \"FM\":    (0.3, 1.4),          # Snowmelt factor\n",
+    "}\n",
+    "\n",
+    "# parameter_ranges = {\n",
+    "#     \"Imax\":  (6.27, 6.28),            # Maximum interception storage\n",
+    "#     \"Ce\":    (0.48, 0.49),       # Evaporation correction factor\n",
+    "#     \"Sumax\": (174, 175),         # Maximum soil moisture storage\n",
+    "#     \"Beta\":  (1.95, 1.96),          # Soil runoff parameter\n",
+    "#     \"Pmax\":  (0.33, 0.34),            # Maximum percolation rate\n",
+    "#     \"Tlag\":  (6.19, 6.2),           # Time lag\n",
+    "#     \"Kf\":    (0.07, 0.08),       # Fast reservoir recession coefficient\n",
+    "#     \"Ks\":    (0.004, 0.0045),     # Slow reservoir recession coefficient\n",
+    "#     \"FM\":    (0.4, 0.41),          # Snowmelt factor\n",
+    "# }\n",
+    "\n",
+    "# Convert to arrays\n",
+    "parameter_names = list(parameter_ranges.keys())\n",
+    "\n",
+    "p_min = np.array([parameter_ranges[name][0] for name in parameter_names])\n",
+    "p_max = np.array([parameter_ranges[name][1] for name in parameter_names])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fc6ef77d-95ba-4277-ab8c-654fa025894d",
+   "metadata": {},
+   "source": [
+    "### Create samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "47df771f-85c1-40a7-9e28-a6dfb3134514",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.80249015e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.65401972e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.78915109e+02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.87292908e+00</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.22401035e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.31882812e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.44797112e-02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.33066933e-02</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8.08732039e-01</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[1;36m6.80249015e+00\u001b[0m \u001b[1;36m5.65401972e-01\u001b[0m \u001b[1;36m1.78915109e+02\u001b[0m \u001b[1;36m1.87292908e+00\u001b[0m\n",
+       " \u001b[1;36m3.22401035e-01\u001b[0m \u001b[1;36m5.31882812e+00\u001b[0m \u001b[1;36m7.44797112e-02\u001b[0m \u001b[1;36m1.33066933e-02\u001b[0m\n",
+       " \u001b[1;36m8.08732039e-01\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Create samples\n",
+    "N = 800\n",
+    "par_samples = np.random.rand(N, len(parameter_ranges))                  # Generates random values between 0-1\n",
+    "parameter_sets = p_min + par_samples * (p_max - p_min)                  # Fits value to parameter range\n",
+    "\n",
+    "print(parameter_sets[:][0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e22418a9-e4ba-4890-85a8-abcfd66c85f2",
+   "metadata": {},
+   "source": [
+    "### Define time period"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "9c72add6-8b9f-4b3e-9e9f-77406215c196",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "calibration_start_date = pd.to_datetime(calibration_start.replace(\"Z\", \"\"))\n",
+    "calibration_end_date = pd.to_datetime(calibration_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for calibration\n",
+    "evaluation_start = pd.to_datetime(f\"{calibration_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= calibration_start_date) & (q_obs[\"Date\"] <= calibration_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "645d5bb0-de70-4b97-9aa0-93094c91ebe6",
+   "metadata": {},
+   "source": [
+    "## Calibration start function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "0f58e61f-7178-44f8-8e5e-e1fa402813c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create function to run the model\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Create model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Create config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=calibration_temp\n",
+    "    )\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs \n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m, \n",
+    "        index=time, \n",
+    "        name=\"Modelled discharge\"\n",
+    "    )\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e93b5d4-0a92-4d09-b135-07101e614d9e",
+   "metadata": {},
+   "source": [
+    "### Run HBV loop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "577e23e5-8db6-45a1-b91b-aae3a46b6c12",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a9d69eee22c54891b96f15b48a0ce521",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "IntProgress(value=0, max=800)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m6\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m7\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m8\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m9\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m10\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m11\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m12\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m13\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m14\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m15\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m16\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m17\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m18\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m19\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m20\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">21</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m21\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m22\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">23</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m23\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m24\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m25\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">26</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m26\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m27\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m28\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">29</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m29\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m30\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m31\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m32\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m33\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m34\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">35</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m35\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m36\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">37</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m37\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">38</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m38\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">39</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m39\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">40</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m40\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m41\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">42</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m42\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">43</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m43\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">44</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m44\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">45</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m45\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">46</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m46\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">47</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m47\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m48\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m49\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">50</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m50\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">51</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m51\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m52\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">53</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m53\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">54</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m54\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">55</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m55\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">56</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m56\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">57</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m57\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">58</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m58\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">59</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m59\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">60</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m60\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">61</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m61\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">62</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m62\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">63</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m63\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m64\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">65</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m65\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">66</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m66\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">67</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m67\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">68</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m68\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">69</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m69\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">70</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m70\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m71\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">72</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m72\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">73</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m73\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m74\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">75</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m75\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">76</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m76\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">77</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m77\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">78</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m78\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">79</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m79\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">80</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m80\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">81</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m81\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">82</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m82\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">83</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m83\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">84</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m84\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">85</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m85\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">86</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m86\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">87</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m87\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">88</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m88\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">89</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m89\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">90</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m90\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m91\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">92</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m92\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">93</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m93\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">94</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m94\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">95</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m95\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">96</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m96\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">97</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m97\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">98</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m98\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">99</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m99\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">100</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m100\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">101</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m101\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">102</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m102\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">103</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m103\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">104</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m104\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">105</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m105\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">106</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m106\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">107</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m107\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">108</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m108\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">109</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m109\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">110</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m110\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">111</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m111\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">112</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m112\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">113</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m113\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">114</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m114\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">115</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m115\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">116</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m116\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">117</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m117\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">118</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m118\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">119</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m119\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">120</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m120\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">121</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m121\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">122</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m122\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">123</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m123\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">124</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m124\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">125</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m125\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">126</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m126\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">127</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m127\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">128</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m128\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">129</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m129\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">130</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m130\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">131</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m131\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">132</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m132\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">133</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m133\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">134</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m134\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">135</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m135\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">136</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m136\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">137</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m137\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">138</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m138\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">139</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m139\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">140</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m140\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">141</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m141\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">142</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m142\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">143</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m143\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">144</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m144\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">145</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m145\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">146</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m146\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">147</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m147\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">148</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m148\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">149</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m149\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">150</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m150\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">151</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m151\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">152</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m152\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">153</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m153\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">154</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m154\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">155</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m155\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">156</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m156\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">157</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m157\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">158</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m158\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">159</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m159\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">160</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m160\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">161</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m161\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">162</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m162\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">163</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m163\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">164</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m164\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">165</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m165\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">166</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m166\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">167</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m167\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">168</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m168\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">169</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m169\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">170</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m170\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">171</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m171\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">172</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m172\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">173</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m173\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m174\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">175</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m175\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">176</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m176\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">177</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m177\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">178</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m178\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m179\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">180</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m180\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">181</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m181\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">182</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m182\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m183\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">184</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m184\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">185</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m185\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">186</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m186\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">187</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m187\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">188</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m188\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">189</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m189\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">190</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m190\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">191</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m191\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">192</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m192\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">193</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m193\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">194</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m194\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">195</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m195\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">196</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m196\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">197</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m197\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">198</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m198\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">199</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m199\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">200</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m200\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">201</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m201\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">202</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m202\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">203</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m203\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">204</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m204\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">205</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m205\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">206</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m206\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">207</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m207\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">208</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m208\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">209</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m209\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">210</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m210\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">211</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m211\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">212</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m212\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">213</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m213\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">214</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m214\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">215</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m215\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">216</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m216\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">217</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m217\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m218\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">219</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m219\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">220</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m220\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">221</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m221\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">222</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m222\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">223</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m223\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">224</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m224\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">225</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m225\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">226</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m226\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">227</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m227\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">228</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m228\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">229</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m229\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">230</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m230\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">231</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m231\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m232\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">233</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m233\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">234</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m234\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">235</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m235\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">236</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m236\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">237</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m237\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">238</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m238\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">239</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m239\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">240</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m240\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">241</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m241\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">242</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m242\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">243</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m243\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">244</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m244\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">245</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m245\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">246</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m246\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">247</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m247\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">248</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m248\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">249</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m249\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">250</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m250\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">251</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m251\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">252</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m252\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">253</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m253\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">254</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m254\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">255</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m255\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">256</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m256\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">257</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m257\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">258</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m258\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">259</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m259\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">260</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m260\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">261</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m261\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">262</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m262\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">263</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m263\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">264</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m264\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">265</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m265\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">266</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m266\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">267</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m267\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">268</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m268\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">276</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m276\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">277</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m277\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">278</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m278\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">279</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m279\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">280</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m280\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">281</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m281\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">282</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m282\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">283</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m283\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">284</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m284\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">285</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m285\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">286</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m286\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">287</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m287\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">288</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m288\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">289</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m289\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">290</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m290\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">291</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m291\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">292</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m292\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">293</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m293\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">294</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m294\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m295\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m296\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m297\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m298\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m299\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m300\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">301</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m301\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">302</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m302\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">303</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m303\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">304</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m304\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">305</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m305\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">306</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m306\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">307</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m307\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">308</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m308\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">309</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m309\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">310</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m310\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">311</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m311\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">312</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m312\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">313</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m313\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">314</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m314\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">315</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m315\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">316</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m316\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">317</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m317\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">318</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m318\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">319</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m319\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">320</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m320\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">321</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m321\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">322</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m322\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">323</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m323\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">324</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m324\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">325</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m325\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">326</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m326\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">327</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m327\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">328</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m328\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">329</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m329\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">330</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m330\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">331</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m331\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">332</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m332\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">333</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m333\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">334</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m334\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">335</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m335\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">336</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m336\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">337</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m337\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">338</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m338\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">339</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m339\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">340</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m340\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">341</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m341\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">342</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m342\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">343</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m343\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">344</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m344\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">345</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m345\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">346</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m346\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">347</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m347\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">348</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m348\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">349</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m349\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">350</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m350\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">351</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m351\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">352</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m352\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">353</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m353\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">354</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m354\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">355</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m355\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">356</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m356\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">357</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m357\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">358</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m358\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">359</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m359\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">360</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m360\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">361</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m361\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">362</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m362\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">363</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m363\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">364</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m364\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">365</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m365\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">366</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m366\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">367</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m367\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">368</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m368\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">369</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m369\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">370</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m370\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">371</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m371\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">372</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m372\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">373</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m373\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">374</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m374\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">375</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m375\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">376</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m376\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">377</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m377\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">378</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m378\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">379</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m379\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">380</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m380\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">381</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m381\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">382</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m382\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">383</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m383\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">384</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m384\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">385</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m385\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">386</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m386\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">387</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m387\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">388</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m388\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">389</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m389\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">390</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m390\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">391</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m391\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">392</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m392\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">393</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m393\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">394</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m394\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">395</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m395\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">396</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m396\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">397</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m397\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">398</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m398\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">399</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m399\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">400</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m400\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">401</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m401\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">402</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m402\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">403</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m403\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">404</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m404\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">405</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m405\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">406</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m406\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">407</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m407\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">408</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m408\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">409</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m409\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">410</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m410\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">411</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m411\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">412</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m412\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">413</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m413\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">414</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m414\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">415</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m415\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">416</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m416\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">417</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m417\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">418</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m418\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">419</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m419\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">420</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m420\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">421</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m421\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">422</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m422\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">423</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m423\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">424</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m424\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">425</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m425\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">426</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m426\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">427</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m427\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">428</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m428\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">429</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m429\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">430</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m430\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">431</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m431\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">432</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m432\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">433</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m433\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">434</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m434\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">435</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m435\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">436</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m436\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">437</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m437\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">438</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m438\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">439</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m439\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">440</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m440\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">441</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m441\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">442</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m442\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">443</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m443\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">444</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m444\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">445</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m445\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">446</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m446\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">447</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m447\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">448</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m448\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">449</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m449\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">450</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m450\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m451\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">452</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m452\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">453</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m453\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">454</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m454\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">455</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m455\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">456</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m456\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">457</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m457\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">458</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m458\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">459</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m459\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">460</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m460\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">461</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m461\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">462</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m462\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">463</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m463\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">464</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m464\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">465</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m465\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">466</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m466\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">467</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m467\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">468</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m468\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">469</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m469\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">470</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m470\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">471</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m471\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">472</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m472\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">473</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m473\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">474</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m474\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">475</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m475\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">476</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m476\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">477</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m477\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">478</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m478\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">479</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m479\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">480</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m480\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">481</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m481\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">482</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m482\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">483</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m483\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">484</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m484\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">485</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m485\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">486</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m486\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">487</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m487\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">488</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m488\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">489</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m489\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">490</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m490\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">491</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m491\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">492</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m492\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">493</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m493\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">494</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m494\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">495</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m495\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">496</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m496\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">497</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m497\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">498</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m498\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">499</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m499\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">500</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m500\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">501</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m501\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">502</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m502\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">503</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m503\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">504</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m504\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">505</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m505\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">506</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m506\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">507</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m507\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">508</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m508\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">509</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m509\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">510</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m510\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">511</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m511\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">512</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m512\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">513</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m513\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">514</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m514\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">515</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m515\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">516</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m516\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">517</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m517\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">518</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m518\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">519</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m519\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">520</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m520\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">521</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m521\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">522</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m522\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">523</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m523\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">524</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m524\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">525</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m525\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">526</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m526\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">527</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m527\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">528</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m528\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">529</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m529\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">530</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m530\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">531</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m531\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">532</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m532\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">533</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m533\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">534</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m534\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">535</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m535\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">536</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m536\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">537</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m537\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">538</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m538\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">539</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m539\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">540</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m540\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">541</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m541\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">542</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m542\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">543</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m543\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">544</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m544\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">545</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m545\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">546</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m546\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">547</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m547\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">548</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m548\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">549</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m549\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">550</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m550\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">551</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m551\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">552</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m552\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">553</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m553\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">554</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m554\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">555</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m555\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">556</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m556\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">557</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m557\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">558</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m558\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">559</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m559\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">560</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m560\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">561</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m561\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">562</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m562\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">563</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m563\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">564</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m564\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">565</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m565\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">566</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m566\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">567</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m567\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">568</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m568\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">569</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m569\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">570</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m570\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">571</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m571\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">572</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m572\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">573</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m573\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">574</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m574\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">575</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m575\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">576</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m576\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">577</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m577\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">578</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m578\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">579</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m579\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">580</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m580\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">581</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m581\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">582</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m582\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">583</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m583\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">584</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m584\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">585</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m585\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">586</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m586\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">587</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m587\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">588</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m588\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">589</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m589\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">590</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m590\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">591</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m591\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">592</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m592\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">593</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m593\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">594</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m594\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m595\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m596\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m597\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m598\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m599\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m600\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">601</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m601\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">602</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m602\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">603</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m603\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">604</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m604\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">605</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m605\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">606</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m606\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">607</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m607\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">608</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m608\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">609</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m609\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">610</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m610\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">611</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m611\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">612</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m612\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">613</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m613\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">614</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m614\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">615</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m615\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">616</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m616\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">617</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m617\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">618</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m618\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">619</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m619\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">620</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m620\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">621</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m621\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">622</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m622\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">623</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m623\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">624</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m624\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">625</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m625\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">626</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m626\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">627</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m627\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">628</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m628\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">629</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m629\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">630</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m630\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">631</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m631\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">632</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m632\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">633</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m633\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">634</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m634\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">635</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m635\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">636</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m636\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">637</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m637\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">638</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m638\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">639</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m639\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">640</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m640\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">641</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m641\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">642</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m642\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">643</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m643\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">644</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m644\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">645</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m645\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">646</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m646\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">647</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m647\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">648</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m648\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">649</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m649\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">650</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m650\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">651</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m651\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">652</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m652\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">653</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m653\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">654</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m654\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">655</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m655\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">656</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m656\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">657</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m657\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">658</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m658\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">659</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m659\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">660</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m660\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">661</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m661\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">662</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m662\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">663</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m663\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">664</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m664\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">665</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m665\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">666</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m666\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">667</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m667\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">668</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m668\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">669</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m669\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">670</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m670\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">671</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m671\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">672</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m672\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">673</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m673\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">674</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m674\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">675</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m675\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">676</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m676\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">677</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m677\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">678</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m678\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">679</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m679\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">680</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m680\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">681</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m681\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">682</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m682\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">683</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m683\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">684</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m684\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">685</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m685\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">686</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m686\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">687</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m687\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">688</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m688\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">689</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m689\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">690</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m690\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">691</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m691\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">692</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m692\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">693</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m693\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">694</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m694\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">695</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m695\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">696</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m696\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">697</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m697\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">698</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m698\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">699</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m699\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">700</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m700\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">701</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m701\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">702</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m702\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">703</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m703\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">704</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m704\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">705</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m705\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">706</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m706\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">707</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m707\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">708</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m708\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">709</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m709\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">710</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m710\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">711</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m711\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">712</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m712\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">713</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m713\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">714</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m714\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">715</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m715\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">716</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m716\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">717</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m717\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">718</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m718\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">719</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m719\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">720</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m720\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">721</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m721\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">722</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m722\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">723</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m723\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">724</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m724\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">725</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m725\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">726</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m726\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "E0521 18:35:50.071878440  529556 backup_poller.cc:113]                 run_poller: UNKNOWN:Timer list shutdown {created_time:\"2026-05-21T18:35:50.071839715+02:00\"}\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">727</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m727\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">728</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m728\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">729</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m729\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">730</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m730\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">731</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m731\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">732</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m732\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">733</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m733\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">734</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m734\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">735</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m735\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">736</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m736\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">737</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m737\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">738</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m738\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">739</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m739\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">740</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m740\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">741</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m741\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">742</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m742\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">743</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m743\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">744</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m744\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">745</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m745\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">746</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m746\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">747</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m747\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">748</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m748\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">749</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m749\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">750</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m750\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">751</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m751\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">752</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m752\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">753</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m753\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">754</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m754\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">755</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m755\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">756</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m756\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">757</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m757\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">758</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m758\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">759</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m759\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">760</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m760\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">761</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m761\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">762</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m762\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">763</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m763\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">764</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m764\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">765</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m765\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">766</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m766\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">767</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m767\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">768</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m768\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">769</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m769\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">770</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m770\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">771</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m771\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">772</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m772\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">773</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m773\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">774</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m774\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">775</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m775\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">776</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m776\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">777</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m777\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">778</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m778\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">779</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m779\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">780</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m780\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">781</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m781\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">782</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m782\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">783</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m783\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">784</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m784\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">785</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m785\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">786</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m786\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">787</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m787\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">788</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m788\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">789</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m789\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">790</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m790\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">791</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m791\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">792</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m792\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">793</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m793\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">794</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m794\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">795</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m795\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">796</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m796\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">797</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">800</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m797\u001b[0m/\u001b[1;36m800\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = []\n",
+    "\n",
+    "# Progress bar for visualization\n",
+    "f = IntProgress(min=0, max=N)\n",
+    "display(f)\n",
+    "\n",
+    "for i in range(N):\n",
+    "    print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "    simulated = run_hbv(\n",
+    "        parameters=parameter_sets[i], \n",
+    "        initial_storages=s_0, \n",
+    "        forcing=ERA5_forcing\n",
+    "    )\n",
+    "\n",
+    "    # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "    simulated_daily = simulated\n",
+    "    observed_daily = observed_output\n",
+    "\n",
+    "    simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "    \n",
+    "    # Align simulated and observed data\n",
+    "    combined_data = pd.DataFrame(\n",
+    "        {\"Modelled discharge\": simulated_daily, \n",
+    "        \"Observed discharge\": observed_daily}\n",
+    "    ).dropna()\n",
+    "\n",
+    "    # Skip first year as warm-up\n",
+    "    combined_data = combined_data[\n",
+    "        (combined_data.index >= evaluation_start) &\n",
+    "        (combined_data.index <= calibration_end_date)\n",
+    "    ]\n",
+    "\n",
+    "    # Exclude ice-affected winter period\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([11, 12, 1, 2, 3, 4])\n",
+    "    ]\n",
+    "\n",
+    "    # Append results and drop nan\n",
+    "    if combined_data.empty:\n",
+    "        print(f\"No overlapping data for parameter set {i+1}\")\n",
+    "        nse = np.nan\n",
+    "        log_nse = np.nan\n",
+    "    else:\n",
+    "        nse = NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "        log_nse = log_NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "        \n",
+    "    results.append({\n",
+    "        \"run\": i,\n",
+    "        \"NSE\": nse,\n",
+    "        \"log_NSE\": log_nse,\n",
+    "        \"parameters\": parameter_sets[i]\n",
+    "    })"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d7b5f35-f872-4ef5-8ced-c92cdd81c8f8",
+   "metadata": {},
+   "source": [
+    "### Display best results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4c69f827-adda-4ec9-8863-abf0ba31e0d2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results = pd.DataFrame(results)\n",
+    "\n",
+    "print(results[[\"run\", \"NSE\", \"log_NSE\"]])\n",
+    "\n",
+    "# Best NSE\n",
+    "best_run_nse = results[\"NSE\"].idxmax()\n",
+    "best_result_nse = results.loc[best_run_nse]\n",
+    "\n",
+    "best_parameters_nse = best_result_nse[\"parameters\"]\n",
+    "best_nse = best_result_nse[\"NSE\"]\n",
+    "\n",
+    "print(f'Best run: {best_run_nse} with NSE: {best_nse}, with parameters:')\n",
+    "print(list(zip(parameter_names, best_parameters_nse)))\n",
+    "\n",
+    "# Best log_NSE\n",
+    "best_run_log_nse = results[\"log_NSE\"].idxmax()\n",
+    "best_result_log_nse = results.loc[best_run_log_nse]\n",
+    "\n",
+    "best_parameters_log_nse = best_result_log_nse[\"parameters\"]\n",
+    "best_log_nse = best_result_log_nse[\"log_NSE\"]\n",
+    "\n",
+    "print(f'Best run: {best_run_log_nse} with log_NSE: {best_log_nse}, with parameters:')\n",
+    "print(list(zip(parameter_names, best_parameters_log_nse)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bb2f1f27-9a79-41fa-b416-e32bbee15075",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get ensemble \n",
+    "\n",
+    "best_5_runs = results[\"log_NSE\"].nlargest(5).index\n",
+    "\n",
+    "best_5_parameters = []\n",
+    "best_5_LNSE = []\n",
+    "\n",
+    "for i in range(len(best_5_runs)):\n",
+    "\n",
+    "    run = best_5_runs[i]\n",
+    "    result = results.loc[run]\n",
+    "\n",
+    "    parameters = result[\"parameters\"]\n",
+    "    lnse = result[\"log_NSE\"]\n",
+    "\n",
+    "    best_5_parameters.append(parameters)\n",
+    "    best_5_LNSE.append(log_nse)\n",
+    "\n",
+    "    print(f\"Rank {i+1}: run {run} with LNSE: {lnse}\")\n",
+    "    print(list(zip(parameter_names, parameters)))\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "127ab139-2d7a-43ad-b012-11188e931c9c",
+   "metadata": {},
+   "source": [
+    "### Plot Observed vs Modelled"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aeb2ea7e-9826-450f-880e-e1e5e72c9dba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Overall Plot\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "simulated_calibrated_nse = run_hbv(\n",
+    "    parameters=best_parameters_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "simulated_calibrated_log_nse = run_hbv(\n",
+    "    parameters=best_parameters_log_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "# Align dates\n",
+    "simulated_plot_nse = simulated_calibrated_nse\n",
+    "simulated_plot_log_nse = simulated_calibrated_log_nse\n",
+    "observed_plot = observed_output\n",
+    "\n",
+    "simulated_plot_nse.index = pd.to_datetime(simulated_plot_nse.index).tz_localize(None).normalize()\n",
+    "simulated_plot_log_nse.index = pd.to_datetime(simulated_plot_log_nse.index).tz_localize(None).normalize()\n",
+    "observed_plot.index = pd.to_datetime(observed_plot.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Combine modelled and observed data\n",
+    "plot_data = pd.DataFrame({\n",
+    "    \"Modelled discharge NSE\": simulated_plot_nse,\n",
+    "    \"Modelled discharge log_NSE\": simulated_plot_log_nse,\n",
+    "    \"Observed discharge\": observed_plot\n",
+    "}).dropna()\n",
+    "\n",
+    "# Calculate NSE & log NSE for plotted data\n",
+    "plot_nse = NSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "plot_log_nse = log_NSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\")\n",
+    "# plt.plot(plot_data.index, plot_data[\"Modelled discharge NSE\"], label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data.index, plot_data[\"Modelled discharge log_NSE\"], label=\"Modelled discharge log_NSE\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001, NSE = {best_nse:.3f}, log NSE = {best_log_nse:.3f}\")\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f'Critical discharge ({q_critical} m³/s', color='black')\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e0743eb6-3efd-435c-866f-d0ea2bddfea8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Plot for 1 year\n",
+    "\n",
+    "selected_year = 2015\n",
+    "\n",
+    "plot_data_year = plot_data[plot_data.index.year == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Observed discharge\"],label=\"Observed discharge\")\n",
+    "# plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge NSE\"],label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge log_NSE\"],label=\"Modelled discharge log_NSE\", color=\"green\")\n",
+    "\n",
+    "plt.axhline(y=q_critical,linestyle=\":\",color=\"black\",label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001 in {selected_year}\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dde634ea-53bd-4c41-ba13-8ec762014b89",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate RMSE for best parameter sets NSE and log_NSE\n",
+    "\n",
+    "rmse_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "rmse_log_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "print(f\"RMSE for best NSE parameter set: {rmse_nse:.3f} m³/s\")\n",
+    "print(f\"RMSE for best log_NSE parameter set: {rmse_log_nse:.3f} m³/s\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "db083f00-6ca7-47a1-8792-c46df17f15ed",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/ERA5_Forcings_Generation.ipynb b/Workyard/ERA5_Forcings_Generation.ipynb
new file mode 100644
index 00000000..d7977e49
--- /dev/null
+++ b/Workyard/ERA5_Forcings_Generation.ipynb
@@ -0,0 +1,580 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e91181a8-c60f-456f-80cc-3923bf7c6a43",
+   "metadata": {},
+   "source": [
+    "# ERA5 Data generation & merging \n",
+    "\n",
+    "ERA5 data will be generated from 1970-2025, loaded and merged into one file"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "680410be-715a-4678-a4e3-c1141939241e",
+   "metadata": {},
+   "source": [
+    "## Start-up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "7ef3318e-968e-418e-bf4c-a8936aade9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# general python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "#niceties\n",
+    "from rich import print\n",
+    "\n",
+    "import yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "f7ff029b-ee4b-4fe2-b5d5-bf768b626989",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74c8c15e-8cab-4e1a-b6eb-c9c165d8c051",
+   "metadata": {},
+   "source": [
+    "### Define range & forcing paths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "b2343410-2713-4089-ae42-dad37b457c41",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ERA5-2019-2021</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/\u001b[0m\u001b[95mERA5-2019-2021\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2022</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2022\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2024</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2024\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining period range\n",
+    "# periods = [\n",
+    "#     [1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020],\n",
+    "#     [1974, 1979, 1984, 1989, 1994, 1999, 2004, 2009, 2014, 2019, 2024]\n",
+    "# ]\n",
+    "\n",
+    "# For calibration 1:\n",
+    "# periods = [\n",
+    "#     [1990, 1995, 2000, 2005, 2010],\n",
+    "#     [1994, 1999, 2004, 2009, 2017]\n",
+    "# ]\n",
+    "\n",
+    "# For calibration 2:\n",
+    "# periods = [\n",
+    "#     [1999, 2005, 2010, 2018],\n",
+    "#     [2004, 2009, 2017, 2019]\n",
+    "# ]\n",
+    "\n",
+    "# For validation 1:\n",
+    "# periods = [\n",
+    "#     [2018, 2022],\n",
+    "#     [2021, 2024]\n",
+    "# ]\n",
+    "\n",
+    "# For validation 2:\n",
+    "periods = [\n",
+    "    [2019, 2022],\n",
+    "    [2021, 2024]\n",
+    "]\n",
+    "\n",
+    "folder_names = []\n",
+    "forcing_paths = {}\n",
+    "\n",
+    "# Generate file names & paths\n",
+    "for i in range(len(periods[0])):\n",
+    "    start_year = periods[0][i]\n",
+    "    end_year = periods[1][i]\n",
+    "    \n",
+    "    folder_name = f'ERA5-{start_year}-{end_year}'                         # Add -cal or -val for cal and val folder name\n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / folder_name\n",
+    "\n",
+    "    folder_names.append(folder_name)\n",
+    "    forcing_paths[folder_name] = forcing_path\n",
+    "\n",
+    "    forcing_path.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "# Call path test\n",
+    "print(forcing_paths[folder_names[0]])\n",
+    "\n",
+    "print(periods[0][1])\n",
+    "\n",
+    "print(periods[1][-1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "619dd21a-0646-4bae-a71b-935f1fca8c04",
+   "metadata": {},
+   "source": [
+    "### Generate ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "cbc7b2b6-88ee-4e7f-b37c-39eaf878c075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2019</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2021</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished ERA5-\u001b[1;36m2019\u001b[0m-\u001b[1;36m2021\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2022</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2024</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m2022\u001b[0m-\u001b[1;36m2024\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Shapefile path\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# Generate forcing data\n",
+    "# for i in range(1):\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Change start year to start time so ERA5 can interpret it\n",
+    "    start_time_ERA5 = f'{periods[0][i]}-01-01T00:00:00Z'\n",
+    "    end_time_ERA5 = f'{periods[1][i]}-12-31T00:00:00Z'\n",
+    "\n",
+    "    # Skip if folder is not empty to prevent errors\n",
+    "    if any(forcing_paths[folder_names[i]].iterdir()):\n",
+    "        print(f\"Skipping {folder_names[i]} because the folder is not empty.\")\n",
+    "        continue\n",
+    "\n",
+    "    # Load forcings\n",
+    "    ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "        dataset=\"ERA5\",\n",
+    "        start_time=start_time_ERA5,\n",
+    "        end_time=end_time_ERA5,\n",
+    "        shape=shape_file,\n",
+    "        directory=forcing_paths[folder_names[i]]\n",
+    "    )\n",
+    "\n",
+    "    # I need info because my patience is limited\n",
+    "    print(f\"Finished {folder_names[i]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91242ae4-3d21-4d18-815f-5cc986d5961e",
+   "metadata": {},
+   "source": [
+    "### Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "f8e8ac64-fee5-4602-a1f1-90b8fb14c2b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-2019-2021'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-2022-2024'</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[32m'ERA5-2019-2021'\u001b[0m, \u001b[32m'ERA5-2022-2024'\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "LumpedMakkinkForcing(start_time='2019-01-01T00:00:00Z', end_time='2021-12-31T00:00:00Z', directory=PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script'), shape=PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script/07DA001_basin.shp'), filenames={'pr': 'OBS6_ERA5_reanaly_1_day_pr_2019-2021.nc', 'tas': 'OBS6_ERA5_reanaly_1_day_tas_2019-2021.nc', 'rsds': 'OBS6_ERA5_reanaly_1_day_rsds_2019-2021.nc', 'evspsblpot': 'Derived_Makkink_evspsblpot.nc'})"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ERA5_forcings = {}\n",
+    "\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Create new path to find relevant files in the folder\n",
+    "    directory_new = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\"\n",
+    "\n",
+    "    # Load forcings\n",
+    "    ERA5_forcings[folder_names[i]] = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=directory_new)\n",
+    "\n",
+    "# Test to see if it works\n",
+    "print(folder_names)\n",
+    "ERA5_forcings[folder_names[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8eddb25-06e3-4702-87e8-258aeda27a15",
+   "metadata": {},
+   "source": [
+    "### Merge ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "1cb12aa2-4b4c-4108-a5c9-2d8156cdecfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to seperate files based on file names and combine same file names from different folders\n",
+    "def combine_variable(var_name):\n",
+    "    datasets = []\n",
+    "\n",
+    "    for i in range(len(folder_names)):\n",
+    "\n",
+    "        if var_name == \"evspsblpot\":\n",
+    "            file_name = \"Derived_Makkink_evspsblpot.nc\"\n",
+    "        else:\n",
+    "            file_name = f\"OBS6_ERA5_reanaly_1_day_{var_name}_{periods[0][i]}-{periods[1][i]}.nc\"\n",
+    "\n",
+    "        directory = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\" / file_name\n",
+    "\n",
+    "        print(f\"Loading {directory}\")\n",
+    "\n",
+    "        datasets.append(xr.open_dataset(directory))\n",
+    "\n",
+    "    combined = xr.concat(datasets, dim=\"time\")\n",
+    "    return combined"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "b21fe2e4-478a-4e0b-9f1f-a40316e22018",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_2019-202</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">1.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_2019-202\u001b[0m\n",
+       "\u001b[95m1.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2022-2024/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_2022-202</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">4.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2022-2024/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_2022-202\u001b[0m\n",
+       "\u001b[95m4.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_2019-20</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">21.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_2019-20\u001b[0m\n",
+       "\u001b[95m21.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2022-2024/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_2022-20</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">24.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2022-2024/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_2022-20\u001b[0m\n",
+       "\u001b[95m24.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_2019-2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">021.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_2019-2\u001b[0m\n",
+       "\u001b[95m021.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2022-2024/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_2022-2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">024.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2022-2024/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_2022-2\u001b[0m\n",
+       "\u001b[95m024.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2021/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2022-2024/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2022-2024/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Running function for various file name types\n",
+    "combined_variables = {}\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "combined_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / f'ERA5-{periods[0][0]}-{periods[1][-1]}'\n",
+    "combined_path.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "    combined_variables[var_names[i]] = combine_variable(var_names[i])\n",
+    "    combined_variables[var_names[i]].to_netcdf(combined_path / f'combined_ERA5_{periods[0][0]}_{periods[1][-1]}_{var_names[i]}.nc')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a439e818-0aa8-4e92-a189-fde70016a911",
+   "metadata": {},
+   "source": [
+    "### Create YAML file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "e60b3316-e100-4af9-a36d-fad721ef6e02",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create yaml\n",
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{periods[0][0]}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{periods[1][-1]}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_ERA5_{periods[0][0]}_{periods[1][-1]}_pr.nc\",\n",
+    "        \"tas\": f\"combined_ERA5_{periods[0][0]}_{periods[1][-1]}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_ERA5_{periods[0][0]}_{periods[1][-1]}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_ERA5_{periods[0][0]}_{periods[1][-1]}_evspsblpot.nc\"\n",
+    "    }}\n",
+    "\n",
+    "# Save the YAML file\n",
+    "yaml_file_path = combined_path / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "10ff50bf-b6e7-4033-9682-3e25d01ecd26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2024-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2024'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'2019-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2024-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2024'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ERA5_combined_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=combined_path)\n",
+    "print(ERA5_combined_forcing)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Shapefiles/07DA001_basin.cpg b/Workyard/Shapefiles/07DA001_basin.cpg
new file mode 100644
index 00000000..3ad133c0
--- /dev/null
+++ b/Workyard/Shapefiles/07DA001_basin.cpg
@@ -0,0 +1 @@
+UTF-8
\ No newline at end of file
diff --git a/Workyard/Shapefiles/07DA001_basin.dbf b/Workyard/Shapefiles/07DA001_basin.dbf
new file mode 100644
index 00000000..b554ebf7
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diff --git a/Workyard/Shapefiles/07DA001_basin.prj b/Workyard/Shapefiles/07DA001_basin.prj
new file mode 100644
index 00000000..f45cbadf
--- /dev/null
+++ b/Workyard/Shapefiles/07DA001_basin.prj
@@ -0,0 +1 @@
+GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]
\ No newline at end of file
diff --git a/Workyard/Shapefiles/07DA001_basin.qmd b/Workyard/Shapefiles/07DA001_basin.qmd
new file mode 100644
index 00000000..74011b2e
--- /dev/null
+++ b/Workyard/Shapefiles/07DA001_basin.qmd
@@ -0,0 +1,27 @@
+<!DOCTYPE qgis PUBLIC 'http://mrcc.com/qgis.dtd' 'SYSTEM'>
+<qgis version="4.0.1-Norrköping">
+  <identifier>MDA_ADP_07_DrainageBasin_BassinDeDrainage</identifier>
+  <parentidentifier></parentidentifier>
+  <language>ENG</language>
+  <type>dataset</type>
+  <title>MDA_ADP_07_DrainageBasin_BassinDeDrainage</title>
+  <abstract></abstract>
+  <links/>
+  <dates/>
+  <fees></fees>
+  <encoding></encoding>
+  <crs>
+    <spatialrefsys nativeFormat="Wkt">
+      <wkt>PROJCRS["Canada_Albers_Equal_Area_Conic",BASEGEOGCRS["NAD83",DATUM["North American Datum 1983",ELLIPSOID["GRS 1980",6378137,298.257222101,LENGTHUNIT["metre",1]]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433]],ID["EPSG",4269]],CONVERSION["Canada_Albers_Equal_Area_Conic",METHOD["Albers Equal Area",ID["EPSG",9822]],PARAMETER["Latitude of false origin",40,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8821]],PARAMETER["Longitude of false origin",-96,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8822]],PARAMETER["Latitude of 1st standard parallel",50,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8823]],PARAMETER["Latitude of 2nd standard parallel",70,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8824]],PARAMETER["Easting at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8826]],PARAMETER["Northing at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8827]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1]],USAGE[SCOPE["Not known."],AREA["Canada - onshore and offshore - Alberta; British Columbia; Manitoba; New Brunswick; Newfoundland and Labrador; Northwest Territories; Nova Scotia; Nunavut; Ontario; Prince Edward Island; Quebec; Saskatchewan; Yukon."],BBOX[38.21,-141.01,86.46,-40.73]],ID["ESRI",102001]]</wkt>
+      <proj4>+proj=aea +lat_0=40 +lon_0=-96 +lat_1=50 +lat_2=70 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs</proj4>
+      <srsid>27124</srsid>
+      <srid>102001</srid>
+      <authid>ESRI:102001</authid>
+      <description>Canada_Albers_Equal_Area_Conic</description>
+      <projectionacronym>aea</projectionacronym>
+      <ellipsoidacronym>EPSG:7019</ellipsoidacronym>
+      <geographicflag>false</geographicflag>
+    </spatialrefsys>
+  </crs>
+  <extent/>
+</qgis>
diff --git a/Workyard/Shapefiles/07DA001_basin.shp b/Workyard/Shapefiles/07DA001_basin.shp
new file mode 100644
index 00000000..7f647ec7
Binary files /dev/null and b/Workyard/Shapefiles/07DA001_basin.shp differ
diff --git a/Workyard/Shapefiles/07DA001_basin.shx b/Workyard/Shapefiles/07DA001_basin.shx
new file mode 100644
index 00000000..bf59e75f
Binary files /dev/null and b/Workyard/Shapefiles/07DA001_basin.shx differ
diff --git a/Workyard/Step1_CMIP6_Forcings_Generation.ipynb b/Workyard/Step1_CMIP6_Forcings_Generation.ipynb
new file mode 100644
index 00000000..13e8b7b1
--- /dev/null
+++ b/Workyard/Step1_CMIP6_Forcings_Generation.ipynb
@@ -0,0 +1,703 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e91181a8-c60f-456f-80cc-3923bf7c6a43",
+   "metadata": {},
+   "source": [
+    "# CMIP6 Data generation & merging \n",
+    "\n",
+    "CMIP6 data will be generated from 1995-2014, loaded and merged into one file\n",
+    "\n",
+    "**Note: Depending on if you want to run historical, or an ssp, changes you need to make are:**\n",
+    "1. Cell 5: Select scenario\n",
+    "2. Cell 6: Define period"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "680410be-715a-4678-a4e3-c1141939241e",
+   "metadata": {},
+   "source": [
+    "## Start-up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "7ef3318e-968e-418e-bf4c-a8936aade9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# general python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "#niceties\n",
+    "from rich import print\n",
+    "\n",
+    "import yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "f7ff029b-ee4b-4fe2-b5d5-bf768b626989",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "df3c38b4-7757-475c-a670-e7a06cc53955",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choose what you want to run:\n",
+    "Scenario = \"ssp126\"    # Options: historical, ssp119, ssp126, ssp245, ssp,370, ssp585"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74c8c15e-8cab-4e1a-b6eb-c9c165d8c051",
+   "metadata": {},
+   "source": [
+    "### Define range & forcing paths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b2343410-2713-4089-ae42-dad37b457c41",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6-2025-2030</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/\u001b[0m\u001b[95mCMIP6-2025-2030\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2025\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining period range\n",
+    "\n",
+    "# For CMIP trial:\n",
+    "# periods = [\n",
+    "#     [1995, 2000, 2005, 2010],\n",
+    "#     [1999, 2004, 2009, 2014]\n",
+    "# ]\n",
+    "\n",
+    "# periods = [\n",
+    "#     [1970, 1975, 1980, 1985, 1990, 1995],\n",
+    "#     [1974, 1979, 1984, 1989, 1994, 1999]\n",
+    "# ]\n",
+    "\n",
+    "# Future projections 2026-2050:\n",
+    "periods = [\n",
+    "    [2025, 2031, 2041],\n",
+    "    [2030, 2040, 2050]\n",
+    "]\n",
+    "\n",
+    "# Future projections 2051-2075:\n",
+    "# periods = [\n",
+    "#     [2050, 2061, 2071],\n",
+    "#     [2060, 2070, 2075]\n",
+    "# ]\n",
+    "\n",
+    "# Future projections 2076-2100:\n",
+    "# periods = [\n",
+    "#     [2075, 2081, 2091],\n",
+    "#     [2080, 2090, 2100]\n",
+    "# ]\n",
+    "\n",
+    "\n",
+    "folder_names = []\n",
+    "forcing_paths = {}\n",
+    "\n",
+    "# Generate file names & paths\n",
+    "for i in range(len(periods[0])):\n",
+    "    start_year = periods[0][i]\n",
+    "    end_year = periods[1][i]\n",
+    "    \n",
+    "    folder_name = f'CMIP6-{start_year}-{end_year}'                        \n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / folder_name\n",
+    "\n",
+    "    folder_names.append(folder_name)\n",
+    "    forcing_paths[folder_name] = forcing_path\n",
+    "\n",
+    "    forcing_path.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "# Call path test\n",
+    "print(forcing_paths[folder_names[0]])\n",
+    "\n",
+    "start_year = periods[0][0]\n",
+    "end_year = periods[1][-1]\n",
+    "\n",
+    "print(start_year)\n",
+    "\n",
+    "print(end_year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "619dd21a-0646-4bae-a71b-935f1fca8c04",
+   "metadata": {},
+   "source": [
+    "### Generate CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "cbc7b2b6-88ee-4e7f-b37c-39eaf878c075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2030</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2025\u001b[0m-\u001b[1;36m2030\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2031</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2040</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2031\u001b[0m-\u001b[1;36m2040\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2041</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2041\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Shapefile path\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\"\n",
+    "\n",
+    "# Choose CMIP6 dataset\n",
+    "CMIP_dataset = {'dataset': 'MPI-ESM1-2-HR', 'project': 'CMIP6', 'grid' : 'gn', 'exp': Scenario, 'ensemble': 'r1i1p1f1'}\n",
+    "\n",
+    "\n",
+    "# Generate forcing data\n",
+    "# for i in range(1):\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Change start year to start time so ERA5 can interpret it\n",
+    "    start_time_CMIP = f'{periods[0][i]}-01-01T00:00:00Z'\n",
+    "    end_time_CMIP = f'{periods[1][i]}-12-31T00:00:00Z'\n",
+    "\n",
+    "    # Skip if folder is not empty to prevent errors\n",
+    "    if any(forcing_paths[folder_names[i]].iterdir()):\n",
+    "        print(f\"Skipping {folder_names[i]} because the folder is not empty.\")\n",
+    "        continue\n",
+    "\n",
+    "    # Load forcings\n",
+    "    CMIP_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "        dataset=CMIP_dataset,\n",
+    "        start_time=start_time_CMIP,\n",
+    "        end_time=end_time_CMIP,\n",
+    "        shape=shape_file,\n",
+    "        directory=forcing_paths[folder_names[i]]\n",
+    "    )\n",
+    "\n",
+    "    # I need info because my patience is limited\n",
+    "    print(f\"Finished {folder_names[i]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91242ae4-3d21-4d18-815f-5cc986d5961e",
+   "metadata": {},
+   "source": [
+    "### Load CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "f8e8ac64-fee5-4602-a1f1-90b8fb14c2b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2025-2030'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2031-2040'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2041-2050'</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[32m'CMIP6-2025-2030'\u001b[0m, \u001b[32m'CMIP6-2031-2040'\u001b[0m, \u001b[32m'CMIP6-2041-2050'\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "LumpedMakkinkForcing(start_time='2025-01-01T00:00:00Z', end_time='2030-12-31T00:00:00Z', directory=PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script'), shape=PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script/07DA001_basin.shp'), filenames={'pr': 'CMIP6_MPI-ESM1-2-HR_day_ssp126_r1i1p1f1_pr_gn_2025-2030.nc', 'tas': 'CMIP6_MPI-ESM1-2-HR_day_ssp126_r1i1p1f1_tas_gn_2025-2030.nc', 'rsds': 'CMIP6_MPI-ESM1-2-HR_day_ssp126_r1i1p1f1_rsds_gn_2025-2030.nc', 'evspsblpot': 'Derived_Makkink_evspsblpot.nc'})"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "CMIP_forcings = {}\n",
+    "\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Create new path to find relevant files in the folder\n",
+    "    directory_new = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\"\n",
+    "    \n",
+    "    # Load forcings\n",
+    "    CMIP_forcings[folder_names[i]] = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=directory_new)\n",
+    "\n",
+    "# Test to see if it works\n",
+    "print(folder_names)\n",
+    "CMIP_forcings[folder_names[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8eddb25-06e3-4702-87e8-258aeda27a15",
+   "metadata": {},
+   "source": [
+    "### Merge CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "1cb12aa2-4b4c-4108-a5c9-2d8156cdecfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to seperate files based on file names and combine same file names from different folders\n",
+    "def combine_variable(var_name):\n",
+    "    datasets = []\n",
+    "\n",
+    "    for i in range(len(folder_names)):\n",
+    "\n",
+    "        if var_name == \"evspsblpot\":\n",
+    "            file_name = \"Derived_Makkink_evspsblpot.nc\"\n",
+    "        else:\n",
+    "            file_name = f\"CMIP6_MPI-ESM1-2-HR_day_{Scenario}_r1i1p1f1_{var_name}_gn_{periods[0][i]}-{periods[1][i]}.nc\"\n",
+    "\n",
+    "        directory = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\" / file_name\n",
+    "\n",
+    "        print(f\"Loading {directory}\")\n",
+    "\n",
+    "        datasets.append(xr.open_dataset(directory))\n",
+    "\n",
+    "    combined = xr.concat(datasets, dim=\"time\")\n",
+    "    return combined"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "b21fe2e4-478a-4e0b-9f1f-a40316e22018",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_d</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ay_ssp126_r1i1p1f1_pr_gn_2025-2030.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_d\u001b[0m\n",
+       "\u001b[95may_ssp126_r1i1p1f1_pr_gn_2025-2030.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2031-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_d</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ay_ssp126_r1i1p1f1_pr_gn_2031-2040.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2031-2040/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_d\u001b[0m\n",
+       "\u001b[95may_ssp126_r1i1p1f1_pr_gn_2031-2040.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2041-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_d</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ay_ssp126_r1i1p1f1_pr_gn_2041-2050.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2041-2050/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_d\u001b[0m\n",
+       "\u001b[95may_ssp126_r1i1p1f1_pr_gn_2041-2050.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_d</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ay_ssp126_r1i1p1f1_tas_gn_2025-2030.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_d\u001b[0m\n",
+       "\u001b[95may_ssp126_r1i1p1f1_tas_gn_2025-2030.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2031-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_d</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ay_ssp126_r1i1p1f1_tas_gn_2031-2040.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2031-2040/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_d\u001b[0m\n",
+       "\u001b[95may_ssp126_r1i1p1f1_tas_gn_2031-2040.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2041-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_d</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ay_ssp126_r1i1p1f1_tas_gn_2041-2050.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2041-2050/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_d\u001b[0m\n",
+       "\u001b[95may_ssp126_r1i1p1f1_tas_gn_2041-2050.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_d</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ay_ssp126_r1i1p1f1_rsds_gn_2025-2030.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_d\u001b[0m\n",
+       "\u001b[95may_ssp126_r1i1p1f1_rsds_gn_2025-2030.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2031-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_d</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ay_ssp126_r1i1p1f1_rsds_gn_2031-2040.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2031-2040/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_d\u001b[0m\n",
+       "\u001b[95may_ssp126_r1i1p1f1_rsds_gn_2031-2040.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2041-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_d</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ay_ssp126_r1i1p1f1_rsds_gn_2041-2050.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2041-2050/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_d\u001b[0m\n",
+       "\u001b[95may_ssp126_r1i1p1f1_rsds_gn_2041-2050.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evsps</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">blpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2030/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evsps\u001b[0m\n",
+       "\u001b[95mblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2031-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evsps</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">blpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2031-2040/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evsps\u001b[0m\n",
+       "\u001b[95mblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2041-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evsps</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">blpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2041-2050/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evsps\u001b[0m\n",
+       "\u001b[95mblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Running function for various file name types\n",
+    "combined_variables = {}\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "combined_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f'CMIP6-{start_year}-{end_year}'\n",
+    "# combined_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / f'ERA5-{periods[0][0]}-{periods[1][-1]}'\n",
+    "combined_path.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "    combined_variables[var_names[i]] = combine_variable(var_names[i])\n",
+    "    combined_variables[var_names[i]].to_netcdf(combined_path / f'combined_CMIP6_{start_year}_{end_year}_{var_names[i]}.nc')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a439e818-0aa8-4e92-a189-fde70016a911",
+   "metadata": {},
+   "source": [
+    "### Create YAML file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "e60b3316-e100-4af9-a36d-fad721ef6e02",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create yaml\n",
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{start_year}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{end_year}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_CMIP6_{start_year}_{end_year}_pr.nc\",\n",
+    "        \"tas\": f\"combined_CMIP6_{start_year}_{end_year}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_CMIP6_{start_year}_{end_year}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_CMIP6_{start_year}_{end_year}_evspsblpot.nc\"\n",
+    "    }}\n",
+    "\n",
+    "# Save the YAML file\n",
+    "yaml_file_path = combined_path / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "10ff50bf-b6e7-4033-9682-3e25d01ecd26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2025-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2050-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2050'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'2025-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2050-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2050'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "CMIP6_combined_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=combined_path)\n",
+    "print(CMIP6_combined_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "83a89024-510b-442f-adeb-8f9e0d07a77f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Step1_ERA5_Forcings_Generation.ipynb b/Workyard/Step1_ERA5_Forcings_Generation.ipynb
new file mode 100644
index 00000000..a8a282f8
--- /dev/null
+++ b/Workyard/Step1_ERA5_Forcings_Generation.ipynb
@@ -0,0 +1,911 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e91181a8-c60f-456f-80cc-3923bf7c6a43",
+   "metadata": {},
+   "source": [
+    "# ERA5 Data generation & merging \n",
+    "\n",
+    "ERA5 data will be generated from 1970-2025, loaded and merged into one file"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "680410be-715a-4678-a4e3-c1141939241e",
+   "metadata": {},
+   "source": [
+    "## Start-up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "7ef3318e-968e-418e-bf4c-a8936aade9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# general python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "#niceties\n",
+    "from rich import print\n",
+    "\n",
+    "import yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "f7ff029b-ee4b-4fe2-b5d5-bf768b626989",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74c8c15e-8cab-4e1a-b6eb-c9c165d8c051",
+   "metadata": {},
+   "source": [
+    "### Define range & forcing paths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b2343410-2713-4089-ae42-dad37b457c41",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ERA5-1970-1974</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/\u001b[0m\u001b[95mERA5-1970-1974\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1975</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m1975\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1999</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m1999\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining period range\n",
+    "# periods = [\n",
+    "#     [1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020],\n",
+    "#     [1974, 1979, 1984, 1989, 1994, 1999, 2004, 2009, 2014, 2019, 2024]\n",
+    "# ]\n",
+    "\n",
+    "# For calibration 1:\n",
+    "# periods = [\n",
+    "#     [1990, 1995, 2000, 2005, 2010],\n",
+    "#     [1994, 1999, 2004, 2009, 2017]\n",
+    "# ]\n",
+    "\n",
+    "# For calibration 2:\n",
+    "# periods = [\n",
+    "#     [1999, 2005, 2010, 2018],\n",
+    "#     [2004, 2009, 2017, 2019]\n",
+    "# ]\n",
+    "\n",
+    "# For validation 1:\n",
+    "# periods = [\n",
+    "#     [2018, 2022],\n",
+    "#     [2021, 2024]\n",
+    "# ]\n",
+    "\n",
+    "# For validation 2:\n",
+    "# periods = [\n",
+    "#     [2019, 2022],\n",
+    "#     [2021, 2024]\n",
+    "# ]\n",
+    "\n",
+    "# For CMIP trial:\n",
+    "# periods = [\n",
+    "#     [1995, 2000, 2005, 2010],\n",
+    "#     [1999, 2004, 2009, 2014]\n",
+    "# ]\n",
+    "\n",
+    "# For CMIP trial 2\n",
+    "periods = [\n",
+    "    [1970, 1975, 1980, 1985, 1990, 1995],\n",
+    "    [1974, 1979, 1984, 1989, 1994, 1999]\n",
+    "]\n",
+    "\n",
+    "folder_names = []\n",
+    "forcing_paths = {}\n",
+    "\n",
+    "# Generate file names & paths\n",
+    "for i in range(len(periods[0])):\n",
+    "    start_year = periods[0][i]\n",
+    "    end_year = periods[1][i]\n",
+    "    \n",
+    "    folder_name = f'ERA5-{start_year}-{end_year}'                         # Add -cal or -val for cal and val folder name\n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / folder_name\n",
+    "\n",
+    "    folder_names.append(folder_name)\n",
+    "    forcing_paths[folder_name] = forcing_path\n",
+    "\n",
+    "    forcing_path.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "# Call path test\n",
+    "print(forcing_paths[folder_names[0]])\n",
+    "\n",
+    "print(periods[0][1])\n",
+    "\n",
+    "print(periods[1][-1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "619dd21a-0646-4bae-a71b-935f1fca8c04",
+   "metadata": {},
+   "source": [
+    "### Generate ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "cbc7b2b6-88ee-4e7f-b37c-39eaf878c075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1970</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1974</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m1970\u001b[0m-\u001b[1;36m1974\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1975</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1979</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m1975\u001b[0m-\u001b[1;36m1979\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1980</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1984</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m1980\u001b[0m-\u001b[1;36m1984\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1985</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1989</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m1985\u001b[0m-\u001b[1;36m1989\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1990</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1994</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m1990\u001b[0m-\u001b[1;36m1994\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1995</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1999</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m1995\u001b[0m-\u001b[1;36m1999\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Shapefile path\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\"\n",
+    "\n",
+    "# Generate forcing data\n",
+    "# for i in range(1):\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Change start year to start time so ERA5 can interpret it\n",
+    "    start_time_ERA5 = f'{periods[0][i]}-01-01T00:00:00Z'\n",
+    "    end_time_ERA5 = f'{periods[1][i]}-12-31T00:00:00Z'\n",
+    "\n",
+    "    # Skip if folder is not empty to prevent errors\n",
+    "    if any(forcing_paths[folder_names[i]].iterdir()):\n",
+    "        print(f\"Skipping {folder_names[i]} because the folder is not empty.\")\n",
+    "        continue\n",
+    "\n",
+    "    # Load forcings\n",
+    "    ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "        dataset=\"ERA5\",\n",
+    "        start_time=start_time_ERA5,\n",
+    "        end_time=end_time_ERA5,\n",
+    "        shape=shape_file,\n",
+    "        directory=forcing_paths[folder_names[i]]\n",
+    "    )\n",
+    "\n",
+    "    # I need info because my patience is limited\n",
+    "    print(f\"Finished {folder_names[i]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91242ae4-3d21-4d18-815f-5cc986d5961e",
+   "metadata": {},
+   "source": [
+    "### Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "f8e8ac64-fee5-4602-a1f1-90b8fb14c2b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1970-1974'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1975-1979'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1980-1984'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1985-1989'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1990-1994'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1995-1999'</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[32m'ERA5-1970-1974'\u001b[0m, \u001b[32m'ERA5-1975-1979'\u001b[0m, \u001b[32m'ERA5-1980-1984'\u001b[0m, \u001b[32m'ERA5-1985-1989'\u001b[0m, \u001b[32m'ERA5-1990-1994'\u001b[0m, \u001b[32m'ERA5-1995-1999'\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "LumpedMakkinkForcing(start_time='1970-01-01T00:00:00Z', end_time='1974-12-31T00:00:00Z', directory=PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script'), shape=PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script/07DA001_basin.shp'), filenames={'pr': 'OBS6_ERA5_reanaly_1_day_pr_1970-1974.nc', 'tas': 'OBS6_ERA5_reanaly_1_day_tas_1970-1974.nc', 'rsds': 'OBS6_ERA5_reanaly_1_day_rsds_1970-1974.nc', 'evspsblpot': 'Derived_Makkink_evspsblpot.nc'})"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ERA5_forcings = {}\n",
+    "\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Create new path to find relevant files in the folder\n",
+    "    directory_new = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\"\n",
+    "    \n",
+    "    # Load forcings\n",
+    "    ERA5_forcings[folder_names[i]] = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=directory_new)\n",
+    "\n",
+    "# Test to see if it works\n",
+    "print(folder_names)\n",
+    "ERA5_forcings[folder_names[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8eddb25-06e3-4702-87e8-258aeda27a15",
+   "metadata": {},
+   "source": [
+    "### Merge ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "1cb12aa2-4b4c-4108-a5c9-2d8156cdecfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to seperate files based on file names and combine same file names from different folders\n",
+    "def combine_variable(var_name):\n",
+    "    datasets = []\n",
+    "\n",
+    "    for i in range(len(folder_names)):\n",
+    "\n",
+    "        if var_name == \"evspsblpot\":\n",
+    "            file_name = \"Derived_Makkink_evspsblpot.nc\"\n",
+    "        else:\n",
+    "            file_name = f\"OBS6_ERA5_reanaly_1_day_{var_name}_{periods[0][i]}-{periods[1][i]}.nc\"\n",
+    "\n",
+    "        directory = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\" / file_name\n",
+    "\n",
+    "        print(f\"Loading {directory}\")\n",
+    "\n",
+    "        datasets.append(xr.open_dataset(directory))\n",
+    "\n",
+    "    combined = xr.concat(datasets, dim=\"time\")\n",
+    "    return combined"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "b21fe2e4-478a-4e0b-9f1f-a40316e22018",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1970-197</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">4.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1970-197\u001b[0m\n",
+       "\u001b[95m4.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1975-1979/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1975-197</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">9.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1975-1979/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1975-197\u001b[0m\n",
+       "\u001b[95m9.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1980-1984/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1980-198</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">4.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1980-1984/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1980-198\u001b[0m\n",
+       "\u001b[95m4.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1985-1989/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1985-198</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">9.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1985-1989/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1985-198\u001b[0m\n",
+       "\u001b[95m9.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1990-1994/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1990-199</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">4.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1990-1994/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1990-199\u001b[0m\n",
+       "\u001b[95m4.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-1999/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1995-199</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">9.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-1999/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1995-199\u001b[0m\n",
+       "\u001b[95m9.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1970-19</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">74.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1970-19\u001b[0m\n",
+       "\u001b[95m74.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1975-1979/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1975-19</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">79.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1975-1979/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1975-19\u001b[0m\n",
+       "\u001b[95m79.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1980-1984/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1980-19</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">84.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1980-1984/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1980-19\u001b[0m\n",
+       "\u001b[95m84.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1985-1989/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1985-19</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">89.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1985-1989/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1985-19\u001b[0m\n",
+       "\u001b[95m89.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1990-1994/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1990-19</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">94.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1990-1994/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1990-19\u001b[0m\n",
+       "\u001b[95m94.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-1999/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1995-19</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">99.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-1999/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1995-19\u001b[0m\n",
+       "\u001b[95m99.nc\u001b[0m\n"
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+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1970-1</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">974.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1970-1\u001b[0m\n",
+       "\u001b[95m974.nc\u001b[0m\n"
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+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1975-1979/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1975-1</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">979.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1975-1979/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1975-1\u001b[0m\n",
+       "\u001b[95m979.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1980-1984/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1980-1</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">984.nc</span>\n",
+       "</pre>\n"
+      ],
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+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1980-1984/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1980-1\u001b[0m\n",
+       "\u001b[95m984.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1985-1989/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1985-1</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">989.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1985-1989/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1985-1\u001b[0m\n",
+       "\u001b[95m989.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1990-1994/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1990-1</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">994.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1990-1994/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1990-1\u001b[0m\n",
+       "\u001b[95m994.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-1999/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1995-1</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-1999/work/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1995-1\u001b[0m\n",
+       "\u001b[95m999.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1974/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
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+      "text/html": [
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+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1975-1979/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1975-1979/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
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+      "text/html": [
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+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1980-1984/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1980-1984/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1985-1989/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1985-1989/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
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+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1990-1994/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1990-1994/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
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+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-1999/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1995-1999/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Running function for various file name types\n",
+    "combined_variables = {}\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "combined_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / f'ERA5-{periods[0][0]}-{periods[1][-1]}'\n",
+    "# combined_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / f'ERA5-{periods[0][0]}-{periods[1][-1]}'\n",
+    "combined_path.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "    combined_variables[var_names[i]] = combine_variable(var_names[i])\n",
+    "    combined_variables[var_names[i]].to_netcdf(combined_path / f'combined_ERA5_{periods[0][0]}_{periods[1][-1]}_{var_names[i]}.nc')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a439e818-0aa8-4e92-a189-fde70016a911",
+   "metadata": {},
+   "source": [
+    "### Create YAML file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "e60b3316-e100-4af9-a36d-fad721ef6e02",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create yaml\n",
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{periods[0][0]}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{periods[1][-1]}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_ERA5_{periods[0][0]}_{periods[1][-1]}_pr.nc\",\n",
+    "        \"tas\": f\"combined_ERA5_{periods[0][0]}_{periods[1][-1]}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_ERA5_{periods[0][0]}_{periods[1][-1]}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_ERA5_{periods[0][0]}_{periods[1][-1]}_evspsblpot.nc\"\n",
+    "    }}\n",
+    "\n",
+    "# Save the YAML file\n",
+    "yaml_file_path = combined_path / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "10ff50bf-b6e7-4033-9682-3e25d01ecd26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1970-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1999-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1999'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1970_1999_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1970_1999_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1970_1999_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1970_1999_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1970-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'1999-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1970-1999'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1970_1999_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1970_1999_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1970_1999_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1970_1999_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ERA5_combined_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=combined_path)\n",
+    "print(ERA5_combined_forcing)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Step2_Algorithm_Ice.ipynb b/Workyard/Step2_Algorithm_Ice.ipynb
new file mode 100644
index 00000000..df6cd4f0
--- /dev/null
+++ b/Workyard/Step2_Algorithm_Ice.ipynb
@@ -0,0 +1,913 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d3382417-3993-4e5d-8390-0c6cc4197326",
+   "metadata": {},
+   "source": [
+    "## Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "bb67d97e-8317-4b2f-be8e-c8ac9f45f196",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "862f09e2-4350-4eb5-8bdc-d865a99076eb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "4c68de36-ea9f-43be-aa9e-13fdd7b4a3ab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining time period & q_critical\n",
+    "\n",
+    "experiment_start_date = \"2014-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2014-12-31T00:00:00Z\"\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "hysets_id = \"hysets_07DA001\"\n",
+    "basin_size = 132572"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "c2d00787-45c7-4f63-8641-5f1f5f67127e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Loading in data\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"ERA5-1970-2024\"\n",
+    "forcing_path_ERA5.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "calibration_temp = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"calibration_temp\"\n",
+    "calibration_temp.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "# Load CSV discharge 07DA001\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bf6b9b66-876f-40da-8862-bd742448d87f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Loading in data\n",
+    "\n",
+    "# forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5-1970-2024\"\n",
+    "# forcing_path_ERA5.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "# discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# calibration_temp = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"calibration_temp\"\n",
+    "# calibration_temp.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "b40fb132-370d-4584-b198-4a789d02abc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>20367</th>\n",
+       "      <td>2014-01-01</td>\n",
+       "      <td>177.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20368</th>\n",
+       "      <td>2014-01-02</td>\n",
+       "      <td>188.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20369</th>\n",
+       "      <td>2014-01-03</td>\n",
+       "      <td>198.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20370</th>\n",
+       "      <td>2014-01-04</td>\n",
+       "      <td>204.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20371</th>\n",
+       "      <td>2014-01-05</td>\n",
+       "      <td>208.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Date  discharge_m3s\n",
+       "20367 2014-01-01          177.0\n",
+       "20368 2014-01-02          188.0\n",
+       "20369 2014-01-03          198.0\n",
+       "20370 2014-01-04          204.0\n",
+       "20371 2014-01-05          208.0"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "q_obs = q_obs[\n",
+    "    (q_obs[\"Date\"] >= start_date) &\n",
+    "    (q_obs[\"Date\"] <= end_date)\n",
+    "].copy()\n",
+    "\n",
+    "q_obs.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "eb8f1766-b180-4486-9cec-6539c086eb7f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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qOq2xFxGpYZydnenVqxfLli0jNja22KQrNjaWrVu3MnDgQLv19QDx8fHUqVPH9nNeXh6JiYl2ye91113HddddR35+Plu2bOHtt99m6tSphISEMHLkSIKCgggMDGTZsmXFxujr62v3c0mzdP379yc8PJyPPvqI/v3789FHH9GlSxe72djSXssaf0nv72ICAwOLbbR3fvO8lJQUli5dyrPPPstjjz1mO25dk30pnJycuP/++3niiSd48803effdd+ndu/dF18if+56LizsyMvKCrw8KCmLWrFnMmjWLI0eOsGTJEh577DESEhJYtmwZtWvXBiy/T+Vh4cKFuLq6snTpUrubACVtFVfc701gYKAtaT/X+Z+Btc/B22+/zTXXXFPs+Yu7QWA1f/58GjRowBdffGEXx/nNAMvKuvZ8+/btdr/neXl57Nmzp0jlgZU10T63D0NZLFmyBJPJxPXXXw9Ymgpak/3ibnxt2LCBXbt20aJFC6666io8PT3Zvn17kXHbt2+nUaNGtr/Pc99fly5dbOOsN+FatWp1SfGLiFzpNGMvIlIDPf744xiGwX333Ud+fr7dc/n5+dx7770YhsHjjz9e5LULFiyw+/nLL78kLy+v2E7ezs7OdOnSxTaTvG3bNgAGDx5MYmIi+fn5dOzYscjjYgnpuecfO3YsixcvZs2aNWzZsqVIt+/SXssaf0nv72J69erFmTNnWLJkid3xzz77zO5nk8mEYRhFZk0//PDDIn8XZXH33Xfj5ubGmDFj2Lt3b7HN4M53zTXX4OHhUeQ9r1u3rkgJ/MXUq1ePBx54gL59+9r+nrt164bZbOa9994rtpS7rEwmEy4uLnY3mzIzM/n0009LfY4ePXqwY8cOdu3aZXd84cKFdj93794df39/du3aVezvTceOHXFzc7tgrG5ubnZJfXx8fJGu+GCpTChtpUaXLl0ICwuz250A4OuvvyYtLa3IXvZguZkwf/58OnfufEmJ8UcffcRPP/3EqFGjbE0L58yZg5OTE4sXL2bVqlV2D+vfx9y5cwFL1cuQIUNYtGiRXSPKI0eOsGrVKruYBwwYgIeHR5H3N2/ePEwmEzfddFOZ4xcRqQk0Yy8iUgN1796dWbNmMXXqVK699loeeOAB6tWrx5EjR/jf//7Hxo0bmTVrFt26dSvy2kWLFuHi4kLfvn1tXfHbtm3LiBEjAHjvvfdYuXIlN954I/Xq1SMrK8v2Bb9Pnz4AjBw5kgULFjBo0CCmTJlC586dcXV1JTY2llWrVjFs2LBSrwO+6667ePXVVxk9ejSenp5FutCX9lrNmzfnjjvuYNasWbi6utKnTx927NjBG2+8ccEu5Vbjxo1j5syZjBs3jpdeeonGjRvz448/8vPPP9uN8/Pz4/rrr+f1118nKCiIyMhIfvvtN+bMmWMrR74U/v7+jBs3jtmzZ1O/fv0i69WLU6tWLR555BFefPFF7r77bm677TaOHj3Kc889d9FS/JSUFHr16sXo0aNp1qwZvr6+bN68mWXLltkSNR8fH958803uvvtu+vTpw6RJkwgJCeHAgQP89ddfvPPOO2V6jzfeeCNvvfUWo0ePZvLkySQmJvLGG2+UqbR86tSpzJ07l4EDB/Lvf/+bkJAQPvvsM/bs2QOc3ULNx8eHt99+m/Hjx5OUlMStt95KcHAwJ0+e5K+//uLkyZPMnj27xOtYt9q77777bLsNvPDCC4SFhbF//367sa1bt2b16tV8//33hIWF4evrW+LNLWdnZ1577TXGjh3LPffcw6hRo9i/fz/Tp0+nb9++DBgwoMhrFi9eTFJS0kVn6zMzM9mwYYPtz4cOHWLx4sUsXbrUtqsBWErqv/vuO/r378+wYcOKPdfMmTP55JNPmDFjBq6urjz//PN06tSJwYMH89hjj5GVlcUzzzxDUFAQ06ZNs70uICCAp556iqeffpqAgAD69evH5s2bee6557j77ruL9Eb4+uuvAWy9PLZs2WLrK3Hrrbde8P2KiFxRHNi4T0REHGz9+vXGrbfeaoSEhBguLi5GcHCwMXz4cGPdunVFxlq7sW/dutUYMmSI4ePjY/j6+hqjRo2ydc63nvPmm2826tevb7i7uxuBgYFGjx49jCVLltidLzc313jjjTeMtm3bGh4eHoaPj4/RrFkz45577jH2799vG1e/fn3jxhtvvOD76NatmwEYY8aMKfb50l4rOzvbmDZtmhEcHGx4eHgY11xzjbF+/Xqjfv36pepaHhsba9xyyy22z+aWW24x1q1bV6Rbt3VcrVq1DF9fX2PAgAHGjh07ilyntF3xrVavXm0AxiuvvHLRWK0KCgqMGTNmGBEREYabm5vRpk0b4/vvvzd69Ohxwa74WVlZxj/+8Q+jTZs2hp+fn+Hp6Wk0bdrUePbZZ4309HS7a/z444+2buleXl5GixYt7Lqrjx8/3vD29i4SW3Hvde7cuUbTpk0Nd3d3o2HDhsaMGTOMOXPmGIARHR1tG3eh35sdO3YYffr0MTw8PIyAgABj4sSJxscff2wAxl9//WU39rfffjNuvPFGIyAgwHB1dTXq1Klj3HjjjcZXX3110c/2lVdeMSIjIw13d3ejefPmxgcffFDse4qKijK6d+9ueHl5FdmNoCSfffaZ0aZNG8PNzc0IDQ01HnrooRJ3QOjbt2+RTvXn69GjhwHYHt7e3kbDhg2NW2+91fjqq6+M/Px829hZs2YZgLF48eISz/fee+8V2Y1iy5YtRu/evQ0vLy/Dz8/PuOmmm4wDBw4U+/r//Oc/RpMmTQw3NzejXr16xrPPPmvk5OQUGXduzOc/RERqEpNhlENtnIiIiDjctGnTmD17NkePHi1Vwz85a/LkyXz++eckJiZesMReRESkKlIpvoiISDW3YcMG9u3bx7vvvss999yjpP4i/v3vfxMeHk7Dhg1JS0tj6dKlfPjhhzz11FNK6kVEpFpSYi8iIlLNde3aFS8vLwYPHsyLL77o6HCqPFdXV15//XViY2PJy8ujcePGvPXWW0yZMsXRoYmIiFwSleKLiIiIiIiIVGPa7k5ERERERESkGlNiLyIiIiIiIlKNOTSxnzFjBp06dcLX15fg4GBuuukm9u7dazfGMAyee+45wsPD8fT0pGfPnuzcudNuTHZ2Ng8++CBBQUF4e3szdOhQYmNj7cYkJyczduxYzGYzZrOZsWPHcvr06Yp+iyIiIiIiIiIVyqFr7AcMGMDIkSPp1KkTeXl5PPnkk2zfvp1du3bh7e0NwKuvvspLL73EvHnzaNKkCS+++CK///47e/fuxdfXF4B7772X77//nnnz5hEYGMi0adNISkpi69atODs7AzBw4EBiY2P5v//7P8CyrU1kZCTff/99qWItKCjg+PHj+Pr6YjKZKuDTEBERERERETnLMAzOnDlDeHg4Tk4XmJcv68b3FSkhIcEAjN9++80wDMMoKCgwQkNDjVdeecU2JisryzCbzcZ7771nGIZhnD592nB1dTUWLlxoG3Ps2DHDycnJWLZsmWEYhrFr1y4DMDZs2GAbs379egMw9uzZU2wsWVlZRkpKiu1hPYceeuihhx566KGHHnrooYceelTm4+jRoxfMpavUdncpKSkABAQEABAdHU18fDz9+vWzjXF3d6dHjx6sW7eOe+65h61bt5Kbm2s3Jjw8nFatWrFu3Tr69+/P+vXrMZvNdOnSxTbmmmuuwWw2s27dOpo2bVoklhkzZvD8888XOX706FH8/PzK7T2LiIiIiIiIFCc1NZWIiAhbtXpJqkxibxgGDz/8MNdeey2tWrUCID4+HoCQkBC7sSEhIRw+fNg2xs3NjVq1ahUZY319fHw8wcHBRa4ZHBxsG3O+xx9/nIcfftj2s/UD9fPzU2IvIiIiIiIileZiy8GrTGL/wAMP8Pfff7N27doiz53/JgzDuOgbO39MceMvdB53d3fc3d1LE7qIiIiIiIiIw1SJ7e4efPBBlixZwqpVq6hbt67teGhoKECRWfWEhATbLH5oaCg5OTkkJydfcMyJEyeKXPfkyZNFqgFEREREREREqhOHJvaGYfDAAw+waNEiVq5cSYMGDeyeb9CgAaGhoSxfvtx2LCcnh99++41u3boB0KFDB1xdXe3GxMXFsWPHDtuYrl27kpKSwqZNm2xjNm7cSEpKim2MiIiIiIiISHXk0FL8+++/n88++4zvvvsOX19f28y82WzG09MTk8nE1KlTefnll2ncuDGNGzfm5ZdfxsvLi9GjR9vGTpw4kWnTphEYGEhAQACPPPIIrVu3pk+fPgA0b96cAQMGMGnSJN5//33Ast3d4MGDi22cJyIiIiJSFeXn55Obm+voMESknDg7O+Pi4nLZW6o7NLGfPXs2AD179rQ7/tFHHzFhwgQApk+fTmZmJvfddx/Jycl06dKFX375xa4r4MyZM3FxcWHEiBFkZmbSu3dv5s2bZ9vDHmDBggU89NBDtu75Q4cO5Z133qnYNygiIiIiUk7S0tKIjY3FMAxHhyIi5cjLy4uwsDDc3Nwu+RwmQ/9nKJXU1FTMZjMpKSnqii8iIiIilSo/P5/9+/fj5eVF7dq1L3t2T0QczzAMcnJyOHnyJPn5+TRu3BgnJ/vV8qXNQ6tMV3wRERERESlebm4uhmFQu3ZtPD09HR2OiJQTT09PXF1dOXz4MDk5OXh4eFzSeapEV3wREREREbk4zdSLXHnOn6W/pHOUQxwiIiIiIiIi4iBK7EVERERERESqMSX2IiIiIiLicJGRkcyaNcvRYZSbS3k/EyZM4KabbrL93LNnT6ZOnXrZscTExGAymYiKirrsc0nVpMReREREREQqzNGjR5k4cSLh4eG4ublRv359pkyZQmJioqNDq/IWLVrECy+84OgwpBpQYi8iIiIiIhXi0KFDdOzYkX379vH5559z4MAB3nvvPX799Ve6du1KUlKSw2LLz8+noKDAYdcvjYCAAHx9fR0dRolycnIcHYIUUmIvIiJSzjZFJzF+7iYOJ6Y7OhQRuUIZhkFGTp5DHoZhlDrO+++/Hzc3N3755Rd69OhBvXr1GDhwICtWrODYsWM8+eSTduPPnDnD6NGj8fHxITw8nLffftvu+eeee4569erh7u5OeHg4Dz30kO25nJwcpk+fTp06dfD29qZLly6sXr3a9vy8efPw9/dn6dKltGjRAnd3dz744AM8PDw4ffq03XUeeughevToYft53bp1XH/99Xh6ehIREcFDDz1EevrZ/8cnJCQwZMgQPD09adCgAQsWLLjoZ5Ofn8/DDz+Mv78/gYGBTJ8+vchne34p/rvvvkvjxo3x8PAgJCSEW2+91fZcQUEBr776Ko0aNcLd3Z169erx0ksv2Z3v0KFD9OrVCy8vL9q2bcv69ettzyUmJjJq1Cjq1q2Ll5cXrVu35vPPPy8SzwMPPMDDDz9MUFAQffv2BWDJkiU0btwYT09PevXqxccff4zJZLL7XC/2Gcrl0T72IiIi5ezNX/ayMTqJD9Yc4sWbWjs6HBG5AmXm5tPimZ8dcu1d/+6Pl9vF04ikpCR+/vlnXnrpJTw9Pe2eCw0NZcyYMXzxxRe8++67tm38Xn/9dZ544gmee+45fv75Z/75z3/SrFkz+vbty9dff83MmTNZuHAhLVu2JD4+nr/++st2zjvvvJOYmBgWLlxIeHg43377LQMGDGD79u00btwYgIyMDGbMmMGHH35IYGAgdevW5dlnn+Wbb75h4sSJgCXh/vLLL/n3v/8NwPbt2+nfvz8vvPACc+bM4eTJkzzwwAM88MADfPTRR4BlbfzRo0dZuXIlbm5uPPTQQyQkJFzw83nzzTeZO3cuc+bMoUWLFrz55pt8++233HDDDcWO37JlCw899BCffvop3bp1IykpiTVr1tief/zxx/nggw+YOXMm1157LXFxcezZs8fuHE8++SRvvPEGjRs35sknn2TUqFEcOHAAFxcXsrKy6NChA48++ih+fn788MMPjB07loYNG9KlSxfbOT7++GPuvfde/vjjDwzDICYmhltvvZUpU6Zw99138+eff/LII4/YXbc0n6FcHpNRlltuNVhqaipms5mUlBT8/PwcHY6IiFRRKRm5tH9xOfkFBuFmD/547AbtOy0ily0rK4vo6GgaNGiAh4cHGTl5VT6x37hxI9dccw3ffvutXUM4q5kzZ/Lwww9z4sQJgoODiYyMpHnz5vz000+2MSNHjiQ1NZUff/yRt956i/fff58dO3bg6upqd66DBw/SuHFjYmNjCQ8Ptx3v06cPnTt35uWXX2bevHnceeedREVF0bZtW9uYKVOmsGPHDn799VcAfvnlF4YMGUJ8fDy1atVi3LhxeHp68v7779tes3btWnr06EF6ejpHjhyhadOmbNiwwZYA79mzh+bNmzNz5swSm9+Fh4czZcoUHn30UQDy8vJo0KABHTp0YPHixYBlhvzqq69m1qxZLFq0iDvvvJPY2Ngi5flnzpyhdu3avPPOO9x9991FrhUTE0ODBg348MMPbTcwdu3aRcuWLdm9ezfNmjUrNsYbb7yR5s2b88Ybb9jiSUlJ4c8//7SNeeyxx/jhhx/Yvn277dhTTz3FSy+9RHJyMv7+/hf9DD08PIq9fk1x/n/f5yptHqoZexERkXL0+/6T5BdY7pkfT8li74kzNAvVDWERKV+ers7s+nd/h127PFjnF8+9+dm1a1e7MV27drV1lr/tttuYNWsWDRs2ZMCAAQwaNIghQ4bg4uLCtm3bMAyDJk2a2L0+OzubwMBA289ubm60adPGbsyYMWPo2rUrx48fJzw8nAULFjBo0CBq1aoFwNatWzlw4IBdeb1hGBQUFBAdHc2+fftwcXGhY8eOtuebNWuGv79/ie89JSWFuLg4u/drPUdJ8659+/alfv36tvc/YMAAbr75Zry8vNi9ezfZ2dn07t27xGsCdu89LCwMsCwjaNasGfn5+bzyyit88cUXHDt2jOzsbLKzs/H29rY7x7nvE2Dv3r106tTJ7ljnzp3tfr7YZ9i8efMLxi0Xp8ReRESkHK3cY196+evuBCX2IlLuTCZTqWbNHalRo0aYTCZ27dpV7Iz9nj17qFWrFkFBQRc8jzXxj4iIYO/evSxfvpwVK1Zw33338frrr/Pbb79RUFCAs7MzW7duxdnZ/saDj4+P7c+enp5Fqqg6d+7MVVddxcKFC7n33nv59ttv7crDCwoKuOeee+zW81vVq1ePvXv32sVZUXx9fdm2bRurV6/ml19+4ZlnnuG5555j8+bNRZY6lOTcSgdrvNYGgm+++SYzZ85k1qxZtG7dGm9vb6ZOnVqkQd75ib5hGEXe+/k3Jy72GcrlU/M8ERGRcpJfYLB6ryWxH9rWUgq6as+F11iKiFypAgMD6du3L++++y6ZmZl2z8XHx7NgwQJuv/12u6Rww4YNduM2bNhgVybu6enJ0KFD+e9//8vq1atZv34927dvp127duTn55OQkECjRo3sHqGhoReNdfTo0SxYsIDvv/8eJycnbrzxRttz7du3Z+fOnUXO26hRI9zc3GjevDl5eXls2bLF9pq9e/cWach3LrPZTFhYmN37zcvLY+vWrReM08XFhT59+vDaa6/x999/ExMTw8qVK22N66zLCS7FmjVrGDZsGHfccQdt27alYcOG7N+//6Kva9asGZs3b7Y7du5nARf/DOXyKbEXEREpJ1FHk0nOyMXPw4V/9W8KwLYjySSlazsgEamZ3nnnHbKzs+nfvz+///47R48eZdmyZfTt25c6deoU6dr+xx9/8Nprr7Fv3z7+97//8dVXXzFlyhTA0tV+zpw57Nixg0OHDvHpp5/i6elJ/fr1adKkCWPGjGHcuHEsWrSI6OhoNm/ezKuvvsqPP/540TjHjBnDtm3beOmll7j11lvt1jk/+uijrF+/nvvvv5+oqCj279/PkiVLePDBBwFo2rQpAwYMYNKkSWzcuJGtW7dy9913X3QWfcqUKbzyyit8++237Nmzh/vuu++CNwOWLl3Kf//7X6Kiojh8+DCffPIJBQUFNG3aFA8PDx599FGmT5/OJ598wsGDB9mwYQNz5sy56Hu3atSoEcuXL2fdunXs3r2be+65h/j4+Iu+7p577mHPnj08+uij7Nu3jy+//JJ58+YBZ6sCLvYZyuVTYi8iIlJOrGX4PZoGExHgRbNQXwoM+G2fZu1FpGZq3LgxW7Zs4aqrruL222/nqquuYvLkyfTq1Yv169cTEBBgN37atGls3bqVdu3a8cILL/Dmm2/Sv7+ll4C/vz8ffPAB3bt3p02bNvz66698//33tjX0H330EePGjWPatGk0bdqUoUOHsnHjRiIiIkoVZ6dOnfj7778ZM2aM3XNt2rTht99+Y//+/Vx33XW0a9eOp59+2rZG3XrtiIgIevTowfDhw5k8eTLBwcEXvOa0adMYN24cEyZMoGvXrvj6+nLzzTeXON7f359FixZxww030Lx5c9577z0+//xzWrZsCcDTTz/NtGnTeOaZZ2jevDm33377RTvzn+vpp5+mffv29O/fn549exIaGlrsEorzNWjQgK+//ppFixbRpk0bZs+ebdvG0N3dHSjdZyiXR13xS0ld8UVE5GIGzPqdPfFnmHl7W25uV5fXf97D/1YdZHCbMN4Z3d7R4YlINXahrtkiVc1LL73Ee++9x9GjRx0dSrVQHl3xNWMvIiJSDs5k5bIn/gwA1zWuDUDfFpZ1nSt2nyAlM9dhsYmIiFSkd999l82bN9uWSLz++uuMHz/e0WHVKFW7laaIiEg1set4KgB1/D0J8rGUHrata6ZpiC97T5xhSdQxxnaNdGCEIiIiFWP//v28+OKLJCUlUa9ePaZNm8bjjz/u6LBqFM3Yi4iIlIPtx1IAaBl+tkzOZDJxeyfL2s7PNx0tcW9iERGR6mzmzJkcP36crKws9u3bx9NPP42Li+aQK5MSexERkXKws3DGvlUds93x4e3r4ObixK64VFvyLyIiIlKelNiLiIiUgx2FSXurOvaNbfy93BjQ0rLWfuFmNRESERGR8qfEXkRE5DJl5ORx8GQaUHTGHmBkZ0s5/pKo46Rn51VqbCIiInLlU2IvIiJymXbHpVJgQLCvO8G+Rbeh6towkMhAL9Ky8/hhe5wDIhQREZErmRJ7ERGRy7TjWPHr661MJhMjCpvoLdx0pNLiEhERkZpBib2IiMhlOru+vvjEHuDWDnVxcTKx7chp9p04U1mhiYiISA2gxF5EROQyWbvdtwr3K3FMsK8HvZsHA7Bwk5roiYhczOrVqzGZTJw+ffqC4yIjI5k1a1a5Xbdnz55MnTq1TK957rnnuPrqq20/T5gwgZtuuqlc4jGZTCxevLhczlWZxo4dy8svv+zoMBwqOzubevXqsXXr1gq/lhJ7ERGRy5CVm8/+hJIb551rZKd6ACz6M5as3PwKj01EpCqIj4/nwQcfpGHDhri7uxMREcGQIUP49ddfL/i6bt26ERcXh9ls+X/rvHnz8Pf3LzJu8+bNTJ48uSJCv2T/+c9/mDdvnqPDcJi///6bH374gQcffNB2bMKECZhMJrvHNddcY/e67OxsHnzwQYKCgvD29mbo0KHExsbajUlOTmbs2LGYzWbMZjNjx4696M2fSzFr1iwGDhxI3759mTRpEoZh2D0/YcIEHnvssQuew93dnUceeYRHH3203OM7nxJ7ERGRy7An/gz5BQaB3m6EmYs2zjvX9U1qE2724HRGLst3naikCEVEHCcmJoYOHTqwcuVKXnvtNbZv386yZcvo1asX999/f4mvy83Nxc3NjdDQUEwm0wWvUbt2bby8vMo79MtiNpuLvQlRVeTk5FTo+d955x1uu+02fH197Y4PGDCAuLg42+PHH3+0e37q1Kl8++23LFy4kLVr15KWlsbgwYPJzz97M3z06NFERUWxbNkyli1bRlRUFGPHji339zB16lTq1KnDwYMH+eyzzzhz5uwyuoKCAn744QeGDRt20fOMGTOGNWvWsHv37nKP8VxK7EVERC7D1sPJALSpa77ol09nJxPD2tUBUGIvIuUiPT2d9PR0u9nEnJwc0tPTyc7OLnZsQUGB7Vhubi7p6elkZWWVamxZ3XfffZhMJjZt2sStt95KkyZNaNmyJQ8//DAbNmywjTOZTLz33nsMGzYMb29vXnzxRbtS/NWrV3PnnXeSkpJim+197rnngKKl+KdPn2by5MmEhITg4eFBq1atWLp0KQCJiYmMGjWKunXr4uXlRevWrfn888/L/L5eeeUVQkJC8PX1ZeLEiUU+v/NL8b/++mtat26Np6cngYGB9OnTh/T0dNvzc+fOpWXLlri7uxMWFsYDDzxgd75Tp05x88034+XlRePGjVmyZIntufz8fCZOnEiDBg3w9PSkadOm/Oc//yk2nhkzZhAeHk6TJk0AWLduHVdffTUeHh507NiRxYsXYzKZiIqKsr12165dDBo0CB8fH0JCQhg7diynTp0q8bMpKCjgq6++YujQoUWec3d3JzQ01PYICAiwPZeSksKcOXN488036dOnD+3atWP+/Pls376dFStWALB7926WLVvGhx9+SNeuXenatSsffPABS5cuZe/evSXGFBkZyYsvvsi4cePw8fGhfv36fPfdd5w8eZJhw4bh4+ND69at2bJli93rPvzwQ/7880/+9a9/2d2k+OOPP3BycqJLly7k5OTwwAMPEBYWhoeHB5GRkcyYMcM2NjAwkG7dul3S71lZKLEXERG5DFtikgDo1CDgIiMtejezrLP/bd9J8vILLjJaROTCfHx88PHxsUu0Xn/9dXx8fIokh8HBwfj4+HDkyNndOf73v//h4+PDxIkT7cZGRkbi4+NjN8tY1tLypKQkli1bxv3334+3t3eR58+f0X722WcZNmwY27dv56677rJ7rlu3bsyaNQs/Pz/bbO8jjzxS5JwFBQUMHDiQdevWMX/+fHbt2sUrr7yCs7MzAFlZWXTo0IGlS5eyY8cOJk+ezNixY9m4cWOp39eXX37Js88+y0svvcSWLVsICwvj3XffLXF8XFwco0aN4q677mL37t2sXr2a4cOH227GzJ49m/vvv5/Jkyezfft2lixZQqNGjezO8fzzzzNixAj+/vtvBg0axJgxY0hKSrK957p16/Lll1+ya9cunnnmGZ544gm+/PJLu3P8+uuv7N69m+XLl7N06VLOnDnDkCFDaN26Ndu2beOFF14oUjIeFxdHjx49uPrqq9myZQvLli3jxIkTjBgxosT3+/fff3P69Gk6duxY5LnVq1cTHBxMkyZNmDRpEgkJCbbntm7dSm5uLv369bMdCw8Pp1WrVqxbtw6A9evXYzab6dKli23MNddcg9lsto0pycyZM+nevTt//vknN954I2PHjmXcuHHccccdbNu2jUaNGjFu3Djb34v1Zo2Hhwcff/wxf/31l+1cS5YsYciQITg5OfHf//6XJUuW8OWXX7J3717mz59PZGSk3bU7d+7MmjVrLhjf5XKp0LOLiIhcwQzDYHNhYt85snSJfbt6tfD3cuV0Ri7bjpymcwk3BBLOZBHg5YaLs+7Bi0j1dODAAQzDoFmzZqUaP3r0aLuEPjo62vZnNzc3zGZLZVRoaGiJ51ixYgWbNm1i9+7dtlnphg0b2p6vU6eO3Q2BBx98kGXLlvHVV1/ZJYsXMmvWLO666y7uvvtuAF588UVWrFhRZNbeKi4ujry8PIYPH079+vUBaN26te35F198kWnTpjFlyhTbsU6dOtmdY8KECYwaNQqAl19+mbfffptNmzYxYMAAXF1def75521jGzRowLp16/jyyy/tEnBvb28+/PBD3NzcAHjvvfcwmUx88MEHeHh40KJFC44dO8akSZNsr5k9ezbt27e3a4I3d+5cIiIi2Ldvn+0zPldMTAzOzs4EBwfbHR84cCC33XYb9evXJzo6mqeffpobbriBrVu34u7uTnx8PG5ubtSqVcvudSEhIcTHxwOWfg3nnxcsN62sY0oyaNAg7rnnHgCeeeYZZs+eTadOnbjtttsAePTRR+natSsnTpwgNDSUESNGkJKSQmJiIn369KFVq1a2cy1ZsoQ33ngDgCNHjtC4cWOuvfZaTCaT7e/4XHXq1CEmJuaC8V0uJfYiIiKXKCYxg1NpObi5ONG67oUb51k5O5no2aQ2i6OOs3JPQrGJ/S874/nH/K3ccU19/j2sVTFnERGxSEuzNO88d435v/71L6ZOnYqLi/1XfevsqKenp+3Y/fffz6RJk2wz2lbWJOTcsRMmTChTbNaZz4stU7Iqboa3rKKioqhbt26xCSdYytZfeeUVvvjiC44dO0Z2djbZ2dnFVhSUZPfu3fzjH/+wO9a1a1dWrVpV7Pi2bdvSu3dvWrduTf/+/enXrx+33nortWrVIiEhgePHj9O7d+8LXrNNmza2P3t7e+Pr62s32/3ee+/x4YcfcvjwYTIzM8nJybHr0g+WmwnWpB5g7969tGnTBg+Ps/1hOnfubPearVu3smrVKnx8fIrEdPDgwWI/58zMTNzd3Yv8vd9+++22P7dq1YqOHTtSv359fvjhB4YPH17iezcMw+5cxf0+nT+mOOd+hiEhIYD9DRbrsYSEBEJDQ+2WO5xr9+7dxMbG0qdPH8Dy30Xfvn1p2rQpAwYMYPDgwXZVB2D57ygjI+OC8V0uTQOIiIhcos3Rltn6tnXNuLs4X2T0Wb0Ky/FX7im6zj4jJ4/nluykwICfdsQX6cIrInIub29vvL297ZIaNzc3vL29cXd3L3ask9PZFMDV1RVvb2+75O5CY8uicePGmEymUjcNK0tyXZJzb0QU580332TmzJlMnz6dlStXEhUVRf/+/Su0mZyzszPLly/np59+okWLFrz99ts0bdqU6Ojoi8Zrdf5nbzKZbP0PvvzyS/75z39y11138csvvxAVFcWdd95Z5D2d//kWlwyf/29OQUEBQ4YMISoqyu6xf/9+rr/++mJjDQoKIiMj46KfaVhYGPXr12f//v0AhIaGkpOTQ3Jyst24hIQEW9IdGhrKiRNF/+08efKkbUxJzv0Mre+7uGPn9pUozpIlS+jbt6/t7659+/ZER0fzwgsvkJmZyYgRI7j11lvtXpOUlETt2rUveN7LpcReRETkElnL8DuVsgzfqkeT2jg7mdh3Io2jSfZ38GevPsjxFEs558kz2RxJqtg7/CIiFSUgIID+/fvzv//9z65RnFVZtyhzc3Oz645enDZt2hAbG8u+ffuKfX7NmjUMGzaMO+64g7Zt29KwYUNbYllazZs3t2v8BxT5+Xwmk4nu3bvz/PPP8+eff+Lm5sa3336Lr68vkZGRF93670LWrFlDt27duO+++2jXrh2NGjXi4MGDF31ds2bN+Pvvv+2aLJ7fPK59+/bs3LmTyMhIGjVqZPco6UaMtVJg165dF7x+YmIiR48eJSwsDIAOHTrg6urK8uXLbWPi4uLYsWMH3bp1AyyVESkpKWzatMk2ZuPGjaSkpNjGVLTvvvuuSGNAPz8/br/9dj744AO++OILvvnmG1sPBIAdO3bQrl27Co1Lib2IiMglutTE3t/LjQ71LGsIP91wmD8OnOKPA6f4eWc87/9+CABfD0sJ7abopBLPIyJS1b377rvk5+fTuXNnvvnmG/bv38/u3bv573//S9euXct0rsjISNLS0vj11185depUsaXNPXr04Prrr+eWW25h+fLlREdH89NPP7Fs2TIAGjVqxPLly1m3bh27d+/mnnvuueja7PNNmTKFuXPnMnfuXPbt28ezzz7Lzp07Sxy/ceNGXn75ZbZs2cKRI0dYtGgRJ0+epHnz5gA899xzvPnmm/z3v/9l//79bNu2jbfffrvU8TRq1IgtW7bw888/s2/fPp5++mk2b9580deNHj2agoICJk+ezO7du/n5559t68ats9f3338/SUlJjBo1ik2bNnHo0CF++eUX7rrrrhJvstSuXZv27duzdu1a27G0tDQeeeQR1q9fT0xMDKtXr2bIkCEEBQVx8803A5YtAidOnMi0adP49ddf+fPPP7njjjto3bq1rey9efPmDBgwgEmTJrFhwwY2bNjApEmTGDx4ME2bNi31Z3apEhIS2Lx5M4MHD7YdmzlzJgsXLmTPnj3s27ePr776itDQULvmkGvWrClSnl/elNiLiIhcgoQzWcQkZmAyQfv6tS7+gvPc0NxSjv9/vx9izIcbGfPhRu75dCs5eQV0bxTImC6W5jtbYpIvdBoRkSqtQYMGbNu2jV69ejFt2jRatWpF3759+fXXX5k9e3aZztWtWzf+8Y9/cPvtt1O7dm1ee+21Ysd98803dOrUiVGjRtGiRQumT59uS0Kffvpp2rdvT//+/enZsyehoaF229KVxu23384zzzzDo48+SocOHTh8+DD33ntvieP9/Pz4/fffGTRoEE2aNOGpp57izTffZODAgQCMHz+eWbNm8e6779KyZUsGDx5cpiqCf/zjHwwfPpzbb7+dLl26kJiYyH333XfR1/n5+fH9998TFRXF1VdfzZNPPskzzzwDYFuaER4ezh9//EF+fj79+/enVatWTJkyBbPZbLdM43yTJ09mwYIFtp+dnZ3Zvn07w4YNo0mTJowfP54mTZqwfv16u23kZs6cyU033cSIESPo3r07Xl5efP/993Y9IBYsWEDr1q3p168f/fr1o02bNnz66ael/rwux/fff0+XLl3sGvj5+Pjw6quv0rFjRzp16kRMTAw//vij7fNZv349KSkpRcrzy5vJ0OK9UklNTcVsNpOSkoKfn5+jwxEREQf7cXsc9y3YRrNQX5ZNLX6d4YWcSsvmoc//JDHNfg2ir4cLb9zWlkOn0rhr3hYaBnmz8pGe5RS1iFRXWVlZREdH06BBgyLr4UXKy4IFC7jzzjtJSUkp9fr/4mRlZdG0aVMWLlxY5sqMqmzo0KFce+21TJ8+vdSvue2222jXrh1PPPFEiWMu9N93afNQdcUXERG5BFsPW2bSy1qGbxXk485nk64p8flaXpbOxYdOpXMqLZsgH/cSx4qIiFyKTz75hIYNG1KnTh3++usvHn30UUaMGHFZST1YZvw/+eQTTp06VU6RVg3XXnutbdvB0sjOzqZt27b885//rMCoLBxaiv/7778zZMgQwsPDMZlMLF682O55k8lU7OP111+3jenZs2eR50eOHGl3nuTkZMaOHYvZbMZsNjN27NgyN+sQERE51574VABa1yndNndlZfZypWmIpTxxS4zW2YuISPmLj4/njjvuoHnz5vzzn//ktttu4//+7//K5dw9evRgyJAh5XKuqmL69OlERESUery7uztPPfXUZd8oKQ2HJvbp6em0bduWd955p9jn4+Li7B5z587FZDJxyy232I2bNGmS3bj333/f7vnRo0cTFRXFsmXLWLZsGVFRUYwdO7bC3peIiFz59p2w7B3dJNT3IiMvXacGlrX7m7XOXkREKsD06dOJiYmxlYLPnDkTLy8vR4cll8ChpfgDBw60NY0oTmhoqN3P3333Hb169aJhw4Z2x728vIqMtdq9ezfLli1jw4YNdOnSBYAPPviArl27snfv3krpnigiIleW5PQcTp6xbA/UONinwq7TKTKA+RuO2Lrvi4iIiBSn2nTFP3HiBD/88AMTJ04s8tyCBQsICgqiZcuWPPLII5w5c8b23Pr16zGbzbakHuCaa67BbDazbt26Eq+XnZ1Namqq3UNERARg3wnLvzN1/D3xdq+4e+QdC9fv7zyeSlbuhfduFpGaQX2vRa485fHfdbVpnvfxxx/j6+vL8OHD7Y6PGTOGBg0aEBoayo4dO3j88cf566+/WL58OWBZN3LudgRWwcHBF9yzcsaMGTz//PPl+yZEROSKsC+hsAw/pOJm6wHCzR74ebiQmpVHTGI6zUK1K4tITWXd7isnJ6dS1uuKSOXJyMgAwNXV9ZLPUW0S+7lz5zJmzJgi7f8nTZpk+3OrVq1o3LgxHTt2ZNu2bbRv3x6wNOE7n2EYxR63evzxx3n44YdtP6emppapUYKIiFy59hfO2DcJqbj19WD596tBkDd/xaYQc0qJvUhN5uLigpeXFydPnsTV1fWCe4iLSPVgGAYZGRkkJCTg7+9vu4F3KapFYr9mzRr27t3LF198cdGx7du3x9XVlf3799O+fXtCQ0M5ceJEkXEnT54kJCSkxPO4u7vj7q6thUREpChrKX7jCk7sAVtif+hUeoVfS0SqLpPJRFhYGNHR0Rw+fNjR4YhIOfL39y+xZ1xpVYvEfs6cOXTo0IG2bdtedOzOnTvJzc0lLCwMgK5du5KSksKmTZvo3LkzABs3biQlJYVu3bpVaNwiInJl2n+ickrxARoEWa4RfVKJvUhN5+bmRuPGjcnJyXF0KCJSTlxdXS9rpt7KoYl9WloaBw4csP0cHR1NVFQUAQEB1KtXD7CUwH/11Ve8+eabRV5/8OBBFixYwKBBgwgKCmLXrl1MmzaNdu3a0b17dwCaN2/OgAEDmDRpkm0bvMmTJzN48GB1xBcRkTI7lZZNYrrlS3WjCuyIb9WgtjcA0ZqxFxHAycmpyNJUERGHLs7ZsmUL7dq1o127dgA8/PDDtGvXjmeeecY2ZuHChRiGwahRo4q83s3NjV9//ZX+/fvTtGlTHnroIfr168eKFSvs7nosWLCA1q1b069fP/r160ebNm349NNPK/4NiojIFcdahh8R4ImXW8XfH28QaEnsYxKV2IuIiEjxTIb2zCiV1NRUzGYzKSkp+PmpeZGISE318boYnl2ykz7Ng/lwfKcKv96ZrFxaP/cLAH892w+z56V3zBUREZHqpbR5qNppioiIlEFlNs4D8PVwpbavpZlrjMrxRUREpBhK7EVERMqgMhvnWTUI0jp7ERERKZkSexERkTKILlzr3qh25czYw9l19krsRUREpDhK7EVERMogNTMXAH+vylvrrs74IiIiciFK7EVEREopN7+A7LwCAHzcK2/HWJXii4iIyIUosRcRESml9Ow825+9KzGxb3hOYq/NbEREROR8SuxFRERKKa0wsXdzccLNpfL+CY0I8MJkslz/VFpOpV1XREREqgcl9iIiIqWUnp0PVG4ZPoCHqzN1/D2BqlGOv+FQIp+uj1H1gIiISBWhxF5ERKSUrDP23u7OlX7ts+vs0yr92ucyDIMHPtvG09/tZFN0kkNjEREREQsl9iIiIqVkXWPv7Va5M/Zwdp39IQfP2B88mWZbDqDEXkREpGpQYi8iIlJK1sS+skvxASILE/sYByf2m2OSbX/eFKPEXkREpCpQYi8iIlJKZ2yl+JWf2FeVLe82nzNLv+1wMnn5BQ6MRkRERECJvYiISKnZZuw9HFGK7wNATGIG+QWOa1q3+fDZxD49J5898WccFouIiIhYKLEXEREpJVti74A19nVqeeLqbCInr4DjpzMr/foA8SlZHE3KxMkEHevXAmCzyvFFREQcTom9iIhIKaUVbnfniFJ8ZycT9QK8AIhJdEw5vjWJbxHuR69mwQBsOWfNvYiIiDhG5X8zERGRK8aZrFyeXryDk2nZALQMN/PYgGY4OZkcHFnFONs8r/K3uwNoEOTDwZPpRJ9K57rGtSv9+tbEvmP9ANuM/aaYJAzDwGS6Mv/ORUREqgMl9iIicskWbDzC4qjjtp//OJBIzya16dYoyIFRVZx0BzbPA2hY2xt2w6GTjpqxt8zOd4oMoG2EP27OTpw8k82RpAzqB3o7JCYRERFRKb6IiFwiwzD4YvNRAO7sHkmf5iEALCw8diVKc3Bi78jO+CmZueyJTwWgU2QtPFydaV3XDNjvZz93bTS3zl7HrbPXMeGjTQ7v4i8iIlITKLEXEZFLsjE6iehT6Xi7OfNIv6ZM6d0YgGU74klOz3FwdBUjzYH72ANEFs6KO2KN/e64VAwD6vh7EuznAcA1DQMA+HlnPAAJqVm89ONuthxOZsvhZFbvPWm7+SMiIiIVR4m9iIhcEmvCNqRtON7uLrSua6ZluB85+QUs+vOYg6OrGFWiFB84mpRBTl757R8ffSqduz/ewtbDJXe4t868Nwr2sR27uV1dAFbuSSA+JYuvtsaSX2DQMtyPkZ0ibLGKiIhIxVJiLyIiZZaSkcuP2+MAGNm5nu249c8LNx3BMBy313pFcfSMfbCvO15uzhQYcKQcE+ZF22JZsfsED30eRWZOfrFjrIm9dTkAWJL8TpG1KDDgqy1HbTd7xneLpHfh0ozyjFNERESKp8ReRETKbHHUMbLzCmgW6kvbwnXWAMOuDsfD1Yn9CWlsO3LlbYOWXrjdnaMSe5PJVCHr7BMLl04cO53Je78dLHaMtWGftWrAamQny82cd1cf5EhSBr7uLgxuE0ZEgCcAR5OV2IuIiFQ0JfYiIlJmv+07CcAt7evabXPm5+FKvxahhWNOOSS2inS2FN8x290BRBYm9jHlmNgnpZ3tifDebweLLZ+3ruuPPK/7/aDWYfh6uJCZa7npMfTqcLzcXIio5QXA6YxcUjJzyy1WERERKUqJvYiIlNn2YykAtK/vX+S59vUsx3YWjrlSGIZBeo5jS/EBGhYm9odOpZXbOZMyLIm9l5sz2XkFvPzjbrvn8wsMDicWLcUH8HRz5qar69h+HlW4HMPb3YVAbzdA6+xFREQqmhJ7EREpk4TULE6eycbJBM3D/Io8b90CbcfxKyuxz8zNp6CwbYCjmufB2eZ1O4+nlts5rbsYTOvXFIBfdp3gdMbZWfxjyZnk5hu4uTgR7u9Z5PVju9bH3cWJaxoG0KrO2aUZEQGWWftYleOLiIhUKCX2IiJSJtaE/araPni5FU1wm4f5YTLBidRsEs5kVXZ4FSYtyzJbbzJZZrYdpWOkZYu5ncdTbUsDLldyYRLftWEgTUJ8yC8wbMst4Gx1QGSgF85OpiKvbxLiy5rpvZg7oZPd8XqFib0a6ImIiFQsJfYiIlIm22MtM8Xnzsyey8vNhatqF84qHyu/WWVHs3bE93ZzsesrUNnq+HtSx9+T/AKDqKOnL/t8BQUGyRmWNfCBPm7c0MzSzX7VngTbmJhiOuKfL9jPo8iNHlsDvaTMy45TRERESqbEXkREysQ6Y19SYg/QKtxSor/jClpn7+iO+OfqGFkLgE3RJe87X1pnsvLIL1xj4O/lyg3NggFYve+k7bi1A3/kBRL74mjGXkREpHIosRcRkTKxNsWzJu/FsSb9V9I6+7Qq0BHfqlNhOf6Ww5ef2Fsb5/m4u+Du4kz7ev6YPV05nZHLn4VbFh4qTOwbljGxt3bG15Z3IiIiFUuJvYiIlFpiWjbHUyzr5luUJrG/gkrxrevZq8KMvTWx//PIaXLzC5i9+iB93vqNuJSyl7wnFTbOq+XtCoCLsxM9mtQGYGVhOX60rRTfp0zntjXPS8qkwNp5UERERMqdEnsRESm1HYWd2BsGeePr4VriOGvSf+x0pi1xrO6sW905siO+VeNgH8yermTk5PPttmO8/vMeDiSk8dP2+DKfy/r3E+DlZjtmLcdfuSeB7Lx8jp223DC40Br74oSZPXB2MpGTX0DCmewyxyYiIiKlo8ReRERKzbpmvuUF1tcD+Hm4Ehloma3deYWU458txXd8Yu/kZKJjfcs6+6cW77Btw3cpSx+SbTP2ZxP7Hk1q42SCPfFn+HJLLIZhqVQI8nEr6TTFcnF2ok7h9nhaZy8iIlJxlNiLiEipWRP71nVKLsO3spbjb79CGuhZt7urCqX4cHbbu5z8AtuxS9mFwLrG/twZ+1rebvRpbumO//TiHYBltv5SdgM42xlfib2IiEhFUWIvIiKlZuuIH37hGXs4d539lZHYp1eh5nkAnRvUsv15TJd6AOxPOENmTn6ZzmOdsQ/wtp+NnzXyaga0DLX9XNYyfCt1xhcREal4SuxFRKRUMnPybfuRNwu7+Ix9s1BfAA4kpFVoXJUlzbbdXcm9BSpT6zr+NA/zo01dM08PbkGQjzsFBuyOL9usfVIxpfgAXm4uvDumPff1vAp3Fyd6Nw++pDjrWjvjK7EXERGpMFWjnlBERKq8mERLZ3Szp2uR2d3iNCzsoB6TmEF+gYGzU9nLuKuSs13xq8aMvZuLEz9NuY6CAgMnJxOt6vixeu9Jdh5LoX29Whc/QaHkjOJn7MGyln/6gGY83LcJLs6XNhdgnbHXlnciIiIVRzP2IiJSKme3PCtdSXadWp64OpvIySvg+Omyb8NW1aRVoa7453IqvGHS+hJ7Gthm7L1KvllzqUk9nN3yTqX4IiIiFUeJvYiIlIo1sW9YysTe2clE/UBvu9dWZ+lVqCt+cVqGW3saXFopfmmqMC6Fdcb+RGo2WbllW/8vIiIipePQxP73339nyJAhhIeHYzKZWLx4sd3zEyZMwGQy2T2uueYauzHZ2dk8+OCDBAUF4e3tzdChQ4mNjbUbk5yczNixYzGbzZjNZsaOHcvp06cr+N2JiFxZyjpjf+5Yaxl/dXa2FL9qJvat61oS+30nzpQpgT6b2FdM74BaXq62zyw2ufpXboiIiFRFDk3s09PTadu2Le+8806JYwYMGEBcXJzt8eOPP9o9P3XqVL799lsWLlzI2rVrSUtLY/DgweTnn/1SM3r0aKKioli2bBnLli0jKiqKsWPHVtj7EhG5ElkT+8gyJPbW2f1DJ6t/Yn8mq2rP2IebPajl5UpegcG+E2dK9Zrc/AJSC9/XhUrxL4fJZKJurcIt77TOXkREpEI49NvJwIEDGThw4AXHuLu7ExoaWuxzKSkpzJkzh08//ZQ+ffoAMH/+fCIiIlixYgX9+/dn9+7dLFu2jA0bNtClSxcAPvjgA7p27crevXtp2rRp+b4pEZEr1KXM2FtvAlwRpfg5Vat53vlMJhOt6phZs/8UO46l0qau/0Vfczojt/C14F9BiT1YyvH3xJ9RZ3wREZEKUuXX2K9evZrg4GCaNGnCpEmTSEhIsD23detWcnNz6devn+1YeHg4rVq1Yt26dQCsX78es9lsS+oBrrnmGsxms21McbKzs0lNTbV7iIjUVCkZubaS7Uspxb8iEvvC7e6q6ow9QKvCBno7jpeugZ61I76/p2uF7lpgbaCnxF5ERKRiVOnEfuDAgSxYsICVK1fy5ptvsnnzZm644Qays7MBiI+Px83NjVq17Lf1CQkJIT4+3jYmOLjo3rvBwcG2McWZMWOGbU2+2WwmIiKiHN+ZiEj1El24Rj7Ez71Mia21FD82OYOcvIIKia2ypFXxNfYAjYMtWwweLmVPg5L2sC9v9dQZX0REpEJV6cT+9ttv58Ybb6RVq1YMGTKEn376iX379vHDDz9c8HWGYWAynZ15OPfPJY053+OPP05KSortcfTo0Ut/IyIi1Vz0qTQAIgNLP1sPUNvXHW83ZwqM6p3U5eYX2G5MVOXEPtzfspb9+OmsUo1PtjbOq8AyfICIAEtcR5LUPE9ERKQiVOnE/nxhYWHUr1+f/fv3AxAaGkpOTg7Jycl24xISEggJCbGNOXHiRJFznTx50jamOO7u7vj5+dk9RERqqujC5ncNa5ctsTeZTDSoXf3L8a0d8aFql+LXKUzsj53OxDCMi45PyqjcGfvYpIxSxSUiIiJlU60S+8TERI4ePUpYWBgAHTp0wNXVleXLl9vGxMXFsWPHDrp16wZA165dSUlJYdOmTbYxGzduJCUlxTZGREQuLDrRMttelvX1VpG2vezTyjWmymQtw3dzccLVuer+0xni54HJBDl5BSQWzsZfSFJa5czY161lSezPZOfZGvaJiIhI+XHotENaWhoHDhyw/RwdHU1UVBQBAQEEBATw3HPPccsttxAWFkZMTAxPPPEEQUFB3HzzzQCYzWYmTpzItGnTCAwMJCAggEceeYTWrVvbuuQ3b96cAQMGMGnSJN5//30AJk+ezODBg9URX0SklKxJeYMgnzK/tqGtgV71LcWvDuvrwXLjIdjXnROp2RxLziTIx/2C4ytrxt7D1ZlgX3cSzmRzNDmjwq8nIiJS0zh02mHLli20a9eOdu3aAfDwww/Trl07nnnmGZydndm+fTvDhg2jSZMmjB8/niZNmrB+/Xp8fX1t55g5cyY33XQTI0aMoHv37nh5efH999/j7Hx2O6IFCxbQunVr+vXrR79+/WjTpg2ffvpppb9fEZHqyDAMWyl+gyCvMr/+bCl+9Z2xt5bie1fRre7OVce2zv7i69mta+wDKyHRjlADPRERkQrj0KmHnj17XnCt3c8//3zRc3h4ePD222/z9ttvlzgmICCA+fPnX1KMIiI13ckz2aTn5ONkOpuclYV1lr86r7E/k2VJ7H3dXR0cycWF+3uy7chpjpUisU8qLIuvjBn0egFebD2czFE10BMRESl3VXehoIiIVAmHChPyOrU8cXcp+4x1g8I19idSs+2a0FUntsTeo2qX4sO5M/YX74yflG7ZPraWV8XfsIioZe2Mrxl7ERGR8qbEXkRELmh/gqWEvlHtsq+vBzB7ueJfmDgeTa6eSV1qlmVm29ejeszYQ+lK8eNTLMl/iJ9HhcYEZ6s9Yqvp74CIiEhVpsReREQuaP+JMwA0CfG9yMiSRRR2RT+SWD2TOuuMvV81mLEPP2fLuwvJys3nVGFXfOssf0WqpzX2IiIiFUaJvYiIXNDe+MtP7K1J3dHk6rm++oxtxr46JPaW2feLzdjHFc7We7k52yoqKpJ1xv5Ycib5BdrLXkREpDwpsRcRkQuyluJf1oy9NbGvprO1Z9fYV/1S/Lr+ls86MT2HrNz8EsdZE/9wf09MJlOFxxXi54GbsxN5BYZm7UVERMqZEnsRESnRqbRsktJzMJmgUfClrbEHiAiwlHpX/8S+6s/Y+3m64O1maXJ4oVn7Y+ck9pXB2cnE1fX8AViz/2SlXFNERKSmUGIvIiIl2le4vj6ilheebpe+h3t1X199pho1zzOZTKVaZ3+scFlEHf+Kb5xndUOzYABW7kmotGuKiIjUBErsRUQEgD8OnCrSsXz/CWsZ/qXP1sPZ5nlHkzMwjOq3vjrV2jzPs+rP2EPpOuPbSvHNlTNjD9C7MLFfdzCRjJzqufWhiIhIVaTEXkRE2B2XypgPN3Lfgm12x60z9o0vY309WBJNJxNk5RZwMi37ss7lCNVpjT2c2xm/5L3sj6cUztjXqrzEvlGwD3VreZKTV8AfBxIr7boiIiJXOiX2IiLC7rhUAHYdTyUnr8B23Dpj3/QyE3s3FyfCzNZ19tWvM3516ooPZ8vrLzxjb0n6K2uNPViWCfRWOb6IiEi5U2IvIiK2ZDuvwCD6VDoAhmGwL8E6Y395pfhQvRvoVad97OHsLPyxErYXNAzDtv6+MvawP1evwsR+1Z6EarksQ0REpCpSYi8iInZN7azl9yfPZHM6IxcnE1xVuxwS+1rVs4GeYRjVqnkenF03by23P19ieg45eQWYTJZt6CrTNQ0D8XR1Jj41i12FlSIiIiJyeZTYi4gIR89pmre/MLHfV1iGXz/QGw/XS++Ib1Wvmu5ln56TT0HhxHJ1KcU/t3lebn5BkeetM/nBvu64uVTuVwEPV2eubRwEwLId8ZV6bRERkSuVEnsREbFLtvfaEvvCMvzL2L/+XPUCq+eMvXW23tnJhGc53OCoDHX8PfFxdyE33+BAQlqR5487qAzfamjbcAC+2hJLXjE3HkRERKRslNiLiNRw2Xn5xKee7Z5ubZi343gKAE1DL69xnlXdwlL82BLWfVdVZzviu2AymRwcTek4OZloGe4HwI5jKUWet66vr8zGeefq1zKEWl6uxKdm8du+kw6JQURE5EqixF5EpIY7lpyJYYBTYc4ak5hOZk4+v+21JFxdrwosl+tYS/GPp2Tadd6v6qpbR3yrVnXMAOw8XnQdu7UjvqNm7N1dnLmlfV0AFm4+6pAYREREriRK7EVEajhraXyjYB/8PFwoMODbP4+RmJ6Dr7sLnSIDyuU6QT5ueLo6YxgX3oatqkm1dcSvHo3zrFrVsczYby9mxv64g2fsAUZ2jgAs294lnFMxIiIiImWnxF5EpIY7WlgaXy/AiyaF+9V/sOYQANc3qY2rc/n8U2EymWxb3lWndfbnluJXJ60LZ+x3HU8lv8B+WzlHl+IDNAr2pWP9WuQXGHy1NdZhcYiIiFwJlNiLiNRw1sZ5EQFeNC5M7K172Vv3HC8v1XHLu+q21Z1VgyAfvNycyczNJ/qUfQM9RzfPsxrRyTJr/+P2OIfGISIiUt0psRcRqeGsib1lxv5sB3yTCXo2rV2u14qwbnmXXJ0S++o5Y+/sZKJFmLWB3tl19lm5+SSm5wCOT+y7FfZv2Bt/hqzcfIfGIiIiUp0psRcRqeGss+cRtbxoGnK2A37buv4E+biX67Wq41721hn76rbGHs420Dt3nb111wNfdxf8PB17s6KOvye1vFzJKzBs2yuKiIhI2SmxFxGp4Wwz9oFnS/EBepdzGT6cM2OfVH2a51XXGXug2C3vVu1NACy7HTh6+z6TyWS7+XBuVYGIiIiUjRJ7EZEaLCUj19b1vW4tT4J83Kjj74nJBH1bhpT79awz9tVpjX1qZvXc7g6gdd2zDfQKChvo/brHktjfUAE3bi5Fy/CiVQUiIiJSNtXvW4qIiJQb61r3IB93vNws/yTMndCJk2eyaRbqV+7Xq1vLsqY7JTOXlMxczJ5Vv7z97Ix91Y/1fI1q++Du4sSZ7DwOJ2Xg4+7C37GngfJvjHiprN37dx5XYi8iInKpNGMvIlKDHbE1zjvbRK1pqC/XNg6qkOt5u7sQ5OMGVJ919tW5FN/F2clW6v7F5qOs3puAYVj2uA/x83BwdBat6lhuIO2JO0NufoGDoxEREamelNiLiNRg5251V1nqFm55F1tNOuOnVuPmeQD39rgKgDlrDzF/w2EAbmhW/sssLlW9AC98PVzIyS9QAz0REZFLpMReRKQGi0vJAiC8Erc9q27r7KvzjD1A7+bB9Gxam9x8g79iLeXuVWV9PRQ20CtcZ79TDfREREQuiRJ7EZEazLp3uI975SWt1S+xtzbPq54z9iaTiWcGt8DV2dIBP8jHjTaF5flVhbUcf4fW2YuIiFwSJfYiIjVYZmFi7+5Sef8cRBSu568OW94ZhkFatmXG3q+aztgDNKztw6TrGgIwoFUoTk6O3ebufGe3vFNiLyIicimq77cUERG5bJk5lsTe08250q55di/7qj9jn56TT+EucdV2xt7qkX5NuaZhIB3q13J0KEVYE/tdcank5Rfg4qx5BxERkbIoc2IfExPDmjVriImJISMjg9q1a9OuXTu6du2Kh0fV6LArIiKlk5Vn6ULu6VqJib2teV4mBQVGlZs9Ppe1DN/FyYSHa/VONp2cTFzfpLajwyhWg0BvvNycycjJJyYxnUbBvo4OSUREpFopdWL/2Wef8d///pdNmzYRHBxMnTp18PT0JCkpiYMHD+Lh4cGYMWN49NFHqV+/fkXGLCIi5STLOmNfiYl9mNkDFycTOfkFnDiTRZi58hr3ldW5jfNMpqp7A6K6c3Iy0TjYh79iU9h3Ik2JvYiISBmVavqhffv2vPXWW9xxxx3ExMQQHx/P1q1bWbt2Lbt27SI1NZXvvvuOgoICOnbsyFdffVXRcYuISDmwrrH3qMTE3sXZydaFv6qvs0/NrN6N86qTxiGWZF5b3omIiJRdqWbsX3jhBW688cYSn3d3d6dnz5707NmTF198kejo6HILUEREKo4jEnuwdMY/kpTBkaQMOjcIqNRrl4V1xt7PUy1pKlqTEB8A9p9Ic3AkIiIi1U+pvqlcKKk/X1BQEEFBQZcckIiIVB7rdneV2TwPzjbQq+pb3qVat7pz14x9RdOMvYiIyKUrcyegbdu2sX37dtvP3333HTfddBNPPPEEOTk55RqciIhULFtiX8kz9tYt72KreGJ/7hp7qVhNChP76FPp5BQ2dRQREZHSKXNif88997Bv3z4ADh06xMiRI/Hy8uKrr75i+vTp5R6giIhUHOt2d5Xd8b1eNZmxP5vYa8a+ooWbPfBxdyGvwCAmMd3R4YiIiFQrZf4mt2/fPq6++moAvvrqK66//no+++wz5s2bxzfffFPe8YmISAUxDMO2xr7SZ+wLt7w7mlzVE3tr8zzN2Fc0k8lE48J19irHFxERKZsyJ/aGYVBQYCmRW7FiBYMGDQIgIiKCU6dOlelcv//+O0OGDCE8PByTycTixYttz+Xm5vLoo4/SunVrvL29CQ8PZ9y4cRw/ftzuHD179sRkMtk9Ro4caTcmOTmZsWPHYjabMZvNjB07ltOnT5f1rYuIXFFy8w0KDMufPSp5jb11xv5EarZtOUBVdDjRcuMh2M/dwZHUDE2Crevs1UBPRESkLMqc2Hfs2JEXX3yRTz/9lN9++83WWC86OpqQkJAynSs9PZ22bdvyzjvvFHkuIyODbdu28fTTT7Nt2zYWLVrEvn37GDp0aJGxkyZNIi4uzvZ4//337Z4fPXo0UVFRLFu2jGXLlhEVFcXYsWPLFKuIyJUm85yE2sOlchN7fy9XfNwts+CxyVVzyzvDMNgUkwRAx/pVt3P/lcQ2Yx+vGXsREZGyKHNt4axZsxgzZgyLFy/mySefpFGjRgB8/fXXdOvWrUznGjhwIAMHDiz2ObPZzPLly+2Ovf3223Tu3JkjR45Qr14923EvLy9CQ0OLPc/u3btZtmwZGzZsoEuXLgB88MEHdO3alb1799K0adMyxSwicqWwzpQ7O5lwdTZV6rVNJhMRAV7sjkvlaFIGjYJ9KvX6pXEkKYOTZ7Jxc3aiTV2zo8OpEawN9PYlKLEXEREpi1In9vv27aNJkya0adPGriu+1euvv46zc8XO+KSkpGAymfD397c7vmDBAubPn09ISAgDBw7k2WefxdfX8uVg/fr1mM1mW1IPcM0112A2m1m3bl2JiX12djbZ2dm2n1NTU8v/DYmIOJC1cZ6nqzMmU+Um9gARtTzZHZdaZRvobYq2zNa3qWvGo5J7ENRU1sT+cGIG2Xn5uFdyJYmIiEh1VepS/Hbt2tG8eXMeffRR1q9fX+R5Dw8PXF0rrmtwVlYWjz32GKNHj8bPz892fMyYMXz++eesXr2ap59+mm+++Ybhw4fbno+Pjyc4OLjI+YKDg4mPjy/xejNmzLCtyTebzURERJTvGxIRcbCsPGtHfMckT9Z19keraGK/JSYZgI6RKsOvLCF+7vh6uJBfYHDopDrji4iIlFapE/vExERee+01EhMTufnmmwkJCWHixIksWbKErKysioyR3NxcRo4cSUFBAe+++67dc5MmTaJPnz60atWKkSNH8vXXX7NixQq2bdtmG1PcTJRhGBecoXr88cdJSUmxPY4ePVp+b0hEpApw1FZ3VvUCq/aWd5sL19d3iqzl4EhqDpPJRFNrOb4644uIiJRaqb/NeXh4MGTIED788EPi4uL49ttvqV27No899hiBgYEMGzaMuXPnkpCQUK4B5ubmMmLECKKjo1m+fLndbH1x2rdvj6urK/v37wcgNDSUEydOFBl38uTJCzb7c3d3x8/Pz+4hInIlcdRWd1Znt7yres3zTqVlc+iUZcZYjfMqV6s6ln4GGw4lOTgSERGR6uOSpmlMJhPdunXjlVdeYdeuXURFRXH99dczb948IiIi+N///lcuwVmT+v3797NixQoCAwMv+pqdO3eSm5tLWFgYAF27diUlJYVNmzbZxmzcuJGUlJQyN/sTEbmSWJvneVbyVndWEeeU4huG4ZAYSmItw28a4ovZq+KWmUlRPZvWBmDVnoQq93shIiJSVZW5K35xGjduzLRp05g2bRqJiYkkJZXuLntaWhoHDhyw/RwdHU1UVBQBAQGEh4dz6623sm3bNpYuXUp+fr5tTXxAQABubm4cPHiQBQsWMGjQIIKCgti1axfTpk2jXbt2dO/eHYDmzZszYMAAJk2aZNsGb/LkyQwePFgd8UWkRsvKLQAct8a+bi1PANKy8zidkUstbzeHxFEcaxl+R5XhV7prGgbi6epMfGoWu+JSaRmuHQlEREQuptQz9osWLWLcuHEsW7aM9u3b88033xQ7LjAwkMaNG5fqnFu2bKFdu3a0a9cOgIcffph27drxzDPPEBsby5IlS4iNjeXqq68mLCzM9li3bh0Abm5u/Prrr/Tv35+mTZvy0EMP0a9fP1asWGHXoX/BggW0bt2afv360a9fP9q0acOnn35a2rcuInJFOrvG3jGJvYerMyF+7kDVW2dv7YjfuYHK8Cubh6sz3RsFAbByd/ku7xMREblSlXrG/t1332Xr1q2MHTuWV155hUceeYRbbrnlsi7es2fPC5bZXawELyIigt9+++2i1wkICGD+/Plljk9E5Ep2do29Y5rngWWd/YnUbI4mZ9A2wt9hcZzrQEIa24+l4GSCrg0vvgRMyl/v5sGs2H2CX/ck8GBvy2RBQYGBk1Plb8soIiJSHZQ6sXdycqJly5b07dsXgFq1VJ4oIlKdZTm4eR5Ytrzbcji5Ss3Yf7nFsgvKDc2CCfbzcHA0NVOvppZtav+KPc3mmCSe+W4nhmHw5T+64uehngciIiLnK/U0TVBQEJ988ont5/z8/AoJSEREKoejm+eBfQO9qiAnr4BvtsYCMLJTPQdHU3OFmj1oGe6HYcCI99ezOy6VPfFn+O+K/Y4OTUREpEoqdWL/4Ycf0rBhQwBycnKYOXNmhQUlIiIVz1qK7+5SFRL7qrHl3fJdJ0hMzyHEz93WnV0co3czy6y9YUDD2t4AzFsXw4EE7W8vIiJyvlIn9l5eXrY/u7m50alTpwoJSEREKkdmjqUrviNn7OsVJvZVpRR/4eYjANzWIQIXZ8f1HhAY3r4uIX7u3NqhLj8+dB19mgeTV2Dw3JJd2gZPRETkPGXe7i4rK4u3336bVatWkZCQQEFBgd3z27ZtK7fgRESk4mRWgTX2EQGWLe+On84kL7/Aocn0sh1xrD1wCoARHSMcFodYRAZ5s/GJPrafnx7cgt/3n2LtgVOs2X+K65uookJERMSqzIn9XXfdxfLly7n11lvp3LkzJpM61IqIVEfZVSCxD/H1wN3Fiey8Ao6dzqR+oHelx2AYBu/9dohXl+0B4OZ2dagX6HWRV0llqx/ozeA2YSzadoxtR5KV2IuIiJyjzIn9Dz/8wI8//kj37t0rIh4REakk1hl7Dwdud+fkZCIy0Ju9J84QfSrdIYn9V1tjbUn9+K71eXpwi0qPQUqnSYgvANGn0h0ciYiISNVS5m9zderUwdfXtyJiERGRSnQ2sXfcjD1AgyBLMu+oZO3nHfEATL6+Ic8Pa6W19VVYZKBjf1dERESqqjJ/e3nzzTd59NFHOXz4cEXEIyIilSQzx/Hb3QE0qO24ZK2gwGDL4WQABrcJq/TrS9k0POd3RQ30REREzipzKX7Hjh3JysqiYcOGeHl54erqavd8UlJSuQUnIiIVJyuvsCt+DZ6x35+QRkpmLl5uzrQI86v060vZ1AvwwmSCM1l5JKbnEOTj7uiQREREqoQyJ/ajRo3i2LFjvPzyy4SEhKh5nohINZWVo1L8TTGWm9Ht69VSCX414OHqTB1/T2KTM4k+la7EXkREpFCZE/t169axfv162rZtWxHxiIhIJalqa+yPnc4kKze/UuPZUpjYd4ysVWnXlMvTIMjblth3igxwdDgiIiJVQpmnJ5o1a0ZmZmZFxCIiIpWoKuxjDxDo7YavhwuGAUeSMir12ltiLOvrlSBWH45utigiIlIVlTmxf+WVV5g2bRqrV68mMTGR1NRUu4eIiFQPWblVo3meyWRySLJ27HQmx05n4uxkol09/0q7rlwe2+/KSSX2IiIiVmUuxR8wYAAAvXv3tjtuGAYmk4n8/PzyiUxERCpUVhXYx96qQZA3f8emVGpiby3DbxXuh5dbmf85FAfRjL2IiEhRZf4ms2rVqoqIQ0REKlFufgG5+Zbtwhxdig+OmYXdFG1dX68y/OrE+rsSk5hOQYGBk5Oa+IqIiJQ5se/Ro0dFxCEiIpXIOlsPjm+eB5U/C2sYBusOJgLQSY3zqpU6/p64OpvIzisgLjWLOv6ejg5JRETE4UpVf3nkyJEynfTYsWOXFIyIiFSOrFzLHvYmE7i7VI1SfIDoxMpJ7LceTib6VDqers50axRUKdeU8uHi7ES9AC9A6+xFRESsSvVtrlOnTkyaNIlNmzaVOCYlJYUPPviAVq1asWjRonILUEREyp9tfb2LMyaT40uZIwsT+5NnsjmTlVvh1/t801EAbmwThp+Ha4VfT8pXgyAfoPJuBImIiFR1pSrF3717Ny+//DIDBgzA1dWVjh07Eh4ejoeHB8nJyezatYudO3fSsWNHXn/9dQYOHFjRcYuIyGXIrCId8a38PFwJ8nHnVFo2MacyaF3XXGHXSsnM5YftxwEY1Tmiwq4jFadBkGbsRUREzlWqGfuAgADeeOMNjh8/zuzZs2nSpAmnTp1i//79AIwZM4atW7fyxx9/KKkXEakGMnOqxh7252pYOGt/4OSZCr3OkqhjZOUW0DjYh/b1tL6+OrLO2B88mebgSERERKqGMjXP8/DwYPjw4QwfPryi4hERkUpgLcV3rwJb3Vm1rmtmU0wSWw8nc3O7uhV2nYWbLWX4IzvXqxLLEKTsmoX5ArArLtXBkYiIiFQNVecbnYiIVBpbKX4VmrG3dqffEpNcYddYu/8UO4+n4ubsxPB2dSrsOlKxWoT54exk4uSZbE6kZjk6HBEREYdTYi8iUgNlVcHEvkN9y37ye0+cISWj/Bvo5eYX8Nz3OwHL2vpa3m7lfg2pHB6uzjSqbSnH33EsxcHRiIiIOJ4SexGRGqiqNc8DqO3rTsMgbwwDth5JKvfzf7wuhgMJaQR4u/Fw36blfn6pXC3r+AGw45jK8UVERJTYi4jUQNZ97N1dqk5iD9CxsBx/czmX4yecyeI/KywNX//VvylmL21xV921rmPZOWG7ZuxFRESU2IuI1ES2rvhVaMYeoGOkpRx/c3T5zdgfTkxn1P9t4Ex2Hm3qmhnRUVvcXQlaFSb2O48rsRcREbmkxP7TTz+le/fuhIeHc/jwYQBmzZrFd999V67BiYhIxTjbPK9q3d/tXJjY/x2bYusDcDm2Hk7ipv/9wcGT6YSZPXhrRFucndQJ/0rQIswPkwniUrI4lZbt6HBEREQcqszf6GbPns3DDz/MoEGDOH36NPn5li9e/v7+zJo1q7zjExGRClAVm+cB1A/0IsjHnZz8Av6OvbyZ2DNZudzz6TaSM3JpU9fMd/d3p1GwbzlFKo7m7e5CwyBvQA30REREypzYv/3223zwwQc8+eSTODuf/ULYsWNHtm/fXq7BiYhIxbAm9h5VLLE3mUx0bmBdZ3955fj/WbGfU2nZNAzy5ovJXQn28yiPEKUKOVuOrwZ6IiJSs5U5sY+OjqZdu3ZFjru7u5Oenl4uQYmISMXKrKKJPUCnwnL81XsTLvkcBxLOMG9dDADPDGlR5XoJSPloFW5J7DVjLyIiNV2ZE/sGDRoQFRVV5PhPP/1EixYtyiMmERGpYJk5lq74VTHhHdgqDCeTpTP+wZNpZX69YRg8t2QXeQUGfZqH0LNpcAVEKVVBK3XGFxERAS4hsf/Xv/7F/fffzxdffIFhGGzatImXXnqJJ554gn/9618VEaOIiJSzqrrGHiDU7MENzSzJ+Bebj5b59duOJLP2wCncnJ14ZrBuOF/JWtaxNNCLTc7kRGqWo8MRERFxmDIn9nfeeSfPPvss06dPJyMjg9GjR/Pee+/xn//8h5EjR1ZEjCIiUs7OrrGvWl3xrW7vVA+Ab7bGkpNXUKbXfr7JcjNgSNtw6gV6lXtsUnX4ebjSpq4/cHlLN0RERKq7S/pGN2nSJA4fPkxCQgLx8fEcPXqUiRMnlndsIiJSQaryGnuAXk1rE+zrTmJ6Dst3nSj161Kzcvnh7zgARnXWfvU1wQ2FSy1+3a3EXkREaq7LmqoJCgoiOFhrF0VEqpvMKlyKD+Di7MRtHesCsGDjYQzDKNXrlkQdJzM3n0bBPnSoX6siQ5Qqondzy/eQtQdOkZ2X7+BoREREHMOlrC9o164dJpOpyHGTyYSHhweNGjViwoQJ9OrVq1wCFBGR8peZU5jYV8HmeVa3d6zH7NUHWXcwkalfRPHqLW0uWmGwcPMRAEZ2iij23yq58rQM9yPEz50TqdlsPJTE9U1qOzokERGRSlfmxH7AgAHMnj2b1q1b07lzZwzDYMuWLfz9999MmDCBXbt20adPHxYtWsSwYcMqImYREblM2YXr1qtqKT5AvUAvXhnehie+3c53UcfZG3+GxiG+JY7PzStgx7FU3JydGN6+biVGKo5kMpno1TSYhZuPsnJPghJ7ERGpkcpcin/q1CmmTZvGmjVrePPNN3nrrbf4/fffeeSRR0hPT+eXX37hqaee4oUXXrjouX7//XeGDBlCeHg4JpOJxYsX2z1vGAbPPfcc4eHheHp60rNnT3bu3Gk3Jjs7mwcffJCgoCC8vb0ZOnQosbGxdmOSk5MZO3YsZrMZs9nM2LFjOX36dFnfuojIFcM2Y1+FE3uAEZ0i+Piuzvh5uLAn/gzf/3W8xMeynfEADGgVSoC3m4Mjl8pk3UVh5Z6EUi/bEBERuZKUecb+yy+/ZOvWrUWOjxw5kg4dOvDBBx8watQo3nrrrYueKz09nbZt23LnnXdyyy23FHn+tdde46233mLevHk0adKEF198kb59+7J37158fS2zNlOnTuX7779n4cKFBAYGMm3aNAYPHszWrVtxdrZ8YR09ejSxsbEsW7YMgMmTJzN27Fi+//77sr59EZErQkZOHlC1S/GtujcK4qep17Ny9wnyCi6ctLk6O3Fj67BKikyqiu6NgnBzduJIUgYHT6bTKNjH0SGJiIhUqjIn9h4eHqxbt45GjRrZHV+3bh0eHh4AFBQU4O7uftFzDRw4kIEDBxb7nGEYzJo1iyeffJLhw4cD8PHHHxMSEsJnn33GPffcQ0pKCnPmzOHTTz+lT58+AMyfP5+IiAhWrFhB//792b17N8uWLWPDhg106dIFgA8++ICuXbuyd+9emjZtWtaPQESk2qvqzfPOV8ffk7FdIx0dhlRR3u4udGkYwJr9p1i9N0GJvYiI1DhlLsV/8MEH+cc//sGUKVOYP38+CxYsYMqUKdx777089NBDAPz888+0a9fusgKLjo4mPj6efv362Y65u7vTo0cP1q1bB8DWrVvJzc21GxMeHk6rVq1sY9avX4/ZbLYl9QDXXHMNZrPZNqY42dnZpKam2j1ERK4EufkF5OZbZr69qsGMvUhpXN/YsrZ+7YFTDo5ERESk8pV5xv6pp56iQYMGvPPOO3z66acANG3alA8++IDRo0cD8I9//IN77733sgKLj7eslQwJCbE7HhISwuHDh21j3NzcqFWrVpEx1tfHx8cXuyVfcHCwbUxxZsyYwfPPP39Z70FEpCqyztZD9SjFFymNaxsHAbDxUBLZefm4u+h3W0REao4yzdjn5eXx/PPPc/3117N+/XqSkpJISkpi/fr1tqQewNPT01aWf7nO367IMIyLbmF0/pjixl/sPI8//jgpKSm2x9GjR8sYuYhI1WRtnOdkAjfnMhduiVRJzUJ9CfJxIzM3nz+PnHZ0OCIiIpWqTN/oXFxceP3118nPz7/44MsUGhoKUGRWPSEhwTaLHxoaSk5ODsnJyRccc+LEiSLnP3nyZJFqgHO5u7vj5+dn9xARuRJYE3svNxft9S5XDJPJRPdGlln7tftVji8iIjVLmadq+vTpw+rVqysgFHsNGjQgNDSU5cuX247l5OTw22+/0a1bNwA6dOiAq6ur3Zi4uDh27NhhG9O1a1dSUlLYtGmTbczGjRtJSUmxjRERqUkyrFvdqQxfrjDXFib2a7TOXkREapgyr7EfOHAgjz/+ODt27KBDhw54e3vbPT906NBSnystLY0DBw7Yfo6OjiYqKoqAgADq1avH1KlTefnll2ncuDGNGzfm5ZdfxsvLy1b2bzabmThxItOmTSMwMJCAgAAeeeQRWrdubeuS37x5cwYMGMCkSZN4//33Act2d4MHD1ZHfBGpkTJzC7e6qyYd8UVKy7rOfnvsaVIycjF7uTo4IhERkcpR5sTe2hSvuH3qTSZTmcr0t2zZQq9evWw/P/zwwwCMHz+eefPmMX36dDIzM7nvvvtITk6mS5cu/PLLL7Y97AFmzpyJi4sLI0aMIDMzk969ezNv3jzbHvYACxYs4KGHHrJ1zx86dCjvvPNO2d64iMgVIsNWiq/EXq4sYWZPrqrtzcGT6aw/dIoBrcIcHZKIiEilMBmGYTg6iOogNTUVs9lMSkqK1tuLSLX2y854Jn+6lXb1/Pn2vu6ODkekXD23ZCfz1sUwqnM9Zgxv7ehwRERELktp81C1QxYRqWGs292pFF+uRDc0s2xx+8Pfx22NIkVERK50ZS7FB0hPT+e3337jyJEj5OTk2D330EMPlUtgIiJSMVSKL1eyaxsFUbeWJ7HJmSz9+zi3dYxwdEgiIiIVrsyJ/Z9//smgQYPIyMggPT2dgIAATp06hZeXF8HBwUrsRUSquExbV/xLurcrUqU5OZkY3aUery3by/yNR5TYi4hIjVDmUvx//vOfDBkyhKSkJDw9PdmwYQOHDx+mQ4cOvPHGGxURo4iIlKOzpfhajSVXphEdI3B1NvHX0dPsOJbi6HBEREQqXJm/1UVFRTFt2jScnZ1xdnYmOzubiIgIXnvtNZ544omKiFFERMpRRo5luzsvzdjLFSrIx93WEX/BxiMOjkZERKTilTmxd3V1xWQyARASEsKRI5Z/MM1ms+3PIiJSdWXmFADgqTX2cgUb06UeAN/+Gcuhk2kOjkZERKRilTmxb9euHVu2bAGgV69ePPPMMyxYsICpU6fSurW2lRERqeoycy0z9uqKL1eyLg0C6NowkKzcAh747E+yctUhX0RErlxlTuxffvllwsIs5W0vvPACgYGB3HvvvSQkJPB///d/5R6giIiUL3XFl5rAZDIxa+TVBHi7sSsulRk/7nZ0SCIiIhWmzAssO3bsaPtz7dq1+fHHH8s1IBERqVhnu+IrsZcrW4ifB2+OaMudH23m4/WHGdI2nI6RAY4OS0REpNypJbKISA1ztiu+Enu58vVqGsywq8MBWL7rhIOjERERqRhlTuxPnDjB2LFjCQ8Px8XFxdYd3/oQEZGqTaX4UtPc0CwYgDX7Tzk4EhERkYpR5lL8CRMmcOTIEZ5++mnCwsJsHfJFRKR6OFuKr+3upGbodlUQALviUjmVlk2Qj7uDIxIRESlfZf5Wt3btWtasWcPVV19dAeGIiEhFUym+1DS1fd1pFurLnvgzrDuYyNC24Y4OSUREpFyVuRQ/IiICwzAqIhYREakEGTmW7e5Uii81yXWNLbP2a/efdHAkIiIi5a/Mif2sWbN47LHHiImJqYBwRESkoqkrvtRE1zauDcDa/ac0QSEiIlecUpXi16pVy24tfXp6OldddRVeXl64urrajU1KSirfCEVEpFypFF9qos6RAbg5O3E8JYvoU+k0rO3j6JBERETKTakS+1mzZlVwGCIiUhly8wvIzbfMVqoUX2oSTzdnOtSvxfpDiaw9cEqJvYiIXFFKldiPHz++ouMQEZFKYJ2tB5XiS81zbeMg1h9K5Pd9pxjXNbJczpmalcuirbEMu7oOtbzdyuWcIiIiZVXmNfY//vgjP//8c5Hjv/zyCz/99FO5BCUiIhXDur7eyQRuzmX+J0CkWuvRxLLOft3BU2Tn5V9kdOm8t/ogz32/iwc+31aqtfsnUrPYG3+mXK4tIiJiVeZvdY899hj5+UX/MSwoKOCxxx4rl6BERKRiZBQm9l5uLna9U0RqgpbhfgT7upORk8/m6ORyOef6Q4kA/HEgke+ijl90/Pi5mxj4n9/ZEqOeRCIiUn7KnNjv37+fFi1aFDnerFkzDhw4UC5BiYhIxVBHfKnJTCaTbdZ+1d6Eyz5fVm4+O46l2H5+8YddpGTkljg+MyefPfFnKDDgme92kl+g7vwiIlI+ypzYm81mDh06VOT4gQMH8Pb2LpegRESkYmTmWvawV0d8qal6NQsGYPVFEvu8/AIeX/Q3TZ76icZP/kjLZ5bx4tJdZJ3Tp+Lv2BRy8w2CfNxpFOzDqbQcXvt5T4nnjElMt/15V1wqn286cpnvRkRExKLMif3QoUOZOnUqBw8etB07cOAA06ZNY+jQoeUanIiIlK+zpfhK7KVmurZxEM5OJg6eTOdIYkaxY/LyC/jnl3/x+aaj5ORZdpJIz8nnw7XRDPrvGrbHWmbpNxeW03eKrMXzQ1sCsPjPYxSUMBN/uDCxd3ayLIN545e9JKfnlOv7ExGRmqnMif3rr7+Ot7c3zZo1o0GDBjRo0IDmzZsTGBjIG2+8URExiohIOVEpvtR0fh6udKxfC4DV+4rO2huGwfSv/+b7v47j6mzif6Pbs+Hx3nwwriPBvu4cOpnO+I82kZGTx9bDlnX6HerXokuDADxcnUjPyefQqfQi5wWIPmW5kTCgVSjNQn05nZHLZ5q1FxGRclCq7e7OZTabWbduHcuXL+evv/7C09OTNm3acP3111dEfCIiUo6s292pFF9qsl7NgtkYncSqPQlFtr1bsTuBRX8ew8XJxNuj2jOgVSgAoWYPOkXWYug7f3AkKYPPNx21JfadIgNwcXaiRZgf246cZsexFBoF+xS5bkxhwt+otg8d6tXi30t38eeR8mniJyIiNdsl7XVkMpno168f//rXv3jggQdo06ZNecclIiIVQKX4ItCrqWWd/doDp4g6etp2vKDA4K3l+wCYdH1DW1Jv5e/lxj09GgIwc/k+UjJz8XR1pkW4HwCt65gB2H5OQ71zRReW4jcI8qZthGXs37HFjxURESmLMif2r776Kl988YXt5xEjRhAYGEidOnX466+/yjU4EREpX2dL8ctcsCVyxWgS4kP/liHk5hvcO38rp9KyAVi2M57dcan4uLsw+bqGxb72lvZ1qe3rTlq2pRFl2wgzrs6Wr1OtLpLYW2fsI4O8aRFmxskECWeyOZGaVa7vT0REap4yJ/bvv/8+ERERACxfvpzly5fz008/MXDgQP71r3+Ve4AiIlJ+zpbiX1LBlsgVwWQy8cZtbWkY5E1cShb3zd/Gqj0JzCycrZ94bQNqebsV+1oPV2fuvraB7eeO9QNsf25d15LY7zqeWqSBXnp2HglnLDcQGgR64+nmTJMQX0Cz9iIicvnK/M0uLi7OltgvXbqUESNG0K9fP6ZPn87mzZvLPUARESk/GTmWWUYvzdhLDefr4cr7Yzvg7ebMppgk7py3mf0JaZg9XZl4XYMLvnbMNfXx87D8N9S5wdnEvlFtHzxcnUjLzrOV3VtZt7qr5eWK2csVOKd0P/Z0eb0tERGpocqc2NeqVYujR48CsGzZMvr06QNYusjm5+df6KUiIuJgmTkFgLriiwA0DvHlk4ldGNwmjKYhvvi6u/DogGb4ebhe8HU+7i58OL4TTw9uwXWNg2zHrQ30ANuWeFaHC7fWiwzyth1rUzjD/3cJpfsiIiKlVeYpm+HDhzN69GgaN25MYmIiAwcOBCAqKopGjRqVe4AiIlJ+MnMtM/bqii9i0aF+LToUbn9XFp0bBNjN1lu1rmNm25HTbD+Wwk3t6tiORxeur28QeDaxb13XH7DcBDAMA5PJVOY4RERE4BIS+5kzZxIZGcnRo0d57bXX8PGxbOcSFxfHfffdV+4BiohI+VFXfJGKVVIDPWvjvPrnJPbNQn1xcTKRmJ7D8ZQs6vh7Vl6gIiJyRSlzYu/q6sojjzxS5PjUqVPLIx4REalAZ7viK7EXqQjnN9BzcrLMwlvX2EcGednGerg60zTUl53HU9kee1qJvYiIXLJSJfZLlixh4MCBuLq6smTJkguOHTp0aLkEJiIi5c/aFV8z9iIV49wGevsT0mgaaul8H33Kssa+wTlr7MGyzn7n8VT+jk1hQKuwSo9XRESuDKVK7G+66Sbi4+MJDg7mpptuKnGcyWRSAz0RkSrMWoqvNfYiFcPF2YluVwWxck8C32yL5YlBzTmTlcupNMtWd5FFEnt/Pt90lL/UGV9ERC5DqbriFxQUEBwcbPtzSQ8l9SIiVdvZUnxtdydSUcZ0qQfAV1uOkpWbb+uQH+jtVqTjvrVx3+aYZM5k5VZuoCIicsUo83Z3IiJSfakUX6Ti9WwaTLjZg+SMXL7/6zgv/rAbgN7Ng4uMbRzsQ8Mgb3LyCli5J6GyQxURkStEmRL7goIC5s6dy+DBg2nVqhWtW7dm6NChfPLJJxiGUVExiohIOcnI0XZ3IhXN2cnEqM6WWftnvtvJrrhUzJ6uTB/QrMhYk8nEwNahAPy0Pb5S4xQRkStHqRN7wzAYOnQod999N8eOHaN169a0bNmSw4cPM2HCBG6++eaKjFNERMqBuuKLVI7bO0Xg7GSyVck8PrAZQT7uxY4dWNg0b9XeBNKz8yotRhERuXKUOrGfN28ev//+O7/++it//vknn3/+OQsXLuSvv/5ixYoVrFy5kk8++aTcA4yMjMRkMhV53H///QBMmDChyHPXXHON3Tmys7N58MEHCQoKwtvbm6FDhxIbG1vusYqIVHUqxRepHMF+HvRrEQJAx/q1GNExosSxLcP9qBfgRXZeAav3nqysEEVE5ApS6sT+888/54knnqBXr15Fnrvhhht47LHHWLBgQbkGB7B582bi4uJsj+XLlwNw22232cYMGDDAbsyPP/5od46pU6fy7bffsnDhQtauXUtaWhqDBw9Wsz8RqVFy8wvIzbcsm1IpvkjFe3pwCyZf35C3R7ez7WdfnHPL8X/cEVdZ4YmIyBWk1In933//zYABA0p8fuDAgfz111/lEtS5ateuTWhoqO2xdOlSrrrqKnr06GEb4+7ubjcmICDA9lxKSgpz5szhzTffpE+fPrRr14758+ezfft2VqxYUe7xiohUVdbZelApvkhlCPf35IlBzQkze1507CBrOf6eBNuSGRERkdIqdWKflJRESEhIic+HhISQnJxcLkGVJCcnh/nz53PXXXdhMp2987169WqCg4Np0qQJkyZNIiHhbFfZrVu3kpubS79+/WzHwsPDadWqFevWrSvxWtnZ2aSmpto9RESqM2uy4Oxkws1Zm6KIVCVt6pqpF+BFRk4+i6OOOTocERGpZkr9zS4/Px8Xl5L3PXZ2diYvr2IbvixevJjTp08zYcIE27GBAweyYMECVq5cyZtvvsnmzZu54YYbyM7OBiA+Ph43Nzdq1apld66QkBDi40vuPjtjxgzMZrPtERFR8to4EZHqIMPaOM/V2e7mqIg4nslkYlzX+gDMXRut3YZERKRMSs7Uz2MYBhMmTMDdvfiOrtZEuiLNmTOHgQMHEh4ebjt2++232/7cqlUrOnbsSP369fnhhx8YPnx4iecyDOOCX2wff/xxHn74YdvPqampSu5FpFpTR3yRqm1EpwhmLt/H/oQ01h44xXWNazs6JBERqSZKndiPHz/+omPGjRt3WcFcyOHDh1mxYgWLFi264LiwsDDq16/P/v37AQgNDSUnJ4fk5GS7WfuEhAS6detW4nnc3d1LvIkhIlIdJWfkAGD2dHVwJCJSHD8PV27rGMG8dTF89EeMEnsRESm1Uif2H330UUXGUarrBwcHc+ONN15wXGJiIkePHiUszNKEpkOHDri6urJ8+XJGjBgBQFxcHDt27OC1116r8LhFRKqKY8mZgKWhl4hUTRO6RfLx+hhW7klg25Fk2terdfEXiYhIjVctuicVFBTw0UcfMX78eLt1/mlpaTzyyCOsX7+emJgYVq9ezZAhQwgKCuLmm28GwGw2M3HiRKZNm8avv/7Kn3/+yR133EHr1q3p06ePo96SiEilO3baktjX8fdwcCQiUpLIIG/6NLc0K75l9joe+Gwbe+LVwFdERC6s1DP2jrRixQqOHDnCXXfdZXfc2dmZ7du388knn3D69GnCwsLo1asXX3zxBb6+vrZxM2fOxMXFhREjRpCZmUnv3r2ZN28ezs5aZyoiNcdxW2KvGXuRquzlm1vj5uzED9vjWPq35dGlQQD39GjIDc1K3qFIRERqLpOhtqulkpqaitlsJiUlBT8/P0eHIyJSZmM+3MAfBxJ5a0Rbhrev6+hwROQidsel8s7KAyzbGU9+geXr2vQBTbmvZyMHRyYiIpWltHlotSjFFxGRy3f8dBagNfYi1UXzMD/+N6Y9ax/tZdsK77Vle5nx025thyciInaU2IuI1AAFBcY5a+yV2ItUJ2FmT/49rBVPDmoOwPu/HeLd1QcdHJWIiFQlSuxFRGqAxPQccvIKMJkgxE/N80Sqo0nXN+Tfw1oC8NbyfWyJSQLAMAzN4IuI1HDVonmeiIhcHmvjvBBfD9xcdE9XpLoae019th1OZnHUcR76/E+GXl2HLzYfIa/A4LYOEYztWp8GQd6ODlNERCqZvt2JiNQA1sQ+XFvdiVRrJpOJF29uTWSgF8dTsnjvt4MkZ+RyJiuPuX9E0+et31j693FHhykiIpVMib2ISA1wzJbYa329SHXn4+7CO6PbExHgSberAnl/bAc+urMT1zYKIr/A4F9f/c2e+FRHhykiIpVIpfgiIjWAGueJXFla1TGzZvoNdseub1ybCR9tYs3+U/zj061898C1mD1dHRShiIhUJs3Yi4jUAMc1Yy9yxXN2MvGfke2o4+9JTGIGj3z1l5rqiYjUEErsRURqAO1hL1IzBHi78d4dHXBzdmL5rhN8vC4GgK2Hk/nfqgNsik6ioEDJvojIlUal+CIiNcBxleKL1Bit65p5fFAznv9+Fy//uIedx1P5elss1sn7ED93Xr2lDT2bBjs2UBERKTeasRcRucJl5uSTmJ4DKLEXqSkmdIukb4sQcvIL+GqrJanv2jAQXw8XTqRm8+g3f5Odl+/oMEVEpJwosRcRucIdT7HM1nu7OePnqUItkZrAZDLx+q1taBzsQ7jZg48mdOLzydew+ck+hPp5cCI1m2+3HXN0mCIiUk6U2IuIXOHObZxnMpkcHI2IVBZ/LzeWTb2ePx67gV7NLGX3Hq7O3H1dAwDe//0Q+VpvLyJyRVBiLyJyhVNHfJGay9nJVOSG3qjO9fD3ciX6VDo/7YhzUGQiIlKelNiLiFzhjqkjvoicw9vdhfFdIwF4d9VBbYknInIFUGIvInKFO3nGktiH+Lk7OBIRqSomdIvE3cWJXXGp7DiWWm7nPZqUQUpGbrmdT0RESkeJvYjIFe7kGUtH/CAfJfYiYlHL240+LUIAWBxVPk30tsQkccObq7n+9VX8eSS5XM4pIiKlo8ReROQKdyotG1BiLyL2br66DgBL/jp+2U300rLzePjLv8jNN0jJzGXMhxtZu/9UeYQpIiKloMReROQKZ03sa/u6OTgSEalKrm9SG38vV06eyWbdwctLwl9cuosjSRnU8ffk2kZBZOTkc9e8zUQdPV0+wYqIyAUpsRcRuYIZhqEZexEplpuLE4PbhAHw7Z+XXo6/Zv9JFm4+iskE/9/enYc3VaZ/A/9madJ0S9uU7qUtLRShQIGyg4CsIgqjKIIK+NOZUZABlXFXUGdEeBUcQcfBEVRQUUcQRBZB9n2r0Jal0NLS0o2m+5KkSZ73j9BIhEJb2mbh+7muXJecPDnnPsnj6bnPs73/UDd8Ni0RwzoGwmAyY+Y3x1Gu45h7IqKWxsSeiMiFVRlM0NWaATCxJ6Jrjb/SHX9LSj5qDKYm7WP1kWwAwKN9ItG3nQZKuQyLH05AhL8K2cU1ePmHZM68T0TUwpjYExG5sKIKS2u9yk0GT6XcztEQkaPpGemHcD8VqgwmbEnNb/Tn9UYTdp4pBAA80DPcut3H3Q1LJvWAXCrBz8l5+OF480zQR0RE18fEnojIhVm74XN8PRFdh0QiwYM9IwAAXx+62OjPH0jXospgQqC3El3D1DbvJUT44tkRHQAAH+84D/MtTtBHRET1Y2JPROTCrBPnsRs+EdVjYq8IyKQSHM4sRlpBRaM++8upAgDAiE5BkEol17w/tX8UvJVyZBRVYVfa5WaJl4iIrsXEnojIhV2u4MR5RHRjwWp3DL8jEEDjWu3NZoFtVyX21+OllGNiL0uPgOX7LtxipEREVB8m9kRELuxypQEAEODNxJ6I6vdo30gAwA/Hc1BtMDboMydySlFYoYeXUo5+MZp6y03tHwWpBNhzrqjRPQKIiKhhmNgTEbkwLnVHRA0xICYAkRoPVOiM+OlE7nXL1JrMNv/elGKZbG9wXBso5bJ69x3h74GRnYIBACvYat+sak1mzN94Gi/+7yQWbj7TpAkQicg1cIpkIiIXVjcrfhsvTp5HRPWTSiV4pE9bvLPxDD789Tzu7RYKD8Xvt4mrD1/Eaz+mIDbQC6Pjg/Fbdil2nrWMmR9ZTzf8qz0+IAqbU/Ox/rdczL23M9zd6n8QQA23OSUf/9mdYbNtw8yBiP/DRIZE5PrYYk9E5MLYYk9EDfVo30iE+apwqbQGH2w7Z92+OSUfr6xNhtEscCa/Ah9sO4edZy9DJpXgsb6RGNs19Kb77hXljxC1O6oMJuw7X9SSp3FbqZu8cGBsALqGW5L5bw43fnUDInJ+TOyJiFxYEcfYE1EDeSjkeHt8ZwDAZ3svYM+5y1h9+CL+tjoJZgE8lBiOhRO6YmSnIEzq3Rbbnx+Mt8fHQ3ad2fD/SCqVYFRnS3f8zSnsLt4cDEYzdp4pBAA8N7IDXhrdEQCw7rfcBs+TQESug13xiYhcGFvsiagx7uoYhLvjg7EpJR+PfXbYun1EpyC886cukMukeCgxokn7Htk5CJ/vz8S20wUwmsyQy9i+dCsOZmhRoTeijbcSCeG+AIBIjQeytNXYcDKvyb8TETknXlGJiFxUtcGIaoMJABDAMfZE1EBz7+0MjacCEgnQJUyNv90ViyWTut9yIt47yh9+Hm4oqa7F4cziZor29vXLKUvPh+F3BEEqlUAqlViT+W+PZNszNCKyA7bYExG5qKIKSzd8pVwKLyUv90TUMMFqd+x6YSjMQsDH3a3Z9iuXSTGiUxC+O5qDLSn56B8T0Gz7vt2YzQLbTlm64V89eeGDPcOxaGsajmWVIK2gAh2CvO0VIhG1MrbYExG5qMtXdcOXSG4+BpaIqI6XUt6sSX2dunH2W1ILYDaLZt//7SL5Uhnyy3XwVMjQL0Zj3R7o445hHQMBAF/sz7RTdERkD0zsiYhclHV8PSfOIyIHMSA2AJ4KGfLLdTiaVWLvcJzWr6cts+EPiQu8ZunAxwdEAwD+dyzH+neAiFwfE3siIhdVd0PHNeyJyFG4u8msy+OtPJhl52ic15FMy0ORge2vHc7Qt50/ukX4Qm80s9We6DbCxJ6IyEXVjbHnjPhE5Ege6xcJANiUnIfCcp2do3E+JrPAiZxSAECPtn7XvC+RSPDUne0AAF8eyEKVnkvfEd0OmNgTEbkoLnVHRI4oPkyNxEg/GM0CXx++aO9wnE5aQQWqDSZ4KeWIDfS6bpmRnYMRHeCJspparOYM+US3BYdO7OfNmweJRGLzCg4Otr4vhMC8efMQGhoKlUqFIUOGIDU11WYfer0eM2fOREBAADw9PXHfffchJyentU+FiKjV/Z7Ysys+ETmWulb7rw9dRK3JbOdonEvSxVIAQLcINWTS60+MKpNK8Jcrrfaf7cngd0x0G3DoxB4AOnfujLy8POsrOTnZ+t7ChQuxaNEiLF26FEeOHEFwcDBGjBiBiooKa5nZs2dj7dq1WL16Nfbu3YvKykqMHTsWJpPJHqdDRNRqOHkeETmqu+NDEOClRGGFHt8dbVqL8rmCCkxadhBLt5+DELfPDPtJFy3j67tHXNsN/2p/6h6GAC8lcst0+OlEbmuERkR25PALG8vlcptW+jpCCHzwwQd49dVXcf/99wMAvvjiCwQFBeHrr7/GX//6V5SVleGzzz7DypUrMXz4cADAqlWrEBERgW3btmHUqFGNjqeqqgre3t7WpaMMBgNqa2shl8uhVCptygGASqWCVGp5flJbWwuDwQCZTAZ3d/cmla2uroYQAu7u7pDJLLOgGo1G6PV6SKVSqFSqJpWtqamB2WyGUqmEXG6pFiaTCTqdrlFlJRIJPDw8rGV1Oh1MJhMUCgXc3NwaXdZsNqOmpgYA4OnpaS2r1+thNBrh5uYGhULR6LJCCFRXVwMAPDw8rvk9G1O2Ib99c9ST6/2ezVFP6n7PW60nf/w9b7We1Pd73mo9ufr3vNV6Ut/v2dR60tzXCG2lZYy9r7sMVVVVvEbwGnFLvz2vEa53jbD3fcRjfcKw+NcMvP5jCmRC4N4ubRp8jThyPh9/WXkM5UYZDmRoUaE3YvaQKJjNZpe/RiRllwIAurf1velv/38Do7Bw81n8Z1cGRsVZHgTwGsFrxI3KOtI1gvcRlrJ6fQNXtxAObO7cucLDw0OEhISIqKgoMXHiRJGeni6EECI9PV0AEMePH7f5zH333SemTJkihBDi119/FQBEcXGxTZmuXbuKN95444bH1ul0oqyszPrKzs4WAAQAUVhYaC33j3/8QwAQTz75pM3nPTw8BABx4cIF67bFixcLAGLy5Mk2ZQMCAgQAkZKSYt22bNkyAUCMGzfOpmxkZKQAIA4fPmzdtmrVKgFADB8+3KZsp06dBACxY8cO67a1a9cKAKJ///42ZRMTEwUAsWHDBuu2X375RQAQ3bp1syk7ePBgAUB899131m179+4VAERsbKxN2TFjxggAYsWKFdZtSUlJAoAIDQ21KTthwgQBQCxdutS6LS0tTQAQarXapuzUqVMFALFw4ULrtpycHAFAyOVym7LTp08XAMTcuXOt20pKSqy/p8FgsG6fM2eOACDmzJlj3WYwGKxlS0pKrNvnzp0rAIjp06fbHE8ulwsAIicnx7pt4cKFAoCYOnWqTVm1Wi0AiLS0NOu2pUuXCgBiwoQJNmVDQ0MFAJGUlGTdtmLFCgFAjBkzxqZsbGysACD27t1r3fbdd98JAGLw4ME2Zbt16yYAiF9++cW6bcOGDQKASExMtCnbv39/AUCsXbvWum3Hjh0CgOjUqZNN2eHDhwsAYtWqVdZthw8fFgBEZGSkTdlx48YJAGLZsmXWbSkpKQKACAgIsCk7efJkAUAsXrzYuu3ChQsCgPDw8LAp++STTwoA4h//+Id1W2FhofX3vNqsWbMEAPHKK69Yt1VWVlrLVlZWWre/8sorAoCYNWuWzT4c7RqR8OYWEfniBvH/ln7Ka4TgNeJqvEZY3O7XiDr2uo9Yvfpb8cL3J0TkixtE0CMLG3yN+GbjLgFAyLz8xaAF20XkixtE5IsbRMd+IwQAMf+9xdayrnaNmPToY9bzLarQ3fQaUVptEJ3f2CwiX9wgNIHBvEYIXiPqOMM1gvcRc62/PQBRVlYmbsShu+L36dMHX375JbZs2YJPP/0U+fn56N+/P7RaLfLz8wEAQUFBNp8JCgqyvpefnw+FQgE/P796y9Rn/vz5UKvV1ldEREQznhkRUcsymwXKamoBAB5K2U1KExG1PqlUgncf6GIdCw4AlQ2Ywb1uwj2FXIqNswZh7r2dAAAXiy0tXou2plnXeXc1JVWWnliRGg9oGjAxqlrlhsl92gIAZ8cncnESIZxnUFJVVRViYmLwwgsvoG/fvhgwYAByc3MREhJiLfPnP/8Z2dnZ2Lx5M77++ms8/vjj13RfGDFiBGJiYvDJJ5/Ueyy9Xm/zufLyckRERCA3NxfBwcHsHsPuMexmyy50Dt2FzgAZur/9KwAgZe5wSMxGXiN4jbil357XCNe6RjjSfYQQAv/ckIplO85CJpPgsycG4K6OQdf9PasNRnSbtxl6nR4bZg5E12hLuY3JeVh3NBOpuSXILq1FdKAPtj43GDIJXOoa8cmuTCzZnYnxCaH44OHuDfrt88t0GLRwO/S6Gix5uDvG9ojkNYLXCKe6Rlxd9na8j6iurkZgYCDKysrg4+OD+jhVYg9YkvLY2Fj8/e9/R0xMDI4fP47u3btb3x83bhx8fX3xxRdfYPv27Rg2bBiKi4ttWu27deuG8ePH480332zwccvLy6FWq2/6hRIROYLs4moMWrgD7m5SnHn7bnuHQ0R0Q2azwJz/ncCa45fg7ibFimm90S9Gc025Lan5+OvKY2jr74Fdfx9ivQGuU6U34s6FO6CtMmD+/V0wqXfb1jqFVjFtxWHsPHsZb97XGVP7RzX4c+9uOoNPdqWjjbcS254dDLWHW8sFSUTNqqF5qEN3xf8jvV6P06dPIyQkBNHR0QgODsbWrVut7xsMBuzatQv9+/cHAPTs2RNubm42ZfLy8pCSkmItQ0TkikqrLd3wfVVc6o6IHJ9UKsGCB7piWMdA6GrNeOKLIzh8ofiacttOWbrYD78j6JqkHgA8lXLMGBoLAPjXtnPQ1TrfKkhGkxllV67hV8sv0+FghhYA0KPtjWfE/6PZw9ujXRtPXK7Q4+2fTzVLnETkWBw6sZ8zZw527dqFCxcu4NChQ5gwYQLKy8sxdepUSCQSzJ49G++88w7Wrl2LlJQUTJs2DR4eHpg8eTIAQK1W44knnsDzzz+PX3/9FUlJSXj00UfRpUsX6yz5RESuqLTGMg5TrWKrDBE5BzeZFB890gOD2geg2mDC4ysO2yT3JrPA9jOFAIDhdwTWu5/JfdoiVO2O/HIdVh3MavG4m1NyThmGvr8TfeZvw4F0rc177/1yFrpaM3pG+iE+rHG9R93dZFj4QFdIJMD/juVgbVJOc4ZNRA7AoRP7nJwcTJo0CXFxcbj//vuhUChw8OBBREZGAgBeeOEFzJ49G9OnT0diYiIuXbqEX375Bd7e3tZ9LF68GOPHj8dDDz2EAQMGwMPDAz/99JN1HAgRkSuqmziP3S2JyJm4u8nw6ZREDIjVoMpgwpTlh7DjrCWZ/y27FNoqA7zd5egV7X/Dfcwe3gEA8NGO86jQXdv67Yi+OXwRD/x7P7KLa6CrNePpr47hQpFlbHTKpTL8cNySjL92zx3X7a1wM4lR/nhyYDQA4LnvTjjdQw8iujGnG2NvLxxjT0TOZNXBLLz2YwpGdgrCsimJ9g6HiKhRdLUmTP/qOLafKYRcKsGMobHILq7GmqRLuLdbKJZM6n7DzxtNZoxcvBsZRVV4dngHzBrevpUib5rzhRUYvmg3AGBEpyAUVuhxIrsU7QI8MW1AFH44fgknsksxLiEU/3r4xud+I2azwNz1qVh5Jal/Y2wn/N+VZJ+IHJNLjrEnIqKGqWux92WLPRE5IXc3Gf7zWE/c1y0URrPAv349hzVJlwDcuBt+HblMiudGWlrtP92TYV0mzlEdzLAMOegd7Y9lj/XEp1N6IlTtjoyiKryxLhUnskuhlEvxwuiOt3QcqVSCt8Z1xoyhMQCAf248jSOZ185lQETOh4k9EZELKq223MT6enDyPCJyTm4yKT6YmIB37++CkZ2CoFa5IVLjgbs63jyxB4Ax8SHoFOKDSr0RS7afhyN3Uk26WAoA6BvtD4lEgkBvd6x6sg8mJkbgni4huKdrCBZPTECYr+rGO2oAiUSCOSPj8KfuYTCZBWZ9k2T9m0FEzktu7wCIiKj5WcfYc/I8InJiUqkED/dui4d7t7Um5g0dXy6VSvD30XF4fMURLN93Aet+u4SB7QPw/Ig4tNV43HwHrSgpuwQA0P2q2e7btfHCggldW+R4EokEb4+Px2/ZpbhQVIU535/Ep1N6NmnsPhE5BrbYExG5oLrl7pjYE5GrkEgkjU48h3RogycGRkPlJoO2yoB1v+XiniV78EtqfoP3IYRArcnc2HAbrLTagIzLlknyEiJ8W+w4f+SllGPJpO5QyKTYdroAn+/PbLVjE1HzY2JPROSCSjnGnogIEokEr4/thBNzR+K7v/ZDj7a+qNAZ8ZeVx/DOxtM3TdiFEHj++xO44/XNeOmHk8gpqW72GH/LLgUARAd4ws+zdYdPxYep8coYy7j9+RvPIOVSWasen4iaDxN7IiIXVHalxd5XxTH2REQKuRS9o/2x+i/98MSVWeCX7c7A5E8PIr9MV+/nlu3OwJrjl2A0C6w+ko2h7+3Eoq1pMJmbb7x+3fj67q3YWn+1qf2jMLJTEAwmM575+rjTLA9IRLaY2BMRuaDSGstESOyKT0T0O4VcitfHdsK/H+kBb6UcRzJLcPe/dmNjct41ZfefL8KCzWcAAH8d3A4DYwNQaxL48NdzmLL8EIoq9c0SU9KVFvuEtr7Nsr/GkkgkWDihK0LV7sjUVmP6V8dhMLbc0AMiahlM7ImIXBCXuyMiqt/dXULw08yB6BTig5LqWkz/6jhmfH0cO88WIre0Bu//chZPfnkUZgFM6BmOl0Z3xKon++BfDydA5SbDvvNajPnXHhy+cGtLxZnNAr9dvDJxXoTfTUq3HF8PBT55rCc8FDLsOVeEOd+fgLkZeyUQUctjYk9E5GJ0tSboai2tLWom9kRE1xUV4IkfZwzAzLtiIZNK8PPJPExbcQT9392OJdvPo9pgQp9of/xjfLx10r5xCWFY/8wAxAZ6obBCj0mfHsS/d6ZDbzQ1KYYL2iqU64xQyqXoGOLdnKfXaF3DffHvR3tCLpVg/Ylc/GXlUaQVVNg1JiJqOCb2REQupq61XiaVwFvJVU2JiOqjkEvx/Mg4/Dh9AB7sGY5wP8s68R2DvfHJoz2x+i994e4ms/lM+yBvrJsxAOMTQmEyCyzYfAYD3t2O93852+j14I9nWVrru4ar4Saz/2354A5t8P5D3SCVANtOF2LUB7vx15VHsTE5D8VVBiTnlGFzSh4Ky+ufl4CI7IN3fERELubqpe64JjER0c11CVfj/z3YDQBQrquFt1J+w+unp1KOxRMT0LedBh9sO4f8ch2WbD+PH47l4KNHetisR18fIQS+PZINAOgV5d88J9IMxiWEoWOwD/71axo2JudjS2oBtqQW2JTxVMjwt2Ht8fiAaCjk9n8gQURssScicjl1LfacOI+IqPF83Bv2UFQikeDh3m2x58Wh+PiRHogO8ERumQ4P/ecAlvx67qat97vPFeFoVgmUcimm9o9qpuibR1ywNz5+pCe2zL4Tfx3cztqTQeOpQJTGA1UGE+ZvOoOxS/bgfCG76xM5AokQgjNjNEB5eTnUajXKysrg4+Nj73CIiOr1S2o+/rLyGBIifPHjjAH2DoeI6LZQoavFSz8k4+crM+y7u0kxslMwwv1UCPBSIrqNJ+KCvBGidgcAjP9oH07klOGJgdF4fWwne4Z+U0IIVOqN8HZ3g9kssCbpEt7ddBpFlQZ4KGSYf38XjEsIs3eYRC6poXkou+ITEbmYUs6IT0TU6rzd3bB0cncMSwrEst0ZOJNfgfUncq8pF+arQo9IP5zIKYPKTYanh8TYIdrGkUgk8Ha3/E2RSiWY0DMcgzu0wazVSdifrsWs1b/hSGYxXh/bCUq57CZ7I6KWwMSeiMjFlF0ZY+/LrvhERK1KIpHg/h7h+FP3MBzJLMGhDC20VQYUVuhwvrASGZercKm0BpdKawAA0wZEIcBLaeeom6aNtxIrn+iDD7alYcn281h18CJOZJdhwQNd0SnUB0IIHL9YiixtFe7tFuoQkwMSuTIm9kRELqa0xjKu09dDYedIiIhuTxKJBL2j/dE72nZSPF2tCTvPFmLDyTzoak146k7Hb62/EZlUgudHxqFnpB+e/fY3JF8qw5gP96B3lD+qa41IuVQOAPjq0EUsndwdIWrVdfdjNJkhZ+JPdEv4fxARkYupmzzPhy32REQOxd1NhtHxIVg6uQf+O7UX1C4yZGpIXCA2/G0Q7ukaAplUgsOZxUi5VA6FXApPhQzHskpwz4d7cShDe81nVx7IRKe5WzDj6+MormrccoFE9Du22BMRuZhSdsUnIqJWFuarwkeTeyC/TIe1SZfgJrMMS6jQ1WL6V8eRmluOaSuO4PPHe6FPOw0AYP2JXLyxPhVCAD+fzMOhDC2eHhKLTiE+uCPEmz3PiBqBiT0RkYsp4+R5RERkJ8Fqd5sJAf09Ffjh6f74y8pj2J12GY9/fgRzRsahXFeLj3achxDA+IRQnMorR1pBJd7ecMr62Y7B3ugXo0G/dhr0idagXFeLA+lanC2ogLZSj3KdET7ucvh5KlBUaUBafgVUChlmD2+PIXGB9jh9IrvhcncNxOXuiMhZ3LtkL5IvlWH5tETc1THI3uEQERFBV2vCk18cxd7zRTbb7+kagiUPd4fBZMYX+zNxJLMYZwsqkF1cc0vHG35HEB5MDEffaI3LDHmg2xOXuyMiuk3Vtdir2RWfiIgchLubDJ9OScTCLWeQfrkKAV4KdAz2xtT+UZBKJXCXyvDXwTH462BLa39RpR6HMopxIKMIB9K1SL9cBblUgoQIXyRE+CLQRwkfdzeU62qhrTLAz0OB9oFeOJihxYp9mdh2ugDbThdAIgE6hfigf4wG/WI06BXlb126j8iVsMW+gdhiT0TOouu8LSjXGbHtucGIDfSydzhERES3rLjKAHc3KTwUN2+XPFdQgS8OZGJ/uhYZl6ts3pNJJegU4oNQX3dovJRo6++BuCBvJET4ws+TY/rJ8bDFnojoNmQyC5TrjAA4xp6IiFyHfyOS7vZB3vjH+C4AgIJyHQ5maHEgXYsDGVpkaauRfKkMyZfKbD7j4y7HnhfvYm83clpM7ImIXEj5lW74ALviExERBfm4Y1xCGMYlhAEAcktrcCK7FEWVelyuNCDjciV2pV1Guc6IfeeLMKZLiJ0jJmoaJvZERC6k9Epi76WUw00mtXM0REREjiXUV4VQX5XNtnnrU/H5/kzsZWJPTox3fURELiSzyDKWMFjtbudIiIiInMOg9gEAgL3nim5SkshxMbEnInIhqbmWMYOdQznJJxERUUP0aaeBXCrBxeJqXNRW2zscoiZhYk9E5EJSLpUDAOJD1XaOhIiIyDl4KeXo3tYXALDn/GX7BkPUREzsiYhcSGoeW+yJiIgaa2BsGwDAvvPsjk/OiYk9EZGLKKuuRXZxDQCgM1vsiYiIGmzglXH2+85rYTILO0dD1HhM7ImIXERda324nwpqrmFPRETUYN3C1fBWylFWU4uUP6xxT+QMmNgTEbmIU7kcX09ERNQUcpkUfWM0AIC97I5PToiJPRGRi6hrYeD4eiIiosbjsnfkzJjYExG5iNS6FvswttgTERE11oBYS2J/LKsENQaTnaMhahwm9kRELqDGYEL65UoAQOcwttgTERE1VrsAT4Sq3WEwmXE4s9je4RA1ChN7IiIXcDq/HGYBtPFWItDb3d7hEBEROR2JRGKdHX/vOa5nT86FiT0RkQtIzrGMr4/n+HoiIqImq+uOv4fj7MnJMLEnInIBa5MuAQB6RfvbORIiIiLnVZfYn8mvwOUKvZ2jIWo4h07s58+fj169esHb2xuBgYEYP348zp49a1Nm2rRpkEgkNq++ffvalNHr9Zg5cyYCAgLg6emJ++67Dzk5Oa15KkRELeZEdil+yy6FQibFQ4kR9g6HiIjIaQV4KdEpxNL7bX86W+3JeTh0Yr9r1y7MmDEDBw8exNatW2E0GjFy5EhUVVXZlBs9ejTy8vKsr40bN9q8P3v2bKxduxarV6/G3r17UVlZibFjx8Jk4myXROT8vjyQBQC4p2sIAryUdo6GiIjIudWNs9+UnA8hhJ2jIWoYub0DuJHNmzfb/HvFihUIDAzEsWPHcOedd1q3K5VKBAcHX3cfZWVl+Oyzz7By5UoMHz4cALBq1SpERERg27ZtGDVqVMudABFRCyuuMuCnk7kAgCn9Iu0cDRERkfMb1TkIy3ZnYHNqPuauT8UbYzvh+MVSHMsqgVkIyKQSDL8jCLGBXvYOlcjKoRP7Pyors0wO5e9vO4Z0586dCAwMhK+vLwYPHox//vOfCAwMBAAcO3YMtbW1GDlypLV8aGgo4uPjsX///noTe71eD73+93E15eXlzX06RES37Nsj2TAYzegSpkZChK+9wyEiInJ6PSP98fb4eLyxLgVfHsjCmuOXUKk32pRZ9Esanh3RAX+5sx1kUomdIiX6nUN3xb+aEALPPfccBg4ciPj4eOv2u+++G1999RW2b9+O999/H0eOHMFdd91lTcrz8/OhUCjg5+dns7+goCDk5+fXe7z58+dDrVZbXxERHLdKRI6lSm/E8n0XAACP9YuERMIbCyIioubwWN9IfDAxAXKpBJV6I7zd5binawgmJkagXzsNDCYzFmw+g4n/OcBJ9sghOE2L/TPPPIOTJ09i7969NtsnTpxo/e/4+HgkJiYiMjISP//8M+6///569yeEuOFN8Msvv4znnnvO+u/y8nIm90TkUP6zKx2XK/SI1HhgXEKovcMhIiJyKeMSwhDTxguXK/XoH6OBUi4DYMkjfjh+CW+uT8XRrBKM/2gfPpuWiI7BXHKW7McpEvuZM2di/fr12L17N8LDw29YNiQkBJGRkTh37hwAIDg4GAaDASUlJTat9oWFhejfv3+9+1EqlVAqOQkVEbWcsupaLN6WhnOFFQAAL6UcwzoGYVTnYKg93G742byyGizbkwEAePnujtabDSIiImo+8WHqa7ZJJBJM6BmOnpF++L/Pj+BCURUm/PsAXry7Iyb3bmvXrvmVeiNySqqhrTSgvKYWPio3aLwUiNJ4wt2N9wquzKETeyEEZs6cibVr12Lnzp2Ijo6+6We0Wi2ys7MREhICAOjZsyfc3NywdetWPPTQQwCAvLw8pKSkYOHChS0aPxFRfXacKcSLP5xE4R+6721JLcCrPybjocQIzBkZBz9PxXU///+2nIWu1ozeUf4Y1fn6k4cSERFRy4kO8MTa6f3x1KpjOJhRjNd/TME3hy7i76PiMLhDG0hbIcGv1Bvx6+kCbErOR/KlMlwqrbluOS+lHCM6BeFP3cMwqH0Ah++5IIlw4DUcpk+fjq+//hrr1q1DXFycdbtarYZKpUJlZSXmzZuHBx54ACEhIcjMzMQrr7yCixcv4vTp0/D29gYAPP3009iwYQM+//xz+Pv7Y86cOdBqtTh27BhksoY9uSovL4darUZZWRl8fNjNhoia7odjOXj++xMAgHYBnnhqSAyUcikuaqvxc3IezuRbWvB9Pdzwt7va46FeEfBSWp7DGoxmvLvpjHVs/fpnBqBruK9dzoOIiIgAo8mMrw9fxHtbzqJcZ5lkL1Ljgcf6RuLBxAioVTfuhdcUKZfK8MX+TKw/kQu90Wzznp+HGwK8lPBRuaFCV4v8Mp01LgAY1D4A8+7rjJg2nNXfGTQ0D3XoxL6+J0krVqzAtGnTUFNTg/HjxyMpKQmlpaUICQnB0KFD8fbbb9uMh9fpdPj73/+Or7/+GjU1NRg2bBg+/vjjRo2ZZ2JvPwajGafyypGWX4FzhRUoKNdDW6VHrUkgwEsBXw8FZFfqipe7HBpPBQK8lPD3VEDjZflvPw8FFHKnmSuSXNj5wgrcu2QfampNmNS7Ld4Y2wkqhe0DxoMZWsxdl4qzBb930R/ZOQieCjlO5JTiZI5lhZBnh3fArOHtW/0ciIiI6FraSj3+vTMd3x7NRsWVRFrlJsOfeoRhar8oxAV73/IxDl8oxuKtaTiQobVuiw7wxNiuIRgYG4C4YG/4etj29jObBZKyS7Dut1ysPpwNg8kMuVSCGUNj8cxdsXCT8R7ZkblEYu9IXDWxv9kkgvZgNJmRfKkMBzK0OJCuxdHMEtTUmm55v2G+KrQP8kKHIG90CPJGx2DLS86LmUsr19Ui43IViir0KK42oNZkeaqtkEmh8VKgjZc7ott4WlvEW5Ku1oTxH+3DmfwKDIjV4Mv/61PvODyjyYzVR7KxfN8FZFyusnnPx12O9x9KwIhOQS0eMxERETVOtcGItUmX8OX+LOtDegDo284f0/pHYfgdQY2+/zyWVYIPtqVhz7kiAIBcKsGYLiGY2j8SPdr6Nfh+PrOoCm9tOIXtZwoBAPFhPnj/wYRmeehALYOJfTNzhcTeZBY4fKEYG07m4khmMYoqDSitNsBDIYfGS4FQtQodgrzQPsgbccHe6BDofdMJvJpLrcmMfeeL8PPJPGxJzbfpLgRYuhR1CvVB+0BvhPupoPFSQCaVoqTKgJJqA4QABIDymloUVxmgrdJDW2mAtsqA4ioDTObrV3NvpRy9o/3RL0aDvu006BTi0yrjoahl5JbW4NAFLU7lluNsQSXOFVQgr0zXoM+G+Vrqf92Dnw5B3ogN9LqmNb2pjCYznv/+BNb9lguNpwKbZg1CoI/7TT9nNgvsSy/CsawSCAEo5FKMSwhFuJ9Hs8RFRERELUMIgYMZxfjyQCZ+OVVgvR8NVbvjnq4h6Bjsc8P7DSEEDqRr8Z/dGdiVdhkA4CaT4KHECMwYGotQX1WT41p/IhdvrEtFWU0tFDIpnh3RAX+5s51dJ/6j62Ni38ycObGvNZmx9vglLNlxDtnF159Qoz4xbTzRL0aDnpF+aB9oufA014yaRpMZBzMsDxo2p+ajtLrW+p5a5Ya+7fzRr50G/WIC0CHIq8k9C8xmgZJqAzKKqpBWUIG0/AqkFVQiJbfM2k2qToCXAnfHh2BMlxD0jPRj930HV1ius/bsOJChRZa2+rrlAr2VCFa7w99TAeWV37Sm1oziKj3yy/Qoqrz++rMyqQTxYWr0becPpVwGbaUebjIpYgO9GvXwS1drwsxvkrD1VAFkUglWTOuFOzu0afqJExERkVPJLa3BV4ey8M3hbBRXGWzek0iACD+PKw0LlnttbaUe+9O1OFdYCcByT/Jgz3DMGBqLCP/mebhfWK7Dy2uS8euV1vsebX3x3oPd0I5j7x0KE/tm5qyJfXJOGWZ+cxyZVxIeH3c5RnUOxsjOwYjwV8HPQ4EqvRFFlQZkaatwrrASZ/MrcK6gArnXael0k0nQLdwX/WI0iA9To0OQN9r6ezT46d7lCj0OZmixP70Iv6QWQHvVha0uqR7bNQSJUf4t/sTQZBY4nVduTQoPXyhGpf73RF/lJkNilB+GdQzEmC4hDWpdpZZVVGmpP3W/2R+7qNcl4t0jfNEhyBtxwV6IDfS+6aQ1JVUGy0OfwsorD34sr5KrHjbVJ8hHaW3hD/JRQoLf663RLJBZVIWjWcVIv1wFhVyKjyb3YBd6IiKi25Su1oQtqfk4nlWCswWWxqY/JvpX81DI8ECPcDw5KBqRGs9mj0cIge+P5eCtn06hUm+Eu5sUL47uiKn9otiL1UEwsW9mzpjYb07Jw+xvf4Ou1gyNpwJPDY7Bo30jG9y1uLTagEMXinEgva5rcwXKaq5NdJRySwtmW38PSKWWtEatcoPGUwGjWUBbacCl0hqkFVRcs7SXn4cbRseH4N6uIegd7W/X8e61JjP2p2ux4UQufj1TaHORlUiAHm390D9Gg/4xAegV5cex+a3kWFYx1v+WiwMZWqQVVNq8J5EAnUN9rvTs0KBXlD+83Ztn+IgQArllOhxM1+JoVglkUsDfUwldrcna8+N6D7/q46mQ4dOpiegfE9As8REREZFrKKrUW+8tzhVWwmQW0HgpEOHngTFdQ+DTTPc2N3KptAYv/u8k9p63jOHvFuGLt+7rjG4Rvi1+bLoxJvbNzNkS+//uycA/fj4NABjcoQ2WTO5+yxcFIQQuFlfjQLoWhzOLkVZQgXMFldcssXEzHYO90S9GgyFxgegfo3HImTjNZoFzhZXYc+4yfk7OQ9LFUpv3NZ4K3N0lGI/2jUTHYMevD86m1mTGsawSfLwzHbuvjCmrU1d/+rXToE+0ptXmgbiecl0tzl0Zy3+2oAJlf2zhlwDhviq0D/JGn3b+CPRmrw8iIiJyTEIIrDp0EQs2nUGl3giJBJiYGIG/j4qDxkvZ6vHojSbrsFkJAB+Vm0PmDS2NiX0zc5bEXgiB9345i492pAMApvSLxBtjO7VY67LJLJBdXI20qyYpM5kFSmtqUVylh1wqhcZTgSAfd8QGeaF9oFeztai2pkulNdh77jIOpGuxK+2yTRfte7qG4G93tedsorfAbBZIyS2zdrE/cqEYVQbLSghyqQTjEsIw7I5A9In2t8sfFiIiIqLbRWGFDu9uOoM1xy8BsAzlnXlXe4zvHoY23s17H2Y2C5zOtwyNPZZVgoJynWXy60oDKvTGa8r7uMsR7ueBDkFe6ByqxqjOwWirce0JhZnYNzNnSOzNZoG561Ox8mAWAOCF0XGYPiTWzlG5nrou+98euYiNyfnW7f1jNHi0byQGtg9olS5TN1JjMOF8YSXOFlQgt7QG3u5yaLyUaOvvgfaBXvBshaXdGiqtoAJzvj9hXZu9jq+HG0Z1CsaMobEuf8EmIiIicjRHM4vxxrpUnMorBwBIJUC/GA0m9W6LUZ2Dm9x6Xm0w4qcTudh+phCHLhTbTKDdFF3D1ZjaLwrjEkJdcqgsE/tm5gyJ/Zn8cty3dB9qTWa8PS4ej/aNtHdILu90XjmWbD+HzSn5qFtRTyoBuoSp0fdKd/EekX4tmuibzQJnCypwIF2LQxe0OJ1XgeySatzo/+xwPxXiriyv0sZbCY2XAhpPJfw9FQj1VcHfU9Fi8dapNZnx3z0XsHhrGgwmMzwVMuuyg/1iNLgjmEsPEhEREdmTySzw3dFsrD6SjRPZpdbtQT5KPNAjHGO7huKOEO8brl4lhOVe9Wx+BZIulmLN8Rybpa09FTL0ivZH33YaRGk8oPFSQuNpuTf1UckhkUhgNguU1dSiqFKPTK2lt/CBdMuE3HX34O3aeGLWsPYY2zXUpZbtY2LfzJwhsQeAracKUG0wYlxCmL1Dua1cKq3BqoNZ2JScZ12B4GohanfcEeKD3tH+6B+jQXyouklJa7XBiKIKA9KLLOO6ky6W4tCF4uvOpqrxVKB9kBci/T1RqTficoUeGUVV9S7tdrUAL4XNeu4DYjXNNhOrEAL707WYuz4V568s4XJXx0DMv78LgrjyABEREZFDyi6uxvfHcvDN4Yu4fNWE2G39PdA/RoMBsQG4Oz7YptX8QlEV5nx/AseySmz2FanxwIQe4RjQPgBdwtRNbv0vqtTj2yPZ+HRPhrXlv32gF54d0QF3xwc3eblsR8LEvpk5S2JP9pdbWmOzJFtOSc01ZYJ93DGmSwju7BCAuGBvBPu421x4hLBM3ncgXYsT2aVIK6xAxuUqVF8Zd/5HKjfLk85+7TToFmFZhjCgnrHoxVeWdjtXUIGMoipoKw3QVumhrTSgqNJQb+LfJUyN0fHB6BejadAF2GwWyCmxrIZQrrNcaLO01fg5Oc+a0Pt7KvDy3R0xoWe4S1x4iYiIiFydwWjG1lMFWH/iEnacvQzDVRNpdwtX4/2HEuChkGHN8Rws3XEeuloz3N2kiA9Vo32QN0Z2CsLgDm2atWdmha4Wn+/LxKd7Mqy9AXpH++PN+zrjjhDnzt2Y2DczJvbUVGU1tThXUIHfsktxMEOLgxnFqPzDZCAqNxkCvBVQq9xQoTOiqEJvnTzuj5RyKSL8PRAX5I07QrzRt50GXcN9oZA3z5iiKr3ROj7/XEEFUi6V43BmMUzm3y8VMqnkpl2czGYBo/n6lxeFTIpJvSPw3Ig4u85qT0RERERNV6k34vAFLfaf1+Lbo9mo0BnhJpOg1vT7PeDA2AAsmNAVYb6qFo+nrKYWn+3JwLI9GdDVmiGVAK+MuQNPDmrX4sduKUzsmxkTe2ouuloT9pwrwqbkPJzIKUWmttomaa7j7iZFYqQ/ekX5o2OIZTx8sI87PBSyVm/d1lbqsSW1ALvTLuPgBW2DJzlRyKWIaeOFAC8FJBIJvJVyDLsjEMM7Bdl9gkEiIiIiaj55ZTV48Ydk7E67DIkE6BXpjwcTw/FAj/BWnzfpUmkN/rHhFDalWCa6njE0BnNGxtncQxtNZkgkN2+ssjcm9s2MiT21FL3RhLxSHbRVepRW10KtcoO/pwJhfioo5TJ7h3cNs1mgsEIP800uHRIJ0MZL6ZKzkxIRERHRtYQQOJ1XAT9PN4SoW76F/mb+vTMdCzafAQCM6RKMpwfHIsxPhW8OX8RXB7Pw+thOuLtLiJ2jvDEm9s2MiT0REREREZFz+frQRbz6Y7J1xSiZVGLtLTuiUxA+nZJox+hurqF5qOMsZk1ERERERETUjCb3aYv4MB+s2JeJDSdzUWsS6BquxtR+Ubinq2O31jcGW+wbiC32REREREREzktbqUe5zogojYfTrMjEFnsiIiIiIiKiKzReSmjqWRLa2XFWKyIiIiIiIiInxsSeiIiIiIiIyIkxsSciIiIiIiJyYkzsiYiIiIiIiJwYE3siIiIiIiIiJ8bEnoiIiIiIiMiJMbEnIiIiIiIicmJM7ImIiIiIiIicGBN7IiIiIiIiIifGxJ6IiIiIiIjIiTGxJyIiIiIiInJiTOyJiIiIiIiInBgTeyIiIiIiIiInxsSeiIiIiIiIyInJ7R2AsxBCAADKy8vtHAkRERERERHdDuryz7p8tD5M7BuooqICABAREWHnSIiIiIiIiOh2UlFRAbVaXe/7EnGz1J8AAGazGbm5ufD29oZEIrF3OPUqLy9HREQEsrOz4ePjY+9wyAGxjlBTsN5QY7HO0K1g/aGmYL2hpnD0eiOEQEVFBUJDQyGV1j+Sni32DSSVShEeHm7vMBrMx8fHISsmOQ7WEWoK1htqLNYZuhWsP9QUrDfUFI5cb27UUl+Hk+cREREREREROTEm9kREREREREROjIm9i1EqlZg7dy6USqW9QyEHxTpCTcF6Q43FOkO3gvWHmoL1hprCVeoNJ88jIiIiIiIicmJssSciIiIiIiJyYkzsiYiIiIiIiJwYE3siIiIiIiIiJ8bEnoiIiIiIiMiJMbFvBfPnz0evXr3g7e2NwMBAjB8/HmfPnrUpI4TAvHnzEBoaCpVKhSFDhiA1NdWmzLJlyzBkyBD4+PhAIpGgtLS03mPq9XokJCRAIpHgt99+u2mMycnJGDx4MFQqFcLCwvDWW2/h6nkV8/LyMHnyZMTFxUEqlWL27NmN+QroJlyhjuzduxcDBgyARqOBSqVCx44dsXjx4kZ9D9Q4rlBvdu7cCYlEcs3rzJkzjfouqGFcoc5MmzbtunWmc+fOjfouqPFcof4AwEcffYQ77rgDKpUKcXFx+PLLLxv8HVDjOXq90el0mDZtGrp06QK5XI7x48dfU4b3wa2vNetNVFTUNX9TXnrppZvG6Gj5ExP7VrBr1y7MmDEDBw8exNatW2E0GjFy5EhUVVVZyyxcuBCLFi3C0qVLceTIEQQHB2PEiBGoqKiwlqmursbo0aPxyiuv3PSYL7zwAkJDQxsUX3l5OUaMGIHQ0FAcOXIES5YswXvvvYdFixZZy+j1erRp0wavvvoqunXr1oizp4ZwhTri6emJZ555Brt378bp06fx2muv4bXXXsOyZcsa8U1QY7hCvalz9uxZ5OXlWV/t27dv0DGocVyhzvzrX/+yqSvZ2dnw9/fHgw8+2IhvgprCFerPv//9b7z88suYN28eUlNT8eabb2LGjBn46aefGvFNUGM4er0xmUxQqVT429/+huHDh1+3DO+DW19r15u33nrL5m/La6+9dsPyDpk/CWp1hYWFAoDYtWuXEEIIs9ksgoODxbvvvmsto9PphFqtFp988sk1n9+xY4cAIEpKSq67/40bN4qOHTuK1NRUAUAkJSXdMJ6PP/5YqNVqodPprNvmz58vQkNDhdlsvqb84MGDxaxZs25+otRkzl5H6vzpT38Sjz766A33Tc3HGevNzY5JLcsZ68wfrV27VkgkEpGZmXmTs6Xm5oz1p1+/fmLOnDk2n5s1a5YYMGBAQ06ZmoGj1ZurTZ06VYwbN+6GZXgfbB8tWW8iIyPF4sWLGxWPI+ZPbLG3g7KyMgCAv78/AODChQvIz8/HyJEjrWWUSiUGDx6M/fv3N2rfBQUF+POf/4yVK1fCw8OjQZ85cOAABg8eDKVSad02atQo5ObmIjMzs1HHp+bhCnUkKSkJ+/fvx+DBgxsVHzWdM9eb7t27IyQkBMOGDcOOHTsaFRs1nTPXmTqfffYZhg8fjsjIyEbFR7fOGeuPXq+Hu7u7zedUKhUOHz6M2traRsVITeNo9YacQ0vWGwBYsGABNBoNEhIS8M9//hMGg+GG5R0xf2Ji38qEEHjuuecwcOBAxMfHAwDy8/MBAEFBQTZlg4KCrO81dN/Tpk3DU089hcTExAZ/Lj8//7rHvjo2aj3OXkfCw8OhVCqRmJiIGTNm4Mknn2zwcajpnLXehISEYNmyZfjhhx+wZs0axMXFYdiwYdi9e3eDj0NN46x15mp5eXnYtGkTrzN24Kz1Z9SoUfjvf/+LY8eOQQiBo0ePYvny5aitrUVRUVGDj0VN44j1hhxfS9YbAJg1axZWr16NHTt24JlnnsEHH3yA6dOn3/Azjpg/ye1y1NvYM888g5MnT2Lv3r3XvCeRSGz+LYS4ZtuNLFmyBOXl5Xj55ZfrLdO5c2dkZWUBAAYNGoRNmzbVe+zrbaeW5+x1ZM+ePaisrMTBgwfx0ksvITY2FpMmTWpwjNQ0zlpv4uLiEBcXZ32/X79+yM7OxnvvvYc777yzwTFS4zlrnbna559/Dl9f3+tOdkUty1nrz+uvv478/Hz07dsXQggEBQVh2rRpWLhwIWQyWYNjpKZx1HpDjq0l6w0APPvss9b/7tq1K/z8/DBhwgRrK76z5E9M7FvRzJkzsX79euzevRvh4eHW7cHBwQAsT3dCQkKs2wsLC695EnQj27dvx8GDB226hABAYmIiHnnkEXzxxRfYuHGjtauZSqWyHv+PT5YKCwsBXPsUjFqWK9SR6OhoAECXLl1QUFCAefPmMbFvYa5Qb67Wt29frFq1qsHxUeO5Qp0RQmD58uV47LHHoFAoGhwb3Tpnrj8qlQrLly/Hf/7zHxQUFFh7DXl7eyMgIKDBMVLjOWq9IcfW0vXmevr27QsAOH/+PDQajfPkTy06gp+EEJbJHWbMmCFCQ0NFWlradd8PDg4WCxYssG7T6/WNnvwhKytLJCcnW19btmwRAMT//vc/kZ2dXW98H3/8sfD19RV6vd667d133+Xkea3I1epInbfeektERkbe4MzpVrhqvXnggQfE0KFDb3Tq1ESuVGfqjp2cnNzQ06db5Er152p33nmnmDRp0o1OnW6Bo9ebq3HyPMfRWvXmen766ScBQGRlZdVbxhHzJyb2reDpp58WarVa7Ny5U+Tl5Vlf1dXV1jLvvvuuUKvVYs2aNSI5OVlMmjRJhISEiPLycmuZvLw8kZSUJD799FMBQOzevVskJSUJrVZ73eNeuHChQbOBlpaWiqCgIDFp0iSRnJws1qxZI3x8fMR7771nUy4pKUkkJSWJnj17ismTJ4ukpCSRmpra9C+GrFyhjixdulSsX79epKWlibS0NLF8+XLh4+MjXn311Vv7cqherlBvFi9eLNauXSvS0tJESkqKeOmllwQA8cMPP9zal0PX5Qp1ps6jjz4q+vTp07QvgprEFerP2bNnxcqVK0VaWpo4dOiQmDhxovD39xcXLly4pe+G6ufo9UYIIVJTU0VSUpK49957xZAhQ6z3vFfjfXDraq16s3//frFo0SKRlJQkMjIyxLfffitCQ0PFfffdd8P4HDF/YmLfCgBc97VixQprGbPZLObOnSuCg4OFUqkUd9555zWtEHPnzr3pfq7WmAvayZMnxaBBg4RSqRTBwcFi3rx51zxtut6x2RrbPFyhjnz44Yeic+fOwsPDQ/j4+Iju3buLjz/+WJhMpqZ8JdQArlBvFixYIGJiYoS7u7vw8/MTAwcOFD///HNTvg5qAFeoM0JYbqhUKpVYtmxZY78CugWuUH9OnTolEhIShEqlEj4+PmLcuHHizJkzTfk6qIGcod5ERkZed983Ow/eB7ec1qo3x44dE3369BFqtVq4u7uLuLg4MXfuXFFVVXXTGB0tf5JcOSAREREREREROSEud0dERERERETkxJjYExERERERETkxJvZEREREREREToyJPREREREREZETY2JPRERERERE5MSY2BMRERERERE5MSb2RERERERERE6MiT0RERERERGRE2NiT0REREREROTEmNgTERHRTU2bNg0SiQQSiQRubm4ICgrCiBEjsHz5cpjN5gbv5/PPP4evr2/LBUpERHQbYmJPREREDTJ69Gjk5eUhMzMTmzZtwtChQzFr1iyMHTsWRqPR3uERERHdtpjYExERUYMolUoEBwcjLCwMPXr0wCuvvIJ169Zh06ZN+PzzzwEAixYtQpcuXeDp6YmIiAhMnz4dlZWVAICdO3fi8ccfR1lZmbX1f968eQAAg8GAF154AWFhYfD09ESfPn2wc+dO+5woERGRk2FiT0RERE121113oVu3blizZg0AQCqV4sMPP0RKSgq++OILbN++HS+88AIAoH///vjggw/g4+ODvLw85OXlYc6cOQCAxx9/HPv27cPq1atx8uRJPPjggxg9ejTOnTtnt3MjIiJyFhIhhLB3EEREROTYpk2bhtLSUvz444/XvPfwww/j5MmTOHXq1DXvff/993j66adRVFQEwDLGfvbs2SgtLbWWSU9PR/v27ZGTk4PQ0FDr9uHDh6N379545513mv18iIiIXInc3gEQERGRcxNCQCKRAAB27NiBd955B6dOnUJ5eTmMRiN0Oh2qqqrg6el53c8fP34cQgh06NDBZrter4dGo2nx+ImIiJwdE3siIiK6JadPn0Z0dDSysrIwZswYPPXUU3j77bfh7++PvXv34oknnkBtbW29nzebzZDJZDh27BhkMpnNe15eXi0dPhERkdNjYk9ERERNtn37diQnJ+PZZ5/F0aNHYTQa8f7770MqtUzj891339mUVygUMJlMNtu6d+8Ok8mEwsJCDBo0qNViJyIichVM7ImIiKhB9Ho98vPzYTKZUFBQgM2bN2P+/PkYO3YspkyZguTkZBiNRixZsgT33nsv9u3bh08++cRmH1FRUaisrMSvv/6Kbt26wcPDAx06dMAjjzyCKVOm4P3330f37t1RVFSE7du3o0uXLhgzZoydzpiIiMg5cFZ8IiIiapDNmzcjJCQEUVFRGD16NHbs2IEPP/wQ69atg0wmQ0JCAhYtWoQFCxYgPj4eX331FebPn2+zj/79++Opp57CxIkT0aZNGyxcuBAAsGLFCkyZMgXPP/884uLicN999+HQoUOIiIiwx6kSERE5Fc6KT0REREREROTE2GJPRERERERE5MSY2BMRERERERE5MSb2RERERERERE6MiT0RERERERGRE2NiT0REREREROTEmNgTEREREREROTEm9kREREREREROjIk9ERERERERkRNjYk9ERERERETkxJjYExERERERETkxJvZERERERERETuz/A0AUbX+MYD6GAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"], label=\"Observed discharge\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.axhline(\n",
+    "    y=q_critical,\n",
+    "    linestyle=\":\",\n",
+    "    label=f\"Critical discharge ({q_critical} m³/s)\",\n",
+    "    color='black'\n",
+    ")\n",
+    "\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "07a239a5-398f-4ad2-9a33-f2d199485309",
+   "metadata": {},
+   "source": [
+    "# Finding range"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9c87425e-c0d7-49ad-aab7-57bb5df5af0d",
+   "metadata": {},
+   "source": [
+    "## Start of range (freshet)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "504d4401-3712-406b-b9ef-884db8702c28",
+   "metadata": {},
+   "source": [
+    "### Idea 1: Rate of change\n",
+    "\n",
+    "gemiddelde dQ over 5 dagen periode moet groter zijn dan 15 m^3/s increase per dag voor consecutive dagen \n",
+    "& Q > Q_kritisch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "204f6612-01b4-43c5-aff4-d345817047d9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Define dQ\n",
+    "\n",
+    "# dQ = Q_today - Q_yesterday\n",
+    "\n",
+    "# dQ over 5 dagen periode moet groter zijn dan x m^3/s increase per dag voor consecutive dagen \n",
+    "# & Q > q_kritisch\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dc8791fb-3dac-425a-b5bd-45cdb8a0331f",
+   "metadata": {},
+   "source": [
+    "### Idea 2: Q_critical "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "727e107a-465a-4947-ba90-494ec323a262",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>first_above_critical_date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>2014-04-23</td>\n",
+       "      <td>506.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   year first_above_critical_date  discharge_m3s\n",
+       "0  2014                2014-04-23          506.0"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create pd for identified critical dates\n",
+    "\n",
+    "freshet_start_date = []\n",
+    "\n",
+    "for year, group in q_obs.groupby(q_obs[\"Date\"].dt.year):\n",
+    "\n",
+    "    # Set start date to March 1\n",
+    "    start_date_algorithm = pd.to_datetime(f\"{year}-03-01\")\n",
+    "    season_data = group[group[\"Date\"] >= start_date_algorithm].copy()\n",
+    "    \n",
+    "    # Identify first day where q > q_critical\n",
+    "    \n",
+    "    above_critical = season_data[\n",
+    "        season_data[\"discharge_m3s\"] > q_critical\n",
+    "    ]\n",
+    "    \n",
+    "    if len(above_critical) > 0:\n",
+    "        first_day = above_critical.iloc[0]\n",
+    "        \n",
+    "        freshet_start_date.append({\n",
+    "            \"year\": year,\n",
+    "            \"first_above_critical_date\": first_day[\"Date\"],\n",
+    "            \"discharge_m3s\": first_day[\"discharge_m3s\"]\n",
+    "        })\n",
+    "    else:\n",
+    "        freshet_start_date.append({\n",
+    "            \"year\": year,\n",
+    "            \"first_above_critical_date\": pd.NaT,\n",
+    "            \"discharge_m3s\": None\n",
+    "        })\n",
+    "\n",
+    "freshet_start_date = pd.DataFrame(freshet_start_date)\n",
+    "\n",
+    "freshet_start_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "e20e293c-245d-47da-9b45-1c9675f989f4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"], label='Observed discharge')\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.axhline(\n",
+    "    y=q_critical,\n",
+    "    linestyle=\":\",\n",
+    "    label=f\"Critical discharge ({q_critical} m³/s)\",\n",
+    "    color='black'\n",
+    "    )\n",
+    "\n",
+    "for date in freshet_start_date[\"first_above_critical_date\"].dropna():\n",
+    "    plt.axvline(\n",
+    "        x=date,\n",
+    "        linestyle=':',\n",
+    "        color='orange',\n",
+    "        label='Start navigable season'\n",
+    "    )\n",
+    "        \n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "39bd4c7f-1a15-464d-bddd-6c3e05088566",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Convert date to day of year\n",
+    "freshet_start_date[\"day_of_year\"] = (freshet_start_date[\"first_above_critical_date\"].dt.dayofyear)\n",
+    "\n",
+    "# Make plot \n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.scatter(freshet_start_date[\"day_of_year\"], freshet_start_date[\"year\"], marker=\"o\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Year\")\n",
+    "plt.title(\"First date discharge exceeds critical threshold between 1970-2024\")\n",
+    "plt.grid(True)\n",
+    "\n",
+    "# Convert day of year to day in months (on the axis)\n",
+    "plt.xticks(\n",
+    "    [60, 65, 70, 75, 80, 85, 90,\n",
+    "     95, 100, 105, 110, 115, 120,\n",
+    "     125, 130, 135, 140, 145, 150],\n",
+    "    [\"Mar 1\", \"Mar 6\", \"Mar 11\", \"Mar 16\", \"Mar 21\", \"Mar 26\", \"Mar 31\",\n",
+    "     \"Apr 5\", \"Apr 10\", \"Apr 15\", \"Apr 20\", \"Apr 25\", \"Apr 30\",\n",
+    "     \"May 5\", \"May 10\", \"May 15\", \"May 20\", \"May 25\", \"May 30\"],\n",
+    ")\n",
+    "\n",
+    "# Automate x-axis range to fit data\n",
+    "plt.xlim((freshet_start_date[\"day_of_year\"].min()-1), (freshet_start_date[\"day_of_year\"].max()+1))\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "1bf87b1f-7a42-4819-af63-2dc95649c8fb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Creating bar graph\n",
+    "\n",
+    "# Choose bin size\n",
+    "bin_size = 5   # use 10 for 10-day periods\n",
+    "\n",
+    "# Convert date to day of year\n",
+    "freshet_start_date[\"day_of_year\"] = freshet_start_date[\"first_above_critical_date\"].dt.dayofyear\n",
+    "\n",
+    "# Create bins\n",
+    "freshet_start_date[\"date_bin\"] = (freshet_start_date[\"day_of_year\"] // bin_size) * bin_size\n",
+    "\n",
+    "# Count how many years fall in each bin\n",
+    "freshet_counts = freshet_start_date.groupby(\"date_bin\").size()\n",
+    "\n",
+    "# Plot bar chart\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.bar(freshet_counts.index, freshet_counts.values, width=bin_size)\n",
+    "\n",
+    "# Convert x-axis from day-of-year to calendar dates\n",
+    "tick_days = freshet_counts.index\n",
+    "tick_labels = [\n",
+    "    (pd.to_datetime(\"2001-01-01\") + pd.to_timedelta(day - 1, unit=\"D\")).strftime(\"%b %d\")\n",
+    "    for day in tick_days\n",
+    "]\n",
+    "\n",
+    "plt.xticks(tick_days, tick_labels, rotation=45)\n",
+    "\n",
+    "plt.xlabel(\"Date period\")\n",
+    "plt.ylabel(\"Number of years\")\n",
+    "plt.title(\"First date discharge exceeds critical threshold\")\n",
+    "plt.grid(axis=\"y\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d32414f7-d742-48cb-9d94-50441c3f550c",
+   "metadata": {},
+   "source": [
+    "## End of range (river freeze-up)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f912ae02-7887-4bf3-af61-0ccc4c154fef",
+   "metadata": {},
+   "source": [
+    "### Idea 1: Critical when AFDD = x\n",
+    "\n",
+    "AFDD is Accumulated Freeze Degree Days. It calculates the accumulative temperature under 0. \n",
+    "Example: If 3 days have a mean temperature of -5 C per day, the AFDD would be 15. \n",
+    "\n",
+    "A study shows the LAR forms an ice sheet when AFDD reaches (approx) 50 degrees. https://www.iahr.org/library/infor?pid=26767 (Figure 6)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7aa6524c-9140-4756-bfc9-c67947740a8e",
+   "metadata": {},
+   "source": [
+    "### Load ERA5-forcings & TAS data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "9e315bb0-0085-43e0-b0a0-0d23d6bc4ba0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate ERA5 data\n",
+    "\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "#     directory=forcing_path_ERA5\n",
+    "# )\n",
+    "\n",
+    "# Load ERA5 data\n",
+    "\n",
+    "# load_location = forcing_path_ERA5 / \"work\" / \"diagnostic\" / \"script\" \n",
+    "# ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=load_location)\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "e90fb4e3-9f06-405c-bc08-fcbc28c0ef7c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Exract tas file from Era5\n",
+    "tas_file = Path(ERA5_forcing.directory) / ERA5_forcing.filenames[\"tas\"]\n",
+    "\n",
+    "# Extract tas data from tas file\n",
+    "temp_data = xr.open_dataset(tas_file)[\"tas\"]\n",
+    "\n",
+    "# Convert to panda\n",
+    "temp_data = temp_data.to_series()\n",
+    "temp_data.index = pd.to_datetime(temp_data.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Convert Kelvin to Celsius:\n",
+    "temp_data = temp_data - 273.15\n",
+    "\n",
+    "# Create dataframe with Date, Temp & year as columns\n",
+    "temp_data = pd.DataFrame({\n",
+    "    \"Date\": temp_data.index,\n",
+    "    \"Temp\": temp_data.values,\n",
+    "    \"year\": temp_data.index.year\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "54ebf5d5-9ad6-4a37-8301-f204b1059c06",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">   year AFDD_critical_date       AFDD       Temp\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41.426453</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-13.859253</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "   year AFDD_critical_date       AFDD       Temp\n",
+       "\u001b[1;36m0\u001b[0m  \u001b[1;36m2014\u001b[0m         \u001b[1;36m2014\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m10\u001b[0m  \u001b[1;36m41.426453\u001b[0m \u001b[1;36m-13.859253\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>AFDD_critical_date</th>\n",
+       "      <th>AFDD</th>\n",
+       "      <th>Temp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>2014-11-10</td>\n",
+       "      <td>41.426453</td>\n",
+       "      <td>-13.859253</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   year AFDD_critical_date       AFDD       Temp\n",
+       "0  2014         2014-11-10  41.426453 -13.859253"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "AFDD_critical = 30\n",
+    "AFDD_critical_dates = []\n",
+    "\n",
+    "# min_subzero_days = 5\n",
+    "# consec_days = 7\n",
+    "\n",
+    "start_year = start_date.year\n",
+    "end_year = end_date.year\n",
+    "\n",
+    "for year in range(start_year, end_year + 1):\n",
+    "\n",
+    "    # Set start date to 1 August\n",
+    "    year_data = temp_data[\n",
+    "        (temp_data[\"year\"] == year) &\n",
+    "        (temp_data[\"Date\"] >= pd.to_datetime(f\"{year}-10-01\"))\n",
+    "    ]\n",
+    "\n",
+    "    AFDD = 0\n",
+    "    \n",
+    "    # Isolate datasets of date & temperature data to each year \n",
+    "    for i in range(len(year_data)):\n",
+    "        temp = year_data.iloc[i][\"Temp\"]\n",
+    "        date = year_data.iloc[i][\"Date\"]\n",
+    "\n",
+    "        # Cumulative AFDD\n",
+    "        if temp < 0:\n",
+    "            AFDD += -temp\n",
+    "\n",
+    "        # Append when AFDD is critical\n",
+    "        if AFDD >= AFDD_critical:\n",
+    "            AFDD_critical_dates.append({\n",
+    "                \"year\": year,\n",
+    "                \"AFDD_critical_date\": date,\n",
+    "                \"AFDD\": AFDD,\n",
+    "                \"Temp\": temp\n",
+    "            })\n",
+    "\n",
+    "            break \n",
+    "\n",
+    "AFDD_critical_dates = pd.DataFrame(AFDD_critical_dates)\n",
+    "\n",
+    "print(AFDD_critical_dates)\n",
+    "\n",
+    "        # # Criteria 1: 5 of 7 consecutive days must be sub-zero\n",
+    "        # if i >= consec_days - 1:\n",
+    "        #     last_7_days = year_data.iloc[i - consec_days + 1 : i + 1]\n",
+    "        #     subzero_days = 0\n",
+    "\n",
+    "        #     for j in range(len(last_7_days)):\n",
+    "        #         if last_7_days.iloc[j][\"Temp\"] < 0:\n",
+    "        #             subzero_days += 1\n",
+    "\n",
+    "        #      if AFDD >= AFDD_critical and subzero_days >= required_subzero_days:\n",
+    "        #         AFDD_critical_dates.append({\n",
+    "        #             \"year\": year,\n",
+    "        #             \"AFDD_critical_date\": date,\n",
+    "        #             \"AFDD\": AFDD,\n",
+    "        #             \"Subzero days in 7 day period\": subzero_days\n",
+    "        #     })\n",
+    "        #     break\n",
+    "\n",
+    "AFDD_critical_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "861083f4-0521-4186-a73d-9c2aca2befa3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Convert date to day of year\n",
+    "AFDD_critical_dates[\"day_of_year\"] = (AFDD_critical_dates[\"AFDD_critical_date\"].dt.dayofyear)\n",
+    "\n",
+    "# Make plot \n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.scatter(AFDD_critical_dates[\"day_of_year\"], AFDD_critical_dates[\"year\"], marker=\"o\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Year\")\n",
+    "plt.title(f\"Date of river freeze-up (AFDD >= {AFDD_critical}) between 1970-2024\")\n",
+    "plt.grid(True)\n",
+    "\n",
+    "# Convert day of year to day in months (on the axis)\n",
+    "plt.xticks(\n",
+    "    [274, 279, 284, 289, 294, 299, 304,\n",
+    "     309, 314, 319, 324, 329, 334, 339,\n",
+    "     344, 349, 354, 359, 364, 366],\n",
+    "    [\"Oct 1\", \"Oct 6\", \"Oct 11\", \"Oct 16\", \"Oct 21\", \"Oct 26\", \"Oct 31\",\n",
+    "     \"Nov 5\", \"Nov 10\", \"Nov 15\", \"Nov 20\", \"Nov 25\", \"Nov 30\", \"Dec 5\",\n",
+    "     \"Dec 10\", \"Dec 15\", \"Dec 20\", \"Dec 25\", \"Dec 30\", \"Dec 31\"],\n",
+    ")\n",
+    "\n",
+    "# Prevent y-axis from showing decimal years\n",
+    "# plt.yticks(range(start_year, end_year + 1))\n",
+    "\n",
+    "# Automate x-axis range to fit data\n",
+    "plt.xlim((AFDD_critical_dates[\"day_of_year\"].min()-1), (AFDD_critical_dates[\"day_of_year\"].max()+1))\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "7995d878-10ac-4e6e-aa0f-b8e281d5aaf6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot temp for 1 year for fun:\n",
+    "selected_year = 2014\n",
+    "year_data = temp_data[temp_data[\"year\"] == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.title(f\"Temperature time series showing date of river freeze-up (AFDD >= {AFDD_critical}) for 2014\")\n",
+    "plt.scatter(year_data[\"Date\"], year_data[\"Temp\"], marker=\"o\")\n",
+    "plt.axhline(\n",
+    "    y=0,\n",
+    "    linestyle=\":\",\n",
+    "    color=\"black\",\n",
+    "    label=\"0°C\"\n",
+    ")\n",
+    "\n",
+    "# Extract & plot critical AFDD date for selected year\n",
+    "AFDD_critical_date = AFDD_critical_dates.loc[AFDD_critical_dates[\"year\"] == selected_year, \"AFDD_critical_date\"].iloc[0]\n",
+    "plt.axvline(\n",
+    "    x=AFDD_critical_date,\n",
+    "    linestyle=\":\",\n",
+    "    color=\"orange\",\n",
+    "    label=\"River freeze-up\"\n",
+    ")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Temperature (°C)\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5b3a1903-f809-45da-ad01-13313da0afea",
+   "metadata": {},
+   "source": [
+    "### Idea 2: Critical when q_critical < 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6e7f55d8-67b3-4721-912b-511875ecdbb4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a0f3c170-d57e-4d00-80c0-1bc1f090b940",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f655679f-10de-42bf-88b9-ef58385bd62c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c6b724d3-19f0-4ec3-9bb6-1828e22b320d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "078fc0ee-197a-45de-87b5-9a00eec5801f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fabbb9d8-1446-474d-b329-83c221d3f018",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Step3_Calibration_HBV.ipynb b/Workyard/Step3_Calibration_HBV.ipynb
new file mode 100644
index 00000000..b2902e3b
--- /dev/null
+++ b/Workyard/Step3_Calibration_HBV.ipynb
@@ -0,0 +1,9072 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fbc7f454-3d60-492d-aa6c-0ce21a0dfc77",
+   "metadata": {},
+   "source": [
+    "## Startup\n",
+    "\n",
+    "\n",
+    "80/20 rule:\n",
+    "80% calibration (2000-2020)\n",
+    "20% validation (2020-2025)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "95a06f73-282f-4c7c-8333-f002e73e205a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print\n",
+    "\n",
+    "from ipywidgets import IntProgress\n",
+    "from IPython.display import display"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8b61a012-64eb-48b2-ba78-f641a1a581a3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a860a623-f634-4b50-822c-51e09ab4e594",
+   "metadata": {},
+   "source": [
+    "### Defining variables & pathways"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "970798cd-b737-44f3-8edd-de3352b86efd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period & basin si\n",
+    "\n",
+    "experiment_start_date = \"2000-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2005-12-31T00:00:00Z\"\n",
+    "\n",
+    "calibration_start = \"1999-01-01T00:00:00Z\"\n",
+    "calibration_end = \"2019-12-31T00:00:00Z\"\n",
+    "\n",
+    "# validation_start = \"\"\n",
+    "# validation_end = \"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "c3b02d32-4be2-47a7-8935-8284af182d66",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "basin_size = 132572\n",
+    "\n",
+    "calibration_temp = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"calibration_temp\"\n",
+    "calibration_temp.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "241efaf0-94fc-4e07-8a62-151661dc4343",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Create pathways for ERA 5 forcings\n",
+    "\n",
+    "# forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "# discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "# basin_size = 132572\n",
+    "\n",
+    "# calibration_temp = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"calibration_temp\"\n",
+    "# calibration_temp.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd4ec71b-d4f6-4a1c-be9a-f8d3b89059d1",
+   "metadata": {},
+   "source": [
+    "### Load & prepare discharge data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "d590f365-72ad-4473-9996-88820ea52c18",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1cec4b74-037a-4d48-8769-e0b57a7683aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "# start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "# end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# q_obs = q_obs[(q_obs[\"Date\"] >= start_date) & (q_obs[\"Date\"] <= end_date)]\n",
+    "# observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7c47f7f-18ff-4441-b1d4-975e46e1719b",
+   "metadata": {},
+   "source": [
+    "### Generate or Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "eb582ebf-8fbc-4542-b785-cee2f332bdd5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1999-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1999-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2019-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load ERA5 data\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6fc290da-fa08-48f0-83e3-a39e8f5c36ef",
+   "metadata": {},
+   "source": [
+    "## Calibration Methods"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9b95e67e-780e-4a4d-a2f1-4cf9de2b0512",
+   "metadata": {},
+   "source": [
+    "### Method 1: RMSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "3da0e944-b4bf-49c6-a986-a94fc14e0bfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def RMSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return np.sqrt(np.mean((obs - sim)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba51d28d-1fdb-46af-8f8e-5dcf904aba7f",
+   "metadata": {},
+   "source": [
+    "### Method 2: NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "9ff8dc21-0959-49a4-9d4b-496726c90f88",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def NSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return 1 - np.sum((obs - sim) ** 2) / np.sum((obs - np.mean(obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "93f96591-ceb4-4671-9a48-04a0ddbfaf5a",
+   "metadata": {},
+   "source": [
+    "### Method 3: Log_NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "826cfb65-21ba-4901-aafe-37738913c0ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def log_NSE(sim, obs):\n",
+    "    # Convert for easy calculations\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8dc2e27c-2caa-493a-8ad0-3a8540ff4a18",
+   "metadata": {},
+   "source": [
+    "### Define Parameters & Storages and Times"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "2ed6540e-ec2f-4f80-975f-66fee4b2a75a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define initial storages\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])\n",
+    "\n",
+    "# Define parameters (range)\n",
+    "parameter_ranges = {\n",
+    "    \"Imax\":  (5.5, 8),            # Maximum interception storage\n",
+    "    \"Ce\":    (0.35, 0.6),       # Evaporation correction factor\n",
+    "    \"Sumax\": (150, 220),         # Maximum soil moisture storage\n",
+    "    \"Beta\":  (1.6, 2),          # Soil runoff parameter\n",
+    "    \"Pmax\":  (0.1, 0.6),            # Maximum percolation rate\n",
+    "    \"Tlag\":  (5.2, 7),           # Time lag\n",
+    "    \"Kf\":    (0.01, 0.1),       # Fast reservoir recession coefficient\n",
+    "    \"Ks\":    (0.001, 0.1),     # Slow reservoir recession coefficient\n",
+    "    \"FM\":    (0.3, 1.4),          # Snowmelt factor\n",
+    "}\n",
+    "\n",
+    "# parameter_ranges = {\n",
+    "#     \"Imax\":  (6.27, 6.28),            # Maximum interception storage\n",
+    "#     \"Ce\":    (0.48, 0.49),       # Evaporation correction factor\n",
+    "#     \"Sumax\": (174, 175),         # Maximum soil moisture storage\n",
+    "#     \"Beta\":  (1.95, 1.96),          # Soil runoff parameter\n",
+    "#     \"Pmax\":  (0.33, 0.34),            # Maximum percolation rate\n",
+    "#     \"Tlag\":  (6.19, 6.2),           # Time lag\n",
+    "#     \"Kf\":    (0.07, 0.08),       # Fast reservoir recession coefficient\n",
+    "#     \"Ks\":    (0.004, 0.0045),     # Slow reservoir recession coefficient\n",
+    "#     \"FM\":    (0.4, 0.41),          # Snowmelt factor\n",
+    "# }\n",
+    "\n",
+    "# Convert to arrays\n",
+    "parameter_names = list(parameter_ranges.keys())\n",
+    "\n",
+    "p_min = np.array([parameter_ranges[name][0] for name in parameter_names])\n",
+    "p_max = np.array([parameter_ranges[name][1] for name in parameter_names])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fc6ef77d-95ba-4277-ab8c-654fa025894d",
+   "metadata": {},
+   "source": [
+    "### Create samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "47df771f-85c1-40a7-9e28-a6dfb3134514",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.85285914e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.89990216e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.76127959e+02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.92058774e+00</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.56024109e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.99810960e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.01314564e-02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.63774925e-02</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.62585104e-01</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[1;36m7.85285914e+00\u001b[0m \u001b[1;36m3.89990216e-01\u001b[0m \u001b[1;36m1.76127959e+02\u001b[0m \u001b[1;36m1.92058774e+00\u001b[0m\n",
+       " \u001b[1;36m5.56024109e-01\u001b[0m \u001b[1;36m6.99810960e+00\u001b[0m \u001b[1;36m3.01314564e-02\u001b[0m \u001b[1;36m6.63774925e-02\u001b[0m\n",
+       " \u001b[1;36m9.62585104e-01\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Create samples\n",
+    "N = 600\n",
+    "par_samples = np.random.rand(N, len(parameter_ranges))                  # Generates random values between 0-1\n",
+    "parameter_sets = p_min + par_samples * (p_max - p_min)                  # Fits value to parameter range\n",
+    "\n",
+    "print(parameter_sets[:][0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e22418a9-e4ba-4890-85a8-abcfd66c85f2",
+   "metadata": {},
+   "source": [
+    "### Define time period"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "9c72add6-8b9f-4b3e-9e9f-77406215c196",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "calibration_start_date = pd.to_datetime(calibration_start.replace(\"Z\", \"\"))\n",
+    "calibration_end_date = pd.to_datetime(calibration_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for calibration\n",
+    "evaluation_start = pd.to_datetime(f\"{calibration_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= calibration_start_date) & (q_obs[\"Date\"] <= calibration_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "645d5bb0-de70-4b97-9aa0-93094c91ebe6",
+   "metadata": {},
+   "source": [
+    "## Calibration start function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "0f58e61f-7178-44f8-8e5e-e1fa402813c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create function to run the model\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Create model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Create config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=calibration_temp\n",
+    "    )\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs \n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m, \n",
+    "        index=time, \n",
+    "        name=\"Modelled discharge\"\n",
+    "    )\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e93b5d4-0a92-4d09-b135-07101e614d9e",
+   "metadata": {},
+   "source": [
+    "### Run HBV loop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "577e23e5-8db6-45a1-b91b-aae3a46b6c12",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1ce6bc7773174ef98c9608eb840d31a4",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "IntProgress(value=0, max=600)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m6\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m7\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m8\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m9\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m10\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m11\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m12\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m13\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m14\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m15\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m16\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m17\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m18\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m19\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m20\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">21</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m21\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m22\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">23</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m23\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m24\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m25\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">26</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m26\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m27\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m28\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">29</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m29\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m30\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m31\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m32\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m33\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m34\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">35</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m35\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m36\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">37</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m37\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">38</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m38\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">39</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m39\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">40</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m40\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m41\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">42</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m42\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">43</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m43\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">44</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m44\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">45</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m45\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">46</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m46\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">47</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m47\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m48\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m49\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">50</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m50\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">51</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m51\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m52\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">53</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m53\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">54</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m54\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">55</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m55\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">56</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m56\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">57</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m57\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">58</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m58\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">59</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m59\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">60</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m60\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">61</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m61\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">62</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m62\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">63</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m63\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m64\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">65</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m65\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">66</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m66\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">67</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m67\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">68</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m68\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">69</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m69\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">70</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m70\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m71\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">72</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m72\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">73</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m73\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m74\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">75</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m75\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">76</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m76\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">77</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m77\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">78</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m78\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">79</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m79\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">80</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m80\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">81</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m81\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">82</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m82\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">83</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m83\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">84</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m84\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">85</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m85\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">86</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m86\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">87</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m87\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">88</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m88\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">89</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m89\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">90</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m90\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m91\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">92</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m92\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">93</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m93\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">94</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m94\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">95</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m95\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">96</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m96\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">97</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m97\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">98</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m98\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">99</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m99\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">100</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m100\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">101</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m101\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">102</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m102\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">103</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m103\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">104</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m104\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">105</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m105\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">106</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m106\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">107</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m107\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">108</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m108\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">109</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m109\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">110</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m110\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">111</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m111\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">112</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m112\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">113</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m113\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">114</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m114\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">115</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m115\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">116</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m116\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">117</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m117\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">118</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m118\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">119</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m119\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">120</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m120\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">121</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m121\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">122</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m122\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">123</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m123\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">124</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m124\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">125</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m125\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">126</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m126\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">127</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m127\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">128</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m128\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">129</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m129\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">130</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m130\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">131</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m131\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">132</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m132\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">133</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m133\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">134</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m134\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">135</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m135\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">136</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m136\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">137</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m137\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">138</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m138\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">139</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m139\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">140</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m140\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">141</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m141\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">142</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m142\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">143</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m143\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">144</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m144\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">145</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m145\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">146</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m146\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">147</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m147\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">148</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m148\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">149</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m149\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">150</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m150\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">151</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m151\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">152</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m152\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">153</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m153\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">154</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m154\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">155</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m155\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">156</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m156\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">157</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m157\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">158</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m158\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">159</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m159\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">160</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m160\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">161</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m161\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">162</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m162\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">163</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m163\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">164</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m164\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">165</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m165\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">166</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m166\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">167</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m167\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">168</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m168\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">169</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m169\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">170</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m170\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">171</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m171\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">172</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m172\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">173</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m173\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m174\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">175</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m175\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">176</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m176\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">177</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m177\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">178</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m178\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m179\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">180</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m180\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">181</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m181\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">182</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m182\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m183\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">184</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m184\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">185</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m185\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">186</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m186\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">187</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m187\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">188</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m188\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">189</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m189\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">190</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m190\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">191</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m191\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">192</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m192\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">193</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m193\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">194</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m194\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">195</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m195\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">196</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m196\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">197</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m197\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">198</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m198\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">199</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m199\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">200</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m200\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">201</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m201\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">202</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m202\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">203</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m203\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">204</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m204\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">205</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m205\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">206</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m206\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">207</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m207\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">208</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m208\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">209</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m209\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">210</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m210\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">211</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m211\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">212</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m212\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">213</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m213\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">214</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m214\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">215</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m215\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">216</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m216\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">217</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m217\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m218\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">219</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m219\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">220</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m220\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">221</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m221\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">222</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m222\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">223</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m223\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">224</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m224\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">225</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m225\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">226</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m226\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">227</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m227\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">228</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m228\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">229</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m229\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">230</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m230\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">231</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m231\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m232\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">233</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m233\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">234</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m234\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">235</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m235\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">236</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m236\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">237</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m237\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">238</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m238\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">239</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m239\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">240</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m240\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">241</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m241\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">242</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m242\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">243</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m243\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">244</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m244\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">245</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m245\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">246</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m246\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">247</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m247\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">248</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m248\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">249</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m249\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">250</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m250\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">251</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m251\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">252</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m252\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">253</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m253\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">254</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m254\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">255</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m255\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">256</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m256\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">257</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m257\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">258</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m258\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">259</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m259\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">260</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m260\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">261</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m261\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">262</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m262\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">263</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m263\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">264</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m264\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">265</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m265\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">266</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m266\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">267</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m267\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">268</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m268\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">269</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m269\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">270</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m270\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">271</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m271\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">272</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m272\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">273</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m273\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">274</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m274\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">275</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m275\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">276</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m276\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">277</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m277\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">278</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m278\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">279</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m279\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">280</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m280\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">281</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m281\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">282</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m282\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">283</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m283\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">284</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m284\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">285</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m285\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">286</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m286\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">287</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m287\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">288</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m288\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">289</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m289\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">290</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m290\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">291</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m291\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">292</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m292\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">293</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m293\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">294</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m294\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m295\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m296\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m297\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m298\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m299\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m300\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">301</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m301\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">302</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m302\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">303</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m303\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">304</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m304\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">305</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m305\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">306</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m306\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">307</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m307\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">308</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m308\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">309</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m309\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">310</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m310\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">311</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m311\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">312</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m312\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">313</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m313\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">314</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m314\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">315</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m315\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">316</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m316\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">317</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m317\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">318</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m318\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">319</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m319\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">320</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m320\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">321</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m321\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">322</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m322\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">323</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m323\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">324</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m324\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">325</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m325\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">326</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m326\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">327</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m327\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">328</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m328\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">329</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m329\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">330</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m330\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">331</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m331\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">332</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m332\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">333</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m333\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">334</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m334\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">335</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m335\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">336</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m336\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">337</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m337\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">338</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m338\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">339</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m339\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">340</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m340\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">341</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m341\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">342</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m342\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">343</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m343\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">344</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m344\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">345</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m345\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">346</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m346\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">347</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m347\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">348</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m348\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">349</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m349\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">350</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m350\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">351</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m351\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">352</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m352\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">353</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m353\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">354</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m354\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">355</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m355\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">356</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m356\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">357</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m357\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">358</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m358\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">359</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m359\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">360</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m360\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">361</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m361\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">362</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m362\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">363</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m363\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">364</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m364\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">365</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m365\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">366</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m366\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">367</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m367\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">368</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m368\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">369</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m369\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">370</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m370\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">371</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m371\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">372</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m372\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">373</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m373\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">374</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m374\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">375</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m375\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">376</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m376\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">377</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m377\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">378</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m378\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">379</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m379\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">380</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m380\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">381</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m381\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">382</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m382\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">383</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m383\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">384</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m384\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">385</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m385\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">386</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m386\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">387</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m387\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">388</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m388\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">389</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m389\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">390</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m390\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">391</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m391\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">392</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m392\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">393</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m393\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">394</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m394\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">395</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m395\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">396</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m396\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">397</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m397\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">398</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m398\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">399</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m399\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">400</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m400\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">401</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m401\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">402</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m402\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">403</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m403\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">404</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m404\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">405</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m405\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">406</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m406\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">407</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m407\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">408</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m408\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">409</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m409\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">410</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m410\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">411</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m411\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">412</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m412\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">413</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m413\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">414</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m414\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">415</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m415\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">416</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m416\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">417</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m417\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">418</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m418\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">419</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m419\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">420</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m420\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">421</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m421\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">422</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m422\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">423</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m423\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">424</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m424\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">425</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m425\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">426</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m426\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">427</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m427\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">428</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m428\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">429</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m429\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">430</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m430\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">431</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m431\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">432</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m432\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">433</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m433\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">434</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m434\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">435</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m435\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">436</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m436\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">437</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m437\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">438</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m438\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">439</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m439\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">440</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m440\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">441</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m441\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">442</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m442\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">443</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m443\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">444</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m444\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">445</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m445\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">446</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m446\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">447</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m447\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">448</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m448\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">449</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m449\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">450</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m450\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m451\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">452</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m452\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">453</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m453\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">454</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m454\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">455</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m455\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">456</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m456\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">457</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m457\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">458</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m458\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">459</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m459\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">460</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m460\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">461</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m461\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">462</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m462\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">463</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m463\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">464</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m464\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">465</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m465\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">466</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m466\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">467</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m467\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">468</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m468\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">469</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m469\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">470</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m470\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">471</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m471\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">472</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m472\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">473</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m473\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">474</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m474\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">475</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m475\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">476</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m476\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">477</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m477\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">478</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m478\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">479</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m479\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">480</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m480\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">481</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m481\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">482</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m482\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">483</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m483\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">484</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m484\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">485</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m485\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">486</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m486\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">487</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m487\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">488</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m488\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">489</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m489\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">490</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m490\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">491</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m491\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">492</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m492\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">493</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m493\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">494</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m494\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">495</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m495\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">496</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m496\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">497</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m497\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">498</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m498\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">499</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m499\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">500</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m500\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">501</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m501\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">502</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m502\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">503</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m503\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">504</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m504\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">505</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m505\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">506</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m506\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">507</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m507\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">508</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m508\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">509</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m509\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">510</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m510\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">511</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m511\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">512</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m512\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">513</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m513\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">514</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m514\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">515</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m515\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">516</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m516\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">517</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m517\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">518</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m518\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">519</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m519\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">520</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m520\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">521</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m521\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">522</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m522\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">523</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m523\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">524</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m524\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">525</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m525\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">526</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m526\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">527</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m527\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">528</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m528\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">529</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m529\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">530</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m530\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">531</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m531\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">532</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m532\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">533</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m533\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">534</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m534\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">535</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m535\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">536</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m536\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">537</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m537\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">538</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m538\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">539</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m539\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">540</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m540\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">541</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m541\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">542</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m542\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">543</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m543\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">544</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m544\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">545</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m545\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">546</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m546\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">547</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m547\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">548</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m548\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">549</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m549\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">550</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m550\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">551</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m551\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">552</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m552\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">553</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m553\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">554</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m554\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">555</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m555\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">556</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m556\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">557</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m557\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">558</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m558\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">559</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m559\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">560</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m560\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">561</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m561\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">562</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m562\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">563</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m563\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">564</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m564\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">565</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m565\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">566</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m566\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">567</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m567\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">568</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m568\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">569</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m569\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">570</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m570\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">571</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m571\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">572</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m572\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">573</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m573\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">574</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m574\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">575</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m575\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">576</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m576\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">577</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m577\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">578</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m578\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">579</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m579\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">580</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m580\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">581</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m581\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">582</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m582\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">583</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m583\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">584</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m584\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">585</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m585\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">586</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m586\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">587</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m587\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">588</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m588\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">589</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m589\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">590</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m590\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">591</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m591\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">592</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m592\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">593</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m593\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">594</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m594\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m595\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m596\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m597\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m598\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m599\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m600\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = []\n",
+    "\n",
+    "# Progress bar for visualization\n",
+    "f = IntProgress(min=0, max=N)\n",
+    "display(f)\n",
+    "\n",
+    "for i in range(N):\n",
+    "    print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "    simulated = run_hbv(\n",
+    "        parameters=parameter_sets[i], \n",
+    "        initial_storages=s_0, \n",
+    "        forcing=ERA5_forcing\n",
+    "    )\n",
+    "\n",
+    "    # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "    simulated_daily = simulated\n",
+    "    observed_daily = observed_output\n",
+    "\n",
+    "    simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "    \n",
+    "    # Align simulated and observed data\n",
+    "    combined_data = pd.DataFrame(\n",
+    "        {\"Modelled discharge\": simulated_daily, \n",
+    "        \"Observed discharge\": observed_daily}\n",
+    "    ).dropna()\n",
+    "\n",
+    "    # Skip first year as warm-up\n",
+    "    combined_data = combined_data[\n",
+    "        (combined_data.index >= evaluation_start) &\n",
+    "        (combined_data.index <= calibration_end_date)\n",
+    "    ]\n",
+    "\n",
+    "    # Exclude ice-affected winter period\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([11, 12, 1, 2, 3, 4])\n",
+    "    ]\n",
+    "\n",
+    "    # Append results and drop nan\n",
+    "    if combined_data.empty:\n",
+    "        print(f\"No overlapping data for parameter set {i+1}\")\n",
+    "        nse = np.nan\n",
+    "        log_nse = np.nan\n",
+    "    else:\n",
+    "        nse = NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "        log_nse = log_NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "        \n",
+    "    results.append({\n",
+    "        \"run\": i,\n",
+    "        \"NSE\": nse,\n",
+    "        \"log_NSE\": log_nse,\n",
+    "        \"parameters\": parameter_sets[i]\n",
+    "    })"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d7b5f35-f872-4ef5-8ced-c92cdd81c8f8",
+   "metadata": {},
+   "source": [
+    "### Display best results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "4c69f827-adda-4ec9-8863-abf0ba31e0d2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">     run       NSE   log_NSE\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.288376</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.337195</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.279102</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.480497</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.384565</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.462463</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.085379</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.265060</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.118825</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.395402</span>\n",
+       "..   <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378628</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.445890</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.190509</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.402412</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.034397</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.105571</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.174568</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.090100</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.379411</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.461890</span>\n",
+       "\n",
+       "<span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span> rows x <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span> columns<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "     run       NSE   log_NSE\n",
+       "\u001b[1;36m0\u001b[0m      \u001b[1;36m0\u001b[0m  \u001b[1;36m0.288376\u001b[0m  \u001b[1;36m0.337195\u001b[0m\n",
+       "\u001b[1;36m1\u001b[0m      \u001b[1;36m1\u001b[0m  \u001b[1;36m0.279102\u001b[0m  \u001b[1;36m0.480497\u001b[0m\n",
+       "\u001b[1;36m2\u001b[0m      \u001b[1;36m2\u001b[0m  \u001b[1;36m0.384565\u001b[0m  \u001b[1;36m0.462463\u001b[0m\n",
+       "\u001b[1;36m3\u001b[0m      \u001b[1;36m3\u001b[0m \u001b[1;36m-0.085379\u001b[0m  \u001b[1;36m0.265060\u001b[0m\n",
+       "\u001b[1;36m4\u001b[0m      \u001b[1;36m4\u001b[0m  \u001b[1;36m0.118825\u001b[0m  \u001b[1;36m0.395402\u001b[0m\n",
+       "..   \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m\n",
+       "\u001b[1;36m595\u001b[0m  \u001b[1;36m595\u001b[0m  \u001b[1;36m0.378628\u001b[0m  \u001b[1;36m0.445890\u001b[0m\n",
+       "\u001b[1;36m596\u001b[0m  \u001b[1;36m596\u001b[0m  \u001b[1;36m0.190509\u001b[0m  \u001b[1;36m0.402412\u001b[0m\n",
+       "\u001b[1;36m597\u001b[0m  \u001b[1;36m597\u001b[0m  \u001b[1;36m0.034397\u001b[0m \u001b[1;36m-0.105571\u001b[0m\n",
+       "\u001b[1;36m598\u001b[0m  \u001b[1;36m598\u001b[0m  \u001b[1;36m0.174568\u001b[0m  \u001b[1;36m0.090100\u001b[0m\n",
+       "\u001b[1;36m599\u001b[0m  \u001b[1;36m599\u001b[0m  \u001b[1;36m0.379411\u001b[0m  \u001b[1;36m0.461890\u001b[0m\n",
+       "\n",
+       "\u001b[1m[\u001b[0m\u001b[1;36m600\u001b[0m rows x \u001b[1;36m3\u001b[0m columns\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span> with NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5042075946097913</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m232\u001b[0m with NSE: \u001b[1;36m0.5042075946097913\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.488362330365561</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4845571293512798</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218.83336737778694</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.7699130278847444</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1358146729030282</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.44235281882723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.04585512368848791</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.008840391568068273</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8983450417631202</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.488362330365561\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.4845571293512798\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m218.83336737778694\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.7699130278847444\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.1358146729030282\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.44235281882723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.04585512368848791\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.008840391568068273\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.8983450417631202\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span> with log_NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5985790718618934</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m451\u001b[0m with log_NSE: \u001b[1;36m0.5985790718618934\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.9919295474161505</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.44128061023639964</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183.49045936834898</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.62907119850059</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5726586861631707</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.2154764587256395</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06546844116401723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0025930490563726475</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.1427426360454793</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.9919295474161505\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.44128061023639964\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m183.49045936834898\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.62907119850059\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.5726586861631707\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.2154764587256395\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.06546844116401723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.0025930490563726475\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.1427426360454793\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = pd.DataFrame(results)\n",
+    "\n",
+    "print(results[[\"run\", \"NSE\", \"log_NSE\"]])\n",
+    "\n",
+    "# # Best NSE\n",
+    "# best_run_nse = results[\"NSE\"].idxmax()\n",
+    "# best_result_nse = results.loc[best_run_nse]\n",
+    "\n",
+    "# best_parameters_nse = best_result_nse[\"parameters\"]\n",
+    "# best_nse = best_result_nse[\"NSE\"]\n",
+    "\n",
+    "# print(f'Best run: {best_run_nse} with NSE: {best_nse}, with parameters:')\n",
+    "# print(list(zip(parameter_names, best_parameters_nse)))\n",
+    "\n",
+    "# Best log_NSE\n",
+    "best_run_log_nse = results[\"log_NSE\"].idxmax()\n",
+    "best_result_log_nse = results.loc[best_run_log_nse]\n",
+    "\n",
+    "best_parameters_log_nse = best_result_log_nse[\"parameters\"]\n",
+    "best_log_nse = best_result_log_nse[\"log_NSE\"]\n",
+    "\n",
+    "print(f'Best run: {best_run_log_nse} with log_NSE: {best_log_nse}, with parameters:')\n",
+    "print(list(zip(parameter_names, best_parameters_log_nse)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "bb2f1f27-9a79-41fa-b416-e32bbee15075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5985790718618934</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m1\u001b[0m: run \u001b[1;36m451\u001b[0m with LNSE: \u001b[1;36m0.5985790718618934\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.9919295474161505</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.44128061023639964</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183.49045936834898</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.62907119850059</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5726586861631707</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.2154764587256395</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06546844116401723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0025930490563726475</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.1427426360454793</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.9919295474161505\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.44128061023639964\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m183.49045936834898\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.62907119850059\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.5726586861631707\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.2154764587256395\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.06546844116401723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.0025930490563726475\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.1427426360454793\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">193</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5871245105302814</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m2\u001b[0m: run \u001b[1;36m193\u001b[0m with LNSE: \u001b[1;36m0.5871245105302814\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.882658193683639</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.47241275652770587</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">194.30386240959916</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.781621276884348</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4608178778064105</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.215364575839981</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06419932503784231</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.015979806886031615</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0919722363345776</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m5.882658193683639\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.47241275652770587\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m194.30386240959916\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.781621276884348\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.4608178778064105\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.215364575839981\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.06419932503784231\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.015979806886031615\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.0919722363345776\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5802931655594039</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m3\u001b[0m: run \u001b[1;36m71\u001b[0m with LNSE: \u001b[1;36m0.5802931655594039\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.279358279165555</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.45738099679628363</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218.06826364855027</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.8389403651683596</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.49366891001367486</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.037707687593043</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.07007118899924838</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.024409700594446738</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.2556224532809368</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.279358279165555\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.45738099679628363\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m218.06826364855027\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.8389403651683596\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.49366891001367486\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.037707687593043\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.07007118899924838\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.024409700594446738\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.2556224532809368\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">152</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5697643546613578</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m4\u001b[0m: run \u001b[1;36m152\u001b[0m with LNSE: \u001b[1;36m0.5697643546613578\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.301551796430246</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.49391712556044987</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">211.00486173599964</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9612109256650778</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.46785716423961</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.467897643950326</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.055226399867357515</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.03429434734237983</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.191697747701756</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m7.301551796430246\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.49391712556044987\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m211.00486173599964\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.9612109256650778\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.46785716423961\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.467897643950326\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.055226399867357515\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.03429434734237983\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.191697747701756\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5666729995545778</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m5\u001b[0m: run \u001b[1;36m232\u001b[0m with LNSE: \u001b[1;36m0.5666729995545778\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.488362330365561</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4845571293512798</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218.83336737778694</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.7699130278847444</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1358146729030282</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.44235281882723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.04585512368848791</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.008840391568068273</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8983450417631202</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.488362330365561\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.4845571293512798\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m218.83336737778694\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.7699130278847444\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.1358146729030282\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.44235281882723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.04585512368848791\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.008840391568068273\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.8983450417631202\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get ensemble \n",
+    "\n",
+    "best_5_runs = results[\"log_NSE\"].nlargest(5).index\n",
+    "\n",
+    "best_5_parameters = []\n",
+    "best_5_LNSE = []\n",
+    "\n",
+    "for i in range(len(best_5_runs)):\n",
+    "\n",
+    "    run = best_5_runs[i]\n",
+    "    result = results.loc[run]\n",
+    "\n",
+    "    parameters = result[\"parameters\"]\n",
+    "    lnse = result[\"log_NSE\"]\n",
+    "\n",
+    "    best_5_parameters.append(parameters)\n",
+    "    best_5_LNSE.append(log_nse)\n",
+    "\n",
+    "    print(f\"Rank {i+1}: run {run} with LNSE: {lnse}\")\n",
+    "    print(list(zip(parameter_names, parameters)))\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "127ab139-2d7a-43ad-b012-11188e931c9c",
+   "metadata": {},
+   "source": [
+    "### Plot Observed vs Modelled"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "aeb2ea7e-9826-450f-880e-e1e5e72c9dba",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Overall Plot\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "simulated_calibrated_nse = run_hbv(\n",
+    "    parameters=best_parameters_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "simulated_calibrated_log_nse = run_hbv(\n",
+    "    parameters=best_parameters_log_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "# Align dates\n",
+    "simulated_plot_nse = simulated_calibrated_nse\n",
+    "simulated_plot_log_nse = simulated_calibrated_log_nse\n",
+    "observed_plot = observed_output\n",
+    "\n",
+    "simulated_plot_nse.index = pd.to_datetime(simulated_plot_nse.index).tz_localize(None).normalize()\n",
+    "simulated_plot_log_nse.index = pd.to_datetime(simulated_plot_log_nse.index).tz_localize(None).normalize()\n",
+    "observed_plot.index = pd.to_datetime(observed_plot.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Combine modelled and observed data\n",
+    "plot_data = pd.DataFrame({\n",
+    "    \"Modelled discharge NSE\": simulated_plot_nse,\n",
+    "    \"Modelled discharge log_NSE\": simulated_plot_log_nse,\n",
+    "    \"Observed discharge\": observed_plot\n",
+    "}).dropna()\n",
+    "\n",
+    "# Calculate NSE & log NSE for plotted data\n",
+    "plot_nse = NSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "plot_log_nse = log_NSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\")\n",
+    "# plt.plot(plot_data.index, plot_data[\"Modelled discharge NSE\"], label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data.index, plot_data[\"Modelled discharge log_NSE\"], label=\"Modelled discharge log_NSE\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001, NSE = {best_nse:.3f}, log NSE = {best_log_nse:.3f}\")\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f'Critical discharge ({q_critical} m³/s', color='black')\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "e0743eb6-3efd-435c-866f-d0ea2bddfea8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for 1 year\n",
+    "\n",
+    "selected_year = 2015\n",
+    "\n",
+    "plot_data_year = plot_data[plot_data.index.year == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Observed discharge\"],label=\"Observed discharge\")\n",
+    "# plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge NSE\"],label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge log_NSE\"],label=\"Modelled discharge log_NSE\", color=\"green\")\n",
+    "\n",
+    "plt.axhline(y=q_critical,linestyle=\":\",color=\"black\",label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001 in {selected_year}\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "dde634ea-53bd-4c41-ba13-8ec762014b89",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">RMSE for best NSE parameter set: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52.403</span> m³/s\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "RMSE for best NSE parameter set: \u001b[1;36m52.403\u001b[0m m³/s\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">RMSE for best log_NSE parameter set: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64.551</span> m³/s\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "RMSE for best log_NSE parameter set: \u001b[1;36m64.551\u001b[0m m³/s\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Calculate RMSE for best parameter sets NSE and log_NSE\n",
+    "\n",
+    "rmse_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "rmse_log_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "print(f\"RMSE for best NSE parameter set: {rmse_nse:.3f} m³/s\")\n",
+    "print(f\"RMSE for best log_NSE parameter set: {rmse_log_nse:.3f} m³/s\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "db083f00-6ca7-47a1-8792-c46df17f15ed",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Step4_HBV_Validation_Ensemble.ipynb b/Workyard/Step4_HBV_Validation_Ensemble.ipynb
new file mode 100644
index 00000000..72c8021c
--- /dev/null
+++ b/Workyard/Step4_HBV_Validation_Ensemble.ipynb
@@ -0,0 +1,1107 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9ca8fd44-6292-4af4-9100-d3256fccd960",
+   "metadata": {},
+   "source": [
+    "# Ensemble validation\n",
+    "\n",
+    "The 5 parameter sets calculkated in Calibration_HBV.ipynb will be used for a validation period, in which the log NSE will be calculated, a mean will be calculated and total low flow days during the navigation season.\n",
+    "\n",
+    "The structure of this notebook is as follows:\n",
+    "\n",
+    "### 1. Startup\n",
+    "### 2. Model Setup\n",
+    "### 3. Running model\n",
+    "### 4. LNSE calculation\n",
+    "### 5. Display results\n",
+    "### 6. Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdb4216e-a341-4c2b-a410-35170773a9a7",
+   "metadata": {},
+   "source": [
+    "## 1. Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "d197b8f0-0f85-4a41-b2fb-1b2a8cf3f9f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "dd7b7d3f-1489-4723-bb51-f3cffcb7a85c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "1c8aee93-b2d6-4291-89ae-1d29e69268cd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d7dce039-d1f3-44a0-b646-98c32ecffb28",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "experiment_start_date = \"2019-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2024-12-31T00:00:00Z\"\n",
+    "\n",
+    "validation_start = \"1999-01-01T00:00:00Z\"\n",
+    "validation_end = \"2019-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "d330bf37-7419-4287-81af-3d09e4c7a30e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "15ea4507-f559-4ef8-9756-60b8502064d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Create pathways for ERA 5 forcings\n",
+    "\n",
+    "# forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"forcings\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "# discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "# hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "46ea8b1e-fb73-49ed-855c-4d95cd932748",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "8bb224ad-d23c-475f-b6af-4a6023a17044",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs to relevant dates\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= validation_start_date) & (q_obs[\"Date\"] <= validation_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "fc27f6f8-e7ff-4be6-b073-05006d25426a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date\n",
+       "1999-01-01    104.0\n",
+       "1999-01-02    103.0\n",
+       "1999-01-03    101.0\n",
+       "1999-01-04    103.0\n",
+       "1999-01-05    105.0\n",
+       "Name: Observed discharge, dtype: float64"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "observed_output.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "7f6f57aa-9f39-4524-ba3a-34f55035ebab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"])\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a48b5085-6478-4cf2-bd02-75b75f82e90f",
+   "metadata": {},
+   "source": [
+    "### Generate/Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "77e79b20-3e4d-405a-bd88-16bdc50bdb39",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1999-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1999-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2019-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "09f9dfb3-40c9-4689-98b8-fd1ea8fd72d1",
+   "metadata": {},
+   "source": [
+    "### Load parameter sets & initial storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "ca2be146-1112-4806-a44f-d57ebd4442c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "# par_0 = [4.45787, 0.42307, 201.57602, 2.36497, 0.26755, 8.62964, 0.083568, 0.0037073, 0.29645]\n",
+    "# par_0 = [2.79874, 0.49211, 255.96478, 1.782968, 0.503199, 6.095956, 0.33279, 0.10539, 0.63857]\n",
+    "# par_0 = [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606]         # 0.725 val, 0.x cal - Fav run 2\n",
+    "# par_0 = [6.28908, 0.423917, 173.56627, 1.63144, 0.402586, 6.56151, 0.0456809, 0.00313744, 0.516696]                 # 0.702 val, 0.x cal\n",
+    "# par_0 = [6.4919, 0.386877, 221.78625, 1.388269, 0.276453, 4.9870704, 0.04126777, 0.05640195, 1.148877]              # 0.668 val, 0.x cal\n",
+    "# par_0 = [7.502398, 0.38028, 194.1899, 1.680197, 0.47956, 4.8566806, 0.041745354, 0.02833896, 1.051862]              # 0.677 val, 0.x cal\n",
+    "# par_0 = [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392]                        # 0.781 val, 0.776 cal\n",
+    "# par_0 = [6.16512, 0.4369419, 151.2515900, 1.727835, 0.3771705, 6.19265974, 0.06959136, 0.001310818, 0.8130732]      # 0.664 val, 0.791 cal\n",
+    "# par_0 = [5.7107, 0.441634, 172.81305, 1.87367, 0.588802, 5.498147, 0.060305, 0.019666, 1.2011814]                    # x val, 0.73 cal         Start of 5+ months exclusion\n",
+    "# par_0 = [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504]                    # 0.82 val, 0.818 cal - Fav run 1      \n",
+    "# par_0 = [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]                    #  val,  0.77 cal    \n",
+    "# par_0 = [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857]                           # 0.78 val, 0.71 cal - potential inclusion\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]\n",
+    "]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"          # Snowmelt factor\n",
+    "               ]\n",
+    "\n",
+    "# Initial: par_0 = [5.085, 0.55, 100.373, 1.612, 0.545, 3.801, 0.196, 0.00, 0.185]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "d5e5bcb4-bf90-470b-90ed-4a0b9d80c35d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "06c977b4-ba9d-4e82-8415-42180eac9f01",
+   "metadata": {},
+   "source": [
+    "## 2. Model setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "055bdbc8-af1f-41ac-ad1d-b4da4d6785f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config\n",
+    "    )\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\"\n",
+    "    )\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "650daf1f-e90f-4b5b-aac5-eca8965de7cf",
+   "metadata": {},
+   "source": [
+    "## 3. Running model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "44092959-524a-4330-a274-77cfad0eacd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing\n",
+    "        )\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Filter observed data by day\n",
+    "    observed_daily = observed_output\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "    ensemble_data['Observed discharge'] = observed_daily\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "079368de-30cf-491f-8cc9-2021f6a4bfa6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set 1</th>\n",
+       "      <th>Set 2</th>\n",
+       "      <th>Set 3</th>\n",
+       "      <th>Set 4</th>\n",
+       "      <th>Set 5</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Observed discharge</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1999-01-02</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>103.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999-01-03</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>101.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999-01-04</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>103.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999-01-05</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>105.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999-01-06</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>108.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Set 1  Set 2  Set 3  Set 4  Set 5  Mean  Observed discharge\n",
+       "1999-01-02    0.0    0.0    0.0    0.0    0.0   0.0               103.0\n",
+       "1999-01-03    0.0    0.0    0.0    0.0    0.0   0.0               101.0\n",
+       "1999-01-04    0.0    0.0    0.0    0.0    0.0   0.0               103.0\n",
+       "1999-01-05    0.0    0.0    0.0    0.0    0.0   0.0               105.0\n",
+       "1999-01-06    0.0    0.0    0.0    0.0    0.0   0.0               108.0"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ensemble_data = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "ensemble_data.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "96d6162f-f432-4dfc-9194-f522a2e6a6da",
+   "metadata": {},
+   "source": [
+    "## 4. LNSE Calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "37567a9e-dff3-4c80-84e0-572a6ed72b68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate log NSE\n",
+    "\n",
+    "def LNSE(sim, obs):\n",
+    "    \n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "dc7850a4-dc30-4aa7-8719-4f810760c320",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call log NSE for relevant timeperiod\n",
+    "\n",
+    "def lnse_ensemble(ensemble_data, lnse_start, lnse_end):\n",
+    "\n",
+    "    # Select evaluation period - skip first year for storages to fill\n",
+    "    combined_data = ensemble_data[\n",
+    "        (ensemble_data.index >= lnse_start) &\n",
+    "        (ensemble_data.index <= lnse_end)\n",
+    "    ].dropna()\n",
+    "\n",
+    "    # Exclude winter months\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])\n",
+    "    ]\n",
+    "\n",
+    "    lnse_results = []\n",
+    "\n",
+    "    # Calculate LNSE for all sets\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        lnse_value = LNSE(\n",
+    "            combined_data[f\"Set {i+1}\"],\n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "\n",
+    "        # Append LNSE\n",
+    "        lnse_results.append({\n",
+    "            \"Set\": f\"Set {i+1}\",\n",
+    "            \"LNSE\": lnse_value\n",
+    "        })\n",
+    "\n",
+    "    # Calculate LNSE of ensemble mean\n",
+    "    mean_lnse = LNSE(\n",
+    "        combined_data[\"Mean\"],\n",
+    "        combined_data[\"Observed discharge\"]\n",
+    "    )\n",
+    "\n",
+    "    # Append LNSE\n",
+    "    lnse_results.append({\n",
+    "        \"Set\": \"Ensemble mean\",\n",
+    "        \"LNSE\": mean_lnse\n",
+    "    })\n",
+    "\n",
+    "    lnse_results = pd.DataFrame(lnse_results)\n",
+    "\n",
+    "    return lnse_results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "80962ebd-6ad7-48ce-b378-acd68ed03a1e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set</th>\n",
+       "      <th>LNSE</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Set 1</td>\n",
+       "      <td>0.644561</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Set 2</td>\n",
+       "      <td>0.716547</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Set 3</td>\n",
+       "      <td>0.708634</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Set 4</td>\n",
+       "      <td>0.661621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Set 5</td>\n",
+       "      <td>0.677477</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Ensemble mean</td>\n",
+       "      <td>0.739374</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             Set      LNSE\n",
+       "0          Set 1  0.644561\n",
+       "1          Set 2  0.716547\n",
+       "2          Set 3  0.708634\n",
+       "3          Set 4  0.661621\n",
+       "4          Set 5  0.677477\n",
+       "5  Ensemble mean  0.739374"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lnse_results = lnse_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    lnse_start=evaluation_start,\n",
+    "    lnse_end=validation_end_date\n",
+    ")\n",
+    "\n",
+    "lnse_results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9b6a719-39c6-4872-87ff-cdb65d853e42",
+   "metadata": {},
+   "source": [
+    "## 5. Display results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "f519854a-a994-44fd-a428-4d0c6daa98e1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_ensemble(ensemble_data, plot_start, plot_end):\n",
+    "\n",
+    "    plot_start = pd.to_datetime(plot_start)\n",
+    "    plot_end = pd.to_datetime(plot_end)\n",
+    "\n",
+    "    # Filter data to start & end time\n",
+    "    plot_data = ensemble_data[\n",
+    "        (ensemble_data.index >= plot_start) &\n",
+    "        (ensemble_data.index <= plot_end)\n",
+    "    ].dropna()\n",
+    "\n",
+    "    # Define figure\n",
+    "    plt.figure()\n",
+    "    plt.figure(figsize=(20, 8))\n",
+    "\n",
+    "    # Plot sets, observed data, ensemble mean and axhline, respectively\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        plt.plot(plot_data.index, plot_data[f\"Set {i+1}\"], color=\"orange\", alpha=0.3, label=\"Parameter sets\" if i == 0 else None)\n",
+    "\n",
+    "    plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\", linewidth=3)\n",
+    "    plt.plot(plot_data.index, plot_data[\"Mean\"], label=\"Ensemble mean\", linewidth=3)\n",
+    "    plt.axhline(y=q_critical, linestyle=\":\", color=\"black\", label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "    # Extras\n",
+    "    plt.xlabel(\"Date\")\n",
+    "    plt.ylabel(\"Discharge (m³/s)\")\n",
+    "    plt.title(\"Observed vs modelled ensemble discharge at 07DA001\")\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "f1bb58f8-3dee-43eb-abc8-4af333b5d064",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for full evaluation period\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=evaluation_start,\n",
+    "    plot_end=validation_end_date\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "b835010a-b272-46b7-9c20-b0db1a99506b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2012\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d017577d-79da-4a97-9522-81f4c307f3aa",
+   "metadata": {},
+   "source": [
+    "## 6. Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "dcc14e37-5aea-4b00-ae71-32b68ee03d4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_counter_ensemble(ensemble_data, start_date, end_date):\n",
+    "    \n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "    \n",
+    "        year = years[i]\n",
+    "    \n",
+    "        # Define start and end month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "    \n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        # Set zeros to count from\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = []\n",
+    "        modelmean_lowflow_days = 0\n",
+    "\n",
+    "        # Count observed lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "        # Count model mean lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "\n",
+    "            modelmean_q = year_data.iloc[j][\"Mean\"]\n",
+    "\n",
+    "            if modelmean_q < q_critical:\n",
+    "                modelmean_lowflow_days += 1\n",
+    "\n",
+    "        # Count modelled lowflow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "        \n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"observed\": observed_lowflow_days,\n",
+    "            \"modelmean\": modelmean_lowflow_days,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)\n",
+    "        })\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "7460b853-5619-44c9-ac89-3c6fc099bde6",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'ensemble_data' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[2], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m lowflow_counter_ensemble(\n\u001b[0;32m----> 2\u001b[0m     ensemble_data\u001b[38;5;241m=\u001b[39m\u001b[43mensemble_data\u001b[49m,\n\u001b[1;32m      3\u001b[0m     start_date\u001b[38;5;241m=\u001b[39mevaluation_start,\n\u001b[1;32m      4\u001b[0m     end_date\u001b[38;5;241m=\u001b[39mvalidation_end_date\n\u001b[1;32m      5\u001b[0m )\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'ensemble_data' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "02d8a545-838c-4da5-9935-22f34d49f4ee",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4dd215db-3fbe-44fa-9c07-26f13e64d255",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a08ca3c-9f66-4797-b4eb-7943785f512d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "efc2756c-f047-4ae1-a491-583e46612a75",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Step5_QDM_Experiment3.ipynb b/Workyard/Step5_QDM_Experiment3.ipynb
new file mode 100644
index 00000000..5723493c
--- /dev/null
+++ b/Workyard/Step5_QDM_Experiment3.ipynb
@@ -0,0 +1,2057 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6dc674b5-d3fe-40e6-80e3-ed1f78221490",
+   "metadata": {},
+   "source": [
+    "# 2. Quantile delta mapping of CMIP6 forcing\n",
+    "\n",
+    "This notebook applies **monthly quantile delta mapping (QDM)** to historical CMIP6 forcing.\n",
+    "\n",
+    "For now, the target period is also historical CMIP6 **1995–2014**. This is useful for testing whether bias-corrected CMIP6 forcing improves the HBV discharge output.\n",
+    "\n",
+    "Inputs:\n",
+    "\n",
+    "- ERA5 forcing 1995–2014 = reference\n",
+    "- CMIP6 historical forcing 1995–2014 = historical model\n",
+    "- CMIP6 historical forcing 1995–2014 = target model for testing\n",
+    "\n",
+    "Output:\n",
+    "\n",
+    "- Corrected CMIP6 forcing folder: `CMIP6-QDM-historical-1995-2014`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7c03cdaf-99e5-46d8-ba07-2843f1c07fc2",
+   "metadata": {},
+   "source": [
+    "## 1. Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "id": "43b2105a-222a-467b-90ae-1733bd907045",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# pip install python-cmethods"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "id": "1fb67b48-9bc2-4150-b724-c1d26291db0b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import xarray as xr\n",
+    "import yaml\n",
+    "from cmethods import adjust\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "id": "6a8d479a-11bd-453b-b1fd-5a454f46770c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ewatercycle\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "id": "05206528-dd3b-45ef-a538-be2dcba07085",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "start_year = 1995\n",
+    "end_year = 2014\n",
+    "\n",
+    "Scenario = \"historical\""
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "56e6454a-306c-44fa-86c5-2ef6afcc389c",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "id": "eeedfb4b-e1f4-4fbb-b5ba-de342f59bddf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ERA5-1995-2014</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/\u001b[0m\u001b[95mERA5-1995-2014\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6-1995-2014</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/\u001b[0m\u001b[95mCMIP6-1995-2014\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6-QDM-1995-2014</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/\u001b[0m\u001b[95mCMIP6-QDM-1995-2014\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining paths\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / f\"ERA5-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_CMIP = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"historical\" / f\"CMIP6-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_CMIP_target = forcing_path_CMIP\n",
+    "forcing_path_CMIP_hist = forcing_path_CMIP\n",
+    "\n",
+    "forcing_path_QDM = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"historical\" / f\"CMIP6-QDM-{start_year}-{end_year}\"\n",
+    "forcing_path_QDM.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "print(forcing_path_ERA5)\n",
+    "print(forcing_path_CMIP_hist)\n",
+    "print(forcing_path_QDM)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "540c0e8c-52ab-4f28-be4e-ccccb35d7d31",
+   "metadata": {},
+   "source": [
+    "## 2. Helper functions for loading forcing variables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "id": "2f524b1b-ee16-49d9-ba70-0bd783d18895",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_file_for_var(folder, var_name):\n",
+    "\n",
+    "    folder = Path(folder)\n",
+    "\n",
+    "    # First try exact final variable pattern, then broader search\n",
+    "    matches = list(folder.glob(f\"*_{var_name}.nc\"))\n",
+    "\n",
+    "    if len(matches) == 0:\n",
+    "        matches = list(folder.glob(f\"*{var_name}*.nc\"))\n",
+    "\n",
+    "    if len(matches) == 0:\n",
+    "        raise FileNotFoundError(f\"No NetCDF file found for {var_name} in {folder}\")\n",
+    "\n",
+    "    if len(matches) > 1:\n",
+    "        print(f\"Multiple files found for {var_name}, using first:\")\n",
+    "        for match in matches:\n",
+    "            print(\" -\", match.name)\n",
+    "\n",
+    "    return matches[0]\n",
+    "\n",
+    "\n",
+    "def get_dataarray(dataset, preferred_name):\n",
+    "\n",
+    "    if preferred_name in dataset.data_vars:\n",
+    "        return dataset[preferred_name]\n",
+    "\n",
+    "    first_var = list(dataset.data_vars)[0]\n",
+    "    print(f\"Variable {preferred_name} not found, using {first_var} instead.\")\n",
+    "    return dataset[first_var]\n",
+    "\n",
+    "\n",
+    "def load_variable(folder, var_name):\n",
+    "\n",
+    "    file_path = find_file_for_var(folder, var_name)\n",
+    "\n",
+    "    ds = xr.open_dataset(file_path)\n",
+    "    da = get_dataarray(ds, var_name).squeeze()\n",
+    "    \n",
+    "        # Normalize daily time coordinate: removes 11:30 / 12:00 differences\n",
+    "    da = da.assign_coords(time=pd.to_datetime(da.time.values).normalize())\n",
+    "\n",
+    "    if \"time\" not in da.dims:\n",
+    "        raise ValueError(f\"{file_path} does not contain a time dimension.\")\n",
+    "\n",
+    "    return da, ds, file_path\n",
+    "\n",
+    "\n",
+    "def check_variable_shapes():\n",
+    "\n",
+    "    for var_name in var_names:\n",
+    "\n",
+    "        era5_da, _, era5_file = load_variable(forcing_path_ERA5, var_name)\n",
+    "        cmip_da, _, cmip_file = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "\n",
+    "        print(\"\\n\", var_name)\n",
+    "        print(\"ERA5:\", era5_da.shape, era5_da.dims, era5_file.name)\n",
+    "        print(\"CMIP:\", cmip_da.shape, cmip_da.dims, cmip_file.name)\n",
+    "        print(\"ERA5 units:\", era5_da.attrs.get(\"units\"))\n",
+    "        print(\"CMIP units:\", cmip_da.attrs.get(\"units\"))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "id": "919cf33d-dd3f-4762-a858-414a00a798f6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       " pr\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       " pr\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_ERA5_1995_2014_pr.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_ERA5_1995_2014_pr.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_CMIP6_1995_2014_pr.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_CMIP6_1995_2014_pr.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5 units: kg m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> s-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5 units: kg m-\u001b[1;36m2\u001b[0m s-\u001b[1;36m1\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP units: kg m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> s-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP units: kg m-\u001b[1;36m2\u001b[0m s-\u001b[1;36m1\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       " tas\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       " tas\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_ERA5_1995_2014_tas.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_ERA5_1995_2014_tas.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_CMIP6_1995_2014_tas.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_CMIP6_1995_2014_tas.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5 units: K\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5 units: K\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP units: K\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP units: K\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       " rsds\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       " rsds\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_ERA5_1995_2014_rsds.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_ERA5_1995_2014_rsds.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_CMIP6_1995_2014_rsds.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_CMIP6_1995_2014_rsds.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5 units: W m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5 units: W m-\u001b[1;36m2\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP units: W m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP units: W m-\u001b[1;36m2\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       " evspsblpot\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       " evspsblpot\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_ERA5_1995_2014_evspsblpot.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_ERA5_1995_2014_evspsblpot.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_CMIP6_1995_2014_evspsblpot.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_CMIP6_1995_2014_evspsblpot.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5 units: kg m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> s-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5 units: kg m-\u001b[1;36m2\u001b[0m s-\u001b[1;36m1\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP units: kg m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> s-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP units: kg m-\u001b[1;36m2\u001b[0m s-\u001b[1;36m1\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "check_variable_shapes()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "63b2e743-44cb-4605-b3fc-644720ec28e1",
+   "metadata": {},
+   "source": [
+    "## 4. Bias-correction settings\n",
+    "\n",
+    "For this version, the correction is done with `cmethods.adjust(method=\"quantile_delta_mapping\")`.\n",
+    "\n",
+    "- `tas`: additive correction (`kind=\"+\"`)\n",
+    "- `pr`, `rsds`, `evspsblpot`: multiplicative correction (`kind=\"*\"`)\n",
+    "- Negative corrected values are removed for non-temperature variables.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "id": "a04adad4-5518-4f51-a95e-2d9bb71cf397",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "method = \"quantile_delta_mapping\"\n",
+    "n_quantiles = 250\n",
+    "\n",
+    "def correction_kind(var_name):\n",
+    "    if var_name == \"tas\":\n",
+    "        return \"+\"\n",
+    "    else:\n",
+    "        return \"*\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "id": "cb6bfd86-81fe-4257-861f-a3a20c7a2627",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def monthly_qdm(obs_da, simh_da, simp_da, var_name):\n",
+    "\n",
+    "    corrected_months = []\n",
+    "\n",
+    "    kind = correction_kind(var_name)\n",
+    "\n",
+    "    for month in range(1, 13):\n",
+    "\n",
+    "        obs_m = obs_da.sel(time=obs_da.time.dt.month == month)\n",
+    "        simh_m = simh_da.sel(time=simh_da.time.dt.month == month)\n",
+    "        simp_m = simp_da.sel(time=simp_da.time.dt.month == month)\n",
+    "\n",
+    "        # Save original target time\n",
+    "        simp_time = simp_m.time\n",
+    "\n",
+    "        # Reset time index so cmethods does not require exact same dates\n",
+    "        obs_m = obs_m.assign_coords(time=np.arange(len(obs_m.time)))\n",
+    "        simh_m = simh_m.assign_coords(time=np.arange(len(simh_m.time)))\n",
+    "        simp_m = simp_m.assign_coords(time=np.arange(len(simp_m.time)))\n",
+    "\n",
+    "        corrected_m = adjust(\n",
+    "            method=method,\n",
+    "            obs=obs_m.astype(\"float64\"),\n",
+    "            simh=simh_m.astype(\"float64\"),\n",
+    "            simp=simp_m.astype(\"float64\"),\n",
+    "            n_quantiles=n_quantiles,\n",
+    "            kind=kind,\n",
+    "        )\n",
+    "\n",
+    "        if isinstance(corrected_m, xr.Dataset):\n",
+    "            corrected_m = corrected_m[var_name]\n",
+    "\n",
+    "        # Put original dates back\n",
+    "        corrected_m = corrected_m.assign_coords(time=simp_time)\n",
+    "\n",
+    "        corrected_months.append(corrected_m)\n",
+    "\n",
+    "    corrected_da = xr.concat(corrected_months, dim=\"time\")\n",
+    "    corrected_da = corrected_da.sortby(\"time\")\n",
+    "\n",
+    "    corrected_da.name = var_name\n",
+    "\n",
+    "    if var_name != \"tas\":\n",
+    "        corrected_da = corrected_da.clip(min=0)\n",
+    "\n",
+    "    return corrected_da.astype(\"float32\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "id": "d4e73e16-e4e6-4202-9901-2fe271f40390",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def derive_monthly_pr_thresholds(reference_pr, corrected_pr, dry_threshold_mm_day=0.1):\n",
+    "\n",
+    "    thresholds = {}\n",
+    "\n",
+    "    ref = to_series(reference_pr) * 86400\n",
+    "    qdm = to_series(corrected_pr) * 86400\n",
+    "\n",
+    "    for month in range(1, 13):\n",
+    "\n",
+    "        ref_m = ref[ref.index.month == month]\n",
+    "        qdm_m = qdm[qdm.index.month == month]\n",
+    "\n",
+    "        # Fraction of dry days in ERA5\n",
+    "        dry_fraction = (ref_m < dry_threshold_mm_day).mean()\n",
+    "\n",
+    "        # QDM precipitation threshold giving same dry-day fraction\n",
+    "        qdm_threshold_mm_day = qdm_m.quantile(dry_fraction)\n",
+    "\n",
+    "        # Convert back to kg m-2 s-1\n",
+    "        thresholds[month] = qdm_threshold_mm_day / 86400\n",
+    "\n",
+    "    return thresholds\n",
+    "\n",
+    "\n",
+    "def apply_monthly_pr_thresholds(pr_da, thresholds):\n",
+    "\n",
+    "    pr_new = pr_da.copy()\n",
+    "\n",
+    "    for month in range(1, 13):\n",
+    "\n",
+    "        month_mask = pr_new.time.dt.month == month\n",
+    "        threshold = thresholds[month]\n",
+    "\n",
+    "        pr_new = pr_new.where(\n",
+    "            ~(month_mask & (pr_new < threshold)),\n",
+    "            0\n",
+    "        )\n",
+    "\n",
+    "    return pr_new"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c21c46dd-a15a-4619-b917-00971ad9c576",
+   "metadata": {},
+   "source": [
+    "## 5. Apply bias correction and save NetCDF files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "id": "78bc5fe6-bc7e-4d1a-b9d2-5d654f49e9c4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def bias_correct_variable(var_name):\n",
+    "\n",
+    "    print(f\"\\nCorrecting {var_name}\")\n",
+    "\n",
+    "    # ERA5 = observed/reference historical period\n",
+    "    obs_da, obs_ds, obs_file = load_variable(forcing_path_ERA5, var_name)\n",
+    "\n",
+    "    # CMIP historical = model historical/control period\n",
+    "    simh_da, simh_ds, simh_file = load_variable(forcing_path_CMIP, var_name)\n",
+    "\n",
+    "    # CMIP target = data to correct\n",
+    "    simp_da, simp_ds, simp_file = load_variable(forcing_path_CMIP_target, var_name)\n",
+    "\n",
+    "    # cmethods works with xarray DataArray objects with a time dimension\n",
+    "    corrected_da = monthly_qdm(\n",
+    "        obs_da=obs_da,\n",
+    "        simh_da=simh_da,\n",
+    "        simp_da=simp_da,\n",
+    "        var_name=var_name\n",
+    "    )\n",
+    "\n",
+    "    # Additional dry-day correction for precipitation\n",
+    "    if var_name == \"pr\":\n",
+    "\n",
+    "        thresholds = derive_monthly_pr_thresholds(\n",
+    "            reference_pr=obs_da,\n",
+    "            corrected_pr=corrected_da,\n",
+    "            dry_threshold_mm_day=0.1\n",
+    "        )\n",
+    "    \n",
+    "        corrected_da = apply_monthly_pr_thresholds(\n",
+    "            pr_da=corrected_da,\n",
+    "            thresholds=thresholds\n",
+    "        )\n",
+    "\n",
+    "    # Sometimes cmethods returns a Dataset instead of DataArray\n",
+    "    if isinstance(corrected_da, xr.Dataset):\n",
+    "        corrected_da = corrected_da[var_name]\n",
+    "\n",
+    "    # Sometimes the output name is lost\n",
+    "    corrected_da.name = var_name\n",
+    "\n",
+    "    # Keep physically realistic bounds for non-temperature variables\n",
+    "    if var_name != \"tas\":\n",
+    "        corrected_da = corrected_da.where(corrected_da >= 0, 0)\n",
+    "\n",
+    "    # Copy metadata from the target data\n",
+    "    corrected_da.attrs = simp_da.attrs\n",
+    "\n",
+    "    # Cast back to original target dtype if possible\n",
+    "    try:\n",
+    "        corrected_da = corrected_da.astype(simp_da.dtype)\n",
+    "    except Exception:\n",
+    "        pass\n",
+    "\n",
+    "    corrected_ds = corrected_da.to_dataset(name=var_name)\n",
+    "    corrected_ds.attrs = simp_ds.attrs\n",
+    "\n",
+    "    output_file = (\n",
+    "        forcing_path_QDM\n",
+    "        / f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_{var_name}.nc\"\n",
+    "    )\n",
+    "\n",
+    "    corrected_ds.to_netcdf(output_file)\n",
+    "\n",
+    "    print(\"Saved:\", output_file)\n",
+    "\n",
+    "    return corrected_da\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "id": "acfa59d9-760d-4e9c-ba62-50632b8fd36f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "Correcting pr\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "Correcting pr\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">combined_CMIP6_QDM_historical_1995_2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">014_pr.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mcombined_CMIP6_QDM_historical_1995_2\u001b[0m\n",
+       "\u001b[95m014_pr.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "Correcting tas\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "Correcting tas\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">combined_CMIP6_QDM_historical_1995_2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">014_tas.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mcombined_CMIP6_QDM_historical_1995_2\u001b[0m\n",
+       "\u001b[95m014_tas.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "Correcting rsds\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "Correcting rsds\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">combined_CMIP6_QDM_historical_1995_2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">014_rsds.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mcombined_CMIP6_QDM_historical_1995_2\u001b[0m\n",
+       "\u001b[95m014_rsds.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "Correcting evspsblpot\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "Correcting evspsblpot\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">combined_CMIP6_QDM_historical_1995_2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">014_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mcombined_CMIP6_QDM_historical_1995_2\u001b[0m\n",
+       "\u001b[95m014_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "corrected_data = {}\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "\n",
+    "    var_name = var_names[i]\n",
+    "    corrected_data[var_name] = bias_correct_variable(var_name)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "01e5d39b-b448-49e1-9a58-a13415143e1c",
+   "metadata": {},
+   "source": [
+    "## 6. Create eWaterCycle forcing YAML"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "id": "329c7270-3e6e-4894-bb4d-cbf349782651",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: <span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ewatercycle_forcing.yaml</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mewatercycle_forcing.yaml\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'start_time'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1995-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'end_time'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'shape'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'filenames'</span>: <span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_tas.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_evspsblpot.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">}</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\n",
+       "    \u001b[32m'start_time'\u001b[0m: \u001b[32m'1995-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[32m'end_time'\u001b[0m: \u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[32m'shape'\u001b[0m: \u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m,\n",
+       "    \u001b[32m'filenames'\u001b[0m: \u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_tas.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_evspsblpot.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{start_year}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{end_year}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_pr.nc\",\n",
+    "        \"tas\": f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_evspsblpot.nc\",\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "yaml_file_path = forcing_path_QDM / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)\n",
+    "\n",
+    "print(\"Saved:\", yaml_file_path)\n",
+    "print(forcing_yaml)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a79f375-f050-4652-92d8-6d85827d2212",
+   "metadata": {},
+   "source": [
+    "## 7. Test-load corrected forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 121,
+   "id": "c2b3c4b9-9565-483e-9f00-a1a617d1254f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1995-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1995-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "CMIP_QDM_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_QDM)\n",
+    "\n",
+    "print(CMIP_QDM_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "929d8298-a9db-4e02-bef7-3de7e8025d0c",
+   "metadata": {},
+   "source": [
+    "## 8. Diagnostics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "id": "86a68f82-bae7-4407-ba9f-a9e2e5f0c2b6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>259.132385</td>\n",
+       "      <td>258.764984</td>\n",
+       "      <td>259.130676</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>262.616638</td>\n",
+       "      <td>260.584747</td>\n",
+       "      <td>262.619354</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>266.683990</td>\n",
+       "      <td>266.945068</td>\n",
+       "      <td>266.679565</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>275.085419</td>\n",
+       "      <td>275.355194</td>\n",
+       "      <td>275.084656</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>281.591614</td>\n",
+       "      <td>283.529388</td>\n",
+       "      <td>281.590942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>286.239655</td>\n",
+       "      <td>287.728638</td>\n",
+       "      <td>286.238739</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>288.825104</td>\n",
+       "      <td>289.488037</td>\n",
+       "      <td>288.840942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>287.475311</td>\n",
+       "      <td>287.564758</td>\n",
+       "      <td>287.473358</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>282.689728</td>\n",
+       "      <td>281.650360</td>\n",
+       "      <td>282.674805</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>275.483521</td>\n",
+       "      <td>275.246124</td>\n",
+       "      <td>275.485504</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>266.516418</td>\n",
+       "      <td>267.792389</td>\n",
+       "      <td>266.535553</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>260.348724</td>\n",
+       "      <td>261.863647</td>\n",
+       "      <td>260.350525</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          ERA5        CMIP         QDM\n",
+       "1   259.132385  258.764984  259.130676\n",
+       "2   262.616638  260.584747  262.619354\n",
+       "3   266.683990  266.945068  266.679565\n",
+       "4   275.085419  275.355194  275.084656\n",
+       "5   281.591614  283.529388  281.590942\n",
+       "6   286.239655  287.728638  286.238739\n",
+       "7   288.825104  289.488037  288.840942\n",
+       "8   287.475311  287.564758  287.473358\n",
+       "9   282.689728  281.650360  282.674805\n",
+       "10  275.483521  275.246124  275.485504\n",
+       "11  266.516418  267.792389  266.535553\n",
+       "12  260.348724  261.863647  260.350525"
+      ]
+     },
+     "execution_count": 122,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def to_series(da):\n",
+    "    return pd.Series(\n",
+    "        data=da.values.squeeze(),\n",
+    "        index=pd.to_datetime(da[\"time\"].values),\n",
+    "        name=da.name,\n",
+    "    )\n",
+    "\n",
+    "\n",
+    "def load_corrected_variable(var_name):\n",
+    "    file_path = (forcing_path_QDM / f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_{var_name}.nc\")\n",
+    "    ds = xr.open_dataset(file_path)\n",
+    "    da = get_dataarray(ds, var_name).squeeze()\n",
+    "    return da\n",
+    "\n",
+    "\n",
+    "def monthly_mean_table(var_name, convert_pr_to_mm_day=False):\n",
+    "\n",
+    "    era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "    cmip_da, _, _ = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "    qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "    era5 = to_series(era5_da)\n",
+    "    cmip = to_series(cmip_da)\n",
+    "    qdm = to_series(qdm_da)\n",
+    "\n",
+    "    factor = 86400 if convert_pr_to_mm_day else 1\n",
+    "\n",
+    "    table = pd.DataFrame({\n",
+    "        \"ERA5\": era5.groupby(era5.index.month).mean() * factor,\n",
+    "        \"CMIP\": cmip.groupby(cmip.index.month).mean() * factor,\n",
+    "        \"QDM\": qdm.groupby(qdm.index.month).mean() * factor,\n",
+    "    })\n",
+    "\n",
+    "    return table\n",
+    "\n",
+    "\n",
+    "monthly_mean_table(\"tas\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "44041a3b-9453-4212-819e-c6ecf7ab9bdd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.915469</td>\n",
+       "      <td>1.014411</td>\n",
+       "      <td>0.923202</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.647922</td>\n",
+       "      <td>0.886178</td>\n",
+       "      <td>0.639437</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.931562</td>\n",
+       "      <td>1.102054</td>\n",
+       "      <td>0.928657</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1.377950</td>\n",
+       "      <td>1.504056</td>\n",
+       "      <td>1.376870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1.892165</td>\n",
+       "      <td>1.992272</td>\n",
+       "      <td>1.889571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>3.134658</td>\n",
+       "      <td>3.328967</td>\n",
+       "      <td>3.145954</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>3.462940</td>\n",
+       "      <td>3.765053</td>\n",
+       "      <td>3.486110</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2.314942</td>\n",
+       "      <td>2.116627</td>\n",
+       "      <td>2.335796</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1.707162</td>\n",
+       "      <td>1.607128</td>\n",
+       "      <td>1.754936</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1.148419</td>\n",
+       "      <td>1.267420</td>\n",
+       "      <td>1.151219</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1.013025</td>\n",
+       "      <td>1.112656</td>\n",
+       "      <td>1.008303</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0.838748</td>\n",
+       "      <td>0.929316</td>\n",
+       "      <td>0.830903</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        ERA5      CMIP       QDM\n",
+       "1   0.915469  1.014411  0.923202\n",
+       "2   0.647922  0.886178  0.639437\n",
+       "3   0.931562  1.102054  0.928657\n",
+       "4   1.377950  1.504056  1.376870\n",
+       "5   1.892165  1.992272  1.889571\n",
+       "6   3.134658  3.328967  3.145954\n",
+       "7   3.462940  3.765053  3.486110\n",
+       "8   2.314942  2.116627  2.335796\n",
+       "9   1.707162  1.607128  1.754936\n",
+       "10  1.148419  1.267420  1.151219\n",
+       "11  1.013025  1.112656  1.008303\n",
+       "12  0.838748  0.929316  0.830903"
+      ]
+     },
+     "execution_count": 123,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Precipitation monthly means in mm/day\n",
+    "monthly_mean_table(\"pr\", convert_pr_to_mm_day=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "id": "ced18668-c114-44c2-ba16-f5f381d4d523",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1995</th>\n",
+       "      <td>79</td>\n",
+       "      <td>82</td>\n",
+       "      <td>84</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1996</th>\n",
+       "      <td>51</td>\n",
+       "      <td>79</td>\n",
+       "      <td>87</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1997</th>\n",
+       "      <td>68</td>\n",
+       "      <td>52</td>\n",
+       "      <td>54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1998</th>\n",
+       "      <td>72</td>\n",
+       "      <td>55</td>\n",
+       "      <td>60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999</th>\n",
+       "      <td>66</td>\n",
+       "      <td>60</td>\n",
+       "      <td>65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000</th>\n",
+       "      <td>82</td>\n",
+       "      <td>49</td>\n",
+       "      <td>58</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2001</th>\n",
+       "      <td>87</td>\n",
+       "      <td>50</td>\n",
+       "      <td>54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2002</th>\n",
+       "      <td>71</td>\n",
+       "      <td>76</td>\n",
+       "      <td>84</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2003</th>\n",
+       "      <td>65</td>\n",
+       "      <td>69</td>\n",
+       "      <td>70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2004</th>\n",
+       "      <td>64</td>\n",
+       "      <td>55</td>\n",
+       "      <td>59</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2005</th>\n",
+       "      <td>77</td>\n",
+       "      <td>44</td>\n",
+       "      <td>54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2006</th>\n",
+       "      <td>66</td>\n",
+       "      <td>73</td>\n",
+       "      <td>76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2007</th>\n",
+       "      <td>44</td>\n",
+       "      <td>77</td>\n",
+       "      <td>75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2008</th>\n",
+       "      <td>70</td>\n",
+       "      <td>78</td>\n",
+       "      <td>82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2009</th>\n",
+       "      <td>69</td>\n",
+       "      <td>61</td>\n",
+       "      <td>65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2010</th>\n",
+       "      <td>75</td>\n",
+       "      <td>39</td>\n",
+       "      <td>49</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011</th>\n",
+       "      <td>51</td>\n",
+       "      <td>64</td>\n",
+       "      <td>67</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012</th>\n",
+       "      <td>67</td>\n",
+       "      <td>106</td>\n",
+       "      <td>113</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013</th>\n",
+       "      <td>53</td>\n",
+       "      <td>78</td>\n",
+       "      <td>77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2014</th>\n",
+       "      <td>59</td>\n",
+       "      <td>47</td>\n",
+       "      <td>46</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      ERA5  CMIP  QDM\n",
+       "1995    79    82   84\n",
+       "1996    51    79   87\n",
+       "1997    68    52   54\n",
+       "1998    72    55   60\n",
+       "1999    66    60   65\n",
+       "2000    82    49   58\n",
+       "2001    87    50   54\n",
+       "2002    71    76   84\n",
+       "2003    65    69   70\n",
+       "2004    64    55   59\n",
+       "2005    77    44   54\n",
+       "2006    66    73   76\n",
+       "2007    44    77   75\n",
+       "2008    70    78   82\n",
+       "2009    69    61   65\n",
+       "2010    75    39   49\n",
+       "2011    51    64   67\n",
+       "2012    67   106  113\n",
+       "2013    53    78   77\n",
+       "2014    59    47   46"
+      ]
+     },
+     "execution_count": 124,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Dry-day diagnostic for precipitation\n",
+    "era5_pr = to_series(load_variable(forcing_path_ERA5, \"pr\")[0])\n",
+    "cmip_pr = to_series(load_variable(forcing_path_CMIP_hist, \"pr\")[0])\n",
+    "qdm_pr = to_series(load_corrected_variable(\"pr\"))\n",
+    "\n",
+    "dry_days = pd.DataFrame({\n",
+    "    \"ERA5\": ((era5_pr * 86400) < 0.1).groupby(era5_pr.index.year).sum(),\n",
+    "    \"CMIP\": ((cmip_pr * 86400) < 0.1).groupby(cmip_pr.index.year).sum(),\n",
+    "    \"QDM\": ((qdm_pr * 86400) < 0.1).groupby(qdm_pr.index.year).sum(),\n",
+    "})\n",
+    "\n",
+    "dry_days\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 125,
+   "id": "4bdfafd5-39a5-41a0-9647-eeb44ce8b894",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_variable_timeseries(var_name, factor=1, start=None, end=None):\n",
+    "\n",
+    "    era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "    cmip_da, _, _ = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "    qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "    era5 = to_series(era5_da) * factor\n",
+    "    cmip = to_series(cmip_da) * factor\n",
+    "    qdm = to_series(qdm_da) * factor\n",
+    "\n",
+    "    if var_name == \"tas\":\n",
+    "        era5 = era5 - 273.15\n",
+    "        cmip = cmip - 273.15\n",
+    "        qdm = qdm - 273.15\n",
+    "\n",
+    "    # Select period\n",
+    "    if start is not None:\n",
+    "        era5 = era5[era5.index >= pd.to_datetime(start)]\n",
+    "        cmip = cmip[cmip.index >= pd.to_datetime(start)]\n",
+    "        qdm = qdm[qdm.index >= pd.to_datetime(start)]\n",
+    "\n",
+    "    if end is not None:\n",
+    "        era5 = era5[era5.index <= pd.to_datetime(end)]\n",
+    "        cmip = cmip[cmip.index <= pd.to_datetime(end)]\n",
+    "        qdm = qdm[qdm.index <= pd.to_datetime(end)]\n",
+    "\n",
+    "    plt.figure(figsize=(12, 5))\n",
+    "    plt.plot(era5.index, era5, label=\"ERA5\")\n",
+    "    plt.plot(cmip.index, cmip, label=\"CMIP\")\n",
+    "    plt.plot(qdm.index, qdm, label=\"QDM\")\n",
+    "    plt.title(var_name)\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 126,
+   "id": "3709b859-a101-4db2-8184-371c7600357a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_variable_timeseries(\n",
+    "    \"pr\",\n",
+    "    factor=86400,\n",
+    "    start=\"2012-05-01\",\n",
+    "    end=\"2012-08-31\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "id": "de19c038-8b47-473e-b6c0-cc9bdd9fe404",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def compare_stats(var_name, factor=1):\n",
+    "\n",
+    "    era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "    cmip_da, _, _ = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "    qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "    era5 = to_series(era5_da) * factor\n",
+    "    cmip = to_series(cmip_da) * factor\n",
+    "    qdm = to_series(qdm_da) * factor\n",
+    "\n",
+    "    stats = pd.DataFrame({\n",
+    "        \"ERA5\": era5.describe(),\n",
+    "        \"CMIP\": cmip.describe(),\n",
+    "        \"QDM\": qdm.describe()\n",
+    "    })\n",
+    "\n",
+    "    return stats"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "id": "d835a397-46ec-4aa5-bc27-edf79756ec00",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>7.305000e+03</td>\n",
+       "      <td>7.305000e+03</td>\n",
+       "      <td>7305.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>1.620587e+00</td>\n",
+       "      <td>1.723259e+00</td>\n",
+       "      <td>1.627803</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>2.418762e+00</td>\n",
+       "      <td>2.675928e+00</td>\n",
+       "      <td>2.508479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-1.665334e-13</td>\n",
+       "      <td>1.174351e-13</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>1.879302e-01</td>\n",
+       "      <td>1.873050e-01</td>\n",
+       "      <td>0.188148</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>7.593266e-01</td>\n",
+       "      <td>7.643056e-01</td>\n",
+       "      <td>0.762794</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>2.028109e+00</td>\n",
+       "      <td>2.214770e+00</td>\n",
+       "      <td>2.038388</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>2.548246e+01</td>\n",
+       "      <td>4.300434e+01</td>\n",
+       "      <td>43.004338</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               ERA5          CMIP          QDM\n",
+       "count  7.305000e+03  7.305000e+03  7305.000000\n",
+       "mean   1.620587e+00  1.723259e+00     1.627803\n",
+       "std    2.418762e+00  2.675928e+00     2.508479\n",
+       "min   -1.665334e-13  1.174351e-13     0.000000\n",
+       "25%    1.879302e-01  1.873050e-01     0.188148\n",
+       "50%    7.593266e-01  7.643056e-01     0.762794\n",
+       "75%    2.028109e+00  2.214770e+00     2.038388\n",
+       "max    2.548246e+01  4.300434e+01    43.004338"
+      ]
+     },
+     "execution_count": 128,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "compare_stats(\"pr\", factor=86400)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "id": "782e5335-f61a-4f59-842b-ca1cec86cdba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_variable_cdf_season(var_name, start_month=5, end_month=10):\n",
+    "\n",
+    "    era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "    cmip_da, _, _ = load_variable(forcing_path_CMIP, var_name)\n",
+    "    qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "    era5 = to_series(era5_da)\n",
+    "    cmip = to_series(cmip_da)\n",
+    "    qdm = to_series(qdm_da)\n",
+    "\n",
+    "    era5 = era5[era5.index.month.isin(range(start_month, end_month + 1))]\n",
+    "    cmip = cmip[cmip.index.month.isin(range(start_month, end_month + 1))]\n",
+    "    qdm = qdm[qdm.index.month.isin(range(start_month, end_month + 1))]\n",
+    "\n",
+    "    if var_name == \"tas\":\n",
+    "        era5 = era5 - 273.15\n",
+    "        cmip = cmip - 273.15\n",
+    "        qdm = qdm - 273.15\n",
+    "        xlabel = \"Temperature (°C)\"\n",
+    "\n",
+    "    elif var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "        era5 = era5 * 86400\n",
+    "        cmip = cmip * 86400\n",
+    "        qdm = qdm * 86400\n",
+    "        xlabel = f\"{var_name} (mm/day)\"\n",
+    "\n",
+    "    elif var_name == \"rsds\":\n",
+    "        xlabel = \"Shortwave radiation (W/m²)\"\n",
+    "    else:\n",
+    "        xlabel = var_name\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    # for name, data in {\"ERA5\": era5, \"CMIP\": cmip, \"QDM\": qdm}.items():\n",
+    "    for name, data in {\"CMIP\": cmip, \"QDM\": qdm, \"ERA5\": era5}.items():\n",
+    "\n",
+    "        values = np.sort(data.dropna().values)\n",
+    "        cdf = np.arange(1, len(values) + 1) / len(values)\n",
+    "\n",
+    "        plt.plot(values, cdf, label=name)\n",
+    "\n",
+    "    plt.xlabel(xlabel)\n",
+    "    plt.ylabel(\"Cumulative probability\")\n",
+    "    plt.title(f\"CDF of {var_name}, months {start_month}-{end_month}\")\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "id": "98ceeada-3d72-4b77-8259-43ed40148b24",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_variable_cdf_season(\"tas\", start_month=5, end_month=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 131,
+   "id": "cc847fac-bb44-41f3-ad17-ffeabc3a2baf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def forcing_summary_for_year(year):\n",
+    "\n",
+    "    variables = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "    rows = []\n",
+    "\n",
+    "    for var_name in variables:\n",
+    "\n",
+    "        era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "        cmip_da, _, _ = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "        qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "        era5 = to_series(era5_da)\n",
+    "        cmip = to_series(cmip_da)\n",
+    "        qdm = to_series(qdm_da)\n",
+    "\n",
+    "        # Select year\n",
+    "        era5_y = era5[era5.index.year == year]\n",
+    "        cmip_y = cmip[cmip.index.year == year]\n",
+    "        qdm_y = qdm[qdm.index.year == year]\n",
+    "\n",
+    "        # Unit conversion\n",
+    "        if var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "            era5_y = era5_y * 86400\n",
+    "            cmip_y = cmip_y * 86400\n",
+    "            qdm_y = qdm_y * 86400\n",
+    "            statistic = \"sum mm/year\"\n",
+    "\n",
+    "            rows.append({\n",
+    "                \"variable\": var_name,\n",
+    "                \"statistic\": statistic,\n",
+    "                \"ERA5\": era5_y.sum(),\n",
+    "                \"CMIP\": cmip_y.sum(),\n",
+    "                \"QDM\": qdm_y.sum()\n",
+    "            })\n",
+    "\n",
+    "        elif var_name == \"tas\":\n",
+    "            era5_y = era5_y - 273.15\n",
+    "            cmip_y = cmip_y - 273.15\n",
+    "            qdm_y = qdm_y - 273.15\n",
+    "            statistic = \"mean °C\"\n",
+    "\n",
+    "            rows.append({\n",
+    "                \"variable\": var_name,\n",
+    "                \"statistic\": statistic,\n",
+    "                \"ERA5\": era5_y.mean(),\n",
+    "                \"CMIP\": cmip_y.mean(),\n",
+    "                \"QDM\": qdm_y.mean()\n",
+    "            })\n",
+    "\n",
+    "        elif var_name == \"rsds\":\n",
+    "            statistic = \"mean W/m²\"\n",
+    "\n",
+    "            rows.append({\n",
+    "                \"variable\": var_name,\n",
+    "                \"statistic\": statistic,\n",
+    "                \"ERA5\": era5_y.mean(),\n",
+    "                \"CMIP\": cmip_y.mean(),\n",
+    "                \"QDM\": qdm_y.mean()\n",
+    "            })\n",
+    "\n",
+    "    return pd.DataFrame(rows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 177,
+   "id": "7dfaa301-cb46-4891-9c6c-3af8c65964d4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>statistic</th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>pr</td>\n",
+       "      <td>sum mm/year</td>\n",
+       "      <td>597.364853</td>\n",
+       "      <td>607.485192</td>\n",
+       "      <td>583.696337</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>tas</td>\n",
+       "      <td>mean °C</td>\n",
+       "      <td>1.458792</td>\n",
+       "      <td>1.674291</td>\n",
+       "      <td>1.379042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>rsds</td>\n",
+       "      <td>mean W/m²</td>\n",
+       "      <td>143.142471</td>\n",
+       "      <td>138.311142</td>\n",
+       "      <td>141.201462</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>evspsblpot</td>\n",
+       "      <td>sum mm/year</td>\n",
+       "      <td>605.052421</td>\n",
+       "      <td>603.664704</td>\n",
+       "      <td>603.770733</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     variable    statistic        ERA5        CMIP         QDM\n",
+       "0          pr  sum mm/year  597.364853  607.485192  583.696337\n",
+       "1         tas      mean °C    1.458792    1.674291    1.379042\n",
+       "2        rsds    mean W/m²  143.142471  138.311142  141.201462\n",
+       "3  evspsblpot  sum mm/year  605.052421  603.664704  603.770733"
+      ]
+     },
+     "execution_count": 177,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "forcing_summary_for_year(2011)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6fb3f02a-ee69-4d00-8d57-02a3eb2ea11c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d64afca3-3f52-430e-8f01-2f9799499a3a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Step6_CMIP_History.ipynb b/Workyard/Step6_CMIP_History.ipynb
new file mode 100644
index 00000000..1a6d2f60
--- /dev/null
+++ b/Workyard/Step6_CMIP_History.ipynb
@@ -0,0 +1,1756 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9ca8fd44-6292-4af4-9100-d3256fccd960",
+   "metadata": {},
+   "source": [
+    "# Ensemble validation\n",
+    "\n",
+    "The 5 parameter sets calculkated in Calibration_HBV.ipynb will be used for a validation period, in which the log NSE will be calculated, a mean will be calculated and total low flow days during the navigation season.\n",
+    "\n",
+    "The structure of this notebook is as follows:\n",
+    "\n",
+    "### 1. Startup\n",
+    "### 2. Model Setup\n",
+    "### 3. Running model\n",
+    "### 4. LNSE calculation\n",
+    "### 5. Display results\n",
+    "### 6. Lowflow calculation\n",
+    "### 7. Cumsum distribution"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdb4216e-a341-4c2b-a410-35170773a9a7",
+   "metadata": {},
+   "source": [
+    "## 1. Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "id": "d197b8f0-0f85-4a41-b2fb-1b2a8cf3f9f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "from scipy.interpolate import interp1d\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 148,
+   "id": "dd7b7d3f-1489-4723-bb51-f3cffcb7a85c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "id": "1c8aee93-b2d6-4291-89ae-1d29e69268cd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "d7dce039-d1f3-44a0-b646-98c32ecffb28",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "# experiment_start_date = \"2019-01-01T00:00:00Z\"\n",
+    "# experiment_end_date = \"2024-12-31T00:00:00Z\"\n",
+    "\n",
+    "start_year = 2025\n",
+    "end_year = 2050\n",
+    "\n",
+    "validation_start = f\"{start_year}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{end_year}-12-31T00:00:00Z\"\n",
+    "\n",
+    "# Choose CMIP Scenario: \n",
+    "Scenario = \"ssp126\"    # Options: historical, ssp119, ssp126, ssp245, ssp,370, ssp585"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "id": "d330bf37-7419-4287-81af-3d09e4c7a30e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / f\"ERA5-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_CMIP = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f\"CMIP6-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_QDM = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f\"CMIP6-QDM-{start_year}-{end_year}\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 125,
+   "id": "15ea4507-f559-4ef8-9756-60b8502064d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Create pathways for ERA 5 forcings\n",
+    "\n",
+    "# forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"forcings\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "# discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "# hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 126,
+   "id": "46ea8b1e-fb73-49ed-855c-4d95cd932748",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "id": "8bb224ad-d23c-475f-b6af-4a6023a17044",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs to relevant dates\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= validation_start_date) & (q_obs[\"Date\"] <= validation_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "id": "fc27f6f8-e7ff-4be6-b073-05006d25426a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date\n",
+       "2025-01-01    189.0\n",
+       "2025-01-02    191.0\n",
+       "2025-01-03    196.0\n",
+       "2025-01-04    201.0\n",
+       "2025-01-05    203.0\n",
+       "Name: Observed discharge, dtype: float64"
+      ]
+     },
+     "execution_count": 128,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "observed_output.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "id": "7f6f57aa-9f39-4524-ba3a-34f55035ebab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"])\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a48b5085-6478-4cf2-bd02-75b75f82e90f",
+   "metadata": {},
+   "source": [
+    "### Generate/Load CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "id": "77e79b20-3e4d-405a-bd88-16bdc50bdb39",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2025-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2050-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2050'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'2025-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2050-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/ssp126/CMIP6-2025-2050'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate data\n",
+    "# CMIP_dataset = {'dataset': 'MPI-ESM1-2-HR', 'project': 'CMIP6', 'grid' : 'gn', 'exp': 'historical', 'ensemble': 'r1i1p1f1'}\n",
+    "\n",
+    "# CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].generate(\n",
+    "#     dataset=CMIP_dataset,\n",
+    "#    start_time=validation_start,\n",
+    "#    end_time=validation_end,\n",
+    "#    shape=shape_file,\n",
+    "# )\n",
+    "# CMIP_forcing_QDM = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].generate(\n",
+    "#     dataset=CMIP_dataset,\n",
+    "#    start_time=validation_start,\n",
+    "#    end_time=validation_end,\n",
+    "#    shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_CMIP)\n",
+    "\n",
+    "# QDM_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_QDM)\n",
+    "\n",
+    "print(CMIP_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "09f9dfb3-40c9-4689-98b8-fd1ea8fd72d1",
+   "metadata": {},
+   "source": [
+    "### Load parameter sets & initial storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 131,
+   "id": "ca2be146-1112-4806-a44f-d57ebd4442c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "# par_0 = [4.45787, 0.42307, 201.57602, 2.36497, 0.26755, 8.62964, 0.083568, 0.0037073, 0.29645]\n",
+    "# par_0 = [2.79874, 0.49211, 255.96478, 1.782968, 0.503199, 6.095956, 0.33279, 0.10539, 0.63857]\n",
+    "# par_0 = [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606]         # 0.725 val, 0.x cal - Fav run 2\n",
+    "# par_0 = [6.28908, 0.423917, 173.56627, 1.63144, 0.402586, 6.56151, 0.0456809, 0.00313744, 0.516696]                 # 0.702 val, 0.x cal\n",
+    "# par_0 = [6.4919, 0.386877, 221.78625, 1.388269, 0.276453, 4.9870704, 0.04126777, 0.05640195, 1.148877]              # 0.668 val, 0.x cal\n",
+    "# par_0 = [7.502398, 0.38028, 194.1899, 1.680197, 0.47956, 4.8566806, 0.041745354, 0.02833896, 1.051862]              # 0.677 val, 0.x cal\n",
+    "# par_0 = [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392]                        # 0.781 val, 0.776 cal\n",
+    "# par_0 = [6.16512, 0.4369419, 151.2515900, 1.727835, 0.3771705, 6.19265974, 0.06959136, 0.001310818, 0.8130732]      # 0.664 val, 0.791 cal\n",
+    "# par_0 = [5.7107, 0.441634, 172.81305, 1.87367, 0.588802, 5.498147, 0.060305, 0.019666, 1.2011814]                    # x val, 0.73 cal         Start of 5+ months exclusion\n",
+    "# par_0 = [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504]                    # 0.82 val, 0.818 cal - Fav run 1      \n",
+    "# par_0 = [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]                    #  val,  0.77 cal    \n",
+    "# par_0 = [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857]                           # 0.78 val, 0.71 cal - potential inclusion\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]\n",
+    "]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"          # Snowmelt factor\n",
+    "               ]\n",
+    "\n",
+    "# Initial: par_0 = [5.085, 0.55, 100.373, 1.612, 0.545, 3.801, 0.196, 0.00, 0.185]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 132,
+   "id": "d5e5bcb4-bf90-470b-90ed-4a0b9d80c35d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "06c977b4-ba9d-4e82-8415-42180eac9f01",
+   "metadata": {},
+   "source": [
+    "## 2. Model setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 133,
+   "id": "055bdbc8-af1f-41ac-ad1d-b4da4d6785f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config\n",
+    "    )\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\"\n",
+    "    )\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0eef7e02-1e23-4d1a-99a3-56c2d3b5f62f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "650daf1f-e90f-4b5b-aac5-eca8965de7cf",
+   "metadata": {},
+   "source": [
+    "## 3. Running model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "id": "44092959-524a-4330-a274-77cfad0eacd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing\n",
+    "        )\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Filter observed data by day\n",
+    "    observed_daily = observed_output\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "    ensemble_data['Observed discharge'] = observed_daily\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 136,
+   "id": "079368de-30cf-491f-8cc9-2021f6a4bfa6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set 1</th>\n",
+       "      <th>Set 2</th>\n",
+       "      <th>Set 3</th>\n",
+       "      <th>Set 4</th>\n",
+       "      <th>Set 5</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Observed discharge</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2025-01-02</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>191.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2025-01-03</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>196.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2025-01-04</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>201.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2025-01-05</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>203.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2025-01-06</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>202.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Set 1  Set 2  Set 3  Set 4  Set 5  Mean  Observed discharge\n",
+       "2025-01-02    0.0    0.0    0.0    0.0    0.0   0.0               191.0\n",
+       "2025-01-03    0.0    0.0    0.0    0.0    0.0   0.0               196.0\n",
+       "2025-01-04    0.0    0.0    0.0    0.0    0.0   0.0               201.0\n",
+       "2025-01-05    0.0    0.0    0.0    0.0    0.0   0.0               203.0\n",
+       "2025-01-06    0.0    0.0    0.0    0.0    0.0   0.0               202.0"
+      ]
+     },
+     "execution_count": 136,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# ensemble_data_ERA5 = run_hbv_ensemble(\n",
+    "#     par_ensemble=par_ensemble,\n",
+    "#     initial_storages=s_0,\n",
+    "#     forcing=ERA5_forcing\n",
+    "# )\n",
+    "\n",
+    "ensemble_data_CMIP = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=CMIP_forcing\n",
+    ")\n",
+    "\n",
+    "# ensemble_data_QDM = run_hbv_ensemble(\n",
+    "#     par_ensemble=par_ensemble,\n",
+    "#     initial_storages=s_0,\n",
+    "#     forcing=QDM_forcing\n",
+    "# )\n",
+    "\n",
+    "# ensemble_data_ERA5.head()\n",
+    "ensemble_data_CMIP.head()\n",
+    "# ensemble_data_QDM.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "96d6162f-f432-4dfc-9194-f522a2e6a6da",
+   "metadata": {},
+   "source": [
+    "## 4. LNSE Calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 137,
+   "id": "37567a9e-dff3-4c80-84e0-572a6ed72b68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate log NSE\n",
+    "\n",
+    "def LNSE(sim, obs):\n",
+    "    \n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 138,
+   "id": "dc7850a4-dc30-4aa7-8719-4f810760c320",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call log NSE for relevant timeperiod\n",
+    "\n",
+    "def lnse_ensemble(ensemble_data, lnse_start, lnse_end):\n",
+    "\n",
+    "    # Select evaluation period - skip first year for storages to fill\n",
+    "    combined_data = ensemble_data[\n",
+    "        (ensemble_data.index >= lnse_start) &\n",
+    "        (ensemble_data.index <= lnse_end)\n",
+    "    ].dropna()\n",
+    "\n",
+    "    # Exclude winter months\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])\n",
+    "    ]\n",
+    "\n",
+    "    lnse_results = []\n",
+    "\n",
+    "    # Calculate LNSE for all sets\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        lnse_value = LNSE(\n",
+    "            combined_data[f\"Set {i+1}\"],\n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "\n",
+    "        # Append LNSE\n",
+    "        lnse_results.append({\n",
+    "            \"Set\": f\"Set {i+1}\",\n",
+    "            \"LNSE\": lnse_value\n",
+    "        })\n",
+    "\n",
+    "    # Calculate LNSE of ensemble mean\n",
+    "    mean_lnse = LNSE(\n",
+    "        combined_data[\"Mean\"],\n",
+    "        combined_data[\"Observed discharge\"]\n",
+    "    )\n",
+    "\n",
+    "    # Append LNSE\n",
+    "    lnse_results.append({\n",
+    "        \"Set\": \"Ensemble mean\",\n",
+    "        \"LNSE\": mean_lnse\n",
+    "    })\n",
+    "\n",
+    "    lnse_results = pd.DataFrame(lnse_results)\n",
+    "\n",
+    "    return lnse_results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
+   "id": "80962ebd-6ad7-48ce-b378-acd68ed03a1e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# lnse_results_ERA5 = lnse_ensemble(\n",
+    "#     ensemble_data=ensemble_data_ERA5,\n",
+    "#     lnse_start=evaluation_start,\n",
+    "#     lnse_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# lnse_results_CMIP = lnse_ensemble(\n",
+    "#     ensemble_data=ensemble_data_CMIP,\n",
+    "#     lnse_start=evaluation_start,\n",
+    "#     lnse_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# lnse_results_QDM = lnse_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     lnse_start=evaluation_start,\n",
+    "#     lnse_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# lnse_results_CMIP\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9b6a719-39c6-4872-87ff-cdb65d853e42",
+   "metadata": {},
+   "source": [
+    "## 5. Display results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "id": "f519854a-a994-44fd-a428-4d0c6daa98e1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_ensemble(ensemble_data, plot_start, plot_end):\n",
+    "\n",
+    "    plot_start = pd.to_datetime(plot_start)\n",
+    "    plot_end = pd.to_datetime(plot_end)\n",
+    "\n",
+    "    # Filter data to start & end time\n",
+    "    plot_data = ensemble_data[\n",
+    "        (ensemble_data.index >= plot_start) &\n",
+    "        (ensemble_data.index <= plot_end)\n",
+    "    ].dropna()\n",
+    "\n",
+    "    # Define figure\n",
+    "    plt.figure()\n",
+    "    plt.figure(figsize=(20, 8))\n",
+    "\n",
+    "    # Plot sets, observed data, ensemble mean and axhline, respectively\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        plt.plot(plot_data.index, plot_data[f\"Set {i+1}\"], color=\"orange\", alpha=0.3, label=\"Parameter sets\" if i == 0 else None)\n",
+    "\n",
+    "    plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\", linewidth=3)\n",
+    "    plt.plot(plot_data.index, plot_data[\"Mean\"], label=\"Ensemble mean\", linewidth=3)\n",
+    "    plt.axhline(y=q_critical, linestyle=\":\", color=\"black\", label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "    # Extras\n",
+    "    plt.xlabel(\"Date\")\n",
+    "    plt.ylabel(\"Discharge (m³/s)\")\n",
+    "    plt.title(\"Observed vs modelled ensemble discharge at 07DA001\")\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "id": "f1bb58f8-3dee-43eb-abc8-4af333b5d064",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Plot for full evaluation period\n",
+    "\n",
+    "# plot_ensemble_ERA5 = plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_ERA5,\n",
+    "#     plot_start=evaluation_start,\n",
+    "#     plot_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# plot_ensemble_CMIP = plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_CMIP,\n",
+    "#     plot_start=evaluation_start,\n",
+    "#     plot_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# plot_ensemble_QDM = plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     plot_start=evaluation_start,\n",
+    "#     plot_end=validation_end_date\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 142,
+   "id": "b835010a-b272-46b7-9c20-b0db1a99506b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2036\n",
+    "\n",
+    "# plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_ERA5,\n",
+    "#     plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "#     plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    "# )\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    ")\n",
+    "\n",
+    "# plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "#     plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d017577d-79da-4a97-9522-81f4c307f3aa",
+   "metadata": {},
+   "source": [
+    "## 6. Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 143,
+   "id": "dcc14e37-5aea-4b00-ae71-32b68ee03d4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_counter_ensemble(ensemble_data, start_date, end_date):\n",
+    "    \n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "    \n",
+    "        year = years[i]\n",
+    "    \n",
+    "        # Define start and end month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "    \n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        # Set zeros to count from\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = []\n",
+    "        modelmean_lowflow_days = 0\n",
+    "\n",
+    "        # Count observed lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "        # Count model mean lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "            modelmean_q = year_data.iloc[j][\"Mean\"]\n",
+    "\n",
+    "            if modelmean_q < q_critical:\n",
+    "                modelmean_lowflow_days += 1\n",
+    "\n",
+    "        # Count modelled lowflow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "        \n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"observed\": observed_lowflow_days,\n",
+    "            \"modelmean\": modelmean_lowflow_days,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)\n",
+    "        })\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    days_sum = lowflow_days[[\"observed\", \"modelmean\", \"set_1\", \"set_2\", \"set_3\", \"set_4\", \"set_5\", \"set_avg\"]].sum()\n",
+    "\n",
+    "    print(days_sum)\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 147,
+   "id": "7460b853-5619-44c9-ac89-3c6fc099bde6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">observed        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>\n",
+       "modelmean     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">878.0</span>\n",
+       "set_1        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1159.0</span>\n",
+       "set_2         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">760.0</span>\n",
+       "set_3         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">889.0</span>\n",
+       "set_4         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">980.0</span>\n",
+       "set_5         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">557.0</span>\n",
+       "set_avg       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">870.0</span>\n",
+       "dtype: float64\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "observed        \u001b[1;36m0.0\u001b[0m\n",
+       "modelmean     \u001b[1;36m878.0\u001b[0m\n",
+       "set_1        \u001b[1;36m1159.0\u001b[0m\n",
+       "set_2         \u001b[1;36m760.0\u001b[0m\n",
+       "set_3         \u001b[1;36m889.0\u001b[0m\n",
+       "set_4         \u001b[1;36m980.0\u001b[0m\n",
+       "set_5         \u001b[1;36m557.0\u001b[0m\n",
+       "set_avg       \u001b[1;36m870.0\u001b[0m\n",
+       "dtype: float64\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>observed</th>\n",
+       "      <th>modelmean</th>\n",
+       "      <th>set_1</th>\n",
+       "      <th>set_2</th>\n",
+       "      <th>set_3</th>\n",
+       "      <th>set_4</th>\n",
+       "      <th>set_5</th>\n",
+       "      <th>set_avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2026</td>\n",
+       "      <td>0</td>\n",
+       "      <td>22</td>\n",
+       "      <td>48</td>\n",
+       "      <td>16</td>\n",
+       "      <td>19</td>\n",
+       "      <td>19</td>\n",
+       "      <td>20</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2027</td>\n",
+       "      <td>0</td>\n",
+       "      <td>34</td>\n",
+       "      <td>51</td>\n",
+       "      <td>25</td>\n",
+       "      <td>36</td>\n",
+       "      <td>39</td>\n",
+       "      <td>22</td>\n",
+       "      <td>35.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2028</td>\n",
+       "      <td>0</td>\n",
+       "      <td>22</td>\n",
+       "      <td>27</td>\n",
+       "      <td>19</td>\n",
+       "      <td>22</td>\n",
+       "      <td>22</td>\n",
+       "      <td>13</td>\n",
+       "      <td>21.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2029</td>\n",
+       "      <td>0</td>\n",
+       "      <td>25</td>\n",
+       "      <td>38</td>\n",
+       "      <td>20</td>\n",
+       "      <td>25</td>\n",
+       "      <td>26</td>\n",
+       "      <td>10</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2030</td>\n",
+       "      <td>0</td>\n",
+       "      <td>75</td>\n",
+       "      <td>86</td>\n",
+       "      <td>71</td>\n",
+       "      <td>73</td>\n",
+       "      <td>82</td>\n",
+       "      <td>54</td>\n",
+       "      <td>73.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2031</td>\n",
+       "      <td>0</td>\n",
+       "      <td>45</td>\n",
+       "      <td>52</td>\n",
+       "      <td>29</td>\n",
+       "      <td>42</td>\n",
+       "      <td>47</td>\n",
+       "      <td>4</td>\n",
+       "      <td>35.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2032</td>\n",
+       "      <td>0</td>\n",
+       "      <td>52</td>\n",
+       "      <td>62</td>\n",
+       "      <td>46</td>\n",
+       "      <td>52</td>\n",
+       "      <td>60</td>\n",
+       "      <td>32</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2033</td>\n",
+       "      <td>0</td>\n",
+       "      <td>44</td>\n",
+       "      <td>49</td>\n",
+       "      <td>41</td>\n",
+       "      <td>48</td>\n",
+       "      <td>50</td>\n",
+       "      <td>28</td>\n",
+       "      <td>43.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2034</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>14</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2035</td>\n",
+       "      <td>0</td>\n",
+       "      <td>143</td>\n",
+       "      <td>141</td>\n",
+       "      <td>145</td>\n",
+       "      <td>143</td>\n",
+       "      <td>145</td>\n",
+       "      <td>142</td>\n",
+       "      <td>143.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2036</td>\n",
+       "      <td>0</td>\n",
+       "      <td>35</td>\n",
+       "      <td>43</td>\n",
+       "      <td>31</td>\n",
+       "      <td>35</td>\n",
+       "      <td>39</td>\n",
+       "      <td>25</td>\n",
+       "      <td>35.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2037</td>\n",
+       "      <td>0</td>\n",
+       "      <td>35</td>\n",
+       "      <td>42</td>\n",
+       "      <td>30</td>\n",
+       "      <td>33</td>\n",
+       "      <td>36</td>\n",
+       "      <td>27</td>\n",
+       "      <td>34.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2038</td>\n",
+       "      <td>0</td>\n",
+       "      <td>63</td>\n",
+       "      <td>75</td>\n",
+       "      <td>47</td>\n",
+       "      <td>60</td>\n",
+       "      <td>73</td>\n",
+       "      <td>40</td>\n",
+       "      <td>59.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2039</td>\n",
+       "      <td>0</td>\n",
+       "      <td>53</td>\n",
+       "      <td>59</td>\n",
+       "      <td>49</td>\n",
+       "      <td>53</td>\n",
+       "      <td>55</td>\n",
+       "      <td>38</td>\n",
+       "      <td>51.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2040</td>\n",
+       "      <td>0</td>\n",
+       "      <td>46</td>\n",
+       "      <td>73</td>\n",
+       "      <td>49</td>\n",
+       "      <td>55</td>\n",
+       "      <td>44</td>\n",
+       "      <td>8</td>\n",
+       "      <td>46.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2041</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2042</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2043</td>\n",
+       "      <td>0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>53</td>\n",
+       "      <td>20</td>\n",
+       "      <td>35</td>\n",
+       "      <td>43</td>\n",
+       "      <td>11</td>\n",
+       "      <td>32.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2044</td>\n",
+       "      <td>0</td>\n",
+       "      <td>59</td>\n",
+       "      <td>63</td>\n",
+       "      <td>56</td>\n",
+       "      <td>60</td>\n",
+       "      <td>61</td>\n",
+       "      <td>48</td>\n",
+       "      <td>58.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2045</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2046</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2047</td>\n",
+       "      <td>0</td>\n",
+       "      <td>23</td>\n",
+       "      <td>34</td>\n",
+       "      <td>15</td>\n",
+       "      <td>23</td>\n",
+       "      <td>26</td>\n",
+       "      <td>0</td>\n",
+       "      <td>20.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2048</td>\n",
+       "      <td>0</td>\n",
+       "      <td>24</td>\n",
+       "      <td>37</td>\n",
+       "      <td>15</td>\n",
+       "      <td>24</td>\n",
+       "      <td>29</td>\n",
+       "      <td>11</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2049</td>\n",
+       "      <td>0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>57</td>\n",
+       "      <td>27</td>\n",
+       "      <td>32</td>\n",
+       "      <td>49</td>\n",
+       "      <td>24</td>\n",
+       "      <td>38.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2050</td>\n",
+       "      <td>0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>22</td>\n",
+       "      <td>6</td>\n",
+       "      <td>15</td>\n",
+       "      <td>16</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    year  observed  modelmean  set_1  set_2  set_3  set_4  set_5  set_avg\n",
+       "0   2026         0         22     48     16     19     19     20     24.0\n",
+       "1   2027         0         34     51     25     36     39     22     35.0\n",
+       "2   2028         0         22     27     19     22     22     13     21.0\n",
+       "3   2029         0         25     38     20     25     26     10     24.0\n",
+       "4   2030         0         75     86     71     73     82     54     73.0\n",
+       "5   2031         0         45     52     29     42     47      4     35.0\n",
+       "6   2032         0         52     62     46     52     60     32     50.0\n",
+       "7   2033         0         44     49     41     48     50     28     43.0\n",
+       "8   2034         0          0     11      0      1     14      0      5.0\n",
+       "9   2035         0        143    141    145    143    145    142    143.0\n",
+       "10  2036         0         35     43     31     35     39     25     35.0\n",
+       "11  2037         0         35     42     30     33     36     27     34.0\n",
+       "12  2038         0         63     75     47     60     73     40     59.0\n",
+       "13  2039         0         53     59     49     53     55     38     51.0\n",
+       "14  2040         0         46     73     49     55     44      8     46.0\n",
+       "15  2041         0          0      6      3      0      3      0      2.0\n",
+       "16  2042         0          0      2      0      0      0      0      0.0\n",
+       "17  2043         0         30     53     20     35     43     11     32.0\n",
+       "18  2044         0         59     63     56     60     61     48     58.0\n",
+       "19  2045         0          0     15      0      3      2      0      4.0\n",
+       "20  2046         0          0     13      0      0      0      0      3.0\n",
+       "21  2047         0         23     34     15     23     26      0     20.0\n",
+       "22  2048         0         24     37     15     24     29     11     23.0\n",
+       "23  2049         0         33     57     27     32     49     24     38.0\n",
+       "24  2050         0         15     22      6     15     16      0     12.0"
+      ]
+     },
+     "execution_count": 147,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# lowflow_ERA5 = lowflow_counter_ensemble(\n",
+    "#     ensemble_data=ensemble_data_ERA5,\n",
+    "#     start_date=evaluation_start,\n",
+    "#     end_date=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "lowflow_CMIP = lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date\n",
+    ")\n",
+    "\n",
+    "# lowflow_QDM = lowflow_counter_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     start_date=evaluation_start,\n",
+    "#     end_date=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "lowflow_CMIP"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d98001e7-ada9-4415-ae0b-ed7cb8888319",
+   "metadata": {},
+   "source": [
+    "## 7. Cumsum"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 145,
+   "id": "1e9e205d-08bf-4f19-9b12-a0141a4fad99",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def rank(lowflow_ERA5, lowflow_CMIP):\n",
+    "\n",
+    "    # Combine tables\n",
+    "    rank_table = pd.DataFrame({\n",
+    "        \"Observed\": np.sort(lowflow_ERA5[\"observed\"]),\n",
+    "        \"ERA5\": np.sort(lowflow_ERA5[\"set_avg\"]),\n",
+    "        \"CMIP6\": np.sort(lowflow_CMIP[\"set_avg\"]),\n",
+    "        \"QDM\": np.sort(lowflow_QDM[\"set_avg\"])\n",
+    "    })\n",
+    "    \n",
+    "    rank_table.insert(0, \"rank\", range(1, len(rank_table) + 1))\n",
+    "\n",
+    "    return rank_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 146,
+   "id": "02d8a545-838c-4da5-9935-22f34d49f4ee",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "All arrays must be of the same length",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[146], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m rank_table \u001b[38;5;241m=\u001b[39m \u001b[43mrank\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlowflow_ERA5\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlowflow_CMIP\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m rank_table \u001b[38;5;241m=\u001b[39m rank(lowflow_ERA5, lowflow_CMIP)\n\u001b[1;32m      4\u001b[0m rank_table\n",
+      "Cell \u001b[0;32mIn[145], line 4\u001b[0m, in \u001b[0;36mrank\u001b[0;34m(lowflow_ERA5, lowflow_CMIP)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mrank\u001b[39m(lowflow_ERA5, lowflow_CMIP):\n\u001b[1;32m      2\u001b[0m \n\u001b[1;32m      3\u001b[0m     \u001b[38;5;66;03m# Combine tables\u001b[39;00m\n\u001b[0;32m----> 4\u001b[0m     rank_table \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mDataFrame\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mObserved\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlowflow_ERA5\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mobserved\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mERA5\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlowflow_ERA5\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mset_avg\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mCMIP6\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlowflow_CMIP\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mset_avg\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      8\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mQDM\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlowflow_QDM\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mset_avg\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      9\u001b[0m \u001b[43m    \u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     11\u001b[0m     rank_table\u001b[38;5;241m.\u001b[39minsert(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrank\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, \u001b[38;5;28mlen\u001b[39m(rank_table) \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m))\n\u001b[1;32m     13\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m rank_table\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/pandas/core/frame.py:778\u001b[0m, in \u001b[0;36mDataFrame.__init__\u001b[0;34m(self, data, index, columns, dtype, copy)\u001b[0m\n\u001b[1;32m    772\u001b[0m     mgr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_init_mgr(\n\u001b[1;32m    773\u001b[0m         data, axes\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mindex\u001b[39m\u001b[38;5;124m\"\u001b[39m: index, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcolumns\u001b[39m\u001b[38;5;124m\"\u001b[39m: columns}, dtype\u001b[38;5;241m=\u001b[39mdtype, copy\u001b[38;5;241m=\u001b[39mcopy\n\u001b[1;32m    774\u001b[0m     )\n\u001b[1;32m    776\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data, \u001b[38;5;28mdict\u001b[39m):\n\u001b[1;32m    777\u001b[0m     \u001b[38;5;66;03m# GH#38939 de facto copy defaults to False only in non-dict cases\u001b[39;00m\n\u001b[0;32m--> 778\u001b[0m     mgr \u001b[38;5;241m=\u001b[39m \u001b[43mdict_to_mgr\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindex\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtyp\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmanager\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    779\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data, ma\u001b[38;5;241m.\u001b[39mMaskedArray):\n\u001b[1;32m    780\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mnumpy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mma\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m mrecords\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/pandas/core/internals/construction.py:503\u001b[0m, in \u001b[0;36mdict_to_mgr\u001b[0;34m(data, index, columns, dtype, typ, copy)\u001b[0m\n\u001b[1;32m    499\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    500\u001b[0m         \u001b[38;5;66;03m# dtype check to exclude e.g. range objects, scalars\u001b[39;00m\n\u001b[1;32m    501\u001b[0m         arrays \u001b[38;5;241m=\u001b[39m [x\u001b[38;5;241m.\u001b[39mcopy() \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(x, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdtype\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01melse\u001b[39;00m x \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m arrays]\n\u001b[0;32m--> 503\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43marrays_to_mgr\u001b[49m\u001b[43m(\u001b[49m\u001b[43marrays\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindex\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtyp\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtyp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconsolidate\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/pandas/core/internals/construction.py:114\u001b[0m, in \u001b[0;36marrays_to_mgr\u001b[0;34m(arrays, columns, index, dtype, verify_integrity, typ, consolidate)\u001b[0m\n\u001b[1;32m    111\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m verify_integrity:\n\u001b[1;32m    112\u001b[0m     \u001b[38;5;66;03m# figure out the index, if necessary\u001b[39;00m\n\u001b[1;32m    113\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m index \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 114\u001b[0m         index \u001b[38;5;241m=\u001b[39m \u001b[43m_extract_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43marrays\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    115\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    116\u001b[0m         index \u001b[38;5;241m=\u001b[39m ensure_index(index)\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/pandas/core/internals/construction.py:677\u001b[0m, in \u001b[0;36m_extract_index\u001b[0;34m(data)\u001b[0m\n\u001b[1;32m    675\u001b[0m lengths \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mset\u001b[39m(raw_lengths))\n\u001b[1;32m    676\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(lengths) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m--> 677\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAll arrays must be of the same length\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    679\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m have_dicts:\n\u001b[1;32m    680\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    681\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMixing dicts with non-Series may lead to ambiguous ordering.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    682\u001b[0m     )\n",
+      "\u001b[0;31mValueError\u001b[0m: All arrays must be of the same length"
+     ]
+    }
+   ],
+   "source": [
+    "rank_table = rank(lowflow_ERA5, lowflow_CMIP)\n",
+    "rank_table = rank(lowflow_ERA5, lowflow_CMIP)\n",
+    "\n",
+    "rank_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f87182f3-7a63-4856-9594-f53b5dd421b8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cumsum_table = pd.DataFrame({\n",
+    "    \"Observed_cumsum\": rank_table[\"Observed\"].cumsum(),\n",
+    "     \"ERA5_cumsum\": rank_table[\"ERA5\"].cumsum(),\n",
+    "    \"CMIP6_cumsum\": rank_table[\"CMIP6\"].cumsum(),\n",
+    "    \"QDM_cumsum\": rank_table[\"QDM\"].cumsum()\n",
+    "})\n",
+    "\n",
+    "cumsum_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "78105310-3388-48fa-9471-54003b019753",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_cumsum(rank_table):\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    # Plot cumsum for all columns, skipping rank column\n",
+    "    for i in range(1, len(rank_table.columns)):\n",
+    "        plt.plot(\n",
+    "            rank_table[\"rank\"],\n",
+    "            rank_table[rank_table.columns[i]].cumsum(),\n",
+    "            marker=\"o\",\n",
+    "            label=rank_table.columns[i]\n",
+    "        )\n",
+    "\n",
+    "    # Plotting\n",
+    "    plt.xlabel(\"Ranked years\")\n",
+    "    plt.ylabel(\"Cumulative low flow days\")\n",
+    "    plt.xticks(rank_table[\"rank\"])\n",
+    "    plt.title(\"Cumulative annual low flow days\")\n",
+    "    # plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b3fa8488-2d3f-4dbd-b82c-e3f8c5bb04d8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_cumsum(rank_table)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3abc8ad5-90fd-4ce8-bb44-4a5d8540b1d9",
+   "metadata": {},
+   "source": [
+    "## 8. Quantile Mapping"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cee6e4aa-f4be-45c7-9d7a-d70782c60ad4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def quantile_mapping(observed, modelled, n):\n",
+    "    # Define a common quantile grid (e.g., 1000 points between 0 and 1)\n",
+    "    quantiles = np.linspace(0, 1, n)\n",
+    "\n",
+    "    # Sort the data\n",
+    "    observed_sorted = np.sort(observed)\n",
+    "    modelled_sorted = np.sort(modelled)\n",
+    "\n",
+    "    # Interpolate both series onto the common quantile grid\n",
+    "    observed_interpolated = interp1d(np.linspace(0, 1, len(observed_sorted)), observed_sorted, bounds_error=False, fill_value=\"extrapolate\")\n",
+    "    modelled_interpolated = interp1d(np.linspace(0, 1, len(modelled_sorted)), modelled_sorted, bounds_error=False, fill_value=\"extrapolate\")\n",
+    "\n",
+    "    observed_on_quantiles = observed_interpolated(quantiles)\n",
+    "    modelled_on_quantiles = modelled_interpolated(quantiles)\n",
+    "\n",
+    "    # Create mapping from modelled deficits to observed using interpolation\n",
+    "    mapping_function = interp1d(modelled_on_quantiles, observed_on_quantiles, bounds_error=False, fill_value=\"extrapolate\")\n",
+    "\n",
+    "    return mapping_function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ccfd9d00-8165-4a95-a9bc-04d017c2d150",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def correct_discharge_ensemble(\n",
+    "    ensemble_data,\n",
+    "    observed_output,\n",
+    "    start_date,\n",
+    "    end_date,\n",
+    "    n=1000\n",
+    "):\n",
+    "\n",
+    "    corrected_data = pd.DataFrame(index=ensemble_data.index)\n",
+    "\n",
+    "    # Prepare observed discharge\n",
+    "    observed = observed_output.copy()\n",
+    "    observed.index = pd.to_datetime(observed.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Prepare model data\n",
+    "    modelled = ensemble_data.copy()\n",
+    "    modelled.index = pd.to_datetime(modelled.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Select calibration period\n",
+    "    start_date = pd.to_datetime(start_date).tz_localize(None).normalize()\n",
+    "    end_date = pd.to_datetime(end_date).tz_localize(None).normalize()\n",
+    "\n",
+    "    observed_period = observed[(observed.index >= start_date) & (observed.index <= end_date)]\n",
+    "    modelled_period = modelled[(modelled.index >= start_date) & (modelled.index <= end_date)]\n",
+    "\n",
+    "    # Correct every parameter set\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "\n",
+    "        set_name = f\"Set {i+1}\"\n",
+    "\n",
+    "        qm_function = quantile_mapping(\n",
+    "            observed=observed_period,\n",
+    "            modelled=modelled_period[set_name],\n",
+    "            n=n\n",
+    "        )\n",
+    "\n",
+    "        corrected_data[set_name] = qm_function(modelled[set_name])\n",
+    "\n",
+    "    # Remove negative discharge\n",
+    "    corrected_data[corrected_data < 0] = 0\n",
+    "\n",
+    "    # Recalculate mean\n",
+    "    corrected_data[\"Mean\"] = corrected_data.mean(axis=1)\n",
+    "\n",
+    "    # Add observed discharge for comparison\n",
+    "    corrected_data[\"Observed discharge\"] = observed\n",
+    "\n",
+    "    return corrected_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2d4ef549-838f-44ce-884b-99c5a3447cbd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ensemble_data_CMIP_corrected = correct_discharge_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    observed_output=observed_output,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date,\n",
+    "    n=1000\n",
+    ")\n",
+    "\n",
+    "ensemble_data_CMIP_corrected.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "63008778-e23d-4fae-b8f9-f61c789934d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lowflow_CMIP_corrected = lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP_corrected,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date\n",
+    ")\n",
+    "\n",
+    "lowflow_CMIP_corrected"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14776cc2-254f-49bf-9c37-5bb2c3295806",
+   "metadata": {},
+   "source": [
+    "## 9. Test test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ad520100-76e2-4a62-b450-4e010ca226d3",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "39bd4f11-bc62-4310-a64d-0a7742962a5d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "09522b58-9fc4-4222-92d7-6d6d241e13df",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "64d999a0-114a-4c60-bf94-516959483af9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "242c2ced-687e-48a6-b160-e50c208e50cb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Step7_CMIP_Projections.ipynb b/Workyard/Step7_CMIP_Projections.ipynb
new file mode 100644
index 00000000..4c23182b
--- /dev/null
+++ b/Workyard/Step7_CMIP_Projections.ipynb
@@ -0,0 +1,2822 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6571f48a-467c-4dc9-8c4b-6029d09672e7",
+   "metadata": {},
+   "source": [
+    "# CMIP Projections\n",
+    "\n",
+    "The 5 parameter sets calculkated in Calibration_HBV.ipynb will be used for a validation period, in which the log NSE will be calculated, a mean will be calculated and total low flow days during the navigation season.\n",
+    "\n",
+    "The structure of this notebook is as follows:\n",
+    "\n",
+    "### 1. Startup\n",
+    "### 2. Model setup\n",
+    "### 3. Running model\n",
+    "### 4. Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14ec2576-8826-48ce-9b0d-3c28be7fec68",
+   "metadata": {},
+   "source": [
+    "## 1. Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "71668e92-f5c4-49b2-9eed-20f91997c193",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Imports\n",
+    "\n",
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "from scipy.interpolate import interp1d\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "f2135c0b-ba31-4f05-bf37-435a99b1788f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "c5166bb7-f81f-4967-a65a-d1933464ce7f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500\n",
+    "\n",
+    "start_year = 2025\n",
+    "end_year = 2050\n",
+    "\n",
+    "# Choose CMIP Scenario: \n",
+    "# Scenario = \"ssp126\"    # Options: historical, ssp119, ssp126, ssp245, ssp,370, ssp585\n",
+    "# Scenario = {\"ssp126\", \"ssp245\", \"ssp370\"}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "1fda9bce-98ad-4f35-bba6-d0315ea40d2d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scenarios = [\"ssp126\", \"ssp245\", \"ssp370\"]\n",
+    "\n",
+    "periods = [\n",
+    "    [2025, 2050, 2075],\n",
+    "    [2050, 2075, 2099]\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "7001cbf2-e95c-469d-970c-118b27d054e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# for i in range(len(scenario)):\n",
+    "#     Scenario = scenario[i]\n",
+    "#     for i in range(len(periods[0])):\n",
+    "#         start_year = periods[0][i]\n",
+    "#         end_year = periods[0][i]\n",
+    "\n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "c398fe4d-66fb-430a-8f82-ad85e924f592",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "def forcing_path_cmip(scenario, start_year, end_year):\n",
+    "    \n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / scenario / f\"CMIP6-{start_year}-{end_year}\"\n",
+    "    \n",
+    "    return forcing_path\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "a7bab7da-b7e7-442c-b4b0-e5c3b0ededcb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Adjust time period\n",
+    "\n",
+    "validation_start = f\"{start_year}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{end_year}-12-31T00:00:00Z\"\n",
+    "\n",
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47ca81c0-59ac-40b1-8cdd-ea6bb4ea1e0d",
+   "metadata": {},
+   "source": [
+    "### Load CMIP data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "c0873cb8-69da-49cd-84fe-d45d9684277f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2025-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2050-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">ngs/CMIP6/ssp126/CMIP6-2025-2050'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">s/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'2025-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2050-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci\u001b[0m\n",
+       "\u001b[32mngs/CMIP6/ssp126/CMIP6-2025-2050'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile\u001b[0m\n",
+       "\u001b[32ms/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load data\n",
+    "CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_CMIP)\n",
+    "\n",
+    "print(CMIP_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f4a7211e-cb74-4a90-8229-de7000cf2dd5",
+   "metadata": {},
+   "source": [
+    "## 2. Model setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d31e5426-3e95-4902-913c-c40da613b8aa",
+   "metadata": {},
+   "source": [
+    "### Load parameter sets & initial storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "d776ff36-b69a-4321-9468-d4fa85350ef3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define parameter ensemble\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]\n",
+    "]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"          # Snowmelt factor\n",
+    "               ]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "c60f825e-520a-4b00-83ab-16bdcfe60471",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define initial storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "70ba5ea1-8a76-463a-a14c-415673632103",
+   "metadata": {},
+   "source": [
+    "### Config model "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "70664027-bb24-47cc-814d-eb8eccbc1715",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model setup create function\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config\n",
+    "    )\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\"\n",
+    "    )\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fc3a24e7-53d6-4b62-aab1-ea705cefa75a",
+   "metadata": {},
+   "source": [
+    "## 3. Running model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "1dab11de-a9f9-4e58-bc05-29926875e2d0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model running create function\n",
+    "\n",
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing\n",
+    "        )\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "8e42b731-3b74-43e3-bef9-267ca46cbe5d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Run model functions\n",
+    "\n",
+    "# ensemble_data_CMIP = run_hbv_ensemble(\n",
+    "#     par_ensemble=par_ensemble,\n",
+    "#     initial_storages=s_0,\n",
+    "#     forcing=CMIP_forcing\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "110cc380-2552-4be7-9846-5cc8b21d1b9d",
+   "metadata": {},
+   "source": [
+    "## 4. Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "4092c20d-19a6-4245-bfc9-a83ae151ba62",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Create low flow counter function\n",
+    "\n",
+    "# def lowflow_counter_ensemble(ensemble_data, start_date, end_date):\n",
+    "    \n",
+    "#     lowflow_days = []\n",
+    "\n",
+    "#     years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "#     for i in range(len(years)):\n",
+    "    \n",
+    "#         year = years[i]\n",
+    "    \n",
+    "#         # Define start and end month-day\n",
+    "#         year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "#         year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "    \n",
+    "#         year_data = ensemble_data[\n",
+    "#             (ensemble_data.index >= year_start) &\n",
+    "#             (ensemble_data.index <= year_end)\n",
+    "#         ]\n",
+    "\n",
+    "#         # Set zeros to count from\n",
+    "#         modelled_lowflow_days = []\n",
+    "#         modelmean_lowflow_days = 0\n",
+    "\n",
+    "#         # Count modelled lowflow days\n",
+    "#         for j in range(len(par_ensemble)):\n",
+    "#             set_lowflow_days = 0\n",
+    "\n",
+    "#             for k in range(len(year_data)):\n",
+    "#                 set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "#                 if set_q < q_critical:\n",
+    "#                     set_lowflow_days += 1\n",
+    "\n",
+    "#             modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "#         setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "        \n",
+    "#         lowflow_days.append({\n",
+    "#             \"year\": year,\n",
+    "#             \"set_1\": modelled_lowflow_days[0],\n",
+    "#             \"set_2\": modelled_lowflow_days[1],\n",
+    "#             \"set_3\": modelled_lowflow_days[2],\n",
+    "#             \"set_4\": modelled_lowflow_days[3],\n",
+    "#             \"set_5\": modelled_lowflow_days[4],\n",
+    "#             \"set_avg\": np.round(setavg_lowflow_days)\n",
+    "#         })\n",
+    "\n",
+    "#     lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "#     # days_sum = lowflow_days[[\"observed\", \"modelmean\", \"set_1\", \"set_2\", \"set_3\", \"set_4\", \"set_5\", \"set_avg\"]].sum()\n",
+    "\n",
+    "#     # print(days_sum)\n",
+    "\n",
+    "#     return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "acf369ed-ebd2-4694-ab43-91730f12fa26",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_counter_future(ensemble_data, start_date, end_date):\n",
+    "\n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "\n",
+    "        year = years[i]\n",
+    "\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "\n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        modelled_lowflow_days = []\n",
+    "\n",
+    "        # Count parameter set low-flow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "\n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)\n",
+    "        })\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "id": "66ff97ac-4f6b-42e6-b114-91eddc72f057",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_cmip_projection(scenario, start_year, end_year):\n",
+    "\n",
+    "    print(f\"Running {scenario}, {start_year}-{end_year}\")\n",
+    "\n",
+    "    forcing_path_CMIP = forcing_path_cmip(\n",
+    "        scenario=scenario,\n",
+    "        start_year=start_year,\n",
+    "        end_year=end_year\n",
+    "    )\n",
+    "\n",
+    "    CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_CMIP)\n",
+    "\n",
+    "    ensemble_data_CMIP = run_hbv_ensemble(\n",
+    "        par_ensemble=par_ensemble,\n",
+    "        initial_storages=s_0,\n",
+    "        forcing=CMIP_forcing\n",
+    "    )\n",
+    "\n",
+    "    start_date = pd.to_datetime(f\"{start_year + 1}-01-01\")\n",
+    "    end_date = pd.to_datetime(f\"{end_year}-12-31\")\n",
+    "\n",
+    "    lowflow_CMIP = lowflow_counter_future(\n",
+    "        ensemble_data=ensemble_data_CMIP,\n",
+    "        start_date=start_date,\n",
+    "        end_date=end_date\n",
+    "    )\n",
+    "\n",
+    "    result = {\n",
+    "        \"scenario\": scenario,\n",
+    "        \"period\": f\"{start_year + 1}-{end_year}\",\n",
+    "        \"start_year\": start_year + 1,\n",
+    "        \"end_year\": end_year,\n",
+    "        \"mean_lowflow_days\": lowflow_CMIP[\"set_avg\"].mean(),\n",
+    "        \"total_lowflow_days\": lowflow_CMIP[\"set_avg\"].sum(),\n",
+    "        \"set_1_avg\": lowflow_CMIP[\"set_1\"].mean(),\n",
+    "        \"set_2_avg\": lowflow_CMIP[\"set_2\"].mean(),\n",
+    "        \"set_3_avg\": lowflow_CMIP[\"set_3\"].mean(),\n",
+    "        \"set_4_avg\": lowflow_CMIP[\"set_4\"].mean(),\n",
+    "        \"set_5_avg\": lowflow_CMIP[\"set_5\"].mean(),\n",
+    "    }\n",
+    "\n",
+    "    return result, lowflow_CMIP, ensemble_data_CMIP"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "1960a3b9-19e8-42a6-8cca-eb553cb17192",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp126, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp126, \u001b[1;36m2025\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp126, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp126, \u001b[1;36m2050\u001b[0m-\u001b[1;36m2075\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp126, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp126, \u001b[1;36m2075\u001b[0m-\u001b[1;36m2099\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp245, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp245, \u001b[1;36m2025\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp245, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp245, \u001b[1;36m2050\u001b[0m-\u001b[1;36m2075\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp245, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp245, \u001b[1;36m2075\u001b[0m-\u001b[1;36m2099\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp370, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp370, \u001b[1;36m2025\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp370, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp370, \u001b[1;36m2050\u001b[0m-\u001b[1;36m2075\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp370, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp370, \u001b[1;36m2075\u001b[0m-\u001b[1;36m2099\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "projection_results = []\n",
+    "lowflow_results = {}\n",
+    "ensemble_results = {}\n",
+    "\n",
+    "for i in range(len(scenarios)):\n",
+    "\n",
+    "    scenario = scenarios[i]\n",
+    "\n",
+    "    for j in range(len(periods[0])):\n",
+    "\n",
+    "        start_year = periods[0][j]\n",
+    "        end_year = periods[1][j]\n",
+    "\n",
+    "        result, lowflow_CMIP, ensemble_data_CMIP = run_cmip_projection(\n",
+    "            scenario=scenario,\n",
+    "            start_year=start_year,\n",
+    "            end_year=end_year\n",
+    "        )\n",
+    "\n",
+    "        projection_results.append(result)\n",
+    "\n",
+    "        key = f\"{scenario}_{start_year + 1}_{end_year}\"\n",
+    "\n",
+    "        lowflow_results[key] = lowflow_CMIP\n",
+    "        ensemble_results[key] = ensemble_data_CMIP"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "4f2191db-b514-4312-bd9a-7301f1f95381",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>period</th>\n",
+       "      <th>start_year</th>\n",
+       "      <th>end_year</th>\n",
+       "      <th>mean_lowflow_days</th>\n",
+       "      <th>total_lowflow_days</th>\n",
+       "      <th>set_1_avg</th>\n",
+       "      <th>set_2_avg</th>\n",
+       "      <th>set_3_avg</th>\n",
+       "      <th>set_4_avg</th>\n",
+       "      <th>set_5_avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ssp126</td>\n",
+       "      <td>2026-2050</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>2050</td>\n",
+       "      <td>34.800000</td>\n",
+       "      <td>870.0</td>\n",
+       "      <td>46.360000</td>\n",
+       "      <td>30.400000</td>\n",
+       "      <td>35.560000</td>\n",
+       "      <td>39.200000</td>\n",
+       "      <td>22.280000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ssp126</td>\n",
+       "      <td>2051-2075</td>\n",
+       "      <td>2051</td>\n",
+       "      <td>2075</td>\n",
+       "      <td>38.520000</td>\n",
+       "      <td>963.0</td>\n",
+       "      <td>50.160000</td>\n",
+       "      <td>35.280000</td>\n",
+       "      <td>39.040000</td>\n",
+       "      <td>42.640000</td>\n",
+       "      <td>26.320000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ssp126</td>\n",
+       "      <td>2076-2099</td>\n",
+       "      <td>2076</td>\n",
+       "      <td>2099</td>\n",
+       "      <td>32.333333</td>\n",
+       "      <td>776.0</td>\n",
+       "      <td>43.916667</td>\n",
+       "      <td>28.916667</td>\n",
+       "      <td>33.750000</td>\n",
+       "      <td>34.875000</td>\n",
+       "      <td>19.666667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>ssp245</td>\n",
+       "      <td>2026-2050</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>2050</td>\n",
+       "      <td>41.640000</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>50.600000</td>\n",
+       "      <td>37.640000</td>\n",
+       "      <td>42.280000</td>\n",
+       "      <td>45.200000</td>\n",
+       "      <td>32.720000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>ssp245</td>\n",
+       "      <td>2051-2075</td>\n",
+       "      <td>2051</td>\n",
+       "      <td>2075</td>\n",
+       "      <td>35.040000</td>\n",
+       "      <td>876.0</td>\n",
+       "      <td>44.960000</td>\n",
+       "      <td>31.920000</td>\n",
+       "      <td>35.200000</td>\n",
+       "      <td>37.000000</td>\n",
+       "      <td>26.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>ssp245</td>\n",
+       "      <td>2076-2099</td>\n",
+       "      <td>2076</td>\n",
+       "      <td>2099</td>\n",
+       "      <td>28.500000</td>\n",
+       "      <td>684.0</td>\n",
+       "      <td>38.708333</td>\n",
+       "      <td>24.250000</td>\n",
+       "      <td>29.958333</td>\n",
+       "      <td>32.458333</td>\n",
+       "      <td>17.166667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2026-2050</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>2050</td>\n",
+       "      <td>35.080000</td>\n",
+       "      <td>877.0</td>\n",
+       "      <td>44.200000</td>\n",
+       "      <td>31.400000</td>\n",
+       "      <td>37.120000</td>\n",
+       "      <td>38.840000</td>\n",
+       "      <td>23.920000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2051-2075</td>\n",
+       "      <td>2051</td>\n",
+       "      <td>2075</td>\n",
+       "      <td>46.960000</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>58.120000</td>\n",
+       "      <td>43.520000</td>\n",
+       "      <td>49.320000</td>\n",
+       "      <td>53.640000</td>\n",
+       "      <td>30.520000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2076-2099</td>\n",
+       "      <td>2076</td>\n",
+       "      <td>2099</td>\n",
+       "      <td>49.000000</td>\n",
+       "      <td>1176.0</td>\n",
+       "      <td>60.375000</td>\n",
+       "      <td>43.875000</td>\n",
+       "      <td>49.291667</td>\n",
+       "      <td>55.541667</td>\n",
+       "      <td>35.666667</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  scenario     period  start_year  end_year  mean_lowflow_days  \\\n",
+       "0   ssp126  2026-2050        2026      2050          34.800000   \n",
+       "1   ssp126  2051-2075        2051      2075          38.520000   \n",
+       "2   ssp126  2076-2099        2076      2099          32.333333   \n",
+       "3   ssp245  2026-2050        2026      2050          41.640000   \n",
+       "4   ssp245  2051-2075        2051      2075          35.040000   \n",
+       "5   ssp245  2076-2099        2076      2099          28.500000   \n",
+       "6   ssp370  2026-2050        2026      2050          35.080000   \n",
+       "7   ssp370  2051-2075        2051      2075          46.960000   \n",
+       "8   ssp370  2076-2099        2076      2099          49.000000   \n",
+       "\n",
+       "   total_lowflow_days  set_1_avg  set_2_avg  set_3_avg  set_4_avg  set_5_avg  \n",
+       "0               870.0  46.360000  30.400000  35.560000  39.200000  22.280000  \n",
+       "1               963.0  50.160000  35.280000  39.040000  42.640000  26.320000  \n",
+       "2               776.0  43.916667  28.916667  33.750000  34.875000  19.666667  \n",
+       "3              1041.0  50.600000  37.640000  42.280000  45.200000  32.720000  \n",
+       "4               876.0  44.960000  31.920000  35.200000  37.000000  26.000000  \n",
+       "5               684.0  38.708333  24.250000  29.958333  32.458333  17.166667  \n",
+       "6               877.0  44.200000  31.400000  37.120000  38.840000  23.920000  \n",
+       "7              1174.0  58.120000  43.520000  49.320000  53.640000  30.520000  \n",
+       "8              1176.0  60.375000  43.875000  49.291667  55.541667  35.666667  "
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "projection_table = pd.DataFrame(projection_results)\n",
+    "\n",
+    "projection_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "09a29265-5d22-4916-874e-270a2107fd53",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>period</th>\n",
+       "      <th>2026-2050</th>\n",
+       "      <th>2051-2075</th>\n",
+       "      <th>2076-2099</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>scenario</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ssp126</th>\n",
+       "      <td>34.80</td>\n",
+       "      <td>38.52</td>\n",
+       "      <td>32.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ssp245</th>\n",
+       "      <td>41.64</td>\n",
+       "      <td>35.04</td>\n",
+       "      <td>28.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ssp370</th>\n",
+       "      <td>35.08</td>\n",
+       "      <td>46.96</td>\n",
+       "      <td>49.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "period    2026-2050  2051-2075  2076-2099\n",
+       "scenario                                 \n",
+       "ssp126        34.80      38.52  32.333333\n",
+       "ssp245        41.64      35.04  28.500000\n",
+       "ssp370        35.08      46.96  49.000000"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "projection_table = pd.DataFrame(projection_results)\n",
+    "\n",
+    "summary_table = projection_table.pivot(\n",
+    "    index=\"scenario\",\n",
+    "    columns=\"period\",\n",
+    "    values=\"mean_lowflow_days\"\n",
+    ")\n",
+    "\n",
+    "summary_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "85d81692-9bd9-4c68-8976-7d717451589a",
+   "metadata": {},
+   "source": [
+    "# 5. Compare forcing inputs "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "id": "23a41e8a-8bf1-41f1-b8df-051deb1f3e78",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_file_for_var(folder, var_name):\n",
+    "\n",
+    "    folder = Path(folder)\n",
+    "\n",
+    "    # First try exact final variable pattern, then broader search\n",
+    "    matches = list(folder.glob(f\"*_{var_name}.nc\"))\n",
+    "\n",
+    "    if len(matches) == 0:\n",
+    "        matches = list(folder.glob(f\"*{var_name}*.nc\"))\n",
+    "\n",
+    "    if len(matches) == 0:\n",
+    "        raise FileNotFoundError(f\"No NetCDF file found for {var_name} in {folder}\")\n",
+    "\n",
+    "    if len(matches) > 1:\n",
+    "        print(f\"Multiple files found for {var_name}, using first:\")\n",
+    "        for match in matches:\n",
+    "            print(\" -\", match.name)\n",
+    "\n",
+    "    return matches[0]\n",
+    "\n",
+    "\n",
+    "\n",
+    "def get_dataarray(dataset, preferred_name):\n",
+    "\n",
+    "    if preferred_name in dataset.data_vars:\n",
+    "        return dataset[preferred_name]\n",
+    "\n",
+    "    first_var = list(dataset.data_vars)[0]\n",
+    "    print(f\"Variable {preferred_name} not found, using {first_var} instead.\")\n",
+    "    return dataset[first_var]\n",
+    "\n",
+    "\n",
+    "def load_variable(folder, var_name):\n",
+    "\n",
+    "    file_path = find_file_for_var(folder, var_name)\n",
+    "\n",
+    "    ds = xr.open_dataset(file_path)\n",
+    "    da = get_dataarray(ds, var_name).squeeze()\n",
+    "    \n",
+    "        # Normalize daily time coordinate: removes 11:30 / 12:00 differences\n",
+    "    da = da.assign_coords(time=pd.to_datetime(da.time.values).normalize())\n",
+    "\n",
+    "    if \"time\" not in da.dims:\n",
+    "        raise ValueError(f\"{file_path} does not contain a time dimension.\")\n",
+    "\n",
+    "    return da, ds, file_path\n",
+    "\n",
+    "def to_series(da):\n",
+    "    return pd.Series(\n",
+    "        data=da.values.squeeze(),\n",
+    "        index=pd.to_datetime(da[\"time\"].values),\n",
+    "        name=da.name,\n",
+    "    )\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "id": "af3b7ac6-6400-4fb2-982c-acba524b2128",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def forcing_summary_period(scenario, start_year, end_year):\n",
+    "\n",
+    "    forcing_path = forcing_path_cmip(scenario, start_year, end_year)\n",
+    "\n",
+    "    variables = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "    rows = []\n",
+    "\n",
+    "    for var_name in variables:\n",
+    "\n",
+    "        da, _, _ = load_variable(forcing_path, var_name)\n",
+    "        s = to_series(da)\n",
+    "\n",
+    "        if var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "            s = s * 86400\n",
+    "            value = s.sum() / (end_year - start_year + 1)\n",
+    "            stat = \"mean annual sum mm/year\"\n",
+    "\n",
+    "        elif var_name == \"tas\":\n",
+    "            s = s - 273.15\n",
+    "            value = s.mean()\n",
+    "            stat = \"mean °C\"\n",
+    "\n",
+    "        elif var_name == \"rsds\":\n",
+    "            value = s.mean()\n",
+    "            stat = \"mean W/m²\"\n",
+    "\n",
+    "        rows.append({\n",
+    "            \"scenario\": scenario,\n",
+    "            \"period\": f\"{start_year}-{end_year}\",\n",
+    "            \"variable\": var_name,\n",
+    "            \"statistic\": stat,\n",
+    "            \"value\": value\n",
+    "        })\n",
+    "\n",
+    "    return pd.DataFrame(rows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "id": "a1684e51-2489-4fad-9ccd-6c98c042ae9b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "forcing_summaries = []\n",
+    "\n",
+    "for scenario in scenarios:\n",
+    "\n",
+    "    for i in range(len(periods[0])):\n",
+    "\n",
+    "        start_year = periods[0][i]\n",
+    "        end_year = periods[1][i]\n",
+    "\n",
+    "        forcing_summaries.append(\n",
+    "            forcing_summary_period(scenario, start_year, end_year)\n",
+    "        )\n",
+    "\n",
+    "forcing_summary_table = pd.concat(forcing_summaries, ignore_index=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "id": "8ebc562a-dd7a-4fc5-95ad-fcc2da9a92d1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>evspsblpot</th>\n",
+       "      <th>pr</th>\n",
+       "      <th>rsds</th>\n",
+       "      <th>tas</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>scenario</th>\n",
+       "      <th>period</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">ssp126</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <td>621.115827</td>\n",
+       "      <td>633.866016</td>\n",
+       "      <td>138.530518</td>\n",
+       "      <td>2.507785</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2050-2075</th>\n",
+       "      <td>625.834602</td>\n",
+       "      <td>630.108168</td>\n",
+       "      <td>138.729980</td>\n",
+       "      <td>2.994848</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2075-2099</th>\n",
+       "      <td>621.526396</td>\n",
+       "      <td>645.313406</td>\n",
+       "      <td>138.176804</td>\n",
+       "      <td>2.738721</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">ssp245</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <td>628.019652</td>\n",
+       "      <td>622.963642</td>\n",
+       "      <td>139.454956</td>\n",
+       "      <td>2.663425</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2050-2075</th>\n",
+       "      <td>632.682703</td>\n",
+       "      <td>637.349485</td>\n",
+       "      <td>138.314972</td>\n",
+       "      <td>3.588089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2075-2099</th>\n",
+       "      <td>635.643577</td>\n",
+       "      <td>659.815115</td>\n",
+       "      <td>137.841309</td>\n",
+       "      <td>3.646670</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">ssp370</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <td>623.396508</td>\n",
+       "      <td>640.490159</td>\n",
+       "      <td>138.547470</td>\n",
+       "      <td>2.715807</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2050-2075</th>\n",
+       "      <td>636.281969</td>\n",
+       "      <td>650.255712</td>\n",
+       "      <td>136.660095</td>\n",
+       "      <td>4.362177</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2075-2099</th>\n",
+       "      <td>656.929423</td>\n",
+       "      <td>645.734789</td>\n",
+       "      <td>136.637268</td>\n",
+       "      <td>5.423460</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "variable            evspsblpot          pr        rsds       tas\n",
+       "scenario period                                                 \n",
+       "ssp126   2025-2050  621.115827  633.866016  138.530518  2.507785\n",
+       "         2050-2075  625.834602  630.108168  138.729980  2.994848\n",
+       "         2075-2099  621.526396  645.313406  138.176804  2.738721\n",
+       "ssp245   2025-2050  628.019652  622.963642  139.454956  2.663425\n",
+       "         2050-2075  632.682703  637.349485  138.314972  3.588089\n",
+       "         2075-2099  635.643577  659.815115  137.841309  3.646670\n",
+       "ssp370   2025-2050  623.396508  640.490159  138.547470  2.715807\n",
+       "         2050-2075  636.281969  650.255712  136.660095  4.362177\n",
+       "         2075-2099  656.929423  645.734789  136.637268  5.423460"
+      ]
+     },
+     "execution_count": 102,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "forcing_summary_pivot = forcing_summary_table.pivot_table(\n",
+    "    index=[\"scenario\", \"period\"],\n",
+    "    columns=\"variable\",\n",
+    "    values=\"value\"\n",
+    ")\n",
+    "\n",
+    "forcing_summary_pivot"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "101971f4-29d2-4cae-8d85-c0536f9a0309",
+   "metadata": {},
+   "source": [
+    "# 6. CDF"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "964447be-e895-417f-8d1c-49f12ac9f8b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_lowflow_cdf_by_scenario(lowflow_results, scenarios, periods):\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "\n",
+    "            lowflow_table = lowflow_results[key]\n",
+    "\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        values = np.sort(all_lowflows)\n",
+    "        cdf = np.arange(1, len(values) + 1) / len(values)\n",
+    "\n",
+    "        plt.plot(\n",
+    "            values,\n",
+    "            cdf,\n",
+    "            marker=\"o\",\n",
+    "            label=scenario\n",
+    "        )\n",
+    "\n",
+    "    plt.xlabel(\"Annual low-flow days\")\n",
+    "    plt.ylabel(\"Cumulative probability\")\n",
+    "    plt.title(\"CDF of annual low-flow days by SSP scenario\")\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "id": "29457adb-46b7-4dba-9bd1-fe4c9680b0e3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "periods = [\n",
+    "    [2026, 2051, 2076],\n",
+    "    [2050, 2075, 2099]\n",
+    "]\n",
+    "\n",
+    "plot_lowflow_cdf_by_scenario(\n",
+    "    lowflow_results=lowflow_results,\n",
+    "    scenarios=scenarios,\n",
+    "    periods=periods\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 125,
+   "id": "abf22269-2b3b-4d07-976f-eaa319abc450",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_lowflow_exceedance_by_scenario(lowflow_results, scenarios, periods):\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "            lowflow_table = lowflow_results[key]\n",
+    "\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        values = np.sort(all_lowflows)\n",
+    "        exceedance = 1 - (np.arange(1, len(values) + 1) / len(values))\n",
+    "\n",
+    "        plt.plot(values, exceedance, marker=\"o\", label=scenario)\n",
+    "\n",
+    "    plt.xlabel(\"Annual low-flow days\")\n",
+    "    plt.ylabel(\"Exceedance probability\")\n",
+    "    plt.title(\"Exceedance probability of annual low-flow days\")\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 126,
+   "id": "32f34c72-bda8-4494-a39d-a20e6cde0c23",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_lowflow_exceedance_by_scenario(lowflow_results, scenarios, periods)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "id": "35dd004b-bef3-4970-9823-a44ced707350",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def boxplot_lowflow_by_scenario(lowflow_results, scenarios, periods):\n",
+    "\n",
+    "    data = []\n",
+    "    labels = []\n",
+    "\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "            lowflow_table = lowflow_results[key]\n",
+    "\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        data.append(all_lowflows)\n",
+    "        labels.append(scenario)\n",
+    "\n",
+    "    plt.figure(figsize=(7, 5))\n",
+    "    plt.boxplot(data, labels=labels)\n",
+    "    plt.ylabel(\"Annual low-flow days\")\n",
+    "    plt.title(\"Distribution of annual low-flow days by SSP scenario\")\n",
+    "    plt.grid(True)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "id": "dfc21d1f-e6ec-4e0c-8d1e-30d33bae63c0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "boxplot_lowflow_by_scenario(lowflow_results, scenarios, periods)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 133,
+   "id": "ed383273-c6ab-419b-8468-db2574759ca6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_quantile_table(lowflow_results, scenarios, periods):\n",
+    "\n",
+    "    rows = []\n",
+    "\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "            lowflow_table = lowflow_results[key]\n",
+    "\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        values = pd.Series(all_lowflows)\n",
+    "\n",
+    "        rows.append({\n",
+    "            \"scenario\": scenario,\n",
+    "            \"mean\": values.mean(),\n",
+    "            \"median\": values.median(),\n",
+    "            \"p75\": values.quantile(0.75),\n",
+    "            \"p90\": values.quantile(0.90),\n",
+    "            \"max\": values.max()\n",
+    "        })\n",
+    "\n",
+    "    return pd.DataFrame(rows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 134,
+   "id": "d8f4d969-f769-4d5d-a1ff-91d7d0c36ca6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>median</th>\n",
+       "      <th>p75</th>\n",
+       "      <th>p90</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ssp126</td>\n",
+       "      <td>35.256757</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>51.00</td>\n",
+       "      <td>71.8</td>\n",
+       "      <td>143.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ssp245</td>\n",
+       "      <td>35.148649</td>\n",
+       "      <td>22.5</td>\n",
+       "      <td>54.75</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>141.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>43.608108</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>63.00</td>\n",
+       "      <td>94.1</td>\n",
+       "      <td>130.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  scenario       mean  median    p75   p90    max\n",
+       "0   ssp126  35.256757    31.0  51.00  71.8  143.0\n",
+       "1   ssp245  35.148649    22.5  54.75  79.0  141.0\n",
+       "2   ssp370  43.608108    43.0  63.00  94.1  130.0"
+      ]
+     },
+     "execution_count": 134,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lowflow_quantile_table(lowflow_results, scenarios, periods)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5cac1501-763f-4b20-a78b-710b2f8f5439",
+   "metadata": {},
+   "source": [
+    "# 7. Algorithm 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "id": "25308279-2c05-4416-ba45-eb4bbe144816",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "selected_scenario = \"ssp370\"\n",
+    "start_year = 2075\n",
+    "end_year = 2099\n",
+    "AFDD_critical = 30"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "id": "ffd467d3-7a30-4ae2-9a69-3cf8cdfcf079",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "forcing_path_CMIP = forcing_path_cmip(\n",
+    "    scenario=selected_scenario,\n",
+    "    start_year=start_year,\n",
+    "    end_year=end_year\n",
+    ")\n",
+    "\n",
+    "CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(\n",
+    "    directory=forcing_path_CMIP\n",
+    ")\n",
+    "\n",
+    "ensemble_data_CMIP = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=CMIP_forcing\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "id": "90cca3f7-b8fc-43ff-83a7-52109a7ac06d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_freshet_start_dates(ensemble_data, start_year, end_year):\n",
+    "\n",
+    "    freshet_dates = []\n",
+    "\n",
+    "    for year in range(start_year, end_year + 1):\n",
+    "\n",
+    "        year_start = pd.to_datetime(f\"{year}-03-01\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-08-01\")\n",
+    "\n",
+    "        season_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        above_critical = season_data[season_data[\"Mean\"] > q_critical]\n",
+    "\n",
+    "        if len(above_critical) > 0:\n",
+    "            freshet_date = above_critical.index[0]\n",
+    "            discharge = above_critical.iloc[0][\"Mean\"]\n",
+    "        else:\n",
+    "            freshet_date = pd.NaT\n",
+    "            discharge = np.nan\n",
+    "\n",
+    "        freshet_dates.append({\n",
+    "            \"year\": year,\n",
+    "            \"freshet_start\": freshet_date,\n",
+    "            \"freshet_discharge\": discharge\n",
+    "        })\n",
+    "\n",
+    "    return pd.DataFrame(freshet_dates)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "id": "cc42c522-f9e6-4ed4-9c20-ca1a79863683",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_freezeup_dates(forcing_path, start_year, end_year, AFDD_critical=30):\n",
+    "\n",
+    "    tas_da, _, _ = load_variable(forcing_path, \"tas\")\n",
+    "\n",
+    "    tas = to_series(tas_da)\n",
+    "\n",
+    "    if tas.mean() > 100:\n",
+    "        tas = tas - 273.15\n",
+    "\n",
+    "    freezeup_dates = []\n",
+    "\n",
+    "    for year in range(start_year, end_year + 1):\n",
+    "\n",
+    "        year_start = pd.to_datetime(f\"{year}-10-01\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-12-31\")\n",
+    "\n",
+    "        year_tas = tas[\n",
+    "            (tas.index >= year_start) &\n",
+    "            (tas.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        AFDD = 0\n",
+    "        freezeup_date = pd.NaT\n",
+    "        freezeup_temp = np.nan\n",
+    "\n",
+    "        for date, temp in year_tas.items():\n",
+    "\n",
+    "            if temp < 0:\n",
+    "                AFDD += -temp\n",
+    "\n",
+    "            if AFDD >= AFDD_critical:\n",
+    "                freezeup_date = date\n",
+    "                freezeup_temp = temp\n",
+    "                break\n",
+    "\n",
+    "        freezeup_dates.append({\n",
+    "            \"year\": year,\n",
+    "            \"freezeup_date\": freezeup_date,\n",
+    "            \"AFDD\": AFDD,\n",
+    "            \"temp_at_freezeup\": freezeup_temp\n",
+    "        })\n",
+    "\n",
+    "    return pd.DataFrame(freezeup_dates)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "id": "7a34f8d4-6ec5-4cc1-ac98-60609c6cb7bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>freshet_start</th>\n",
+       "      <th>freshet_discharge</th>\n",
+       "      <th>freezeup_date</th>\n",
+       "      <th>AFDD</th>\n",
+       "      <th>temp_at_freezeup</th>\n",
+       "      <th>open_water_days</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2075</td>\n",
+       "      <td>2075-04-21</td>\n",
+       "      <td>519.219346</td>\n",
+       "      <td>2075-11-19</td>\n",
+       "      <td>35.262756</td>\n",
+       "      <td>-8.498932</td>\n",
+       "      <td>212</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2076</td>\n",
+       "      <td>2076-03-24</td>\n",
+       "      <td>520.049117</td>\n",
+       "      <td>2076-11-21</td>\n",
+       "      <td>39.384277</td>\n",
+       "      <td>-9.844208</td>\n",
+       "      <td>242</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2077</td>\n",
+       "      <td>2077-03-29</td>\n",
+       "      <td>546.557068</td>\n",
+       "      <td>2077-11-10</td>\n",
+       "      <td>32.923767</td>\n",
+       "      <td>-5.950165</td>\n",
+       "      <td>226</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2078</td>\n",
+       "      <td>2078-04-07</td>\n",
+       "      <td>514.114383</td>\n",
+       "      <td>2078-10-22</td>\n",
+       "      <td>30.640839</td>\n",
+       "      <td>-5.857758</td>\n",
+       "      <td>198</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2079</td>\n",
+       "      <td>2079-03-30</td>\n",
+       "      <td>510.619604</td>\n",
+       "      <td>2079-11-27</td>\n",
+       "      <td>33.224365</td>\n",
+       "      <td>-5.251129</td>\n",
+       "      <td>242</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2080</td>\n",
+       "      <td>2080-04-01</td>\n",
+       "      <td>569.975708</td>\n",
+       "      <td>2080-11-23</td>\n",
+       "      <td>37.704834</td>\n",
+       "      <td>-8.989227</td>\n",
+       "      <td>236</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2081</td>\n",
+       "      <td>2081-04-01</td>\n",
+       "      <td>542.075464</td>\n",
+       "      <td>2081-11-16</td>\n",
+       "      <td>30.076477</td>\n",
+       "      <td>-5.813904</td>\n",
+       "      <td>229</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2082</td>\n",
+       "      <td>2082-04-07</td>\n",
+       "      <td>538.807757</td>\n",
+       "      <td>2082-10-26</td>\n",
+       "      <td>30.872345</td>\n",
+       "      <td>-7.023956</td>\n",
+       "      <td>202</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2083</td>\n",
+       "      <td>2083-04-20</td>\n",
+       "      <td>504.327828</td>\n",
+       "      <td>2083-11-11</td>\n",
+       "      <td>40.646301</td>\n",
+       "      <td>-12.157623</td>\n",
+       "      <td>205</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2084</td>\n",
+       "      <td>2084-04-01</td>\n",
+       "      <td>534.445682</td>\n",
+       "      <td>2084-11-15</td>\n",
+       "      <td>31.272736</td>\n",
+       "      <td>-2.706055</td>\n",
+       "      <td>228</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2085</td>\n",
+       "      <td>2085-03-15</td>\n",
+       "      <td>535.753353</td>\n",
+       "      <td>2085-11-18</td>\n",
+       "      <td>32.819702</td>\n",
+       "      <td>-8.045135</td>\n",
+       "      <td>248</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086-04-08</td>\n",
+       "      <td>510.921158</td>\n",
+       "      <td>2086-10-30</td>\n",
+       "      <td>31.245911</td>\n",
+       "      <td>-5.614410</td>\n",
+       "      <td>205</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2087</td>\n",
+       "      <td>2087-04-09</td>\n",
+       "      <td>544.183194</td>\n",
+       "      <td>2087-10-26</td>\n",
+       "      <td>36.040955</td>\n",
+       "      <td>-6.891754</td>\n",
+       "      <td>200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2088</td>\n",
+       "      <td>2088-03-23</td>\n",
+       "      <td>513.473558</td>\n",
+       "      <td>2088-11-23</td>\n",
+       "      <td>34.870117</td>\n",
+       "      <td>-9.704865</td>\n",
+       "      <td>245</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2089</td>\n",
+       "      <td>2089-03-30</td>\n",
+       "      <td>540.635754</td>\n",
+       "      <td>2089-11-10</td>\n",
+       "      <td>33.336151</td>\n",
+       "      <td>-5.598053</td>\n",
+       "      <td>225</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2090</td>\n",
+       "      <td>2090-03-01</td>\n",
+       "      <td>805.603357</td>\n",
+       "      <td>2090-11-28</td>\n",
+       "      <td>38.458557</td>\n",
+       "      <td>-8.481995</td>\n",
+       "      <td>272</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2091</td>\n",
+       "      <td>2091-03-05</td>\n",
+       "      <td>523.091265</td>\n",
+       "      <td>2091-11-26</td>\n",
+       "      <td>30.777435</td>\n",
+       "      <td>-5.819916</td>\n",
+       "      <td>266</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2092</td>\n",
+       "      <td>2092-04-15</td>\n",
+       "      <td>537.450487</td>\n",
+       "      <td>2092-12-10</td>\n",
+       "      <td>31.693726</td>\n",
+       "      <td>-5.528595</td>\n",
+       "      <td>239</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2093</td>\n",
+       "      <td>2093-03-04</td>\n",
+       "      <td>503.797591</td>\n",
+       "      <td>2093-11-17</td>\n",
+       "      <td>31.754303</td>\n",
+       "      <td>-2.685608</td>\n",
+       "      <td>258</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2094</td>\n",
+       "      <td>2094-03-25</td>\n",
+       "      <td>563.613810</td>\n",
+       "      <td>2094-11-12</td>\n",
+       "      <td>32.975311</td>\n",
+       "      <td>-10.855835</td>\n",
+       "      <td>232</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2095</td>\n",
+       "      <td>2095-03-06</td>\n",
+       "      <td>573.481886</td>\n",
+       "      <td>2095-11-15</td>\n",
+       "      <td>32.214935</td>\n",
+       "      <td>-7.631531</td>\n",
+       "      <td>254</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2096</td>\n",
+       "      <td>2096-03-23</td>\n",
+       "      <td>520.442698</td>\n",
+       "      <td>2096-11-25</td>\n",
+       "      <td>34.426178</td>\n",
+       "      <td>-6.217194</td>\n",
+       "      <td>247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2097</td>\n",
+       "      <td>2097-04-19</td>\n",
+       "      <td>511.132103</td>\n",
+       "      <td>2097-11-19</td>\n",
+       "      <td>35.140442</td>\n",
+       "      <td>-7.922821</td>\n",
+       "      <td>214</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2098</td>\n",
+       "      <td>2098-03-16</td>\n",
+       "      <td>601.581833</td>\n",
+       "      <td>2098-11-14</td>\n",
+       "      <td>31.264648</td>\n",
+       "      <td>-9.818970</td>\n",
+       "      <td>243</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2099</td>\n",
+       "      <td>2099-03-12</td>\n",
+       "      <td>545.881703</td>\n",
+       "      <td>2099-11-21</td>\n",
+       "      <td>32.216797</td>\n",
+       "      <td>-10.493774</td>\n",
+       "      <td>254</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    year freshet_start  freshet_discharge freezeup_date       AFDD  \\\n",
+       "0   2075    2075-04-21         519.219346    2075-11-19  35.262756   \n",
+       "1   2076    2076-03-24         520.049117    2076-11-21  39.384277   \n",
+       "2   2077    2077-03-29         546.557068    2077-11-10  32.923767   \n",
+       "3   2078    2078-04-07         514.114383    2078-10-22  30.640839   \n",
+       "4   2079    2079-03-30         510.619604    2079-11-27  33.224365   \n",
+       "5   2080    2080-04-01         569.975708    2080-11-23  37.704834   \n",
+       "6   2081    2081-04-01         542.075464    2081-11-16  30.076477   \n",
+       "7   2082    2082-04-07         538.807757    2082-10-26  30.872345   \n",
+       "8   2083    2083-04-20         504.327828    2083-11-11  40.646301   \n",
+       "9   2084    2084-04-01         534.445682    2084-11-15  31.272736   \n",
+       "10  2085    2085-03-15         535.753353    2085-11-18  32.819702   \n",
+       "11  2086    2086-04-08         510.921158    2086-10-30  31.245911   \n",
+       "12  2087    2087-04-09         544.183194    2087-10-26  36.040955   \n",
+       "13  2088    2088-03-23         513.473558    2088-11-23  34.870117   \n",
+       "14  2089    2089-03-30         540.635754    2089-11-10  33.336151   \n",
+       "15  2090    2090-03-01         805.603357    2090-11-28  38.458557   \n",
+       "16  2091    2091-03-05         523.091265    2091-11-26  30.777435   \n",
+       "17  2092    2092-04-15         537.450487    2092-12-10  31.693726   \n",
+       "18  2093    2093-03-04         503.797591    2093-11-17  31.754303   \n",
+       "19  2094    2094-03-25         563.613810    2094-11-12  32.975311   \n",
+       "20  2095    2095-03-06         573.481886    2095-11-15  32.214935   \n",
+       "21  2096    2096-03-23         520.442698    2096-11-25  34.426178   \n",
+       "22  2097    2097-04-19         511.132103    2097-11-19  35.140442   \n",
+       "23  2098    2098-03-16         601.581833    2098-11-14  31.264648   \n",
+       "24  2099    2099-03-12         545.881703    2099-11-21  32.216797   \n",
+       "\n",
+       "    temp_at_freezeup  open_water_days  \n",
+       "0          -8.498932              212  \n",
+       "1          -9.844208              242  \n",
+       "2          -5.950165              226  \n",
+       "3          -5.857758              198  \n",
+       "4          -5.251129              242  \n",
+       "5          -8.989227              236  \n",
+       "6          -5.813904              229  \n",
+       "7          -7.023956              202  \n",
+       "8         -12.157623              205  \n",
+       "9          -2.706055              228  \n",
+       "10         -8.045135              248  \n",
+       "11         -5.614410              205  \n",
+       "12         -6.891754              200  \n",
+       "13         -9.704865              245  \n",
+       "14         -5.598053              225  \n",
+       "15         -8.481995              272  \n",
+       "16         -5.819916              266  \n",
+       "17         -5.528595              239  \n",
+       "18         -2.685608              258  \n",
+       "19        -10.855835              232  \n",
+       "20         -7.631531              254  \n",
+       "21         -6.217194              247  \n",
+       "22         -7.922821              214  \n",
+       "23         -9.818970              243  \n",
+       "24        -10.493774              254  "
+      ]
+     },
+     "execution_count": 119,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "freshet_dates = find_freshet_start_dates(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    start_year=start_year,\n",
+    "    end_year=end_year\n",
+    ")\n",
+    "\n",
+    "freezeup_dates = find_freezeup_dates(\n",
+    "    forcing_path=forcing_path_CMIP,\n",
+    "    start_year=start_year,\n",
+    "    end_year=end_year,\n",
+    "    AFDD_critical=AFDD_critical\n",
+    ")\n",
+    "\n",
+    "open_water_dates = freshet_dates.merge(\n",
+    "    freezeup_dates,\n",
+    "    on=\"year\",\n",
+    "    how=\"inner\"\n",
+    ")\n",
+    "\n",
+    "open_water_dates[\"open_water_days\"] = (\n",
+    "    open_water_dates[\"freezeup_date\"] - open_water_dates[\"freshet_start\"]\n",
+    ").dt.days\n",
+    "\n",
+    "open_water_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b3ab704a-8d4d-41c8-bb15-afdabd658204",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Workyard/Trial model LAR.ipynb b/Workyard/Trial model LAR.ipynb
new file mode 100644
index 00000000..5adbaf59
--- /dev/null
+++ b/Workyard/Trial model LAR.ipynb	
@@ -0,0 +1,844 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bdb4216e-a341-4c2b-a410-35170773a9a7",
+   "metadata": {},
+   "source": [
+    "## Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "d197b8f0-0f85-4a41-b2fb-1b2a8cf3f9f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "dd7b7d3f-1489-4723-bb51-f3cffcb7a85c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "1c8aee93-b2d6-4291-89ae-1d29e69268cd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining basin size\n",
+    "\n",
+    "basin_size = 132572"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "d7dce039-d1f3-44a0-b646-98c32ecffb28",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "experiment_start_date = \"2019-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2024-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "d330bf37-7419-4287-81af-3d09e4c7a30e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"ERA5-2019-2024\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "46ea8b1e-fb73-49ed-855c-4d95cd932748",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "8bb224ad-d23c-475f-b6af-4a6023a17044",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>22193</th>\n",
+       "      <td>2019-01-01</td>\n",
+       "      <td>213.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22194</th>\n",
+       "      <td>2019-01-02</td>\n",
+       "      <td>213.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22195</th>\n",
+       "      <td>2019-01-03</td>\n",
+       "      <td>213.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22196</th>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>214.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22197</th>\n",
+       "      <td>2019-01-05</td>\n",
+       "      <td>214.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Date  discharge_m3s\n",
+       "22193 2019-01-01          213.0\n",
+       "22194 2019-01-02          213.0\n",
+       "22195 2019-01-03          213.0\n",
+       "22196 2019-01-04          214.0\n",
+       "22197 2019-01-05          214.0"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "q_obs = q_obs[\n",
+    "    (q_obs[\"Date\"] >= start_date) &\n",
+    "    (q_obs[\"Date\"] <= end_date)\n",
+    "].copy()\n",
+    "\n",
+    "q_obs.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "7f6f57aa-9f39-4524-ba3a-34f55035ebab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"])\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "77e79b20-3e4d-405a-bd88-16bdc50bdb39",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2024-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2024'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'2019-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2024-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-2019-2024'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "ca2be146-1112-4806-a44f-d57ebd4442c9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.35776</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.432509</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">192.67085</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.66088</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.289296</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.323766</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.037268</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.004399</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.146504</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m7.35776\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.432509\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m192.67085\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.66088\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.289296\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.323766\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.037268\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.004399\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.146504\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "# par_0 = [4.45787, 0.42307, 201.57602, 2.36497, 0.26755, 8.62964, 0.083568, 0.0037073, 0.29645]\n",
+    "# par_0 = [2.79874, 0.49211, 255.96478, 1.782968, 0.503199, 6.095956, 0.33279, 0.10539, 0.63857]\n",
+    "# par_0 = [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606]         # 0.725 val, 0.x cal - Fav run 2\n",
+    "# par_0 = [6.28908, 0.423917, 173.56627, 1.63144, 0.402586, 6.56151, 0.0456809, 0.00313744, 0.516696]                 # 0.702 val, 0.x cal\n",
+    "# par_0 = [6.4919, 0.386877, 221.78625, 1.388269, 0.276453, 4.9870704, 0.04126777, 0.05640195, 1.148877]              # 0.668 val, 0.x cal\n",
+    "# par_0 = [7.502398, 0.38028, 194.1899, 1.680197, 0.47956, 4.8566806, 0.041745354, 0.02833896, 1.051862]              # 0.677 val, 0.x cal\n",
+    "# par_0 = [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392]                        # 0.781 val, 0.776 cal\n",
+    "# par_0 = [6.16512, 0.4369419, 151.2515900, 1.727835, 0.3771705, 6.19265974, 0.06959136, 0.001310818, 0.8130732]      # 0.664 val, 0.791 cal\n",
+    "# par_0 = [5.7107, 0.441634, 172.81305, 1.87367, 0.588802, 5.498147, 0.060305, 0.019666, 1.2011814]                    # x val, 0.73 cal         Start of 5+ months exclusion\n",
+    "par_0 = [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504]                    # 0.82 val, 0.818 cal - Fav run 1      \n",
+    "# par_0 = [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]                    #  val,  0.77 cal    \n",
+    "# par_0 = [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857]                           # 0.78 val, 0.71 cal - potential inclusion\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"          # Snowmelt factor\n",
+    "               ]\n",
+    "\n",
+    "# Initial: par_0 = [5.085, 0.55, 100.373, 1.612, 0.545, 3.801, 0.196, 0.00, 0.185]\n",
+    "\n",
+    "print(list(zip(par_names, par_0)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "d5e5bcb4-bf90-470b-90ed-4a0b9d80c35d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5bbaae8e-18fa-4383-9973-5a2560840699",
+   "metadata": {},
+   "source": [
+    "## Setup model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "055bdbc8-af1f-41ac-ad1d-b4da4d6785f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create model object\n",
+    "\n",
+    "model = ewatercycle.models.HBV(forcing=ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "44092959-524a-4330-a274-77cfad0eacd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create config file\n",
+    "\n",
+    "config_file, _ = model.setup(parameters=par_0, initial_storages=s_0, cfg_dir=hbv_config)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "079368de-30cf-491f-8cc9-2021f6a4bfa6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Initialising model\n",
+    "\n",
+    "model.initialize(config_file)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "327222c7-bd08-4992-826e-07f40f61b783",
+   "metadata": {},
+   "source": [
+    "## Running the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "93b4084b-21e5-4009-9fc7-122b7b739a86",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define outputs\n",
+    "\n",
+    "Q_m = []\n",
+    "time = []\n",
+    "\n",
+    "while model.time < model.end_time:\n",
+    "    model.update()\n",
+    "    Q_m.append(model.get_value(\"Q\")[0])\n",
+    "    time.append(pd.Timestamp(model.time_as_datetime))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "f1bb58f8-3dee-43eb-abc8-4af333b5d064",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.finalize()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "39872047-cba7-47c4-b2f8-6ed47c56fdc6",
+   "metadata": {},
+   "source": [
+    "## Process results "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "715c5274-8ab4-45d0-b154-bb0cf30b52bd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Make Series for model output and q_obs\n",
+    "model_output_mmday = pd.Series(data=Q_m, name=\"Modelled discharge\", index=time)\n",
+    "model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "# Date_obs = q_obs[\"Date\"]\n",
+    "# discharge_m3s_obs = q_obs[\"discharge_m3s\"]\n",
+    "\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])\n",
+    "\n",
+    "# q_obs.set_index(\"Date\")[\"discharge_m3s\"]\n",
+    "# observed_output.name = \"Observed discharge\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "9ee05f10-c416-4238-be5f-0dd3901ba3ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for year range\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "observed_output.plot(label=\"Observed discharge\")\n",
+    "model_output_m3s.plot(label=\"Modelled discharge\")\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f'Critical discharge ({q_critical} m³/s)', color='black')\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Modelled vs observed discharge at 07DA001\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.xlim(\"2020-01-01\", \"2024-12-31\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "494883ac-e9f0-4806-93d9-bb6a52372309",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for 1 year\n",
+    "\n",
+    "selected_year = 2024\n",
+    "\n",
+    "observed_plot = observed_output\n",
+    "modelled_plot = model_output_m3s\n",
+    "\n",
+    "observed_plot.index = pd.to_datetime(observed_plot.index).tz_localize(None).normalize()\n",
+    "modelled_plot.index = pd.to_datetime(modelled_plot.index).tz_localize(None).normalize()\n",
+    "\n",
+    "plot_data = pd.DataFrame({\n",
+    "    \"Modelled discharge\": modelled_plot,\n",
+    "    \"Observed discharge\": observed_plot\n",
+    "}).dropna()\n",
+    "\n",
+    "plot_data_year = plot_data[plot_data.index.year == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Observed discharge\"],label=\"Observed discharge\")\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge\"],label=\"Modelled discharge\")\n",
+    "\n",
+    "plt.axhline(y=q_critical,linestyle=\":\",color=\"black\",label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001 in {selected_year}\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e2e1edf-f9a2-4d42-8de0-13e5dfc29fd5",
+   "metadata": {},
+   "source": [
+    "### "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b4a1bc95-7122-4372-8b79-991d1344452c",
+   "metadata": {},
+   "source": [
+    "### Log NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "0c3e7e10-16ba-46cf-96a6-9bb2d01f8287",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate log NSE\n",
+    "\n",
+    "def log_NSE(sim, obs):\n",
+    "    \n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "6bcc0656-5f3a-450a-b758-e4c93e9feb07",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call log NSE for relevant timeperiod\n",
+    "\n",
+    "def lognse_for_period(sim, obs, lognse_start, lognse_end):\n",
+    "\n",
+    "    simulated_daily = sim\n",
+    "    observed_daily = obs\n",
+    "\n",
+    "    simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    combined_data = pd.DataFrame({\n",
+    "        \"Modelled discharge\": simulated_daily,\n",
+    "        \"Observed discharge\": observed_daily\n",
+    "    }).dropna()\n",
+    "\n",
+    "    lognse_start = pd.to_datetime(lognse_start).tz_localize(None).normalize()\n",
+    "    lognse_end = pd.to_datetime(lognse_end).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Set time period - Skip 1st year\n",
+    "    combined_data = combined_data[\n",
+    "        (combined_data.index >= lognse_start) &\n",
+    "        (combined_data.index <= lognse_end)\n",
+    "    ]\n",
+    "\n",
+    "    # Exclude winter months\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])\n",
+    "    ]\n",
+    "\n",
+    "    if combined_data.empty:\n",
+    "        print(\"No data left after filtering.\")\n",
+    "        return np.nan\n",
+    "\n",
+    "    log_nse = log_NSE(\n",
+    "        combined_data[\"Modelled discharge\"],\n",
+    "        combined_data[\"Observed discharge\"]\n",
+    "    )\n",
+    "\n",
+    "    return log_nse"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "aa07b0d5-9144-48bf-9ca6-a43812e30020",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">log NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.7712583391721999</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "log NSE: \u001b[1;36m0.7712583391721999\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Return log NSE\n",
+    "evaluation_start = pd.to_datetime(f\"{start_date.year + 1}-01-01\")\n",
+    "\n",
+    "lognse_value = lognse_for_period(\n",
+    "    model_output_m3s,\n",
+    "    observed_output,\n",
+    "    evaluation_start,\n",
+    "    end_date\n",
+    ")\n",
+    "\n",
+    "print(\"log NSE:\", lognse_value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56592f44-6174-48c3-a724-2ed1036228ff",
+   "metadata": {},
+   "source": [
+    "### Days calc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "2d2cda32-61ff-4710-998b-4c4a5205cefc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def days_counter(sim, obs, start_date, end_date):\n",
+    "\n",
+    "    # Combine dataset in Dataframe\n",
+    "    combined_data = pd.DataFrame({\n",
+    "        \"Modelled discharge\": sim,\n",
+    "        \"Observed discharge\": obs\n",
+    "    }).dropna()\n",
+    "\n",
+    "    # Make list of years\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    # Loop through each year\n",
+    "    for i in range(len(years)):\n",
+    "\n",
+    "        year = years[i]\n",
+    "\n",
+    "        # Define start month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "\n",
+    "        year_data = combined_data[\n",
+    "            (combined_data.index >= year_start) &\n",
+    "            (combined_data.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = 0\n",
+    "\n",
+    "        # Loop through each  year to identify lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "            modelled_q = year_data.iloc[j][\"Modelled discharge\"]\n",
+    "\n",
+    "            # Check if that day is low flow and accumulate\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "            if modelled_q < q_critical:\n",
+    "                modelled_lowflow_days += 1\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    # average_error = round(lowflow_days[\"%error\"].abs().mean(), 1)\n",
+    "\n",
+    "    return lowflow_days\n",
+    "    \n",
+    "    # , print(f\"average error = {average_error}%\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "c04c46cc-b80a-40ec-b741-e78fa5168dcd",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: []\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Define period (based on algorithm date > q_critical & freeze-up date output) & prepare\n",
+    "day_calc_start = pd.to_datetime(f\"{start_date.year + 1}-01-01\")\n",
+    "q_critical = 500\n",
+    "\n",
+    "lowflow_days = days_counter(\n",
+    "    sim=model_output_m3s,\n",
+    "    obs=observed_output,\n",
+    "    start_date=day_calc_start,\n",
+    "    end_date=end_date\n",
+    ")\n",
+    "\n",
+    "lowflow_days\n",
+    "\n",
+    "# NOTE TO CHANGE TIME RANGE -> EDIT DEF days_counter FUNCTION UNDER # Define start month day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3d9701be-4df6-41b8-904e-cb4cda096e80",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/_toc.yml b/book/_toc.yml
index 54405714..4152bbe6 100644
--- a/book/_toc.yml
+++ b/book/_toc.yml
@@ -152,7 +152,47 @@ parts:
               - file: thesis_projects/BSc/2025_Q4_ZoeLucius_CEG/Report/References.ipynb
                 title: References
 
+          - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/BSc_MaximedeBekker.md
+            sections:
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/0_Preface.ipynb
+                title: Preface
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/1_Introduction.ipynb
+                title: 1. Introduction
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/2_LiteratureStudy.ipynb
+                title: 2. Literature Study
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/3_Determination_of_navigable_season.ipynb
+                title: 3. Determination of navigable season
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/4_Calibration_of_the_HBV_model.ipynb
+                title: 4. Calibration of the HBV model
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/5_Climate_scenarios.ipynb
+                title: 5. Climate scenarios
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/6_Results.ipynb
+                title: 6. Results
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/7_Discussion.ipynb
+                title: 7. Discussion
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/8_Conclusion.ipynb
+                title: 8. Conclusion
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Reference_list.ipynb
+                title: Reference list
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/AI_Statement.ipynb
+                title: AI Statement
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_A_Snow_depletion_curve.ipynb
+                title: Appendix A: Snow depletion curve
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_B_Calibration_output_parameters.ipynb
+                title: Appendix B: Calibration output parameters
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_C_Calibration_code.ipynb
+                title: Appendix C: Calibration output parameters
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_D_Validation_results_per_year.ipynb
+                title: Appendix D: Validation results per year
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_E_Forcing_data_analysis.ipynb
+                title: Appendix E: Forcing data analysis             
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_F_ERA5_Forcings_Generation.ipynb
+                title: Appendix F: ERA5 Forcings generation
+              - file: thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_G_CMIP6_Forcings_Generation.ipynb
+                title: Appendix G: CMIP6 Forcings generation
 
+                
+                
       - file: thesis_projects/MSc/overview_MSc_thesis_projects.md
 
   - caption: Research Projects
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/BSc_MaximedeBekker.md b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/BSc_MaximedeBekker.md
new file mode 100644
index 00000000..1b7c0265
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/BSc_MaximedeBekker.md
@@ -0,0 +1,16 @@
+# The influence of climate change on the river discharge of the Lower Athabasca River and its implications for navigation   - Maxime de Bekker
+
+
+## Abstract
+
+Climate change is expected to alter discharge patterns in cold region river basins, affecting both low flow conditions and river ice processes. This study investigates how climate exchange may impact discharge in the Lower Athabasca River in Alberta, Canada and what implications this has for navigation. The river is important for Indigenous communities who use navigation for transportation of resources, hunting and fishing. 
+
+To assess navigation constraints, a critical discharge threshold of 500 m3/s at Fort McMurray was used, representing conditions where navigation is restricted at 8 critical locations throughout the rivers. An algorithm was developed to identify when the river breaks and freezes up. This defined the narrowest fixed open water season to occur from 18 May to 17 October. The hydrological HBV model was calibrated and validated using observed discharge data and ERA5 forcing data. The model was then run using CMIP6 MPI-ESM1-2-HR forcing data under future climate scenarios SSP126, SSP245 and SSP370 for the period 2025-2099, where:
+
+- SSP126: Optimistic climate approach, global temperatures expected to increase by 1,8 ℃.
+- SSP245: Limited climate action, global temperatures expected to increase by 2,7 ℃.
+- SSP370: Large global disparities, global temperatures expected to increase by 3,7 ℃.
+
+The results show that annual low flow days are generally higher in the future compared to the historical period. The observed period contains an average of 27 annual low flow days, while future periods range between 31 and 49 annual low flow days depending on the climate scenario. SSP370 shows a weak increasing trend over time. Extreme low flow years become more frequent in all future scenarios. The open water season is also projected to expand, with earlier river ice break up and later freeze up.
+
+These results indicate that climate change is expected to increase navigation constraints in the Lower Athabasca River, especially under SSP370.
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/00_Abstract.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/00_Abstract.ipynb
new file mode 100644
index 00000000..ec75700c
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/00_Abstract.ipynb
@@ -0,0 +1,59 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "b1ad5b62-b24a-42e4-97ea-cc7d4979d955",
+   "metadata": {},
+   "source": [
+    "# Abstract"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ecbdf121-e5b2-4ef6-b4db-e49671e529a6",
+   "metadata": {},
+   "source": [
+    "Climate change is expected to alter discharge patterns in cold region river basins, affecting both low flow conditions and river ice processes. This study investigates how climate exchange may impact discharge in the Lower Athabasca River in Alberta, Canada and what implications this has for navigation. The river is important for Indigenous communities who use navigation for transportation of resources, hunting and fishing. \n",
+    "\n",
+    "To assess navigation constraints, a critical discharge threshold of 500 m3/s at Fort McMurray was used, representing conditions where navigation is restricted at 8 critical locations throughout the rivers. An algorithm was developed to identify when the river breaks and freezes up. This defined the narrowest fixed open water season to occur from 18 May to 17 October. The hydrological HBV model was calibrated and validated using observed discharge data and ERA5 forcing data. The model was then run using CMIP6 MPI-ESM1-2-HR forcing data under future climate scenarios SSP126, SSP245 and SSP370 for the period 2025-2099, where:\n",
+    "\n",
+    "- SSP126: Optimistic climate approach, global temperatures expected to increase by 1,8 ℃.\n",
+    "- SSP245: Limited climate action, global temperatures expected to increase by 2,7 ℃.\n",
+    "- SSP370: Large global disparities, global temperatures expected to increase by 3,7 ℃.\n",
+    "\n",
+    "The results show that annual low flow days are generally higher in the future compared to the historical period. The observed period contains an average of 27 annual low flow days, while future periods range between 31 and 49 annual low flow days depending on the climate scenario. SSP370 shows a weak increasing trend over time. Extreme low flow years become more frequent in all future scenarios. The open water season is also projected to expand, with earlier river ice break up and later freeze up.\n",
+    "\n",
+    "These results indicate that climate change is expected to increase navigation constraints in the Lower Athabasca River, especially under SSP370."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "40c0cc05-f256-4bc3-82f4-9beb9e1b4ef7",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/0_Preface.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/0_Preface.ipynb
new file mode 100644
index 00000000..d4679e07
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/0_Preface.ipynb
@@ -0,0 +1,54 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5d9f1370-1b4b-4cad-aad3-fa7bdf6f6a57",
+   "metadata": {},
+   "source": [
+    "# Preface"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cb620af6-0a59-4e8c-9b01-d3fd09075cef",
+   "metadata": {},
+   "source": [
+    "This report is a bachelor thesis for the BSc Civil Engineering at the Delft University of Technology. The topic was to investigate the impact of climate change on a river of choice. My interest in cold regions and unique processes that occur in these environments inspired me to focus on rivers in Canada. This led to the investigation of the Lower Athabasca River, where climate change may affect low flow conditions, river ice processes and navigation. The relevance of this topic is strengthened by the dependence of Indigenous communities on the river for transportation, hunting and fishing. \n",
+    "\n",
+    "First, I would like to thank my supervisors Dr. Ir. R.W. Hut and Dr. Ir. G.H.W. Schoups for their support and guidance throughout the thesis. I am also grateful to Ir. M. Melotto for technical guidance regarding the usage of eWaterCycle and for providing insights into computational hydrological modelling. Furthermore, I would like to thank my fellow bachelor students Beau Buijtenhuijs, Julian Steenhuisen and Niels Eijer for meaningful discussions about our projects. \n",
+    "\n",
+    "*Delft, June 2026*  \n",
+    "*Maxime de Bekker*\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a108a988-8f7c-4c2f-b445-4263dd7f02bd",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/1_Introduction.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/1_Introduction.ipynb
new file mode 100644
index 00000000..f6ce3580
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/1_Introduction.ipynb
@@ -0,0 +1,140 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "78a03b30-b0ff-4155-acfe-a22e36147559",
+   "metadata": {},
+   "source": [
+    "# 1. Introduction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "80acbbb0-84be-42d0-aa6c-d197fad3388e",
+   "metadata": {},
+   "source": [
+    "## 1.1 Context to the research projection:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7026b630-8f55-4c67-a8ba-3f2fe059a615",
+   "metadata": {},
+   "source": [
+    "In September 2015, low flows in the Lower Athabasca River (LAR) severely restricted navigation for the Mikisew Cree First Nation. At a discharge of 368 m3/s, navigation was described as “essentially at zero”, meaning that community members could not leave the harbour to fish, hunt, gather nor receive supplies by boat (Mikisew Cree First Nation, 2016). A year later, October 2016, another low flow event was associated with a Mikisew member having to pull a small boat across a sandbar in a distributary channel (Mikisew Cree First Nation, 2016). These events show that low flow conditions in the LAR directly affect river navigation for communities who depend on it. \n",
+    "\n",
+    "Such low flow events may become more prevalent due to climate change. Rising temperatures alongside changing precipitation patterns can alter snow accumulation, snowmelt timing, evapotranspiration and seasonal discharge patterns. In cold region basins such as the LAR, these processes may influence the hydrology and the length of the open water season during which the river is navigable. The LAR forms a relevant case study for investigating how climate driven hydrological change may affect low flow conditions and navigability. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c5744c0e-3e3f-43bc-af90-3ac87303c2b0",
+   "metadata": {},
+   "source": [
+    "## 1.2 Problem Analysis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "12ad988e-fc3b-4118-88af-f740dd1f3c33",
+   "metadata": {},
+   "source": [
+    "The LAR feeds into the McKenzie River and is the largest undammed river in Canada, covering a basin of 160.000 km2 (Athabasca University, n.d.). The basin is home to several indigenous communities such as the Mikisew Cree First Nation and the Athabasca Chipewyan First Nation (Kashyap, 2022). These communities utilise a hybrid transportation system, relying on ice roads in winter and marine navigation and aviation outside of winter for the transportation of resources (Adam, et al., 2024; ADCS, 2026) with marine navigation being a cheaper alternative. Waterways are also used for hunting, fishing (Candler, et al., 2015)  and evacuation routes during fires (Adam, et al., 2024) . Navigational routes for these communities are therefore of great importance (Canada Transport, 2020) and have been referred to as the ‘life blood’ for First Nations (Mikisew Cree First Nation, 2016). Low flow extremes in the Lower Athabasca River are expected to increase in frequency and severity over time (Mikisew Cree First Nation, 2016; Kashyap, 2022). If such critical water levels were to be reached more frequently, threatening navigational use of the river, it would be problematic for such indigenous communities who rely on it (Mikisew Cree First Nation, 2016). "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "241151ce-8938-4d9d-8152-692b389f64f5",
+   "metadata": {},
+   "source": [
+    "## 1.3 Research Objective"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9e16b61b-08e3-4d44-84e6-b90d0fa5b2ae",
+   "metadata": {},
+   "source": [
+    "The goal of this Bachelor thesis is to quantify the impacts of climate change on the hydrology of the Lower Athabasca River and its secondary impacts. This leads to the following research question:  \n",
+    "\n",
+    "*“How will climate change impact the river discharge of the Lower Athabasca River and what implications does this have for navigation?”*\n",
+    "\n",
+    "To answer this research question, the following sub-questions are to be considered:\n",
+    "- What is the critical low flow discharge for which navigation in the LAR is constricted?\n",
+    "- How often has this critical discharge been undershot in the past, before 2025?\n",
+    "- How many days from 2025 to 2100 is this critical discharge expected to be undershot, under various climate scenarios?\n",
+    "- During what time of year is the river navigable due to the absence of ice (open-water)?\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fbcf02de-fdd3-4398-acc2-dd2a2bc91f53",
+   "metadata": {},
+   "source": [
+    "## 1.4 Approach"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ee7794e5-cd34-40ac-9afd-c50f0ed69a4d",
+   "metadata": {},
+   "source": [
+    "As a starting point, a literature study is performed to gain understanding of the hydrological and navigational context of the LAR, as well as identifying further challenges needing to be tackled in answering the research question. This literature study focuses primarily on answering the sub-questions regarding the determination of a critical discharge minimum for navigation and the identification of the open water navigation season. \n",
+    "\n",
+    "The hydrological analysis is carried out using the eWaterCycle platform. eWaterCycle is a hydrological modelling platform allowing users to run hydrological models, such as HBV, in a standardised and reproducible manner using Jupyter notebooks (eWaterCycle, n.d.). This makes it easy to switch between, to calibrate and to use various models. The platform simplifies accessing large databases such as ERA5 and CMIP6 which will be used for this research. \n",
+    "\n",
+    "The HBV model is used to model discharge data in the LAR. It is chosen for the model to take ERA5 climate data and calibration parameters as input variables. The model is calibrated for the period 1999-2019 using observed discharge data at Fort McMurray, provided by the government of Canada. A random sampler approach is used in generating various parameter sets, where model performance is evaluated using the logarithmic Nash-Sutcliffe Efficiency (LNSE) to find the optimal parameter set. After calibration and validation, the model will be forced with CMIP6 forcings, containing simulated future climate data, alongside optimal parameters to model future discharge under various climate scenarios. See Figure 1 for a visualisation of how the model works using eWaterCycle. The output of this model is used to analyse the frequency of future critical low flow conditions with the aim of answering the research question. \n",
+    "\n",
+    "<figure>\n",
+    "  <img src=\"Figures/Workflow_diagram.jpg\">\n",
+    "  <figcaption><b>Figure 1:</b> Figure 1: HBV Inputs and outputs using eWaterCycle (AI Generated using ChatGPT).</figcaption>\n",
+    "</figure>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d93ead2-36f9-46bc-97fb-7f76be909ee1",
+   "metadata": {},
+   "source": [
+    "## 1.5 Reading Guide"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e27de1cc-09ee-4f4a-ab79-4dc3566d7e03",
+   "metadata": {},
+   "source": [
+    "In Chapter 2, a literature study will be conducted examining the region and identifying challenges that may arise for computational hydrology. This is followed by the determination of a critical discharge for navigation. In Chapter 3, the start and end period of the open water season will be determined. In Chapter 4, the model will be selected and justified, followed by calibration and validation justification and evaluation. In Chapter 5, climate scenarios are given and the model performance is evaluated under CMIP6 forcing inputs. The model will be used to model discharge in the future under climate scenarios in the results section in Chapter 6. This is followed by a discussion in Chapter 7 and a conclusion in Chapter 8. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7f3b1c2f-0367-4489-bc13-55d97b726f7d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/2_LiteratureStudy.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/2_LiteratureStudy.ipynb
new file mode 100644
index 00000000..261f61db
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/2_LiteratureStudy.ipynb
@@ -0,0 +1,112 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9d734e3f-cde3-460d-9ab0-dd11484b6fe4",
+   "metadata": {},
+   "source": [
+    "# 2. Literature Study"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9f6b5935-1dbd-494c-af83-75d1e6ebec37",
+   "metadata": {},
+   "source": [
+    "## 2.1 Background "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c091e444-345d-4c2e-95b6-133bb8908199",
+   "metadata": {},
+   "source": [
+    "The Lower Athabasca River spans 200km and is located in northern Alberta, Canada. It forms the downstream part of the 1200 km Athabasca River (see Figure 2) originating from Jasper National Park in the Rockies and meets at Fort McMurray (Athabasca Watershed Council, 2026). The river feeds Lake Athabasca and ends up in the McKenzie River further downstream. The river basin is largely influenced by cold region hydrological processes, namely, snow accumulation, snowmelt and to a lesser extent, glacial melt (Kashyap, 2022). In the river basin feeding Fort McMurray, the mean precipitation contribution between 1991-2020 consisted 78% of rainfall and 22% snowfall (Government of Canada, n.d.). This is a decrease in snowfall contribution from 25% between 1981-2010 and 1971-2000, and 28% between 1961-1990 (Government of Canada, n.d.). See Appendix A for a snow cover depletion curve over time. Glacial melt contributes to 3,9% of annual discharge at Hinton, upstream of the Athabasca River and is projected to increase to 5,7% over 2071-2100 under RCP 8.5 (Chernos et al., 2020). As Fort McMurray lies much farther downstream and covers a much larger river basin of 132.000 km2, the relative contribution of glacial melt is expected to be much lower. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0dec4b03-20e3-4a22-90a9-4f1569e38179",
+   "metadata": {},
+   "source": [
+    "<figure>\n",
+    "  <img src=\"Figures/Map_LARbasin.jpg\">\n",
+    "  <figcaption><b>Figure 2:</b> Map of Athabasca River Basin (Aryal, et al., 2023).</figcaption>\n",
+    "</figure>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e8e60463-0966-4913-af23-73e282d8a6e1",
+   "metadata": {},
+   "source": [
+    "Hydrological processes occurring in the LAR are strongly seasonal. Ice cover typically forms along the LAR in early November and remains until late April or early May, when it breaks up due to warming temperatures and snowmelt runoff (Peters et al., 2023). During break up, ice jams can occur which is when a large chunk of ice acts as a temporary dam often leading to rapid, unpredictable streams (Nottawasaga Valley Conservation Authority, 2026). These are most likely to occur farther upstream in narrow mountainous streams. In April 2020, a large ice jam caused severe flooding around Fort McMurray affecting 13.000 people (Canadian Red Cross, n.d.). Although freeze up and break up is not the main focus of this study, they are useful in defining the open water navigation season for which low flow days are analysed (See chapter 3). Ice jams are usually unpredictable and may influence the accuracy of the model used in this study.\n",
+    "\n",
+    "Boreal and Taiga regions make up a large part of the Athabasca River Basin which may contain potholes (Ecosystems Classifications Group, 2008).  According to D. Eythorsson, these potholes can store water locally, creating non-contributing areas, limiting drainage from snowmelt or precipitation to the receiving rivers (personal communication, 2026). When the potholes are filled, all overflown water will drain into the river. This may introduce conceptual model challenges or errors when not accounted for (personal communication, 2026; Faramarzi et al., 2015). \n",
+    "\n",
+    "Finally, the region is also affected by oil sands industries near Fort McMurray who take up to 4,4% of annual water flow to produce Bitumen (Axelrod, J., 2015). Extraction limits are present during low flow conditions (Alberta Environment and Parks, 2026). Current withdrawals are expected to reduce water depth by under 0,02 m (Peters et al., 2023), having very little influence on navigation on the LAR during low flow (Canada, T., 2020) but rather on water quality (Normand, G., et al., 2018). "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1be3ced0-4600-4263-89a0-2d43e7d19b44",
+   "metadata": {},
+   "source": [
+    "## 2.2 Determination of critical threshold"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "163811ce-5cc8-4223-94d0-dfe18a99ca84",
+   "metadata": {},
+   "source": [
+    "To analyse low flow navigation constraints, a critical discharge threshold must be defined. Critical depth depends on vessel type, loading condition and local channel bathymetry. The standard of navigation used by indigenous communities is considered a fully loaded vessel (loaded after a hunt or with resources) with a trapping cabin and an outboard motor (Candler et al., 2010). The safe navigational depth for this type of boat is approximated to be 1,2 meters (Candler et al., 2010; Kashyap et al., 2022). \n",
+    "\n",
+    "In order to utilise this depth threshold for modelling, a critical discharge must be determined. For this, the Aboriginal Navigational Index (ANI) is used. The ANI links discharge at Fort McMurray to navigation conditions along the Lower Athabasca River by evaluating water depths at known critical navigation sites (Kashyap et al., 2022). Transport Canada investigated the 200 km reach between Fort McMurray and Embarras Portage, selecting 11 high risk sites for detailed field survey (2020). These were selected from a larger set of 35 concern sites identified through indigenous consultation and channel characteristics (Transport Canada, 2020). As a result, it was found that at a critical discharge of 500 m3/s at Fort McMurray, 8 of 11 sites experienced water depths below 1,2 m (See Figure 3 for a location of the 8 critical sites). Besides these critical sites, low flow may be experienced in distributary channels too. This threshold is also supported by the Mikisew Cree First Nation who stated navigation is significantly hindered between 450-500 m3/s at Fort McMurray (2016).\n",
+    "\n",
+    "The critical threshold for this study is therefore taken to be:   \n",
+    "$Q_{critical}=500  [m^3/s]$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "652949b8-f321-42e8-b9b2-1d0644e095df",
+   "metadata": {},
+   "source": [
+    "<figure>\n",
+    "  <img src=\"Figures/Map_LARbasin_criticalloc.jpg\">\n",
+    "  <figcaption><b>Figure 3:</b>Map of LAR showing critical locations for navigation (Adapted from DSI, 2019).</figcaption>\n",
+    "</figure>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fbb61cce-15bb-4f90-9613-036c7a6aacb8",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/3_Determination_of_navigable_season.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/3_Determination_of_navigable_season.ipynb
new file mode 100644
index 00000000..ad87981c
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/3_Determination_of_navigable_season.ipynb
@@ -0,0 +1,550 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "2646499c-e8dd-4c5e-9d87-5fda946a7196",
+   "metadata": {},
+   "source": [
+    "# 3. Determination of navigable season"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "428d3ada-c6ee-4d3c-9f8f-40622858308b",
+   "metadata": {},
+   "source": [
+    "The Lower Athabasca River is located in a cold region where below freezing temperatures cause the river to freeze during winter. Since the aim of this research is to analyse low flow navigation constraints, a consistent open water time window must be defined in which navigation restrictions are limited to discharge rather than ice formation. \n",
+    "\n",
+    "The timing of river ice break up and freeze up varies from year to year as the climate system is dynamic. Therefore, a simplified algorithm is developed to identify the approximate break up and freeze up dates for each year between 1970 and 2024. The algorithm is based on observed discharge data and temperature data from ERA5. The latest identified break up is used as the starting boundary of the fixed open water season, and the earliest identified freeze up date as the ending boundary. According to Peters et al., ice break up typically occurs in late April to early May, while freeze up may occur in late October to November (2023). These ranges are used as a reference to assess whether the algorithm produces realistic results.\n",
+    "\n",
+    "Based on evaluations made in 3.1, start of navigable season and 3.2, end of navigable season, the study defines the navigational open water season as 18 May to 17 October. \n",
+    "\n",
+    "The same algorithms are applied to modelled future discharge and temperature data under climate scenarios to evaluate how the navigational period changes over time (See 6.2). \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4ef338a3-1225-4966-898b-945250d61fe9",
+   "metadata": {},
+   "source": [
+    "## 3.1 Start of navigable season"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eacd94d4-51a0-4b6f-b2d0-3e4277e293df",
+   "metadata": {},
+   "source": [
+    "The start of the navigable season is approximated using observed discharge at Fort McMurray, discharge station 07DA001. As temperatures begin to rise in spring, accumulated snow melts rapidly causing a significant increase in discharge. This period is called freshet and is often associated with increased flood risk. Once Qcritical is initially reached, low flows are unlikely to occur shortly after due to a continuous rise in discharge during freshet. Therefore, the first date each year on which discharge exceeds Qcritical is used as an indicator for the beginning of the open water analysis period. \n",
+    "\n",
+    "This method does not necessarily identify the exact date when all river ice has disappeared. Instead, it is used to prevent low flow days before the spring freshet from being included in the navigation analysis. This is important because discharge prior to break up may be low  due to low winter baseflow, while navigation is limited by ice. \n",
+    "\n",
+    "Figure 4 shows the first date each year when observed discharge exceeds the critical threshold. Most years fall between late April and early May, in line with expectations. The year 2009 forms an anomaly with 18 May identified as the start of freshet. Although this may be a late date, it is still considered suitable as the starting boundary. A later start date may help account for delayed modelled freshet peaks which the hydrological model is not specifically calibrated for (see chapter 4), preventing prior low baseflow days from being counted incorrectly. It is also notable that there is no visible indication of the start date changing over the years. \n",
+    "\n",
+    "Figure 5 gives one example year, illustrating the initial freshet period and how Qcritical is approached to identify the starting date.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "9ab44ca1-e279-4bef-a132-7e12a112e342",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python imports\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "be9a1be8-5c71-4d21-9004-eac0135eb058",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "ad794f20-34f2-450b-9879-7baa8c35739f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining time period & q_critical\n",
+    "\n",
+    "experiment_start_date = \"1970-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2024-12-31T00:00:00Z\"\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "hysets_id = \"hysets_07DA001\"\n",
+    "basin_size = 132572"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "id": "ccfaa64b-5613-4155-95d6-9d3c92826d9d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Loading in data\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5\" / \"ERA5-1970-2024\"\n",
+    "forcing_path_ERA5.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "# Load CSV discharge 07DA001\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "id": "b95a5594-f90f-441e-ae13-bd0ca220384e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "q_obs = q_obs[\n",
+    "    (q_obs[\"Date\"] >= start_date) &\n",
+    "    (q_obs[\"Date\"] <= end_date)].copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "id": "ebbb5515-41d0-4fef-a5b4-626f11a7e3c2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pd for identified critical dates\n",
+    "\n",
+    "freshet_start_date = []\n",
+    "\n",
+    "for year, group in q_obs.groupby(q_obs[\"Date\"].dt.year):\n",
+    "\n",
+    "    # Set start date to March 1\n",
+    "    start_date_algorithm = pd.to_datetime(f\"{year}-03-01\")\n",
+    "    season_data = group[group[\"Date\"] >= start_date_algorithm].copy()\n",
+    "    \n",
+    "    # Identify first day where q > q_critical\n",
+    "    \n",
+    "    above_critical = season_data[\n",
+    "        season_data[\"discharge_m3s\"] > q_critical]\n",
+    "    \n",
+    "    if len(above_critical) > 0:\n",
+    "        first_day = above_critical.iloc[0]\n",
+    "        \n",
+    "        freshet_start_date.append({\n",
+    "            \"year\": year,\n",
+    "            \"first_above_critical_date\": first_day[\"Date\"],\n",
+    "            \"discharge_m3s\": first_day[\"discharge_m3s\"]})\n",
+    "\n",
+    "freshet_start_date = pd.DataFrame(freshet_start_date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "id": "e5d5de0d-daa0-4b1f-9692-591c1c01a7db",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Convert date to day of year\n",
+    "freshet_start_date[\"day_of_year\"] = (freshet_start_date[\"first_above_critical_date\"].dt.dayofyear)\n",
+    "\n",
+    "# Make plot \n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.scatter(freshet_start_date[\"day_of_year\"], freshet_start_date[\"year\"], marker=\"o\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Year\")\n",
+    "plt.title(\"First date discharge exceeds critical threshold between 1970-2024\")\n",
+    "plt.grid(True)\n",
+    "\n",
+    "# Convert day of year to day in months (on the axis)\n",
+    "plt.xticks(\n",
+    "    [60, 65, 70, 75, 80, 85, 90,\n",
+    "     95, 100, 105, 110, 115, 120,\n",
+    "     125, 130, 135, 140, 145, 150],\n",
+    "    [\"Mar 1\", \"Mar 6\", \"Mar 11\", \"Mar 16\", \"Mar 21\", \"Mar 26\", \"Mar 31\",\n",
+    "     \"Apr 5\", \"Apr 10\", \"Apr 15\", \"Apr 20\", \"Apr 25\", \"Apr 30\",\n",
+    "     \"May 5\", \"May 10\", \"May 15\", \"May 20\", \"May 25\", \"May 30\"],)\n",
+    "\n",
+    "# Automate x-axis range to fit data\n",
+    "plt.xlim((freshet_start_date[\"day_of_year\"].min()-1), (freshet_start_date[\"day_of_year\"].max()+1))\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4ad17432-2817-4839-9d25-a41c68379019",
+   "metadata": {},
+   "source": [
+    "**Figure 4:** Scatter plot showing yearly start of open-water season.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "id": "f62bbca0-228f-45ef-aec3-9e182aad231f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_discharge_for_year(q_obs, freshet_start_date, q_critical, selected_year):\n",
+    "\n",
+    "    # Define plotting period to selected year\n",
+    "    start_date = f\"{selected_year}-01-01\"\n",
+    "    end_date = f\"{selected_year}-12-31\"\n",
+    "\n",
+    "    # Adjust q_obs and freshet_start_date to fit plotting period\n",
+    "    q_obs_year = q_obs[\n",
+    "        (q_obs[\"Date\"] >= start_date) &\n",
+    "        (q_obs[\"Date\"] <= end_date)]\n",
+    "\n",
+    "    freshet_year = freshet_start_date[\n",
+    "        (freshet_start_date[\"first_above_critical_date\"] >= start_date) &\n",
+    "        (freshet_start_date[\"first_above_critical_date\"] <= end_date)]\n",
+    "\n",
+    "    # Start figure\n",
+    "    plt.figure(figsize=(12, 5))\n",
+    "\n",
+    "    # Plot q_obs\n",
+    "    plt.plot(q_obs_year[\"Date\"], q_obs_year[\"discharge_m3s\"], label=\"Observed discharge\")\n",
+    "\n",
+    "    # Plot q_critical\n",
+    "    plt.axhline(y=q_critical, linestyle=\":\", label=f\"Critical discharge ({q_critical} m³/s)\", color=\"black\")\n",
+    "\n",
+    "    # Plot when q_critical is reached\n",
+    "    for date in freshet_year[\"first_above_critical_date\"].dropna():\n",
+    "        plt.axvline(x=date, linestyle=':', color='orange', label='Start navigable season')\n",
+    "\n",
+    "    plt.xlabel(\"Date\")\n",
+    "    plt.ylabel(\"Discharge (m³/s)\")\n",
+    "    plt.title(f\"Observed daily discharge at 07DA001 in {selected_year}\")\n",
+    "\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "ce973ec4-5c14-4fb7-bf01-05f60665a301",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "selected_year = 2014\n",
+    "\n",
+    "plot_discharge_for_year(q_obs, freshet_start_date, q_critical, selected_year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "10cd5f4f-0879-4a6a-aa53-3965afb2da8c",
+   "metadata": {},
+   "source": [
+    "**Figure 5:** Graph showing first time Q reaches Q critical in 2014. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0547a860-596c-4b2e-9a97-35a02415c858",
+   "metadata": {},
+   "source": [
+    "## 3.1 End of navigable season"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "797c8dfe-eeb3-4af7-aa31-e65e1c9637a5",
+   "metadata": {},
+   "source": [
+    "The end of the open water season is approximated using accumulated freezing degree days (AFDD), calculated from ERA5 2 m above surface temperature. AFDD is calculated by accumulating daily temperatures below 0 ℃. If the daily temperature is below 0 ℃, the absolute temperature is added to the cumulative AFDD. If the temperature is above 0 ℃, no value is added.\n",
+    "\n",
+    "In the LAR there is a correlation between AFDD and ice formation. Andrishak reports that initial ice formation occurs around 10-12 ℃ AFDD, while complete ice cover forms around 50-52 ℃ AFDD (2008). Initial ice is likely to form near shallow river banks which may not immediately limit navigation. However, navigation may become constricted before a complete ice cover has formed. Therefore, this study assumes navigation becomes limited at a threshold of:\n",
+    "\n",
+    "$AFDD > 30 ℃$\n",
+    "\n",
+    "The AFDD is calculated from 1 October onwards to eliminate freeze degree day anomalies in prior months. A more detailed ice freeze up study could use net freezing degree days rather than cumulative freeze degree days, as this would reduce the influence of warmer periods in between cold spells. However, this lies outside the scope of this research. To remain consistent with Andrishak’s finding, AFDD is used. \n",
+    "\n",
+    "Figure 6 shows the estimated freeze up date for each year. Most identified dates occur between mid October to early November, in line with expectations. One clear outlier is 2009 with a freeze up date of 12 October. This outlier will not be used as the end of the navigation period because it falls 5 days before the next datapoint (1992, 17 October), which for all the other years is a relevant evaluation period for navigation. \n",
+    "\n",
+    "Figure 7 shows the temperature time series for an example year, 2014, illustrating how the freeze up date is determined using AFDD."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "id": "42b38876-9ec2-481a-8d59-08faec50f358",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate ERA5 data\n",
+    "\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "#     directory=forcing_path_ERA5\n",
+    "# )\n",
+    "\n",
+    "# Load ERA5 data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "56e77e15-32bf-4c36-bb56-4b15d00b90e8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Exract tas file from Era5\n",
+    "tas_file = Path(ERA5_forcing.directory) / ERA5_forcing.filenames[\"tas\"]\n",
+    "\n",
+    "# Extract tas data from tas file\n",
+    "temp_data = xr.open_dataset(tas_file)[\"tas\"]\n",
+    "\n",
+    "# Convert to panda\n",
+    "temp_data = temp_data.to_series()\n",
+    "temp_data.index = pd.to_datetime(temp_data.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Convert Kelvin to Celsius:\n",
+    "temp_data = temp_data - 273.15\n",
+    "\n",
+    "# Create dataframe with Date, Temp & year as columns\n",
+    "temp_data = pd.DataFrame({\n",
+    "    \"Date\": temp_data.index,\n",
+    "    \"Temp\": temp_data.values,\n",
+    "    \"year\": temp_data.index.year})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "id": "d6eb939a-f972-4019-84cd-6d58c25f135d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "AFDD_critical = 30\n",
+    "AFDD_critical_dates = []\n",
+    "\n",
+    "start_year = start_date.year\n",
+    "end_year = end_date.year\n",
+    "\n",
+    "for year in range(start_year, end_year + 1):\n",
+    "\n",
+    "    # Set start date to 1 October\n",
+    "    year_data = temp_data[\n",
+    "        (temp_data[\"year\"] == year) &\n",
+    "        (temp_data[\"Date\"] >= pd.to_datetime(f\"{year}-10-01\"))]\n",
+    "\n",
+    "    AFDD = 0\n",
+    "    \n",
+    "    # Isolate datasets of date & temperature data to each year \n",
+    "    for i in range(len(year_data)):\n",
+    "        temp = year_data.iloc[i][\"Temp\"]\n",
+    "        date = year_data.iloc[i][\"Date\"]\n",
+    "\n",
+    "        # Cumulative AFDD\n",
+    "        if temp < 0:\n",
+    "            AFDD += -temp\n",
+    "\n",
+    "        # Append when AFDD is critical\n",
+    "        if AFDD >= AFDD_critical:\n",
+    "            AFDD_critical_dates.append({\n",
+    "                \"year\": year,\n",
+    "                \"AFDD_critical_date\": date,\n",
+    "                \"AFDD\": AFDD,\n",
+    "                \"Temp\": temp\n",
+    "            })\n",
+    "\n",
+    "            break \n",
+    "\n",
+    "AFDD_critical_dates = pd.DataFrame(AFDD_critical_dates)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "id": "716607d9-b158-4020-a72e-800ec08bdb94",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Convert date to day of year\n",
+    "AFDD_critical_dates[\"day_of_year\"] = (AFDD_critical_dates[\"AFDD_critical_date\"].dt.dayofyear)\n",
+    "\n",
+    "# Make plot \n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.scatter(AFDD_critical_dates[\"day_of_year\"], AFDD_critical_dates[\"year\"], marker=\"o\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Year\")\n",
+    "plt.title(f\"Date of river freeze-up (AFDD >= {AFDD_critical}) between 1970-2024\")\n",
+    "plt.grid(True)\n",
+    "\n",
+    "# Convert day of year to day in months (on the axis)\n",
+    "plt.xticks(\n",
+    "    [274, 279, 284, 289, 294, 299, 304,\n",
+    "     309, 314, 319, 324, 329, 334, 339,\n",
+    "     344, 349, 354, 359, 364, 366],\n",
+    "    [\"Oct 1\", \"Oct 6\", \"Oct 11\", \"Oct 16\", \"Oct 21\", \"Oct 26\", \"Oct 31\",\n",
+    "     \"Nov 5\", \"Nov 10\", \"Nov 15\", \"Nov 20\", \"Nov 25\", \"Nov 30\", \"Dec 5\",\n",
+    "     \"Dec 10\", \"Dec 15\", \"Dec 20\", \"Dec 25\", \"Dec 30\", \"Dec 31\"],)\n",
+    "\n",
+    "# Automate x-axis range to fit data\n",
+    "plt.xlim((AFDD_critical_dates[\"day_of_year\"].min()-1), (AFDD_critical_dates[\"day_of_year\"].max()+1))\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4a8cc638-8cf4-4515-a67c-56024a554ce9",
+   "metadata": {},
+   "source": [
+    "**Figure 6:** Scatter plot showing yearly end of open-water season."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "id": "4018b628-04ca-4fc5-b21b-74107c44ec11",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot temp for 1 year for fun:\n",
+    "selected_year = 2014\n",
+    "year_data = temp_data[temp_data[\"year\"] == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.title(f\"Temperature time series showing date of river freeze-up (AFDD >= {AFDD_critical}) for 2014\")\n",
+    "plt.scatter(year_data[\"Date\"], year_data[\"Temp\"], marker=\"o\")\n",
+    "plt.axhline(y=0, linestyle=\":\", color=\"black\", label=\"0°C\")\n",
+    "\n",
+    "# Extract & plot critical AFDD date for selected year\n",
+    "AFDD_critical_date = AFDD_critical_dates.loc[AFDD_critical_dates[\"year\"] == selected_year, \"AFDD_critical_date\"].iloc[0]\n",
+    "plt.axvline(x=AFDD_critical_date, linestyle=\":\", color=\"orange\", label=\"River freeze-up\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Temperature (°C)\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "78040047-ce71-413d-8c6b-6ee47c6b0dcd",
+   "metadata": {},
+   "source": [
+    "**Figure 7:** Graph showing temperature time series showing river freeze-up date for 2014."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "42749e66-7066-453f-bce2-5c0efa310720",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/4_Calibration_of_the_HBV_model.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/4_Calibration_of_the_HBV_model.ipynb
new file mode 100644
index 00000000..55fcf88e
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/4_Calibration_of_the_HBV_model.ipynb
@@ -0,0 +1,1124 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "24321024-ee24-48df-a579-3fbdd3270fa2",
+   "metadata": {},
+   "source": [
+    "# 4. Calibration of the HBV model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0adfbb0f-12b9-4594-a199-79dc6c9d6a47",
+   "metadata": {},
+   "source": [
+    "## 4.1 Model selection"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0a56fdb2-66c3-4bf7-bab1-04b032b8e884",
+   "metadata": {},
+   "source": [
+    "The HBV model will be selected to simulate discharge in the Lower Athabasca River. HBV is a rainfall runoff model representing hydrological processes requiring limited parameter input and storage components. This makes the model computationally efficient which is useful for calibration. See Table 4.1 for a list of the input parameters. \n",
+    "\n",
+    "HBV has the ability to represent snow accumulation and snowmelt with its snowmelt parameter. This is important for the LAR, where snow processes heavily influence discharge. The basin contains both high elevation mountains in the Rockies and lower plains downstream resulting in a spatial variability, which HBV can account for.\n",
+    "\n",
+    "This model also has limitations. The HBV model does not explicitly include a glacier melt parameter. A HBV adaptation such as HBV-EC could be more suitable, which is not provided by eWaterCycle. However, this contribution is small at the LAR and therefore expected to cause minor conceptual errors. In addition, this model does not explicitly represent non-contributing areas such as potholes that occur in the boreal basin. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74d0f26f-b4a2-47cb-b287-8cffff88f3e6",
+   "metadata": {},
+   "source": [
+    "*Table 4.1: HBV model parameters.*\n",
+    "\n",
+    "| **Parameter**            | **Description**                                          |\n",
+    "|--------------------------|----------------------------------------------------------|\n",
+    "| $I_{\\text{max}}$         | Maximum interception storage [mm]                        |\n",
+    "| $C_{\\text{e}}$           | Evaporation correction factor [-]                        |\n",
+    "| $S_{\\text{u,max}}$       | Maximum soil moisture storage [mm]                       |\n",
+    "| $\\beta$                  | Soil runoff parameter [-]                                |\n",
+    "| $P_{\\text{max}}$         | Maximum percolation rate [mm/day]                        |\n",
+    "| $T_{\\text{lag}}$         | Time lag [days]                                          |\n",
+    "| $K_{\\text{f}}$           | Fast reservoir recession coeofficient     [1/day]        |\n",
+    "| $K_{\\text{s}}$           | Slow reservoir recession coeofficient     [1/day]        |\n",
+    "| $F_{\\text{M}}$           | Snowmelt factor                           [-]            |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "deaa74c9-d454-408a-8e73-0d5b820d530d",
+   "metadata": {},
+   "source": [
+    "A visual representation of the model, parameters and storages can be seen in Figure 8 below:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8c042d07-8482-4ecc-ae60-05fd74803acc",
+   "metadata": {},
+   "source": [
+    "<figure>\n",
+    "  <img src=\"Figures/HBV_Visualisation.jpg\">\n",
+    "  <figcaption><b>Figure 8:</b> Visualisation of the HBV model parameters and storages (Hrachowitz, n.d.).</figcaption>\n",
+    "</figure>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de7472c8-5043-4c38-9928-6e60b19899b7",
+   "metadata": {},
+   "source": [
+    "## 4.2 Calibration methodology"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "010c4b48-b5e4-46cb-85df-47897e465ee6",
+   "metadata": {},
+   "source": [
+    "The HBV model is calibrated using observed daily discharge data from station 07DA001 at Fort McMurray and ERA5 climate data. ERA5 provides 2 m above surface temperature, precipitation, shortwave radiation and calculates potential evaporation. The available discharge data is divided into a calibration and validation period using an 80/20 split, respectively. The calibration period runs from 1999-2019 and the validation period from 2019-2024. For both calibration and validation, the first year will act as a warm up period allowing model storages to fill up.\n",
+    "\n",
+    "The HBV model is run multiple times using various parameter sets. Each parameter set is randomly sampled from parameter ranges manually determined based on previous runs. For every run, the used parameter set is evaluated based on differences between modelled and observed data using statistical analysis,  LNSE (See 4.3). The model will be run 1000 times for calibration. As a result, 1000 different sets of parameters are rated and ranked based on model performance. Instead of selecting one optimal parameter set, the 5 best parameter sets will be returned, creating an ensemble of best sets. The selected ensemble will be applied to the validation period and later to future climate forcing, producing a range and mean estimate of future discharge and low flow days. This ensemble approach gives an estimate of model uncertainty and improves reproducibility of the calibration results, as the influence of errors in one parameter set are reduced by averaging. Furthermore, various parameter sets might have varying strengths in modelling accuracy (e.g. identifying low flow between peaks or identifying transition timing between long high and low flow periods). For a list and interpretation of calibrated parameter values for each set, see Appendix B. \n",
+    "\n",
+    "Winter months from December to April are excluded from evaluating parameter set performance during calibration. This is because low winter baseflow is not the focus of this study and will significantly dilute calibration results. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3362b7e6-87f0-4af3-a037-57fa588abb66",
+   "metadata": {},
+   "source": [
+    "## 4.3 Logarithmic Nash-Sutcliff Efficiency"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a2cf1289-bc97-4ceb-8054-83f596e82e4a",
+   "metadata": {},
+   "source": [
+    "The logarithmic Nash-Sutcliffe Efficiency (LNSE) is a commonly used metric to evaluate how well modelled discharge coincides with observed discharge (Duc & Sawada, 2023). It originates from the NSE method, which compares the variance of the modelled prediction errors to the variance in observed data. NSE is strongly influenced by high flow peaks where errors are squared. By applying a logarithmic transformation to both discharge and modelled data, errors during low flow are relatively weighed more heavily. This makes LNSE a suitable method for this research. \n",
+    "\n",
+    "The logarithmic Nash-Sutcliffe Efficiency is calculated as:\n",
+    "\n",
+    "$log NSE = 1 - \\frac{\\Sigma(logQ_{obs}-logQ_{sim})^2}{\\Sigma(logQ_{obs} - \\overline{logQ_{obs}})^2}$\n",
+    "\n",
+    "Where $Q_{obs}$ is the observed discharge at one time step, $Q_{sim}$ the simulated discharge at one time step and $\\overline{logQ_{sim}}$the mean of the log observed discharge. The output result may range from -∞ to 1, where 1 indicates a perfect model fit (HEC-HMS, n.d.). "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c66535de-7a8e-4bdb-b88f-62063e8364ca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "LNSE will be calculated using the following functions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f836be72-70d8-4d18-ac1a-1c209f690e42",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate log NSE\n",
+    "\n",
+    "def LNSE(sim, obs):\n",
+    "    \n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8fea8ebc-ab8f-4251-b4f9-243c4a9d6848",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call log NSE for relevant timeperiod\n",
+    "\n",
+    "def lnse_ensemble(ensemble_data, lnse_start, lnse_end):\n",
+    "\n",
+    "    # Select evaluation period - skip first year for storages to fill\n",
+    "    combined_data = ensemble_data[\n",
+    "        (ensemble_data.index >= lnse_start) &\n",
+    "        (ensemble_data.index <= lnse_end)].dropna()\n",
+    "\n",
+    "    # Exclude winter months\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])]\n",
+    "\n",
+    "    lnse_results = []\n",
+    "\n",
+    "    # Calculate LNSE for all sets\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        lnse_value = LNSE(\n",
+    "            combined_data[f\"Set {i+1}\"],\n",
+    "            combined_data[\"Observed discharge\"])\n",
+    "\n",
+    "        # Append LNSE\n",
+    "        lnse_results.append({\n",
+    "            \"Set\": f\"Set {i+1}\",\n",
+    "            \"LNSE\": lnse_value})\n",
+    "\n",
+    "    # Calculate LNSE of ensemble mean\n",
+    "    mean_lnse = LNSE(\n",
+    "        combined_data[\"Mean\"],\n",
+    "        combined_data[\"Observed discharge\"])\n",
+    "\n",
+    "    # Append LNSE\n",
+    "    lnse_results.append({\n",
+    "        \"Set\": \"Ensemble mean\",\n",
+    "        \"LNSE\": mean_lnse})\n",
+    "\n",
+    "    lnse_results = pd.DataFrame(lnse_results)\n",
+    "\n",
+    "    return lnse_results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d49d874-51df-4c38-893a-418a8b3bbcc8",
+   "metadata": {},
+   "source": [
+    "## 4.4 Calibration results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fdc1955a-65b0-422e-bf2a-946011a35c96",
+   "metadata": {},
+   "source": [
+    "As mentioned before, the HBV model was calibrated from 1999-2019 excluding the first year as a warm up period and 5 winter months. Figure 9 shows the observed and modelled data over this period. Overall, the model reproduces the discharge reasonably well. The 5 best parameter sets returned an LNSE ranging from 0,64 to 0,72 with a 0,68 median. The mean discharge from the sets returns an improved LNSE of 0,74, which can be considered a good model fit. Most high flow peaks are not modelled accurately, which is acceptable within the scope of the study. Low flow periods and the transition from high to low discharge periods are generally represented well which is important for identifying critical low flow days. The code used for the calibration can be seen in Appendix C. The code for generating ERA5 & CMIP6 data can be seen in Appendix F & G."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "ea79a0dc-277b-4745-9c61-1d3d28f51804",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "2cdd5f48-19d1-431b-af45-e74f4b15e3ca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "ccb789d1-40a2-4b0f-a257-48a0a98c1416",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500\n",
+    "\n",
+    "# Choosing time period\n",
+    "\n",
+    "validation_start_yr = 1999\n",
+    "validation_end_yr = 2019\n",
+    "\n",
+    "experiment_start_date = f\"{validation_start_yr}-01-01T00:00:00Z\"\n",
+    "experiment_end_date = f\"{validation_end_yr}-12-31T00:00:00Z\"\n",
+    "\n",
+    "validation_start = f\"{validation_start_yr}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{validation_end_yr}-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "ae67ce30-2cdc-4c2e-9320-6883b83ee861",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"forcings\" / \"ERA5\" / f\"ERA5-{validation_start_yr}-{validation_end_yr}\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "824c3746-479f-4bdb-b0c1-4687321aaab6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "ca69d964-30b0-4806-ac9d-93a775f4a62f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs to relevant dates\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= validation_start_date) & (q_obs[\"Date\"] <= validation_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "id": "03f9569b-c0c4-492f-87de-eda5529176e3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "1c20167e-73e0-47dc-8992-27855fa04e97",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"]          # Snowmelt factor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "9a80b64e-bab0-4f67-a77e-7c9242e5d380",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "17c73c6f-c695-492c-bd4a-057dcf337f07",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model setup\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config)\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\")\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "23761caa-ef00-408b-ac41-38d6b21ae299",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Running model\n",
+    "\n",
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing)\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Filter observed data by day\n",
+    "    observed_daily = observed_output\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "    ensemble_data['Observed discharge'] = observed_daily\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "b556e82d-3d20-4182-8cbe-f205ad3fac7f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ensemble_data = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "df33c5f6-e31c-443b-8908-6f3122612135",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Plotting function\n",
+    "\n",
+    "def plot_ensemble(ensemble_data, plot_start, plot_end):\n",
+    "\n",
+    "    plot_start = pd.to_datetime(plot_start)\n",
+    "    plot_end = pd.to_datetime(plot_end)\n",
+    "\n",
+    "    # Filter data to start & end time\n",
+    "    plot_data = ensemble_data[\n",
+    "        (ensemble_data.index >= plot_start) &\n",
+    "        (ensemble_data.index <= plot_end)].dropna()\n",
+    "\n",
+    "    # Define figure\n",
+    "    plt.figure()\n",
+    "    plt.figure(figsize=(15, 6))\n",
+    "\n",
+    "    # Plot sets, observed data, ensemble mean and axhline, respectively\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        plt.plot(plot_data.index, plot_data[f\"Set {i+1}\"], color=\"orange\", alpha=0.3, label=\"Parameter sets\" if i == 0 else None)\n",
+    "\n",
+    "    plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\", linewidth=3)\n",
+    "    plt.plot(plot_data.index, plot_data[\"Mean\"], label=\"Ensemble mean\", linewidth=3)\n",
+    "    plt.axhline(y=q_critical, linestyle=\":\", color=\"black\", label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "    # Extras\n",
+    "    plt.xlabel(\"Date\")\n",
+    "    plt.ylabel(\"Discharge (m³/s)\")\n",
+    "    plt.title(\"Observed vs modelled ensemble discharge at 07DA001\")\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "a50c6d2f-1f78-421f-a919-c5f6aeb6c634",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for full evaluation period\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=evaluation_start,\n",
+    "    plot_end=validation_end_date)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23459947-3c26-4015-ba34-938f08816ccf",
+   "metadata": {},
+   "source": [
+    "**Figure 9:** Modelled vs observed discharge over the calibration period."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "30415751-47cd-4029-b67d-d837d881deb0",
+   "metadata": {},
+   "source": [
+    "## 4.5 Validation results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "92604c10-ecd3-4bba-bcbe-0927605317aa",
+   "metadata": {},
+   "source": [
+    "The 5 best parameter sets were applied to the validation period 2019-2024, excluding the first year as a warm up period. Figure 10 shows the observed and modelled discharge over this period. The parameter sets returned an LNSE ranging from 0,72 to 0,77 with a 0,74 median. The model mean has an improved LNSE of 0,81,  which suggests a very good model performance. Interestingly, this shows an improvement from the calibration period which may suggest the parameter set’s performance is consistent which is important when modelling discharge in the far future. For yearly graphs, see Appendix D. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "d16a1fc0-e8ee-47c6-b872-33b4450aa901",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing new time period\n",
+    "\n",
+    "validation_start_yr = 2019\n",
+    "validation_end_yr = 2024\n",
+    "\n",
+    "experiment_start_date = f\"{validation_start_yr}-01-01T00:00:00Z\"\n",
+    "experiment_end_date = f\"{validation_end_yr}-12-31T00:00:00Z\"\n",
+    "\n",
+    "validation_start = f\"{validation_start_yr}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{validation_end_yr}-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "72c7acad-73ed-4d01-ab13-d5ea81ea3d20",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"forcings\" / \"ERA5\" / f\"ERA5-{validation_start_yr}-{validation_end_yr}\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "3b0059db-7c6c-4628-ac0f-ae814598615d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "5c84c09f-34cf-4b1f-97fc-06042c60c8c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs to relevant dates\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= validation_start_date) & (q_obs[\"Date\"] <= validation_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "d452d567-72fd-4a8f-b012-6a77eb5cd625",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "42531e49-fb29-42a5-8887-1b9dfd4f65aa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ensemble_data = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "360d3df3-6991-4081-93e6-0a1b1d52df87",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for full evaluation period\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=evaluation_start,\n",
+    "    plot_end=validation_end_date)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a9ab0905-25a8-4841-9cac-c3728f346d77",
+   "metadata": {},
+   "source": [
+    "**Figure 10:** Observed vs modelled discharge for the validation period. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8cd1fba-7743-4fe3-9aeb-1071d7c73344",
+   "metadata": {},
+   "source": [
+    "Although low flow periods are reproduced reasonably accurately visually, when comparing low flow days between observed and modelled data, the model varies significantly in accuracy. In years such as 2020 and 2022, the difference is almost zero. In other years such as 2021 and 2024, errors exceed almost 100%. \n",
+    "\n",
+    "An explanation could be that fluctuations close to Qcritical may significantly influence results as can be seen in both 2021 and 2024. Even though observed discharge may be slightly above Qcritical, navigation may still be restricted on 7 critical sites rather than 8. An inflation of modelled low flow days may therefore not be problematic in answering the research question if this is the nature of the errors. Furthermore, errors could occur due to conceptual modelling errors (potholes and glacial melt exclusion). "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "10fe0727-f767-44f1-9ede-4e5fdc51ca3a",
+   "metadata": {},
+   "source": [
+    "*Table 4.2: Observed and modelled low flow days for validation period.*\n",
+    "\n",
+    "| **Year**  | **Observed lowflow days** | **Mean modelled lowflow days** |\n",
+    "|-----------|---------------------------|--------------------------------|\n",
+    "| 2020      | 0                         | 0                              |\n",
+    "| 2021      | 30                        | 67                             | \n",
+    "| 2022      | 34                        | 40                             |\n",
+    "| 2023      | 27                        | 22                             | \n",
+    "|2024       | 34                        | 14                             |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "54893b9d-d61b-4db7-9d81-daf69280a38f",
+   "metadata": {},
+   "source": [
+    "The function used to generate the data used to manually create this table can be seen in the cell below:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "3da26d79-985e-45cf-939d-9b001c01ec33",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_counter_ensemble(ensemble_data, start_date, end_date):\n",
+    "    \n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "    \n",
+    "        year = years[i]\n",
+    "    \n",
+    "        # Define start and end month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "    \n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)]\n",
+    "\n",
+    "        # Set zeros to count from\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = []\n",
+    "        modelmean_lowflow_days = 0\n",
+    "\n",
+    "        # Count observed lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "        # Count model mean lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "\n",
+    "            modelmean_q = year_data.iloc[j][\"Mean\"]\n",
+    "\n",
+    "            if modelmean_q < q_critical:\n",
+    "                modelmean_lowflow_days += 1\n",
+    "\n",
+    "        # Count modelled lowflow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "        \n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"observed\": observed_lowflow_days,\n",
+    "            \"modelmean\": modelmean_lowflow_days,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)})\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "15119a14-1470-4b9b-8665-1c257cbfdcef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>observed</th>\n",
+       "      <th>modelmean</th>\n",
+       "      <th>set_1</th>\n",
+       "      <th>set_2</th>\n",
+       "      <th>set_3</th>\n",
+       "      <th>set_4</th>\n",
+       "      <th>set_5</th>\n",
+       "      <th>set_avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>30</td>\n",
+       "      <td>67</td>\n",
+       "      <td>71</td>\n",
+       "      <td>68</td>\n",
+       "      <td>70</td>\n",
+       "      <td>68</td>\n",
+       "      <td>53</td>\n",
+       "      <td>66.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2022</td>\n",
+       "      <td>34</td>\n",
+       "      <td>40</td>\n",
+       "      <td>47</td>\n",
+       "      <td>35</td>\n",
+       "      <td>39</td>\n",
+       "      <td>42</td>\n",
+       "      <td>32</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2023</td>\n",
+       "      <td>27</td>\n",
+       "      <td>22</td>\n",
+       "      <td>31</td>\n",
+       "      <td>15</td>\n",
+       "      <td>21</td>\n",
+       "      <td>23</td>\n",
+       "      <td>12</td>\n",
+       "      <td>20.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2024</td>\n",
+       "      <td>34</td>\n",
+       "      <td>14</td>\n",
+       "      <td>38</td>\n",
+       "      <td>13</td>\n",
+       "      <td>14</td>\n",
+       "      <td>11</td>\n",
+       "      <td>1</td>\n",
+       "      <td>15.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   year  observed  modelmean  set_1  set_2  set_3  set_4  set_5  set_avg\n",
+       "0  2020         0          0      9      0      0      0      0      2.0\n",
+       "1  2021        30         67     71     68     70     68     53     66.0\n",
+       "2  2022        34         40     47     35     39     42     32     39.0\n",
+       "3  2023        27         22     31     15     21     23     12     20.0\n",
+       "4  2024        34         14     38     13     14     11      1     15.0"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/5_Climate_scenarios.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/5_Climate_scenarios.ipynb
new file mode 100644
index 00000000..daf4258b
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/5_Climate_scenarios.ipynb
@@ -0,0 +1,586 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4db569bd-a7df-4727-b1df-d1457e0fde6f",
+   "metadata": {},
+   "source": [
+    "# Climate scenarios"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3e323d17-b350-4980-a847-183fb7ea813f",
+   "metadata": {},
+   "source": [
+    "## 5.1 Description"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc493cf2-4fbb-4f8d-8dd9-3c7ee203d7ae",
+   "metadata": {},
+   "source": [
+    "The model will be run for the future under various Shared Socioeconomic Pathway Scenarios (SSP’s). These scenarios represent different possible future outcomes depending on the increase in trapped radiation in the atmosphere. CMIP6 provides 5 scenarios ranging from SSP119 to SSP585. These outer extreme scenarios were not included in this study because recent emission trends and climate policy indicate these scenarios have become less plausible (van Vuuren et al., 2026). For a description of the scenarios used in this study see table 3. \n",
+    "\n",
+    "*Table 5.1: Table 3: description of various CMIP6 SSP’s from 2025-2099 (Government of Canada, 2019).*\n",
+    "\n",
+    "| **Scenarios**  | **Description**                    | **Global $\\Delta$T$^{\\circ}$C** | Period  |\n",
+    "|----------------|------------------------------------|---------------------------------|---------|\n",
+    "| SSP126         | “Middle of the road”: Trends do not shift from historical  patterns                         | 1,8      | 2025 - 2099 |\n",
+    "| SSP245         | “A rocky road”: Low international priority in addressing environmental concerns. High challenges to mitigation and adaptation, resurgent nationalism, slow economic growth.                        | 2,7                             | 2025 - 2099 |\n",
+    "| SSP370         | “A road divided”: Large gap between high and low tech economies, widening global disparities, diverse investment in fossil fuels and renewable energy sources.                        | 3,7                             | 2025 - 2099 |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "52d8382b-f9c3-469b-af18-f975b1879ecf",
+   "metadata": {},
+   "source": [
+    "## 5.2 CMIP6 low flow comparison/validation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5aeeb9a0-62dd-4342-82fd-8d999bfd4a0d",
+   "metadata": {},
+   "source": [
+    "To see if the CMIP6 dataset produces realistic model outcomes, historical low flow data will be compared to observed and ERA5 low flow data over a 25 year period from 1989-2014. It should be noted that CMIP6 is not a reanalysis model like ERA5 but a climate model, meaning it is not expected to reproduce the timing of peaks or wet and dry years precisely. Instead, model outcomes are expected to statistically match observed and ERA5 outcomes over a longer time period. Figure 11 shows the cumulative distribution of low flow days for this 25 year period. \n",
+    "\n",
+    "To match CMIP6 data to ERA5, quantile delta mapping may be applied. This is a correction method to align the distribution of climate model outputs with observational data and thus minimising distributional biases. This has been applied on forcing inputs using the adjust function from python module cmethods and discharge outputs using interp1d from scipy.interpolate. However, both did not yield better results and were therefore not used.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6a350a59-dc70-4e4e-bd1a-722a4352c798",
+   "metadata": {},
+   "source": [
+    "### Startup & Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "de9878c0-b29f-4acd-852a-72854cf5ce87",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "from scipy.interpolate import interp1d\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "62d0bc46-4f32-464e-b482-195ad233332f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "209a285e-e9f4-4bac-bdfe-57d871377fcb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "fbc38b7f-b459-4203-b6e1-272647f05a5a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "start_year = 1995\n",
+    "end_year = 2014\n",
+    "\n",
+    "validation_start = f\"{start_year}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{end_year}-12-31T00:00:00Z\"\n",
+    "\n",
+    "# Choose CMIP Scenario: \n",
+    "Scenario = \"historical\"    # Options: historical, ssp119, ssp126, ssp245, ssp,370, ssp585\n",
+    "\n",
+    "# Attach colours to scenarios to make plotting easier \n",
+    "colours = {\"historical\": \"tab:blue\", \"ssp126\": \"green\", \"ssp245\": \"orange\", \"ssp370\": \"red\"}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "4774cae5-b6ee-42dd-8713-2aeac17ca5ef",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Create pathways for forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"forcings\" / \"ERA5\" / f\"ERA5-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_CMIP = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f\"CMIP6-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_QDM = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f\"CMIP6-QDM-{start_year}-{end_year}\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "2080cade-6139-4002-be29-e53c964634bb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "8658d9ea-cbe0-4c05-8852-1670e97c6fc2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs to relevant dates\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= validation_start_date) & (q_obs[\"Date\"] <= validation_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "9ae1e827-bc39-4981-8468-9c26e979d6d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load data\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_CMIP)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "384d2614-987c-48d2-afb2-e7eb0d69aa18",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"]          # Snowmelt factor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "df6090f2-c132-4c1f-861b-feca6e9b1bca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a3e70436-b290-4a70-a951-be4fb77a3074",
+   "metadata": {},
+   "source": [
+    "### Model setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "5369ec54-1451-4397-b993-273c3f97324a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config)\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\")\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "80009d98-d172-4707-8da7-44ea6c345118",
+   "metadata": {},
+   "source": [
+    "### Running model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "b5319ba8-fc7b-4f54-b7a1-cff954ab2be4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing)\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Filter observed data by day\n",
+    "    observed_daily = observed_output\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "    ensemble_data['Observed discharge'] = observed_daily\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "1f6be5d9-e9ec-4df6-b99c-6e894ef7d26f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ensemble_data_ERA5 = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)\n",
+    "\n",
+    "ensemble_data_CMIP = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=CMIP_forcing)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "742dae79-fbcc-4a58-981f-e62488a10196",
+   "metadata": {},
+   "source": [
+    "### Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "46f5f06e-0e12-419b-9325-1ec965f11356",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_counter_ensemble(ensemble_data, start_date, end_date):\n",
+    "    \n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "    \n",
+    "        year = years[i]\n",
+    "    \n",
+    "        # Define start and end month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "    \n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)]\n",
+    "\n",
+    "        # Set zeros to count from\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = []\n",
+    "        modelmean_lowflow_days = 0\n",
+    "\n",
+    "        # Count observed lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "        # Count model mean lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "            modelmean_q = year_data.iloc[j][\"Mean\"]\n",
+    "\n",
+    "            if modelmean_q < q_critical:\n",
+    "                modelmean_lowflow_days += 1\n",
+    "\n",
+    "        # Count modelled lowflow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "        \n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"observed\": observed_lowflow_days,\n",
+    "            \"modelmean\": modelmean_lowflow_days,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)})\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    days_sum = lowflow_days[[\"observed\", \"modelmean\", \"set_1\", \"set_2\", \"set_3\", \"set_4\", \"set_5\", \"set_avg\"]].sum()\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "679a1ce6-4557-435b-ab38-4e9f97a617d4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lowflow_ERA5 = lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data_ERA5,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date)\n",
+    "\n",
+    "lowflow_CMIP = lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "550c1adc-d371-4158-a156-dfd37273e962",
+   "metadata": {},
+   "source": [
+    "### CDF Calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "e8cdd3fe-4527-43d5-8bb6-ac21bf11d5a2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def rank(lowflow_ERA5, lowflow_CMIP):\n",
+    "\n",
+    "    # Combine tables\n",
+    "    rank_table = pd.DataFrame({\n",
+    "        \"Observed\": np.sort(lowflow_ERA5[\"observed\"]),\n",
+    "        \"ERA5\": np.sort(lowflow_ERA5[\"set_avg\"]),\n",
+    "        \"CMIP6\": np.sort(lowflow_CMIP[\"set_avg\"]),})\n",
+    "    \n",
+    "    rank_table.insert(0, \"rank\", range(1, len(rank_table) + 1))\n",
+    "\n",
+    "    return rank_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "b07f6791-152b-4214-9eda-d3b94bf9435a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rank_table = rank(lowflow_ERA5, lowflow_CMIP)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "962c3168-0a43-48bf-bedc-2276b27ff52f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_cumsum(rank_table):\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    # Plot cumsum for all columns, skipping rank column\n",
+    "    for i in range(1, len(rank_table.columns)):\n",
+    "        plt.plot(rank_table[\"rank\"], rank_table[rank_table.columns[i]].cumsum(), marker=\"o\", label=rank_table.columns[i])\n",
+    "\n",
+    "    # Plotting\n",
+    "    plt.xlabel(\"Ranked years\")\n",
+    "    plt.ylabel(\"Cumulative low flow days\")\n",
+    "    plt.xticks(rank_table[\"rank\"])\n",
+    "    plt.title(\"Cumulative annual low flow days\")\n",
+    "    # plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "500631ec-14fe-4c7e-bc94-ffb65dc0fc17",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_cumsum(rank_table)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6c672c78-15ec-46e9-9d26-da316aa8a241",
+   "metadata": {},
+   "source": [
+    "**Figure 11:** Cumulative distribution of low flow days between 1989-2014 for historical, ERA5 and CMIP6 data. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97b4e9a1-7cc8-4f32-8da9-3eb968697b84",
+   "metadata": {},
+   "source": [
+    "Figure 11 shows a slight deviation in CMIP6 low flow days compared to the observed and ERA5 curves, particularly in the lower and higher ranked years. This suggests that CMIP6 may slightly overestimate extremes i.e. driest years appear drier and wettest years appear wetter. Despite this, CMIP6 follows the general curve trend reasonably well and precisely reproduces the total number of low flow days. The observed data shows 532 total low flow days over this period, ERA5 537 days and CMIP6 532 days. Future CMIP6 forcings are therefore considered suitable for analysing trends in low flow days over long periods although extreme years should be interpreted with caution. "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/6_Results.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/6_Results.ipynb
new file mode 100644
index 00000000..19859153
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/6_Results.ipynb
@@ -0,0 +1,1788 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f95db18c-ac96-43f0-aff9-5a0feeaf38a3",
+   "metadata": {},
+   "source": [
+    "# Results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c3545962-b925-487e-8af0-9db4b13c65ff",
+   "metadata": {},
+   "source": [
+    "## 6.1 Low flow climate analysis "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "75dce6f0-4c6b-4fc3-a43f-a7ecccbe04f9",
+   "metadata": {},
+   "source": [
+    "To evaluate low flow conditions, the annual low flow days were calculated for each climate scenario, shown in table 6.1. The future climate scenarios between 2025-2099 show an increase in annual low flow days compared to the observed historical period between 2000-2025. The observed period shows an average of 27 low flow days per year while future periods range from 31 to 49. \n",
+    "\n",
+    "*Table 6.1: Annual mean low flow days during the open water season under climate scenarios in 25 year periods.*\n",
+    "\n",
+    "| **Scenario**   | **Observed 2000-2025**  | 2025-2050 | 2050-2075  | 2075-2099 |\n",
+    "|----------------|-------------------------|-----------|------------|-----------|\n",
+    "| SSP126         | 27                      | 36        | 38         | 35        | \n",
+    "| SSP245         | 27                      | 40        | 38         | 31        |\n",
+    "| SSP370         | 27                      | 34        | 45         | 49        |\n",
+    "\n",
+    "Figure 12 shows annual low flow days for the observed period and future climate scenarios. Visually, SSP126 remains relatively stable between 2025-2099, while SSP245 shows a slight decreasing trend. SSp370 shows the clearest increase over time. This is consistent with the forcing data trends shown in Appendix E, where SSP370 shows the strongest increase in temperature and potential evaporation. For SSP245, the increase in precipitation may partly explain the decrease in low flow days between 2075-2099. To evaluate whether the fitted trends in annual low flow days were statistically meaningful, a linear regression was applied for each climate scenario. The p value of the fitted slope was used to test whether the trend was statistically significant using a threshold of 0,05. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b22692fd-a67e-41ca-91ef-f6889930d543",
+   "metadata": {},
+   "source": [
+    "### Startup & Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "44aaf7ce-4fc2-438b-a539-d7a69eb45c25",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "from scipy.interpolate import interp1d\n",
+    "from scipy.stats import linregress\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "3507c914-b4db-48ae-96ff-a146f9b0a3a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "62bbbc99-afb6-4de6-b8b7-862bd3735fbc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500\n",
+    "\n",
+    "start_year = 2025\n",
+    "end_year = 2050"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "578e0810-07ab-4bdf-95e6-a06ba4a2d4ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define only future scenarios\n",
+    "scenarios = [\"ssp126\", \"ssp245\", \"ssp370\"]\n",
+    "\n",
+    "# Redefine scenarios to include historical\n",
+    "scenarios_new = [\"historical\", \"ssp126\", \"ssp245\", \"ssp370\"]\n",
+    "\n",
+    "# Attach colours to scenarios to make plotting easier \n",
+    "colours = {\"historical\": \"tab:blue\", \"ssp126\": \"green\", \"ssp245\": \"orange\", \"ssp370\": \"red\"}\n",
+    "\n",
+    "# Define periods\n",
+    "periods = [[2025, 2050, 2075],\n",
+    "           [2050, 2075, 2099]]\n",
+    "\n",
+    "hist_periods = ([1989], [2014]) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "f819dab1-c52f-464c-9ec8-f107fae004b1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways\n",
+    "\n",
+    "def forcing_path_cmip(scenario, start_year, end_year):\n",
+    "    \n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / scenario / f\"CMIP6-{start_year}-{end_year}\"\n",
+    "    \n",
+    "    return forcing_path\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "68e9fd3d-375f-4496-98b3-37b8b903fbac",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Adjust time period\n",
+    "\n",
+    "validation_start = f\"{start_year}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{end_year}-12-31T00:00:00Z\"\n",
+    "\n",
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "194d418f-97c0-42d0-bcf0-047d91766a66",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load in observed discharge data\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "19e65d1f-6ca5-4557-a055-3d6911cbdf31",
+   "metadata": {},
+   "source": [
+    "### Model Setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "e81db75b-c3f4-484e-99aa-e2afa77814e6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define parameter ensemble\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"]          # Snowmelt factor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "e826bb2f-280b-4037-8c6f-a33a3e7a0e41",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define initial storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "54e49856-da5d-4ec3-b90e-cc67e36a9532",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model configuration function\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config)\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\")\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "e41394d6-dab4-4e43-9825-8e49b862dece",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model running create function\n",
+    "\n",
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        # print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing)\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba3a79ac-9d31-4949-bd57-8d055430d55e",
+   "metadata": {},
+   "source": [
+    "### Lowflow setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "60a566a4-edff-4fef-aeb1-189bec494ed2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Lowflow count for the future\n",
+    "\n",
+    "def lowflow_counter_future(ensemble_data, start_date, end_date):\n",
+    "\n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "\n",
+    "        year = years[i]\n",
+    "\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "\n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)]\n",
+    "\n",
+    "        modelled_lowflow_days = []\n",
+    "\n",
+    "        # Count parameter set low-flow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "\n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)})\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "cd520624-9985-4818-8ada-20d57ba485f7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Lowflow counter for the past \n",
+    "\n",
+    "def observed_lowflow_days(start_year=2000, end_year=2025):\n",
+    "\n",
+    "    observed_lowflows = []\n",
+    "\n",
+    "    for year in range(start_year, end_year + 1):\n",
+    "\n",
+    "        season_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        season_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "\n",
+    "        year_data = q_obs[\n",
+    "            (q_obs[\"Date\"] >= season_start) &\n",
+    "            (q_obs[\"Date\"] <= season_end)]\n",
+    "\n",
+    "        lowflow_days = (year_data[\"discharge_m3s\"] < q_critical).sum()\n",
+    "\n",
+    "        observed_lowflows.append({\n",
+    "            \"year\": year,\n",
+    "            \"observed_lowflow_days\": lowflow_days})\n",
+    "\n",
+    "    observed_lowflows = pd.DataFrame(observed_lowflows)\n",
+    "\n",
+    "    observed_average = round(observed_lowflows[\"observed_lowflow_days\"].mean())\n",
+    "    observed_total = observed_lowflows[\"observed_lowflow_days\"].sum()\n",
+    "\n",
+    "    print(\"Observed average low-flow days/year:\", observed_average)\n",
+    "    print(\"Observed total low-flow days:\", observed_total)\n",
+    "\n",
+    "    return observed_lowflows, observed_average"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "faae1fb2-ced9-4af6-85ed-102006e8a865",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Observed average low-flow days/year: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Observed average low-flow days/year: \u001b[1;36m27\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Observed total low-flow days: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">703</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Observed total low-flow days: \u001b[1;36m703\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "observed_lowflows, observed_avg = observed_lowflow_days(start_year=2000, end_year=2025)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9cc4515f-6d36-49ad-8ac7-af15ce518c2d",
+   "metadata": {},
+   "source": [
+    "### Running model "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "31c8727b-fea5-404e-809e-d551bac9ee03",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function for running one projection\n",
+    "\n",
+    "def run_one_projection(scenario, start_year, end_year):\n",
+    "\n",
+    "    print(f\"Running {scenario}, {start_year}-{end_year}\")\n",
+    "\n",
+    "    # Find forcing path for scenario and period\n",
+    "    forcing_path = forcing_path_cmip(\n",
+    "        scenario=scenario,\n",
+    "        start_year=start_year,\n",
+    "        end_year=end_year)\n",
+    "\n",
+    "    # Generate forcing\n",
+    "    CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path)\n",
+    "\n",
+    "    # Run ensemble \n",
+    "    ensemble_data = run_hbv_ensemble(\n",
+    "        par_ensemble=par_ensemble,\n",
+    "        initial_storages=s_0,\n",
+    "        forcing=CMIP_forcing)\n",
+    "\n",
+    "    # Calculate lowflows\n",
+    "    lowflow_table = lowflow_counter_future(\n",
+    "        ensemble_data=ensemble_data,\n",
+    "        start_date=pd.to_datetime(f\"{start_year}-01-01\"),\n",
+    "        end_date=pd.to_datetime(f\"{end_year}-12-31\"))\n",
+    "\n",
+    "    return ensemble_data, lowflow_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "3d4ddfeb-9b75-42d2-9d83-11c1d32f1e31",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp126, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp126, \u001b[1;36m2025\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp126, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp126, \u001b[1;36m2050\u001b[0m-\u001b[1;36m2075\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp126, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp126, \u001b[1;36m2075\u001b[0m-\u001b[1;36m2099\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp245, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp245, \u001b[1;36m2025\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp245, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp245, \u001b[1;36m2050\u001b[0m-\u001b[1;36m2075\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp245, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp245, \u001b[1;36m2075\u001b[0m-\u001b[1;36m2099\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp370, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp370, \u001b[1;36m2025\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp370, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp370, \u001b[1;36m2050\u001b[0m-\u001b[1;36m2075\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp370, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp370, \u001b[1;36m2075\u001b[0m-\u001b[1;36m2099\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Running every projection and storing data\n",
+    "\n",
+    "projection_data = {}\n",
+    "use_periods = []\n",
+    "\n",
+    "for scenario in scenarios:\n",
+    "    \n",
+    "    for i in range(len(periods[0])):\n",
+    "\n",
+    "        # Define start year\n",
+    "        start_year = periods[0][i]\n",
+    "        end_year = periods[1][i]\n",
+    "\n",
+    "        # Define key where data will be saved\n",
+    "        key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "\n",
+    "        # Run HBV\n",
+    "        ensemble_data, lowflow_table = run_one_projection(scenario=scenario, start_year=start_year, end_year=end_year)\n",
+    "\n",
+    "        # Save data in projection_data\n",
+    "        projection_data[key] = {\n",
+    "            \"ensemble\": ensemble_data,\n",
+    "            \"lowflow\": lowflow_table}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd5f691e-55dc-4f09-8d50-5138b1593262",
+   "metadata": {},
+   "source": [
+    "### Display data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "9418de41-94c2-4e17-9373-c5ff0e62d04f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function for making lowflow table \n",
+    "\n",
+    "def create_lowflow_summary_table(projection_data, scenarios, periods):\n",
+    "\n",
+    "    rows = []\n",
+    "\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        # Define table rows \n",
+    "        row = {\"scenario\": scenario}\n",
+    "\n",
+    "        # Put observed data in table\n",
+    "        row[\"Observed 2000-2025\"] = round(observed_avg)\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            # Define period\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            # Take data for relevant scenario and period \n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "            period_name = f\"{start_year}-{end_year}\"\n",
+    "\n",
+    "            # Extract data from projection_key\n",
+    "            lowflow_table = projection_data[key][\"lowflow\"]\n",
+    "\n",
+    "            # Put extracted data in new table\n",
+    "            row[period_name] = round(lowflow_table[\"set_avg\"].mean())\n",
+    "\n",
+    "        rows.append(row)\n",
+    "\n",
+    "    return pd.DataFrame(rows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "9a04d440-878a-46ae-b047-15dab562c917",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>Observed 2000-2025</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <th>2050-2075</th>\n",
+       "      <th>2075-2099</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ssp126</td>\n",
+       "      <td>27</td>\n",
+       "      <td>36</td>\n",
+       "      <td>38</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ssp245</td>\n",
+       "      <td>27</td>\n",
+       "      <td>40</td>\n",
+       "      <td>38</td>\n",
+       "      <td>31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>27</td>\n",
+       "      <td>34</td>\n",
+       "      <td>45</td>\n",
+       "      <td>49</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  scenario  Observed 2000-2025  2025-2050  2050-2075  2075-2099\n",
+       "0   ssp126                  27         36         38         35\n",
+       "1   ssp245                  27         40         38         31\n",
+       "2   ssp370                  27         34         45         49"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Show lowflow table\n",
+    "\n",
+    "summary_table = create_lowflow_summary_table(\n",
+    "    projection_data=projection_data,\n",
+    "    scenarios=scenarios,\n",
+    "    periods=periods)\n",
+    "\n",
+    "summary_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "f0509863-c25f-47d9-bf62-6463e2f07fdf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function for plotting future lowflows \n",
+    "\n",
+    "def plot_annual_lowflow_days(projection_data, scenarios, periods, observed_lowflows):\n",
+    "\n",
+    "    plt.figure(figsize=(9, 5))\n",
+    "\n",
+    "    # Plot observed historical low flow days\n",
+    "    observed_data = observed_lowflows.copy()\n",
+    "\n",
+    "    plt.scatter(observed_data[\"year\"], observed_data[\"observed_lowflow_days\"], color=colours[\"historical\"], alpha=0.5, label=\"historical\")\n",
+    "\n",
+    "    # Historical trendline for 2000-2025\n",
+    "    x = observed_data[\"year\"].values\n",
+    "    y = observed_data[\"observed_lowflow_days\"].values\n",
+    "\n",
+    "    slope, intercept = np.polyfit(x, y, 1)\n",
+    "    trend = slope * x + intercept\n",
+    "\n",
+    "    plt.plot(x, trend, linestyle=\"--\", color=colours[\"historical\"])\n",
+    "\n",
+    "    # Plot future scenarios\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_years = []\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "\n",
+    "            lowflow_table = projection_data[key][\"lowflow\"]\n",
+    "\n",
+    "            years = lowflow_table[\"year\"].values\n",
+    "            lowflows = lowflow_table[\"set_avg\"].values\n",
+    "\n",
+    "            all_years.extend(years)\n",
+    "            all_lowflows.extend(lowflows)\n",
+    "\n",
+    "        scenario_data = pd.DataFrame({\n",
+    "            \"year\": all_years,\n",
+    "            \"set_avg\": all_lowflows})\n",
+    "\n",
+    "        scenario_data = scenario_data.sort_values(\"year\")\n",
+    "\n",
+    "\n",
+    "        # Plot yearly low flow days\n",
+    "        plt.scatter(scenario_data[\"year\"], scenario_data[\"set_avg\"], color=colours[scenario], alpha=0.30, label=scenario)\n",
+    "\n",
+    "        # Plot trendline for 2025-2099\n",
+    "        x = scenario_data[\"year\"].values\n",
+    "        y = scenario_data[\"set_avg\"].values\n",
+    "\n",
+    "        slope, intercept = np.polyfit(x, y, 1)\n",
+    "        trend = slope * x + intercept\n",
+    "\n",
+    "        plt.plot(x, trend, linestyle=\"--\", color=colours[scenario])\n",
+    "\n",
+    "    plt.xlabel(\"Year\")\n",
+    "    plt.ylabel(\"Annual low flow days\")\n",
+    "    plt.title(\"Annual low flow days in LAR basin by climate scenario\")\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "id": "f0476652-7102-4de6-8be3-cdb28408cba8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Show lowflow plot\n",
+    "\n",
+    "plot_annual_lowflow_days(\n",
+    "    projection_data=projection_data,\n",
+    "    scenarios=scenarios,\n",
+    "    periods=periods,\n",
+    "    observed_lowflows=observed_lowflows)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "edfaeec4-5096-4166-8ff5-4927fe8390ec",
+   "metadata": {},
+   "source": [
+    "**Figure 12:** Annual low flow days and trendline between 2000-2099 under climate scenarios."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "7675d9fe-bb67-43f0-83d5-7d76e32c5bf0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate p values to determine trend statistical significance\n",
+    "\n",
+    "def slope_significance(projection_data, observed_lowflows):\n",
+    "    results = []\n",
+    "\n",
+    "    # Historical observed period\n",
+    "    x = observed_lowflows[\"year\"].values\n",
+    "    y = observed_lowflows[\"observed_lowflow_days\"].values\n",
+    "\n",
+    "    reg = linregress(x, y)\n",
+    "\n",
+    "    results.append({\n",
+    "        \"scenario\": \"historical\",\n",
+    "        \"p_value\": reg.pvalue})\n",
+    "\n",
+    "    # Future scenarios\n",
+    "    for scenario in scenarios:\n",
+    "        all_years = []\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "            lowflow_table = projection_data[key][\"lowflow\"]\n",
+    "\n",
+    "            all_years.extend(lowflow_table[\"year\"].values)\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        reg = linregress(all_years, all_lowflows)\n",
+    "\n",
+    "        results.append({\n",
+    "            \"scenario\": scenario,\n",
+    "            \"p_value\": reg.pvalue})\n",
+    "\n",
+    "    return pd.DataFrame(results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "0e08eb92-7a5b-404c-914b-cc26d2984d95",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>p_value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>0.349174</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ssp126</td>\n",
+       "      <td>0.483318</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ssp245</td>\n",
+       "      <td>0.188232</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>0.053621</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     scenario   p_value\n",
+       "0  historical  0.349174\n",
+       "1      ssp126  0.483318\n",
+       "2      ssp245  0.188232\n",
+       "3      ssp370  0.053621"
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Show slope significanc output\n",
+    "\n",
+    "slope_results = slope_significance(projection_data=projection_data, observed_lowflows=observed_lowflows)\n",
+    "\n",
+    "slope_results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "998b6cb6-09d2-418f-9651-4db8a8b88636",
+   "metadata": {},
+   "source": [
+    "The significance of the fitted slopes in Figure 12  show p values of 0,48 for SSP126, 0,19 for SSP245 and 0,054 for SSP370. The trends for SSP126 and SSP245 are not statistically significant as p >> 0,05. The trend is clearest for SSP370, where the p value lies very close to 0,05 although still exceeding the threshold. This suggests there is close to significant evidence for a long term increase in low flow days, although year to year variability remains large. This is expected due to the natural climate variability and multi year climate cycles such as El Niño and La Niña. It is also notable that the evidence for a long term trend becomes stronger as the severity of the climate scenario increases. \n",
+    "\n",
+    "Figure 13 shows the cumulative distribution frequency (CDF) of annual low flow days for the observed period and future climate scenarios. The future scenarios shifted upward compared to the observed period, indicating that years with many low flow days become more frequent. This shift is strongest for SSP370, followed by SSP245 and SSP126, suggesting low flow occurrence increases with scenario severity. The observed period does not exceed 60 low flow days, while more than 20% of future years exceed this value. The magnitude of the highest low flow years also increases strongly in the future scenarios with annual total exceeding 100 days in several cases for each scenario. However, these should be interpreted with caution as the CMIP6 validation indicated that extreme years may be overestimated. \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "19fd5af5-4688-402e-9de6-7e738874287f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create CDF plotting function\n",
+    "\n",
+    "def plot_cdf(projection_data, scenarios, periods):\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    # Observed CDF\n",
+    "    observed_values = np.sort(observed_lowflows[\"observed_lowflow_days\"].values)\n",
+    "    observed_cdf = np.arange(1, len(observed_values) + 1) / len(observed_values)\n",
+    "\n",
+    "    # plt.plot(observed_values,observed_cdf,marker=\"o\",label=\"Observed 2000-2025\")\n",
+    "    plt.plot(observed_cdf, observed_values, marker=\"o\", label=\"Observed 2000-2025\", color=colours[\"historical\"])\n",
+    "\n",
+    "    # Scenario CDFs\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "\n",
+    "            lowflow_table = projection_data[key][\"lowflow\"]\n",
+    "\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        values = np.sort(all_lowflows)\n",
+    "        cdf = np.arange(1, len(values) + 1) / len(values)\n",
+    "\n",
+    "        plt.plot(cdf,values,marker=\"o\",label=scenario, color=colours[scenario])\n",
+    "\n",
+    "    plt.ylabel(\"Annual low flow days\")\n",
+    "    plt.xlabel(\"Cumulative probability\")\n",
+    "    plt.title(\"CDF of annual low flow days\")\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "aab2ce06-24d1-4239-bdc4-fd118dd18632",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Show CDF plot\n",
+    "\n",
+    "plot_cdf(\n",
+    "    projection_data=projection_data,\n",
+    "    scenarios=scenarios,\n",
+    "    periods=periods)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdc449d2-5efc-4a4b-a5dc-cd1bf1a8080b",
+   "metadata": {},
+   "source": [
+    "**Figure 13:** CDF of annual low flow days for the observed period (2000-2025) and future scenarios (2025-2099). \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "id": "64732f83-bdd6-49df-8440-65161eade40f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create quantile table function\n",
+    "\n",
+    "def lowflow_quantile_table(lowflow_results, scenarios, periods):\n",
+    "\n",
+    "    rows = []\n",
+    "\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "            \n",
+    "            lowflow_table = lowflow_results[key][\"lowflow\"]\n",
+    "\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        values = pd.Series(all_lowflows)\n",
+    "\n",
+    "        # Append table and define quantiles \n",
+    "        rows.append({\n",
+    "            \"scenario\": scenario,\n",
+    "            \"mean\": round(values.mean(), 1),\n",
+    "            \"median\": values.median(),\n",
+    "            \"p50\": values.quantile(0.5),\n",
+    "            \"p75\": values.quantile(0.75),\n",
+    "            \"p90\": values.quantile(0.90),\n",
+    "            \"max\": values.max()})\n",
+    "\n",
+    "    return pd.DataFrame(rows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "id": "e5d0d029-feac-4d3d-8a46-7e8555815166",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Show table\n",
+    "# lowflow_quantile_table(projection_data, scenarios, periods)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f37d718b-9bec-4367-8157-8e097d9d8565",
+   "metadata": {},
+   "source": [
+    "Table 6 summarises the distribution of annual low flow days for each future scenario. SSP370 has the highest mean, median, p75 and p90 values, indicating that both typical and relative dry years contain significantly more low flow days under the scenario with the most warming. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "32545009-9884-4cdc-b259-e96928f51eae",
+   "metadata": {},
+   "source": [
+    "*Table 6: Summary of statistics of annual low flow days for future climate scenarios between 2025-2099.* \n",
+    "\n",
+    "| **Scenario**   | mean  | median | p75  | p90 | max |\n",
+    "|----------------|-------------------------|-----------|------------|-----------|-------|\n",
+    "| SSP126         | 36                      | 31        | 52         | 74        | 143   |\n",
+    "| SSP245         | 37                      | 23        | 56         | 84        | 141   |\n",
+    "| SSP370         | 43                      | 43        | 63         | 93        | 130   |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e29ffbbb-dbbe-4951-bd32-ed5c050ebe12",
+   "metadata": {},
+   "source": [
+    "## 6.2 Seasonal changes in navigational period "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "19ec21f3-1cc1-48d3-ae09-2e776ce792c5",
+   "metadata": {},
+   "source": [
+    "Besides low flow days, the timing of the open water season was re-evaluated for each climate scenario between 2025-2099 and compared to the historical period between 2000-2025. Figure 14 shows the distribution of estimated river break up dates. Compared to the historical period, all future scenarios show a shift toward earlier break up dates. The shift is strongest for SSP370, where break up occurs more frequently in March and early April. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "id": "6f6215ba-72f9-470c-96f3-ff7f474d883d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to calculate break up / freshet dates for every year and scenario\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "def find_breakup_dates(projection_data, start_year_hist, end_year_hist,start_year_fut, end_year_fut):\n",
+    "\n",
+    "    freshet_start_dates = []\n",
+    "\n",
+    "    for scenario in scenarios_new:\n",
+    "\n",
+    "        # Select years and discharge data depending on scenario\n",
+    "        if scenario == \"historical\":\n",
+    "\n",
+    "            start_year_use = start_year_hist\n",
+    "            end_year_use = end_year_hist\n",
+    "\n",
+    "            discharge_data = q_obs.copy()\n",
+    "            discharge_data[\"Year\"] = discharge_data[\"Date\"].dt.year\n",
+    "            \n",
+    "            discharge_col = \"discharge_m3s\"\n",
+    "\n",
+    "        else:\n",
+    "\n",
+    "            start_year_use = start_year_fut\n",
+    "            end_year_use = end_year_fut\n",
+    "\n",
+    "            discharge_data_list = []\n",
+    "\n",
+    "            for i in range(len(periods[0])):\n",
+    "\n",
+    "                start_year = periods[0][i]\n",
+    "                end_year = periods[1][i]\n",
+    "\n",
+    "                key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "\n",
+    "                period_data = projection_data[key][\"ensemble\"].copy()\n",
+    "\n",
+    "                period_data[\"Date\"] = pd.to_datetime(period_data.index)\n",
+    "                period_data[\"Year\"] = period_data[\"Date\"].dt.year\n",
+    "\n",
+    "                discharge_data_list.append(period_data)\n",
+    "\n",
+    "            discharge_data = pd.concat(discharge_data_list)\n",
+    "            discharge_data = discharge_data.drop_duplicates(subset=\"Date\", keep=\"first\")\n",
+    "            discharge_data = discharge_data.sort_values(\"Date\")\n",
+    "\n",
+    "            discharge_col = \"Mean\"\n",
+    "\n",
+    "        # Loop through every year\n",
+    "        for year in range(start_year_use, end_year_use + 1):\n",
+    "\n",
+    "            # Select data after March 1\n",
+    "            season_data = discharge_data[\n",
+    "                (discharge_data[\"Year\"] == year) &\n",
+    "                (discharge_data[\"Date\"] >= pd.to_datetime(f\"{year}-03-01\"))]\n",
+    "\n",
+    "            # Identify first day where q > q_critical\n",
+    "            above_critical = season_data[\n",
+    "                season_data[discharge_col] > q_critical]\n",
+    "\n",
+    "            if len(above_critical) > 0:\n",
+    "\n",
+    "                first_day = above_critical.iloc[0]\n",
+    "\n",
+    "                freshet_start_dates.append({\n",
+    "                    \"scenario\": scenario,\n",
+    "                    \"year\": year,\n",
+    "                    \"freshet_start_date\": first_day[\"Date\"],\n",
+    "                    \"discharge_m3s\": first_day[discharge_col]})\n",
+    "\n",
+    "    freshet_start_dates = pd.DataFrame(freshet_start_dates)\n",
+    "\n",
+    "    return freshet_start_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "id": "312b6d81-13cb-4d38-9b9e-84c2e83c7b54",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Run function\n",
+    "\n",
+    "breakup_start_dates = find_breakup_dates(\n",
+    "    projection_data=projection_data,\n",
+    "    start_year_hist=2000,\n",
+    "    end_year_hist=2025,\n",
+    "    start_year_fut=2025,\n",
+    "    end_year_fut=2099)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "id": "05ad8b99-cce0-44c3-a540-538a5e23d20c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to plot results on a barchart\n",
+    "\n",
+    "def plot_freshet_barchart_10day(freshet_dates, title, colname):\n",
+    "\n",
+    "    data = freshet_dates.copy()\n",
+    "\n",
+    "    # Convert freshet start date to day-of-year\n",
+    "    data[\"doy\"] = data[colname].dt.dayofyear\n",
+    "\n",
+    "    # Define 10-day bins\n",
+    "    min_doy = int(data[\"doy\"].min())\n",
+    "    max_doy = int(data[\"doy\"].max())\n",
+    "\n",
+    "    bins = np.arange(min_doy, max_doy + 10, 10)\n",
+    "\n",
+    "    data[\"date_bin\"] = pd.cut(data[\"doy\"], bins=bins, right=False)\n",
+    "\n",
+    "    # Count number of freshet dates per scenario per bin\n",
+    "    count_table = (data.groupby([\"date_bin\", \"scenario\"]).size().reset_index(name=\"count\"))\n",
+    "\n",
+    "    # Create readable labels for bins\n",
+    "    bin_labels = []\n",
+    "\n",
+    "    for interval in count_table[\"date_bin\"].cat.categories:\n",
+    "        start_date = pd.Timestamp(\"2000-01-01\") + pd.Timedelta(days=int(interval.left) - 1)\n",
+    "        end_date   = pd.Timestamp(\"2000-01-01\") + pd.Timedelta(days=int(interval.right) - 2)\n",
+    "\n",
+    "        label = f\"{start_date.strftime('%b %d')}-{end_date.strftime('%b %d')}\"\n",
+    "        bin_labels.append(label)\n",
+    "\n",
+    "    label_map = dict(zip(count_table[\"date_bin\"].cat.categories, bin_labels))\n",
+    "    \n",
+    "    count_table[\"date_bin_label\"] = count_table[\"date_bin\"].map(label_map)\n",
+    "\n",
+    "    # Pivot for plotting\n",
+    "    plot_table = count_table.pivot_table(index=\"date_bin_label\", columns=\"scenario\", values=\"count\", fill_value=0)\n",
+    "\n",
+    "    # Remove bins where all scenarios have zero observations\n",
+    "    plot_table = plot_table.loc[plot_table.sum(axis=1) > 0]\n",
+    "\n",
+    "    # Plot\n",
+    "    plot_table.plot(kind=\"bar\", figsize=(10, 5), color=[colours[scenario] for scenario in plot_table.columns])\n",
+    "\n",
+    "    plt.xlabel(f\"{title} date range\")\n",
+    "    plt.ylabel(\"Number of years\")\n",
+    "    plt.title(f\"Distribution of {title} dates by climate scenario\")\n",
+    "    plt.grid(axis=\"y\")\n",
+    "    plt.legend(title=\"Scenario\")\n",
+    "    plt.xticks(rotation=45, ha=\"right\")\n",
+    "    plt.yticks(range(0, int(plot_table.to_numpy().max()) + 1, 3))\n",
+    "\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "c08dafbb-f79e-4f35-ae27-f3dd187a5491",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_232300/1249854821.py:19: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
+      "/tmp/ipykernel_232300/1249854821.py:36: FutureWarning: The default value of observed=False is deprecated and will change to observed=True in a future version of pandas. Specify observed=False to silence this warning and retain the current behavior\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_freshet_barchart_10day(freshet_dates=breakup_start_dates, colname=\"freshet_start_date\", title=\"Break up\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8e4b742-7513-4202-919e-3cb90d9aca40",
+   "metadata": {},
+   "source": [
+    "**Figure 14:** Timing of river ice break up dates for historical period 2000-2025 and climate scenarios 2025-2099. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d21e43b-bcd0-494a-bd91-eec148888a80",
+   "metadata": {},
+   "source": [
+    "Figure 15 shows the distribution of estimated freeze up dates. The future scenarios show a shift toward later freeze up dates compared to the historical period. This indicated that the open water season becomes longer under future climate scenarios. Again, this shift is strongest for SSP370, where freeze up occurs more frequently in middle to late November with outliers in December. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9c6266fb-bc48-483b-a9f5-759d736b9dcf",
+   "metadata": {},
+   "source": [
+    "### Extract & prepare forcing data for freeze up calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "id": "90f8b01b-3cd8-4817-9b22-da65ff5ab41e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define vars for extraction\n",
+    "\n",
+    "var_names = {\"evspsblpot\", \"pr\", \"rsds\", \"tas\"}\n",
+    "\n",
+    "forcing_data = {}\n",
+    "annual_avg = []\n",
+    "period_avg = []\n",
+    "\n",
+    "for scenario in scenarios:\n",
+    "\n",
+    "    forcing_data[scenario] = {}\n",
+    "\n",
+    "    for var_name in var_names:\n",
+    "\n",
+    "        merged_data_list = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            # Define file path\n",
+    "            forcing_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / scenario / f\"CMIP6-{start_year}-{end_year}\" / f\"combined_CMIP6_{start_year}_{end_year}_{var_name}.nc\"\n",
+    "            \n",
+    "            # Load file as dataset\n",
+    "            ds = xr.open_dataset(forcing_file)\n",
+    "\n",
+    "            # Load file as array\n",
+    "            da = ds[var_name]\n",
+    "\n",
+    "            # Convert to series \n",
+    "            series = pd.Series(data=da.values.squeeze(),index=pd.to_datetime(da[\"time\"].values).normalize(),name=var_name)\n",
+    "\n",
+    "            # Convert pr and evap from km^2/s to mm^2/day\n",
+    "            if var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "                series = series * 86400\n",
+    "                annual = series.groupby(series.index.year).sum()\n",
+    "\n",
+    "            # Convert temp from Kelvin to Celcius\n",
+    "            elif var_name == \"tas\":\n",
+    "                series = series - 273.15\n",
+    "                annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "            elif var_name == \"rsds\":\n",
+    "                annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "            # Save for merged time series\n",
+    "            merged_data_list.append(series)\n",
+    "\n",
+    "            # Save annual values\n",
+    "            for year, annual_value in annual.items():\n",
+    "\n",
+    "                annual_avg.append({\n",
+    "                    \"scenario\": scenario,\n",
+    "                    \"period\": f\"{start_year}-{end_year}\",\n",
+    "                    \"year\": year,\n",
+    "                    \"variable\": var_name,\n",
+    "                    \"value\": annual_value})\n",
+    "\n",
+    "            # Save 25 year average\n",
+    "            period_avg.append({\n",
+    "                \"scenario\": scenario,\n",
+    "                \"period\": f\"{start_year}-{end_year}\",\n",
+    "                \"variable\": var_name,\n",
+    "                \"value\": annual.mean()})\n",
+    "\n",
+    "        # Merge periods into one 2025–2099 series\n",
+    "        merged_data = pd.concat(merged_data_list)\n",
+    "        merged_data = merged_data[~merged_data.index.duplicated(keep=\"first\")]\n",
+    "        merged_data = merged_data.sort_index()\n",
+    "\n",
+    "        forcing_data[scenario][var_name] = merged_data\n",
+    "\n",
+    "# Create summary table for annual avg values\n",
+    "annual_table = pd.DataFrame(annual_avg)\n",
+    "\n",
+    "# Create summary table for period avg values\n",
+    "period_table = pd.DataFrame(period_avg).pivot_table(index=[\"scenario\", \"period\"],columns=\"variable\",values=\"value\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "692e6d03-9bae-44d3-9f24-5a7206714292",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Prepare historical data\n",
+    "\n",
+    "def load_hist(start_year, end_year):\n",
+    "\n",
+    "    forcing_data_hist = {}\n",
+    "    scenario = \"historical\"\n",
+    "    forcing_data_hist[scenario] = {}\n",
+    "    annual_avg = []\n",
+    "\n",
+    "    for var_name in var_names:\n",
+    "\n",
+    "        merged_data_list = []\n",
+    "    \n",
+    "        forcing_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / scenario / f\"CMIP6-{start_year}-{end_year}\" / f\"combined_CMIP6_{start_year}_{end_year}_{var_name}.nc\"\n",
+    "\n",
+    "        # Load file as dataset\n",
+    "        ds = xr.open_dataset(forcing_file)\n",
+    "\n",
+    "        # Load file as array\n",
+    "        da = ds[var_name]\n",
+    "\n",
+    "        # Convert to series \n",
+    "        series = pd.Series(data=da.values.squeeze(),index=pd.to_datetime(da[\"time\"].values).normalize(),name=var_name)\n",
+    "\n",
+    "        # Convert pr and evap from km^2/s to mm^2/day\n",
+    "        if var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "            series = series * 86400\n",
+    "            annual = series.groupby(series.index.year).sum()\n",
+    "\n",
+    "        # Convert temp from Kelvin to Celcius\n",
+    "        elif var_name == \"tas\":\n",
+    "            series = series - 273.15\n",
+    "            annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "        elif var_name == \"rsds\":\n",
+    "            annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "        # Save for merged time series\n",
+    "        merged_data_list.append(series)\n",
+    "\n",
+    "        # Save annual values\n",
+    "        for year, annual_value in annual.items():\n",
+    "\n",
+    "            annual_avg.append({\n",
+    "                \"scenario\": scenario,\n",
+    "                \"period\": f\"{start_year}-{end_year}\",\n",
+    "                \"year\": year,\n",
+    "                \"variable\": var_name,\n",
+    "                \"value\": annual_value})\n",
+    "\n",
+    "        # Merge period into one series\n",
+    "        merged_data = pd.concat(merged_data_list)\n",
+    "        merged_data = merged_data[~merged_data.index.duplicated(keep=\"first\")]\n",
+    "        merged_data = merged_data.sort_index()\n",
+    "\n",
+    "        forcing_data_hist[scenario][var_name] = merged_data\n",
+    "            \n",
+    "    annual_hist_table = pd.DataFrame(annual_avg)\n",
+    "    \n",
+    "    return annual_hist_table, forcing_data_hist"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "id": "f645e6f7-14ae-46ca-b53b-21e42e83000e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Run function\n",
+    "\n",
+    "annual_hist_table, forcing_data_hist = load_hist(start_year=1989,end_year=2014)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "id": "9d5627b7-9b0e-4418-a8d5-2e2cbafb53f7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Merge forcing data (useful for freeze up calculation)\n",
+    "\n",
+    "forcing_data_all = forcing_data.copy()\n",
+    "\n",
+    "forcing_data_all[\"historical\"] = forcing_data_hist[\"historical\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cf7e74ca-1014-492f-816f-67147b56c1fd",
+   "metadata": {},
+   "source": [
+    "### Calculate freeze up dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "id": "449fdd42-58fd-4848-a3e6-c1bf6cc256e0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to calculate freeze up dates for every year and scenario\n",
+    "\n",
+    "AFDD_critical = 30\n",
+    "\n",
+    "def find_freezeup_dates(forcing_data, start_year_fut, end_year_fut, start_year_hist, end_year_hist):\n",
+    "\n",
+    "    AFDD_critical_dates = []\n",
+    "\n",
+    "    for scenario in scenarios_new:\n",
+    "\n",
+    "        # Extract temperature above surface (tas) data\n",
+    "        temp_data = forcing_data_all[scenario][\"tas\"]\n",
+    "\n",
+    "        # Convert into df to make life easier\n",
+    "        temp_data = pd.DataFrame({\"Date\": temp_data.index, \"Temp\": temp_data.values})\n",
+    "\n",
+    "        # Conver to datetime\n",
+    "        temp_data[\"Date\"] = pd.to_datetime(temp_data[\"Date\"])\n",
+    "\n",
+    "        # Assign year to each data point\n",
+    "        temp_data[\"Year\"] = temp_data[\"Date\"].dt.year\n",
+    "\n",
+    "        if scenario == \"historical\":\n",
+    "            \n",
+    "            start_year_use = start_year_hist\n",
+    "            end_year_use = end_year_hist\n",
+    "\n",
+    "        else:\n",
+    "\n",
+    "            start_year_use = start_year_fut\n",
+    "            end_year_use = end_year_fut\n",
+    "    \n",
+    "        # Loop through every year\n",
+    "        for year in range(start_year_use, end_year_use + 1):\n",
+    "\n",
+    "            # Start counting from October 1 to eliminate anomalies\n",
+    "            year_data = temp_data[\n",
+    "                (temp_data[\"Year\"] == year) &\n",
+    "                (temp_data[\"Date\"] >= pd.to_datetime(f\"{year}-10-01\"))]\n",
+    "\n",
+    "            # Set 0 as starting point for counting cumulative\n",
+    "            AFDD = 0\n",
+    "\n",
+    "            # Loop through all data points in a year\n",
+    "            for i in range(len(year_data)):\n",
+    "\n",
+    "                temp = year_data.iloc[i][\"Temp\"]\n",
+    "                date = year_data.iloc[i][\"Date\"]\n",
+    "\n",
+    "                # Cumulative AFDD\n",
+    "                if temp < 0:\n",
+    "                    AFDD += -temp\n",
+    "\n",
+    "                # Append when AFDD is critical\n",
+    "                if AFDD >= AFDD_critical:\n",
+    "\n",
+    "                    AFDD_critical_dates.append({\n",
+    "                        \"scenario\": scenario,\n",
+    "                        \"year\": year,\n",
+    "                        \"AFDD_critical_date\": date,\n",
+    "                        \"AFDD\": AFDD,\n",
+    "                        \"Temp\": temp})\n",
+    "                    \n",
+    "                    break\n",
+    "\n",
+    "    AFDD_critical_dates = pd.DataFrame(AFDD_critical_dates)\n",
+    "\n",
+    "    return AFDD_critical_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "id": "8314f9f1-d1d1-4854-95f5-873682d6d648",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Run function\n",
+    "\n",
+    "freezeup_dates_future = find_freezeup_dates(\n",
+    "    forcing_data=forcing_data,\n",
+    "    start_year_fut=2025,\n",
+    "    end_year_fut=2099,\n",
+    "    start_year_hist=1989,\n",
+    "    end_year_hist=2014)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "id": "91bb6224-b16f-4589-98eb-a03f79be029b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_232300/1249854821.py:19: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
+      "/tmp/ipykernel_232300/1249854821.py:36: FutureWarning: The default value of observed=False is deprecated and will change to observed=True in a future version of pandas. Specify observed=False to silence this warning and retain the current behavior\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Call barchart function\n",
+    "\n",
+    "plot_freshet_barchart_10day(freshet_dates=freezeup_dates_future, colname=\"AFDD_critical_date\", title=\"Freeze up\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "967f66c0-9471-46f7-b8ee-0fe83b01136e",
+   "metadata": {},
+   "source": [
+    "**Figure 15:** Timing of river freeze up dates for historical period 2000-2025 and climate scenarios 2025-2099. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d44c79cb-f885-485f-a9eb-1f84fcf16555",
+   "metadata": {},
+   "source": [
+    "Overall, the results indicate an expansion of the open water navigational season where under all climate scenarios, ice breaks up earlier and freezes up later compared to the historical period."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "05f79166-fc9f-4881-9ac0-5ffc116817e9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e14f19e-0bf2-4232-9dc9-14e1c68f5ad0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/7_Discussion.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/7_Discussion.ipynb
new file mode 100644
index 00000000..668c8fb8
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/7_Discussion.ipynb
@@ -0,0 +1,75 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "b304477c-8ec3-434b-b232-1407d2e51e64",
+   "metadata": {},
+   "source": [
+    "# 7. Discussion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "952ffbe8-6911-4ab2-ad6f-d437f12fef47",
+   "metadata": {},
+   "source": [
+    "## 7.1 Key Findings and implications for navigation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ad2f55ae-f649-43e5-885e-1acd56bbb150",
+   "metadata": {},
+   "source": [
+    "This study shows that future low flow days are generally higher than in the historical period, although clear long term trends over time are only visible under SSP370. The observed period contains an average of 27 annual low flow days, while future periods range from 31 to 49 annual low flow days depending on the climate scenario. SSP370 shows the clearest increase in low flow days between 2025-2099 and is the only scenario approaching statistical significance, with a p value of 0,054 exceeding the 0,05 threshold. This suggests the evidence for a long term increase in low flow days becomes stronger under the most severe climate scenario. \n",
+    "\n",
+    "However, the distribution of annual low flow days shows that extreme low flow years become more frequent in all climate scenarios. This is most extreme for SSP370, where 25% of years exceed 60 low flow days in a year, equal to the observed period's most extreme year. The magnitude of extreme years with the number of low flow days also increases as the most extreme year for all climate scenarios exceeds 130 low flow days, compared to the 60 days of the observed period. This is important for navigation because impacts are stronger when low flow conditions last several weeks or months. This would negatively affect indigenous communities that depend on the river for hunting, fishing, travel and transportation of resources. The severity of these impacts is scenario dependent and becomes stronger under SSP370, where both the long term trend and frequency of extreme years increase. \n",
+    "\n",
+    "The seasonal river ice break up and freeze up analysis shows that the open water season expands under all future climate scenarios. River ice break up shifts from late April in the historical period toward early to mid April in the future scenarios. Freeze up shifts from early November in the historical period toward early to mid November for SSP126 and SSP245 and from mid to late November for SSP370. An expansion of the open water season may improve transportation potential because river navigation does not require the construction and maintenance of ice roads. A longer open water period may increase navigation flexibility and accessibility. However, if current ice road days are replaced by warmer open water days with low flows, transportation may become limited entirely. An expansion of the open water season can therefore be problematic for indigenous communities. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f10bec21-b4f2-466d-85be-464045f9a66e",
+   "metadata": {},
+   "source": [
+    "## 7.2 Research Limitations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2cf20103-927a-4eee-ab86-145ced578b93",
+   "metadata": {},
+   "source": [
+    "A limitation of this study is regarding conceptual HBV model errors. The LAR basin has a complex structure of which some elements are not accounted for in the model. For example, the model does not explicitly account for glacier melt or non contributing areas created by potholes in the landscape. The unpredictability of ice jams make high flow or flood timings difficult to model. Using an ensemble of hydrological models or HBV model adaptations that explicitly include glacier melt, pothole storage and ice jams may yield more reliable results. \n",
+    "\n",
+    "This study only uses MPI-ESM1-2 as the earth system model within CMIP6 in generating the forcing data. A more reliable approach would use an ensemble of CMIP6 models or Canada specialised CMIP6 models, allowing uncertainty between climate models to be assessed. \n",
+    "\n",
+    "Another limitation is that the model assumes hydrological behaviour to remain constant over time. The HBV parameters are calibrated over a 20 year period and validated over a 5 year period but applied to future periods up to 2099. However, processes in the river basin may change over time. As mentioned in Chapter 2, snowfall contribution to total precipitation has decreased over time and might change further as temperatures keep rising. This could influence snow storages in the model, altering timing of runoff. Soil behavior may also change, for example through changes in seasonal frozen ground. This influences soil infiltration and HBV calibration parameters such as maximum soil moisture storage, soil runoff and maximum percolation rate. Therefore, the basin may respond differently to water in the future. \n",
+    "\n",
+    "Finally, the usage of a fixed open water period does not account for ice break up occurring earlier causing a shift in the hydrograph. Winter precipitation is partly stored as snow and released during spring melt when temperatures exceed 0 ℃. After this period, precipitation falls as rain instead of snow. If break up occurs substantially earlier under future scenarios, part of this snowmelt driven freshet as well as a fraction of rainfall may occur before the fixed start date of 18 May. As a result of this, the period after 18 May may appear drier when in reality, the seasonal hydrograph is shifted in time. For example, days in April that were frozen in the historical period may become high flow days instead. At the same time, high flow days occurring in July during the historical period may now become low flow days. \n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/8_Conclusion.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/8_Conclusion.ipynb
new file mode 100644
index 00000000..7827e424
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/8_Conclusion.ipynb
@@ -0,0 +1,81 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "68c4f63c-35cb-453e-bc48-3349b654b433",
+   "metadata": {},
+   "source": [
+    "# 8. Conclusion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "983f04be-f39f-4ad0-8b84-614f69a43fcb",
+   "metadata": {},
+   "source": [
+    "## 8.1 Conclusion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "55b90f17-1ec9-4c71-b7d0-89b21dbef406",
+   "metadata": {},
+   "source": [
+    "This study answers the research question: *“How will climate change impact discharge in the Lower Athabasca River in Canada and what implications this has for navigation?”* A critical discharge of 500 $m^3/s$ was used to identify low flow conditions that will restrict navigation at 8 critical points in the river. This threshold was applied within a fixed open water season from 18 May to 17 October. The hydrological model HBV was calibrated and validated using discharge data at Fort McMurray and ERA5 forcing data. The model was then forced with CMIP6 climate data under climate scenarios SSP126, SSP245 and SSP370 to analyse future annual low flow days in this fixed open water season between 2025-2099. \n",
+    "\n",
+    "The results indicate that future low flow days are generally higher than in the historical period. The observed period contains an average of 27 low flow days per year, while future periods range between 31 and 49 low flow days depending on the climate scenario. A clear long term increase over time is only visible under SSP370, approaching statistical significance with a p value of 0,054. However, the distribution of annual low flow days shows that extreme low flow years become more frequent in all climate scenarios. This may suggest that navigation in the LAR may become more restricted in the future, especially during longer periods where discharge falls below the critical threshold. This is particularly relevant for Indigenous communities that depend on the river for hunting, fishing, travel and transportation of resources.\n",
+    "\n",
+    "The open water season is expected to expand under future climate scenarios. River ice break up occurs earlier in spring and freeze up occurs later in autumn. This may further impact communities if cold days where ice roads may be utilised are replaced by warmer days where navigation may be restricted due to low flows. Overall, climate change is expected to increase pressure on navigation in the LAR with the strongest impacts occurring under SSP370. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5f7b8ecc-7fd1-4f05-b024-0d70905b6e2d",
+   "metadata": {},
+   "source": [
+    "## 8.2 Future Recommendations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c14793be-fa4e-47a1-8e9d-b97614f3cd32",
+   "metadata": {},
+   "source": [
+    "Future research should focus on seasonal changes in navigation. The results show that winters become shorter and the open water season expands, but the effect of this on regional transportation needs to be further investigated. This could include analysing low flow days outside the fixed open water season used in this study, to assess whether earlier ice break up and later freeze up create additional periods of restricted navigation. \n",
+    "\n",
+    "Future research should use an ensemble of climate models and hydrological models to better assess uncertainty in the projected low flow results. \n",
+    "\n",
+    "Finally, future studies should also analyse high flow conditions and flood risk during the spring freshet. Earlier snowmelt and changing precipitation patterns may shift the timing and magnitude of high flows, which could influence flood risk and navigational controls in the LAR.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fa2fb119-275f-4fab-be8f-947695359cc0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/AI_Statement.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/AI_Statement.ipynb
new file mode 100644
index 00000000..caeab22f
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/AI_Statement.ipynb
@@ -0,0 +1,49 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "cb2421af-e1a9-4664-b806-17d5a76a68c0",
+   "metadata": {},
+   "source": [
+    "# AI Statement"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ed849be7-2ba3-4ab3-a918-ca4724aa4eb6",
+   "metadata": {},
+   "source": [
+    "AI tools such as Scribbr have been used to aid with reference list generation: It should be noted outputs were manually checked.  The Language Learning Models (LLM) ChatGPT has been used for the generation of Figure 1. ChatGPT has also been used as a spelling and grammar checker for most parts of the report and used for minor improvements to improve readability. Finally, ChatGPT has been used as an assisting coding tool. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c0721f4f-489d-4785-bd3c-51aea87d3cce",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_A_Snow_depletion_curve.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_A_Snow_depletion_curve.ipynb
new file mode 100644
index 00000000..759d4400
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_A_Snow_depletion_curve.ipynb
@@ -0,0 +1,52 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d0383cc4-b9c6-415f-8d21-08287825c391",
+   "metadata": {},
+   "source": [
+    "# Appendix A: Snow depletion curve"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f9b78e60-dbf5-4556-9c81-ea4599d67efd",
+   "metadata": {},
+   "source": [
+    "Figure 16 below shows the snow depletion curve for the Upper Athabasca River (UAR) region above Hinton, covering around 10,000 km2 (Siemens et al., 2021). This shows how snowmelt may lead to sudden peaks in discharge when the snow cover depletes quickly. Although the figure is based on the UAR, the vast majority of the LAR basin lies below 1500 m elevation and may behave similarly. This line will therefore have the biggest contribution to discharge into the LAR: The snow cover depletes around the end April to start of May which is when freshet starts and aligns with the freshet algorithm (see chapter 3). "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "831855b2-e1d9-40c6-b375-7ca390ba333a",
+   "metadata": {},
+   "source": [
+    "<figure>\n",
+    "  <img src=\"Figures/SnowDepletion.jpg\">\n",
+    "  <figcaption><b>Figure 16:</b> Snow depletion curve for the Upper Athabasca River basin for the year 2000 (Siemens et al., 2021).</figcaption>\n",
+    "</figure>"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_B_Calibration_output_parameters.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_B_Calibration_output_parameters.ipynb
new file mode 100644
index 00000000..de6fc5af
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_B_Calibration_output_parameters.ipynb
@@ -0,0 +1,89 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f78804b5-42b7-4d43-90dd-62984587d028",
+   "metadata": {},
+   "source": [
+    "# Appendix B Calibration parameters output "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3bf68a02-ffee-479e-af13-c5b799b11e39",
+   "metadata": {},
+   "source": [
+    "The tables below show the HBV parameter descriptions and calibration results. Most notable from table x is the variance in soil moisture storage, maximum percolation rate, slow reservoir recession coefficient and snowmelt factor. Throughout the year soils may behave differently. During winter, frozen soils can reduce infiltration and percolation causing a larger fraction to become surface runoff, while after thawing, infiltration and soil water storage may increase. These seasonal changes can influence variability in values of Su,max, Pmax and KS. Variability in FM may be due to differences in snow accumulation and timing across the large basin. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dadc7f0e-5f9b-4101-9b28-2eeb30df566b",
+   "metadata": {},
+   "source": [
+    "*Table B.1: HBV model parameters.*\n",
+    "\n",
+    "| **Parameter**            | **Description**                                          |\n",
+    "|--------------------------|----------------------------------------------------------|\n",
+    "| $I_{\\text{max}}$         | Maximum interception storage [mm]                        |\n",
+    "| $C_{\\text{e}}$           | Evaporation correction factor [-]                        |\n",
+    "| $S_{\\text{u,max}}$       | Maximum soil moisture storage [mm]                       |\n",
+    "| $\\beta$                  | Soil runoff parameter [-]                                |\n",
+    "| $P_{\\text{max}}$         | Maximum percolation rate [mm/day]                        |\n",
+    "| $T_{\\text{lag}}$         | Time lag [days]                                          |\n",
+    "| $K_{\\text{f}}$           | Fast reservoir recession coeofficient     [1/day]        |\n",
+    "| $K_{\\text{s}}$           | Slow reservoir recession coeofficient     [1/day]        |\n",
+    "| $F_{\\text{M}}$           | Snowmelt factor                           [-]            |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "764ec9eb-001d-42e1-a1be-389fb1d82d08",
+   "metadata": {},
+   "source": [
+    "*Table B.2: Table showing 5 best calibration parameter sets.*\n",
+    "\n",
+    "| **Parameter**            | **Set 1** | **Set 2** | **Set 3** | **Set 4** | **Set 5** |                                         \n",
+    "|--------------------------|-----------|-----------|-----------|-----------|-----------|\n",
+    "| $I_{\\text{max}}$         | 6,27      | 7,36      | 7,94      | 5,55      | 7,24      |                        \n",
+    "| $C_{\\text{e}}$           | 0,48      | 0,43      | 0,46      | 0,46      | 0,47      |   \n",
+    "| $S_{\\text{u,max}}$       | 174,13    | 192,67    | 219,70    | 187,85    | 181,82    |   \n",
+    "| $\\beta$                  | 1,95      | 1,66      | 1,73      | 1,83      | 1,82      |  \n",
+    "| $P_{\\text{max}}$         | 0,33      | 0,29      | 0,26      | 0,44      | 0,48      |   \n",
+    "| $T_{\\text{lag}}$         | 6,20      | 5,32      | 5,81      | 6,29      | 5,55      |\n",
+    "| $K_{\\text{f}}$           | 0,077     | 0,094     | 0,048     | 0,063     | 0,045     |  \n",
+    "| $K_{\\text{s}}$           | 0,0044    | 0,0044    | 0,0016    | 0,033     | 0,0023    | \n",
+    "| $F_{\\text{M}}$           | 0,41      | 1,15      | 0,77      | 0,80      | 1,25      |                                        "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e904e75a-5f93-402c-8259-656e2afc6170",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_C_Calibration_code.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_C_Calibration_code.ipynb
new file mode 100644
index 00000000..83a6c5ac
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_C_Calibration_code.ipynb
@@ -0,0 +1,8959 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "25158536-a09e-49ab-8d99-f82378f29ea0",
+   "metadata": {},
+   "source": [
+    "# Appendix C: Calibration code"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c1a2e54c-fc53-4cff-a4d6-e1802f3119b5",
+   "metadata": {},
+   "source": [
+    "In this appendix is the code used to calibrate the model. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fbc7f454-3d60-492d-aa6c-0ce21a0dfc77",
+   "metadata": {},
+   "source": [
+    "## Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "95a06f73-282f-4c7c-8333-f002e73e205a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print\n",
+    "\n",
+    "from ipywidgets import IntProgress\n",
+    "from IPython.display import display"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8b61a012-64eb-48b2-ba78-f641a1a581a3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a860a623-f634-4b50-822c-51e09ab4e594",
+   "metadata": {},
+   "source": [
+    "### Defining variables & pathways"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "970798cd-b737-44f3-8edd-de3352b86efd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period & basin si\n",
+    "\n",
+    "experiment_start_date = \"2000-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2005-12-31T00:00:00Z\"\n",
+    "\n",
+    "calibration_start = \"1999-01-01T00:00:00Z\"\n",
+    "calibration_end = \"2019-12-31T00:00:00Z\"\n",
+    "\n",
+    "# validation_start = \"\"\n",
+    "# validation_end = \"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "241efaf0-94fc-4e07-8a62-151661dc4343",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "basin_size = 132572\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd4ec71b-d4f6-4a1c-be9a-f8d3b89059d1",
+   "metadata": {},
+   "source": [
+    "### Load & prepare discharge data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "d590f365-72ad-4473-9996-88820ea52c18",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1cec4b74-037a-4d48-8769-e0b57a7683aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "# start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "# end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# q_obs = q_obs[(q_obs[\"Date\"] >= start_date) & (q_obs[\"Date\"] <= end_date)]\n",
+    "# observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7c47f7f-18ff-4441-b1d4-975e46e1719b",
+   "metadata": {},
+   "source": [
+    "### Generate or Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "eb582ebf-8fbc-4542-b785-cee2f332bdd5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1999-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1999-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2019-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load ERA5 data\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6fc290da-fa08-48f0-83e3-a39e8f5c36ef",
+   "metadata": {},
+   "source": [
+    "## Calibration Methods"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba51d28d-1fdb-46af-8f8e-5dcf904aba7f",
+   "metadata": {},
+   "source": [
+    "### Method 1: NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "9ff8dc21-0959-49a4-9d4b-496726c90f88",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def NSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return 1 - np.sum((obs - sim) ** 2) / np.sum((obs - np.mean(obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "93f96591-ceb4-4671-9a48-04a0ddbfaf5a",
+   "metadata": {},
+   "source": [
+    "### Method 2: Log_NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "826cfb65-21ba-4901-aafe-37738913c0ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def log_NSE(sim, obs):\n",
+    "    # Convert for easy calculations\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8dc2e27c-2caa-493a-8ad0-3a8540ff4a18",
+   "metadata": {},
+   "source": [
+    "### Define Parameters & Storages and Times"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "2ed6540e-ec2f-4f80-975f-66fee4b2a75a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define initial storages\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])\n",
+    "\n",
+    "# Define parameters (range)\n",
+    "parameter_ranges = {\n",
+    "    \"Imax\":  (5.5, 8),            # Maximum interception storage\n",
+    "    \"Ce\":    (0.35, 0.6),       # Evaporation correction factor\n",
+    "    \"Sumax\": (150, 220),         # Maximum soil moisture storage\n",
+    "    \"Beta\":  (1.6, 2),          # Soil runoff parameter\n",
+    "    \"Pmax\":  (0.1, 0.6),            # Maximum percolation rate\n",
+    "    \"Tlag\":  (5.2, 7),           # Time lag\n",
+    "    \"Kf\":    (0.01, 0.1),       # Fast reservoir recession coefficient\n",
+    "    \"Ks\":    (0.001, 0.1),     # Slow reservoir recession coefficient\n",
+    "    \"FM\":    (0.3, 1.4),          # Snowmelt factor\n",
+    "}\n",
+    "\n",
+    "# Convert to arrays\n",
+    "parameter_names = list(parameter_ranges.keys())\n",
+    "\n",
+    "p_min = np.array([parameter_ranges[name][0] for name in parameter_names])\n",
+    "p_max = np.array([parameter_ranges[name][1] for name in parameter_names])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fc6ef77d-95ba-4277-ab8c-654fa025894d",
+   "metadata": {},
+   "source": [
+    "### Create samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "47df771f-85c1-40a7-9e28-a6dfb3134514",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.85285914e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.89990216e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.76127959e+02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.92058774e+00</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.56024109e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.99810960e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.01314564e-02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.63774925e-02</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.62585104e-01</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[1;36m7.85285914e+00\u001b[0m \u001b[1;36m3.89990216e-01\u001b[0m \u001b[1;36m1.76127959e+02\u001b[0m \u001b[1;36m1.92058774e+00\u001b[0m\n",
+       " \u001b[1;36m5.56024109e-01\u001b[0m \u001b[1;36m6.99810960e+00\u001b[0m \u001b[1;36m3.01314564e-02\u001b[0m \u001b[1;36m6.63774925e-02\u001b[0m\n",
+       " \u001b[1;36m9.62585104e-01\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Create samples\n",
+    "N = 10\n",
+    "par_samples = np.random.rand(N, len(parameter_ranges))                  # Generates random values between 0-1\n",
+    "parameter_sets = p_min + par_samples * (p_max - p_min)                  # Fits value to parameter range\n",
+    "\n",
+    "print(parameter_sets[:][0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e22418a9-e4ba-4890-85a8-abcfd66c85f2",
+   "metadata": {},
+   "source": [
+    "### Define time period"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "9c72add6-8b9f-4b3e-9e9f-77406215c196",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "calibration_start_date = pd.to_datetime(calibration_start.replace(\"Z\", \"\"))\n",
+    "calibration_end_date = pd.to_datetime(calibration_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for calibration\n",
+    "evaluation_start = pd.to_datetime(f\"{calibration_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= calibration_start_date) & (q_obs[\"Date\"] <= calibration_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "645d5bb0-de70-4b97-9aa0-93094c91ebe6",
+   "metadata": {},
+   "source": [
+    "## Calibration start function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "0f58e61f-7178-44f8-8e5e-e1fa402813c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create function to run the model\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Create model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Create config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config)\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs \n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m, \n",
+    "        index=time, \n",
+    "        name=\"Modelled discharge\")\n",
+    "    \n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e93b5d4-0a92-4d09-b135-07101e614d9e",
+   "metadata": {},
+   "source": [
+    "### Run HBV loop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "577e23e5-8db6-45a1-b91b-aae3a46b6c12",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1ce6bc7773174ef98c9608eb840d31a4",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "IntProgress(value=0, max=600)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m6\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m7\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m8\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m9\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m10\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m11\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m12\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m13\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m14\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m15\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m16\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m17\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m18\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m19\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m20\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">21</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m21\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m22\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">23</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m23\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m24\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m25\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">26</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m26\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m27\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m28\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">29</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m29\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m30\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m31\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m32\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m33\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m34\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">35</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m35\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m36\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">37</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m37\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">38</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m38\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">39</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m39\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">40</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m40\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m41\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">42</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m42\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">43</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m43\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">44</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m44\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">45</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m45\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">46</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m46\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">47</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m47\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m48\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m49\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">50</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m50\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">51</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m51\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m52\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">53</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m53\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">54</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m54\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">55</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m55\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">56</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m56\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">57</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m57\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">58</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m58\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">59</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m59\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">60</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m60\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">61</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m61\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">62</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m62\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">63</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m63\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m64\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">65</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m65\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">66</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m66\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">67</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m67\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">68</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m68\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">69</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m69\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">70</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m70\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m71\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">72</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m72\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">73</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m73\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m74\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">75</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m75\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">76</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m76\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">77</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m77\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">78</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m78\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">79</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m79\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">80</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m80\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">81</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m81\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">82</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m82\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">83</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m83\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">84</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m84\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">85</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m85\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">86</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m86\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">87</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m87\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">88</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m88\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">89</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m89\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">90</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m90\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m91\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">92</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m92\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">93</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m93\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">94</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m94\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">95</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m95\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">96</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m96\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">97</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m97\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">98</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m98\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">99</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m99\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">100</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m100\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">101</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m101\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">102</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m102\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">103</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m103\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">104</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m104\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">105</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m105\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">106</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m106\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">107</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m107\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">108</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m108\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">109</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m109\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">110</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m110\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">111</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m111\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">112</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m112\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">113</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m113\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">114</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m114\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">115</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m115\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">116</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m116\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">117</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m117\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">118</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m118\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">119</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m119\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">120</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m120\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">121</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m121\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">122</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m122\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">123</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m123\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">124</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m124\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">125</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m125\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">126</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m126\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">127</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m127\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">128</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m128\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">129</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m129\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">130</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m130\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">131</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m131\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">132</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m132\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">133</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m133\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">134</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m134\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">135</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m135\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">136</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m136\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">137</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m137\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">138</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m138\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">139</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m139\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">140</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m140\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">141</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m141\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">142</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m142\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">143</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m143\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">144</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m144\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">145</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m145\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">146</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m146\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">147</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m147\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">148</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m148\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">149</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m149\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">150</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m150\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">151</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m151\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">152</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m152\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">153</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m153\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">154</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m154\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">155</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m155\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">156</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m156\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">157</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m157\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">158</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m158\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">159</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m159\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">160</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m160\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">161</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m161\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">162</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m162\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">163</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m163\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">164</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m164\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">165</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m165\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">166</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m166\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">167</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m167\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">168</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m168\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">169</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m169\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">170</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m170\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">171</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m171\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">172</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m172\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">173</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m173\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m174\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">175</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m175\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">176</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m176\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">177</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m177\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">178</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m178\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m179\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">180</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m180\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">181</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m181\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">182</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m182\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m183\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">184</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m184\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">185</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m185\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">186</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m186\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">187</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m187\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">188</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m188\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">189</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m189\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">190</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m190\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">191</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m191\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">192</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m192\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">193</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m193\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">194</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m194\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">195</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m195\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">196</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m196\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">197</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m197\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">198</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m198\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">199</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m199\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">200</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m200\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">201</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m201\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">202</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m202\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">203</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m203\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">204</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m204\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">205</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m205\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">206</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m206\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">207</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m207\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">208</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m208\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">209</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m209\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">210</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m210\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">211</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m211\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">212</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m212\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">213</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m213\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">214</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m214\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">215</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m215\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">216</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m216\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">217</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m217\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m218\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">219</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m219\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">220</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m220\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">221</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m221\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">222</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m222\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">223</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m223\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">224</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m224\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">225</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m225\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">226</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m226\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">227</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m227\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">228</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m228\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">229</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m229\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">230</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m230\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">231</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m231\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m232\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">233</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m233\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">234</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m234\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">235</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m235\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">236</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m236\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">237</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m237\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">238</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m238\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">239</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m239\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">240</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m240\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">241</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m241\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">242</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m242\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">243</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m243\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">244</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m244\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">245</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m245\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">246</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m246\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">247</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m247\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">248</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m248\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">249</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m249\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">250</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m250\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">251</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m251\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">252</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m252\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">253</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m253\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">254</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m254\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">255</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m255\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">256</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m256\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">257</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m257\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">258</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m258\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">259</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m259\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">260</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m260\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">261</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m261\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">262</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m262\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">263</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m263\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">264</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m264\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">265</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m265\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">266</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m266\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">267</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m267\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">268</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m268\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">269</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m269\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">270</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m270\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">271</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m271\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">272</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m272\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">273</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m273\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">274</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m274\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">275</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m275\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">276</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m276\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">277</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m277\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">278</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m278\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">279</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m279\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">280</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m280\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">281</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m281\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">282</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m282\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">283</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m283\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">284</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m284\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">285</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m285\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">286</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m286\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">287</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m287\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">288</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m288\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">289</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m289\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">290</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m290\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">291</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m291\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">292</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m292\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">293</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m293\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">294</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m294\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m295\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m296\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m297\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m298\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m299\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m300\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">301</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m301\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">302</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m302\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">303</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m303\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">304</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m304\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">305</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m305\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">306</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m306\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">307</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m307\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">308</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m308\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">309</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m309\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">310</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m310\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">311</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m311\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">312</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m312\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">313</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m313\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">314</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m314\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">315</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m315\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">316</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m316\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">317</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m317\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">318</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m318\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">319</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m319\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">320</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m320\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">321</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m321\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">322</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m322\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">323</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m323\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">324</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m324\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">325</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m325\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">326</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m326\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">327</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m327\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">328</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m328\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">329</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m329\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">330</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m330\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">331</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m331\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">332</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m332\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">333</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m333\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">334</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m334\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">335</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m335\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">336</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m336\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">337</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m337\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">338</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m338\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">339</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m339\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">340</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m340\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">341</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m341\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">342</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m342\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">343</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m343\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">344</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m344\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">345</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m345\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">346</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m346\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">347</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m347\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">348</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m348\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">349</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m349\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">350</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m350\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">351</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m351\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">352</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m352\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">353</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m353\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">354</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m354\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">355</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m355\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">356</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m356\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">357</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m357\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">358</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m358\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">359</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m359\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">360</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m360\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">361</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m361\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">362</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m362\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">363</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m363\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">364</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m364\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">365</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m365\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">366</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m366\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">367</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m367\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">368</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m368\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">369</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m369\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">370</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m370\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">371</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m371\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">372</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m372\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">373</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m373\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">374</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m374\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">375</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m375\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">376</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m376\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">377</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m377\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">378</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m378\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">379</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m379\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">380</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m380\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">381</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m381\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">382</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m382\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">383</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m383\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">384</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m384\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">385</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m385\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">386</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m386\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">387</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m387\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">388</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m388\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">389</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m389\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">390</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m390\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">391</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m391\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">392</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m392\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">393</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m393\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">394</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m394\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">395</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m395\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">396</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m396\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">397</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m397\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">398</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m398\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">399</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m399\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">400</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m400\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">401</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m401\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">402</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m402\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">403</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m403\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">404</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m404\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">405</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m405\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">406</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m406\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">407</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m407\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">408</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m408\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">409</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m409\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">410</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m410\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">411</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m411\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">412</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m412\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">413</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m413\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">414</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m414\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">415</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m415\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">416</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m416\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">417</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m417\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">418</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m418\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">419</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m419\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">420</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m420\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">421</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m421\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">422</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m422\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">423</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m423\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">424</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m424\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">425</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m425\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">426</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m426\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">427</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m427\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">428</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m428\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">429</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m429\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">430</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m430\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">431</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m431\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">432</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m432\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">433</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m433\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">434</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m434\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">435</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m435\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">436</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m436\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">437</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m437\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">438</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m438\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">439</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m439\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">440</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m440\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">441</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m441\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">442</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m442\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">443</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m443\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">444</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m444\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">445</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m445\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">446</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m446\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">447</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m447\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">448</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m448\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">449</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m449\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">450</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m450\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m451\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">452</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m452\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">453</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m453\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">454</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m454\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">455</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m455\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">456</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m456\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">457</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m457\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">458</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m458\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">459</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m459\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">460</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m460\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">461</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m461\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">462</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m462\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">463</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m463\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">464</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m464\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">465</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m465\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">466</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m466\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">467</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m467\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">468</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m468\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">469</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m469\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">470</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m470\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">471</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m471\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">472</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m472\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">473</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m473\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">474</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m474\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">475</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m475\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">476</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m476\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">477</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m477\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">478</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m478\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">479</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m479\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">480</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m480\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">481</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m481\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">482</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m482\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">483</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m483\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">484</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m484\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">485</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m485\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">486</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m486\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">487</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m487\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">488</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m488\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">489</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m489\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">490</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m490\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">491</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m491\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">492</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m492\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">493</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m493\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">494</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m494\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">495</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m495\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">496</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m496\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">497</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m497\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">498</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m498\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">499</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m499\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">500</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m500\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">501</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m501\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">502</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m502\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">503</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m503\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">504</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m504\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">505</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m505\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">506</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m506\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">507</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m507\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">508</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m508\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">509</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m509\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">510</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m510\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">511</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m511\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">512</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m512\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">513</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m513\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">514</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m514\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">515</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m515\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">516</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m516\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">517</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m517\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">518</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m518\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">519</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m519\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">520</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m520\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">521</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m521\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">522</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m522\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">523</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m523\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">524</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m524\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">525</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m525\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">526</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m526\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">527</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m527\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">528</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m528\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">529</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m529\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">530</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m530\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">531</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m531\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">532</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m532\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">533</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m533\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">534</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m534\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">535</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m535\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">536</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m536\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">537</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m537\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">538</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m538\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">539</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m539\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">540</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m540\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">541</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m541\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">542</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m542\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">543</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m543\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">544</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m544\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">545</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m545\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">546</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m546\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">547</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m547\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">548</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m548\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">549</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m549\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">550</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m550\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">551</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m551\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">552</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m552\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">553</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m553\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">554</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m554\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">555</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m555\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">556</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m556\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">557</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m557\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">558</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m558\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">559</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m559\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">560</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m560\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">561</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m561\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">562</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m562\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">563</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m563\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">564</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m564\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">565</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m565\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">566</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m566\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">567</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m567\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">568</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m568\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">569</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m569\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">570</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m570\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">571</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m571\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">572</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m572\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">573</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m573\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">574</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m574\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">575</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m575\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">576</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m576\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">577</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m577\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">578</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m578\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">579</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m579\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">580</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m580\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">581</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m581\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">582</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m582\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">583</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m583\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">584</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m584\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">585</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m585\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">586</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m586\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">587</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m587\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">588</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m588\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">589</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m589\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">590</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m590\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">591</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m591\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">592</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m592\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">593</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m593\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">594</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m594\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m595\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m596\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m597\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m598\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m599\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m600\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = []\n",
+    "\n",
+    "# Progress bar for visualization\n",
+    "f = IntProgress(min=0, max=N)\n",
+    "display(f)\n",
+    "\n",
+    "for i in range(N):\n",
+    "    print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "    simulated = run_hbv(\n",
+    "        parameters=parameter_sets[i], \n",
+    "        initial_storages=s_0, \n",
+    "        forcing=ERA5_forcing)\n",
+    "\n",
+    "    # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "    simulated_daily = simulated\n",
+    "    observed_daily = observed_output\n",
+    "\n",
+    "    simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "    \n",
+    "    # Align simulated and observed data\n",
+    "    combined_data = pd.DataFrame(\n",
+    "        {\"Modelled discharge\": simulated_daily, \n",
+    "        \"Observed discharge\": observed_daily}).dropna()\n",
+    "\n",
+    "    # Skip first year as warm-up\n",
+    "    combined_data = combined_data[\n",
+    "        (combined_data.index >= evaluation_start) &\n",
+    "        (combined_data.index <= calibration_end_date)]\n",
+    "\n",
+    "    # Exclude ice affected winter period\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])]\n",
+    "\n",
+    "    # Append results and drop nan\n",
+    "    if combined_data.empty:\n",
+    "        print(f\"No overlapping data for parameter set {i+1}\")\n",
+    "        nse = np.nan\n",
+    "        log_nse = np.nan\n",
+    "    else:\n",
+    "        nse = NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"])\n",
+    "        \n",
+    "        log_nse = log_NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"])\n",
+    "        \n",
+    "    results.append({\n",
+    "        \"run\": i,\n",
+    "        \"NSE\": nse,\n",
+    "        \"log_NSE\": log_nse,\n",
+    "        \"parameters\": parameter_sets[i]})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d7b5f35-f872-4ef5-8ced-c92cdd81c8f8",
+   "metadata": {},
+   "source": [
+    "### Display best results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "4c69f827-adda-4ec9-8863-abf0ba31e0d2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">     run       NSE   log_NSE\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.288376</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.337195</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.279102</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.480497</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.384565</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.462463</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.085379</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.265060</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.118825</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.395402</span>\n",
+       "..   <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378628</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.445890</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.190509</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.402412</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.034397</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.105571</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.174568</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.090100</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.379411</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.461890</span>\n",
+       "\n",
+       "<span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span> rows x <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span> columns<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "     run       NSE   log_NSE\n",
+       "\u001b[1;36m0\u001b[0m      \u001b[1;36m0\u001b[0m  \u001b[1;36m0.288376\u001b[0m  \u001b[1;36m0.337195\u001b[0m\n",
+       "\u001b[1;36m1\u001b[0m      \u001b[1;36m1\u001b[0m  \u001b[1;36m0.279102\u001b[0m  \u001b[1;36m0.480497\u001b[0m\n",
+       "\u001b[1;36m2\u001b[0m      \u001b[1;36m2\u001b[0m  \u001b[1;36m0.384565\u001b[0m  \u001b[1;36m0.462463\u001b[0m\n",
+       "\u001b[1;36m3\u001b[0m      \u001b[1;36m3\u001b[0m \u001b[1;36m-0.085379\u001b[0m  \u001b[1;36m0.265060\u001b[0m\n",
+       "\u001b[1;36m4\u001b[0m      \u001b[1;36m4\u001b[0m  \u001b[1;36m0.118825\u001b[0m  \u001b[1;36m0.395402\u001b[0m\n",
+       "..   \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m\n",
+       "\u001b[1;36m595\u001b[0m  \u001b[1;36m595\u001b[0m  \u001b[1;36m0.378628\u001b[0m  \u001b[1;36m0.445890\u001b[0m\n",
+       "\u001b[1;36m596\u001b[0m  \u001b[1;36m596\u001b[0m  \u001b[1;36m0.190509\u001b[0m  \u001b[1;36m0.402412\u001b[0m\n",
+       "\u001b[1;36m597\u001b[0m  \u001b[1;36m597\u001b[0m  \u001b[1;36m0.034397\u001b[0m \u001b[1;36m-0.105571\u001b[0m\n",
+       "\u001b[1;36m598\u001b[0m  \u001b[1;36m598\u001b[0m  \u001b[1;36m0.174568\u001b[0m  \u001b[1;36m0.090100\u001b[0m\n",
+       "\u001b[1;36m599\u001b[0m  \u001b[1;36m599\u001b[0m  \u001b[1;36m0.379411\u001b[0m  \u001b[1;36m0.461890\u001b[0m\n",
+       "\n",
+       "\u001b[1m[\u001b[0m\u001b[1;36m600\u001b[0m rows x \u001b[1;36m3\u001b[0m columns\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span> with NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5042075946097913</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m232\u001b[0m with NSE: \u001b[1;36m0.5042075946097913\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.488362330365561</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4845571293512798</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218.83336737778694</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.7699130278847444</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1358146729030282</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.44235281882723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.04585512368848791</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.008840391568068273</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8983450417631202</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.488362330365561\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.4845571293512798\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m218.83336737778694\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.7699130278847444\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.1358146729030282\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.44235281882723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.04585512368848791\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.008840391568068273\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.8983450417631202\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span> with log_NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5985790718618934</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m451\u001b[0m with log_NSE: \u001b[1;36m0.5985790718618934\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.9919295474161505</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.44128061023639964</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183.49045936834898</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.62907119850059</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5726586861631707</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.2154764587256395</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06546844116401723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0025930490563726475</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.1427426360454793</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.9919295474161505\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.44128061023639964\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m183.49045936834898\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.62907119850059\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.5726586861631707\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.2154764587256395\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.06546844116401723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.0025930490563726475\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.1427426360454793\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = pd.DataFrame(results)\n",
+    "\n",
+    "print(results[[\"run\", \"NSE\", \"log_NSE\"]])\n",
+    "\n",
+    "# # Best NSE\n",
+    "# best_run_nse = results[\"NSE\"].idxmax()\n",
+    "# best_result_nse = results.loc[best_run_nse]\n",
+    "\n",
+    "# best_parameters_nse = best_result_nse[\"parameters\"]\n",
+    "# best_nse = best_result_nse[\"NSE\"]\n",
+    "\n",
+    "# print(f'Best run: {best_run_nse} with NSE: {best_nse}, with parameters:')\n",
+    "# print(list(zip(parameter_names, best_parameters_nse)))\n",
+    "\n",
+    "# Best log_NSE\n",
+    "best_run_log_nse = results[\"log_NSE\"].idxmax()\n",
+    "best_result_log_nse = results.loc[best_run_log_nse]\n",
+    "\n",
+    "best_parameters_log_nse = best_result_log_nse[\"parameters\"]\n",
+    "best_log_nse = best_result_log_nse[\"log_NSE\"]\n",
+    "\n",
+    "print(f'Best run: {best_run_log_nse} with log_NSE: {best_log_nse}, with parameters:')\n",
+    "print(list(zip(parameter_names, best_parameters_log_nse)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "bb2f1f27-9a79-41fa-b416-e32bbee15075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5985790718618934</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m1\u001b[0m: run \u001b[1;36m451\u001b[0m with LNSE: \u001b[1;36m0.5985790718618934\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.9919295474161505</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.44128061023639964</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183.49045936834898</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.62907119850059</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5726586861631707</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.2154764587256395</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06546844116401723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0025930490563726475</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.1427426360454793</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.9919295474161505\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.44128061023639964\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m183.49045936834898\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.62907119850059\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.5726586861631707\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.2154764587256395\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.06546844116401723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.0025930490563726475\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.1427426360454793\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">193</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5871245105302814</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m2\u001b[0m: run \u001b[1;36m193\u001b[0m with LNSE: \u001b[1;36m0.5871245105302814\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.882658193683639</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.47241275652770587</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">194.30386240959916</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.781621276884348</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4608178778064105</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.215364575839981</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06419932503784231</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.015979806886031615</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0919722363345776</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m5.882658193683639\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.47241275652770587\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m194.30386240959916\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.781621276884348\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.4608178778064105\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.215364575839981\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.06419932503784231\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.015979806886031615\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.0919722363345776\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5802931655594039</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m3\u001b[0m: run \u001b[1;36m71\u001b[0m with LNSE: \u001b[1;36m0.5802931655594039\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.279358279165555</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.45738099679628363</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218.06826364855027</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.8389403651683596</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.49366891001367486</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.037707687593043</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.07007118899924838</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.024409700594446738</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.2556224532809368</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.279358279165555\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.45738099679628363\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m218.06826364855027\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.8389403651683596\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.49366891001367486\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.037707687593043\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.07007118899924838\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.024409700594446738\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.2556224532809368\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">152</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5697643546613578</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m4\u001b[0m: run \u001b[1;36m152\u001b[0m with LNSE: \u001b[1;36m0.5697643546613578\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.301551796430246</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.49391712556044987</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">211.00486173599964</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9612109256650778</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.46785716423961</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.467897643950326</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.055226399867357515</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.03429434734237983</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.191697747701756</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m7.301551796430246\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.49391712556044987\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m211.00486173599964\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.9612109256650778\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.46785716423961\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.467897643950326\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.055226399867357515\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.03429434734237983\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.191697747701756\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5666729995545778</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m5\u001b[0m: run \u001b[1;36m232\u001b[0m with LNSE: \u001b[1;36m0.5666729995545778\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.488362330365561</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4845571293512798</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218.83336737778694</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.7699130278847444</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1358146729030282</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.44235281882723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.04585512368848791</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.008840391568068273</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8983450417631202</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.488362330365561\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.4845571293512798\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m218.83336737778694\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.7699130278847444\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.1358146729030282\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.44235281882723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.04585512368848791\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.008840391568068273\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.8983450417631202\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get ensemble \n",
+    "\n",
+    "best_5_runs = results[\"log_NSE\"].nlargest(5).index\n",
+    "\n",
+    "best_5_parameters = []\n",
+    "best_5_LNSE = []\n",
+    "\n",
+    "for i in range(len(best_5_runs)):\n",
+    "\n",
+    "    run = best_5_runs[i]\n",
+    "    result = results.loc[run]\n",
+    "\n",
+    "    parameters = result[\"parameters\"]\n",
+    "    lnse = result[\"log_NSE\"]\n",
+    "\n",
+    "    best_5_parameters.append(parameters)\n",
+    "    best_5_LNSE.append(log_nse)\n",
+    "\n",
+    "    print(f\"Rank {i+1}: run {run} with LNSE: {lnse}\")\n",
+    "    print(list(zip(parameter_names, parameters)))\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "127ab139-2d7a-43ad-b012-11188e931c9c",
+   "metadata": {},
+   "source": [
+    "### Plot Observed vs Modelled"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "aeb2ea7e-9826-450f-880e-e1e5e72c9dba",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Overall Plot\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "simulated_calibrated_nse = run_hbv(\n",
+    "    parameters=best_parameters_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)\n",
+    "\n",
+    "simulated_calibrated_log_nse = run_hbv(\n",
+    "    parameters=best_parameters_log_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)\n",
+    "\n",
+    "# Align dates\n",
+    "simulated_plot_nse = simulated_calibrated_nse\n",
+    "simulated_plot_log_nse = simulated_calibrated_log_nse\n",
+    "observed_plot = observed_output\n",
+    "\n",
+    "simulated_plot_nse.index = pd.to_datetime(simulated_plot_nse.index).tz_localize(None).normalize()\n",
+    "simulated_plot_log_nse.index = pd.to_datetime(simulated_plot_log_nse.index).tz_localize(None).normalize()\n",
+    "observed_plot.index = pd.to_datetime(observed_plot.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Combine modelled and observed data\n",
+    "plot_data = pd.DataFrame({\n",
+    "    \"Modelled discharge NSE\": simulated_plot_nse,\n",
+    "    \"Modelled discharge log_NSE\": simulated_plot_log_nse,\n",
+    "    \"Observed discharge\": observed_plot}).dropna()\n",
+    "\n",
+    "# Calculate NSE & log NSE for plotted data\n",
+    "plot_nse = NSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"])\n",
+    "\n",
+    "plot_log_nse = log_NSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"])\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\")\n",
+    "# plt.plot(plot_data.index, plot_data[\"Modelled discharge NSE\"], label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data.index, plot_data[\"Modelled discharge log_NSE\"], label=\"Modelled discharge log_NSE\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001, NSE = {best_nse:.3f}, log NSE = {best_log_nse:.3f}\")\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f'Critical discharge ({q_critical} m³/s', color='black')\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "e0743eb6-3efd-435c-866f-d0ea2bddfea8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for 1 year\n",
+    "\n",
+    "selected_year = 2015\n",
+    "\n",
+    "plot_data_year = plot_data[plot_data.index.year == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Observed discharge\"],label=\"Observed discharge\")\n",
+    "# plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge NSE\"],label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge log_NSE\"],label=\"Modelled discharge log_NSE\", color=\"green\")\n",
+    "\n",
+    "plt.axhline(y=q_critical,linestyle=\":\",color=\"black\",label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001 in {selected_year}\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_D_Validation_results_per_year.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_D_Validation_results_per_year.ipynb
new file mode 100644
index 00000000..4acc427e
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_D_Validation_results_per_year.ipynb
@@ -0,0 +1,847 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "648afeb2-160d-44ab-888e-a6bce6114433",
+   "metadata": {},
+   "source": [
+    "# Appendix D: Validation results per year"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4238eded-6718-4915-893c-28b9549355ed",
+   "metadata": {},
+   "source": [
+    "The structure of this notebook is as follows:\n",
+    "\n",
+    "### 1. Startup\n",
+    "### 2. Model Setup\n",
+    "### 3. Running model\n",
+    "### 4. Display Results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8a3abf9d-a072-425a-a3ae-b3ea2cf7f2ea",
+   "metadata": {},
+   "source": [
+    "## 1. Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "8d58675e-0bb1-4f3b-9500-19e3b46098b2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "5b3ff9cd-6ea3-4a4e-b8f0-136252ef130b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "77f19b14-be2c-4a15-ac6e-5195a6909841",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500\n",
+    "\n",
+    "# Choosing time period\n",
+    "\n",
+    "validation_start_yr = 2019\n",
+    "validation_end_yr = 2024\n",
+    "\n",
+    "experiment_start_date = f\"{validation_start_yr}-01-01T00:00:00Z\"\n",
+    "experiment_end_date = f\"{validation_end_yr}-12-31T00:00:00Z\"\n",
+    "\n",
+    "validation_start = f\"{validation_start_yr}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{validation_end_yr}-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "9cf31d32-6f63-43fb-87be-1cb75655035e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"forcings\" / \"ERA5\" / f\"ERA5-{validation_start_yr}-{validation_end_yr}\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "fbd77d74-78b7-414b-b793-a750366b8516",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "72225e3b-955f-4bdc-912e-fe7c8f8056a1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs to relevant dates\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= validation_start_date) & (q_obs[\"Date\"] <= validation_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c77c0de3-bcb2-4c16-9c48-1734033fbb5d",
+   "metadata": {},
+   "source": [
+    "### Generate/Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "a348803f-8798-4a77-890a-622d46ee816d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2024-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">ngs/ERA5/ERA5-2019-2024'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">s/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_2019_2024_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'2019-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2024-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci\u001b[0m\n",
+       "\u001b[32mngs/ERA5/ERA5-2019-2024'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile\u001b[0m\n",
+       "\u001b[32ms/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_2019_2024_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "081a6035-fa82-4ede-b33f-6e90dd4d8255",
+   "metadata": {},
+   "source": [
+    "### Load parameter sets & initial storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "621ec44f-c5e9-4de7-a6fb-6f8d5ebf60a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"]          # Snowmelt factor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "f586d4c6-abaf-407b-9f5d-7346c013e302",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2e231c20-f290-41c8-9734-ee6b5088d951",
+   "metadata": {},
+   "source": [
+    "## 2. Model setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "93de22e4-b44a-4eef-9655-685bbb4465ca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config)\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\")\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3d978890-678e-4458-9704-837691c0b69b",
+   "metadata": {},
+   "source": [
+    "## 3. Running model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "7f3b0ee6-5498-403e-9654-b1c9934322f2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing)\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Filter observed data by day\n",
+    "    observed_daily = observed_output\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "    ensemble_data['Observed discharge'] = observed_daily\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "f49a5d8b-2ad6-4f06-b58f-d0ae52a9a8dc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set 1</th>\n",
+       "      <th>Set 2</th>\n",
+       "      <th>Set 3</th>\n",
+       "      <th>Set 4</th>\n",
+       "      <th>Set 5</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Observed discharge</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2019-01-02</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>213.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-01-03</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>213.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-01-04</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>214.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-01-05</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>214.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-01-06</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>214.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Set 1  Set 2  Set 3  Set 4  Set 5  Mean  Observed discharge\n",
+       "2019-01-02    0.0    0.0    0.0    0.0    0.0   0.0               213.0\n",
+       "2019-01-03    0.0    0.0    0.0    0.0    0.0   0.0               213.0\n",
+       "2019-01-04    0.0    0.0    0.0    0.0    0.0   0.0               214.0\n",
+       "2019-01-05    0.0    0.0    0.0    0.0    0.0   0.0               214.0\n",
+       "2019-01-06    0.0    0.0    0.0    0.0    0.0   0.0               214.0"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ensemble_data = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)\n",
+    "\n",
+    "ensemble_data.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "06841a30-01ee-4972-819f-c058e15f94eb",
+   "metadata": {},
+   "source": [
+    "## 4. Display results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "2c2e229c-6796-4d97-b1c5-ae25ceb1a411",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_ensemble(ensemble_data, plot_start, plot_end):\n",
+    "\n",
+    "    plot_start = pd.to_datetime(plot_start)\n",
+    "    plot_end = pd.to_datetime(plot_end)\n",
+    "\n",
+    "    # Filter data to start & end time\n",
+    "    plot_data = ensemble_data[\n",
+    "        (ensemble_data.index >= plot_start) &\n",
+    "        (ensemble_data.index <= plot_end)].dropna()\n",
+    "\n",
+    "    # Define figure\n",
+    "    plt.figure()\n",
+    "    plt.figure(figsize=(15, 6))\n",
+    "\n",
+    "    # Plot sets, observed data, ensemble mean and axhline, respectively\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        plt.plot(plot_data.index, plot_data[f\"Set {i+1}\"], color=\"orange\", alpha=0.3, label=\"Parameter sets\" if i == 0 else None)\n",
+    "\n",
+    "    plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\", linewidth=3)\n",
+    "    plt.plot(plot_data.index, plot_data[\"Mean\"], label=\"Ensemble mean\", linewidth=3)\n",
+    "    plt.axhline(y=q_critical, linestyle=\":\", color=\"black\", label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "    # Extras\n",
+    "    plt.xlabel(\"Date\")\n",
+    "    plt.ylabel(\"Discharge (m³/s)\")\n",
+    "    plt.title(\"Observed vs modelled ensemble discharge at 07DA001\")\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "2abfb14e-54ee-467e-a096-aeeaa7beea59",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2020\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "36e717bf-29ca-4307-b698-4af9157fc386",
+   "metadata": {},
+   "source": [
+    "**Figure 17:** Validation results showing observed and ERA5 discharge for 2020. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "ab19e911-4d6f-4e67-a458-dbf7d92f8912",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2021\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f84d18e5-59c7-4e91-a72b-269e65718bb5",
+   "metadata": {},
+   "source": [
+    "**Figure 18:** Validation results showing observed and ERA5 discharge for 2021. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "d2b56585-9701-45ef-aa89-aeeda234f566",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2022\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "689d5905-1e82-4de6-ad82-36d1a737b3f6",
+   "metadata": {},
+   "source": [
+    "**Figure 19:** Validation results showing observed and ERA5 discharge for 2022. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "e05d111a-b4a1-4034-986b-2d0a7b739cdc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2023\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fc021c83-ee3b-4258-a0ff-3047631a599c",
+   "metadata": {},
+   "source": [
+    "**Figure 20:** Validation results showing observed and ERA5 discharge for 2023. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "ad29be6a-a264-4b97-aff7-60f2203bb5a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2024\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6c95f4d5-d0ba-4a9b-962e-1ac2bf2e611d",
+   "metadata": {},
+   "source": [
+    "**Figure 21:** Validation results showing observed and ERA5 discharge for 2024. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bec79310-234d-463b-b5d6-f8108821108a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_E_Forcing_data_analysis.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_E_Forcing_data_analysis.ipynb
new file mode 100644
index 00000000..fb038a81
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_E_Forcing_data_analysis.ipynb
@@ -0,0 +1,796 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3d4c966f-bfaa-480d-8119-39977afb7fb3",
+   "metadata": {},
+   "source": [
+    "# Forcing data analysis\n",
+    "\n",
+    "The CMIP6 forcing data have been plotted to analyse changing trends. This has been done for all forcing inputs: Temperature, precipitation, shortwave radiation and potential evaporation in the LAR basin. \n",
+    "\n",
+    "The structure of the notebook below is as follows:\n",
+    "\n",
+    "##### 1. Startup & Imports\n",
+    "##### 2. Preparing the forcing data\n",
+    "##### 4. 3. Period forcing avg table\n",
+    "##### 4. Yearly forcing avg graph"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f87ddfbc-011a-4fba-8e0c-38e04f89dc13",
+   "metadata": {},
+   "source": [
+    "## 1. Startup & Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "0f1acb46-b1cb-487a-9a0f-fb16148520c3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Imports\n",
+    "\n",
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "from scipy.interpolate import interp1d\n",
+    "from scipy.stats import linregress\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "d35ea351-fb1c-468b-a0a5-731e14655f5d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "8af890d8-47f7-4c5d-8dc4-5ee3aa03a62d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500\n",
+    "\n",
+    "# Define only future scenarios\n",
+    "scenarios = [\"ssp126\", \"ssp245\", \"ssp370\"]\n",
+    "\n",
+    "# Redefine scenarios to include historical\n",
+    "scenarios_new = [\"historical\", \"ssp126\", \"ssp245\", \"ssp370\"]\n",
+    "\n",
+    "# Attach colours to scenarios to make plotting easier \n",
+    "colours = {\"historical\": \"tab:blue\", \"ssp126\": \"green\", \"ssp245\": \"orange\", \"ssp370\": \"red\"}\n",
+    "\n",
+    "# Define periods\n",
+    "periods = [[2025, 2050, 2075],\n",
+    "           [2050, 2075, 2099]]\n",
+    "\n",
+    "hist_periods = ([1989], [2014]) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "55371032-41c4-4feb-81f1-afe203dcd1a3",
+   "metadata": {},
+   "source": [
+    "## 2. Preparing the forcing data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "2a90d494-1f3e-4941-9775-e25b6786f5ab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "var_names = {\"evspsblpot\", \"pr\", \"rsds\", \"tas\"}\n",
+    "\n",
+    "forcing_data = {}\n",
+    "annual_avg = []\n",
+    "period_avg = []\n",
+    "\n",
+    "for scenario in scenarios:\n",
+    "\n",
+    "    forcing_data[scenario] = {}\n",
+    "\n",
+    "    for var_name in var_names:\n",
+    "\n",
+    "        merged_data_list = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            # Define file path\n",
+    "            forcing_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / scenario / f\"CMIP6-{start_year}-{end_year}\" / f\"combined_CMIP6_{start_year}_{end_year}_{var_name}.nc\"\n",
+    "            \n",
+    "            # Load file as dataset\n",
+    "            ds = xr.open_dataset(forcing_file)\n",
+    "\n",
+    "            # Load file as array\n",
+    "            da = ds[var_name]\n",
+    "\n",
+    "            # Convert to series \n",
+    "            series = pd.Series(data=da.values.squeeze(),index=pd.to_datetime(da[\"time\"].values).normalize(),name=var_name)\n",
+    "\n",
+    "            # Convert pr and evap from km^2/s to mm^2/day\n",
+    "            if var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "                series = series * 86400\n",
+    "                annual = series.groupby(series.index.year).sum()\n",
+    "\n",
+    "            # Convert temp from Kelvin to Celcius\n",
+    "            elif var_name == \"tas\":\n",
+    "                series = series - 273.15\n",
+    "                annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "            elif var_name == \"rsds\":\n",
+    "                annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "            # Save for merged time series\n",
+    "            merged_data_list.append(series)\n",
+    "\n",
+    "            # Save annual values\n",
+    "            for year, annual_value in annual.items():\n",
+    "\n",
+    "                annual_avg.append({\n",
+    "                    \"scenario\": scenario,\n",
+    "                    \"period\": f\"{start_year}-{end_year}\",\n",
+    "                    \"year\": year,\n",
+    "                    \"variable\": var_name,\n",
+    "                    \"value\": annual_value})\n",
+    "\n",
+    "            # Save 25 year average\n",
+    "            period_avg.append({\n",
+    "                \"scenario\": scenario,\n",
+    "                \"period\": f\"{start_year}-{end_year}\",\n",
+    "                \"variable\": var_name,\n",
+    "                \"value\": annual.mean()})\n",
+    "\n",
+    "        # Merge periods into one 2025–2099 series\n",
+    "        merged_data = pd.concat(merged_data_list)\n",
+    "        merged_data = merged_data[~merged_data.index.duplicated(keep=\"first\")]\n",
+    "        merged_data = merged_data.sort_index()\n",
+    "\n",
+    "        forcing_data[scenario][var_name] = merged_data\n",
+    "\n",
+    "# Create summary table for annual avg values\n",
+    "annual_table = pd.DataFrame(annual_avg)\n",
+    "\n",
+    "# Create summary table for period avg values\n",
+    "period_table = pd.DataFrame(period_avg).pivot_table(index=[\"scenario\", \"period\"],columns=\"variable\",values=\"value\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "24b4c670-e207-4b8d-9e94-7ccb545d185f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Prepare historical data\n",
+    "\n",
+    "def load_hist(start_year, end_year):\n",
+    "\n",
+    "    forcing_data_hist = {}\n",
+    "    scenario = \"historical\"\n",
+    "    forcing_data_hist[scenario] = {}\n",
+    "    annual_avg = []\n",
+    "\n",
+    "    for var_name in var_names:\n",
+    "\n",
+    "        merged_data_list = []\n",
+    "    \n",
+    "        forcing_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / scenario / f\"CMIP6-{start_year}-{end_year}\" / f\"combined_CMIP6_{start_year}_{end_year}_{var_name}.nc\"\n",
+    "\n",
+    "        # Load file as dataset\n",
+    "        ds = xr.open_dataset(forcing_file)\n",
+    "\n",
+    "        # Load file as array\n",
+    "        da = ds[var_name]\n",
+    "\n",
+    "        # Convert to series \n",
+    "        series = pd.Series(data=da.values.squeeze(),index=pd.to_datetime(da[\"time\"].values).normalize(),name=var_name)\n",
+    "\n",
+    "        # Convert pr and evap from km^2/s to mm^2/day\n",
+    "        if var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "            series = series * 86400\n",
+    "            annual = series.groupby(series.index.year).sum()\n",
+    "\n",
+    "        # Convert temp from Kelvin to Celcius\n",
+    "        elif var_name == \"tas\":\n",
+    "            series = series - 273.15\n",
+    "            annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "        elif var_name == \"rsds\":\n",
+    "            annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "        # Save for merged time series\n",
+    "        merged_data_list.append(series)\n",
+    "\n",
+    "        # Save annual values\n",
+    "        for year, annual_value in annual.items():\n",
+    "\n",
+    "            annual_avg.append({\n",
+    "                \"scenario\": scenario,\n",
+    "                \"period\": f\"{start_year}-{end_year}\",\n",
+    "                \"year\": year,\n",
+    "                \"variable\": var_name,\n",
+    "                \"value\": annual_value})\n",
+    "\n",
+    "        # Merge period into one series\n",
+    "        merged_data = pd.concat(merged_data_list)\n",
+    "        merged_data = merged_data[~merged_data.index.duplicated(keep=\"first\")]\n",
+    "        merged_data = merged_data.sort_index()\n",
+    "\n",
+    "        forcing_data_hist[scenario][var_name] = merged_data\n",
+    "            \n",
+    "    annual_hist_table = pd.DataFrame(annual_avg)\n",
+    "    \n",
+    "    return annual_hist_table, forcing_data_hist"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "e09d0416-6e0d-4ad4-850a-3f5a2bdcf860",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>period</th>\n",
+       "      <th>year</th>\n",
+       "      <th>variable</th>\n",
+       "      <th>value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1989</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>2.562430</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1990</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>1.319359</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1991</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>1.052132</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>0.776736</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1993</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>1.499663</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     scenario     period  year variable     value\n",
+       "0  historical  1989-2014  1989      tas  2.562430\n",
+       "1  historical  1989-2014  1990      tas  1.319359\n",
+       "2  historical  1989-2014  1991      tas  1.052132\n",
+       "3  historical  1989-2014  1992      tas  0.776736\n",
+       "4  historical  1989-2014  1993      tas  1.499663"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "annual_hist_table,forcing_data_hist = load_hist(start_year=1989,end_year=2014)\n",
+    "\n",
+    "annual_hist_table.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "956dae57-790b-4a00-a774-0ed954aa711c",
+   "metadata": {},
+   "source": [
+    "## 3. Period forcing avg table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "5c6faa8a-8fb7-4e20-8330-267ac0fde9a0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_period_forcing_table(annual_table):\n",
+    "\n",
+    "    period_forcing_table = (annual_table.groupby([\"scenario\", \"period\", \"variable\"])[\"value\"].mean().reset_index())\n",
+    "\n",
+    "    period_forcing_table = period_forcing_table.pivot_table(index=[\"scenario\", \"period\"], columns=\"variable\", values=\"value\")\n",
+    "\n",
+    "    return period_forcing_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e9310e49-7987-4011-93b2-7bfe02c20198",
+   "metadata": {},
+   "source": [
+    "*Table 9: 25 year average forcing data values for future climate scenarios.*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "7ab38b92-8e8b-4447-a0a1-25fc7e5e8cda",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>evspsblpot</th>\n",
+       "      <th>pr</th>\n",
+       "      <th>rsds</th>\n",
+       "      <th>tas</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>scenario</th>\n",
+       "      <th>period</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">ssp126</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <td>621.1</td>\n",
+       "      <td>633.9</td>\n",
+       "      <td>138.5</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2050-2075</th>\n",
+       "      <td>625.8</td>\n",
+       "      <td>630.1</td>\n",
+       "      <td>138.7</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2075-2099</th>\n",
+       "      <td>621.5</td>\n",
+       "      <td>645.3</td>\n",
+       "      <td>138.2</td>\n",
+       "      <td>2.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">ssp245</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <td>628.0</td>\n",
+       "      <td>623.0</td>\n",
+       "      <td>139.5</td>\n",
+       "      <td>2.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2050-2075</th>\n",
+       "      <td>632.7</td>\n",
+       "      <td>637.3</td>\n",
+       "      <td>138.3</td>\n",
+       "      <td>3.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2075-2099</th>\n",
+       "      <td>635.6</td>\n",
+       "      <td>659.8</td>\n",
+       "      <td>137.8</td>\n",
+       "      <td>3.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">ssp370</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <td>623.4</td>\n",
+       "      <td>640.5</td>\n",
+       "      <td>138.5</td>\n",
+       "      <td>2.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2050-2075</th>\n",
+       "      <td>636.3</td>\n",
+       "      <td>650.3</td>\n",
+       "      <td>136.7</td>\n",
+       "      <td>4.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2075-2099</th>\n",
+       "      <td>656.9</td>\n",
+       "      <td>645.7</td>\n",
+       "      <td>136.6</td>\n",
+       "      <td>5.4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "variable            evspsblpot     pr   rsds  tas\n",
+       "scenario period                                  \n",
+       "ssp126   2025-2050       621.1  633.9  138.5  2.5\n",
+       "         2050-2075       625.8  630.1  138.7  3.0\n",
+       "         2075-2099       621.5  645.3  138.2  2.7\n",
+       "ssp245   2025-2050       628.0  623.0  139.5  2.7\n",
+       "         2050-2075       632.7  637.3  138.3  3.6\n",
+       "         2075-2099       635.6  659.8  137.8  3.6\n",
+       "ssp370   2025-2050       623.4  640.5  138.5  2.7\n",
+       "         2050-2075       636.3  650.3  136.7  4.4\n",
+       "         2075-2099       656.9  645.7  136.6  5.4"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "period_forcing_table = round(create_period_forcing_table(annual_table), 1)\n",
+    "period_forcing_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2a61199-ced1-4957-b77e-d91a49770d1a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "period_forcing_table = round(create_period_forcing_table(annual_table), 1)\n",
+    "\n",
+    "period_forcing_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "510ade0c-1910-4ac1-b9f4-2414062c18ec",
+   "metadata": {},
+   "source": [
+    "## 4. Yearly forcing avg graph"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "11a82ee9-53a5-415b-910b-29ea9a805791",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_annual_forcing_variable(annual_forcing_table, var_name):\n",
+    "\n",
+    "    # Combine historical and scenarios\n",
+    "    annual_forcing_table_all = pd.concat([annual_hist_table, annual_forcing_table],ignore_index=True)\n",
+    "    data = annual_forcing_table_all[annual_forcing_table_all[\"variable\"] == var_name]\n",
+    "    \n",
+    "    plt.figure(figsize=(9, 5))\n",
+    "    \n",
+    "    # Loop through scenarios\n",
+    "    for scenario in scenarios_new:\n",
+    "\n",
+    "        # Extract one scenario and colour \n",
+    "        scenario_data = data[data[\"scenario\"] == scenario]\n",
+    "        colour = colours[scenario]\n",
+    "\n",
+    "        # Plot historical \n",
+    "        if scenario == \"historical\":\n",
+    "            \n",
+    "            # Plot yearly average \n",
+    "            plt.plot(scenario_data[\"year\"], scenario_data[\"value\"], color=colour, linewidth=0.3, label=scenario)\n",
+    "\n",
+    "            x = scenario_data[\"year\"].values\n",
+    "            y = scenario_data[\"value\"].values\n",
+    "\n",
+    "            # Polyfit method for making trendline function\n",
+    "            slope, intercept = np.polyfit(x, y, 1)\n",
+    "            trend = slope * x + intercept\n",
+    "\n",
+    "            # Plot trendline\n",
+    "            plt.plot(x,trend,linestyle=\"--\",color=colour)\n",
+    "\n",
+    "        # Plot other scenarios\n",
+    "        else:\n",
+    "\n",
+    "            # Plot yearly average\n",
+    "            plt.plot(scenario_data[\"year\"], scenario_data[\"value\"], alpha=0.3, color=colour, label=scenario)\n",
+    "\n",
+    "        # Look at each 25 year period\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            # Define period range\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            # Adjust data to fit period range\n",
+    "            period_data = scenario_data[\n",
+    "            (scenario_data[\"year\"] >= start_year) & \n",
+    "            (scenario_data[\"year\"] <= end_year)]\n",
+    "\n",
+    "            # Plot trend line over each 25 year period\n",
+    "            if len(period_data) > 1:\n",
+    "\n",
+    "                x = period_data[\"year\"].values\n",
+    "                y = period_data[\"value\"].values\n",
+    "\n",
+    "                # Polyfit method for making trendline function\n",
+    "                slope, intercept = np.polyfit(x, y, 1)\n",
+    "                trend = slope * x + intercept\n",
+    "\n",
+    "                # Plot trendline\n",
+    "                plt.plot(x,trend,linestyle=\"--\",color=colour)\n",
+    "\n",
+    "    # Define titles and labels based on var_name\n",
+    "    if var_name == \"pr\":\n",
+    "        ylabel = \"Annual precipitation (mm/year)\"\n",
+    "        title = \"Annual precipitation in LAR basin by climate scenario\"\n",
+    "\n",
+    "    elif var_name == \"evspsblpot\":\n",
+    "        ylabel = \"Annual potential evaporation (mm/year)\"\n",
+    "        title = \"Annual potential evaporation in LAR basin by climate scenario\"\n",
+    "\n",
+    "    elif var_name == \"tas\":\n",
+    "        ylabel = \"Annual mean temperature increase (°C)\"\n",
+    "        title = \"Annual mean temperature in LAR basin by climate scenario\"\n",
+    "\n",
+    "    elif var_name == \"rsds\":\n",
+    "        ylabel = \"Annual mean shortwave radiation (W/m²)\"\n",
+    "        title = \"Annual mean shortwave radiation in LAR basin by climate scenario\"\n",
+    "\n",
+    "    plt.xlabel(\"Year\")\n",
+    "    plt.ylabel(ylabel)\n",
+    "    plt.title(title)\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "5266e2f6-809c-4af8-ae55-98b52e4afe3e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Figure <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22</span>: pr-time series for future climate scenarios between <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span> and historical CMIP6 forcings between \n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1989</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Figure \u001b[1;36m22\u001b[0m: pr-time series for future climate scenarios between \u001b[1;36m2025\u001b[0m-\u001b[1;36m2099\u001b[0m and historical CMIP6 forcings between \n",
+       "\u001b[1;36m1989\u001b[0m-\u001b[1;36m2014\u001b[0m.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Figure <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">23</span>: tas-time series for future climate scenarios between <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span> and historical CMIP6 forcings between \n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1989</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Figure \u001b[1;36m23\u001b[0m: tas-time series for future climate scenarios between \u001b[1;36m2025\u001b[0m-\u001b[1;36m2099\u001b[0m and historical CMIP6 forcings between \n",
+       "\u001b[1;36m1989\u001b[0m-\u001b[1;36m2014\u001b[0m.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Figure <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24</span>: rsds-time series for future climate scenarios between <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span> and historical CMIP6 forcings between \n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1989</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Figure \u001b[1;36m24\u001b[0m: rsds-time series for future climate scenarios between \u001b[1;36m2025\u001b[0m-\u001b[1;36m2099\u001b[0m and historical CMIP6 forcings between \n",
+       "\u001b[1;36m1989\u001b[0m-\u001b[1;36m2014\u001b[0m.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Figure <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25</span>: evspsblpot-time series for future climate scenarios between <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span> and historical CMIP6 forcings \n",
+       "between <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1989</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Figure \u001b[1;36m25\u001b[0m: evspsblpot-time series for future climate scenarios between \u001b[1;36m2025\u001b[0m-\u001b[1;36m2099\u001b[0m and historical CMIP6 forcings \n",
+       "between \u001b[1;36m1989\u001b[0m-\u001b[1;36m2014\u001b[0m.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Define figure number for first figure\n",
+    "n = 22\n",
+    "\n",
+    "# Define var names\n",
+    "vars = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "# Run function to display plots for each var_name in vars\n",
+    "for i in range(len(vars)):\n",
+    "    plot_annual_forcing_variable(annual_table, vars[i])\n",
+    "    print(f\"Figure {n + i}: {vars[i]}-time series for future climate scenarios between 2025-2099 and historical CMIP6 forcings between 1989-2014.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68793e28-0a37-4d24-bdbe-1cd63bbbd039",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "96e43fcd-cb94-4ec2-bb7f-3af180989e7e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_F_ERA5_Forcings_Generation.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_F_ERA5_Forcings_Generation.ipynb
new file mode 100644
index 00000000..f50dabf5
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_F_ERA5_Forcings_Generation.ipynb
@@ -0,0 +1,897 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e91181a8-c60f-456f-80cc-3923bf7c6a43",
+   "metadata": {},
+   "source": [
+    "# ERA5 Data generation & merging \n",
+    "\n",
+    "ERA5 data will be generated from 1970-2025, loaded and merged into one file"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "680410be-715a-4678-a4e3-c1141939241e",
+   "metadata": {},
+   "source": [
+    "## Start-up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "7ef3318e-968e-418e-bf4c-a8936aade9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# general python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "#niceties\n",
+    "from rich import print\n",
+    "\n",
+    "import yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "f7ff029b-ee4b-4fe2-b5d5-bf768b626989",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "cc4de849-39a5-40e6-9f4a-865da369e8b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'OBS6'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/data/shared/climate-data/obs6'</span><span style=\"font-weight: bold\">)]</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'default'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/data/shared/climate-data'</span><span style=\"font-weight: bold\">)]</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/.esmvaltool/downloads/CMIP6'</span><span style=\"font-weight: bold\">)]</span>\n",
+       "<span style=\"font-weight: bold\">}</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\n",
+       "    \u001b[32m'OBS6'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/data/shared/climate-data/obs6'\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+       "    \u001b[32m'default'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/data/shared/climate-data'\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+       "    \u001b[32m'CMIP6'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/.esmvaltool/downloads/CMIP6'\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'CMIP3'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP5'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CORDEX'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'obs4MIPs'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span><span style=\"font-weight: bold\">}</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\u001b[32m'CMIP3'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'CMIP5'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'CMIP6'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'CORDEX'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'obs4MIPs'\u001b[0m: \u001b[32m'ESGF'\u001b[0m\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Fix ERA5 config error\n",
+    "from esmvalcore.config import CFG   # older: from esmvalcore.experimental import CFG\n",
+    "from pathlib import Path\n",
+    "home = Path.home()\n",
+    "OBS6 = Path('/data/shared/climate-data/obs6')\n",
+    "default = Path('/data/shared/climate-data')\n",
+    "CMIP_path = Path(f'{str(home)}/.esmvaltool/downloads/CMIP6')\n",
+    "CFG['rootpath'] = {'OBS6': [OBS6], 'default': [default], 'CMIP6': [CMIP_path]}\n",
+    "print(CFG['rootpath'])\n",
+    "print(CFG['drs'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74c8c15e-8cab-4e1a-b6eb-c9c165d8c051",
+   "metadata": {},
+   "source": [
+    "### Define range & forcing paths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "b2343410-2713-4089-ae42-dad37b457c41",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ERA5-1989-1994</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/\u001b[0m\u001b[95mERA5-1989-1994\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1989</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m1989\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2014\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining period range\n",
+    "# periods = [\n",
+    "#     [1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020],\n",
+    "#     [1974, 1979, 1984, 1989, 1994, 1999, 2004, 2009, 2014, 2019, 2024]]\n",
+    "\n",
+    "# For calibration 1:\n",
+    "# periods = [\n",
+    "#     [1990, 1995, 2000, 2005, 2010],\n",
+    "#     [1994, 1999, 2004, 2009, 2017]]\n",
+    "\n",
+    "# For calibration 2:\n",
+    "# periods = [\n",
+    "#     [1999, 2005, 2010, 2018],\n",
+    "#     [2004, 2009, 2017, 2019]]\n",
+    "\n",
+    "# For validation 1:\n",
+    "# periods = [\n",
+    "#     [2018, 2022],\n",
+    "#     [2021, 2024]]\n",
+    "\n",
+    "# For validation 2:\n",
+    "# periods = [\n",
+    "#     [2019, 2022],\n",
+    "#     [2021, 2024]]\n",
+    "\n",
+    "# For CMIP trial:\n",
+    "# periods = [\n",
+    "#     [1995, 2000, 2005, 2010],\n",
+    "#     [1999, 2004, 2009, 2014]]\n",
+    "\n",
+    "# For CMIP trial 2\n",
+    "# periods = [\n",
+    "#     [1970, 1975, 1980, 1985, 1990, 1995],\n",
+    "#     [1974, 1979, 1984, 1989, 1994, 1999]]\n",
+    "\n",
+    "periods = [\n",
+    "    [1989, 1995, 2000, 2005, 2010],\n",
+    "    [1994, 1999, 2004, 2009, 2014]]\n",
+    "\n",
+    "folder_names = []\n",
+    "forcing_paths = {}\n",
+    "\n",
+    "# Generate file names & paths\n",
+    "for i in range(len(periods[0])):\n",
+    "    start_year = periods[0][i]\n",
+    "    end_year = periods[1][i]\n",
+    "    \n",
+    "    folder_name = f'ERA5-{start_year}-{end_year}'                         # Add -cal or -val for cal and val folder name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / folder_name\n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5\" / folder_name\n",
+    "\n",
+    "    folder_names.append(folder_name)\n",
+    "    forcing_paths[folder_name] = forcing_path\n",
+    "\n",
+    "    forcing_path.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "# Call path test\n",
+    "print(forcing_paths[folder_names[0]])\n",
+    "\n",
+    "start_year = periods[0][0]\n",
+    "end_year = periods[1][-1]\n",
+    "\n",
+    "print(start_year)\n",
+    "print(end_year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "619dd21a-0646-4bae-a71b-935f1fca8c04",
+   "metadata": {},
+   "source": [
+    "### Generate ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "cbc7b2b6-88ee-4e7f-b37c-39eaf878c075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1989</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1994</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished ERA5-\u001b[1;36m1989\u001b[0m-\u001b[1;36m1994\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1995</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1999</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m1995\u001b[0m-\u001b[1;36m1999\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2000</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2004</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m2000\u001b[0m-\u001b[1;36m2004\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2005</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2009</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m2005\u001b[0m-\u001b[1;36m2009\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2010</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m2010\u001b[0m-\u001b[1;36m2014\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Shapefile path\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# Generate forcing data\n",
+    "# for i in range(1):\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Change start year to start time so ERA5 can interpret it\n",
+    "    start_time_ERA5 = f'{periods[0][i]}-01-01T00:00:00Z'\n",
+    "    end_time_ERA5 = f'{periods[1][i]}-12-31T00:00:00Z'\n",
+    "\n",
+    "    # Skip if folder is not empty to prevent errors\n",
+    "    if any(forcing_paths[folder_names[i]].iterdir()):\n",
+    "        print(f\"Skipping {folder_names[i]} because the folder is not empty.\")\n",
+    "        continue\n",
+    "\n",
+    "    # Load forcings\n",
+    "    ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "        dataset=\"ERA5\",\n",
+    "        start_time=start_time_ERA5,\n",
+    "        end_time=end_time_ERA5,\n",
+    "        shape=shape_file,\n",
+    "        directory=forcing_paths[folder_names[i]])\n",
+    "\n",
+    "    # I need info because my patience is limited\n",
+    "    print(f\"Finished {folder_names[i]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91242ae4-3d21-4d18-815f-5cc986d5961e",
+   "metadata": {},
+   "source": [
+    "### Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "f8e8ac64-fee5-4602-a1f1-90b8fb14c2b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1989-1994'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1995-1999'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-2000-2004'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-2005-2009'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-2010-2014'</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[32m'ERA5-1989-1994'\u001b[0m, \u001b[32m'ERA5-1995-1999'\u001b[0m, \u001b[32m'ERA5-2000-2004'\u001b[0m, \u001b[32m'ERA5-2005-2009'\u001b[0m, \u001b[32m'ERA5-2010-2014'\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "LumpedMakkinkForcing(start_time='1989-01-01T00:00:00Z', end_time='1994-12-31T00:00:00Z', directory=PosixPath('/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/work/diagnostic/script'), shape=PosixPath('/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/work/diagnostic/script/07DA001_basin.shp'), filenames={'pr': 'OBS6_ERA5_reanaly_1_day_pr_1989-1994.nc', 'tas': 'OBS6_ERA5_reanaly_1_day_tas_1989-1994.nc', 'rsds': 'OBS6_ERA5_reanaly_1_day_rsds_1989-1994.nc', 'evspsblpot': 'Derived_Makkink_evspsblpot.nc'})"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ERA5_forcings = {}\n",
+    "\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Create new path to find relevant files in the folder\n",
+    "    directory_new = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\"\n",
+    "    \n",
+    "    # Load forcings\n",
+    "    ERA5_forcings[folder_names[i]] = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=directory_new)\n",
+    "\n",
+    "# Test to see if it works\n",
+    "print(folder_names)\n",
+    "ERA5_forcings[folder_names[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8eddb25-06e3-4702-87e8-258aeda27a15",
+   "metadata": {},
+   "source": [
+    "### Merge ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "1cb12aa2-4b4c-4108-a5c9-2d8156cdecfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to seperate files based on file names and combine same file names from different folders\n",
+    "def combine_variable(var_name):\n",
+    "    datasets = []\n",
+    "\n",
+    "    for i in range(len(folder_names)):\n",
+    "\n",
+    "        if var_name == \"evspsblpot\":\n",
+    "            file_name = \"Derived_Makkink_evspsblpot.nc\"\n",
+    "        else:\n",
+    "            file_name = f\"OBS6_ERA5_reanaly_1_day_{var_name}_{periods[0][i]}-{periods[1][i]}.nc\"\n",
+    "\n",
+    "        directory = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\" / file_name\n",
+    "\n",
+    "        print(f\"Loading {directory}\")\n",
+    "\n",
+    "        datasets.append(xr.open_dataset(directory))\n",
+    "\n",
+    "    combined = xr.concat(datasets, dim=\"time\")\n",
+    "    return combined"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "b21fe2e4-478a-4e0b-9f1f-a40316e22018",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1989-1994.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1989-1994.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1995-1999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1995-1999.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_2000-2004.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_2000-2004.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_2005-2009.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_2005-2009.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_2010-2014.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_2010-2014.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1989-1994.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1989-1994.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1995-1999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1995-1999.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_2000-2004.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_2000-2004.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_2005-2009.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_2005-2009.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_2010-2014.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_2010-2014.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1989-1994.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1989-1994.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1995-1999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1995-1999.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_2000-2004.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_2000-2004.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_2005-2009.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_2005-2009.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_2010-2014.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_2010-2014.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Running function for various file name types\n",
+    "combined_variables = {}\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "# combined_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / f'ERA5-{periods[0][0]}-{periods[1][-1]}'\n",
+    "combined_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5\" / f'ERA5-{start_year}-{end_year}'\n",
+    "combined_path.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "    combined_variables[var_names[i]] = combine_variable(var_names[i])\n",
+    "    combined_variables[var_names[i]].to_netcdf(combined_path / f'combined_ERA5_{start_year}_{end_year}_{var_names[i]}.nc')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a439e818-0aa8-4e92-a189-fde70016a911",
+   "metadata": {},
+   "source": [
+    "### Create YAML file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "e60b3316-e100-4af9-a36d-fad721ef6e02",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create yaml\n",
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{start_year}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{end_year}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_ERA5_{start_year}_{end_year}_pr.nc\",\n",
+    "        \"tas\": f\"combined_ERA5_{start_year}_{end_year}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_ERA5_{start_year}_{end_year}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_ERA5_{start_year}_{end_year}_evspsblpot.nc\"}}\n",
+    "\n",
+    "# Save the YAML file\n",
+    "yaml_file_path = combined_path / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "10ff50bf-b6e7-4033-9682-3e25d01ecd26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1989-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">ngs/ERA5/ERA5-1989-2014'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">s/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1989_2014_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1989_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1989_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1989_2014_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1989-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci\u001b[0m\n",
+       "\u001b[32mngs/ERA5/ERA5-1989-2014'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile\u001b[0m\n",
+       "\u001b[32ms/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1989_2014_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1989_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1989_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1989_2014_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ERA5_combined_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=combined_path)\n",
+    "print(ERA5_combined_forcing)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_G_CMIP6_Forcings_Generation.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_G_CMIP6_Forcings_Generation.ipynb
new file mode 100644
index 00000000..ae645d83
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Appendix_G_CMIP6_Forcings_Generation.ipynb
@@ -0,0 +1,913 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e91181a8-c60f-456f-80cc-3923bf7c6a43",
+   "metadata": {},
+   "source": [
+    "# CMIP6 Data generation & merging \n",
+    "\n",
+    "CMIP6 data will be generated from 1995-2014, loaded and merged into one file\n",
+    "\n",
+    "**Note: Depending on if you want to run historical, or an ssp, changes you need to make are:**\n",
+    "1. Cell 5: Select scenario\n",
+    "2. Cell 6: Define period"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "680410be-715a-4678-a4e3-c1141939241e",
+   "metadata": {},
+   "source": [
+    "## Start-up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "7ef3318e-968e-418e-bf4c-a8936aade9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# general python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "#niceties\n",
+    "from rich import print\n",
+    "\n",
+    "import yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f7ff029b-ee4b-4fe2-b5d5-bf768b626989",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "OSError",
+     "evalue": "[Errno 5] Input/output error: '/data/shared/observation/grdc/dailies'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# General eWaterCycle\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mewatercycle\u001b[39;00m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mewatercycle\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodels\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mewatercycle\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mforcing\u001b[39;00m\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/ewatercycle/__init__.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"ewatercycle package.\"\"\"\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfig\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m CFG \u001b[38;5;28;01mas\u001b[39;00m CFG\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mversion\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m __version__ \u001b[38;5;28;01mas\u001b[39;00m __version__\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/ewatercycle/config/__init__.py:321\u001b[0m\n\u001b[1;32m    317\u001b[0m _SOURCES \u001b[38;5;241m=\u001b[39m (USER_HOME_CONFIG, SYSTEM_CONFIG)\n\u001b[1;32m    319\u001b[0m USER_CONFIG \u001b[38;5;241m=\u001b[39m _find_user_config(_SOURCES)\n\u001b[0;32m--> 321\u001b[0m CFG \u001b[38;5;241m=\u001b[39m \u001b[43mConfiguration\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_load_user_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43mUSER_CONFIG\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mif\u001b[39;00m USER_CONFIG \u001b[38;5;28;01melse\u001b[39;00m Configuration()\n\u001b[1;32m    322\u001b[0m \u001b[38;5;124;03m\"\"\"eWaterCycle configuration object.\u001b[39;00m\n\u001b[1;32m    323\u001b[0m \n\u001b[1;32m    324\u001b[0m \u001b[38;5;124;03mThe configuration is loaded from:\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    341\u001b[0m \u001b[38;5;124;03m    # apptainer pull docker://ewatercycle/wflow-grpc4bmi:2020.1.1\u001b[39;00m\n\u001b[1;32m    342\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/ewatercycle/config/__init__.py:197\u001b[0m, in \u001b[0;36mConfiguration._load_user_config\u001b[0;34m(cls, filename)\u001b[0m\n\u001b[1;32m    195\u001b[0m mapping \u001b[38;5;241m=\u001b[39m _read_config_file(filename)\n\u001b[1;32m    196\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 197\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mConfiguration\u001b[49m\u001b[43m(\u001b[49m\u001b[43mewatercycle_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmapping\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    198\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ValidationError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    199\u001b[0m     \u001b[38;5;66;03m# Append filename to error locs\u001b[39;00m\n\u001b[1;32m    200\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m error \u001b[38;5;129;01min\u001b[39;00m e\u001b[38;5;241m.\u001b[39merrors():\n",
+      "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/pydantic/types.py:1282\u001b[0m, in \u001b[0;36mPathType.validate_directory\u001b[0;34m(path, _)\u001b[0m\n\u001b[1;32m   1280\u001b[0m \u001b[38;5;129m@staticmethod\u001b[39m\n\u001b[1;32m   1281\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mvalidate_directory\u001b[39m(path: Path, _: core_schema\u001b[38;5;241m.\u001b[39mValidationInfo) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Path:\n\u001b[0;32m-> 1282\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[43mpath\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mis_dir\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m   1283\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m path\n\u001b[1;32m   1284\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/pathlib.py:875\u001b[0m, in \u001b[0;36mPath.is_dir\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    871\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    872\u001b[0m \u001b[38;5;124;03mWhether this path is a directory.\u001b[39;00m\n\u001b[1;32m    873\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    874\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 875\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m S_ISDIR(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstat\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mst_mode)\n\u001b[1;32m    876\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    877\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _ignore_error(e):\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/pathlib.py:840\u001b[0m, in \u001b[0;36mPath.stat\u001b[0;34m(self, follow_symlinks)\u001b[0m\n\u001b[1;32m    835\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mstat\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m, follow_symlinks\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[1;32m    836\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    837\u001b[0m \u001b[38;5;124;03m    Return the result of the stat() system call on this path, like\u001b[39;00m\n\u001b[1;32m    838\u001b[0m \u001b[38;5;124;03m    os.stat() does.\u001b[39;00m\n\u001b[1;32m    839\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 840\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstat\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfollow_symlinks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfollow_symlinks\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[0;31mOSError\u001b[0m: [Errno 5] Input/output error: '/data/shared/observation/grdc/dailies'"
+     ]
+    }
+   ],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "df3c38b4-7757-475c-a670-e7a06cc53955",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choose what you want to run:\n",
+    "Scenario = \"ssp370\"    # Options: historical, ssp119, ssp126, ssp245, ssp,370, ssp585"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74c8c15e-8cab-4e1a-b6eb-c9c165d8c051",
+   "metadata": {},
+   "source": [
+    "### Define range & forcing paths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "b2343410-2713-4089-ae42-dad37b457c41",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6-20</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">25-2030</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/\u001b[0m\u001b[95mCMIP6-20\u001b[0m\n",
+       "\u001b[95m25-2030\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2025\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining period range\n",
+    "\n",
+    "# For CMIP trial:\n",
+    "# periods = [\n",
+    "#     [1989, 1995, 2000, 2005, 2010],\n",
+    "#     [1994, 1999, 2004, 2009, 2014]\n",
+    "# ]\n",
+    "\n",
+    "# periods = [\n",
+    "#     [1970, 1975, 1980, 1985, 1990, 1995],\n",
+    "#     [1974, 1979, 1984, 1989, 1994, 1999]\n",
+    "# ]\n",
+    "\n",
+    "# Future projections 2025-2050:\n",
+    "periods = [\n",
+    "    [2025, 2031, 2036, 2041, 2046],\n",
+    "    [2030, 2035, 2040, 2045, 2050]\n",
+    "]\n",
+    "\n",
+    "# Future projections 2050-2075:\n",
+    "# periods = [\n",
+    "#     [2050, 2056, 2061, 2066, 2071],\n",
+    "#     [2055, 2060, 2065, 2070, 2075]\n",
+    "# ]\n",
+    "\n",
+    "# Future projections 2075-2099:\n",
+    "# periods = [\n",
+    "#     [2075, 2081, 2086, 2091, 2096],\n",
+    "#     [2080, 2085, 2090, 2095, 2099]\n",
+    "# ]\n",
+    "\n",
+    "\n",
+    "folder_names = []\n",
+    "forcing_paths = {}\n",
+    "\n",
+    "# Generate file names & paths\n",
+    "for i in range(len(periods[0])):\n",
+    "    start_year = periods[0][i]\n",
+    "    end_year = periods[1][i]\n",
+    "    \n",
+    "    folder_name = f'CMIP6-{start_year}-{end_year}'                        \n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / folder_name\n",
+    "\n",
+    "    folder_names.append(folder_name)\n",
+    "    forcing_paths[folder_name] = forcing_path\n",
+    "\n",
+    "    forcing_path.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "# Call path test\n",
+    "print(forcing_paths[folder_names[0]])\n",
+    "\n",
+    "start_year = periods[0][0]\n",
+    "end_year = periods[1][-1]\n",
+    "\n",
+    "print(start_year)\n",
+    "print(end_year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "619dd21a-0646-4bae-a71b-935f1fca8c04",
+   "metadata": {},
+   "source": [
+    "### Generate CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "cbc7b2b6-88ee-4e7f-b37c-39eaf878c075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2030</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping CMIP6-\u001b[1;36m2025\u001b[0m-\u001b[1;36m2030\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2031</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2035</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2031\u001b[0m-\u001b[1;36m2035\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2036</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2040</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2036\u001b[0m-\u001b[1;36m2040\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2041</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2045</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2041\u001b[0m-\u001b[1;36m2045\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2046</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2046\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Shapefile path\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# Choose CMIP6 dataset\n",
+    "# CMIP_dataset = {'dataset': 'MPI-ESM1-2-HR', 'project': 'CMIP6', 'grid' : 'gn', 'exp': Scenario, 'ensemble': 'r1i1p1f1'}\n",
+    "CMIP_dataset =  {'project': 'CMIP6', 'activity': 'ScenarioMIP', 'exp': Scenario, 'mip': 'day', 'dataset': 'MPI-ESM1-2-HR', 'ensemble': 'r1i1p1f1', 'institute': 'DKRZ', 'grid': 'gn'}\n",
+    "\n",
+    "# Generate forcing data\n",
+    "# for i in range(1):\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Change start year to start time so ERA5 can interpret it\n",
+    "    start_time_CMIP = f'{periods[0][i]}-01-01T00:00:00Z'\n",
+    "    end_time_CMIP = f'{periods[1][i]}-12-31T00:00:00Z'\n",
+    "\n",
+    "    # Skip if folder is not empty to prevent errors\n",
+    "    if any(forcing_paths[folder_names[i]].iterdir()):\n",
+    "        print(f\"Skipping {folder_names[i]} because the folder is not empty.\")\n",
+    "        continue\n",
+    "\n",
+    "    # Load forcings\n",
+    "    CMIP_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "        dataset=CMIP_dataset,\n",
+    "        start_time=start_time_CMIP,\n",
+    "        end_time=end_time_CMIP,\n",
+    "        shape=shape_file,\n",
+    "        directory=forcing_paths[folder_names[i]]\n",
+    "    )\n",
+    "\n",
+    "    # I need info because my patience is limited\n",
+    "    print(f\"Finished {folder_names[i]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91242ae4-3d21-4d18-815f-5cc986d5961e",
+   "metadata": {},
+   "source": [
+    "### Load CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "f8e8ac64-fee5-4602-a1f1-90b8fb14c2b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2025-2030'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2031-2035'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2036-2040'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2041-2045'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2046-2050'</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[32m'CMIP6-2025-2030'\u001b[0m, \u001b[32m'CMIP6-2031-2035'\u001b[0m, \u001b[32m'CMIP6-2036-2040'\u001b[0m, \u001b[32m'CMIP6-2041-2045'\u001b[0m, \u001b[32m'CMIP6-2046-2050'\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "LumpedMakkinkForcing(start_time='2025-01-01T00:00:00Z', end_time='2030-12-31T00:00:00Z', directory=PosixPath('/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-2025-2030/work/diagnostic/script'), shape=PosixPath('/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-2025-2030/work/diagnostic/script/07DA001_basin.shp'), filenames={'pr': 'CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2025-2030.nc', 'tas': 'CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2025-2030.nc', 'rsds': 'CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2025-2030.nc', 'evspsblpot': 'Derived_Makkink_evspsblpot.nc'})"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "CMIP_forcings = {}\n",
+    "\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Create new path to find relevant files in the folder\n",
+    "    directory_new = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\"\n",
+    "    \n",
+    "    # Load forcings\n",
+    "    CMIP_forcings[folder_names[i]] = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=directory_new)\n",
+    "\n",
+    "# Test to see if it works\n",
+    "print(folder_names)\n",
+    "CMIP_forcings[folder_names[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8eddb25-06e3-4702-87e8-258aeda27a15",
+   "metadata": {},
+   "source": [
+    "### Merge CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "1cb12aa2-4b4c-4108-a5c9-2d8156cdecfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to seperate files based on file names and combine same file names from different folders\n",
+    "def combine_variable(var_name):\n",
+    "    datasets = []\n",
+    "\n",
+    "    for i in range(len(folder_names)):\n",
+    "\n",
+    "        if var_name == \"evspsblpot\":\n",
+    "            file_name = \"Derived_Makkink_evspsblpot.nc\"\n",
+    "        else:\n",
+    "            file_name = f\"CMIP6_MPI-ESM1-2-HR_day_{Scenario}_r1i1p1f1_{var_name}_gn_{periods[0][i]}-{periods[1][i]}.nc\"\n",
+    "\n",
+    "        directory = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\" / file_name\n",
+    "\n",
+    "        print(f\"Loading {directory}\")\n",
+    "\n",
+    "        datasets.append(xr.open_dataset(directory))\n",
+    "\n",
+    "    combined = xr.concat(datasets, dim=\"time\")\n",
+    "    return combined"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "b21fe2e4-478a-4e0b-9f1f-a40316e22018",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">25-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2025-2030.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m25-2030/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2025-2030.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">31-2035/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2031-2035.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m31-2035/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2031-2035.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">36-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2036-2040.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m36-2040/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2036-2040.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">41-2045/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2041-2045.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m41-2045/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2041-2045.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">46-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2046-2050.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m46-2050/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2046-2050.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">25-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2025-2030.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m25-2030/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2025-2030.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">31-2035/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2031-2035.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m31-2035/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2031-2035.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">36-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2036-2040.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m36-2040/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2036-2040.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">41-2045/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2041-2045.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m41-2045/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2041-2045.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">46-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2046-2050.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m46-2050/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2046-2050.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">25-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2025-2030.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m25-2030/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2025-2030.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">31-2035/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2031-2035.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m31-2035/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2031-2035.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">36-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2036-2040.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m36-2040/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2036-2040.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">41-2045/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2041-2045.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m41-2045/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2041-2045.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">46-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2046-2050.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m46-2050/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2046-2050.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">25-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m25-2030/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">31-2035/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m31-2035/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">36-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m36-2040/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">41-2045/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m41-2045/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">46-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m46-2050/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Running function for various file name types\n",
+    "combined_variables = {}\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "# combined_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f'CMIP6-{start_year}-{end_year}'\n",
+    "combined_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f'CMIP6-{start_year}-{end_year}'\n",
+    "combined_path.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "    combined_variables[var_names[i]] = combine_variable(var_names[i])\n",
+    "    combined_variables[var_names[i]].to_netcdf(combined_path / f'combined_CMIP6_{start_year}_{end_year}_{var_names[i]}.nc')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a439e818-0aa8-4e92-a189-fde70016a911",
+   "metadata": {},
+   "source": [
+    "### Create YAML file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "e60b3316-e100-4af9-a36d-fad721ef6e02",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create yaml\n",
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{start_year}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{end_year}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_CMIP6_{start_year}_{end_year}_pr.nc\",\n",
+    "        \"tas\": f\"combined_CMIP6_{start_year}_{end_year}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_CMIP6_{start_year}_{end_year}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_CMIP6_{start_year}_{end_year}_evspsblpot.nc\"\n",
+    "    }}\n",
+    "\n",
+    "# Save the YAML file\n",
+    "yaml_file_path = combined_path / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "10ff50bf-b6e7-4033-9682-3e25d01ecd26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2025-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2050-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">ngs/CMIP6/ssp370/CMIP6-2025-2050'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">s/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'2025-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2050-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci\u001b[0m\n",
+       "\u001b[32mngs/CMIP6/ssp370/CMIP6-2025-2050'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile\u001b[0m\n",
+       "\u001b[32ms/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "CMIP6_combined_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=combined_path)\n",
+    "print(CMIP6_combined_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "83a89024-510b-442f-adeb-8f9e0d07a77f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a8771eeb-24fc-4030-a653-1bafbfd45aec",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eb1f2d7f-6efb-4d2c-a892-45d5792a5ede",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6cb15558-ec6b-4d6c-b1fc-8a8843b617db",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Figures/HBV_Visualisation.jpg b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Figures/HBV_Visualisation.jpg
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+author: "Markus Hrachowitz"
+license: "Apache 2.0"
+date: "24-04-2026"
\ No newline at end of file
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Figures/Map_LARbasin.jpg b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Figures/Map_LARbasin.jpg
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+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Figures/Map_LARbasin.jpg.yml
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+author: "Aryal, S., Babel, M. S., Gupta, A., & Farjad, B."
+license: "CC-BY-4.0"
+date: "06-2024"
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+author: "DSI, LLC."
+license: "CC-BY-4.0"
+date: "14-09-2019"
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+author: "Siemens, K., Dibike, Y., Shrestha, R. R., & Prowse, T."
+license: "CC-BY-4.0"
+date: "24-02-2021"
\ No newline at end of file
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diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Figures/Workflow_diagram.jpg.yml b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Figures/Workflow_diagram.jpg.yml
new file mode 100644
index 00000000..328b466b
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Figures/Workflow_diagram.jpg.yml
@@ -0,0 +1,3 @@
+author: "Maxime de Bekker using ChatGPT"
+license: "Apache 2.0"
+date: "01-04-2026"
\ No newline at end of file
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Reference_list.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Reference_list.ipynb
new file mode 100644
index 00000000..8baa1c2c
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Report/Reference_list.ipynb
@@ -0,0 +1,107 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ee10651c-f7ea-45f3-ad19-4b47471132d0",
+   "metadata": {},
+   "source": [
+    "# Reference list"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d8acfec-6db0-4b51-b11e-f1b04a2760a0",
+   "metadata": {},
+   "source": [
+    "ADCS. (2026, April 28). Transportation and shipping. Athabasca Delta Community School. https://adcs.psd.ca/staff/shipping   \n",
+    "\n",
+    "Adam, A., Tucarro, B. J., & Cardinal, K. (2024, August 23). Environmental contamination in the vicinity of the dock in Fort Chipewyan. Transport Canada. https://tc.canada.ca/en/binder/august-27-2024-0   \n",
+    "\n",
+    "Alberta Environment and Parks. (2026). Athabasca River Conditions and Use - Alberta Environment. Government of Alberta. Retrieved April 27, 2026, from https://www.environment.alberta.ca/apps/OSEM/   \n",
+    "\n",
+    "Andrishak, R., Abarca, J. N., Wojtowicz, A., & Wicks, F. (2008). Freeze-up study on the lower Athabasca River (Alberta, Canada). ETDEWEB. Retrieved May 21, 2026, from https://www.iahr.org/library/infor?pid=26767  \n",
+    "\n",
+    "Aryal, S., Babel, M. S., Gupta, A., & Farjad, B. (2023). Assessment of hydrological baseline condition and its alteration in Athabasca River Basin, Canada. Journal of Hydrology Regional Studies, 53(22). https://doi.org/10.1016/j.ejrh.2024.101805   \n",
+    "\n",
+    "Athabasca Watershed Council. (2026, February 6). The Athabasca Watershed | Athabasca Watershed Council. https://athabascawatershed.ca/the-athabasca-watershed/  \n",
+    "\n",
+    "Athabasca University. (n.d.). About the Athabasca River Basin. Athabasca River Basin Research Institute, Athabasca University. Retrieved April 24, 2026, from https://arbri.athabascau.ca/About-the-Athabasca-River-basin/Index.php   \n",
+    "\n",
+    "Axelrod, J. (2015, October 14). Low Water Levels in the Athabasca River are a Preview of Future Problems for Alberta’s Tar Sands Industry. NRDC Expert Blog. https://www.nrdc.org/bio/josh-axelrod/low-water-levels-athabasca-river-are-preview-future-problems-albertas-tar-sands   \n",
+    "\n",
+    "Candler, C., Malone, M., & Firelight Group Research Cooperative. (2015). Addendum to MCFN Indigenous Knowledge and Use Report for TECK Frontier. In www.thefirelightgroup.com (pp. 20–23). https://ceaa-acee.gc.ca/050/documents/p65505/114502E.pdf   \n",
+    "\n",
+    "Candler, C., Olson, R., DeRoy, S., Firelight Group Research Cooperative, Athabasca Chipewyan First Nation, & Mikisew Cree First Nation. (2010). As long as the rivers flow: Athabasca River knowledge, use and change. https://s3-us-west-2.amazonaws.com/parkland-research-pdfs/aslongastheriversflow.pdf   \n",
+    "\n",
+    "Canada, T. (2020, February 7). Navigation study of the lower Athabasca River. Transport Canada. https://tc.canada.ca/en/marine/navigation-study-lower-athabasca-river \n",
+    "Canadian Red Cross. (n.d.). Fort McMurray and Area Floods. Retrieved May 21, 2026, from https://www.redcross.ca/in-your-community/alberta/major-responses/past-emergencies/fort-mcmurray-and-area-floods  \n",
+    "\n",
+    "Chernos, M., MacDonald, R. J., Nemeth, M. W., & Craig, J. R. (2020, September 11). Current and future projections of glacier contribution to streamflow in the upper Athabasca River Basin. Canadian Water Resources Journal / Revue Canadienne Des Ressources Hydriques, 45(4), 324–344. https://doi.org/10.1080/07011784.2020.1815587  \n",
+    "\n",
+    "DSI. (2019, September 14). Lower Athabasca River Water Quality and Toxics Modeling (Canada). https://dsi.llc/representative-projects/lower-athabasca-river-water-quality-modeling-canada/\n",
+    "Duc, L., & Sawada, Y. (2023). A signal-processing-based interpretation of the Nash–Sutcliffe efficiency. Hydrology and Earth System Sciences, 27(9), 1827–1839. https://doi.org/10.5194/hess-27-1827-2023  \n",
+    "\n",
+    "Ecosystem Classification Group. (2008). Taiga Shield. In Government of Canada. https://www.gov.nt.ca/sites/ecc/files/resources/taiga_shield_ecological_land_classification_report_0.pdf\n",
+    "eWaterCycle (n.d.). eWaterCycle About. Retrieved May 21, 2026, from https://www.ewatercycle.org/about.html   \n",
+    "\n",
+    "Faramarzi, M., Srinivasan, R., Iravani, M., Bladon, K. D., Abbaspour, K. C., Zehnder, A. J. B., & Goss, G. G. (2015). Setting up a hydrological model of Alberta: data discrimination analyses prior to calibration. Environmental Modelling & Software, 74. https://doi.org/10.1016/j.envsoft.2015.09.006  \n",
+    "\n",
+    "Government of Canada. (n.d.). Canadian Climate Normals 1991-2020 Data. Retrieved June 15, 2026, from https://climate.weather.gc.ca/climate_normals/results_1991_2020_e.html?searchType=stnName_1991&txtStationName_1991=Fort+McMurray&searchMethod=contains&txtCentralLatMin=0&txtCentralLatSec=0&txtCentralLongMin=0&txtCentralLongSec=0&climate_id=3062693&dispBack=1  \n",
+    "\n",
+    "Government of Canada. (2019, March 1). CMIP6 and Shared Socio-economic Pathways Overview. https://climate-scenarios.canada.ca/?page=cmip6-overview-notes  \n",
+    "\n",
+    "Government of Canada. (2026, March 9). Disclaimer for Hydrometric information - Water Level and Flow - Environment Canada. Retrieved May 21, 2026, from https://wateroffice.ec.gc.ca/report/historical_e.html?stn=07DA001   \n",
+    "\n",
+    "HEC-HMS. (n.d.). Calibration Summary Statistics. Retrieved May 21, 2026, from https://www.hec.usace.army.mil/confluence/hmsdocs/hmstrm/calibration/calibration-summary-statistics  \n",
+    "\n",
+    "Hrachowitz, M. & eWaterCycle. (n.d.). GitHub - eWaterCycle/HBV-bmi: BMI implementation of the BMI in a markov chain process using python. eWaterCycle. Retrieved May 21, 2026, from https://github.com/eWaterCycle/HBV-bmi  \n",
+    "\n",
+    "Kashyap, S., Kerkhoven, E., Islam, Z., Petty, A., & Depoe, S. (2022). Predicting navigability in the Lower Athabasca river system through numerical modelling. In Lecture notes in civil engineering (pp. 479–490). https://doi.org/10.1007/978-981-19-1065-4_40   \n",
+    "\n",
+    "Miguel’s Youtube Channel. (2026, April 26). Athabasca River south of Fort Mcmurray, April 26, 2026 [Video]. YouTube. https://www.youtube.com/watch?v=vfWEjK4YqaE  \n",
+    "\n",
+    "Mikisew Cree First Nation. (2016). Written brief of the Mikisew Cree First Nation to the Standing Committee on Transport, Infrastructure and Communities. https://www.ourcommons.ca/Content/Committee/421/TRAN/Brief/BR8708926/br-external/MikisewCreeFirstNation-e.pdf   \n",
+    "\n",
+    "Normand, G., & Bakx, K. (2018, December 25). Why Indigenous groups are tired of fighting oilsands development. CBC News. https://newsinteractives.cbc.ca/longform/drawing-a-line-in-the-oilsands-fight/   \n",
+    "\n",
+    "Nottawasaga Valley Conservation Authority. (2026, January 9). Ice Jams - the Nottawasaga Valley Conservation Authority. The Nottawasaga Valley Conservation Authority. https://www.nvca.on.ca/flooding/ice-jams/  \n",
+    "\n",
+    "Peters, D. L., Dibike, Y. B., Shudian, J., Monk, W. A., & Baird, D. J. (2023). Effects of climate change on navigability indicators of the Lower Athabasca River, Canada. Water, 15(7). https://doi.org/10.3390/w15071373\n",
+    "Siemens, K., Dibike, Y., Shrestha, R. R., & Prowse, T. (2021). Runoff projection from an alpine watershed in western Canada: application of a snowmelt runoff model. Water, 13(9). https://doi.org/10.3390/w13091199  \n",
+    "\n",
+    "Transport Canada, & Carver, M. (2020). Transport Canada Navigational Study of the Lower Athabasca River – Outcomes and Technical review. Aqua Environmental Associates. https://registrydocumentsprd.blob.core.windows.net/commentsblob/project-80521/comment-54376/TC-nav-study_review-FINAL.pdf  \n",
+    "\n",
+    "Van Vuuren, D. P., O’Neill, B. C., Tebaldi, C., Sanderson, B. M., Chini, L. P., Friedlingstein, P., Hasegawa, T., Riahi, K., Govindasamy, B., Bauer, N., Eyring, V., Fall, C. M. N., Frieler, K., Gidden, M. J., Gohar, L. K., Högner, A., Jones, A. D., Kikstra, J., King, A., . . . Ziehn, T. (2026). The Scenario Model Intercomparison Project for CMIP7 (ScenarioMIP-CMIP7). 1, 19(7). https://doi.org/10.5194/gmd-19-2627-2026"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c9503c71-cd04-436c-a561-be847a148976",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/07DA001_discharge_daily_withoutmissing.csv b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/07DA001_discharge_daily_withoutmissing.csv
new file mode 100644
index 00000000..f253723b
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/07DA001_discharge_daily_withoutmissing.csv
@@ -0,0 +1,24744 @@
+Daily Discharge (m3/s) (PARAM = 1) and Daily Water Level (m) (PARAM = 2)
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diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Draft notebooks/Calibration file deletion.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Draft notebooks/Calibration file deletion.ipynb
new file mode 100644
index 00000000..e72b2b28
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Draft notebooks/Calibration file deletion.ipynb	
@@ -0,0 +1,138 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "180f6063-930f-49dd-86b3-9bab1c4d82af",
+   "metadata": {},
+   "source": [
+    "## Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "5037dc08-d28b-4299-b220-454411e406a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print\n",
+    "\n",
+    "from ipywidgets import IntProgress\n",
+    "from IPython.display import display\n",
+    "import shutil"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c2bdabd1-470a-450e-bbd2-5a49b57e18f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "6acd5b8a-f2fb-45ee-8b14-aa0c7f14ad04",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[3;92mTrue\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1990-1994/run'),\n",
+       " PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1990-1994/preproc'),\n",
+       " PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1990-1994/work'),\n",
+       " PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1990-1994/plots'),\n",
+       " PosixPath('/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-1990-1994/index.html')]"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# file_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"ssp245\" / \"CMIP6-1000-1000\"\n",
+    "file_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"historical\" / \"CMIP6-1995-1994\" \n",
+    "print(file_path.exists())\n",
+    "\n",
+    "list(file_path.iterdir())[:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "03635a99-3dbb-4216-b27e-bfdc27f8ed21",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if file_path.exists() and file_path.is_dir():\n",
+    "    for item in file_path.iterdir():\n",
+    "        if item.is_dir():\n",
+    "            shutil.rmtree(item)\n",
+    "        else:\n",
+    "            item.unlink()\n",
+    "else:\n",
+    "    print(\"Folder does not exist or is not a folder.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "14ad44ce-1fcf-4b6c-9525-9e5e49d04e34",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Draft notebooks/Step2_Calibration_trial.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Draft notebooks/Step2_Calibration_trial.ipynb
new file mode 100644
index 00000000..f19a8b8f
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Draft notebooks/Step2_Calibration_trial.ipynb	
@@ -0,0 +1,4767 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fbc7f454-3d60-492d-aa6c-0ce21a0dfc77",
+   "metadata": {},
+   "source": [
+    "## Startup\n",
+    "\n",
+    "\n",
+    "80/20 rule:\n",
+    "80% calibration (2000-2020)\n",
+    "20% validation (2020-2025)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "95a06f73-282f-4c7c-8333-f002e73e205a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print\n",
+    "\n",
+    "from ipywidgets import IntProgress\n",
+    "from IPython.display import display"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8b61a012-64eb-48b2-ba78-f641a1a581a3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a860a623-f634-4b50-822c-51e09ab4e594",
+   "metadata": {},
+   "source": [
+    "### Defining variables & pathways"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "7d407089-bbfc-40d7-983f-efbc4a7ccaf5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Naming region \n",
+    "\n",
+    "hysets_id = \"hysets_07DA001\"\n",
+    "basin_size = 132572"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "970798cd-b737-44f3-8edd-de3352b86efd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "experiment_start_date = \"2000-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2005-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "c3b02d32-4be2-47a7-8935-8284af182d66",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcing_trial\" / hysets_id / \"ERA5\"\n",
+    "forcing_path_ERA5.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "calibration_temp = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"calibration_temp\"\n",
+    "calibration_temp.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd4ec71b-d4f6-4a1c-be9a-f8d3b89059d1",
+   "metadata": {},
+   "source": [
+    "### Load & prepare discharge data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "d590f365-72ad-4473-9996-88820ea52c18",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "1cec4b74-037a-4d48-8769-e0b57a7683aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= start_date) & (q_obs[\"Date\"] <= end_date)].copy()\n",
+    "\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7c47f7f-18ff-4441-b1d4-975e46e1719b",
+   "metadata": {},
+   "source": [
+    "### Generate ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "eb582ebf-8fbc-4542-b785-cee2f332bdd5",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'ewatercycle' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Generate ERA5 data\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m ERA5_forcing \u001b[38;5;241m=\u001b[39m \u001b[43mewatercycle\u001b[49m\u001b[38;5;241m.\u001b[39mforcing\u001b[38;5;241m.\u001b[39msources[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mLumpedMakkinkForcing\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mgenerate(\n\u001b[1;32m      4\u001b[0m     dataset\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mERA5\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m      5\u001b[0m     start_time\u001b[38;5;241m=\u001b[39mexperiment_start_date,\n\u001b[1;32m      6\u001b[0m     end_time\u001b[38;5;241m=\u001b[39mexperiment_end_date,\n\u001b[1;32m      7\u001b[0m     shape\u001b[38;5;241m=\u001b[39mshape_file,\n\u001b[1;32m      8\u001b[0m )\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'ewatercycle' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "    dataset=\"ERA5\",\n",
+    "    start_time=experiment_start_date,\n",
+    "    end_time=experiment_end_date,\n",
+    "    shape=shape_file,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6fc290da-fa08-48f0-83e3-a39e8f5c36ef",
+   "metadata": {},
+   "source": [
+    "## Calibration Methods"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9b95e67e-780e-4a4d-a2f1-4cf9de2b0512",
+   "metadata": {},
+   "source": [
+    "### Method 1: RMSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "3da0e944-b4bf-49c6-a986-a94fc14e0bfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def RMSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return np.sqrt(np.mean((obs - sim)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba51d28d-1fdb-46af-8f8e-5dcf904aba7f",
+   "metadata": {},
+   "source": [
+    "### Method 2: NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "9ff8dc21-0959-49a4-9d4b-496726c90f88",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def NSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return 1 - np.sum((obs - sim) ** 2) / np.sum((obs - np.mean(obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "93f96591-ceb4-4671-9a48-04a0ddbfaf5a",
+   "metadata": {},
+   "source": [
+    "### Method 3: Log_NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "826cfb65-21ba-4901-aafe-37738913c0ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def log_NSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "645d5bb0-de70-4b97-9aa0-93094c91ebe6",
+   "metadata": {},
+   "source": [
+    "## Calibration start"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "0f58e61f-7178-44f8-8e5e-e1fa402813c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create function to run the model\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Create model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Create config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=calibration_temp\n",
+    "    )\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs \n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m, \n",
+    "        index=time, \n",
+    "        name=\"Modelled discharge\"\n",
+    "    )\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "210b14c5-80b4-4b84-9e1d-09d2c0968c23",
+   "metadata": {},
+   "source": [
+    "### Define Parameters & Storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "42429a8f-42c3-4864-b351-cb8e80404a5b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.04132074e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.86890731e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.00329377e+02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.57156950e+00</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.93221286e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8.51057360e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.11747433e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.11115492e-02</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.50756202e-01</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[1;36m7.04132074e+00\u001b[0m \u001b[1;36m3.86890731e-01\u001b[0m \u001b[1;36m2.00329377e+02\u001b[0m \u001b[1;36m1.57156950e+00\u001b[0m\n",
+       " \u001b[1;36m2.93221286e-01\u001b[0m \u001b[1;36m8.51057360e+00\u001b[0m \u001b[1;36m3.11747433e-01\u001b[0m \u001b[1;36m2.11115492e-02\u001b[0m\n",
+       " \u001b[1;36m9.50756202e-01\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Define initial storages\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])\n",
+    "\n",
+    "# # Define parameters\n",
+    "# par_names = [\"Imax\",\n",
+    "#                \"Ce\",\n",
+    "#                \"Sumax\",\n",
+    "#                \"Beta\",\n",
+    "#                \"Pmax\",\n",
+    "#                \"Tlag\",\n",
+    "#                \"Kf\",\n",
+    "#                \"Ks\",\n",
+    "#                \"FM\"\n",
+    "#                ]\n",
+    "# p_min = np.array([0,   0.1,  10,  0.1, 0.001, 0,   0.001, 0.0001, 0.01])\n",
+    "# p_max = np.array([10,  2.0, 500,  5.0, 0.3,   10,  0.1,   0.01,   0.5])\n",
+    "\n",
+    "# Define parameters\n",
+    "parameter_ranges = {\n",
+    "    \"Imax\":  (2.5, 8.5),            # Maximum interception storage\n",
+    "    \"Ce\":    (0.38, 0.5),       # Evaporation correction factor\n",
+    "    \"Sumax\": (140, 275),         # Maximum soil moisture storage\n",
+    "    \"Beta\":  (1.5, 2.3),          # Soil runoff parameter\n",
+    "    \"Pmax\":  (0.2, 1.4),            # Maximum percolation rate\n",
+    "    \"Tlag\":  (5.8, 8.7),           # Time lag\n",
+    "    \"Kf\":    (0.02, 0.35),       # Fast reservoir recession coefficient\n",
+    "    \"Ks\":    (0.001, 0.1),     # Slow reservoir recession coefficient\n",
+    "    \"FM\":    (0.35, 1),          # Snowmelt factor\n",
+    "}\n",
+    "\n",
+    "# parameter_ranges = {\n",
+    "#     \"Imax\":  (3, 8.5),\n",
+    "#     \"Ce\":    (0.35, 0.48),\n",
+    "#     \"Sumax\": (140, 280),\n",
+    "#     \"Beta\":  (1.5, 2.2),\n",
+    "#     \"Pmax\":  (0.15, 1.2),\n",
+    "#     \"Tlag\":  (6, 9),\n",
+    "#     \"Kf\":    (0.04, 0.30),\n",
+    "#     \"Ks\":    (0.025, 0.07),\n",
+    "#     \"FM\":    (0.35, 1.1),\n",
+    "# }\n",
+    "\n",
+    "# Convert to arrays\n",
+    "parameter_names = list(parameter_ranges.keys())\n",
+    "\n",
+    "p_min = np.array([parameter_ranges[name][0] for name in parameter_names])\n",
+    "p_max = np.array([parameter_ranges[name][1] for name in parameter_names])\n",
+    "\n",
+    "# Create samples\n",
+    "N = 300\n",
+    "par_samples = np.random.rand(N, len(parameter_ranges))                  # Generates values between 0-1\n",
+    "parameter_sets = p_min + par_samples * (p_max - p_min)                  # Fits value to parameter range\n",
+    "\n",
+    "print(parameter_sets[:][0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e93b5d4-0a92-4d09-b135-07101e614d9e",
+   "metadata": {},
+   "source": [
+    "## LoopdiLoop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "577e23e5-8db6-45a1-b91b-aae3a46b6c12",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d5d2bf84579442978bea3ee6ec8bd1a0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "IntProgress(value=0, max=300)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m6\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m7\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m8\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m9\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m10\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m11\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m12\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m13\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m14\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m15\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m16\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m17\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m18\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m19\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m20\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">21</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m21\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m22\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">23</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m23\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m24\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m25\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">26</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m26\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m27\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m28\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">29</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m29\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m30\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m31\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m32\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m33\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m34\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">35</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m35\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m36\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">37</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m37\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">38</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m38\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">39</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m39\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">40</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m40\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m41\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">42</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m42\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">43</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m43\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">44</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m44\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">45</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m45\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">46</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m46\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">47</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m47\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m48\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m49\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">50</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m50\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">51</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m51\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m52\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">53</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m53\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">54</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m54\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">55</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m55\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">56</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m56\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">57</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m57\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">58</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m58\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">59</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m59\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">60</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m60\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">61</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m61\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">62</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m62\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">63</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m63\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m64\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">65</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m65\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">66</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m66\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">67</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m67\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">68</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m68\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">69</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m69\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">70</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m70\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m71\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">72</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m72\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">73</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m73\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m74\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">75</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m75\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">76</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m76\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">77</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m77\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">78</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m78\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">79</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m79\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">80</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m80\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">81</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m81\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">82</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m82\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">83</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m83\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">84</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m84\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">85</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m85\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">86</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m86\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">87</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m87\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">88</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m88\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">89</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m89\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">90</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m90\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m91\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">92</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m92\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">93</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m93\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">94</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m94\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">95</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m95\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">96</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m96\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">97</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m97\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">98</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m98\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">99</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m99\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">100</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m100\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">101</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m101\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">102</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m102\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">103</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m103\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">104</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m104\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">105</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m105\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">106</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m106\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">107</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m107\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">108</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m108\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">109</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m109\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">110</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m110\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">111</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m111\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">112</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m112\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">113</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m113\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">114</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m114\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">115</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m115\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">116</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m116\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">117</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m117\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">118</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m118\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">119</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m119\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">120</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m120\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">121</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m121\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">122</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m122\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">123</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m123\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">124</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m124\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">125</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m125\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">126</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m126\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">127</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m127\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">128</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m128\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">129</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m129\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">130</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m130\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">131</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m131\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">132</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m132\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">133</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m133\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">134</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m134\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">135</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m135\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">136</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m136\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">137</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m137\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">138</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m138\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">139</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m139\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">140</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m140\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">141</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m141\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">142</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m142\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">143</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m143\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">144</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m144\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">145</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m145\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">146</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m146\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">147</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m147\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">148</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m148\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">149</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m149\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">150</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m150\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">151</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m151\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">152</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m152\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">153</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m153\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">154</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m154\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">155</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m155\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">156</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m156\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">157</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m157\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">158</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m158\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">159</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m159\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">160</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m160\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">161</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m161\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">162</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m162\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">163</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m163\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">164</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m164\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">165</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m165\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">166</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m166\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">167</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m167\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">168</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m168\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">169</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m169\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">170</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m170\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">171</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m171\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">172</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m172\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">173</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m173\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m174\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">175</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m175\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">176</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m176\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">177</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m177\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">178</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m178\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m179\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">180</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m180\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">181</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m181\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">182</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m182\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m183\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">184</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m184\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">185</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m185\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">186</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m186\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">187</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m187\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">188</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m188\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">189</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m189\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">190</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m190\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">191</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m191\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">192</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m192\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">193</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m193\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">194</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m194\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">195</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m195\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">196</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m196\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">197</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m197\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">198</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m198\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">199</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m199\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">200</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m200\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">201</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m201\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">202</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m202\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">203</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m203\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">204</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m204\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">205</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m205\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">206</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m206\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">207</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m207\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">208</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m208\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">209</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m209\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">210</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m210\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">211</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m211\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">212</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m212\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">213</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m213\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">214</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m214\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">215</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m215\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">216</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m216\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">217</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m217\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m218\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">219</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m219\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">220</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m220\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">221</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m221\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">222</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m222\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">223</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m223\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">224</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m224\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">225</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m225\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">226</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m226\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">227</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m227\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">228</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m228\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">229</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m229\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">230</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m230\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">231</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m231\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m232\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">233</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m233\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">234</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m234\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">235</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m235\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">236</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m236\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">237</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m237\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">238</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m238\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">239</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m239\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">240</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m240\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">241</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m241\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">242</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m242\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">243</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m243\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">244</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m244\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">245</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m245\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">246</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m246\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">247</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m247\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">248</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m248\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">249</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m249\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">250</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m250\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">251</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m251\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">252</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m252\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">253</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m253\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">254</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m254\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">255</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m255\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">256</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m256\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">257</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m257\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">258</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m258\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">259</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m259\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">260</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m260\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">261</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m261\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">262</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m262\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">263</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m263\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">264</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m264\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">265</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m265\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">266</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m266\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">267</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m267\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">268</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m268\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">269</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m269\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">270</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m270\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">271</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m271\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">272</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m272\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">273</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m273\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">274</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m274\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">275</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m275\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">276</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m276\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">277</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m277\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">278</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m278\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">279</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m279\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">280</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m280\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">281</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m281\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">282</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m282\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">283</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m283\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">284</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m284\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">285</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m285\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">286</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m286\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">287</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m287\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">288</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m288\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">289</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m289\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">290</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m290\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">291</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m291\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">292</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m292\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">293</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m293\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">294</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m294\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m295\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m296\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m297\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m298\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m299\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m300\u001b[0m/\u001b[1;36m300\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = []\n",
+    "\n",
+    "# Progress bar for visualization\n",
+    "f = IntProgress(min=0, max=N)\n",
+    "display(f)\n",
+    "\n",
+    "for i in range(N):\n",
+    "    print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "    simulated = run_hbv(\n",
+    "        parameters=parameter_sets[i], \n",
+    "        initial_storages=s_0, \n",
+    "        forcing=ERA5_forcing\n",
+    "    )\n",
+    "\n",
+    "    # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "    simulated_daily = simulated\n",
+    "    observed_daily = observed_output\n",
+    "\n",
+    "    simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "    \n",
+    "    # Align simulated and observed data\n",
+    "    combined_data = pd.DataFrame(\n",
+    "        {\"Modelled discharge\": simulated_daily, \n",
+    "        \"Observed discharge\": observed_daily}\n",
+    "    ).dropna()\n",
+    "\n",
+    "    # Skip first year as warm-up\n",
+    "    combined_data = combined_data[combined_data.index >= \"2001-01-01\"]\n",
+    "    \n",
+    "    # Append results\n",
+    "    if combined_data.empty:\n",
+    "        print(f\"No overlapping data for parameter set {i+1}\")\n",
+    "        nse = np.nan\n",
+    "        log_nse = np.nan\n",
+    "    else:\n",
+    "        nse = NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "        log_nse = log_NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "        \n",
+    "    results.append({\n",
+    "        \"run\": i,\n",
+    "        \"NSE\": nse,\n",
+    "        \"log_NSE\": log_nse,\n",
+    "        \"parameters\": parameter_sets[i]\n",
+    "    })"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d7b5f35-f872-4ef5-8ced-c92cdd81c8f8",
+   "metadata": {},
+   "source": [
+    "### Display results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "4c69f827-adda-4ec9-8863-abf0ba31e0d2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">     run       NSE   log_NSE\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.439754</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.709099</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.699835</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.776052</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.782790</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.795898</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.408743</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.376669</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.382206</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.721494</span>\n",
+       "..   <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.705821</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.809451</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.666569</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.698280</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.481626</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.689337</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.472785</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.363001</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.230548</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.231731</span>\n",
+       "\n",
+       "<span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span> rows x <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span> columns<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "     run       NSE   log_NSE\n",
+       "\u001b[1;36m0\u001b[0m      \u001b[1;36m0\u001b[0m  \u001b[1;36m0.439754\u001b[0m  \u001b[1;36m0.709099\u001b[0m\n",
+       "\u001b[1;36m1\u001b[0m      \u001b[1;36m1\u001b[0m  \u001b[1;36m0.699835\u001b[0m  \u001b[1;36m0.776052\u001b[0m\n",
+       "\u001b[1;36m2\u001b[0m      \u001b[1;36m2\u001b[0m  \u001b[1;36m0.782790\u001b[0m  \u001b[1;36m0.795898\u001b[0m\n",
+       "\u001b[1;36m3\u001b[0m      \u001b[1;36m3\u001b[0m  \u001b[1;36m0.408743\u001b[0m  \u001b[1;36m0.376669\u001b[0m\n",
+       "\u001b[1;36m4\u001b[0m      \u001b[1;36m4\u001b[0m  \u001b[1;36m0.382206\u001b[0m  \u001b[1;36m0.721494\u001b[0m\n",
+       "..   \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m\n",
+       "\u001b[1;36m295\u001b[0m  \u001b[1;36m295\u001b[0m  \u001b[1;36m0.705821\u001b[0m  \u001b[1;36m0.809451\u001b[0m\n",
+       "\u001b[1;36m296\u001b[0m  \u001b[1;36m296\u001b[0m  \u001b[1;36m0.666569\u001b[0m  \u001b[1;36m0.698280\u001b[0m\n",
+       "\u001b[1;36m297\u001b[0m  \u001b[1;36m297\u001b[0m  \u001b[1;36m0.481626\u001b[0m  \u001b[1;36m0.689337\u001b[0m\n",
+       "\u001b[1;36m298\u001b[0m  \u001b[1;36m298\u001b[0m  \u001b[1;36m0.472785\u001b[0m  \u001b[1;36m0.363001\u001b[0m\n",
+       "\u001b[1;36m299\u001b[0m  \u001b[1;36m299\u001b[0m  \u001b[1;36m0.230548\u001b[0m  \u001b[1;36m0.231731\u001b[0m\n",
+       "\n",
+       "\u001b[1m[\u001b[0m\u001b[1;36m300\u001b[0m rows x \u001b[1;36m3\u001b[0m columns\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span> with NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8095358934408565</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m179\u001b[0m with NSE: \u001b[1;36m0.8095358934408565\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.279135309789487</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.48082432749007864</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174.127749336179</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9527195686909842</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3305087197271726</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.199192091400492</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.07683628832422615</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.004363984839521473</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.40766060413663546</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.279135309789487\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.48082432749007864\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m174.127749336179\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.9527195686909842\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.3305087197271726\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.199192091400492\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.07683628832422615\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.004363984839521473\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.40766060413663546\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span> with log_NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8717169479201906</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m179\u001b[0m with log_NSE: \u001b[1;36m0.8717169479201906\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.279135309789487</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.48082432749007864</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174.127749336179</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9527195686909842</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3305087197271726</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.199192091400492</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.07683628832422615</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.004363984839521473</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.40766060413663546</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.279135309789487\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.48082432749007864\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m174.127749336179\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.9527195686909842\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.3305087197271726\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.199192091400492\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.07683628832422615\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.004363984839521473\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.40766060413663546\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = pd.DataFrame(results)\n",
+    "\n",
+    "print(results[[\"run\", \"NSE\", \"log_NSE\"]])\n",
+    "\n",
+    "# Best NSE\n",
+    "best_run_nse = results[\"NSE\"].idxmax()\n",
+    "best_result_nse = results.loc[best_run_nse]\n",
+    "\n",
+    "best_parameters_nse = best_result_nse[\"parameters\"]\n",
+    "best_nse = best_result_nse[\"NSE\"]\n",
+    "\n",
+    "print(f'Best run: {best_run_nse} with NSE: {best_nse}, with parameters:')\n",
+    "print(list(zip(parameter_names, best_parameters_nse)))\n",
+    "\n",
+    "# Best log_NSE\n",
+    "best_run_log_nse = results[\"log_NSE\"].idxmax()\n",
+    "best_result_log_nse = results.loc[best_run_log_nse]\n",
+    "\n",
+    "best_parameters_log_nse = best_result_log_nse[\"parameters\"]\n",
+    "best_log_nse = best_result_log_nse[\"log_NSE\"]\n",
+    "\n",
+    "print(f'Best run: {best_run_log_nse} with log_NSE: {best_log_nse}, with parameters:')\n",
+    "print(list(zip(parameter_names, best_parameters_log_nse)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "68ac955d-5bc7-4c75-a862-0a6ddec6b96a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.2391126094287115</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4059034482695777</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">154.67204503110761</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.754032781455765</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.39617478157458713</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8.374403905226643</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1561690712250938</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.01336758499776439</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4720208296914324</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.2391126094287115\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.4059034482695777\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m154.67204503110761\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.754032781455765\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.39617478157458713\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m8.374403905226643\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.1561690712250938\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.01336758499776439\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.4720208296914324\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Manual check for other runs\n",
+    "\n",
+    "selected_run = results.loc[295]\n",
+    "print(list(zip(parameter_names, selected_run[\"parameters\"])))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "dc27944c-bad7-49ac-acb0-d050c6471452",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">RMSE for best NSE parameter set: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52.624</span> m³/s\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "RMSE for best NSE parameter set: \u001b[1;36m52.624\u001b[0m m³/s\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">RMSE for best log_NSE parameter set: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">62.495</span> m³/s\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "RMSE for best log_NSE parameter set: \u001b[1;36m62.495\u001b[0m m³/s\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Calculate RMSE for best parameter sets NSE and log_NSE\n",
+    "\n",
+    "rmse_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "rmse_log_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "print(f\"RMSE for best NSE parameter set: {rmse_nse:.3f} m³/s\")\n",
+    "print(f\"RMSE for best log_NSE parameter set: {rmse_log_nse:.3f} m³/s\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "aeb2ea7e-9826-450f-880e-e1e5e72c9dba",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "simulated_calibrated_nse = run_hbv(\n",
+    "    parameters=best_parameters_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "simulated_calibrated_log_nse = run_hbv(\n",
+    "    parameters=best_parameters_log_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing\n",
+    ")\n",
+    "\n",
+    "# Align dates\n",
+    "simulated_plot_nse = simulated_calibrated_nse\n",
+    "simulated_plot_log_nse = simulated_calibrated_log_nse\n",
+    "observed_plot = observed_output\n",
+    "\n",
+    "simulated_plot_nse.index = pd.to_datetime(simulated_plot_nse.index).tz_localize(None).normalize()\n",
+    "simulated_plot_log_nse.index = pd.to_datetime(simulated_plot_log_nse.index).tz_localize(None).normalize()\n",
+    "observed_plot.index = pd.to_datetime(observed_plot.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Combine modelled and observed data\n",
+    "plot_data = pd.DataFrame({\n",
+    "    \"Modelled discharge NSE\": simulated_plot_nse,\n",
+    "    \"Modelled discharge log_NSE\": simulated_plot_log_nse,\n",
+    "    \"Observed discharge\": observed_plot\n",
+    "}).dropna()\n",
+    "\n",
+    "# Calculate NSE for plotted data\n",
+    "plot_nse = NSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "plot_log_nse = log_NSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"]\n",
+    ")\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\")\n",
+    "plt.plot(plot_data.index, plot_data[\"Modelled discharge NSE\"], label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data.index, plot_data[\"Modelled discharge log_NSE\"], label=\"Modelled discharge log_NSE\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001, NSE = {best_nse:.3f}, log NSE = {best_log_nse:.3f}\")\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f'Critical discharge ({q_critical} m³/s', color='black')\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dde634ea-53bd-4c41-ba13-8ec762014b89",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Draft notebooks/Step2_Trial_model_LAR.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Draft notebooks/Step2_Trial_model_LAR.ipynb
new file mode 100644
index 00000000..67dd806a
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Draft notebooks/Step2_Trial_model_LAR.ipynb	
@@ -0,0 +1,921 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bdb4216e-a341-4c2b-a410-35170773a9a7",
+   "metadata": {},
+   "source": [
+    "## Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d197b8f0-0f85-4a41-b2fb-1b2a8cf3f9f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "dd7b7d3f-1489-4723-bb51-f3cffcb7a85c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "6c47c679-3f14-431b-8c59-908c581e2f1d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'OBS6'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/data/shared/climate-data/obs6'</span><span style=\"font-weight: bold\">)]</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'default'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/data/shared/climate-data'</span><span style=\"font-weight: bold\">)]</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/.esmvaltool/downloads/CMIP6'</span><span style=\"font-weight: bold\">)]</span>\n",
+       "<span style=\"font-weight: bold\">}</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\n",
+       "    \u001b[32m'OBS6'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/data/shared/climate-data/obs6'\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+       "    \u001b[32m'default'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/data/shared/climate-data'\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+       "    \u001b[32m'CMIP6'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/.esmvaltool/downloads/CMIP6'\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'CMIP3'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP5'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CORDEX'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'obs4MIPs'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span><span style=\"font-weight: bold\">}</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\u001b[32m'CMIP3'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'CMIP5'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'CMIP6'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'CORDEX'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'obs4MIPs'\u001b[0m: \u001b[32m'ESGF'\u001b[0m\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from esmvalcore.config import CFG   # older: from esmvalcore.experimental import CFG\n",
+    "from pathlib import Path\n",
+    "home = Path.home()\n",
+    "OBS6 = Path('/data/shared/climate-data/obs6')\n",
+    "default = Path('/data/shared/climate-data')\n",
+    "CMIP_path = Path(f'{str(home)}/.esmvaltool/downloads/CMIP6')\n",
+    "CFG['rootpath'] = {'OBS6': [OBS6], 'default': [default], 'CMIP6': [CMIP_path]}\n",
+    "print(CFG['rootpath'])\n",
+    "print(CFG['drs'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "1c8aee93-b2d6-4291-89ae-1d29e69268cd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining basin size\n",
+    "\n",
+    "basin_size = 132572"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "d7dce039-d1f3-44a0-b646-98c32ecffb28",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "experiment_start_date = \"2019-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2024-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "d330bf37-7419-4287-81af-3d09e4c7a30e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Create pathways for ERA 5 forcings\n",
+    "\n",
+    "# forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "# discharge_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# hbv_config = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"hbv_config\"\n",
+    "# hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "12cc30f9-29ad-4b43-b3dd-9cd5612ff4e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5-2019-2024\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "46ea8b1e-fb73-49ed-855c-4d95cd932748",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "8bb224ad-d23c-475f-b6af-4a6023a17044",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>22193</th>\n",
+       "      <td>2019-01-01</td>\n",
+       "      <td>213.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22194</th>\n",
+       "      <td>2019-01-02</td>\n",
+       "      <td>213.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22195</th>\n",
+       "      <td>2019-01-03</td>\n",
+       "      <td>213.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22196</th>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>214.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22197</th>\n",
+       "      <td>2019-01-05</td>\n",
+       "      <td>214.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Date  discharge_m3s\n",
+       "22193 2019-01-01          213.0\n",
+       "22194 2019-01-02          213.0\n",
+       "22195 2019-01-03          213.0\n",
+       "22196 2019-01-04          214.0\n",
+       "22197 2019-01-05          214.0"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "q_obs = q_obs[\n",
+    "    (q_obs[\"Date\"] >= start_date) &\n",
+    "    (q_obs[\"Date\"] <= end_date)\n",
+    "].copy()\n",
+    "\n",
+    "q_obs.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "7f6f57aa-9f39-4524-ba3a-34f55035ebab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"])\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "77e79b20-3e4d-405a-bd88-16bdc50bdb39",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2024-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/esmvaltool_output/ewcrep8rzr6k8h_20260611_140830/work/diagnostic/script'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">s/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'OBS6_ERA5_reanaly_1_day_pr_2019-2024.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'OBS6_ERA5_reanaly_1_day_tas_2019-2024.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'OBS6_ERA5_reanaly_1_day_rsds_2019-2024.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Derived_Makkink_evspsblpot.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'2019-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2024-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/esmvaltool_output/ewcrep8rzr6k8h_20260611_140830/work/diagnostic/script'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile\u001b[0m\n",
+       "\u001b[32ms/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'OBS6_ERA5_reanaly_1_day_pr_2019-2024.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'OBS6_ERA5_reanaly_1_day_tas_2019-2024.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'OBS6_ERA5_reanaly_1_day_rsds_2019-2024.nc'\u001b[0m,\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'Derived_Makkink_evspsblpot.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "    dataset=\"ERA5\",\n",
+    "    start_time=experiment_start_date,\n",
+    "    end_time=experiment_end_date,\n",
+    "    shape=shape_file)\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "ca2be146-1112-4806-a44f-d57ebd4442c9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.991929</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.44128</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183.49046</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.62907</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.572658</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.215476</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0654684</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00259304</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.14274</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.991929\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.44128\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m183.49046\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.62907\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.572658\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.215476\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.0654684\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.00259304\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.14274\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "# par_0 = [4.45787, 0.42307, 201.57602, 2.36497, 0.26755, 8.62964, 0.083568, 0.0037073, 0.29645]\n",
+    "# par_0 = [2.79874, 0.49211, 255.96478, 1.782968, 0.503199, 6.095956, 0.33279, 0.10539, 0.63857]\n",
+    "# par_0 = [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606]         # 0.725 val, 0.x cal - Fav run 2\n",
+    "# par_0 = [6.28908, 0.423917, 173.56627, 1.63144, 0.402586, 6.56151, 0.0456809, 0.00313744, 0.516696]                 # 0.702 val, 0.x cal\n",
+    "# par_0 = [6.4919, 0.386877, 221.78625, 1.388269, 0.276453, 4.9870704, 0.04126777, 0.05640195, 1.148877]              # 0.668 val, 0.x cal\n",
+    "# par_0 = [7.502398, 0.38028, 194.1899, 1.680197, 0.47956, 4.8566806, 0.041745354, 0.02833896, 1.051862]              # 0.677 val, 0.x cal\n",
+    "# par_0 = [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392]                        # 0.781 val, 0.776 cal\n",
+    "# par_0 = [6.16512, 0.4369419, 151.2515900, 1.727835, 0.3771705, 6.19265974, 0.06959136, 0.001310818, 0.8130732]      # 0.664 val, 0.791 cal\n",
+    "# par_0 = [5.7107, 0.441634, 172.81305, 1.87367, 0.588802, 5.498147, 0.060305, 0.019666, 1.2011814]                    # x val, 0.73 cal         Start of 5+ months exclusion\n",
+    "# par_0 = [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504]                    # 0.82 val, 0.818 cal - Fav run 1      \n",
+    "# par_0 = [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]                    #  val,  0.77 cal    \n",
+    "# par_0 = [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857]                           # 0.78 val, 0.71 cal - potential inclusion\n",
+    "par_0 = [6.991929, 0.44128, 183.49046, 1.62907, 0.572658, 5.215476, 0.0654684, 0.00259304, 1.14274]                   # 0,69 c, 0.73 v - 6 months excluded N = 600 #1\n",
+    "# par_0 = [5.882658, 0.472413, 194.30386, 1.78162, 0.460818, 5.215365, 0.0641993, 0.159898, 1.091972]                   # 0,637 c, 0,65 v - 6 months excluded N = 600 #2\n",
+    "# par_0 = [6.991929, 0.44128, 183.49046, 1.62907, 0.572658, 5.215476, 0.0654684, 0.00259304, 1.14274]                   # c, v - 6 months excluded N = 600 #3\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"          # Snowmelt factor\n",
+    "               ]\n",
+    "\n",
+    "# Initial: par_0 = [5.085, 0.55, 100.373, 1.612, 0.545, 3.801, 0.196, 0.00, 0.185]\n",
+    "\n",
+    "print(list(zip(par_names, par_0)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "d5e5bcb4-bf90-470b-90ed-4a0b9d80c35d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5bbaae8e-18fa-4383-9973-5a2560840699",
+   "metadata": {},
+   "source": [
+    "## Setup model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "055bdbc8-af1f-41ac-ad1d-b4da4d6785f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create model object\n",
+    "\n",
+    "model = ewatercycle.models.HBV(forcing=ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "id": "44092959-524a-4330-a274-77cfad0eacd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create config file\n",
+    "\n",
+    "config_file, _ = model.setup(parameters=par_0, initial_storages=s_0, cfg_dir=hbv_config)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "079368de-30cf-491f-8cc9-2021f6a4bfa6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Initialising model\n",
+    "\n",
+    "model.initialize(config_file)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "327222c7-bd08-4992-826e-07f40f61b783",
+   "metadata": {},
+   "source": [
+    "## Running the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "id": "93b4084b-21e5-4009-9fc7-122b7b739a86",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define outputs\n",
+    "\n",
+    "Q_m = []\n",
+    "time = []\n",
+    "\n",
+    "while model.time < model.end_time:\n",
+    "    model.update()\n",
+    "    Q_m.append(model.get_value(\"Q\")[0])\n",
+    "    time.append(pd.Timestamp(model.time_as_datetime))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "id": "f1bb58f8-3dee-43eb-abc8-4af333b5d064",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.finalize()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "39872047-cba7-47c4-b2f8-6ed47c56fdc6",
+   "metadata": {},
+   "source": [
+    "## Process results "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "id": "715c5274-8ab4-45d0-b154-bb0cf30b52bd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Make Series for model output and q_obs\n",
+    "model_output_mmday = pd.Series(data=Q_m, name=\"Modelled discharge\", index=time)\n",
+    "model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "# Date_obs = q_obs[\"Date\"]\n",
+    "# discharge_m3s_obs = q_obs[\"discharge_m3s\"]\n",
+    "\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])\n",
+    "\n",
+    "# q_obs.set_index(\"Date\")[\"discharge_m3s\"]\n",
+    "# observed_output.name = \"Observed discharge\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "id": "9ee05f10-c416-4238-be5f-0dd3901ba3ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for year range\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "observed_output.plot(label=\"Observed discharge\")\n",
+    "model_output_m3s.plot(label=\"Modelled discharge\")\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f'Critical discharge ({q_critical} m³/s)', color='black')\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Modelled vs observed discharge at 07DA001\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.xlim(\"2020-01-01\", \"2024-12-31\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "id": "494883ac-e9f0-4806-93d9-bb6a52372309",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for 1 year\n",
+    "\n",
+    "selected_year = 2024\n",
+    "\n",
+    "observed_plot = observed_output\n",
+    "modelled_plot = model_output_m3s\n",
+    "\n",
+    "observed_plot.index = pd.to_datetime(observed_plot.index).tz_localize(None).normalize()\n",
+    "modelled_plot.index = pd.to_datetime(modelled_plot.index).tz_localize(None).normalize()\n",
+    "\n",
+    "plot_data = pd.DataFrame({\n",
+    "    \"Modelled discharge\": modelled_plot,\n",
+    "    \"Observed discharge\": observed_plot\n",
+    "}).dropna()\n",
+    "\n",
+    "plot_data_year = plot_data[plot_data.index.year == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Observed discharge\"],label=\"Observed discharge\")\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge\"],label=\"Modelled discharge\")\n",
+    "\n",
+    "plt.axhline(y=q_critical,linestyle=\":\",color=\"black\",label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001 in {selected_year}\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e2e1edf-f9a2-4d42-8de0-13e5dfc29fd5",
+   "metadata": {},
+   "source": [
+    "### "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b4a1bc95-7122-4372-8b79-991d1344452c",
+   "metadata": {},
+   "source": [
+    "### Log NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "id": "0c3e7e10-16ba-46cf-96a6-9bb2d01f8287",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate log NSE\n",
+    "\n",
+    "def log_NSE(sim, obs):\n",
+    "    \n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "id": "6bcc0656-5f3a-450a-b758-e4c93e9feb07",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call log NSE for relevant timeperiod\n",
+    "\n",
+    "def lognse_for_period(sim, obs, lognse_start, lognse_end):\n",
+    "\n",
+    "    simulated_daily = sim\n",
+    "    observed_daily = obs\n",
+    "\n",
+    "    simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    combined_data = pd.DataFrame({\n",
+    "        \"Modelled discharge\": simulated_daily,\n",
+    "        \"Observed discharge\": observed_daily\n",
+    "    }).dropna()\n",
+    "\n",
+    "    lognse_start = pd.to_datetime(lognse_start).tz_localize(None).normalize()\n",
+    "    lognse_end = pd.to_datetime(lognse_end).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Set time period - Skip 1st year\n",
+    "    combined_data = combined_data[\n",
+    "        (combined_data.index >= lognse_start) &\n",
+    "        (combined_data.index <= lognse_end)\n",
+    "    ]\n",
+    "\n",
+    "    # Exclude winter months\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])\n",
+    "    ]\n",
+    "\n",
+    "    if combined_data.empty:\n",
+    "        print(\"No data left after filtering.\")\n",
+    "        return np.nan\n",
+    "\n",
+    "    log_nse = log_NSE(\n",
+    "        combined_data[\"Modelled discharge\"],\n",
+    "        combined_data[\"Observed discharge\"]\n",
+    "    )\n",
+    "\n",
+    "    return log_nse"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "id": "aa07b0d5-9144-48bf-9ca6-a43812e30020",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">log NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.6899179967067883</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "log NSE: \u001b[1;36m0.6899179967067883\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Return log NSE\n",
+    "evaluation_start = pd.to_datetime(f\"{start_date.year + 1}-01-01\")\n",
+    "\n",
+    "lognse_value = lognse_for_period(\n",
+    "    model_output_m3s,\n",
+    "    observed_output,\n",
+    "    evaluation_start,\n",
+    "    end_date\n",
+    ")\n",
+    "\n",
+    "print(\"log NSE:\", lognse_value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56592f44-6174-48c3-a724-2ed1036228ff",
+   "metadata": {},
+   "source": [
+    "### Days calc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "id": "2d2cda32-61ff-4710-998b-4c4a5205cefc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def days_counter(sim, obs, start_date, end_date):\n",
+    "\n",
+    "    # Combine dataset in Dataframe\n",
+    "    combined_data = pd.DataFrame({\n",
+    "        \"Modelled discharge\": sim,\n",
+    "        \"Observed discharge\": obs\n",
+    "    }).dropna()\n",
+    "\n",
+    "    # Make list of years\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    # Loop through each year\n",
+    "    for i in range(len(years)):\n",
+    "\n",
+    "        year = years[i]\n",
+    "\n",
+    "        # Define start month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "\n",
+    "        year_data = combined_data[\n",
+    "            (combined_data.index >= year_start) &\n",
+    "            (combined_data.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = 0\n",
+    "\n",
+    "        # Loop through each  year to identify lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "            modelled_q = year_data.iloc[j][\"Modelled discharge\"]\n",
+    "\n",
+    "            # Check if that day is low flow and accumulate\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "            if modelled_q < q_critical:\n",
+    "                modelled_lowflow_days += 1\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    # average_error = round(lowflow_days[\"%error\"].abs().mean(), 1)\n",
+    "\n",
+    "    return lowflow_days\n",
+    "    \n",
+    "    # , print(f\"average error = {average_error}%\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "id": "c04c46cc-b80a-40ec-b741-e78fa5168dcd",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: []\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Define period (based on algorithm date > q_critical & freeze-up date output) & prepare\n",
+    "day_calc_start = pd.to_datetime(f\"{start_date.year + 1}-01-01\")\n",
+    "q_critical = 500\n",
+    "\n",
+    "lowflow_days = days_counter(\n",
+    "    sim=model_output_m3s,\n",
+    "    obs=observed_output,\n",
+    "    start_date=day_calc_start,\n",
+    "    end_date=end_date\n",
+    ")\n",
+    "\n",
+    "lowflow_days\n",
+    "\n",
+    "# NOTE TO CHANGE TIME RANGE -> EDIT DEF days_counter FUNCTION UNDER # Define start month day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3d9701be-4df6-41b8-904e-cb4cda096e80",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.cpg b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.cpg
new file mode 100644
index 00000000..3ad133c0
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.cpg
@@ -0,0 +1 @@
+UTF-8
\ No newline at end of file
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.dbf b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.dbf
new file mode 100644
index 00000000..b554ebf7
Binary files /dev/null and b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.dbf differ
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.prj b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.prj
new file mode 100644
index 00000000..f45cbadf
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.prj
@@ -0,0 +1 @@
+GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]
\ No newline at end of file
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.qmd b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.qmd
new file mode 100644
index 00000000..74011b2e
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.qmd
@@ -0,0 +1,27 @@
+<!DOCTYPE qgis PUBLIC 'http://mrcc.com/qgis.dtd' 'SYSTEM'>
+<qgis version="4.0.1-Norrköping">
+  <identifier>MDA_ADP_07_DrainageBasin_BassinDeDrainage</identifier>
+  <parentidentifier></parentidentifier>
+  <language>ENG</language>
+  <type>dataset</type>
+  <title>MDA_ADP_07_DrainageBasin_BassinDeDrainage</title>
+  <abstract></abstract>
+  <links/>
+  <dates/>
+  <fees></fees>
+  <encoding></encoding>
+  <crs>
+    <spatialrefsys nativeFormat="Wkt">
+      <wkt>PROJCRS["Canada_Albers_Equal_Area_Conic",BASEGEOGCRS["NAD83",DATUM["North American Datum 1983",ELLIPSOID["GRS 1980",6378137,298.257222101,LENGTHUNIT["metre",1]]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433]],ID["EPSG",4269]],CONVERSION["Canada_Albers_Equal_Area_Conic",METHOD["Albers Equal Area",ID["EPSG",9822]],PARAMETER["Latitude of false origin",40,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8821]],PARAMETER["Longitude of false origin",-96,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8822]],PARAMETER["Latitude of 1st standard parallel",50,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8823]],PARAMETER["Latitude of 2nd standard parallel",70,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8824]],PARAMETER["Easting at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8826]],PARAMETER["Northing at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8827]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1]],USAGE[SCOPE["Not known."],AREA["Canada - onshore and offshore - Alberta; British Columbia; Manitoba; New Brunswick; Newfoundland and Labrador; Northwest Territories; Nova Scotia; Nunavut; Ontario; Prince Edward Island; Quebec; Saskatchewan; Yukon."],BBOX[38.21,-141.01,86.46,-40.73]],ID["ESRI",102001]]</wkt>
+      <proj4>+proj=aea +lat_0=40 +lon_0=-96 +lat_1=50 +lat_2=70 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs</proj4>
+      <srsid>27124</srsid>
+      <srid>102001</srid>
+      <authid>ESRI:102001</authid>
+      <description>Canada_Albers_Equal_Area_Conic</description>
+      <projectionacronym>aea</projectionacronym>
+      <ellipsoidacronym>EPSG:7019</ellipsoidacronym>
+      <geographicflag>false</geographicflag>
+    </spatialrefsys>
+  </crs>
+  <extent/>
+</qgis>
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.shp b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.shp
new file mode 100644
index 00000000..7f647ec7
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diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.shx b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.shx
new file mode 100644
index 00000000..bf59e75f
Binary files /dev/null and b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefiles/07DA001_basin.shx differ
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step1_CMIP6_Forcings_Generation.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step1_CMIP6_Forcings_Generation.ipynb
new file mode 100644
index 00000000..ae645d83
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step1_CMIP6_Forcings_Generation.ipynb
@@ -0,0 +1,913 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e91181a8-c60f-456f-80cc-3923bf7c6a43",
+   "metadata": {},
+   "source": [
+    "# CMIP6 Data generation & merging \n",
+    "\n",
+    "CMIP6 data will be generated from 1995-2014, loaded and merged into one file\n",
+    "\n",
+    "**Note: Depending on if you want to run historical, or an ssp, changes you need to make are:**\n",
+    "1. Cell 5: Select scenario\n",
+    "2. Cell 6: Define period"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "680410be-715a-4678-a4e3-c1141939241e",
+   "metadata": {},
+   "source": [
+    "## Start-up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "7ef3318e-968e-418e-bf4c-a8936aade9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# general python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "#niceties\n",
+    "from rich import print\n",
+    "\n",
+    "import yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f7ff029b-ee4b-4fe2-b5d5-bf768b626989",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "OSError",
+     "evalue": "[Errno 5] Input/output error: '/data/shared/observation/grdc/dailies'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# General eWaterCycle\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mewatercycle\u001b[39;00m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mewatercycle\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodels\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mewatercycle\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mforcing\u001b[39;00m\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/ewatercycle/__init__.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"ewatercycle package.\"\"\"\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfig\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m CFG \u001b[38;5;28;01mas\u001b[39;00m CFG\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mversion\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m __version__ \u001b[38;5;28;01mas\u001b[39;00m __version__\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/ewatercycle/config/__init__.py:321\u001b[0m\n\u001b[1;32m    317\u001b[0m _SOURCES \u001b[38;5;241m=\u001b[39m (USER_HOME_CONFIG, SYSTEM_CONFIG)\n\u001b[1;32m    319\u001b[0m USER_CONFIG \u001b[38;5;241m=\u001b[39m _find_user_config(_SOURCES)\n\u001b[0;32m--> 321\u001b[0m CFG \u001b[38;5;241m=\u001b[39m \u001b[43mConfiguration\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_load_user_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43mUSER_CONFIG\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mif\u001b[39;00m USER_CONFIG \u001b[38;5;28;01melse\u001b[39;00m Configuration()\n\u001b[1;32m    322\u001b[0m \u001b[38;5;124;03m\"\"\"eWaterCycle configuration object.\u001b[39;00m\n\u001b[1;32m    323\u001b[0m \n\u001b[1;32m    324\u001b[0m \u001b[38;5;124;03mThe configuration is loaded from:\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    341\u001b[0m \u001b[38;5;124;03m    # apptainer pull docker://ewatercycle/wflow-grpc4bmi:2020.1.1\u001b[39;00m\n\u001b[1;32m    342\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/ewatercycle/config/__init__.py:197\u001b[0m, in \u001b[0;36mConfiguration._load_user_config\u001b[0;34m(cls, filename)\u001b[0m\n\u001b[1;32m    195\u001b[0m mapping \u001b[38;5;241m=\u001b[39m _read_config_file(filename)\n\u001b[1;32m    196\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 197\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mConfiguration\u001b[49m\u001b[43m(\u001b[49m\u001b[43mewatercycle_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmapping\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    198\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ValidationError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    199\u001b[0m     \u001b[38;5;66;03m# Append filename to error locs\u001b[39;00m\n\u001b[1;32m    200\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m error \u001b[38;5;129;01min\u001b[39;00m e\u001b[38;5;241m.\u001b[39merrors():\n",
+      "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/site-packages/pydantic/types.py:1282\u001b[0m, in \u001b[0;36mPathType.validate_directory\u001b[0;34m(path, _)\u001b[0m\n\u001b[1;32m   1280\u001b[0m \u001b[38;5;129m@staticmethod\u001b[39m\n\u001b[1;32m   1281\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mvalidate_directory\u001b[39m(path: Path, _: core_schema\u001b[38;5;241m.\u001b[39mValidationInfo) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Path:\n\u001b[0;32m-> 1282\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[43mpath\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mis_dir\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m   1283\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m path\n\u001b[1;32m   1284\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/pathlib.py:875\u001b[0m, in \u001b[0;36mPath.is_dir\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    871\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    872\u001b[0m \u001b[38;5;124;03mWhether this path is a directory.\u001b[39;00m\n\u001b[1;32m    873\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    874\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 875\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m S_ISDIR(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstat\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mst_mode)\n\u001b[1;32m    876\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    877\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _ignore_error(e):\n",
+      "File \u001b[0;32m/opt/conda/envs/ewatercycle2/lib/python3.12/pathlib.py:840\u001b[0m, in \u001b[0;36mPath.stat\u001b[0;34m(self, follow_symlinks)\u001b[0m\n\u001b[1;32m    835\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mstat\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m, follow_symlinks\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[1;32m    836\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    837\u001b[0m \u001b[38;5;124;03m    Return the result of the stat() system call on this path, like\u001b[39;00m\n\u001b[1;32m    838\u001b[0m \u001b[38;5;124;03m    os.stat() does.\u001b[39;00m\n\u001b[1;32m    839\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 840\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstat\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfollow_symlinks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfollow_symlinks\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[0;31mOSError\u001b[0m: [Errno 5] Input/output error: '/data/shared/observation/grdc/dailies'"
+     ]
+    }
+   ],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "df3c38b4-7757-475c-a670-e7a06cc53955",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choose what you want to run:\n",
+    "Scenario = \"ssp370\"    # Options: historical, ssp119, ssp126, ssp245, ssp,370, ssp585"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74c8c15e-8cab-4e1a-b6eb-c9c165d8c051",
+   "metadata": {},
+   "source": [
+    "### Define range & forcing paths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "b2343410-2713-4089-ae42-dad37b457c41",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6-20</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">25-2030</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/\u001b[0m\u001b[95mCMIP6-20\u001b[0m\n",
+       "\u001b[95m25-2030\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2025\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining period range\n",
+    "\n",
+    "# For CMIP trial:\n",
+    "# periods = [\n",
+    "#     [1989, 1995, 2000, 2005, 2010],\n",
+    "#     [1994, 1999, 2004, 2009, 2014]\n",
+    "# ]\n",
+    "\n",
+    "# periods = [\n",
+    "#     [1970, 1975, 1980, 1985, 1990, 1995],\n",
+    "#     [1974, 1979, 1984, 1989, 1994, 1999]\n",
+    "# ]\n",
+    "\n",
+    "# Future projections 2025-2050:\n",
+    "periods = [\n",
+    "    [2025, 2031, 2036, 2041, 2046],\n",
+    "    [2030, 2035, 2040, 2045, 2050]\n",
+    "]\n",
+    "\n",
+    "# Future projections 2050-2075:\n",
+    "# periods = [\n",
+    "#     [2050, 2056, 2061, 2066, 2071],\n",
+    "#     [2055, 2060, 2065, 2070, 2075]\n",
+    "# ]\n",
+    "\n",
+    "# Future projections 2075-2099:\n",
+    "# periods = [\n",
+    "#     [2075, 2081, 2086, 2091, 2096],\n",
+    "#     [2080, 2085, 2090, 2095, 2099]\n",
+    "# ]\n",
+    "\n",
+    "\n",
+    "folder_names = []\n",
+    "forcing_paths = {}\n",
+    "\n",
+    "# Generate file names & paths\n",
+    "for i in range(len(periods[0])):\n",
+    "    start_year = periods[0][i]\n",
+    "    end_year = periods[1][i]\n",
+    "    \n",
+    "    folder_name = f'CMIP6-{start_year}-{end_year}'                        \n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"SSP\" / folder_name\n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / folder_name\n",
+    "\n",
+    "    folder_names.append(folder_name)\n",
+    "    forcing_paths[folder_name] = forcing_path\n",
+    "\n",
+    "    forcing_path.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "# Call path test\n",
+    "print(forcing_paths[folder_names[0]])\n",
+    "\n",
+    "start_year = periods[0][0]\n",
+    "end_year = periods[1][-1]\n",
+    "\n",
+    "print(start_year)\n",
+    "print(end_year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "619dd21a-0646-4bae-a71b-935f1fca8c04",
+   "metadata": {},
+   "source": [
+    "### Generate CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "cbc7b2b6-88ee-4e7f-b37c-39eaf878c075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2030</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping CMIP6-\u001b[1;36m2025\u001b[0m-\u001b[1;36m2030\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2031</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2035</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2031\u001b[0m-\u001b[1;36m2035\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2036</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2040</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2036\u001b[0m-\u001b[1;36m2040\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2041</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2045</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2041\u001b[0m-\u001b[1;36m2045\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished CMIP6-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2046</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished CMIP6-\u001b[1;36m2046\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Shapefile path\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# Choose CMIP6 dataset\n",
+    "# CMIP_dataset = {'dataset': 'MPI-ESM1-2-HR', 'project': 'CMIP6', 'grid' : 'gn', 'exp': Scenario, 'ensemble': 'r1i1p1f1'}\n",
+    "CMIP_dataset =  {'project': 'CMIP6', 'activity': 'ScenarioMIP', 'exp': Scenario, 'mip': 'day', 'dataset': 'MPI-ESM1-2-HR', 'ensemble': 'r1i1p1f1', 'institute': 'DKRZ', 'grid': 'gn'}\n",
+    "\n",
+    "# Generate forcing data\n",
+    "# for i in range(1):\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Change start year to start time so ERA5 can interpret it\n",
+    "    start_time_CMIP = f'{periods[0][i]}-01-01T00:00:00Z'\n",
+    "    end_time_CMIP = f'{periods[1][i]}-12-31T00:00:00Z'\n",
+    "\n",
+    "    # Skip if folder is not empty to prevent errors\n",
+    "    if any(forcing_paths[folder_names[i]].iterdir()):\n",
+    "        print(f\"Skipping {folder_names[i]} because the folder is not empty.\")\n",
+    "        continue\n",
+    "\n",
+    "    # Load forcings\n",
+    "    CMIP_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "        dataset=CMIP_dataset,\n",
+    "        start_time=start_time_CMIP,\n",
+    "        end_time=end_time_CMIP,\n",
+    "        shape=shape_file,\n",
+    "        directory=forcing_paths[folder_names[i]]\n",
+    "    )\n",
+    "\n",
+    "    # I need info because my patience is limited\n",
+    "    print(f\"Finished {folder_names[i]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91242ae4-3d21-4d18-815f-5cc986d5961e",
+   "metadata": {},
+   "source": [
+    "### Load CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "f8e8ac64-fee5-4602-a1f1-90b8fb14c2b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2025-2030'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2031-2035'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2036-2040'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2041-2045'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6-2046-2050'</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[32m'CMIP6-2025-2030'\u001b[0m, \u001b[32m'CMIP6-2031-2035'\u001b[0m, \u001b[32m'CMIP6-2036-2040'\u001b[0m, \u001b[32m'CMIP6-2041-2045'\u001b[0m, \u001b[32m'CMIP6-2046-2050'\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "LumpedMakkinkForcing(start_time='2025-01-01T00:00:00Z', end_time='2030-12-31T00:00:00Z', directory=PosixPath('/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-2025-2030/work/diagnostic/script'), shape=PosixPath('/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-2025-2030/work/diagnostic/script/07DA001_basin.shp'), filenames={'pr': 'CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2025-2030.nc', 'tas': 'CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2025-2030.nc', 'rsds': 'CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2025-2030.nc', 'evspsblpot': 'Derived_Makkink_evspsblpot.nc'})"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "CMIP_forcings = {}\n",
+    "\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Create new path to find relevant files in the folder\n",
+    "    directory_new = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\"\n",
+    "    \n",
+    "    # Load forcings\n",
+    "    CMIP_forcings[folder_names[i]] = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=directory_new)\n",
+    "\n",
+    "# Test to see if it works\n",
+    "print(folder_names)\n",
+    "CMIP_forcings[folder_names[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8eddb25-06e3-4702-87e8-258aeda27a15",
+   "metadata": {},
+   "source": [
+    "### Merge CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "1cb12aa2-4b4c-4108-a5c9-2d8156cdecfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to seperate files based on file names and combine same file names from different folders\n",
+    "def combine_variable(var_name):\n",
+    "    datasets = []\n",
+    "\n",
+    "    for i in range(len(folder_names)):\n",
+    "\n",
+    "        if var_name == \"evspsblpot\":\n",
+    "            file_name = \"Derived_Makkink_evspsblpot.nc\"\n",
+    "        else:\n",
+    "            file_name = f\"CMIP6_MPI-ESM1-2-HR_day_{Scenario}_r1i1p1f1_{var_name}_gn_{periods[0][i]}-{periods[1][i]}.nc\"\n",
+    "\n",
+    "        directory = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\" / file_name\n",
+    "\n",
+    "        print(f\"Loading {directory}\")\n",
+    "\n",
+    "        datasets.append(xr.open_dataset(directory))\n",
+    "\n",
+    "    combined = xr.concat(datasets, dim=\"time\")\n",
+    "    return combined"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "b21fe2e4-478a-4e0b-9f1f-a40316e22018",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">25-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2025-2030.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m25-2030/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2025-2030.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">31-2035/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2031-2035.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m31-2035/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2031-2035.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">36-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2036-2040.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m36-2040/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2036-2040.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">41-2045/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2041-2045.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m41-2045/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2041-2045.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">46-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2046-2050.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m46-2050/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_pr_gn_2046-2050.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">25-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2025-2030.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m25-2030/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2025-2030.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">31-2035/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2031-2035.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m31-2035/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2031-2035.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">36-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2036-2040.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m36-2040/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2036-2040.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">41-2045/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2041-2045.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m41-2045/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2041-2045.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">46-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2046-2050.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m46-2050/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_tas_gn_2046-2050.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">25-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2025-2030.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m25-2030/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2025-2030.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">31-2035/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2031-2035.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m31-2035/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2031-2035.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">36-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2036-2040.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m36-2040/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2036-2040.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">41-2045/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2041-2045.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m41-2045/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2041-2045.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">46-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2046-2050.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m46-2050/work/diagnostic/script/\u001b[0m\u001b[95mCMIP6_MPI-ESM1-2-HR_day_ssp370_r1i1p1f1_rsds_gn_2046-2050.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">25-2030/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m25-2030/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">31-2035/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m31-2035/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">36-2040/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m36-2040/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">41-2045/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m41-2045/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">46-2050/work/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/CMIP6/ssp370/CMIP6-20\u001b[0m\n",
+       "\u001b[35m46-2050/work/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Running function for various file name types\n",
+    "combined_variables = {}\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "# combined_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f'CMIP6-{start_year}-{end_year}'\n",
+    "combined_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f'CMIP6-{start_year}-{end_year}'\n",
+    "combined_path.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "    combined_variables[var_names[i]] = combine_variable(var_names[i])\n",
+    "    combined_variables[var_names[i]].to_netcdf(combined_path / f'combined_CMIP6_{start_year}_{end_year}_{var_names[i]}.nc')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a439e818-0aa8-4e92-a189-fde70016a911",
+   "metadata": {},
+   "source": [
+    "### Create YAML file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "e60b3316-e100-4af9-a36d-fad721ef6e02",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create yaml\n",
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{start_year}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{end_year}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_CMIP6_{start_year}_{end_year}_pr.nc\",\n",
+    "        \"tas\": f\"combined_CMIP6_{start_year}_{end_year}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_CMIP6_{start_year}_{end_year}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_CMIP6_{start_year}_{end_year}_evspsblpot.nc\"\n",
+    "    }}\n",
+    "\n",
+    "# Save the YAML file\n",
+    "yaml_file_path = combined_path / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "10ff50bf-b6e7-4033-9682-3e25d01ecd26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2025-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2050-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">ngs/CMIP6/ssp370/CMIP6-2025-2050'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">s/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_2025_2050_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'2025-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2050-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci\u001b[0m\n",
+       "\u001b[32mngs/CMIP6/ssp370/CMIP6-2025-2050'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile\u001b[0m\n",
+       "\u001b[32ms/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_2025_2050_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "CMIP6_combined_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=combined_path)\n",
+    "print(CMIP6_combined_forcing)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "83a89024-510b-442f-adeb-8f9e0d07a77f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a8771eeb-24fc-4030-a653-1bafbfd45aec",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eb1f2d7f-6efb-4d2c-a892-45d5792a5ede",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6cb15558-ec6b-4d6c-b1fc-8a8843b617db",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step1_ERA5_Forcings_Generation.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step1_ERA5_Forcings_Generation.ipynb
new file mode 100644
index 00000000..f50dabf5
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step1_ERA5_Forcings_Generation.ipynb
@@ -0,0 +1,897 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e91181a8-c60f-456f-80cc-3923bf7c6a43",
+   "metadata": {},
+   "source": [
+    "# ERA5 Data generation & merging \n",
+    "\n",
+    "ERA5 data will be generated from 1970-2025, loaded and merged into one file"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "680410be-715a-4678-a4e3-c1141939241e",
+   "metadata": {},
+   "source": [
+    "## Start-up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "7ef3318e-968e-418e-bf4c-a8936aade9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# general python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "#niceties\n",
+    "from rich import print\n",
+    "\n",
+    "import yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "f7ff029b-ee4b-4fe2-b5d5-bf768b626989",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "cc4de849-39a5-40e6-9f4a-865da369e8b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'OBS6'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/data/shared/climate-data/obs6'</span><span style=\"font-weight: bold\">)]</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'default'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/data/shared/climate-data'</span><span style=\"font-weight: bold\">)]</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/.esmvaltool/downloads/CMIP6'</span><span style=\"font-weight: bold\">)]</span>\n",
+       "<span style=\"font-weight: bold\">}</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\n",
+       "    \u001b[32m'OBS6'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/data/shared/climate-data/obs6'\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+       "    \u001b[32m'default'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/data/shared/climate-data'\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+       "    \u001b[32m'CMIP6'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/.esmvaltool/downloads/CMIP6'\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'CMIP3'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP5'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CMIP6'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'CORDEX'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'obs4MIPs'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'ESGF'</span><span style=\"font-weight: bold\">}</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\u001b[32m'CMIP3'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'CMIP5'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'CMIP6'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'CORDEX'\u001b[0m: \u001b[32m'ESGF'\u001b[0m, \u001b[32m'obs4MIPs'\u001b[0m: \u001b[32m'ESGF'\u001b[0m\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Fix ERA5 config error\n",
+    "from esmvalcore.config import CFG   # older: from esmvalcore.experimental import CFG\n",
+    "from pathlib import Path\n",
+    "home = Path.home()\n",
+    "OBS6 = Path('/data/shared/climate-data/obs6')\n",
+    "default = Path('/data/shared/climate-data')\n",
+    "CMIP_path = Path(f'{str(home)}/.esmvaltool/downloads/CMIP6')\n",
+    "CFG['rootpath'] = {'OBS6': [OBS6], 'default': [default], 'CMIP6': [CMIP_path]}\n",
+    "print(CFG['rootpath'])\n",
+    "print(CFG['drs'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74c8c15e-8cab-4e1a-b6eb-c9c165d8c051",
+   "metadata": {},
+   "source": [
+    "### Define range & forcing paths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "b2343410-2713-4089-ae42-dad37b457c41",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ERA5-1989-1994</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/\u001b[0m\u001b[95mERA5-1989-1994\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1989</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m1989\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;36m2014\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining period range\n",
+    "# periods = [\n",
+    "#     [1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020],\n",
+    "#     [1974, 1979, 1984, 1989, 1994, 1999, 2004, 2009, 2014, 2019, 2024]]\n",
+    "\n",
+    "# For calibration 1:\n",
+    "# periods = [\n",
+    "#     [1990, 1995, 2000, 2005, 2010],\n",
+    "#     [1994, 1999, 2004, 2009, 2017]]\n",
+    "\n",
+    "# For calibration 2:\n",
+    "# periods = [\n",
+    "#     [1999, 2005, 2010, 2018],\n",
+    "#     [2004, 2009, 2017, 2019]]\n",
+    "\n",
+    "# For validation 1:\n",
+    "# periods = [\n",
+    "#     [2018, 2022],\n",
+    "#     [2021, 2024]]\n",
+    "\n",
+    "# For validation 2:\n",
+    "# periods = [\n",
+    "#     [2019, 2022],\n",
+    "#     [2021, 2024]]\n",
+    "\n",
+    "# For CMIP trial:\n",
+    "# periods = [\n",
+    "#     [1995, 2000, 2005, 2010],\n",
+    "#     [1999, 2004, 2009, 2014]]\n",
+    "\n",
+    "# For CMIP trial 2\n",
+    "# periods = [\n",
+    "#     [1970, 1975, 1980, 1985, 1990, 1995],\n",
+    "#     [1974, 1979, 1984, 1989, 1994, 1999]]\n",
+    "\n",
+    "periods = [\n",
+    "    [1989, 1995, 2000, 2005, 2010],\n",
+    "    [1994, 1999, 2004, 2009, 2014]]\n",
+    "\n",
+    "folder_names = []\n",
+    "forcing_paths = {}\n",
+    "\n",
+    "# Generate file names & paths\n",
+    "for i in range(len(periods[0])):\n",
+    "    start_year = periods[0][i]\n",
+    "    end_year = periods[1][i]\n",
+    "    \n",
+    "    folder_name = f'ERA5-{start_year}-{end_year}'                         # Add -cal or -val for cal and val folder name\n",
+    "    # forcing_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / folder_name\n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5\" / folder_name\n",
+    "\n",
+    "    folder_names.append(folder_name)\n",
+    "    forcing_paths[folder_name] = forcing_path\n",
+    "\n",
+    "    forcing_path.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "# Call path test\n",
+    "print(forcing_paths[folder_names[0]])\n",
+    "\n",
+    "start_year = periods[0][0]\n",
+    "end_year = periods[1][-1]\n",
+    "\n",
+    "print(start_year)\n",
+    "print(end_year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "619dd21a-0646-4bae-a71b-935f1fca8c04",
+   "metadata": {},
+   "source": [
+    "### Generate ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "cbc7b2b6-88ee-4e7f-b37c-39eaf878c075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Finished ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1989</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1994</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Finished ERA5-\u001b[1;36m1989\u001b[0m-\u001b[1;36m1994\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1995</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1999</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m1995\u001b[0m-\u001b[1;36m1999\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2000</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2004</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m2000\u001b[0m-\u001b[1;36m2004\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2005</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2009</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m2005\u001b[0m-\u001b[1;36m2009\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Skipping ERA5-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2010</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span> because the folder is not empty.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Skipping ERA5-\u001b[1;36m2010\u001b[0m-\u001b[1;36m2014\u001b[0m because the folder is not empty.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Shapefile path\n",
+    "# shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "# Generate forcing data\n",
+    "# for i in range(1):\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Change start year to start time so ERA5 can interpret it\n",
+    "    start_time_ERA5 = f'{periods[0][i]}-01-01T00:00:00Z'\n",
+    "    end_time_ERA5 = f'{periods[1][i]}-12-31T00:00:00Z'\n",
+    "\n",
+    "    # Skip if folder is not empty to prevent errors\n",
+    "    if any(forcing_paths[folder_names[i]].iterdir()):\n",
+    "        print(f\"Skipping {folder_names[i]} because the folder is not empty.\")\n",
+    "        continue\n",
+    "\n",
+    "    # Load forcings\n",
+    "    ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "        dataset=\"ERA5\",\n",
+    "        start_time=start_time_ERA5,\n",
+    "        end_time=end_time_ERA5,\n",
+    "        shape=shape_file,\n",
+    "        directory=forcing_paths[folder_names[i]])\n",
+    "\n",
+    "    # I need info because my patience is limited\n",
+    "    print(f\"Finished {folder_names[i]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91242ae4-3d21-4d18-815f-5cc986d5961e",
+   "metadata": {},
+   "source": [
+    "### Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "f8e8ac64-fee5-4602-a1f1-90b8fb14c2b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1989-1994'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-1995-1999'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-2000-2004'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-2005-2009'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'ERA5-2010-2014'</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[32m'ERA5-1989-1994'\u001b[0m, \u001b[32m'ERA5-1995-1999'\u001b[0m, \u001b[32m'ERA5-2000-2004'\u001b[0m, \u001b[32m'ERA5-2005-2009'\u001b[0m, \u001b[32m'ERA5-2010-2014'\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "LumpedMakkinkForcing(start_time='1989-01-01T00:00:00Z', end_time='1994-12-31T00:00:00Z', directory=PosixPath('/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/work/diagnostic/script'), shape=PosixPath('/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/work/diagnostic/script/07DA001_basin.shp'), filenames={'pr': 'OBS6_ERA5_reanaly_1_day_pr_1989-1994.nc', 'tas': 'OBS6_ERA5_reanaly_1_day_tas_1989-1994.nc', 'rsds': 'OBS6_ERA5_reanaly_1_day_rsds_1989-1994.nc', 'evspsblpot': 'Derived_Makkink_evspsblpot.nc'})"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ERA5_forcings = {}\n",
+    "\n",
+    "for i in range(len(folder_names)):\n",
+    "    # Create new path to find relevant files in the folder\n",
+    "    directory_new = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\"\n",
+    "    \n",
+    "    # Load forcings\n",
+    "    ERA5_forcings[folder_names[i]] = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=directory_new)\n",
+    "\n",
+    "# Test to see if it works\n",
+    "print(folder_names)\n",
+    "ERA5_forcings[folder_names[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8eddb25-06e3-4702-87e8-258aeda27a15",
+   "metadata": {},
+   "source": [
+    "### Merge ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "1cb12aa2-4b4c-4108-a5c9-2d8156cdecfe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Function to seperate files based on file names and combine same file names from different folders\n",
+    "def combine_variable(var_name):\n",
+    "    datasets = []\n",
+    "\n",
+    "    for i in range(len(folder_names)):\n",
+    "\n",
+    "        if var_name == \"evspsblpot\":\n",
+    "            file_name = \"Derived_Makkink_evspsblpot.nc\"\n",
+    "        else:\n",
+    "            file_name = f\"OBS6_ERA5_reanaly_1_day_{var_name}_{periods[0][i]}-{periods[1][i]}.nc\"\n",
+    "\n",
+    "        directory = forcing_paths[folder_names[i]] / \"work\" / \"diagnostic\" / \"script\" / file_name\n",
+    "\n",
+    "        print(f\"Loading {directory}\")\n",
+    "\n",
+    "        datasets.append(xr.open_dataset(directory))\n",
+    "\n",
+    "    combined = xr.concat(datasets, dim=\"time\")\n",
+    "    return combined"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "b21fe2e4-478a-4e0b-9f1f-a40316e22018",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1989-1994.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1989-1994.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_1995-1999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_1995-1999.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_2000-2004.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_2000-2004.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_2005-2009.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_2005-2009.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_pr_2010-2014.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_pr_2010-2014.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1989-1994.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1989-1994.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_1995-1999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_1995-1999.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_2000-2004.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_2000-2004.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_2005-2009.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_2005-2009.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_tas_2010-2014.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_tas_2010-2014.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1989-1994.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1989-1994.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_1995-1999.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_1995-1999.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_2000-2004.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_2000-2004.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_2005-2009.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_2005-2009.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">OBS6_ERA5_reanaly_1_day_rsds_2010-2014.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mOBS6_ERA5_reanaly_1_day_rsds_2010-2014.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1989-1994/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-1995-1999/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2000-2004/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2005-2009/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Loading \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w</span>\n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">ork/diagnostic/script/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">Derived_Makkink_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Loading \n",
+       "\u001b[35m/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forcings/ERA5/ERA5-2010-2014/w\u001b[0m\n",
+       "\u001b[35mork/diagnostic/script/\u001b[0m\u001b[95mDerived_Makkink_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Running function for various file name types\n",
+    "combined_variables = {}\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "# combined_path = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / f'ERA5-{periods[0][0]}-{periods[1][-1]}'\n",
+    "combined_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5\" / f'ERA5-{start_year}-{end_year}'\n",
+    "combined_path.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "    combined_variables[var_names[i]] = combine_variable(var_names[i])\n",
+    "    combined_variables[var_names[i]].to_netcdf(combined_path / f'combined_ERA5_{start_year}_{end_year}_{var_names[i]}.nc')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a439e818-0aa8-4e92-a189-fde70016a911",
+   "metadata": {},
+   "source": [
+    "### Create YAML file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "e60b3316-e100-4af9-a36d-fad721ef6e02",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create yaml\n",
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{start_year}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{end_year}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_ERA5_{start_year}_{end_year}_pr.nc\",\n",
+    "        \"tas\": f\"combined_ERA5_{start_year}_{end_year}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_ERA5_{start_year}_{end_year}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_ERA5_{start_year}_{end_year}_evspsblpot.nc\"}}\n",
+    "\n",
+    "# Save the YAML file\n",
+    "yaml_file_path = combined_path / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "10ff50bf-b6e7-4033-9682-3e25d01ecd26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1989-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">ngs/ERA5/ERA5-1989-2014'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">s/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1989_2014_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1989_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1989_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1989_2014_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1989-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci\u001b[0m\n",
+       "\u001b[32mngs/ERA5/ERA5-1989-2014'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile\u001b[0m\n",
+       "\u001b[32ms/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1989_2014_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1989_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1989_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1989_2014_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ERA5_combined_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=combined_path)\n",
+    "print(ERA5_combined_forcing)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step2_Algorithm_Ice.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step2_Algorithm_Ice.ipynb
new file mode 100644
index 00000000..7e927ad9
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step2_Algorithm_Ice.ipynb
@@ -0,0 +1,1173 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d3382417-3993-4e5d-8390-0c6cc4197326",
+   "metadata": {},
+   "source": [
+    "## Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "bb67d97e-8317-4b2f-be8e-c8ac9f45f196",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "862f09e2-4350-4eb5-8bdc-d865a99076eb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "4c68de36-ea9f-43be-aa9e-13fdd7b4a3ab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining time period & q_critical\n",
+    "\n",
+    "experiment_start_date = \"1970-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2024-12-31T00:00:00Z\"\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "hysets_id = \"hysets_07DA001\"\n",
+    "basin_size = 132572"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "bf6b9b66-876f-40da-8862-bd742448d87f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Loading in data\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5\" / \"ERA5-1970-2024\"\n",
+    "forcing_path_ERA5.mkdir(exist_ok=True, parents=True)\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "# Load CSV discharge 07DA001\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "b40fb132-370d-4584-b198-4a789d02abc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>14888</th>\n",
+       "      <td>1999-01-01</td>\n",
+       "      <td>104.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14889</th>\n",
+       "      <td>1999-01-02</td>\n",
+       "      <td>103.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14890</th>\n",
+       "      <td>1999-01-03</td>\n",
+       "      <td>101.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14891</th>\n",
+       "      <td>1999-01-04</td>\n",
+       "      <td>103.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14892</th>\n",
+       "      <td>1999-01-05</td>\n",
+       "      <td>105.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Date  discharge_m3s\n",
+       "14888 1999-01-01          104.0\n",
+       "14889 1999-01-02          103.0\n",
+       "14890 1999-01-03          101.0\n",
+       "14891 1999-01-04          103.0\n",
+       "14892 1999-01-05          105.0"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "q_obs = q_obs[\n",
+    "    (q_obs[\"Date\"] >= start_date) &\n",
+    "    (q_obs[\"Date\"] <= end_date)].copy()\n",
+    "\n",
+    "q_obs.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "eb8f1766-b180-4486-9cec-6539c086eb7f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"], label=\"Observed discharge\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f\"Critical discharge ({q_critical} m³/s)\", color='black')\n",
+    "\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "07a239a5-398f-4ad2-9a33-f2d199485309",
+   "metadata": {},
+   "source": [
+    "# Finding range"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9c87425e-c0d7-49ad-aab7-57bb5df5af0d",
+   "metadata": {},
+   "source": [
+    "## Start of range (freshet)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dc8791fb-3dac-425a-b5bd-45cdb8a0331f",
+   "metadata": {},
+   "source": [
+    "### Idea 1: Q_critical "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "727e107a-465a-4947-ba90-494ec323a262",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>first_above_critical_date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1999</td>\n",
+       "      <td>1999-04-20</td>\n",
+       "      <td>823.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2000</td>\n",
+       "      <td>2000-05-17</td>\n",
+       "      <td>561.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2001</td>\n",
+       "      <td>2001-05-04</td>\n",
+       "      <td>510.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2002</td>\n",
+       "      <td>2002-05-07</td>\n",
+       "      <td>600.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2003</td>\n",
+       "      <td>2003-04-26</td>\n",
+       "      <td>600.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2004</td>\n",
+       "      <td>2004-04-14</td>\n",
+       "      <td>533.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2005</td>\n",
+       "      <td>2005-04-10</td>\n",
+       "      <td>570.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2006</td>\n",
+       "      <td>2006-04-15</td>\n",
+       "      <td>591.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2007</td>\n",
+       "      <td>2007-04-20</td>\n",
+       "      <td>1200.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>2008-05-01</td>\n",
+       "      <td>520.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2009</td>\n",
+       "      <td>2009-04-20</td>\n",
+       "      <td>560.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2010</td>\n",
+       "      <td>2010-04-21</td>\n",
+       "      <td>525.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2011</td>\n",
+       "      <td>2011-04-26</td>\n",
+       "      <td>512.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2012</td>\n",
+       "      <td>2012-04-20</td>\n",
+       "      <td>520.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2013</td>\n",
+       "      <td>2013-05-01</td>\n",
+       "      <td>523.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>2014-04-23</td>\n",
+       "      <td>506.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2015</td>\n",
+       "      <td>2015-04-07</td>\n",
+       "      <td>719.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2016</td>\n",
+       "      <td>2016-04-29</td>\n",
+       "      <td>502.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2017</td>\n",
+       "      <td>2017-04-16</td>\n",
+       "      <td>518.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2018</td>\n",
+       "      <td>2018-04-26</td>\n",
+       "      <td>555.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2019</td>\n",
+       "      <td>2019-04-01</td>\n",
+       "      <td>503.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    year first_above_critical_date  discharge_m3s\n",
+       "0   1999                1999-04-20          823.0\n",
+       "1   2000                2000-05-17          561.0\n",
+       "2   2001                2001-05-04          510.0\n",
+       "3   2002                2002-05-07          600.0\n",
+       "4   2003                2003-04-26          600.0\n",
+       "5   2004                2004-04-14          533.0\n",
+       "6   2005                2005-04-10          570.0\n",
+       "7   2006                2006-04-15          591.0\n",
+       "8   2007                2007-04-20         1200.0\n",
+       "9   2008                2008-05-01          520.0\n",
+       "10  2009                2009-04-20          560.0\n",
+       "11  2010                2010-04-21          525.0\n",
+       "12  2011                2011-04-26          512.0\n",
+       "13  2012                2012-04-20          520.0\n",
+       "14  2013                2013-05-01          523.0\n",
+       "15  2014                2014-04-23          506.0\n",
+       "16  2015                2015-04-07          719.0\n",
+       "17  2016                2016-04-29          502.0\n",
+       "18  2017                2017-04-16          518.0\n",
+       "19  2018                2018-04-26          555.0\n",
+       "20  2019                2019-04-01          503.0"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create pd for identified critical dates\n",
+    "\n",
+    "freshet_start_date = []\n",
+    "\n",
+    "for year, group in q_obs.groupby(q_obs[\"Date\"].dt.year):\n",
+    "\n",
+    "    # Set start date to March 1\n",
+    "    start_date_algorithm = pd.to_datetime(f\"{year}-03-01\")\n",
+    "    season_data = group[group[\"Date\"] >= start_date_algorithm].copy()\n",
+    "    \n",
+    "    # Identify first day where q > q_critical\n",
+    "    \n",
+    "    above_critical = season_data[\n",
+    "        season_data[\"discharge_m3s\"] > q_critical]\n",
+    "    \n",
+    "    if len(above_critical) > 0:\n",
+    "        first_day = above_critical.iloc[0]\n",
+    "        \n",
+    "        freshet_start_date.append({\n",
+    "            \"year\": year,\n",
+    "            \"first_above_critical_date\": first_day[\"Date\"],\n",
+    "            \"discharge_m3s\": first_day[\"discharge_m3s\"]})\n",
+    "\n",
+    "freshet_start_date = pd.DataFrame(freshet_start_date)\n",
+    "\n",
+    "freshet_start_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "e20e293c-245d-47da-9b45-1c9675f989f4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_discharge_for_year(q_obs, freshet_start_date, q_critical, selected_year):\n",
+    "\n",
+    "    # Define plotting period to selected year\n",
+    "    start_date = f\"{selected_year}-01-01\"\n",
+    "    end_date = f\"{selected_year}-12-31\"\n",
+    "\n",
+    "    # Adjust q_obs and freshet_start_date to fit plotting period\n",
+    "    q_obs_year = q_obs[\n",
+    "        (q_obs[\"Date\"] >= start_date) &\n",
+    "        (q_obs[\"Date\"] <= end_date)]\n",
+    "\n",
+    "    freshet_year = freshet_start_date[\n",
+    "        (freshet_start_date[\"first_above_critical_date\"] >= start_date) &\n",
+    "        (freshet_start_date[\"first_above_critical_date\"] <= end_date)]\n",
+    "\n",
+    "    # Start figure\n",
+    "    plt.figure(figsize=(12, 5))\n",
+    "\n",
+    "    # Plot q_obs\n",
+    "    plt.plot(q_obs_year[\"Date\"], q_obs_year[\"discharge_m3s\"], label=\"Observed discharge\")\n",
+    "\n",
+    "    # Plot q_critical\n",
+    "    plt.axhline(y=q_critical, linestyle=\":\", label=f\"Critical discharge ({q_critical} m³/s)\", color=\"black\")\n",
+    "\n",
+    "    # Plot when q_critical is reached\n",
+    "    for date in freshet_year[\"first_above_critical_date\"].dropna():\n",
+    "        plt.axvline(x=date, linestyle=':', color='orange', label='Start navigable season')\n",
+    "\n",
+    "    plt.xlabel(\"Date\")\n",
+    "    plt.ylabel(\"Discharge (m³/s)\")\n",
+    "    plt.title(f\"Observed daily discharge at 07DA001 in {selected_year}\")\n",
+    "\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "356ed65e-463c-486b-ac4a-a0d9c44cbfda",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "selected_year = 2014\n",
+    "\n",
+    "plot_discharge_for_year(q_obs, freshet_start_date, q_critical, selected_year)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "39bd4c7f-1a15-464d-bddd-6c3e05088566",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Convert date to day of year\n",
+    "freshet_start_date[\"day_of_year\"] = (freshet_start_date[\"first_above_critical_date\"].dt.dayofyear)\n",
+    "\n",
+    "# Make plot \n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.scatter(freshet_start_date[\"day_of_year\"], freshet_start_date[\"year\"], marker=\"o\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Year\")\n",
+    "plt.title(\"First date discharge exceeds critical threshold between 1970-2024\")\n",
+    "plt.grid(True)\n",
+    "\n",
+    "# Convert day of year to day in months (on the axis)\n",
+    "plt.xticks(\n",
+    "    [60, 65, 70, 75, 80, 85, 90,\n",
+    "     95, 100, 105, 110, 115, 120,\n",
+    "     125, 130, 135, 140, 145, 150],\n",
+    "    [\"Mar 1\", \"Mar 6\", \"Mar 11\", \"Mar 16\", \"Mar 21\", \"Mar 26\", \"Mar 31\",\n",
+    "     \"Apr 5\", \"Apr 10\", \"Apr 15\", \"Apr 20\", \"Apr 25\", \"Apr 30\",\n",
+    "     \"May 5\", \"May 10\", \"May 15\", \"May 20\", \"May 25\", \"May 30\"],)\n",
+    "\n",
+    "# Automate x-axis range to fit data\n",
+    "plt.xlim((freshet_start_date[\"day_of_year\"].min()-1), (freshet_start_date[\"day_of_year\"].max()+1))\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "1bf87b1f-7a42-4819-af63-2dc95649c8fb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Creating bar graph\n",
+    "\n",
+    "# Choose bin size\n",
+    "bin_size = 5   # use 10 for 10-day periods\n",
+    "\n",
+    "# Convert date to day of year\n",
+    "freshet_start_date[\"day_of_year\"] = freshet_start_date[\"first_above_critical_date\"].dt.dayofyear\n",
+    "\n",
+    "# Create bins\n",
+    "freshet_start_date[\"date_bin\"] = (freshet_start_date[\"day_of_year\"] // bin_size) * bin_size\n",
+    "\n",
+    "# Count how many years fall in each bin\n",
+    "freshet_counts = freshet_start_date.groupby(\"date_bin\").size()\n",
+    "\n",
+    "# Plot bar chart\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.bar(freshet_counts.index, freshet_counts.values, width=bin_size)\n",
+    "\n",
+    "# Convert x-axis from day-of-year to calendar dates\n",
+    "tick_days = freshet_counts.index\n",
+    "tick_labels = [\n",
+    "    (pd.to_datetime(\"2001-01-01\") + pd.to_timedelta(day - 1, unit=\"D\")).strftime(\"%b %d\")\n",
+    "    for day in tick_days]\n",
+    "\n",
+    "plt.xticks(tick_days, tick_labels, rotation=45)\n",
+    "\n",
+    "plt.xlabel(\"Date period\")\n",
+    "plt.ylabel(\"Number of years\")\n",
+    "plt.title(\"First date discharge exceeds critical threshold\")\n",
+    "plt.grid(axis=\"y\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d32414f7-d742-48cb-9d94-50441c3f550c",
+   "metadata": {},
+   "source": [
+    "## End of range (river freeze-up)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f912ae02-7887-4bf3-af61-0ccc4c154fef",
+   "metadata": {},
+   "source": [
+    "### Idea 1: Critical when AFDD = x\n",
+    "\n",
+    "AFDD is Accumulated Freeze Degree Days. It calculates the accumulative temperature under 0. \n",
+    "Example: If 3 days have a mean temperature of -5 C per day, the AFDD would be 15. \n",
+    "\n",
+    "A study shows the LAR forms an ice sheet when AFDD reaches (approx) 50 degrees. https://www.iahr.org/library/infor?pid=26767 (Figure 6)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7aa6524c-9140-4756-bfc9-c67947740a8e",
+   "metadata": {},
+   "source": [
+    "### Load ERA5-forcings & TAS data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "9e315bb0-0085-43e0-b0a0-0d23d6bc4ba0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate ERA5 data\n",
+    "\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "#     directory=forcing_path_ERA5\n",
+    "# )\n",
+    "\n",
+    "# Load ERA5 data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "e90fb4e3-9f06-405c-bc08-fcbc28c0ef7c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Exract tas file from Era5\n",
+    "tas_file = Path(ERA5_forcing.directory) / ERA5_forcing.filenames[\"tas\"]\n",
+    "\n",
+    "# Extract tas data from tas file\n",
+    "temp_data = xr.open_dataset(tas_file)[\"tas\"]\n",
+    "\n",
+    "# Convert to panda\n",
+    "temp_data = temp_data.to_series()\n",
+    "temp_data.index = pd.to_datetime(temp_data.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Convert Kelvin to Celsius:\n",
+    "temp_data = temp_data - 273.15\n",
+    "\n",
+    "# Create dataframe with Date, Temp & year as columns\n",
+    "temp_data = pd.DataFrame({\n",
+    "    \"Date\": temp_data.index,\n",
+    "    \"Temp\": temp_data.values,\n",
+    "    \"year\": temp_data.index.year})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "54ebf5d5-9ad6-4a37-8301-f204b1059c06",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">    year AFDD_critical_date       AFDD       Temp\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1999</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1999</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30.221619</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.962982</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2000</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2000</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">06</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36.068024</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-10.174591</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2001</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2001</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30.810608</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.809998</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2002</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2002</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33.166534</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-5.441467</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2003</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2003</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">01</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34.717468</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-7.344391</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2004</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2004</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31.703094</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-4.081665</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2005</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2005</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30.604706</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-5.060822</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2006</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2006</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31.405975</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-8.236450</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2007</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2007</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33.085419</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-3.336060</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2008</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2008</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33.410309</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-4.401947</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2009</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2009</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31.520508</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-7.005463</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2010</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2010</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33.449890</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-3.697540</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2011</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2011</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">08</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31.026093</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-2.132233</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2012</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2012</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30.493774</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-4.729126</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2013</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2013</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">05</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34.175323</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-10.181244</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2014</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41.426453</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-13.859253</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2015</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2015</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33.754425</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-3.863159</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2016</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2016</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">01</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31.235596</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-3.254517</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2017</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2017</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">03</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">42.753876</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-14.209076</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2018</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2018</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">02</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32.042358</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-2.240051</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2019</span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2019</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">29</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41.300140</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-11.644196</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "    year AFDD_critical_date       AFDD       Temp\n",
+       "\u001b[1;36m0\u001b[0m   \u001b[1;36m1999\u001b[0m         \u001b[1;36m1999\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m13\u001b[0m  \u001b[1;36m30.221619\u001b[0m  \u001b[1;36m-1.962982\u001b[0m\n",
+       "\u001b[1;36m1\u001b[0m   \u001b[1;36m2000\u001b[0m         \u001b[1;36m2000\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m06\u001b[0m  \u001b[1;36m36.068024\u001b[0m \u001b[1;36m-10.174591\u001b[0m\n",
+       "\u001b[1;36m2\u001b[0m   \u001b[1;36m2001\u001b[0m         \u001b[1;36m2001\u001b[0m-\u001b[1;36m10\u001b[0m-\u001b[1;36m30\u001b[0m  \u001b[1;36m30.810608\u001b[0m  \u001b[1;36m-1.809998\u001b[0m\n",
+       "\u001b[1;36m3\u001b[0m   \u001b[1;36m2002\u001b[0m         \u001b[1;36m2002\u001b[0m-\u001b[1;36m10\u001b[0m-\u001b[1;36m28\u001b[0m  \u001b[1;36m33.166534\u001b[0m  \u001b[1;36m-5.441467\u001b[0m\n",
+       "\u001b[1;36m4\u001b[0m   \u001b[1;36m2003\u001b[0m         \u001b[1;36m2003\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m01\u001b[0m  \u001b[1;36m34.717468\u001b[0m  \u001b[1;36m-7.344391\u001b[0m\n",
+       "\u001b[1;36m5\u001b[0m   \u001b[1;36m2004\u001b[0m         \u001b[1;36m2004\u001b[0m-\u001b[1;36m10\u001b[0m-\u001b[1;36m22\u001b[0m  \u001b[1;36m31.703094\u001b[0m  \u001b[1;36m-4.081665\u001b[0m\n",
+       "\u001b[1;36m6\u001b[0m   \u001b[1;36m2005\u001b[0m         \u001b[1;36m2005\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m12\u001b[0m  \u001b[1;36m30.604706\u001b[0m  \u001b[1;36m-5.060822\u001b[0m\n",
+       "\u001b[1;36m7\u001b[0m   \u001b[1;36m2006\u001b[0m         \u001b[1;36m2006\u001b[0m-\u001b[1;36m10\u001b[0m-\u001b[1;36m31\u001b[0m  \u001b[1;36m31.405975\u001b[0m  \u001b[1;36m-8.236450\u001b[0m\n",
+       "\u001b[1;36m8\u001b[0m   \u001b[1;36m2007\u001b[0m         \u001b[1;36m2007\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m14\u001b[0m  \u001b[1;36m33.085419\u001b[0m  \u001b[1;36m-3.336060\u001b[0m\n",
+       "\u001b[1;36m9\u001b[0m   \u001b[1;36m2008\u001b[0m         \u001b[1;36m2008\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m17\u001b[0m  \u001b[1;36m33.410309\u001b[0m  \u001b[1;36m-4.401947\u001b[0m\n",
+       "\u001b[1;36m10\u001b[0m  \u001b[1;36m2009\u001b[0m         \u001b[1;36m2009\u001b[0m-\u001b[1;36m10\u001b[0m-\u001b[1;36m12\u001b[0m  \u001b[1;36m31.520508\u001b[0m  \u001b[1;36m-7.005463\u001b[0m\n",
+       "\u001b[1;36m11\u001b[0m  \u001b[1;36m2010\u001b[0m         \u001b[1;36m2010\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m12\u001b[0m  \u001b[1;36m33.449890\u001b[0m  \u001b[1;36m-3.697540\u001b[0m\n",
+       "\u001b[1;36m12\u001b[0m  \u001b[1;36m2011\u001b[0m         \u001b[1;36m2011\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m08\u001b[0m  \u001b[1;36m31.026093\u001b[0m  \u001b[1;36m-2.132233\u001b[0m\n",
+       "\u001b[1;36m13\u001b[0m  \u001b[1;36m2012\u001b[0m         \u001b[1;36m2012\u001b[0m-\u001b[1;36m10\u001b[0m-\u001b[1;36m25\u001b[0m  \u001b[1;36m30.493774\u001b[0m  \u001b[1;36m-4.729126\u001b[0m\n",
+       "\u001b[1;36m14\u001b[0m  \u001b[1;36m2013\u001b[0m         \u001b[1;36m2013\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m05\u001b[0m  \u001b[1;36m34.175323\u001b[0m \u001b[1;36m-10.181244\u001b[0m\n",
+       "\u001b[1;36m15\u001b[0m  \u001b[1;36m2014\u001b[0m         \u001b[1;36m2014\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m10\u001b[0m  \u001b[1;36m41.426453\u001b[0m \u001b[1;36m-13.859253\u001b[0m\n",
+       "\u001b[1;36m16\u001b[0m  \u001b[1;36m2015\u001b[0m         \u001b[1;36m2015\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m17\u001b[0m  \u001b[1;36m33.754425\u001b[0m  \u001b[1;36m-3.863159\u001b[0m\n",
+       "\u001b[1;36m17\u001b[0m  \u001b[1;36m2016\u001b[0m         \u001b[1;36m2016\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m01\u001b[0m  \u001b[1;36m31.235596\u001b[0m  \u001b[1;36m-3.254517\u001b[0m\n",
+       "\u001b[1;36m18\u001b[0m  \u001b[1;36m2017\u001b[0m         \u001b[1;36m2017\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m03\u001b[0m  \u001b[1;36m42.753876\u001b[0m \u001b[1;36m-14.209076\u001b[0m\n",
+       "\u001b[1;36m19\u001b[0m  \u001b[1;36m2018\u001b[0m         \u001b[1;36m2018\u001b[0m-\u001b[1;36m11\u001b[0m-\u001b[1;36m02\u001b[0m  \u001b[1;36m32.042358\u001b[0m  \u001b[1;36m-2.240051\u001b[0m\n",
+       "\u001b[1;36m20\u001b[0m  \u001b[1;36m2019\u001b[0m         \u001b[1;36m2019\u001b[0m-\u001b[1;36m10\u001b[0m-\u001b[1;36m29\u001b[0m  \u001b[1;36m41.300140\u001b[0m \u001b[1;36m-11.644196\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>AFDD_critical_date</th>\n",
+       "      <th>AFDD</th>\n",
+       "      <th>Temp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1999</td>\n",
+       "      <td>1999-11-13</td>\n",
+       "      <td>30.221619</td>\n",
+       "      <td>-1.962982</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2000</td>\n",
+       "      <td>2000-11-06</td>\n",
+       "      <td>36.068024</td>\n",
+       "      <td>-10.174591</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2001</td>\n",
+       "      <td>2001-10-30</td>\n",
+       "      <td>30.810608</td>\n",
+       "      <td>-1.809998</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2002</td>\n",
+       "      <td>2002-10-28</td>\n",
+       "      <td>33.166534</td>\n",
+       "      <td>-5.441467</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2003</td>\n",
+       "      <td>2003-11-01</td>\n",
+       "      <td>34.717468</td>\n",
+       "      <td>-7.344391</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2004</td>\n",
+       "      <td>2004-10-22</td>\n",
+       "      <td>31.703094</td>\n",
+       "      <td>-4.081665</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2005</td>\n",
+       "      <td>2005-11-12</td>\n",
+       "      <td>30.604706</td>\n",
+       "      <td>-5.060822</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2006</td>\n",
+       "      <td>2006-10-31</td>\n",
+       "      <td>31.405975</td>\n",
+       "      <td>-8.236450</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2007</td>\n",
+       "      <td>2007-11-14</td>\n",
+       "      <td>33.085419</td>\n",
+       "      <td>-3.336060</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>2008-11-17</td>\n",
+       "      <td>33.410309</td>\n",
+       "      <td>-4.401947</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2009</td>\n",
+       "      <td>2009-10-12</td>\n",
+       "      <td>31.520508</td>\n",
+       "      <td>-7.005463</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2010</td>\n",
+       "      <td>2010-11-12</td>\n",
+       "      <td>33.449890</td>\n",
+       "      <td>-3.697540</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2011</td>\n",
+       "      <td>2011-11-08</td>\n",
+       "      <td>31.026093</td>\n",
+       "      <td>-2.132233</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2012</td>\n",
+       "      <td>2012-10-25</td>\n",
+       "      <td>30.493774</td>\n",
+       "      <td>-4.729126</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2013</td>\n",
+       "      <td>2013-11-05</td>\n",
+       "      <td>34.175323</td>\n",
+       "      <td>-10.181244</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>2014-11-10</td>\n",
+       "      <td>41.426453</td>\n",
+       "      <td>-13.859253</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2015</td>\n",
+       "      <td>2015-11-17</td>\n",
+       "      <td>33.754425</td>\n",
+       "      <td>-3.863159</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2016</td>\n",
+       "      <td>2016-11-01</td>\n",
+       "      <td>31.235596</td>\n",
+       "      <td>-3.254517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2017</td>\n",
+       "      <td>2017-11-03</td>\n",
+       "      <td>42.753876</td>\n",
+       "      <td>-14.209076</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2018</td>\n",
+       "      <td>2018-11-02</td>\n",
+       "      <td>32.042358</td>\n",
+       "      <td>-2.240051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2019</td>\n",
+       "      <td>2019-10-29</td>\n",
+       "      <td>41.300140</td>\n",
+       "      <td>-11.644196</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    year AFDD_critical_date       AFDD       Temp\n",
+       "0   1999         1999-11-13  30.221619  -1.962982\n",
+       "1   2000         2000-11-06  36.068024 -10.174591\n",
+       "2   2001         2001-10-30  30.810608  -1.809998\n",
+       "3   2002         2002-10-28  33.166534  -5.441467\n",
+       "4   2003         2003-11-01  34.717468  -7.344391\n",
+       "5   2004         2004-10-22  31.703094  -4.081665\n",
+       "6   2005         2005-11-12  30.604706  -5.060822\n",
+       "7   2006         2006-10-31  31.405975  -8.236450\n",
+       "8   2007         2007-11-14  33.085419  -3.336060\n",
+       "9   2008         2008-11-17  33.410309  -4.401947\n",
+       "10  2009         2009-10-12  31.520508  -7.005463\n",
+       "11  2010         2010-11-12  33.449890  -3.697540\n",
+       "12  2011         2011-11-08  31.026093  -2.132233\n",
+       "13  2012         2012-10-25  30.493774  -4.729126\n",
+       "14  2013         2013-11-05  34.175323 -10.181244\n",
+       "15  2014         2014-11-10  41.426453 -13.859253\n",
+       "16  2015         2015-11-17  33.754425  -3.863159\n",
+       "17  2016         2016-11-01  31.235596  -3.254517\n",
+       "18  2017         2017-11-03  42.753876 -14.209076\n",
+       "19  2018         2018-11-02  32.042358  -2.240051\n",
+       "20  2019         2019-10-29  41.300140 -11.644196"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "AFDD_critical = 30\n",
+    "AFDD_critical_dates = []\n",
+    "\n",
+    "start_year = start_date.year\n",
+    "end_year = end_date.year\n",
+    "\n",
+    "for year in range(start_year, end_year + 1):\n",
+    "\n",
+    "    # Set start date to 1 October\n",
+    "    year_data = temp_data[\n",
+    "        (temp_data[\"year\"] == year) &\n",
+    "        (temp_data[\"Date\"] >= pd.to_datetime(f\"{year}-10-01\"))]\n",
+    "\n",
+    "    AFDD = 0\n",
+    "    \n",
+    "    # Isolate datasets of date & temperature data to each year \n",
+    "    for i in range(len(year_data)):\n",
+    "        temp = year_data.iloc[i][\"Temp\"]\n",
+    "        date = year_data.iloc[i][\"Date\"]\n",
+    "\n",
+    "        # Cumulative AFDD\n",
+    "        if temp < 0:\n",
+    "            AFDD += -temp\n",
+    "\n",
+    "        # Append when AFDD is critical\n",
+    "        if AFDD >= AFDD_critical:\n",
+    "            AFDD_critical_dates.append({\n",
+    "                \"year\": year,\n",
+    "                \"AFDD_critical_date\": date,\n",
+    "                \"AFDD\": AFDD,\n",
+    "                \"Temp\": temp\n",
+    "            })\n",
+    "\n",
+    "            break \n",
+    "\n",
+    "AFDD_critical_dates = pd.DataFrame(AFDD_critical_dates)\n",
+    "\n",
+    "print(AFDD_critical_dates)\n",
+    "\n",
+    "AFDD_critical_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "861083f4-0521-4186-a73d-9c2aca2befa3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Convert date to day of year\n",
+    "AFDD_critical_dates[\"day_of_year\"] = (AFDD_critical_dates[\"AFDD_critical_date\"].dt.dayofyear)\n",
+    "\n",
+    "# Make plot \n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.scatter(AFDD_critical_dates[\"day_of_year\"], AFDD_critical_dates[\"year\"], marker=\"o\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Year\")\n",
+    "plt.title(f\"Date of river freeze-up (AFDD >= {AFDD_critical}) between 1970-2024\")\n",
+    "plt.grid(True)\n",
+    "\n",
+    "# Convert day of year to day in months (on the axis)\n",
+    "plt.xticks(\n",
+    "    [274, 279, 284, 289, 294, 299, 304,\n",
+    "     309, 314, 319, 324, 329, 334, 339,\n",
+    "     344, 349, 354, 359, 364, 366],\n",
+    "    [\"Oct 1\", \"Oct 6\", \"Oct 11\", \"Oct 16\", \"Oct 21\", \"Oct 26\", \"Oct 31\",\n",
+    "     \"Nov 5\", \"Nov 10\", \"Nov 15\", \"Nov 20\", \"Nov 25\", \"Nov 30\", \"Dec 5\",\n",
+    "     \"Dec 10\", \"Dec 15\", \"Dec 20\", \"Dec 25\", \"Dec 30\", \"Dec 31\"],)\n",
+    "\n",
+    "# Prevent y-axis from showing decimal years\n",
+    "plt.yticks(range(start_year, end_year + 1))\n",
+    "\n",
+    "# Automate x-axis range to fit data\n",
+    "plt.xlim((AFDD_critical_dates[\"day_of_year\"].min()-1), (AFDD_critical_dates[\"day_of_year\"].max()+1))\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "7995d878-10ac-4e6e-aa0f-b8e281d5aaf6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot temp for 1 year for fun:\n",
+    "selected_year = 2014\n",
+    "year_data = temp_data[temp_data[\"year\"] == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.title(f\"Temperature time series showing date of river freeze-up (AFDD >= {AFDD_critical}) for 2014\")\n",
+    "plt.scatter(year_data[\"Date\"], year_data[\"Temp\"], marker=\"o\")\n",
+    "plt.axhline(y=0, linestyle=\":\", color=\"black\", label=\"0°C\")\n",
+    "\n",
+    "# Extract & plot critical AFDD date for selected year\n",
+    "AFDD_critical_date = AFDD_critical_dates.loc[AFDD_critical_dates[\"year\"] == selected_year, \"AFDD_critical_date\"].iloc[0]\n",
+    "plt.axvline(x=AFDD_critical_date, linestyle=\":\", color=\"orange\", label=\"River freeze-up\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Temperature (°C)\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5b3a1903-f809-45da-ad01-13313da0afea",
+   "metadata": {},
+   "source": [
+    "### Idea 2: Critical when q_critical < 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6e7f55d8-67b3-4721-912b-511875ecdbb4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a0f3c170-d57e-4d00-80c0-1bc1f090b940",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f655679f-10de-42bf-88b9-ef58385bd62c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c6b724d3-19f0-4ec3-9bb6-1828e22b320d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "078fc0ee-197a-45de-87b5-9a00eec5801f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fabbb9d8-1446-474d-b329-83c221d3f018",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step3_Calibration_HBV.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step3_Calibration_HBV.ipynb
new file mode 100644
index 00000000..48aa921d
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step3_Calibration_HBV.ipynb
@@ -0,0 +1,9004 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fbc7f454-3d60-492d-aa6c-0ce21a0dfc77",
+   "metadata": {},
+   "source": [
+    "## Startup\n",
+    "\n",
+    "\n",
+    "80/20 rule:\n",
+    "80% calibration (2000-2020)\n",
+    "20% validation (2020-2025)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "95a06f73-282f-4c7c-8333-f002e73e205a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print\n",
+    "\n",
+    "from ipywidgets import IntProgress\n",
+    "from IPython.display import display"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8b61a012-64eb-48b2-ba78-f641a1a581a3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a860a623-f634-4b50-822c-51e09ab4e594",
+   "metadata": {},
+   "source": [
+    "### Defining variables & pathways"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "970798cd-b737-44f3-8edd-de3352b86efd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period & basin si\n",
+    "\n",
+    "experiment_start_date = \"2000-01-01T00:00:00Z\"\n",
+    "experiment_end_date = \"2005-12-31T00:00:00Z\"\n",
+    "\n",
+    "calibration_start = \"1999-01-01T00:00:00Z\"\n",
+    "calibration_end = \"2019-12-31T00:00:00Z\"\n",
+    "\n",
+    "# validation_start = \"\"\n",
+    "# validation_end = \"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "241efaf0-94fc-4e07-8a62-151661dc4343",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"ERA5\" / \"ERA5-1999-2019\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "basin_size = 132572\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd4ec71b-d4f6-4a1c-be9a-f8d3b89059d1",
+   "metadata": {},
+   "source": [
+    "### Load & prepare discharge data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "d590f365-72ad-4473-9996-88820ea52c18",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1cec4b74-037a-4d48-8769-e0b57a7683aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Filter q_obs to start & end date\n",
+    "\n",
+    "# start_date = pd.to_datetime(experiment_start_date.replace(\"Z\", \"\"))\n",
+    "# end_date = pd.to_datetime(experiment_end_date.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# q_obs = q_obs[(q_obs[\"Date\"] >= start_date) & (q_obs[\"Date\"] <= end_date)]\n",
+    "# observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7c47f7f-18ff-4441-b1d4-975e46e1719b",
+   "metadata": {},
+   "source": [
+    "### Generate or Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "eb582ebf-8fbc-4542-b785-cee2f332bdd5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1999-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1999-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2019-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/ERA5-1999-2019'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load ERA5 data\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6fc290da-fa08-48f0-83e3-a39e8f5c36ef",
+   "metadata": {},
+   "source": [
+    "## Calibration Methods"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba51d28d-1fdb-46af-8f8e-5dcf904aba7f",
+   "metadata": {},
+   "source": [
+    "### Method 1: NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "9ff8dc21-0959-49a4-9d4b-496726c90f88",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def NSE(sim, obs):\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    return 1 - np.sum((obs - sim) ** 2) / np.sum((obs - np.mean(obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "93f96591-ceb4-4671-9a48-04a0ddbfaf5a",
+   "metadata": {},
+   "source": [
+    "### Method 2: Log_NSE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "826cfb65-21ba-4901-aafe-37738913c0ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def log_NSE(sim, obs):\n",
+    "    # Convert for easy calculations\n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8dc2e27c-2caa-493a-8ad0-3a8540ff4a18",
+   "metadata": {},
+   "source": [
+    "### Define Parameters & Storages and Times"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "2ed6540e-ec2f-4f80-975f-66fee4b2a75a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define initial storages\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])\n",
+    "\n",
+    "# Define parameters (range)\n",
+    "parameter_ranges = {\n",
+    "    \"Imax\":  (5.5, 8),            # Maximum interception storage\n",
+    "    \"Ce\":    (0.35, 0.6),       # Evaporation correction factor\n",
+    "    \"Sumax\": (150, 220),         # Maximum soil moisture storage\n",
+    "    \"Beta\":  (1.6, 2),          # Soil runoff parameter\n",
+    "    \"Pmax\":  (0.1, 0.6),            # Maximum percolation rate\n",
+    "    \"Tlag\":  (5.2, 7),           # Time lag\n",
+    "    \"Kf\":    (0.01, 0.1),       # Fast reservoir recession coefficient\n",
+    "    \"Ks\":    (0.001, 0.1),     # Slow reservoir recession coefficient\n",
+    "    \"FM\":    (0.3, 1.4),          # Snowmelt factor\n",
+    "}\n",
+    "\n",
+    "# Convert to arrays\n",
+    "parameter_names = list(parameter_ranges.keys())\n",
+    "\n",
+    "p_min = np.array([parameter_ranges[name][0] for name in parameter_names])\n",
+    "p_max = np.array([parameter_ranges[name][1] for name in parameter_names])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fc6ef77d-95ba-4277-ab8c-654fa025894d",
+   "metadata": {},
+   "source": [
+    "### Create samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "47df771f-85c1-40a7-9e28-a6dfb3134514",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.85285914e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.89990216e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.76127959e+02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.92058774e+00</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.56024109e-01</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.99810960e+00</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.01314564e-02</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.63774925e-02</span>\n",
+       " <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.62585104e-01</span><span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\u001b[1;36m7.85285914e+00\u001b[0m \u001b[1;36m3.89990216e-01\u001b[0m \u001b[1;36m1.76127959e+02\u001b[0m \u001b[1;36m1.92058774e+00\u001b[0m\n",
+       " \u001b[1;36m5.56024109e-01\u001b[0m \u001b[1;36m6.99810960e+00\u001b[0m \u001b[1;36m3.01314564e-02\u001b[0m \u001b[1;36m6.63774925e-02\u001b[0m\n",
+       " \u001b[1;36m9.62585104e-01\u001b[0m\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Create samples\n",
+    "N = 10\n",
+    "par_samples = np.random.rand(N, len(parameter_ranges))                  # Generates random values between 0-1\n",
+    "parameter_sets = p_min + par_samples * (p_max - p_min)                  # Fits value to parameter range\n",
+    "\n",
+    "print(parameter_sets[:][0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e22418a9-e4ba-4890-85a8-abcfd66c85f2",
+   "metadata": {},
+   "source": [
+    "### Define time period"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "9c72add6-8b9f-4b3e-9e9f-77406215c196",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "calibration_start_date = pd.to_datetime(calibration_start.replace(\"Z\", \"\"))\n",
+    "calibration_end_date = pd.to_datetime(calibration_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for calibration\n",
+    "evaluation_start = pd.to_datetime(f\"{calibration_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= calibration_start_date) & (q_obs[\"Date\"] <= calibration_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "645d5bb0-de70-4b97-9aa0-93094c91ebe6",
+   "metadata": {},
+   "source": [
+    "## Calibration start function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "0f58e61f-7178-44f8-8e5e-e1fa402813c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create function to run the model\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Create model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Create config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config)\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs \n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m, \n",
+    "        index=time, \n",
+    "        name=\"Modelled discharge\")\n",
+    "    \n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e93b5d4-0a92-4d09-b135-07101e614d9e",
+   "metadata": {},
+   "source": [
+    "### Run HBV loop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "577e23e5-8db6-45a1-b91b-aae3a46b6c12",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1ce6bc7773174ef98c9608eb840d31a4",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "IntProgress(value=0, max=600)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m6\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m7\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m8\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m9\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m10\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m11\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m12\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m13\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m14\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m15\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m16\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m17\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m18\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m19\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m20\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">21</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m21\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m22\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">23</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m23\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m24\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m25\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">26</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m26\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m27\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m28\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">29</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m29\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m30\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m31\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m32\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m33\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m34\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">35</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m35\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m36\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">37</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m37\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">38</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m38\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">39</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m39\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">40</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m40\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">41</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m41\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">42</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m42\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">43</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m43\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">44</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m44\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">45</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m45\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">46</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m46\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">47</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m47\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m48\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m49\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">50</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m50\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">51</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m51\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m52\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">53</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m53\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">54</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m54\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">55</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m55\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">56</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m56\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">57</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m57\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">58</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m58\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">59</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m59\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">60</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m60\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">61</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m61\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">62</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m62\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">63</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m63\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m64\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">65</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m65\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">66</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m66\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">67</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m67\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">68</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m68\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">69</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m69\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">70</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m70\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m71\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">72</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m72\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">73</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m73\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m74\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">75</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m75\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">76</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m76\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">77</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m77\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">78</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m78\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">79</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m79\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">80</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m80\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">81</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m81\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">82</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m82\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">83</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m83\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">84</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m84\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">85</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m85\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">86</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m86\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">87</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m87\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">88</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m88\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">89</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m89\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">90</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m90\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m91\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">92</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m92\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">93</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m93\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">94</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m94\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">95</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m95\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">96</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m96\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">97</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m97\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">98</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m98\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">99</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m99\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">100</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m100\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">101</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m101\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">102</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m102\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">103</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m103\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">104</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m104\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">105</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m105\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">106</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m106\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">107</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m107\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">108</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m108\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">109</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m109\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">110</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m110\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">111</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m111\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">112</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m112\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">113</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m113\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">114</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m114\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">115</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m115\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">116</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m116\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">117</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m117\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">118</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m118\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">119</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m119\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">120</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m120\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">121</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m121\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">122</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m122\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">123</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m123\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">124</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m124\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">125</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m125\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">126</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m126\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">127</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m127\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">128</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m128\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">129</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m129\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">130</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m130\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">131</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m131\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">132</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m132\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">133</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m133\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">134</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m134\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">135</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m135\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">136</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m136\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">137</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m137\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">138</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m138\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">139</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m139\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">140</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m140\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">141</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m141\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">142</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m142\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">143</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m143\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">144</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m144\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">145</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m145\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">146</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m146\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">147</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m147\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">148</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m148\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">149</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m149\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">150</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m150\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">151</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m151\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">152</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m152\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">153</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m153\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">154</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m154\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">155</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m155\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">156</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m156\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">157</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m157\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">158</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m158\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">159</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m159\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">160</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m160\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">161</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m161\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">162</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m162\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">163</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m163\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">164</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m164\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">165</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m165\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">166</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m166\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">167</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m167\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">168</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m168\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">169</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m169\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">170</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m170\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">171</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m171\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">172</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m172\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">173</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m173\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">174</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m174\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">175</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m175\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">176</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m176\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">177</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m177\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">178</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m178\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">179</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m179\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">180</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m180\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">181</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m181\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">182</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m182\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m183\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">184</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m184\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">185</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m185\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">186</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m186\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">187</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m187\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">188</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m188\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">189</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m189\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">190</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m190\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">191</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m191\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">192</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m192\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">193</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m193\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">194</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m194\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">195</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m195\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">196</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m196\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">197</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m197\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">198</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m198\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">199</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m199\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">200</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m200\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">201</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m201\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">202</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m202\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">203</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m203\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">204</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m204\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">205</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m205\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">206</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m206\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">207</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m207\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">208</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m208\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">209</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m209\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">210</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m210\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">211</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m211\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">212</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m212\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">213</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m213\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">214</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m214\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">215</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m215\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">216</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m216\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">217</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m217\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m218\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">219</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m219\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">220</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m220\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">221</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m221\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">222</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m222\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">223</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m223\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">224</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m224\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">225</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m225\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">226</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m226\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">227</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m227\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">228</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m228\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">229</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m229\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">230</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m230\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">231</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m231\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m232\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">233</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m233\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">234</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m234\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">235</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m235\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">236</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m236\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">237</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m237\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">238</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m238\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">239</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m239\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">240</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m240\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">241</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m241\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">242</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m242\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">243</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m243\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">244</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m244\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">245</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m245\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">246</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m246\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">247</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m247\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">248</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m248\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">249</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m249\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">250</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m250\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">251</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m251\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">252</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m252\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">253</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m253\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">254</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m254\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">255</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m255\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">256</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m256\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">257</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m257\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">258</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m258\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">259</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m259\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">260</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m260\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">261</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m261\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">262</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m262\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">263</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m263\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">264</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m264\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">265</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m265\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">266</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m266\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">267</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m267\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">268</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m268\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">269</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m269\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">270</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m270\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">271</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m271\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">272</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m272\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">273</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m273\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">274</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m274\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">275</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m275\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">276</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m276\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">277</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m277\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">278</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m278\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">279</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m279\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">280</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m280\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">281</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m281\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">282</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m282\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">283</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m283\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">284</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m284\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">285</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m285\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">286</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m286\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">287</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m287\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">288</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m288\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">289</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m289\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">290</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m290\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">291</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m291\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">292</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m292\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">293</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m293\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">294</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m294\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">295</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m295\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">296</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m296\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">297</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m297\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">298</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m298\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">299</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m299\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">300</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m300\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">301</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m301\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">302</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m302\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">303</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m303\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">304</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m304\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">305</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m305\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">306</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m306\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">307</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m307\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">308</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m308\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">309</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m309\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">310</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m310\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">311</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m311\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">312</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m312\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">313</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m313\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">314</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m314\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">315</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m315\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">316</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m316\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">317</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m317\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">318</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m318\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">319</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m319\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">320</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m320\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">321</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m321\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">322</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m322\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">323</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m323\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">324</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m324\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">325</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m325\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">326</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m326\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">327</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m327\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">328</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m328\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">329</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m329\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">330</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m330\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">331</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m331\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">332</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m332\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">333</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m333\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">334</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m334\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">335</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m335\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">336</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m336\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">337</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m337\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">338</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m338\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">339</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m339\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">340</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m340\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">341</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m341\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">342</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m342\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">343</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m343\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">344</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m344\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">345</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m345\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">346</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m346\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">347</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m347\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">348</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m348\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">349</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m349\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">350</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m350\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">351</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m351\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">352</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m352\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">353</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m353\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">354</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m354\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">355</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m355\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">356</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m356\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">357</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m357\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">358</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m358\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">359</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m359\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">360</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m360\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">361</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m361\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">362</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m362\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">363</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m363\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">364</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m364\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">365</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m365\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">366</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m366\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">367</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m367\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">368</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m368\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">369</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m369\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">370</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m370\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">371</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m371\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">372</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m372\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">373</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m373\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">374</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m374\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">375</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m375\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">376</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m376\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">377</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m377\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">378</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m378\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">379</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m379\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">380</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m380\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">381</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m381\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">382</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m382\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">383</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m383\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">384</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m384\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">385</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m385\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">386</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m386\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">387</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m387\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">388</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m388\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">389</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m389\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">390</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m390\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">391</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m391\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">392</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m392\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">393</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m393\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">394</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m394\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">395</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m395\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">396</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m396\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">397</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m397\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">398</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m398\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">399</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m399\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">400</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m400\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">401</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m401\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">402</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m402\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">403</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m403\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">404</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m404\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">405</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m405\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">406</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m406\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">407</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m407\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">408</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m408\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">409</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m409\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">410</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m410\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">411</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m411\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">412</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m412\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">413</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m413\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">414</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m414\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">415</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m415\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">416</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m416\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">417</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m417\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">418</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m418\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">419</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m419\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">420</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m420\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">421</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m421\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">422</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m422\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">423</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m423\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">424</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m424\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">425</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m425\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">426</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m426\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">427</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m427\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">428</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m428\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">429</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m429\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">430</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m430\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">431</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m431\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">432</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m432\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">433</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m433\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">434</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m434\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">435</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m435\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">436</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m436\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">437</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m437\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">438</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m438\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">439</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m439\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">440</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m440\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">441</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m441\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">442</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m442\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">443</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m443\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">444</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m444\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">445</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m445\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">446</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m446\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">447</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m447\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">448</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m448\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">449</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m449\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">450</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m450\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m451\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">452</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m452\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">453</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m453\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">454</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m454\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">455</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m455\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">456</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m456\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">457</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m457\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">458</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m458\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">459</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m459\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">460</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m460\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">461</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m461\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">462</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m462\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">463</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m463\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">464</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m464\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">465</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m465\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">466</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m466\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">467</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m467\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">468</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m468\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">469</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m469\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">470</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m470\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">471</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m471\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">472</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m472\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">473</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m473\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">474</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m474\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">475</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m475\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">476</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m476\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">477</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m477\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">478</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m478\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">479</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m479\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">480</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m480\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">481</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m481\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">482</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m482\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">483</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m483\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">484</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m484\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">485</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m485\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">486</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m486\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">487</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m487\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">488</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m488\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">489</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m489\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">490</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m490\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">491</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m491\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">492</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m492\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">493</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m493\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">494</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m494\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">495</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m495\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">496</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m496\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">497</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m497\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">498</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m498\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">499</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m499\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">500</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m500\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">501</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m501\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">502</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m502\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">503</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m503\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">504</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m504\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">505</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m505\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">506</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m506\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">507</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m507\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">508</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m508\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">509</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m509\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">510</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m510\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">511</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m511\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">512</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m512\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">513</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m513\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">514</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m514\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">515</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m515\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">516</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m516\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">517</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m517\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">518</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m518\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">519</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m519\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">520</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m520\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">521</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m521\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">522</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m522\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">523</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m523\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">524</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m524\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">525</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m525\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">526</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m526\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">527</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m527\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">528</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m528\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">529</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m529\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">530</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m530\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">531</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m531\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">532</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m532\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">533</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m533\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">534</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m534\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">535</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m535\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">536</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m536\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">537</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m537\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">538</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m538\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">539</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m539\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">540</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m540\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">541</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m541\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">542</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m542\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">543</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m543\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">544</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m544\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">545</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m545\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">546</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m546\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">547</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m547\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">548</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m548\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">549</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m549\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">550</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m550\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">551</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m551\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">552</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m552\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">553</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m553\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">554</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m554\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">555</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m555\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">556</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m556\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">557</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m557\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">558</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m558\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">559</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m559\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">560</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m560\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">561</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m561\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">562</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m562\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">563</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m563\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">564</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m564\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">565</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m565\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">566</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m566\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">567</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m567\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">568</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m568\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">569</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m569\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">570</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m570\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">571</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m571\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">572</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m572\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">573</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m573\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">574</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m574\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">575</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m575\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">576</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m576\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">577</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m577\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">578</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m578\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">579</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m579\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">580</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m580\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">581</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m581\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">582</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m582\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">583</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m583\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">584</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m584\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">585</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m585\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">586</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m586\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">587</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m587\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">588</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m588\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">589</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m589\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">590</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m590\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">591</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m591\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">592</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m592\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">593</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m593\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">594</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m594\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m595\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m596\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m597\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m598\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m599\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m600\u001b[0m/\u001b[1;36m600\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = []\n",
+    "\n",
+    "# Progress bar for visualization\n",
+    "f = IntProgress(min=0, max=N)\n",
+    "display(f)\n",
+    "\n",
+    "for i in range(N):\n",
+    "    print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "    simulated = run_hbv(\n",
+    "        parameters=parameter_sets[i], \n",
+    "        initial_storages=s_0, \n",
+    "        forcing=ERA5_forcing)\n",
+    "\n",
+    "    # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "    simulated_daily = simulated\n",
+    "    observed_daily = observed_output\n",
+    "\n",
+    "    simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "    \n",
+    "    # Align simulated and observed data\n",
+    "    combined_data = pd.DataFrame(\n",
+    "        {\"Modelled discharge\": simulated_daily, \n",
+    "        \"Observed discharge\": observed_daily}).dropna()\n",
+    "\n",
+    "    # Skip first year as warm-up\n",
+    "    combined_data = combined_data[\n",
+    "        (combined_data.index >= evaluation_start) &\n",
+    "        (combined_data.index <= calibration_end_date)]\n",
+    "\n",
+    "    # Exclude ice-affected winter period\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])]\n",
+    "\n",
+    "    # Append results and drop nan\n",
+    "    if combined_data.empty:\n",
+    "        print(f\"No overlapping data for parameter set {i+1}\")\n",
+    "        nse = np.nan\n",
+    "        log_nse = np.nan\n",
+    "    else:\n",
+    "        nse = NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"])\n",
+    "        \n",
+    "        log_nse = log_NSE(\n",
+    "            combined_data[\"Modelled discharge\"], \n",
+    "            combined_data[\"Observed discharge\"])\n",
+    "        \n",
+    "    results.append({\n",
+    "        \"run\": i,\n",
+    "        \"NSE\": nse,\n",
+    "        \"log_NSE\": log_nse,\n",
+    "        \"parameters\": parameter_sets[i]})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d7b5f35-f872-4ef5-8ced-c92cdd81c8f8",
+   "metadata": {},
+   "source": [
+    "### Display best results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "4c69f827-adda-4ec9-8863-abf0ba31e0d2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">     run       NSE   log_NSE\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.288376</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.337195</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.279102</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.480497</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.384565</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.462463</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.085379</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.265060</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.118825</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.395402</span>\n",
+       "..   <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>       <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">595</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378628</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.445890</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">596</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.190509</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.402412</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">597</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.034397</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.105571</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">598</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.174568</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.090100</span>\n",
+       "<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">599</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.379411</span>  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.461890</span>\n",
+       "\n",
+       "<span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">600</span> rows x <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span> columns<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "     run       NSE   log_NSE\n",
+       "\u001b[1;36m0\u001b[0m      \u001b[1;36m0\u001b[0m  \u001b[1;36m0.288376\u001b[0m  \u001b[1;36m0.337195\u001b[0m\n",
+       "\u001b[1;36m1\u001b[0m      \u001b[1;36m1\u001b[0m  \u001b[1;36m0.279102\u001b[0m  \u001b[1;36m0.480497\u001b[0m\n",
+       "\u001b[1;36m2\u001b[0m      \u001b[1;36m2\u001b[0m  \u001b[1;36m0.384565\u001b[0m  \u001b[1;36m0.462463\u001b[0m\n",
+       "\u001b[1;36m3\u001b[0m      \u001b[1;36m3\u001b[0m \u001b[1;36m-0.085379\u001b[0m  \u001b[1;36m0.265060\u001b[0m\n",
+       "\u001b[1;36m4\u001b[0m      \u001b[1;36m4\u001b[0m  \u001b[1;36m0.118825\u001b[0m  \u001b[1;36m0.395402\u001b[0m\n",
+       "..   \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m       \u001b[33m...\u001b[0m\n",
+       "\u001b[1;36m595\u001b[0m  \u001b[1;36m595\u001b[0m  \u001b[1;36m0.378628\u001b[0m  \u001b[1;36m0.445890\u001b[0m\n",
+       "\u001b[1;36m596\u001b[0m  \u001b[1;36m596\u001b[0m  \u001b[1;36m0.190509\u001b[0m  \u001b[1;36m0.402412\u001b[0m\n",
+       "\u001b[1;36m597\u001b[0m  \u001b[1;36m597\u001b[0m  \u001b[1;36m0.034397\u001b[0m \u001b[1;36m-0.105571\u001b[0m\n",
+       "\u001b[1;36m598\u001b[0m  \u001b[1;36m598\u001b[0m  \u001b[1;36m0.174568\u001b[0m  \u001b[1;36m0.090100\u001b[0m\n",
+       "\u001b[1;36m599\u001b[0m  \u001b[1;36m599\u001b[0m  \u001b[1;36m0.379411\u001b[0m  \u001b[1;36m0.461890\u001b[0m\n",
+       "\n",
+       "\u001b[1m[\u001b[0m\u001b[1;36m600\u001b[0m rows x \u001b[1;36m3\u001b[0m columns\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span> with NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5042075946097913</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m232\u001b[0m with NSE: \u001b[1;36m0.5042075946097913\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.488362330365561</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4845571293512798</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218.83336737778694</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.7699130278847444</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1358146729030282</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.44235281882723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.04585512368848791</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.008840391568068273</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8983450417631202</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.488362330365561\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.4845571293512798\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m218.83336737778694\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.7699130278847444\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.1358146729030282\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.44235281882723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.04585512368848791\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.008840391568068273\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.8983450417631202\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best run: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span> with log_NSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5985790718618934</span>, with parameters:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Best run: \u001b[1;36m451\u001b[0m with log_NSE: \u001b[1;36m0.5985790718618934\u001b[0m, with parameters:\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.9919295474161505</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.44128061023639964</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183.49045936834898</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.62907119850059</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5726586861631707</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.2154764587256395</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06546844116401723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0025930490563726475</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.1427426360454793</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.9919295474161505\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.44128061023639964\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m183.49045936834898\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.62907119850059\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.5726586861631707\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.2154764587256395\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.06546844116401723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.0025930490563726475\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.1427426360454793\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = pd.DataFrame(results)\n",
+    "\n",
+    "print(results[[\"run\", \"NSE\", \"log_NSE\"]])\n",
+    "\n",
+    "# # Best NSE\n",
+    "# best_run_nse = results[\"NSE\"].idxmax()\n",
+    "# best_result_nse = results.loc[best_run_nse]\n",
+    "\n",
+    "# best_parameters_nse = best_result_nse[\"parameters\"]\n",
+    "# best_nse = best_result_nse[\"NSE\"]\n",
+    "\n",
+    "# print(f'Best run: {best_run_nse} with NSE: {best_nse}, with parameters:')\n",
+    "# print(list(zip(parameter_names, best_parameters_nse)))\n",
+    "\n",
+    "# Best log_NSE\n",
+    "best_run_log_nse = results[\"log_NSE\"].idxmax()\n",
+    "best_result_log_nse = results.loc[best_run_log_nse]\n",
+    "\n",
+    "best_parameters_log_nse = best_result_log_nse[\"parameters\"]\n",
+    "best_log_nse = best_result_log_nse[\"log_NSE\"]\n",
+    "\n",
+    "print(f'Best run: {best_run_log_nse} with log_NSE: {best_log_nse}, with parameters:')\n",
+    "print(list(zip(parameter_names, best_parameters_log_nse)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "bb2f1f27-9a79-41fa-b416-e32bbee15075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">451</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5985790718618934</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m1\u001b[0m: run \u001b[1;36m451\u001b[0m with LNSE: \u001b[1;36m0.5985790718618934\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.9919295474161505</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.44128061023639964</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">183.49045936834898</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.62907119850059</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5726586861631707</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.2154764587256395</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06546844116401723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0025930490563726475</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.1427426360454793</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.9919295474161505\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.44128061023639964\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m183.49045936834898\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.62907119850059\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.5726586861631707\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.2154764587256395\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.06546844116401723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.0025930490563726475\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.1427426360454793\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">193</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5871245105302814</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m2\u001b[0m: run \u001b[1;36m193\u001b[0m with LNSE: \u001b[1;36m0.5871245105302814\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.882658193683639</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.47241275652770587</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">194.30386240959916</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.781621276884348</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4608178778064105</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.215364575839981</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06419932503784231</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.015979806886031615</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0919722363345776</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m5.882658193683639\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.47241275652770587\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m194.30386240959916\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.781621276884348\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.4608178778064105\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.215364575839981\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.06419932503784231\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.015979806886031615\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.0919722363345776\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5802931655594039</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m3\u001b[0m: run \u001b[1;36m71\u001b[0m with LNSE: \u001b[1;36m0.5802931655594039\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.279358279165555</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.45738099679628363</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218.06826364855027</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.8389403651683596</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.49366891001367486</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.037707687593043</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.07007118899924838</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.024409700594446738</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.2556224532809368</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.279358279165555\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.45738099679628363\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m218.06826364855027\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.8389403651683596\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.49366891001367486\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.037707687593043\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.07007118899924838\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.024409700594446738\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.2556224532809368\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">152</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5697643546613578</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m4\u001b[0m: run \u001b[1;36m152\u001b[0m with LNSE: \u001b[1;36m0.5697643546613578\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.301551796430246</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.49391712556044987</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">211.00486173599964</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9612109256650778</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.46785716423961</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.467897643950326</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.055226399867357515</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.03429434734237983</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.191697747701756</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m7.301551796430246\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.49391712556044987\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m211.00486173599964\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.9612109256650778\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.46785716423961\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m6.467897643950326\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.055226399867357515\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.03429434734237983\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m1.191697747701756\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Rank <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>: run <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">232</span> with LNSE: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5666729995545778</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Rank \u001b[1;36m5\u001b[0m: run \u001b[1;36m232\u001b[0m with LNSE: \u001b[1;36m0.5666729995545778\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Imax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.488362330365561</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ce'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4845571293512798</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Sumax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">218.83336737778694</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Beta'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.7699130278847444</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Pmax'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1358146729030282</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Tlag'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.44235281882723</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Kf'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.04585512368848791</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'Ks'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.008840391568068273</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'FM'</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8983450417631202</span><span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">]</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Imax'\u001b[0m, \u001b[1;36m6.488362330365561\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ce'\u001b[0m, \u001b[1;36m0.4845571293512798\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Sumax'\u001b[0m, \u001b[1;36m218.83336737778694\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Beta'\u001b[0m, \u001b[1;36m1.7699130278847444\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Pmax'\u001b[0m, \u001b[1;36m0.1358146729030282\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Tlag'\u001b[0m, \u001b[1;36m5.44235281882723\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Kf'\u001b[0m, \u001b[1;36m0.04585512368848791\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'Ks'\u001b[0m, \u001b[1;36m0.008840391568068273\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[1m(\u001b[0m\u001b[32m'FM'\u001b[0m, \u001b[1;36m0.8983450417631202\u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get ensemble \n",
+    "\n",
+    "best_5_runs = results[\"log_NSE\"].nlargest(5).index\n",
+    "\n",
+    "best_5_parameters = []\n",
+    "best_5_LNSE = []\n",
+    "\n",
+    "for i in range(len(best_5_runs)):\n",
+    "\n",
+    "    run = best_5_runs[i]\n",
+    "    result = results.loc[run]\n",
+    "\n",
+    "    parameters = result[\"parameters\"]\n",
+    "    lnse = result[\"log_NSE\"]\n",
+    "\n",
+    "    best_5_parameters.append(parameters)\n",
+    "    best_5_LNSE.append(log_nse)\n",
+    "\n",
+    "    print(f\"Rank {i+1}: run {run} with LNSE: {lnse}\")\n",
+    "    print(list(zip(parameter_names, parameters)))\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "127ab139-2d7a-43ad-b012-11188e931c9c",
+   "metadata": {},
+   "source": [
+    "### Plot Observed vs Modelled"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "aeb2ea7e-9826-450f-880e-e1e5e72c9dba",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Overall Plot\n",
+    "\n",
+    "q_critical = 500\n",
+    "\n",
+    "simulated_calibrated_nse = run_hbv(\n",
+    "    parameters=best_parameters_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)\n",
+    "\n",
+    "simulated_calibrated_log_nse = run_hbv(\n",
+    "    parameters=best_parameters_log_nse,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)\n",
+    "\n",
+    "# Align dates\n",
+    "simulated_plot_nse = simulated_calibrated_nse\n",
+    "simulated_plot_log_nse = simulated_calibrated_log_nse\n",
+    "observed_plot = observed_output\n",
+    "\n",
+    "simulated_plot_nse.index = pd.to_datetime(simulated_plot_nse.index).tz_localize(None).normalize()\n",
+    "simulated_plot_log_nse.index = pd.to_datetime(simulated_plot_log_nse.index).tz_localize(None).normalize()\n",
+    "observed_plot.index = pd.to_datetime(observed_plot.index).tz_localize(None).normalize()\n",
+    "\n",
+    "# Combine modelled and observed data\n",
+    "plot_data = pd.DataFrame({\n",
+    "    \"Modelled discharge NSE\": simulated_plot_nse,\n",
+    "    \"Modelled discharge log_NSE\": simulated_plot_log_nse,\n",
+    "    \"Observed discharge\": observed_plot}).dropna()\n",
+    "\n",
+    "# Calculate NSE & log NSE for plotted data\n",
+    "plot_nse = NSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"])\n",
+    "\n",
+    "plot_log_nse = log_NSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"])\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\")\n",
+    "# plt.plot(plot_data.index, plot_data[\"Modelled discharge NSE\"], label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data.index, plot_data[\"Modelled discharge log_NSE\"], label=\"Modelled discharge log_NSE\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001, NSE = {best_nse:.3f}, log NSE = {best_log_nse:.3f}\")\n",
+    "plt.axhline(y=q_critical, linestyle=\":\", label=f'Critical discharge ({q_critical} m³/s', color='black')\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "e0743eb6-3efd-435c-866f-d0ea2bddfea8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for 1 year\n",
+    "\n",
+    "selected_year = 2015\n",
+    "\n",
+    "plot_data_year = plot_data[plot_data.index.year == selected_year]\n",
+    "\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Observed discharge\"],label=\"Observed discharge\")\n",
+    "# plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge NSE\"],label=\"Modelled discharge NSE\")\n",
+    "plt.plot(plot_data_year.index,plot_data_year[\"Modelled discharge log_NSE\"],label=\"Modelled discharge log_NSE\", color=\"green\")\n",
+    "\n",
+    "plt.axhline(y=q_critical,linestyle=\":\",color=\"black\",label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(f\"Observed vs modelled discharge at 07DA001 in {selected_year}\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "dde634ea-53bd-4c41-ba13-8ec762014b89",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">RMSE for best NSE parameter set: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">52.403</span> m³/s\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "RMSE for best NSE parameter set: \u001b[1;36m52.403\u001b[0m m³/s\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">RMSE for best log_NSE parameter set: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64.551</span> m³/s\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "RMSE for best log_NSE parameter set: \u001b[1;36m64.551\u001b[0m m³/s\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Calculate RMSE for best parameter sets NSE and log_NSE\n",
+    "\n",
+    "rmse_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge NSE\"],\n",
+    "    plot_data[\"Observed discharge\"])\n",
+    "\n",
+    "rmse_log_nse = RMSE(\n",
+    "    plot_data[\"Modelled discharge log_NSE\"],\n",
+    "    plot_data[\"Observed discharge\"])\n",
+    "\n",
+    "print(f\"RMSE for best NSE parameter set: {rmse_nse:.3f} m³/s\")\n",
+    "print(f\"RMSE for best log_NSE parameter set: {rmse_log_nse:.3f} m³/s\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "db083f00-6ca7-47a1-8792-c46df17f15ed",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step4_HBV_Validation_Ensemble.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step4_HBV_Validation_Ensemble.ipynb
new file mode 100644
index 00000000..b96e9cb3
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step4_HBV_Validation_Ensemble.ipynb
@@ -0,0 +1,1451 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9ca8fd44-6292-4af4-9100-d3256fccd960",
+   "metadata": {},
+   "source": [
+    "# Ensemble validation\n",
+    "\n",
+    "The 5 parameter sets calculkated in Calibration_HBV.ipynb will be used for a validation period, in which the log NSE will be calculated, a mean will be calculated and total low flow days during the navigation season.\n",
+    "\n",
+    "The structure of this notebook is as follows:\n",
+    "\n",
+    "### 1. Startup\n",
+    "### 2. Model Setup\n",
+    "### 3. Running model\n",
+    "### 4. LNSE calculation\n",
+    "### 5. Display results\n",
+    "### 6. Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdb4216e-a341-4c2b-a410-35170773a9a7",
+   "metadata": {},
+   "source": [
+    "## 1. Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d197b8f0-0f85-4a41-b2fb-1b2a8cf3f9f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "dd7b7d3f-1489-4723-bb51-f3cffcb7a85c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1c8aee93-b2d6-4291-89ae-1d29e69268cd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "d7dce039-d1f3-44a0-b646-98c32ecffb28",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "validation_start_yr = 1999\n",
+    "validation_end_yr = 2019\n",
+    "\n",
+    "experiment_start_date = f\"{validation_start_yr}-01-01T00:00:00Z\"\n",
+    "experiment_end_date = f\"{validation_end_yr}-12-31T00:00:00Z\"\n",
+    "\n",
+    "validation_start = f\"{validation_start_yr}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{validation_end_yr}-12-31T00:00:00Z\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "15ea4507-f559-4ef8-9756-60b8502064d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways for ERA 5 forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"forcings\" / \"ERA5\" / f\"ERA5-{validation_start_yr}-{validation_end_yr}\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "46ea8b1e-fb73-49ed-855c-4d95cd932748",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "8bb224ad-d23c-475f-b6af-4a6023a17044",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs to relevant dates\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= validation_start_date) & (q_obs[\"Date\"] <= validation_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "fc27f6f8-e7ff-4be6-b073-05006d25426a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date\n",
+       "1999-01-01    104.0\n",
+       "1999-01-02    103.0\n",
+       "1999-01-03    101.0\n",
+       "1999-01-04    103.0\n",
+       "1999-01-05    105.0\n",
+       "Name: Observed discharge, dtype: float64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "observed_output.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "7f6f57aa-9f39-4524-ba3a-34f55035ebab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"])\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a48b5085-6478-4cf2-bd02-75b75f82e90f",
+   "metadata": {},
+   "source": [
+    "### Generate/Load ERA5 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "77e79b20-3e4d-405a-bd88-16bdc50bdb39",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1999-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2019-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">ngs/ERA5/ERA5-1999-2019'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_ERA5_1999_2019_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1999-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2019-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci\u001b[0m\n",
+       "\u001b[32mngs/ERA5/ERA5-1999-2019'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_ERA5_1999_2019_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate ERA5 data\n",
+    "# ERA5_forcing = ewatercycle.forcing.sources['LumpedMakkinkForcing'].generate(\n",
+    "#     dataset=\"ERA5\",\n",
+    "#     start_time=experiment_start_date,\n",
+    "#     end_time=experiment_end_date,\n",
+    "#     shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "print(ERA5_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "09f9dfb3-40c9-4689-98b8-fd1ea8fd72d1",
+   "metadata": {},
+   "source": [
+    "### Load parameter sets & initial storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "ca2be146-1112-4806-a44f-d57ebd4442c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"]          # Snowmelt factor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "d5e5bcb4-bf90-470b-90ed-4a0b9d80c35d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "06c977b4-ba9d-4e82-8415-42180eac9f01",
+   "metadata": {},
+   "source": [
+    "## 2. Model setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "055bdbc8-af1f-41ac-ad1d-b4da4d6785f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config)\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\")\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "650daf1f-e90f-4b5b-aac5-eca8965de7cf",
+   "metadata": {},
+   "source": [
+    "## 3. Running model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "44092959-524a-4330-a274-77cfad0eacd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing)\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Filter observed data by day\n",
+    "    observed_daily = observed_output\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "    ensemble_data['Observed discharge'] = observed_daily\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "079368de-30cf-491f-8cc9-2021f6a4bfa6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set 1</th>\n",
+       "      <th>Set 2</th>\n",
+       "      <th>Set 3</th>\n",
+       "      <th>Set 4</th>\n",
+       "      <th>Set 5</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Observed discharge</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1999-01-02</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>103.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999-01-03</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>101.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999-01-04</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>103.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999-01-05</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>105.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999-01-06</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>108.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-02-01</th>\n",
+       "      <td>102.047985</td>\n",
+       "      <td>108.044177</td>\n",
+       "      <td>114.497993</td>\n",
+       "      <td>172.121394</td>\n",
+       "      <td>121.357509</td>\n",
+       "      <td>123.613811</td>\n",
+       "      <td>106.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-02-02</th>\n",
+       "      <td>102.042292</td>\n",
+       "      <td>107.316083</td>\n",
+       "      <td>114.024552</td>\n",
+       "      <td>171.530269</td>\n",
+       "      <td>120.753231</td>\n",
+       "      <td>123.133285</td>\n",
+       "      <td>112.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-02-03</th>\n",
+       "      <td>102.040484</td>\n",
+       "      <td>106.619178</td>\n",
+       "      <td>113.571341</td>\n",
+       "      <td>170.944800</td>\n",
+       "      <td>120.184211</td>\n",
+       "      <td>122.672003</td>\n",
+       "      <td>115.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-02-04</th>\n",
+       "      <td>102.041573</td>\n",
+       "      <td>105.952250</td>\n",
+       "      <td>113.137337</td>\n",
+       "      <td>170.358388</td>\n",
+       "      <td>119.648759</td>\n",
+       "      <td>122.227661</td>\n",
+       "      <td>115.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-02-05</th>\n",
+       "      <td>102.044468</td>\n",
+       "      <td>105.313917</td>\n",
+       "      <td>112.721567</td>\n",
+       "      <td>169.767270</td>\n",
+       "      <td>119.145094</td>\n",
+       "      <td>121.798463</td>\n",
+       "      <td>116.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>400 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 Set 1       Set 2       Set 3       Set 4       Set 5  \\\n",
+       "1999-01-02    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "1999-01-03    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "1999-01-04    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "1999-01-05    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "1999-01-06    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "...                ...         ...         ...         ...         ...   \n",
+       "2000-02-01  102.047985  108.044177  114.497993  172.121394  121.357509   \n",
+       "2000-02-02  102.042292  107.316083  114.024552  171.530269  120.753231   \n",
+       "2000-02-03  102.040484  106.619178  113.571341  170.944800  120.184211   \n",
+       "2000-02-04  102.041573  105.952250  113.137337  170.358388  119.648759   \n",
+       "2000-02-05  102.044468  105.313917  112.721567  169.767270  119.145094   \n",
+       "\n",
+       "                  Mean  Observed discharge  \n",
+       "1999-01-02    0.000000               103.0  \n",
+       "1999-01-03    0.000000               101.0  \n",
+       "1999-01-04    0.000000               103.0  \n",
+       "1999-01-05    0.000000               105.0  \n",
+       "1999-01-06    0.000000               108.0  \n",
+       "...                ...                 ...  \n",
+       "2000-02-01  123.613811               106.0  \n",
+       "2000-02-02  123.133285               112.0  \n",
+       "2000-02-03  122.672003               115.0  \n",
+       "2000-02-04  122.227661               115.0  \n",
+       "2000-02-05  121.798463               116.0  \n",
+       "\n",
+       "[400 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ensemble_data = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)\n",
+    "\n",
+    "ensemble_data.head(400)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "96d6162f-f432-4dfc-9194-f522a2e6a6da",
+   "metadata": {},
+   "source": [
+    "## 4. LNSE Calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "37567a9e-dff3-4c80-84e0-572a6ed72b68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate log NSE\n",
+    "\n",
+    "def LNSE(sim, obs):\n",
+    "    \n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "dc7850a4-dc30-4aa7-8719-4f810760c320",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call log NSE for relevant timeperiod\n",
+    "\n",
+    "def lnse_ensemble(ensemble_data, lnse_start, lnse_end):\n",
+    "\n",
+    "    # Select evaluation period - skip first year for storages to fill\n",
+    "    combined_data = ensemble_data[\n",
+    "        (ensemble_data.index >= lnse_start) &\n",
+    "        (ensemble_data.index <= lnse_end)].dropna()\n",
+    "\n",
+    "    # Exclude winter months\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])]\n",
+    "\n",
+    "    lnse_results = []\n",
+    "\n",
+    "    # Calculate LNSE for all sets\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        lnse_value = LNSE(\n",
+    "            combined_data[f\"Set {i+1}\"],\n",
+    "            combined_data[\"Observed discharge\"])\n",
+    "\n",
+    "        # Append LNSE\n",
+    "        lnse_results.append({\n",
+    "            \"Set\": f\"Set {i+1}\",\n",
+    "            \"LNSE\": lnse_value})\n",
+    "\n",
+    "    # Calculate LNSE of ensemble mean\n",
+    "    mean_lnse = LNSE(\n",
+    "        combined_data[\"Mean\"],\n",
+    "        combined_data[\"Observed discharge\"])\n",
+    "\n",
+    "    # Append LNSE\n",
+    "    lnse_results.append({\n",
+    "        \"Set\": \"Ensemble mean\",\n",
+    "        \"LNSE\": mean_lnse})\n",
+    "\n",
+    "    lnse_results = pd.DataFrame(lnse_results)\n",
+    "\n",
+    "    return lnse_results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "80962ebd-6ad7-48ce-b378-acd68ed03a1e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set</th>\n",
+       "      <th>LNSE</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Set 1</td>\n",
+       "      <td>0.644561</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Set 2</td>\n",
+       "      <td>0.716547</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Set 3</td>\n",
+       "      <td>0.708634</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Set 4</td>\n",
+       "      <td>0.661621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Set 5</td>\n",
+       "      <td>0.677477</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Ensemble mean</td>\n",
+       "      <td>0.739374</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             Set      LNSE\n",
+       "0          Set 1  0.644561\n",
+       "1          Set 2  0.716547\n",
+       "2          Set 3  0.708634\n",
+       "3          Set 4  0.661621\n",
+       "4          Set 5  0.677477\n",
+       "5  Ensemble mean  0.739374"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lnse_results = lnse_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    lnse_start=evaluation_start,\n",
+    "    lnse_end=validation_end_date)\n",
+    "\n",
+    "lnse_results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e267bdfc-ff06-4737-b6f6-e2a40c10a9c5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "03d86b26-2ea9-40ef-834e-b0ec36d842b4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9b6a719-39c6-4872-87ff-cdb65d853e42",
+   "metadata": {},
+   "source": [
+    "## 5. Display results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "f519854a-a994-44fd-a428-4d0c6daa98e1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_ensemble(ensemble_data, plot_start, plot_end):\n",
+    "\n",
+    "    plot_start = pd.to_datetime(plot_start)\n",
+    "    plot_end = pd.to_datetime(plot_end)\n",
+    "\n",
+    "    # Filter data to start & end time\n",
+    "    plot_data = ensemble_data[\n",
+    "        (ensemble_data.index >= plot_start) &\n",
+    "        (ensemble_data.index <= plot_end)].dropna()\n",
+    "\n",
+    "    # Define figure\n",
+    "    plt.figure()\n",
+    "    plt.figure(figsize=(15, 6))\n",
+    "\n",
+    "    # Plot sets, observed data, ensemble mean and axhline, respectively\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        plt.plot(plot_data.index, plot_data[f\"Set {i+1}\"], color=\"orange\", alpha=0.3, label=\"Parameter sets\" if i == 0 else None)\n",
+    "\n",
+    "    plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\", linewidth=3)\n",
+    "    plt.plot(plot_data.index, plot_data[\"Mean\"], label=\"Ensemble mean\", linewidth=3)\n",
+    "    plt.axhline(y=q_critical, linestyle=\":\", color=\"black\", label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "    # Extras\n",
+    "    plt.xlabel(\"Date\")\n",
+    "    plt.ylabel(\"Discharge (m³/s)\")\n",
+    "    plt.title(\"Observed vs modelled ensemble discharge at 07DA001\")\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "f1bb58f8-3dee-43eb-abc8-4af333b5d064",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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cfW7r1q0oVKgQ2rZti4yMDPGnWrVqCAwM1OuqFRISgvLly+ss8/X1Rdu2bfHjjz+KM+c9evQIv//+O3r16iV2pzX2vbLiN9S+vFSpUgU1atTQqfY6f/48jhw5otMlq3bt2jh58iQGDhyI7du348mTJ3m+dnZt2rTR+b1SpUoAoDdwfaVKlZCYmCh2Pc2q0spZ1dWlSxe4u7uLXd/ysx22bt2KJk2aoGjRojrbNmuMqH379hndritXruDChQvi+2Z/vdatW+Pu3bu4ePGiGGPTpk0REBAgPt/e3h7vvfeeSd8nS7t27XR+z6q4yeoyZ47PfLVq1VCsWDHx96z93LhxY7i5uektz9l9D9Dfh927dwfwYh9L2bp1KypXroxq1arpxBkWFpbn7LTR0dFITU3Ve9969erpVDcZUrt2baxcuRJTp07FoUOH9LoRR0VF4cmTJxg4cGCu1XdA5nmrbdu2OstCQkL0ttPff/+NZs2awdvbG/b29nB0dMTEiRPx8OFDJCQk6D0/53lo3759qFy5sjhuWJZu3brpxZ6YmIjevXvrbFetVouWLVvi6NGjeXbr3bBhA+rXrw8PDw84ODjA0dERy5Ytw/nz53N9njEMbc/ctvOyZcvg6+uLjh075vv9hBzdegFgxYoV0Gq1OufLPn36IDk5WW9suLxiy/6YsesREZE8MflGREQ2yc/PD25uboiNjc11vbi4OLi5ucHHx0dneWBgoM7vDg4O8PX1FbuGlSlTBrt27YK/vz8GDRokDtKdfUyze/fu4fHjx3BycoKjo6POT3x8PB48eKDzHkFBQZIx9unTB7dv38bOnTsBZHbxTEtL00kwGfteWfEbap8x+vTpg+joaFy4cAFA5s2ks7Ozzo342LFjMWfOHBw6dAitWrWCr68vmjZtanDcrpxy7g8nJ6dcl6emportc3BwQJEiRXTWU6lUCAwMFNufn+1w7949/PHHH3rb9Y033gAAvf2Ym3v37gEARowYofd6AwcO1Hm9hw8f6sUnFfOrvk+WnO3O6p6bkpICwDyf+Zfdz1mk9lfW9snejVNq+5w6dUovRk9PTwiCkOs+NfTZMbQsp19++QW9e/fG0qVLUbduXfj4+KBXr16Ij48HAHFsPEPd5bNzc3ODi4uLzjJnZ2ed7XTkyBG0aNECALBkyRIcPHgQR48exbhx4wC82L9ZpM5DDx8+1EkCZ8m5LOtz17lzZ71t+9VXX0EQBCQmJhpsz6ZNm9C1a1cUK1YMq1atQnR0NI4ePYo+ffro7fv8yPqMSH0mEhMT9T5vWU6dOoVjx47hgw8+EI+H/MhKghYtWhRA5vAAK1euRNGiRVGjRg08fvwYjx8/RrNmzeDu7o5ly5YZHbNKpUKhQoXEdVNTUyXHOsytfUREJB8c842IiGySvb09mjRpgsjISNy6dUvyRvbWrVs4fvw4WrVqpTeDXXx8vE5FTkZGBh4+fKhzo9+gQQM0aNAAGo0Gx44dw/z58xEREYGAgAC8//774sD1kZGRkjF6enrq/G6oOiEsLAxFixbFihUrEBYWhhUrVqBOnTo6VSjGvldW/IbaZ4xu3brhs88+w8qVKzFt2jT8/PPP6NChAwoXLiyu4+DggM8++wyfffYZHj9+jF27duHzzz9HWFgYbt68qVPVZEq+vr7IyMjA/fv3dRJwgiAgPj4etWrVEtcDjNsOfn5+CAkJwbRp0yTfM+vG2hh+fn4AMpOT2SfLyC5rzDBfX18xIZOd1LJXeZ/8MPVn/lVJHZdZ2ye3ZLKfnx9cXV2xfPlyg48bkv2zk1N8fDxKliyZa8x+fn6YN28e5s2bhxs3bmDLli0YM2YMEhISEBkZKX5ub926levrGGvdunVwdHTE1q1bdRJ12Qfhz07qPOTr6ysm1rLLuQ2yttv8+fMNzvIqlcTLsmrVKpQqVQq//PKLThw5J5DIr6yx0E6fPq1z3szIyMCFCxf0KviyZCXDPvroo5d63y1btkClUqFhw4YAMieiyErISX0+Dx06hHPnzuH1119HmTJl4OrqitOnT+utd/r0aZQtW1bcn9nbV6dOHXG9rIR35cqVXyp+IiKyHUy+ERGRzRo7diz++usvDBw4EJs3b9ZJsGk0GnzyyScQBAFjx47Ve+7q1atRo0YN8ff169cjIyNDckY9e3t71KlTBxUrVsTq1atx4sQJvP/++2jTpg3WrVsHjUajc0OUX/b29ujZsyfmzZuH/fv349ixY/jhhx901jH2vbLiN9Q+YxQuXBgdOnTATz/9hLp16yI+Pj7XWQALFSqEzp074/bt24iIiEBcXJxe9zVTadq0KWbNmoVVq1bh008/FZf/+uuvSE5OFgd7z892aNOmDbZt24YyZcroJBhfRoUKFVCuXDmcPHkS06dPz3XdJk2aYMuWLbh3756YsNBoNJJd017lfV6GuT/z+bF69WoMHTpU/D1rQorcZr9s06YNpk+fDl9f33wPov/mm2/CxcUFq1evxrvvvisuj4qKwvXr1/NMvmVXvHhxDB48GLt378bBgwcBZHZf9fb2xuLFi/H++++/cpdBlUoFBwcHnfNfSkoKfv75Z6Nfo1GjRpgzZ46YGMqybt06nfXq16+PQoUK4dy5c5KTMRgTq5OTk06b4+Pj9WY7BTIr/HJW7RlSp04dBAUFYeXKlTrdtjdu3Ihnz55JJqjT0tKwatUq1K5d+6WSVytWrMBff/2F7t27ixNdLFu2DHZ2dti0aRO8vb111r916xZ69uyJ5cuXY86cOXBwcEDbtm2xadMmzJo1S0xc37hxA3v27NE5v7Vs2RIuLi5YuXKlznGXNZNxhw4d8h0/ERHZFibfiIjIZtWvXx/z5s1DREQE3nrrLQwePBjFixfHjRs38P333+Pw4cOYN28e6tWrp/fcTZs2wcHBAc2bNxdnO61atSq6du0KAFi8eDH+/vtvvPPOOyhevDhSU1PFKppmzZoBAN5//32sXr0arVu3xrBhw1C7dm04Ojri1q1b2LNnD9q3b2/0OEJ9+vTBV199he7du8PV1VVv3C9j36tSpUr44IMPMG/ePDg6OqJZs2Y4c+YM5syZk+tsgVLx/PLLLxg8eDBee+01sc1Z2rZti8qVK6NmzZooUqQIrl+/jnnz5qFEiRI6s7aaWvPmzREWFobRo0fjyZMnqF+/vjjbaWhoKHr27AkA+doOX3zxBXbu3Il69eph6NChqFChAlJTUxEXF4dt27Zh8eLFRnURzPLDDz+gVatWCAsLQ3h4OIoVK4bExEScP38eJ06cwIYNGwAA48ePx5YtW/D2229j4sSJcHNzw/fff5/nmFn5fR9jWfozbwwnJyd8/fXXePbsGWrVqiXOdtqqVSudmSNzioiIwK+//oqGDRvi008/RUhICLRaLW7cuIEdO3Zg+PDhBpOHhQsXxogRIzB16lR89NFH6NKlC27evInJkyfn2e00KSkJTZo0Qffu3VGxYkV4enri6NGjiIyMFBNAHh4e+Prrr/HRRx+hWbNm6NevHwICAnDlyhWcPHkSCxYsyNc2euedd/DNN9+ge/fu6N+/Px4+fIg5c+bkqxtlREQEli9fjlatWuGLL75AQEAA1qxZI3Y9t7OzE2OfP38+evfujcTERHTu3Bn+/v64f/8+Tp48ifv372PRokUG36dNmzbYtGkTBg4cKM4i++WXXyIoKAiXL1/WWbdKlSrYu3cv/vjjDwQFBcHT09NgNae9vT1mzZqFnj17YsCAAejWrRsuX76MUaNGoXnz5mjZsqXec3777TckJibmWfWWkpKCQ4cOif+/du0afvvtN2zdulWcrRbI7D76+++/IywsDO3bt5d8rblz5+Knn37CjBkz4OjoiClTpqBWrVpo06YNxowZg9TUVEycOBF+fn4YPny4+DwfHx+MHz8eEyZMgI+PD1q0aIGjR49i8uTJ+Oijj/S+7Ni4cSMAiOM2Hjt2DB4eHgAyuwwTEZENsuZsD0RERMaIjo4WOnfuLAQEBAgODg6Cv7+/0KlTJyEqKkpv3azZTo8fPy60bdtW8PDwEDw9PYVu3bqJM6JmvWbHjh2FEiVKCM7OzoKvr6/QqFEjndkYBUEQ1Gq1MGfOHKFq1aqCi4uL4OHhIVSsWFEYMGCAcPnyZXG9EiVKCO+8806u7ahXr54AQOjRo4fk48a+V1pamjB8+HDB399fcHFxEd58800hOjpab0bI3Gg0GiE4OFgAIIwbN07v8a+//lqoV6+e4OfnJzg5OQnFixcX+vbtK8TFxeX6ulmzg27YsEFnedaMnDlnp8zaX/fv3xeXpaSkCKNHjxZKlCghODo6CkFBQcInn3wiPHr0SOe5+dkO9+/fF4YOHSqUKlVKcHR0FHx8fIQaNWoI48aNE549eyauByNmOxUEQTh58qTQtWtXwd/fX3B0dBQCAwOFt99+W1i8eLHOegcPHhTefPNNwdnZWQgMDBRGjhwp/O9//zNqtlNj38fQts0Zu6U+8wCEQYMG6SzLmjV09uzZ4rLevXsL7u7uwqlTp4TGjRsLrq6ugo+Pj/DJJ5/o7JOs98q5T589eyaMHz9eqFChguDk5CR4e3sLVapUET799FOdGWalaLVaYcaMGUJwcLDg5OQkhISECH/88YfQqFGjXGc7TU1NFT7++GMhJCRE8PLyElxdXYUKFSoIkyZN0pndVRAEYdu2beIsmG5ubsLrr7+uM2tmVvtzyjomslu+fLlQoUIFwdnZWShdurQwY8YMYdmyZXqfo9zOQ2fOnBGaNWsmuLi4CD4+PkLfvn2FH3/8UQAgnDx5Umfdffv2Ce+8847g4+MjODo6CsWKFRPeeecdveNaysyZM4WSJUsKzs7OQqVKlYQlS5ZItikmJkaoX7++4ObmpjfLrCFr1qwRQkJCBCcnJyEwMFAYOnSo8PTpU8l1mzdvrjcDaU6NGjUSAIg/7u7uQunSpYXOnTsLGzZsEGcUFgRBmDdvngBA+O233wy+3uLFi/VmCz527JjQtGlTwc3NTfDy8hI6dOggXLlyRfL53377rVC+fHnxnDtp0iQhPT1db73sMef8ISIi26QSBIlpfIiIiIiISNH69++PtWvX4uHDh+KkGERERGR67HZKRERERKRwX3zxBYoWLYrSpUvj2bNn2Lp1K5YuXYrx48cz8UZERGRmTL4RERERESmco6MjZs+ejVu3biEjIwPlypXDN998g2HDhlk7NCIiIsVjt1MiIiIiIiIiIiIzsbN2AERERERERERERErF5BsREREREREREZGZMPlGRERERERERERkJpxwwUharRZ37tyBp6cnVCqVtcMhIiIiIiIiIiIrEQQBT58+RdGiRWFnl3ttG5NvRrpz5w6Cg4OtHQYREREREREREdmImzdv4rXXXst1HSbfjOTp6Qkgc6N6eXlZORrTUKvV2LFjB1q0aAFHR0drh0MkWzyWiEyDxxKR6fB4IjINHktEpqO04+nJkycIDg4W80W5YfLNSFldTb28vBSVfHNzc4OXl5ciPvhE1sJjicg0eCwRmQ6PJyLT4LFEZDpKPZ6MGZqMEy4QERERERERERGZCZNvREREREREREREZsLkGxERERERERERkZlwzDciIiIiIiKiVyQIAjIyMqDRaKwdCpFNUqvVcHBwQGpqqmyOE0dHR9jb27/y6zD5RkRERERERPQK0tPTcffuXTx//tzaoRDZLEEQEBgYiJs3bxo1SYEtUKlUeO211+Dh4fFKr8PkGxEREREREdFL0mq1iI2Nhb29PYoWLQonJyfZJBaILEmr1eLZs2fw8PCAnZ3tj4ImCALu37+PW7duoVy5cq9UAcfkGxEREREREdFLSk9Ph1arRXBwMNzc3KwdDpHN0mq1SE9Ph4uLiyySbwBQpEgRxMXFQa1Wv1LyTR6tJSIiIiIiIrJhckkmEJHxTFXFyrMDERERERERERGRmTD5RkREREREREREZCZMvhEREREREREREZkJk29EREREREREBVB4eDhUKhVUKhUcHR1RunRpjBgxAsnJydYO7aWVLFkS8+bNs3YYkuLi4qBSqRATE2PtUMjCONspERERERERUQHVsmVLrFixAmq1Gvv378dHH32E5ORkLFq0KN+vJQgCNBoNHBzkn2pIT0+Hk5OTtcMghWDlGxEREREREZGpaTXW+cknZ2dnBAYGIjg4GN27d0ePHj3w22+/AQBWrVqFmjVrwtPTE4GBgejevTsSEhLE5+7duxcqlQrbt29HzZo14ezsjP379+Pq1ato3749AgIC4OHhgVq1amHXrl0671uyZElMnToVvXr1goeHB0qUKIHff/8d9+/fR/v27eHh4YEqVarg2LFjOs+LiopCw4YN4erqiuDgYAwdOlSs1GvcuDGuX7+OTz/9VKzoM+Z52eMJDw+Ht7c3+vXrJ7m9Nm7ciCpVqsDV1RW+vr5o1qyZzuusWLEClSpVgouLCypWrIiFCxeKj5UqVQoAEBoaCpVKhcaNG4vbsXbt2nB3d0ehQoVQv359XL9+3dhdSDIg/3Q0ERERERERkS3RaoA726zz3kVbA3b2L/10V1dXqNVqAJnVX19++SUqVKiAhIQEfPrppwgPD8e2bbptGzVqFObMmYPSpUujUKFCuHXrFlq3bo2pU6fCxcUFP/74I9q2bYuLFy+iePHi4vPmzp2L6dOnY8KECZg7dy569uyJ+vXro0+fPpg9ezZGjx6NXr164ezZs1CpVDh9+jTCwsLw5ZdfYtmyZbh//z4GDx6MwYMHY8WKFdi0aROqVq2K/v376yTP8npeltmzZ2PChAkYP3685La5e/cuunXrhlmzZqFjx454+vQp9u/fD0EQAABLlizBpEmTsGDBAoSGhuLff/9Fv3794O7ujt69e+PIkSOoXbs2du3ahTfeeANOTk7IyMhAhw4d0K9fP6xduxbp6ek4cuSITuKQ5I/JNyIiIiIiCxEEAceuP4Kroz0qF/O2djhERDqOHDmCNWvWoGnTpgCAPn36iI+VLl0a3333HWrXro1nz57Bw8NDfOyLL75A8+bNxd99fX1RtWpV8fepU6di8+bN2LJlCwYPHiwub926NQYMGAAAmDhxIhYtWoRatWqhS5cuAIDRo0ejbt26uHfvHgIDAzF79mx0794dERERAIBy5crhu+++Q6NGjbBo0SL4+PjA3t5erNTLktfzXFxcAABvv/02RowYYXD73L17FxkZGejUqRNKlCgBAKhSpYr4+Jdffomvv/4anTp1ApBZ6Xbu3Dn88MMP6N27N4oUKSJun6z4EhMTkZSUhDZt2qBMmTIAgEqVKhmMgeSJyTciIiIiIgsZui4Gf5y8AwAY1bICBjYua+WIiMgs7OwzK9Cs9d75sHXrVnh4eCAjIwNqtRrt27fH/PnzAQD//vsvJk+ejJiYGCQmJkKr1QIAbty4gddff118jZo1a+q8ZnJyMqZMmYKtW7fizp07yMjIQEpKCm7cuKGzXkhIiPj/gIAAALrJrKxlCQkJCAwMxPHjx3HlyhWsXr1aXEcQBGi1WsTGxhpMWhn7vJztyKlq1apo2rQpqlSpgrCwMLRo0QKdO3dG4cKFcf/+fdy8eRN9+/bVqbrLyMiAt7fhL1t8fHwQHh6OsLAwNG/eHM2aNUPXrl0RFBSUaywkL0y+ERERERFZQOyDZDHxBgCzIi8y+UakZK/Q9dOSmjRpgkWLFsHR0RFFixaFo6MjgMwEWosWLdCiRQusWrUKRYoUwY0bNxAWFob09HSd13B3d9f5feTIkdi+fTvmzJmDsmXLwtXVFZ07d9Z7XtZ7ARC7WUoty0r6abVaDBgwAEOHDtVrR/burDkZ+7yc7cjJ3t4eO3fuRFRUFHbs2IH58+dj3LhxOHz4MNzc3ABkdj2tU6eO3vNys2LFCgwdOhSRkZH45ZdfMH78eOzcuRNvvvlmrs8j+WDyjYiIiIjIAk7demztEIiI9Li7u6NsWf0vAi5cuIAHDx5g5syZCA4OBgC9yQ8M2b9/P8LDw9GxY0cAwLNnzxAXF/fKsVavXh1nz56VjDeLk5MTNBrdiSeMeZ6xVCoV6tevj/r162PixIkoUaIENm/ejM8++wzFihXDtWvX0KNHD4OxAdCLD8ichCE0NBRjx45F3bp1sWbNGibfFISznRIRERERWQAHzyYiOSlevDicnJwwf/58XLt2DVu2bMGXX35p1HPLli2LTZs2ISYmBidPnkT37t3F6rVXMXr0aERHR2PQoEGIiYnB5cuXsWXLFgwZMkRcp2TJkvjnn39w+/ZtPHjwwOjnGePw4cOYPn06jh07hhs3bmDTpk24f/++2G118uTJmDFjBr799ltcunQJp0+fxooVK/DNN98AAPz9/eHq6orIyEjcu3cPSUlJiI2NxdixYxEdHY3r169jx44duHTpEsd9Uxgm34iIiIiILEAq9ZY1Qx4Rka0pUqQIVq5ciQ0bNuD111/HzJkzMWfOHKOeO3fuXBQuXBj16tVD27ZtERYWhurVq79yTCEhIdi3bx8uX76MBg0aIDQ0FBMmTNAZH+2LL75AXFwcypQpI05wYMzzjOHl5YV//vkHrVu3Rvny5TF+/Hh8/fXXaNWqFQDgo48+wtKlS7Fy5UpUqVIFjRo1wsqVK1GqVCkAgIODA7777jv88MMPKFq0KNq3bw83NzdcuHAB7777LsqXL4/+/ftj8ODB4kQUpAwqgX/xjfLkyRN4e3sjKSkJXl5e1g7HJNRqNbZt24bWrVvr9KsnovzhsURkGjyWSOn+OHkHQ9b+q7Ps2vTWsLMzfUUcjyci0zDmWEpNTUVsbCxKlSolzppJRPq0Wi2ePHkCLy8v2NnJoxYst+M7P3kiebSWiIiIiEjm7CS6nfJbcCIiIuVj8o2IiIiIyAKkhnzTshMKERGR4jH5RkRERERkJcy9ERERKR+Tb0REREREFiA54QI7nhIRESkek29ERERERBYg1e2UlW9ERETKx+QbERERERERERGRmTD5RkRERERkERKznbLyjYiISPGYfCMiIiIisgDJbqcc842IiEjxmHwjIiIiIrIAqQkXtMy9ERERKR6Tb0REREREFqCSKH0T2O+UiGSiZMmSmDdvnrXDMJmXaU94eDg6dOgg/t64cWNERES8cixxcXFQqVSIiYl55dci28TkGxERERGRlTD1RkTWdvPmTfTt2xdFixaFk5MTSpQogWHDhuHhw4fWDs3mbdq0CV9++aW1wyAZcLB2AEREREREBYFUt1MWvhEpj1Yr4NHzdKvGUNjNCXZ2UmcdXdeuXUPdunVRvnx5rF27FqVKlcLZs2cxcuRI/PXXXzh06BB8fHwsELE+jUYDlUoFOzvbrRmy1rYxVnp6OpycnKwdBoHJNyIiIiIii5CacIGlb0TK8+h5OmpM3WXVGI6PbwZfD+c81xs0aBCcnJywY8cOuLq6AgCKFy+O0NBQlClTBuPGjcOiRYvE9Z8+fYru3btjy5Yt8PLywtixYzFkyBDx8cmTJ2P58uW4d+8efH190blzZ3z33XcAMhNB48ePx+rVq/H48WNUrlwZX331FRo3bgwAWLlyJSIiIrBq1SqMGjUKly5dwvfff49hw4YhPj4ehQoVEt9n6NChOHnyJPbt2wcAiIqKwpgxY3D06FH4+fmhY8eOmDFjBtzd3QEACQkJ6Nu3L3bt2oXAwEBMnTo1z22j0WgwcuRILF++HPb29ujbt6/eUAGNGzdGtWrVxO6rCxcuxNy5c3Hz5k14e3ujQYMG2LhxIwBAq9Vi9uzZWLJkCW7evImAgAAMGDAA48aNE1/v2rVr+PTTT3H48GGUK1cOixcvRt26dQEADx8+xODBg7F//34kJiaiTJky+Pzzz9GtWzedeCpXrgwnJyf89NNPeOONN7Bv3z5s2bIFw4cPx61bt/Dmm28iPDwc4eHhePTokbhd89qG9GpsN4VMRERERKQgnO2UiGxJYmIitm/fjoEDB4qJtyyBgYHo0aMHfvnlF52E0+zZsxESEoITJ05g7Nix+PTTT7Fz504AwMaNGzF37lz88MMPuHz5Mn777TdUqVJFfO6HH36IgwcPYt26dTh16hS6dOmCli1b4vLly+I6z58/x4wZM7B06VKcPXsWH3zwAQoVKoRff/1VXEej0WD9+vXo0aMHAOD06dMICwtDp06dcOrUKfzyyy84cOAABg8eLD4nPDwccXFx+Pvvv7Fx40YsXLgQCQkJuW6fr7/+GsuXL8eyZctw4MABJCYmYvPmzQbXP3bsGIYOHYovvvgCFy9eRGRkJBo2bCg+PnbsWHz11VeYMGECzp07hzVr1iAgIEDnNcaNG4cRI0YgJiYG5cuXR7du3ZCRkQEASE1NRY0aNbB161acOXMG/fv3R8+ePXH48GGd1/jxxx/h4OCAgwcP4ocffkBcXBw6d+6MDh06ICYmRi/hZ+w2pFfDyjciIiIiIgtQSXQ85WynRGQtly9fhiAIqFSpkuTjlSpVwqNHj3D//n34+/sDAOrXr48xY8YAAMqXL4+DBw9i7ty5aN68OW7cuIHAwEA0a9YMjo6OKF68OGrXrg0AuHr1KtauXYtbt26haNGiAIARI0YgMjISK1aswPTp0wEAarUaCxcuRNWqVcU43nvvPaxZswZ9+/YFAOzevRuPHj1Cly5dAGQmBLt37y5OfFCuXDl89913aNSoERYtWoQbN26IXWjr1KkDAFi2bJnBdmeZN28exo4di3fffRcAsHjxYmzfvt3g+jdu3IC7uzvatGkDT09PlChRAqGhoQAyKwa//fZbLFiwAL179wYAlClTBm+99ZbOa4wYMQLvvPMOAGDKlCl44403cOXKFVSsWBHFihXDiBEjxHWHDBmCyMhIbNiwQWwXAJQtWxazZs0Sfx8zZgwqVKiA2bNnAwAqVKiAM2fOYNq0aeI6eW1DFxeXXLcV5Y2Vb0REREREliBV+cZB34jIRmWdn7LP1JzVBTL77+fPnwcAdOnSBSkpKShdujT69euHzZs3i1VbJ06cgCAIKF++PDw8PMSfffv24erVq+LrOTk5ISQkROc9evTogb179+LOnTsAgNWrV6N169YoXLgwAOD48eNYuXKlzuuGhYVBq9UiNjYW58+fh4ODA2rWrCm+ZsWKFXW6seaUlJSEu3fv6rQ352vk1Lx5c5QoUQKlS5dGz549sXr1ajx//hwAcP78eaSlpaFp06YGnw9Ap+1BQUEAIFboaTQaTJs2DSEhIfD19YWHhwd27NiBGzdu6LxGzhgvXryIWrVq6SzLSopmyWsb0qtj5RsRERERkZUw9UakPIXdnHB8fDOrx5CXsmXLQqVS4dy5c+jQoYPe4xcuXEDhwoXh5+eX6+tkJeeCg4Nx8eJF7Ny5E7t27cLAgQMxe/Zs7Nu3D1qtFvb29jh+/Djs7e11nu/h4SH+39XVVSfZB2QmisqUKYN169bhk08+webNm7FixQrxca1WiwEDBmDo0KF6sRUvXhwXL17UidNcPD09ceLECezduxc7duzAxIkTMXnyZBw9elSvW68hjo6O4v+z4tVqtQAyu8HOnTsX8+bNQ5UqVeDu7o6IiAikp+tO7pFzjDZBEPTanvOLn7y2Ib06Jt+IiIiIiCyAs50SFQx2diqjJjuwNl9fXzRv3hwLFy7Ep59+qpMgio+Px+rVq9GrVy+dxM2hQ4d0XuPQoUOoWLGi+LurqyvatWuHdu3aYdCgQahYsSJOnz6N0NBQaDQaJCQkoEGDBvmOtXv37li9ejVee+012NnZiV0zAaB69eo4e/YsypYtK/ncSpUqISMjA8eOHRMrvi5evIjHjx8bfD9vb28EBQXh0KFD4rhtGRkZOH78OKpXr27weQ4ODmjWrBmaNWuGSZMmoVChQvj777/RunVruLq6Yvfu3fjoo4/y3X4A2L9/P9q3b48PPvgAQGbC7PLly3l2n61YsSK2bdums+zYsWM6v+e1DenVsdspEREREZGVcMIFIrKmBQsWIC0tDWFhYfjnn39w8+ZNREZGonnz5ihWrJjOuGAAcPDgQcyaNUuciXTDhg0YNmwYgMzZSpctW4YzZ87g2rVr+Pnnn+Hq6ooSJUqgfPny6NGjB3r16oVNmzYhNjYWR48exVdffaWXGJLSo0cPnDhxAtOmTUPnzp11xiAbPXo0oqOjMWjQIMTExODy5cvYsmWLOAtrhQoV0LJlS/Tr1w+HDx/G8ePH8dFHH+VZjTZs2DDMnDkTmzdvxoULFzBw4MBcE3Zbt27Fd999h5iYGFy/fh0//fQTtFotKlSoABcXF4wePRqjRo3CTz/9hKtXr+LQoUNYtmxZnm3PUrZsWezcuRNRUVE4f/48BgwYgPj4+DyfN2DAAFy4cAGjR4/GpUuXsH79eqxcuRLAi+q6vLYhvTom34iIiIiILECyyxNzb0RkReXKlcOxY8dQpkwZvPfeeyhTpgz69++PJk2aIDo6Gj4+PjrrDx8+HMePH0doaCi+/PJLfP311wgLCwMAFCpUCEuWLEH9+vUREhKC3bt3448//oCvry8AYMWKFejVqxeGDx+OChUqoF27djh8+DCCg4ONirNWrVo4deqUOMtplpCQEOzbtw+XL19GgwYNEBoaigkTJohjpmW9d3BwMBo1aoROnTqhf//+4iQShgwfPhy9evVCeHg46tatC09PT3Ts2NHg+oUKFcKmTZvw9ttvo1KlSli8eDHWrl2LN954AwAwYcIEDB8+HBMnTkSlSpXw3nvv5TnjanYTJkxA9erVERYWhsaNGyMwMFCyu3BOpUqVwsaNG7Fp0yaEhIRg0aJF4mynzs6ZFZrGbEN6NSqBo7wa5cmTJ/D29kZSUhK8vLysHY5JqNVqbNu2Da1bt9bpW05E+cNjicg0eCyR0v1z6T56LT+is+zw500R4GX6WeR4PBGZhjHHUmpqKmJjY1GqVCnOCkmyMG3aNCxevBg3b9606PtqtVo8efIEXl5esLOTRy1Ybsd3fvJEHPONiIiIiMgCpArftPwenIiIzGzhwoWoVasWfH19cfDgQcyePRuDBw+2dlgFCpNvREREREQWoJKYcoG5NyIiMrfLly9j6tSpSExMRPHixTF8+HCMHTvW2mEVKEy+ERERERFZAId8IyIia5g7dy7mzp1r7TAKNHl0siUiIiIiUiAOv0xERKR8TL4REREREVmAROEbu50SEREVAEy+ERERERFZglT2jYiIiBSPyTciIiIiIgvghAs2TBCA9EeAoLV2JEREpEBMvhERERERWYDUhAtaZt9sQ+o9IOEA8CDa2pEQEZECMflGRERERGQBkmO+WTwKkpSemPlvWqJ14yAiIkVi8o2IiIiIyEo426mtyJYa1aRbLwwiMkpcXBxUKhViYmIMrrN3716oVCo8fvzYYnERGcLkGxERERGRBagk+p0y9WYjso/1JmisFweRhYWHh0OlUun9tGzZ0tqhESmKzSTfZsyYAZVKhYiICHGZIAiYPHkyihYtCldXVzRu3Bhnz57VeV5aWhqGDBkCPz8/uLu7o127drh165bOOo8ePULPnj3h7e0Nb29v9OzZk9lvIiIiIrI6Fr7ZCsHA/4leglYLJD+w7o/W+MlDWrZsibt37+r8rF271owbiKjgsYnk29GjR/G///0PISEhOstnzZqFb775BgsWLMDRo0cRGBiI5s2b4+nTp+I6ERER2Lx5M9atW4cDBw7g2bNnaNOmDTSaF99Yde/eHTExMYiMjERkZCRiYmLQs2dPi7WPiIiIiMhOatA3JnpsD2c8pVeVkgjMLmPdnxTjxy90dnZGYGCgzk/hwoXFx1UqFZYuXYqOHTvCzc0N5cqVw5YtW8THHz16hB49eqBIkSJwdXVFuXLlsGLFCvHx27dv47333kPhwoXh6+uL9u3bIy4uTnw8PDwcHTp0wPTp0xEQEIBChQphypQpyMjIwMiRI+Hj44PXXnsNy5cv14v9woULqFevHlxcXPDGG29g7969ubY1KioKDRs2hKurK4KDgzF06FAkJycbXH/y5MmoVq0ali9fjuLFi8PDwwOffPIJNBoNZs2ahcDAQPj7+2PatGk6z0tKSkL//v3h7+8PLy8vvP322zh58qT4+NWrV9G+fXsEBATAw8MDtWrVwq5du3Reo2TJkpg+fTr69OkDT09PFC9eHP/73/9ybR/ZLgdrB/Ds2TP06NEDS5YswdSpU8XlgiBg3rx5GDduHDp16gQA+PHHHxEQEIA1a9ZgwIABSEpKwrJly/Dzzz+jWbNmAIBVq1YhODgYu3btQlhYGM6fP4/IyEgcOnQIderUAQAsWbIEdevWxcWLF1GhQgXJuNLS0pCWlib+/uTJEwCAWq2GWq02y7awtKx2KKU9RNbCY4nINHgskdJlZGToLUtPzzDLZ57HUz5lpEOlydw/gjodALcbZTLmWFKr1RAEAVqtFlqtFtBqrV7lkhVHXgRBEGPPzZQpUzBz5kx89dVXWLBgAXr06IHY2Fj4+Phg/PjxOHfuHP7880/4+fnhypUrSElJgVarxfPnz9GkSRO89dZb2Lt3LxwcHDBt2jS0bNkSMTExcHJygiAI+Pvvv1GsWDHs3bsXBw8eRL9+/cREWXR0NNavX4+PP/4YTZs2RXBwsBjvyJEj8c033+D111/H3Llz0a5dO1y9ehW+vr7iOln75fTp0wgLC8MXX3yBJUuW4P79+xg6dCgGDRokmdjL2j5Xr17Ftm3bsG3bNly9ehVdu3bFtWvXUL58eezZswdRUVH46KOP0KRJE7z55psQBAHvvPMOChcujK1bt8Lb2xv/+9//0LRpU1y4cAE+Pj548uQJWrZsiS+++AIuLi746aef0LZtW5w/fx7FixcX3//rr7/GF198gTFjxuDXX3/FJ598grfeegsVK1Y09qNgU7LGOTXmM2crtFotBEGAWq2Gvb29zmP5+RurEqw8ymvv3r3h4+ODuXPnonHjxqhWrRrmzZuHa9euoUyZMjhx4gRCQ0PF9du3b49ChQrhxx9/xN9//42mTZsiMTFRJzNftWpVdOjQAVOmTMHy5cvx2Wef6XUzLVSoEObOnYsPP/xQMq7JkydjypQpesvXrFkDNzc30zSeiIiIiAqMa0+Ab8/qfvc9umoGivLS0uq8tHFw1SYAAB7av4EMlbuVIyI5cXBwQGBgIIKDg+Hk5ATV84fw/l91q8aU1P8EBDffPNcbOHAg1q9fDxcXF53lw4YNw8iRIwEAhQsXxogRIzBu3DgAQHJyMoKDg7F+/Xo0a9YM3bp1g6+vLxYsWKD3+qtWrcJ3332Hw4cPi+Nepqeno2TJkli1ahXefvttDBw4EAcOHEBMTAzs7DLTlrVr14afnx+2bdsGANBoNChRogS+/fZbvPvuu7hx4waqVq2KSZMmiUNXZWRkoGrVqujfvz+GDRuGAwcOoG3btoiLi4O3tzc+/vhjuLi4YN68eWJ80dHRaNOmDW7fvq23DQBg5syZmD9/Pi5cuABPT08AQOfOnXH58mX8+++/OvF269YNn376Kf755x988MEHuHz5MpydncXXql69OoYOHYrw8HDJfVG3bl18+OGH6N+/PwAgJCQEdevWxQ8//AAgM2FVoUIFjBkzBn369DGwR8nU0tPTcfPmTcTHx+t9ifb8+XN0794dSUlJ8PLyyvV1rFr5tm7dOpw4cQJHjx7Veyw+Ph4AEBAQoLM8ICAA169fF9dxcnLSSbxlrZP1/Pj4ePj7++u9vr+/v7iOlLFjx+Kzzz4Tf3/y5AmCg4PRokWLPDeqXKjVauzcuRPNmzeHo6OjtcMhki0eS0SmwWOJlO749Uf49qzudW+DtxqgQqCnyd+Lx1M+PT4F1fMbAADB7y3AqZB14yGbYcyxlJqaips3b8LDwyMzgWNv/RlzPT09Afe871sdHR3RuHFjLFy4UGe5j4+Pzn1vzZo1xd+9vLzg6emJZ8+ewcvLC4MHD0aXLl1w5swZNG/eHO3bt0e9evUAAOfOncO1a9cQHBys8/qpqam4e/cuvLy84OjoiMqVK6NQoULi40FBQXjjjTd0YvD19RXf08PDAwDQuHFjnXVq1aqF2NhYeHl5iUUznp6e8PLywunTp3HlyhVs3LhRXD+rAuvhw4eoVKmS3vZxdnZGyZIlUaxYMXFZ0aJF4eTkpBfvkydP4OXlhQsXLiA5ORllypTRea2UlBTcuXMHXl5eSE5OxhdffIE///wTd+7cQUZGBlJSUnD//n2xPXZ2dqhRo4ZO+4KCgvD06VPZ5iQEQcDTp0/h6ekpOQmRLUpNTYWrqysaNmyol6DN6iFpDKsl327evIlhw4Zhx44dkhnmLDl3iCAIee6knOtIziyVx+s4OzvrZKmzODo6Ku4CRoltIrIGHktEpsFjiZTK3kH/0tvewcGsn3ceT0ZycADs/9s/DvYAtxnlkNuxpNFooFKpYGdnl1kJ5e4HjLxq4Qh12bn6AHZ5d35VqVTw8PBA+fLlc13P2dlZrPLKeh6QmSB65513cP36dfz555/YtWsXmjdvjkGDBmHOnDkQBAE1atTA6tWr9V6zSJEisLOzg0qlgpOTk97rSy0TBOHFdv7v/XOuk7Us5zparRYDBgzA0KFD9WIpXry4zutkfz1HR0edx+zs7HKNTRAEBAUFSY4/V6hQIdjZ2WH06NHYvn075syZg7Jly8LV1RWdO3eGWq3Wed3c3keOsrqaZu0nOcj6jEqdA/Lz99Vqybfjx48jISEBNWrUEJdpNBr8888/WLBgAS5evAggs3ItKChIXCchIUGshgsMDER6ejoePXqkU/2WkJAgZtoDAwNx7949vfe/f/++XlUdEREREZElcbZTW8SdQq8oKwFXgBQpUgTh4eEIDw9HgwYNMHLkSMyZMwfVq1fHL7/8Ik48YGqHDh1Cw4YNAWR2Oz1+/DgGDx4suW716tVx9uxZlC1b1uRx5Hyf+Ph4ODg4oGTJkpLr7N+/H+Hh4ejYsSOAzLHws09CQcpjtVRj06ZNcfr0acTExIg/NWvWRI8ePRATE4PSpUsjMDAQO3fuFJ+Tnp6Offv2iYm1GjVqwNHRUWedu3fv4syZM+I6devWRVJSEo4cOSKuc/jwYSQlJYnrEBERERFZg8BEj43Ith+YEaUCJi0tDfHx8To/Dx48MPr5EydOxO+//44rV67g7Nmz2Lp1q9iFs0ePHvDz80P79u2xf/9+xMbGYt++fRg2bBhu3br1yrF///332Lx5My5cuIBBgwbh0aNHBsdDGz16NKKjozFo0CDExMTg8uXL2LJlC4YMGfLKcWTXrFkz1K1bFx06dMD27dsRFxeHqKgojB8/HseOHQMAlC1bFps2bUJMTAxOnjyJ7t27y2YCAno5Vqt88/T0ROXKlXWWubu7w9fXV1weERGB6dOno1y5cihXrhymT58ONzc3dO/eHQDg7e2Nvn37Yvjw4fD19YWPjw9GjBiBKlWqiLOfVqpUCS1btkS/fv3EgQr79++PNm3aGJzplIiIiIjI1KRyOszz2CLeAFPBEhkZqdPbDAAqVKiACxcuGPV8JycnjB07FnFxcXB1dUWDBg2wbt06AICbmxv++ecfjB49Gp06dcLTp09RrFgxNG3a1CSVcFkzsP77778oU6YMfv/9d/j5SVcdhoSEYN++fRg3bhwaNGgAQRBQpkwZvPfee68cR3YqlQrbtm3DuHHj0KdPH9y/fx+BgYFo2LCh2Ptu7ty56NOnD+rVqwc/Pz+MHj06X+OHkfxYfbbT7LLPdgpkjss2ZcoU/PDDD3j06BHq1KmD77//Xidpl5qaipEjR2LNmjVISUlB06ZNsXDhQp0BHRMTEzF06FBs2bIFANCuXTssWLBAZ4DEvDx58gTe3t5GzWIhF2q1Gtu2bUPr1q05FgjRK+CxRGQaPJZI6Y7EJqLrD9E6y/4Y/BaqvOZt8vfi8ZRPif8Cz/+rwvGtDbhyeBrKZMyxlJqaitjYWJQqVSrX8cyJCjqtVitOTCGXMd9yO77zkyey6mynOeUckFClUmHy5MmYPHmywee4uLhg/vz5mD9/vsF1fHx8sGrVKhNFSURERESUf1LfebPbqa3Ivh9Y+UZERKYlj1QjEREREZEC2U4fFBJxpxARkYkx+UZEREREZCVM89gi7hUiIjItJt+IiIiIiCxAKqVjQ8MvF3DZZztlt1MiIjItJt+IiIiIiKyEqTcboZME5V4hIiLTYvKNiIiIiMhKWPhmi7hTiIjItJh8IyIiIiKyAKlEG7ud2ors3U65T4iIyLSYfCMiIiIishKmeWwR9woREZkWk29ERERERFbCIisbwTHfiIjIjJh8IyIiIiKyAEEiqcNupzaI+4TIKHv37oVKpcLjx49zXa9kyZKYN2+eyd63cePGiIiIyNdzJk+ejGrVqom/h4eHo0OHDiaJR6VS4bfffjPJa1lSz549MX36dGuHYVVpaWkoXrw4jh8/bvb3YvKNiIiIiMhKmOaxFax8o4IrPj4eQ4YMQenSpeHs7Izg4GC0bdsWu3fvzvV59erVw927d+Ht7Q0AWLlyJQoVKqS33tGjR9G/f39zhP7Svv32W6xcudLaYVjNqVOn8Oeff2LIkCHisvDwcKhUKp2fN998U+d5aWlpGDJkCPz8/ODu7o527drh1q1bOus8evQIPXv2hLe3N7y9vdGzZ888E7QvY968eWjVqhWaN2+Ofv366X2ZFR4ejjFjxuT6Gs7OzhgxYgRGjx5t8vhyYvKNiIiIAE0qqz2IrICHna3ghAtUMMXFxaFGjRr4+++/MWvWLJw+fRqRkZFo0qQJBg0aZPB5arUaTk5OCAwMhEqlyvU9ihQpAjc3N1OH/kq8vb0lE4W2Ij093ayvv2DBAnTp0gWenp46y1u2bIm7d++KP9u2bdN5PCIiAps3b8a6detw4MABPHv2DG3atIFGoxHX6d69O2JiYhAZGYnIyEjExMSgZ8+eJm9DREQEihUrhqtXr2LNmjV4+vSp+JhWq8Wff/6J9u3b5/k6PXr0wP79+3H+/HmTx5gdk29EREQFXeoD4O5O4OFRa0dCpGyc7ZSowElOTkZycrLOsZ6eno7k5GSkpaVJrqvVasVlarUaycnJSE1NNWrd/Bo4cCBUKhWOHDmCzp07o3z58njjjTfw2Wef4dChQ+J6KpUKixcvRvv27eHu7o6pU6fqdDvdu3cvPvzwQyQlJYlVU5MnTwag3+308ePH6N+/PwICAuDi4oLKlStj69atAICHDx+iW7dueO211+Dm5oYqVapg7dq1+W7XzJkzERAQAE9PT/Tt21dv++Xsdrpx40ZUqVIFrq6u8PX1RbNmzZCcnCw+vnz5crzxxhtwdnZGUFAQBg8erPN6Dx48QMeOHeHm5oZy5cphy5Yt4mMajQZ9+/ZFqVKl4OrqigoVKuDbb7+VjGfGjBkoWrQoypcvDwCIiopCtWrV4OLigpo1a+K3336DSqVCTEyM+Nxz586hdevW8PDwQEBAAHr27IkHDx4Y3DZarRYbNmxAu3bt9B5zdnZGYGCg+OPj4yM+lpSUhGXLluHrr79Gs2bNEBoailWrVuH06dPYtWsXAOD8+fOIjIzE0qVLUbduXdStWxdLlizB1q1bcfHiRYMxlSxZElOnTkWvXr3g4eGBEiVK4Pfff8f9+/fRvn17eHh4oEqVKjh27JjO85YuXYp///0XI0eO1EkkHjx4EHZ2dqhTpw7S09MxePBgBAUFwcXFBSVLlsSMGTPEdX19fVGvXr2X+pzlB5NvREREBV1ybOa/qfesGwdRAcTUm43ghAtkJh4eHvDw8NBJhsyePRseHh56CRx/f394eHjgxo0b4rLvv/8eHh4e6Nu3r866JUuWhIeHh061Tn67USYmJiIyMhKDBg2Cu7u73uM5K8MmTZqE9u3b4/Tp0+jTp4/OY/Xq1cO8efPg5eUlVk2NGDFC7zW1Wi1atWqFqKgorFq1CufOncPMmTNhb28PAEhNTUWNGjWwdetWnDlzBv3790fPnj1x+PBho9u1fv16TJo0CdOmTcOxY8cQFBSEhQsXGlz/7t276NatG/r06YPz589j79696NSpk5gwXbRoEQYNGoT+/fvj9OnT2LJlC8qWLavzGlOmTEHXrl1x6tQptG7dGj169EBiYqLY5tdeew3r16/HuXPnMHHiRHz++edYv369zmvs3r0b58+fx86dO7F161Y8ffoUbdu2RZUqVXDixAl8+eWXet0j7969i0aNGqFatWo4duwYIiMjce/ePXTt2tVge0+dOoXHjx+jZs2aeo/t3bsX/v7+KF++PPr164eEhATxsePHj0OtVqNFixbisqJFi6Jy5cqIiooCAERHR8Pb2xt16tQR13nzzTfh7e0trmPI3LlzUb9+ffz7779455130LNnT/Tq1QsffPABTpw4gbJly6JXr17ifslKqLq4uODHH3/EyZMnxdfasmUL2rZtCzs7O3z33XfYsmUL1q9fj4sXL2LVqlUoWbKkznvXrl0b+/fvzzW+V+Vg1lcnIiIi26eyt3YERAWCVEqHhW+2iDuFCoYrV65AEARUrFjRqPW7d++uk3SLjY0V/+/k5ARvb2+oVCoEBgYafI1du3bhyJEjOH/+vFjdVbp0afHxYsWK6STthgwZgsjISGzYsEEnoZObefPmoU+fPvjoo48AAFOnTsWuXbv0qt+y3L17FxkZGejUqRNKlCgBAKhSpYr4+NSpUzF8+HAMGzZMXFarVi2d1wgPD0e3bt0AANOnT8f8+fNx5MgRtGzZEo6OjpgyZYq4bqlSpRAVFYX169frJMnc3d2xdOlSODk5AQAWL14MlUqFJUuWwMXFBa+//jpu376Nfv36ic9ZtGgRqlevrjNxwvLlyxEcHIxLly6J2zi7uLg42Nvbw9/fX2d5q1at0KVLF5QoUQKxsbGYMGEC3n77bRw/fhzOzs6Ij4+Hk5MTChcurPO8gIAAxMfHA8gcPzDn6wKZieWsdQxp3bo1BgwYAACYOHEiFi1ahFq1aqFLly4AgNGjR6Nu3bq4d+8eAgMD0bVrVyQlJeHhw4do1qwZKleuLL7Wli1bMGfOHADAjRs3UK5cObz11ltQqVTiPs6uWLFiiIuLyzW+V8XkGxERUUHH5BuR2R2//gg7z+lXl0rNgErWwDHfyDyePXsGADpjno0cORIRERFwcNC9Hc+qMnJ1dRWXDRo0CP369RMrw7JkJQqyrxseHp6v2LIqiPIasy2LVKVUfsXExOC1116TTAoBmV00Z86ciV9++QW3b99GWloa0tLSJCvzDDl//jw+/vhjnWV169bFnj17JNevWrUqmjZtiipVqiAsLAwtWrRA586dUbhwYSQkJODOnTto2rRpru8ZEhIi/t/d3R2enp46VWOLFy/G0qVLcf36daSkpCA9PV1n9lUgM+GXlXgDgIsXLyIkJAQuLi7istq1a+s85/jx49izZw88PDz0Yrp69arkdk5JSYGzs7Pefn/vvffE/1euXBk1a9ZEiRIl8Oeff6JTp04G2y4Igs5rSX2ecq4jJfs2DAgIAKCbBM1alpCQgMDAQJ2uvdmdP38et27dQrNmzQBkHhfNmzdHhQoV0LJlS7Rp00aneg/IPI6eP3+ea3yvit1OiYiIiIjMaOn+a3h3URRWRsXpPcY8jy3iTiHTcXd3h7u7u07iwcnJCe7u7nB2dpZc187uxW26o6Mj3N3ddRIwua2bH+XKlYNKpTJ6oPn8JMAMyZ4slPL1119j7ty5GDVqFP7++2/ExMQgLCzMrBMQ2NvbY+fOnfjrr7/w+uuvY/78+ahQoQJiY2PzjDdLzm2vUqnE8fjWr1+PTz/9FH369MGOHTsQExODDz/8UK9NObevVMIq5zihWq0Wbdu2RUxMjM7P5cuX0bBhQ8lY/fz88Pz58zy3aVBQEEqUKIHLly8DAAIDA5Geno5Hjx7prJeQkCAmxgIDA3Hvnv4XTffv3xfXMST7Nsxqt9Sy7OMcStmyZQuaN28u7rvq1asjNjYWX375JVJSUtC1a1d07txZ5zmJiYkoUqRIrq/7qph8IyIiIiIyo6l/Gr6xZZrHVnDMNyp4fHx8EBYWhu+//15ncoEsjx8/ztfrOTk56cx6KSUkJAS3bt3CpUuXJB/fv38/2rdvjw8++ABVq1ZF6dKlxeSPsSpVqqQzWQQAvd9zUqlUqF+/PqZMmYJ///0XTk5O2Lx5Mzw9PVGyZEns3r07XzFkt3//ftSrVw8DBw5EaGgoypYti6tXr+b5vIoVK+LUqVM6E3PknHCgevXqOHv2LEqWLImyZcvq/BhKlmZV3J07dy7X93/48CFu3ryJoKAgAECNGjXg6OiInTt3iuvcvXsXZ86cQb169QBkVhgmJSXhyJEj4jqHDx9GUlKSuI65/f7773qTSXh5eeG9997DkiVL8Msvv+DXX38Vx+QDgDNnziA0NNSscTH5RkRERERkJZzt1AZxn1ABsnDhQmg0GtSuXRu//vorLl++jPPnz+O7775D3bp18/VaJUuWxLNnz7B79248ePBAshtfo0aN0LBhQ7z77rvYuXMnYmNj8ddffyEyMhIAULZsWezcuRNRUVE4f/48BgwYkOdYYTkNGzYMy5cvx/Lly3Hp0iVMmjQJZ8+eNbj+4cOHMX36dBw7dgw3btzApk2bcP/+fVSqVAkAMHnyZHz99df47rvvcPnyZZw4cQLz5883Op6yZcvi2LFj2L59Oy5duoQJEybg6NG8Z5jv3r07tFot+vfvj/Pnz2P79u3iOGZZVWCDBg1CYmIiunXrhiNHjuDatWvYsWMH+vTpYzARWqRIEVSvXh0HDhwQlz179gwjRoxAdHQ04uLisHfvXrRt2xZ+fn7o2LEjAMDb2xt9+/bF8OHDsXv3bvz777/44IMPUKVKFbGLZ6VKldCyZUv069cPhw4dwqFDh9CvXz+0adMGFSpUMHqbvayEhAQcPXoUbdq0EZfNnTsX69atw4ULF3Dp0iVs2LABgYGBOhOK7N+/X68rqqkx+UZERFTg8UaTyFqY57ER3BFUQJUqVQonTpxAkyZNMHz4cFSuXBnNmzfH7t27sWjRony9Vr169fDxxx/jvffeQ5EiRTBr1izJ9X799VfUqlUL3bp1w+uvv45Ro0aJiaIJEyagevXqCAsLQ+PGjREYGIgOHTrkK4733nsPEydOxOjRo1GjRg1cv34dn3zyicH1vby88M8//6B169YoX748xo8fj6+//hqtWrUCAPTu3Rvz5s3DwoUL8cYbb6BNmzb5qsb7+OOP0alTJ7z33nuoU6cOHj58iIEDB+b5PC8vL/zxxx+IiYlBtWrVMG7cOEycOBEAxG7IRYsWxcGDB6HRaBAWFobKlStj2LBh8Pb21umSnFP//v2xevVq8Xd7e3ucPn0a7du3R/ny5dG7d2+UL18e0dHR8PT0FNebO3cuOnTogK5du6J+/fpwc3PDH3/8oTMm4erVq1GlShW0aNECLVq0QEhICH7++Wejt9er+OOPP1CnTh2dSR88PDzw1VdfoWbNmqhVqxbi4uKwbds2cftER0cjKSlJryuqqakEft1mlCdPnsDb2xtJSUnw8vKydjgmoVarsW3bNrRu3Trf4wMQ0Qs8lkj2HsUAyTcz//9aW6uFwWOJlKrkmD8NPrY8vCberpj7ODgvg8dTPiXsB9IfZ/7foxRQqHKuq1PBYcyxlJqaitjYWJQqVUpvbDYiU1q9ejU+/PBDJCUlGT0enZTU1FRUqFAB69aty3eF46vQarV48uQJvLy8ck0Ovqx27drhrbfewqhRo4x+TpcuXRAaGorPP/9c8vHcju/85Ik42ykREVFBx+/hiKyGh58t4k4hItvw008/oXTp0ihWrBhOnjyJ0aNHo2vXrq+UeAMyK+d++uknPHjwwESR2oa33noL3bp1M3r9tLQ0VK1aFZ9++qkZo8rE5BsRERERkZUoKfmWodHi50PXkfA0DR+8WQLFCr3azaFlZdsRStopRCRr8fHxmDhxIuLj4xEUFIQuXbpg2rRpJnntRo0ameR1bEl+Kt4AwNnZGePHjzdTNLqYfCMiIiIishIlpXmm/nkeK6PiAAAbjt1E1JimcHKQ4xDTStorRCRno0aNyndCiWyTHP8aEhEREREpgpKGX85KvAHAg2fp+C3mtvWCyS+d/aCcfUJERLaByTciIiIiIivRKjjPc+1+srVDeDkKSoiSZSkpmU5EmUx1XDP5RkREVNCpVNaOgKgA4826bWDlG728rFlQnz9/buVIiMjU0tPTAQD29vav9Doc842IiIiIyEqUXCgjyCqJJadYydbY29ujUKFCSEhIAAC4ublBxS+2iPRotVqkp6cjNTUVdna2Xwum1Wpx//59uLm5wcHh1dJnTL4REREVeLxBILIWpnxsEfcK5V9gYCAAiAk4ItInCAJSUlLg6uoqmwS1nZ0dihcv/srxMvlGRERERGQlSq58k5XsO4I7hV6CSqVCUFAQ/P39oVarrR0OkU1Sq9X4559/0LBhQ7G7tq1zcnIySZUek29ERET0giBwDDgiC5JX18x8km3TZBs42QB7e/tXHhuKSKns7e2RkZEBFxcX2STfTMX2O9kSERGRBfGmk8iU8poljUVWtoKVb0REZD5MvhERERV4rHQjMhdtHnkcrYITPfJtmXwjJyIi28TkGxEREb2g4EQAkTXkVflGtkIw8H8iIqJXx+QbERERZcObTiJTyqvyTcm5OdkmHuUaNxER2Swm34iIiAo6nQkWeNNJZEp5Taig6AkX5ERg5RsREZkPk29ERERERGaSVxEVi6xsEXcKERGZFpNvRERE9AIzAUQmVZCTb/Jqm6yCJSIimWHyjYiIqMBjt1Mic8lrNlMecTYi+36SV9aQiIhkgMk3IiKiAo9jHRGZS15HVF7JOTmTb8vkGzkREdkmJt+IiIiIiMwkz+Qa8zw2gl9CEBGR+TD5RkREVNCxuxWR2eSde1PuMSfb04lsAyciIlvF5BsRERFlw5tOIlMS8hrzjYecjWDlGxERmQ+Tb0REREREZlKQe53Kt6pPrnETEZGtYvKNiIiowGPFB5G55DnbKQ8528Du90REZEZMvhEREdELvOkkMqmCPNupvHA/EBGR+TD5RkRERERkJnlWvlkoDmuQb15RtoETEZGNYvKNiIiowGO3UyKzyeuQkm+GSmF4HiQiIvNh8o2IiIiy4U0nkSlpC/CEC7LFhCgREZkYk29EREQFHW80icwmrxk/efjZCIGVb0REZD5MvhEREdELzAQQmVSelW8KPuZk2za5xk1ERDaLyTciIqICjxUfROaSVwKKR5wN0NtH3CtERGRaTL4RERFRNrzpJDKlvIqo8qqMIyIiIvlj8o2IiIiIyEzySr7JtmumEeTTMla+ERGReTH5RkRERC8oOBFAZA1aHlPyo5R9lv4484eIiKyOyTciIqICj2O+EZlLXkeUUvI8UmTTNiWO+SZogfsHgIT9gCbV2tEQERV4TL4REREREZlJXpVvghISPYqjgH2iVb9IKjL5RkRkdUy+ERERFXTZkwOyKVUhkoe8x3yzTBzWIJ/EYo44lbBThIzsv1gtDCIiysTkGxEREWXDmzQiU8prQgUecbZAYi/IPQGnzZZ8k3tbiIgUgMk3IiKiAo83ZkTmktfRpeQJGeTdNFkHr1v5JmitFwcREQFg8o2IiIh0yPyGk8jG5DnmGw8561PiTtCqs/2iwPYREckMk29ERET0ghJvQomsiIeUTMl9xwma7L9YLQwiIsrE5BsREVFBp3OTyZs0IlPKu/JNucecfFomFal8opeUvfKN3U6JiKyOyTciIiIiIjMpyLOdypvMdwxnOyUisilMvhEREVE2vEkjMqU8k2+WCcMq5JNYVOBsp9mr3eTeFiIiBWDyjYiIqMDLdmPGmzQikxLySK8pebZT2VFlvzWS+37hcAJERLaEyTciIiLKhjdpRKakLdDdTmXSOMmdIJPYDdEZ503mbSEiUgAm34iIiAo83pgRmUteEyrw6LMlKkClsnYQJsKKZiIiW8LkGxEREWXDmzQii1JIYkTes7Zmj/2/5Jus2wNWvhER2Rgm34iIiOgFud9wEtmYvI4oJR9x8jmd/BeoSgUx+Sb7PSP3+ImIlIXJNyIiooJO4MDcRNYinwRV7pTRjuzdTmXeIFa+ERHZFCbfiIiICrjE51rEP8v6jTdpRKaUV1Iqr9lQ5Uw2CTlBgd1OOeYbEZFNYfKNiIioAPvt39t483+P8eZKO0w/qJSBxonkI6/ZUOVC3s3Iil4lsUymWPlGRGRTmHwjIiIqwEZuPIl0Teb///evCrcfp1k3ICLFyWO2UwXnReRT1af0Md/k3hYiIvlj8o2IiKgAU2t0b8r2X3tmYE0iehkFpdupvGc7zZJ9zDeZy175poh9Q0Qkb0y+ERERkUjLmzQiy1LwISeb04kSx3zjRDpERDbFwdoBEBERke3QKmUAKiIbkdcRpZQjTt7tyN7tNMcy2WLlGxGRLWHyjYiIiES8RyOyLGV011TKuUNByTdl7BAiIsVgt1MiIiISKWX8KSJbkeeYbwo+5OTTNAV2OwVnOyUisiVMvhEREZGI3U6JLEsph5ysE/diok0hky3okfG+ISJSCHY7JSIiIhEnXCAyrby6lco6aZUH2Z1OlDTmW/aNL7sdQUSkPKx8IyIiIhFv0YgsSyl5EXm3Q4ndTuUePxGRsjD5RkRERCKlDP5OZCsK8hElm6o+nW6nWdVvMondIMHA/4mIyBrY7ZSIiIhEzL0RWRYT3rYgcx88VwNrTqvx6JkKneuloFQxK4dlMvyMERFZG5NvREREJOKYb0Smledsp5YJw+yUcOoYHpmKv65oAKiw7vx57B0VBE8XR2uH9XI45hsRkU1ht1MiIqICSqrihsk3IstS9DEnm6YJ0Ar4L/GW6eHzDOy9eN+KMZmSbHYEEZFiWTX5tmjRIoSEhMDLywteXl6oW7cu/vrrL/FxQRAwefJkFC1aFK6urmjcuDHOnj2r8xppaWkYMmQI/Pz84O7ujnbt2uHWrVs66zx69Ag9e/aEt7c3vL290bNnTzx+/NgSTSQiIrJZUvf87AJHZFp5jXumlENONuO7SREyk2853XmcYvlYTIZjvhER2RKrJt9ee+01zJw5E8eOHcOxY8fw9ttvo3379mKCbdasWfjmm2+wYMECHD16FIGBgWjevDmePn0qvkZERAQ2b96MdevW4cCBA3j27BnatGkDjebFN1fdu3dHTEwMIiMjERkZiZiYGPTs2dPi7SUiIrJ1TL4RWZaSjzj5tE1QTBL0BXY7JSKyJVYd861t27Y6v0+bNg2LFi3CoUOH8Prrr2PevHkYN24cOnXqBAD48ccfERAQgDVr1mDAgAFISkrCsmXL8PPPP6NZs2YAgFWrViE4OBi7du1CWFgYzp8/j8jISBw6dAh16tQBACxZsgR169bFxYsXUaFCBcs2moiIyEZI3Y5ptVqLx0GkaHmN+aaQvIjc2yEVvsyblI1yWkJEJFc2M+GCRqPBhg0bkJycjLp16yI2Nhbx8fFo0aKFuI6zszMaNWqEqKgoDBgwAMePH4dardZZp2jRoqhcuTKioqIQFhaG6OhoeHt7i4k3AHjzzTfh7e2NqKgog8m3tLQ0pKWlib8/efIEAKBWq6FWq03dfKvIaodS2kNkLTyWSK40Ev2s1BqN1T7LPJZIiTI0Gbk+rtWa55iz9PGkVuu3U6PRyuN4VqdDrckA4KSzOCPDeufDV6XKUAP/ffaEDDUg03bYAv5tIiV7np6Bb3dfxc1HKej1ZnG8WdrHrO+ntOMpP+2wevLt9OnTqFu3LlJTU+Hh4YHNmzfj9ddfR1RUFAAgICBAZ/2AgABcv34dABAfHw8nJycULlxYb534+HhxHX9/f7339ff3F9eRMmPGDEyZMkVv+Y4dO+Dm5pa/Rtq4nTt3WjsEIkXgsURyoxGAnJcC16/fwLZt26wSTxYeS6QkF5NUAOwNPn7jxk1s23bdbO9vqeMpVQPkPJ/cvnMb27bdtMj7vwoXbSJcM64CqKuz/OLFC9j27Lx1gnpFfpqTsBcyCwlSVHF4Yn/byhHJH/82kRJtvGaH/fcyRyPbff4evqipgacFJnlWyvH0/Plzo9e1evKtQoUKiImJwePHj/Hrr7+id+/e2Ldvn/i4SqXSWV8QBL1lOeVcR2r9vF5n7Nix+Oyzz8Tfnzx5guDgYLRo0QJeXl55tksO1Go1du7ciebNm8PRUabTqBPZAB5LJFdqjRafHdqlsyw4+DW0bt3QOvHwWCIFKnT1IRaeO27w8deCg9G69Rsmf19LH0/P0jIw+sjfOsuKFi2K1q1DzP7eryzlDtLuFwJy7KYKFSqidcNSVgnpVanuuQCazJtCwbUYUDjUyhHJF/82kZINm7BD/L8WKlxzKoOxrcw3NJfSjqesHpLGsHryzcnJCWXLlgUA1KxZE0ePHsW3336L0aNHA8isXAsKChLXT0hIEKvhAgMDkZ6ejkePHulUvyUkJKBevXriOvfu3dN73/v37+tV1WXn7OwMZ2dnveWOjo6K+JBkp8Q2EVkDjyWSHTv98d3sVHZW/xzzWCIlsbfP63JbZdbPu6WOJweN/jI7O+ufT4yidoBGYj+p5BK/FAd7iLd6Dg6AXNthQ/i3iQqC+KdpFvmcK+V4yk8brDrbqRRBEJCWloZSpUohMDBQpxwxPT0d+/btExNrNWrUgKOjo846d+/exZkzZ8R16tati6SkJBw5ckRc5/Dhw0hKShLXISIiKoikBkjXCpxwgciSlDIUvrzbocDZTnUapLTGEZG5cN4t87Fq5dvnn3+OVq1aITg4GE+fPsW6deuwd+9eREZGQqVSISIiAtOnT0e5cuVQrlw5TJ8+HW5ubujevTsAwNvbG3379sXw4cPh6+sLHx8fjBgxAlWqVBFnP61UqRJatmyJfv364YcffgAA9O/fH23atOFMp0RERDlIzMFARK9AyCPxobikjxwJee0lIqKCgWdD87Fq8u3evXvo2bMn7t69C29vb4SEhCAyMhLNmzcHAIwaNQopKSkYOHAgHj16hDp16mDHjh3w9PQUX2Pu3LlwcHBA165dkZKSgqZNm2LlypWwt38xsO3q1asxdOhQcVbUdu3aYcGCBZZtLClW0nM1xm4+hVO3kvBOSBBGtqgAB3ubKyolItIjdYGlZSaAyKKUcqMj91OHVPyCrBuVLXZZt4OILImnC/OxavJt2bJluT6uUqkwefJkTJ482eA6Li4umD9/PubPn29wHR8fH6xateplwyTK1cqoOGw7nTlz7g/7rqFeGT80Kl/EylEREeVNeTebRLYnz0NKwYecfE4n0ilQ+cQvgd1OieglsAeE+bA8h+gVzd11Sef3kRtOWikSIqJXx+QbkWUp5oiTdUOUUn9oAM/rRGQkXgeaD5NvRCaWlKK2dghERC+N3U6JTCvPwjcFH3NyaplkJbDlwzAhVr4RUf7xOtB8mHwjMjGer4hIzpScCCCyRUrp4iPr2jHFT7ig7NYRkenwbGE+TL4RmZjSL9+ISDmk8mxKSQQQ2Yq8EtpKPuTkk8wXJHeEbMKXJOvgichK5H3es21MvhGZGG9ciUgupL4skM/NMpEyKOWYk3czFPjVafYdIu+dQ0QWxG6n5sPkG5GJ8YRFRHLGMxiRaRWUyU7l3g7pMd/k3CqO+UZEZEuYfCMyMebeiEguJLudsnyXyLIUfMjJpmkGxnxTzjWdYhpCRGamnPOe7WHyjegVXL731NohEBG9NKnrKy1v0ohMK49DSt7VVS/Iu/usdOxybpFO9LLeN0RkSezFZT5MvhG9gt9j7lg7BCIik+I1F5FlabXWjsCM5HI+MTTbqWJOiEppBxGZG5Nv5sPkG9ErcHd2sHYIREQvTapSRWC3UyKTyquyTTGVb9YO4BUp7n5Tp0FKaxwRmQsvA82HyTeiV+DubG/tEIiITIrdToksS3FJn2zkk1g0MOabxeMwkZwfKiV/yIiIZCLfZTtxcXHYv38/4uLi8Pz5cxQpUgShoaGoW7cuXFxczBEjkc1ysGP+mojkS3LMNyV3gSOygrzyHkpJi8g7vyPgcqK1YyAiIiUzOvm2Zs0afPfddzhy5Aj8/f1RrFgxuLq6IjExEVevXoWLiwt69OiB0aNHo0SJEuaMmchmqFTWjoCI6OVl3SyHqi6jr8NfuC9446q2k3WDIipg5J20ekE+VW769lxNxoe/6X+hKt99kzNw2TaEiCyNpwuzMSr5Vr16ddjZ2SE8PBzr169H8eLFdR5PS0tDdHQ01q1bh5o1a2LhwoXo0qWLWQImsiXMvRGR3HnjGVY4zUIhVTIA4N8HjwG8b9WYiJQk7wSOcu90bD55pc0A0h5g9J8Jkg/LOaGoSyntICKSL6OSb19++SXeeecdg487OzujcePGaNy4MaZOnYrY2FiTBUhky1j5RkSyJgA97XeKiTcACH1+2IoBERU8Np+gMpYc2/EoBki5i4RnChtGhGO+EdFLUs6XDrbHqORbbom3nPz8/ODn5/fSAREREZHllLS7Z+0QiBQtr9sYrYITIzbftJS7uT5s8/EbJNvAicjK5Hves335/prnxIkTOH36tPj777//jg4dOuDzzz9Henq6SYMjsnUqdjwlIhkTIEAr8DxGZE1Kuc9RSjuUgWO+ERHZmnwn3wYMGIBLly4BAK5du4b3338fbm5u2LBhA0aNGmXyAIlsGu9ZiUjGBAHQSp3I+LUnkckIeRxPSj7c5N59Sd7RZ6eclhARyVW+k2+XLl1CtWrVAAAbNmxAw4YNsWbNGqxcuRK//vqrqeMjsmnMvRGR3Ekm37QaywdCVEAppdupQpqhDBzzjYjI5uQ7+SYIArRaLQBg165daN26NQAgODgYDx48MG10REREZDYCAEHqUkCrtngsREqVV9pDyXkRm29bHjNn2Xz8RlNMQ4jIzHi2MJ98J99q1qyJqVOn4ueff8a+ffvEyRhiY2MREBBg8gCJbJmK050SkcxJVr5pOIYrkaUopvJNlrdseSXf5NgmQO/2WbbtICJSjnwn3+bNm4cTJ05g8ODBGDduHMqWLQsA2LhxI+rVq2fyAIlsGVNvRCRngiAYSL6x8o3IVPLKeygm+SbHZqjyfSskE5xwgYjI1jgYu+KlS5dQvnx5hISE6Mx2mmX27Nmwt7c3aXBEto6Fb0QkZwIArdT3cKx8I7IYrYLzIrbftNyTb7YfPxGRacm34tf2Gf11T2hoKCpVqoTRo0cjOjpa73EXFxc4OjqaNDgiIiKyAibfiEwo9xsZrUKyb7JshUqFDK21gzADvZtnWe4dIrKCEzceIy2DE2+Zg9HJt4cPH2LWrFl4+PAhOnbsiICAAPTt2xdbtmxBamqqOWMkslmsfCMiORMEQ5Vv7HZKZClK6XYqxeabprKDOpd7TPlWgHDMNyJ6ed/uumztEBTJ6OSbi4sL2rZti6VLl+Lu3bvYvHkzihQpgjFjxsDX1xft27fH8uXLkZCQYM54iWyKiqO+EZGMCRCgkqqIYOUbkcnkPeabZeIwN3kmquwKSE1YwWglEZnGwr1XrR2CIr3UKKMqlQr16tXDzJkzce7cOcTExKBhw4ZYuXIlgoOD8f3335s6TiKbxMo3IpI7O0j0uWLyjchi5Jm0MpaNt83BLdfkqHx3DbudEhHZGqMnXMhNuXLlMHz4cAwfPhwPHz5EYmKiKV6WiIiIzEkAHCDR50qTYflYiBQqr7SHcirfrB3By5Cs/RUpJjGqlHYQEcmY0ZVvmzZtQq9evRAZGYnq1avj119/lVzP19cX5cqVM1mARLZMxdI3IpI5e6nKNy3HfCOyFI1Ssm8y8SwtA8PXn8TbX+/FrP3JeUy4INN9w2QbEZHNMTr5tnDhQvzxxx+wt7fHzJkzMWXKFHPGRSQLTL0RkZwJMFD5pmXlG5Gp5D3mm3ITJbbYtFWHruPXE7dw7X4yFh5OwZ7rhte1wfCNJBG5Le4MIqICxOhup3Z2dnjjjTfQvHlzAEDhwoXNFhQRERGZnyAA9iqO+UZkTUrJicilHTP/uqDz+6c7c6tFkEmj9PwXt8oOELTZlvFrYyIiazG68s3Pzw8//fST+LtGk8u83EQFBHudEpHcSVa+ZbDbKZGpCHkkcBRd+WbtAF6R/HdNtgtV+TeGiEjWjK58W7p0Kdzc3AAA6enpmDt3rtmCIpILFb9BJCIZEyBIz3YqsPKNyFKUknzLK8koR7KdcEHIXvmW9QWLTNtCZCFpGRqM23wGW0/dQZVi3ljQvToCvFysHRYpiNGVb1mJNwBwcnJCrVq1zBIQkZyw8o2I5M5BKvnGyjcik8krfyPX/I4xZJu8+o/c42c3UyLj/XPpATYev4VUtRZH4x7hx6g4a4dECmN05VuW1NRUzJ8/H3v27EFCQgK0Wt2L9hMnTpgsOCIiIjIfQQDsJSdcYPKNyFI0sk/wZFJIM3TItyoxW+VbzmVEJGnEhpM6vy/cexWjWla0UjSkRPlOvvXp0wc7d+5E586dUbt2bahY+kMFGD/9RCRnBmc71TD5RmQqeaU85JvgyZvcWybffZOVfOOYb0TG0mh5jJB55Tv59ueff2Lbtm2oX7++OeIhIiIiC7KX6nbKyjcii9FKHIJypMTbVtl2OxXjZuUbkbFYVEHmZvSYb1mKFSsGT09Pc8RCJDu8jCEiORMEQbryTZth+WCIFCqvBI5sEzw5KKUd2SmiSWL1mxIaQ2RGzL6RmeU7+fb1119j9OjRuH79ujniISIiIguyV0mU3Wg42ymRpSi5p5Pck1fyTShm73bKjAIRkS3Id7fTmjVrIjU1FaVLl4abmxscHR11Hk9MTDRZcES2TrbXZEREyDyHSVe+sdspkaXIccKFtAwNLtx9iqBCLvD3dAGgzLoq+Y75JkFJbSEyA6apydzynXzr1q0bbt++jenTpyMgIIATLhDl8HqQl7VDICIymuRsp5xwgchi5FZd9Tw9A10WR+PsnSfwdHbA0t41Uae0r+S68mqZPrntG5EYd/bKN5m2hchCmNcgc8t38i0qKgrR0dGoWrWqOeIhkhVB4kLGySHfvbmJiKzGgRMuEJlVXvkbuXU7/fXEbZy98wQA8DQtA5O2nEVkREPZF1Y5Ix0f2O+CM9KxTvM2EuElu33zQrbkm0r136+ybQyRRTD3RuaW7+RbxYoVkZKSYo5YiBRBtt+SElGBIwisfCOyNrl1bfwpKk7n9wvxTw2uK6drom8dv0dL+6MAgJb2R9Eh/UtZxW/YfxkFRbSFyHwKYu5NGec4+ch3ic7MmTMxfPhw7N27Fw8fPsSTJ090fogKEqnzFU9hRCQXAgTpyjcNZzslMhWpKvnstDIrrzJcHSKvdmTnjHQ0tzsm/h5iF4s6dudlfGMqNeGCXNtCROYi21OcTOW78q1ly5YAgKZNm+osFwQBKpUKGo3EN+hEBQhPYkQkJ3ZSybfkG4D6KeDoafmAiAoYpVw3yLkdhfAM9irdBgSrEpAm10YJObqdZi60VjREslAQx3zjWcGy8p1827NnjzniIFIMuXUfIaKCSxAAldSll/oZ8PAoEPi25YMiUpi8LgvkONup0nirkvWWZQj2sk4ovlDwEgpEL4NHCplbvpNvjRo1MkccRLIkdU2mjAs1Iioo7KTOZIIWyNC/GSUi01PKl3ZyboUH9MezdlGp8US2+yb7bKdZi+TaFiLLKICFbzLuWi9PRo35duPGjXy96O3bt18qGCIl4CmMiORCAGDPMd+IzEpps52q8lEfIpf7Ok+VfvLNFal5jtdnu7KN+cZup0RkAM8KlmVU8q1WrVro168fjhw5YnCdpKQkLFmyBJUrV8amTZtMFiCRLZP6toDfIBAZ7+CVB/h212XE3Hxs7VAKpMzxWg1UvhGRRcjtusFQdYj0JFTyaJu7ROWbG9JkkzzMXdbtniIaQ2RGBa/0TRnnOPkwqtvp+fPnMX36dLRs2RKOjo6oWbMmihYtChcXFzx69Ajnzp3D2bNnUbNmTcyePRutWrUyd9xENosnMSLj7LmYgA9XHAUAfPf3Zfw+qD4qF/O2clQFj+SEC9qMgtn/gsgM8roskFvlW37I5ZrIQ6LyzV2VJrvEqEhqwgW5toXIQgriZY9cviBRCqMq33x8fDBnzhzcuXMHixYtQvny5fHgwQNcvnwZANCjRw8cP34cBw8eZOKNCjyljN1CZG4jN5wS/6/RCvjij3NWjKZgMtjtVKtBQfwGmMgaNArJvkndxMnlksgDqXrLXJEq42u67GO+ZSXfWNFMlJuCeNUj21OcTOVrwgUXFxd06tQJnTp1Mlc8RLLHcxiRcR48S9P5/UhcopUiKdgkJ1zQagGVUd/PEVEejKme0moF2Nkp79ZPLlUVhrqdKiMvyjHfiIxRECvfyLLyPdspEb0gOb4Jv0IgIpkQBEAlmXzLQMH8DpjIOuR05aAycIcqfU1k5mBMRKrbqZsqVcbXdJxwgazn4bM0zP/7CgRBwKAmZeHv5WLtkIySn8lkiF4Gv9YmMjHZXqcRUQEkGBjzTcPKNyITMeayQL7dG1+QnnBBHqS6nSpjwgUVxNs9+TeGZKLfT8ewMioOP0ZfR+//xvaVg4JY+ZbbaWHsplOIT9I/N9LL45U10SuQHN/ECnEQEb0syTHfBCbfiCxJCck3STJpliMy9JY5Qy2bbrN6sn+eWPlGFnT/aRpO3Hgs/n7+7hPEPUi2XkD5IJl702osHYZF5XaOW3vkJj5cKZ/kqRzwyprIxBR7AU1EimO426kGvEQgMhEjLgvkdOlgqDhE+gtJeTTMQaV/g+2sUsv4mo4TLpB1PE/XT2Q/S9NfJhtp960dgVnldYqTU/JUDnhlTfQK5Dy+CRERYGjCBQVVvqU+AO7uAFLirR0JkUHyTfLkTi7NcoBE8g1q2cRvkCpb8k0miVCSN6nZm+1k0p9TcjxLhSetjTkryDp5amNe6sr6559/Rv369VG0aFFcv34dADBv3jz8/vvvJg2OSI7k8i0vEZEA6eSboKTk28NDgCYNeMiuE2QdxlwXyGlWTUP30XIe881Q8k2+SVF2OyXrkDqX2cn6ckLZx418J5WRp3wfCosWLcJnn32G1q1b4/Hjx9BoMv9YFSpUCPPmzTN1fEQ2Tep8pVX2FyREpCCCYGDMNyWNcZJ1os5IBp5dk08pDhUo8k3y5E4uN3bSybd0+Z4uhOzdTjnhAlmSnCvfrB2B5RlzVuCpw3TynXybP38+lixZgnHjxsHe3l5cXrNmTZw+fdqkwREREZF5qaSSb5oM5V1tJZ0FHp8FUu9ZOxIqYIw5lOTUsyk/N6hyOYtIJt/kOuZb8k0g8V9Am5G5s1j5RhYkWfkm66SWso8bo/4+KXwbWFK+k2+xsbEIDQ3VW+7s7IzkZA7GRwWL1KlIlhdqRFQgCRCku51q1FDsBWf6Y2tHQKRHo4BrBzmPgyuVfHNChqy6A4sexQDpD4GUO/8t4IQLZDlS90GSY6nZIJmEaXFyOY/LQb6Tb6VKlUJMTIze8r/++guvv/66KWIikjWeoIhILgQBcFDp35CplJx8ExTUpZZkwZgjSalf3Nlaqwx1gzU45psss28AIACp8cDzu6x8I4uS8/A7Kqm5nBV6bhYZVflGpuKQ3yeMHDkSgwYNQmpqKgRBwJEjR7B27VrMmDEDS5cuNUeMRLLC0lwikg1DF5WK63aarS0CZ+0iyzLmUJJT8k3yBhUGrn9srF2GwrGX+BLCGenQyDmTAADPrgBuRf/7xbb2BSmT1LlMLmM/Sle+ySP2l2XMfatc9p8c5Dv59uGHHyIjIwOjRo3C8+fP0b17dxQrVgzffvst3n//fXPESGSzpE5Gsv2SlIgKHMHQjaUmA4q64Mze3YqVb2SDlHpvY2vNMhSPI/ST8vYqQb6Tz2T/QKk44QJZjlTyTS73RgWx16lxY76RqeQ7+QYA/fr1Q79+/fDgwQNotVr4+/ubOi4i2eK1DRHJh3TyTaVRy/emU1K2E7OWlW9kWcZUFsiq8s3AHaocxnwzVMEhOeszAHtBbc5wzCj7bKcc840sRyrRZmvngfyRdfB54mynlvVSybcsfn5+poqDSJakz0U8QxGRTOSWiNKkWy4Oc8t+5chup2SD5FIZAuSvOsTWhuIwXPkm/WWDSivX5FuWbMk3G9sXpCypasNf2MnlywW5TAxhSsZ1KZXH/pODfCffQkNDJT+YKpUKLi4uKFu2LMLDw9GkSROTBEgkN3K6gCaigi3Xi66MNMsFYnbZKj5kfzNNcmPUmG8KuHiQaoGt3XMbHPPNQPLNTgmVspxwgczs5+g4TPnjHOztVHi/VrDe4/JJvkkslEnsL4uVb5aV79lOW7ZsiWvXrsHd3R1NmjRB48aN4eHhgatXr6JWrVq4e/cumjVrht9//90c8RLZFsnSap6hiEgeVLl1Q1JU8i17t1MFVfSRYtj8pYMm/aW6ottauwxV4knNdgooodspIN7u2drOIEVIVWsw4fezyNAKSMvQ4sfo63rryOWjJ133xu7aMtl9spDvyrcHDx5g+PDhmDBhgs7yqVOn4vr169ixYwcmTZqEL7/8Eu3btzdZoERyoYAvr4mooMht8gElJd8E7YtBx5l8Iwsz5rLApitDtGrg7nbA3hkIaoG0DOmbUakvH22tVYY2s6Hkm50Suqmz8o3M6MztpDzXsenzW17kHLsRjJpwQdmbwKLyXfm2fv16dOvWTW/5+++/j/Xr1wMAunXrhosXL756dEQ2TuobVFa+EZFsKL3yLavLmKDFi+oPLQceJ5ujseVrh/THmf9q0gBBQIqBsZ2ku53aVrsMdjtVSZ8T7GTbTf2/hqpULxrN8x6ZgTHjpMmlMEG6LTIJ/iUZMy6nrZ3H5SzfyTcXFxdERUXpLY+KioKLiwsAQKvVwtnZ+dWjI5Ihnp6ISDZyuyJWQvItq2pFEKDToSS3ij8iUzPixsWmb27ssnWUETKQki7f48fQjaYjpCvcHORa+SY2M1vyjVeoZAZ2RsxRIJfKN8mmyCT2l2ZM5Zv5oygw8t3tdMiQIfj4449x/Phx1KpVCyqVCkeOHMHSpUvx+eefAwC2b9+O0NBQkwdLZGukzsdKP0cTkXIISu92Kg6WLkDn8pEVIGRj5FIZAkFrMFY5XBMZnnBBaZVvWVR4ce6zsZ1BimBM5ZtNf7mQjXRT5BH7y+KEC5aV7+Tb+PHjUapUKSxYsAA///wzAKBChQpYsmQJunfvDgD4+OOP8cknn5g2UiKZkMsfGCIiVa7JNwWMjSYOlq4Fk29kLbIf803neBEM3KAaeKqN3bgaisZQ5Zu93CrfJKvchByPEZmOMZVvsv7oKfx6wagx32zsPC5n+Uq+ZWRkYNq0aejTpw969OhhcD1XV9dXDoxIDqRORbL59pqICjwh126n6ZlXZfm507Y1WRfNQo7KN85eRjZGa8sfyew3n4LWwIyAgNRVka3ddBv6gtRQ5Zv8ZjvNkXxTAS/Odza2M0gR7JQ05pvk2U0mwb8koxJryt4EFpWvMd8cHBwwe/ZsaDTyHeuByNz47QARyYUqtyRURhpkf8WVfaBxgZVvZB3GJKCUW/lmWwzFo+jZTjnhAlmZTZ/fsimQ3U6Ze7OofE+40KxZM+zdu9cMoRDJjxzGNyEiMkTI7WZMo1bACS0rfnY7Jdtm24datuCe34FKK90lXfqayLYaZigcQ8k3R7kl38REW9YCFVj5RuZkXOWbjD97co6dbE6+x3xr1aoVxo4dizNnzqBGjRpwd3fXebxdu3YmC45IjniOJiLZ0OY15ptSTmjZxjxSZb8ZJTI/YxJQtn1zmi22xBOwgztyzgtoqI021yrJgAQ4qJTW7TSLKtuXDTa3N0gBjKmEtenTW55kHXyeOOGCZeU7+ZY1kcI333yj95hKpWKXVCpQpLqYstspEclGrpVvCuh2qjfQuADdm1Ei22DTyTed2KS7nWoFA+Pg2thgT1Lb2VDVGwDYG5iIwXblMrOpLX/GSLaUVPkmPXOrPGJ/WcZ8OSSkPwbgZ/ZYCoJ8J9+0Nj0iLJH12dh1JhGRYbkloTIU0O1Ub6wjjn1ElmfcbKdmD+MV5Ei+SayhFQTJ04XGxs4hUtEYmmwBABy0cku+Zck24QIr38iMjKl8s+3z2wuSqTetJpdJZuTPqDHfks4DKGv2WAqCfI/5RkQvyGF8EyIiQ4Tcup1q1JD/zVqOKhAOPE42yrYrQwSd/0pXvknHb2vf2Utdoymq8k3Ica7LXunL8x6ZgVHJG5s+v70gdW5jjyZAm/bY2iEoRr4r3wAgOTkZ+/btw40bN5Cerjvo6tChQ00SGJFc8RRNRHKhyu2MpVHCmG/ZJ1yQ+p3I/Iya7dSWS0Nydjs1sIrUDbbGxtolFU1uyTcHuU24IN35N5fHiF6NMckpmeTeJAk2dg4zNaOSp6kJQMo9wDXA/AEpXL6Tb//++y9at26N58+fIzk5GT4+Pnjw4AHc3Nzg7+/P5BsVeHL+A0NEBYyQR+WbUk5oOmO+gRUgZHNs+/5ON/lmJ5F9M5Rks7lupxLh5JZ8c0OKGaOxhOyVb7a1L0gZjKlute3K3hcMVfXaWz4UizFm32gFAA+PAN6VAE92P30V+e52+umnn6Jt27ZITEyEq6srDh06hOvXr6NGjRqYM2eOOWIkslmGTldyKa8mooJNleuECwrodpqzC1bOJByRBRg3m5xMPpOCAEeJO9H0DK1kO22tXVJVOrkl30rhjjnDMYNs7VPZ51hmW/uClMGYyjfb/nLhBZVEXa9cEocvy7jk23/b5VmsmaNRvnwn32JiYjB8+HDY29vD3t4eaWlpCA4OxqxZs/D555+bI0Yi2VH4eZqIFELIbYbyDAUk38RKN02O31n5RrbFtm9OdSvfnKWSbxrpY8rWup1KndIcVYbPg8VV98wYjBlkXYCqVMD9BOD4H8Dt01kPWi0sUi6jutXL5MZIqqpX6d1OjWker5hMJ9/JN0dHR3Ea3oCAANy4cQMA4O3tLf6fqMAwNMCwTP7IEFFBl0flm+zPZTkrPlgBQpZnTPWXTV835BjzzUki+Zam1krPdmpjN645wymvuom/nMYYXN8HT2yues8oN04D+1cDF/YDW8YD96/xSweyGtkcQxL9TpU+4YIx+0Yuu08O8p18Cw0NxbFjxwAATZo0wcSJE7F69WpERESgSpUqJg+QSI54jiIiOci122mGAiZc0BvrjZVvZJtsOvmmM9upAEeJu4e0DI3kTaqN5d70YpzquByeKsPjurmp0mwugZi7/2K9HpNtkRY4spbnPTIL4yrfzB+Hudj0ZDgmYFTlm6ACnlwAtOl5r0y5ynfybfr06QgKCgIAfPnll/D19cUnn3yChIQE/O9//8vXa82YMQO1atWCp6cn/P390aFDB1y8eFFnHUEQMHnyZBQtWhSurq5o3Lgxzp49q7NOWloahgwZAj8/P7i7u6Ndu3a4deuWzjqPHj1Cz5494e3tDW9vb/Ts2ROPHz/Ob/OJdBg6X9n2RTQRUSZBm9uECwpIvul1M2XyjWyTbV825D3hwoTfz6DvymN6y20tcZVzO9e2uyi94n+ckGFzk0bk7r9Yb+Vo193zYOcxMgdj7nnkcghJzeSsVfj1glFjvgGA+gnw7KrZ41G6fCffatasiSZNmgAAihQpgm3btuHJkyc4ceIEqlatmq/X2rdvHwYNGoRDhw5h586dyMjIQIsWLZCcnCyuM2vWLHzzzTdYsGABjh49isDAQDRv3hxPnz4V14mIiMDmzZuxbt06HDhwAM+ePUObNm2gyTaWTffu3RETE4PIyEhERkYiJiYGPXv2zG/ziXQYOl/J5Y8MERVsqtymKVNEt9P/6E20oJB2kWLY9Jd2OWKTivTQtUSkqPWT+baWuMq7JbqcoDZqNkdZUHgSgazDmCPcps9v2Ria7VTJ8jXhgkbusz9bn4M13zwyMlLn9xUrVsDf3x/Hjx9Hw4YNIQgC5s2bh3HjxqFTp04AgB9//BEBAQFYs2YNBgwYgKSkJCxbtgw///wzmjVrBgBYtWoVgoODsWvXLoSFheH8+fOIjIzEoUOHUKdOHQDAkiVLULduXVy8eBEVKlSwbMNJMWQzhgERkQQhl1n+FDHbqRj/fzedWbP/8SaULEj+3bIEA//Pm6112cp+3eaEjDzXd0IG0uV0rScIgDpV+rGku0CgZcMh5ZP9mJbZSFW+KX3CBWN2jUx2nyzkO/l27949jBgxArt370ZCQoLeAafJbea0PCQlJQEAfHx8AACxsbGIj49HixYtxHWcnZ3RqFEjREVFYcCAATh+/DjUarXOOkWLFkXlypURFRWFsLAwREdHw9vbW0y8AcCbb74Jb29vREVFSSbf0tLSkJaWJv7+5MkTAIBarYZarX7pNtqSrHYopT3WkGHg856Wng576+a2yYJ4LJlOenq6OKkPmZ8mw/BnVtCkI0OdDqgs97k2+bGkTodKkwGVJgPQav67iM6AoE4DeLyShWhy6979n3QzXF+a7Hj67zgCAGjU/91IG3ee1giCTf1tVKtfJNzcYCBJlY2jSoOnqc/hZOdqzrBMR50Ou3uXITEnBjSPb0NrQ/tCTnidZ5g6I+8ktjpDI4ttJ5VIVGco595fSrqBttlBi77229DELgb1/j0HIdYfQqlq0JR79W2htOMpP+3Id3YgPDwcN27cwIQJExAUFGSymyRBEPDZZ5/hrbfeQuXKlQEA8fHxADJnVc0uICAA169fF9dxcnJC4cKF9dbJen58fDz8/f313tPf319cJ6cZM2ZgypQpest37NgBNze3fLbOtu3cudPaIcjW2bsqQOISZ/v2HXCWuvIhReOxlF/6f4L+3PaX5HhCZB5p8WcQYuCx9JTn2L1zB9QqT4vGBJjuWHLT3oOn9jo8tTdgL6QhyV4LAfZItruNZ3bXTPIeRHk5f0f6WiG7Y8dPICPOPOUFr3o8uWtvw0N7GwDgJCTh6VMPAN5GPVcQgD//3CbZncsaHqYCWX973I1IvgHAru1b4ezsbr6gTMhBeI4KD46jrMRjl8+dwsX4bRaPSUl4nacv9imQV0ohJiYGjrf/tUg8r+LxY3vk/GLhyNEjyDidZJ2ALOD6M0Bq/3WwO4BxjmvE31WPE6D6dwcOJH+HR+5SZ5j8U8rx9Pz5c6PXzXfy7cCBA9i/fz+qVauW36fmavDgwTh16hQOHDig91jOBJ8gCHkm/XKuI7V+bq8zduxYfPbZZ+LvT548QXBwMFq0aAEvL69c31su1Go1du7ciebNm8PR0dHa4cjSvajr2BynP1hvs+Yt4OnCyreCgsfSyxkWvUNvWYuwlnByyPdwpPSSLhxUA3elH3OyV6F5s2aAs6/F4jH5sfTsGlRJZ6F6BEDQQvCpCajsILiXArzfePXXJzLCnQNx+P36pVzXCQ0NRavKpu0TaLLj6elFqJ5ezvx/agI8bnsCT3N/SnZhLVvCwd42zuvXE58D/2bea4QYmYBvVK82fAJKmDMs01E/gd3+aOCW/kPlSgajzFutLR+TAvA6z7Dj1x8BZ47muk6VkBC0Di1moYhe3k+3jyD26WOdZTVq1IRviQbWCcgC/jwdD5w+pbe8sf1JyfUbJG1GRpc9r/SeSjuesnpIGiPf2YHg4GCTj3M1ZMgQbNmyBf/88w9ee+01cXlgYOZFSHx8vDjDKgAkJCSI1XCBgYFIT0/Ho0ePdKrfEhISUK9ePXGde/fu6b3v/fv39arqsjg7O8PZ2VlvuaOjoyI+JNkpsU2WYmcnfTHp4OjAbVoAWeJYOnHjEcb+ehopag3GtqqIVlWC8n6SjVKp9MeRsHdwgKMjy0Ytxd7O8N9zVUY6HB0cACucy0x2LDk6AuoEIOUGYOcKODgDEAArtYsKJkPXCtmp7OzN9vfjlY8ne4fMHwCws8t3rxc7Bwc4OtjGed3B/sWtzwCHP4x6jr2QJp9rOsEBhsbls9eqYe/gID2qPBmF90z67B3yTieY8/xmSnYSXS/s7Oz0Yr+blIIRG07iSsIzdK9dAkOblpXtkCmzd1yWXN7G7pDkctWDiybbl0o5nvLThnx/DTVv3jyMGTMGcXFx+X2qHkEQMHjwYGzatAl///03SpUqpfN4qVKlEBgYqFOSmJ6ejn379omJtRo1asDR0VFnnbt37+LMmTPiOnXr1kVSUhKOHDkirnP48GEkJSWJ6xCZEgemJHP5fNNpXLz3FDcSn2PkxlNIlZhdztYkPE1F9yWHUHXKDkz6/Qw0/w1eKz2lOw8ei9LmMlaLEiZcEATg+R0AApCRxAkXyGbJ49wn4GXOCbY0W2j26F9TPdB7/M3U+frPSTe+S5H1CYbP65oMyP6cTjbHuAH75fu5EyTG7Fzw9xUcvPIQ956kYe6uSzh7x/jKJ1tz+7H0DKZ2KgP7jNdPr8SoyrfChQvrZHOTk5NRpkwZuLm56WX6EhMTjX7zQYMGYc2aNfj999/h6ekpjr/m7e0NV1dXqFQqREREYPr06ShXrhzKlSuH6dOnw83NDd27dxfX7du3L4YPHw5fX1/4+PhgxIgRqFKlijj7aaVKldCyZUv069cPP/zwAwCgf//+aNOmDWc6pVdi6G+JnP/IkO3SagVciH/R1+dZWgb2XEiw+eq3ZftjEXX1IQDgx+jraFLRH40r+Gf+XclxrCh8Uimbo8rtrljQAlqZD4arTf8vX/DfB0tl99+9Jy8eycwEbebnDcalO2z7skHI9q+Q71g1NtS47NdnzwRX+Kl0b5ofQX+MS22GcWPD2YZckm/aDEDQiJ9LIlMw5osDjUz+5KokvhbWPtcfH3714Rs6v0/fdh5r+r1ptrhsCpNvr8So5Nu8efPM8uaLFi0CADRu3Fhn+YoVKxAeHg4AGDVqFFJSUjBw4EA8evQIderUwY4dO+Dp+eKP49y5c+Hg4ICuXbsiJSUFTZs2xcqVK2Fv/6LEffXq1Rg6dKg4K2q7du2wYMECs7SLCg7BwCW1DV1nkoJIfazin9j+TcEP/+iOqzNiwykcG98Mdiog5/eJGmbfLEqVW+UbAKjTcn/clgla4H4UkHz1xcVi1heJPEmTOWnSgXt7ANcAoHA1o55i25VvrxabLZ3Xs0fyGB4AXgxL86X6A6RL3BoJatv/O6vD0Oy6GjVvnMnkjDl12VICPlcSXTK0GunKsOyep9t+LxST4TnklRiVfOvdu7dZ3tyY6iCVSoXJkydj8uTJBtdxcXHB/PnzMX++fql4Fh8fH6xateplwiTKN9u+iCa5kvpcrTp0HR/WLyWxtu168CwzoZP5DaNum1g1amFC7heMaWnPoT/6qUxoUgBBndlGQftf4i2r4oMXj2RGz29kVl0m3wQKVzPq5tSG8lP6shogCIBg6GtHw7Q21Ljs+8IZupW9DwQvCLBDumAPJ9WLc6OQIaMvIQQBgiZDclgHaDJ440wmZ8wZQSOT0jfp4VDyjl2J164Zgh0cVPLYb3KS77rjbdu2Yfv27XrLd+zYgb/++sskQRHJhcFup5YNgwoIqc/b1fvJlg/EVCSucmypQqJAyKPyrfX3Mdh1Tn/CInnIltwVK9/sdH8nMov8D7xt21/aCTr/l3O30+xtccqRfEtH5lA66hy1CbJKvkHA3Se5VL7xiwcyNSMO7wyZXNvZSUyaoNXkfT6XSfPyJQO2MUmO0uQ7+TZmzBhoNPonda1WizFjxpgkKCK5MHSutanrTJIvbQaQmiAmCvJfb2DbpL9htHgYBVselW/q9DRM2nLWQsGYmpDtJJ31H4V0O312DUi6YO0oyJAcN3DGnLujrugP/m87dMd8yy9bqnzLHooTdL98yOpympWEE58js26nMXcMnNe1rHwj0zPm6JbLF6v2ErOdZuRxnQTIp33GE+CgNzAMmUK+k2+XL1/G66+/rre8YsWKuHLlikmCIpILTrhAZpV4HHhwGHhyEYDM8gVaDZB4Aki5a3AVqVnZbbv6Q3lUhsYG+o8L0g3OhGXzdD5LOSrf5Fz9IQjA47PA08tAhowrXxUt/5Vvv8XcMUMcJpKRljn5ykt2O7WlyrfsoTipdCvfsirecla+QZNu7rBMRxBgJ+Qy2ymTb2RiRk24YEPngNzYSSTfNJq8Y1fatasz1Oxyaib5Tr55e3vj2rVresuvXLkCd3d3kwRFJBdZl6BN7Y5jqsMytLWLgvLqk8hqUhMy/02Os2oYL+XZNeD5beDhMYOrSM4qpbALGJuXR/Ita0wk+X6rmyNusdupXNsD3WpFI76RJ2vI9vkStLL+uEGrAR5GA4/P/Je4yX9jbOn8Ieh0O81Z+eb437/y7nbqJBio1NOy2ymZnlETLhiRwLJVGbnNCv8fWZ/jJbhDXtW+cmLUhAvZtWvXDhEREdi8eTPKlCkDIDPxNnz4cLRr187kARLZMkEAaqvOY5nT1wCAD7Ab6emOEIRmVo6MlCUzYSCrP+5GzA4l8QWjTd2kFQiGKiT+44zMig+1Rgt7O7mN/5Gti5zewSPjG9Ds+0xWJ4WCJNvJTaLSyA5a1LM7CyeocVBbGWlwsmBs+aR5ntkGQf3fT/6TiUbcu1qMTuVbzjHfBIcX/2bfhXKqfMP/2fvueNmN+vozkrbd/npz770b44LB4ArGcajBiQkkOCQEggOE9qOHHggECDUQMDYQijE22Ma9Ppfn8lzf8+u93Ptu364yvz+02pVmRlptH92n8/nY765Wu3d0JY1mzpzvOYDGHFcVsfItRgcQpjuIiuebqHLJMy41CnaYDoO5tnB8urKu102Ys2hY+fYf//Ef6O/vxzHHHINDDz0Uhx56KI499lgsWLAAX/va1zrRxhgxpMb/S9zgef21xPfnXCcco8eo1GdGS1MZLs2a+1SUDnEuoI5yKlUpyypHJKnMC8r/PBcCF9whGbHyTVIEk2+f0q7D9ckv4SfJr+H65BehyEwGu9VuVf/RxiBTyZmXfPMuPpR8AhcQMeVbAn5lp3q0+74YUiKM1U6UF1Y9xOGeu4DRB7h95tq87yPar3rdhDmLhpVvw8PDWLlyJe68804888wzyGQyOOmkk3D++ed3on0xYkgNSilOVrxl2IOkgJketSeGjVzJwNPbpnDwgj4cOL+v181pHc6EZ24925Et8ROEKA/QoghSJ+3UKTvVjQhO2KgTuOAuAeR+iB48yrcInpf9AZ6FBe85UmHirep91ddnKuvwOuVR3GKd05WmNQ5X+6mBZlSjMvXrziIWgYUE8ZLXfmWnUfN8S/iR8pYZ9xkx2o4wY9PoKN/4bWHaPtfG50codTxILQtQGtZwxUAT5BtgqxUuvvhiXHzxxQCAqampdrYpRozIwK+zlSnZa3/DbFHHX/z3w9g0lkNKU/Djvz0T5x25sNfNahHU9f+IgAQ/lH/68Gbh9rm2eig9Qnq+RVr5Vi4BY3uAwflgFTyRhGdiHeHjmMtw92OUepQhSejIEC+Z8+3kd3BLUVLyjVW+0cafRTL1605TWNUbUCPdWOVb1DzfVL+UQjP2fIvRfoSpyjBlqj0PgOhYjP0wcKEujCKQnAPihh6gYcryK1/5Cv7v//6v+votb3kLFixYgBUrVuCZZ55pa+NixJAd+1lXGwn87skd2DRmJwCWDAsfvfHZHreoDag81EXS/sFUU2soXUBw2t9nbnlRuH2/G8D0GiHJt2iuJ1CgnAcefRhYsxZ4fCWw8eHKW9GYCAhhxco3+SFI2q1AjRr5Qa0aY0VNRF75VmlKSuCLVqaO8i3hfcP08VCTERNPI0F9yMLY8y1GBxAqcCEil53oWKr9V8C9I1NpfTswSkeCdzDiQIZm0TD59oMf/AAHHnggAODOO+/EnXfeidtuuw2XXXYZ/u3f/q3tDYwRQ2b49bVzrA+OFH61arvn9Y7J+sb/8sNf+TbXyCqJ5mj7BXQjeFKZrih0IqnmpRTY/BRQdqmMVjkenRE8HgeekIwIH8echn/aqR/5dijZ3eE2NQnPhLPyc4OXnVTkW6XxQco3J3ihCiMiZaeUAqVRaH6eb5Ye+0TGaDvCkW/RYN8Cy04D7p2IHF5opFFH7avnu9OQOYiGJRO7d++ukm9//OMf8Za3vAUXX3wxDjnkEJx11lltb2CMGDLDT2o91wiRKCGViFoiYxg4yjf+HYnmNAyClW9+kGmSNtfx0p5Z3PrcKI5P+O/jqEOi2aVRYP3j3k0TWytvRXikHHu+RQs0nPLtG4n/BvCuLjSoUbhu/opn2NwoOxUo3/w83wTphlKCGgANKjuNlW8x2o8w93dkPN8EvZtpoeIh638MYUInZMW8vgQm897+UKuncNZj5VuzaFj5Nm/ePGzfbitLbr/9dlx44YUA7IvONOPVlBj7F3yVb91tRgwXUtocNACtlvzwb8k0qfFAkGQaBtIezxzD8zuncck3H6hbApdCRfkWxfNCKaD6kfERPB4Hcdmp/PDcL16yyo8YOUXZJGmqpnvSSdHMvSPToorTkiQRkW9izzcSlbLTijJH8esXYs+3GB1AmLtbpj4gCELlWzW4yf8YInJ4oeGrnnUQK9+aRsOz1De84Q246qqrcNFFF2F8fByXXXYZAGD16tU44ogj2t7AGHML0wUdP35oM258akc0y5gY/Pih2DReNsxF8u3ercAPH9iI7ZP8w26uXWpzTbovK752x0sAAJWE9XyL4oVGAeJDvkWZtPKUnfLH8fjmCfzwgY1YuyfO3e4dvIELbgQR3lZJwgkNdU06K+ROo92BTP2Ho1AJLDvlPN+ionyzry1f8s2KlW8x2o85lXYq2FZVvgVApj6uUfAtp0jWGRtCnwuWPr1Bw2Wn3/jGN3DIIYdg+/bt+OpXv4qBgQEAdjnqe97znrY3MMbcgWVRvOG7D2NjxQz/+Z0z+NTrj+txq1pDtmTASCnQiHcwE+E+OPJQmlRcyYpfvwh8+B4FwFrh+/I+8GPlm8y476UxAPXN31MkyoELABQBGW9ZAInwBNTtO8NMpO97aRTv/OkqUAp87Y51+NP7zsORSwa73MAYHjCeb+x4wQ2jnEeyf14XGtUI3OSb1RR5I5PZelX5xpSdlqkKWtEksMq3yAQuVJJpFT9vqqiVnRo5gCQANdnrlsQIRJi004gMInw93yzxmxVE5fBEYMUwoUKBjJh8axYNk2+JRAIf+tCHuO3XXnttO9oTYw5j5cbxKvEGAD95eHPkyTcAMKEKauMj3AtHHMrc4t4qxJs/5hpZNdcSo2RHPV+P6CvfBPePUQRUWVOCQyCg7PRDv3m2SvSUDQtfu+Ml/ODqM7rYuBgAuLJTN5SAe47KriaoXG+N9gYyTbxrnm9e5Ztb7VamXsUsiYrnW4Ug8Pd806NDvplFYM89dh++4nW9bk2MAIQLXJCnDwiCyPPNCHHLRNnzjW255td/uCH7s0pihBp93nzzzbjsssuQSCRw8803B+57xRVXtKVhMeYeNo5le92EjkCHykXWR+QZMycx15Rv9SDvtdZcw+ZCOXqUEEQEABEn3ygVK9+MEpDs63572oWAwIV9Wa9n2J9f2NuNFsXgwKSdul4HTWxMGctOPcq3uRC4YLclxXi+uUMW2LJTYpTse01E5suESn+g+infLCM6aaflKftfR20p+9++VVAKjD0IqH3AgmgtmIQZtkWGfBMq31C5DoOUb9E4PiGYpoueUTmaQj9xjS9i8q1phCLfrrzySuzZsweLFy/GlVde6bsfISQOXYjhC5EXl25aSKjRfqCaAutEGpGHzFzEfsa9yYsmByLxrdNd1FvhTDuBCxERS3jhp3yrqFgojWaH4Va+1aFBonh4cw40vPLNKks4oXE834yCfT8p6Ya/QqaJd63s1F/5VkTK8x4xy/Z9J3v5Y+Va8+3XTT065Ju777Z0QE357zsXoE8B5WkA05F7NonUYiyMiAwiqOunM8hLSBEdZtkCpp4Dho/1/ZxMfVyjCKN8yyKDfsTkWzsQinyzXDeMFZGbJ4Z8SCX4SVBRNyNPvhngDb2tqPiDzElEZ8Ayt9HcQCTKA5gooq7yjURY+QYq7A6+/1gZbz4PWEAt/0AGmRGgfGORECn/YnQB1POzx/MtkHyTVPlGARS2A6U0MHBYw2srMtkJ1MpOWc+32pQoR71Ej2oWAaoDiAL5Rv3JN8tEZNJOLdf5iQph2BJcDytq2F53EcGcKjutHMxHtV/iH7U/AgA27zgCyB6F0WIS332AQBWMKyTq4hoGWzKbEJFvNIMlZKq2IU47bRoRNj2JETWkNH6SUzIsRN0K2hSQb5FJxpqDiNBi4RxHcyORKPtmRBH1lG9O2WkkTwulQsneHetK+PMUwe/fbwGi/lt21Ek7dUOdayaYUYH7hmGIg8C0U1knNA7JS2mFhGoMMtkJ+KWdupVveXjVfapRiggBZJfGBXq+WXzKq5TwkG8RaXNLcN0jlgEoESLfQuwTlbRTAEjAwN+qd1RfH5rbAEzvxd/eOYg1Y+JnajQXKG2wp0bUf0xiEMDu2obCZGcbNYfR0JKoZVn4yU9+gssvvxwnnHACTjzxRFxxxRW47rrr4glTjLoQzQFkGpA1C0NwG5GYfOsZ4rlmtCGTQmIuwyFl6nu+VcpOI3leqHCimSElPL2XYHQ6omUTAYELLOL+UAZ4i7J8iREAtFzsfHMahpP0V/nZMqMduFD5l1O+uci3LDKe91SzEI2ggkobRcqVKoyS/3syYT9Svo3OFvGR36/HtXcQbJoEIqNOrCAMByBTHxAECmAhppEh3nnc6NZNWDPmTwJH5PCEYMuGE4S/33bQhd4NM7s62aQ5jdDKN0oprrjiCtx66604+eSTceKJJ4JSijVr1uAd73gHbrzxRtx0000dbGqM6IOfBcyFibZBVf7QzIgMbuYg9rfABWkRe75JDYUAJvgSOJ2qnoFXpAMXAKHyra/iW5IrRdQewDMpDZ6kxfdTr+ANXKj1hxTnKc/5fkpK5Zvj+QYAqAQuNHhdydR/VMtOCat8q02J8kzZqWZEiXyjSCCgbzNkJHgFcKvdoqLWaxLv/cXTeHzzBACCVbuBB48yoUSoNm1ulZ0CwyTHbS/Q4BMiUx/XKNima+Dvtx10kXfD7G5unxjhEPrW/ulPf4oHHngAd999Ny644ALPe/fccw+uvPJKXHfddXj729/e9kbGmBsQcSIR6YsDIfJ8o1FZWZyDiLk3WRCnncoMm6SmUIl3QplHCsOoEQA1z7dutq5dECvf+mBPPq0oTKZZUAuw3CvywccwFxa4ogk27dTGZ7Sf4R3aHcJPAAB0SYkRD4HY+H1jSnSr1cpOvQRVyaV8KxEv+TZU2BUN8g0UoFagr2BkFof3E+Vb2bAqxJuNnbMEq7ZO4ayjhnrYqsYQLnAhGs8iipri3w21zn0T5Uct23SRNcIYHfFuKM10rD1zHaHLTn/5y1/i4x//OEe8AcCrX/1qfPSjH8UNN9zQ1sbFmFsQKZLmwkQ7Jt/kAhEoLOd6Wbycx9es8k3GY5l7cMpO2RK4HON15KSdynmN1QGloIIE9gFSrLwdwQmdwSij6inf5sAzNpKgXvINANIoBRNvAKiUCXIUyG4CCnthE2+NX1MykcC+ZacuZUtWHeY/OLOzg61qE6gJGHVUYlEh3+j+Qb6JxjwTuYicowrmkvINlHJ+kACg1rETivTYlWk6W7ZuUcKNDVHOdrhRcxehybdnn30Wl156qe/7l112GZ555pm2NCrG3IRIkBSZzjgAVHRkMfnWefhMOueqwjIIUt5HlFYGzI2pBaQ8ljkIlTjkm/f8FJhyq0RlEBrN00KRL/PX3wBsgoNGMb2dMx4PPjEykR77L+wyzUGEINZkJN8svULYVFSXTRAhMpHAzi2RCghc2Js6kP/grqc72aw2gQJG8DX04EYJrzERPN6Wc7vslEVJjxbZ+OTW+ub7kVK+Eb5sW7OC53VRftayxCFbdqpD5UrxUeZLc2OEQ2jybWJiAkuWLPF9f8mSJZicjJMvYvhDTIpEt7NyoAgmP9SIAxc6ivIksOs2YPpF7i0iuNDmOqEj5UPf0oGJp4DptY19TMJDmYtQFDH5VkLS89pJQ41mX02RLfLt7icV8i0SZWQMWOKjzjFE8rTNCbiVbxQUAQmU7k/J6MdFDVSPh1pNeb7J9Ax2+rIkYQMXasq34cF+3mA8H4E5DrWAmfWBu3zh3iym8xHwu9xPyk5Fz9aSEZ3jNS2KGx7bFmK/aDxvKeVVsQCg7Edlp6zyzYSKPFjyTUJ/0oggNPlmmiY0zd8iTlVVGPWkzjH2awjLTqPcW1UgSguMybcOY+p5e5A5u5F7S5iqOweusyDINLGpojwOexW+MWn6XD9XskD1Id+KLvUHUDMlj+R58SkfGawq36IzwanCmYRSs/JfNCY0+x/c94tNViVIiDGyjMo3N/FBzaZmmTItEDktYfs+x0LkzEUz0BQF660V3g8WpzrfuFZBrbrKN2IZ+OWq+mRJz7GfBC6Ihm9lIzr9+urtU6H2M0x5+oAgUPiVnc7diibWVoRdKDKgokCZslMZw4EigobSTt/xjncglUoJ3y+V5u5FGaNzkMmEt1mIybf4fugs/FMV5hLJq1vh0iOkI98sE8jvsQfMigaFhFe0RfVcRQ0OSc0OsorUq3xzyk6jeVpo1bPODafsNLKBCwAw/YJdCrjsot62J0Z9WCYoFOGEjoOMYwdqwqN8g1UxWA+fbiRX2andFpZ8Myt6hKuP3IsbdizGFAa8HyzIr3yzLBOKwOfSjSR0TOYjsEDsJt/msPJN5KcaJVV2WKIwKmM7SsWBC4opoSq5TWDPjMYEceki5VtMvjWN0OTb3/7t39bdJ046jREEURpOVDpjEfwGcACAOsacMVoE8RftziVvwQe2hZvcSKfmn10P5DYDhR1A/yFQCQl9r0f1XEUNio/nW3EulZ1aJjKE74v7q4ELst04YUABWIAzEcjvAPbeC4ycBKQW9LRlMVyY3QgUx4DUPGDfStDCsUgJSpk41FEt9QSU1th3agcuNFx2KlH/4TSFtQyxKuQbge2JOUW95JuR3Rd+0tRljM4U8d5fPI3V2yfx/pFF+OeAfZMwYEZBheQJLdm/lG9RCjhSReUmAkTG843WFP8eGBEo1W4S7OXGLsoKy05N3f5P9VZLxKiP0M+R//3f/+1kO2LsBxARBFGeaFcHcERwDDKuXs8lBJBvIvZNOnIqJD58d7j9ZJrYAACKe+x/LZv4UBVAD3kOZDuUuQr/slOx8i2SXbVPmUhV+RbFjoFSW1nqILsZ0AaAsZXAAa/vXbti1GDkgNw2oDQGWCVbtaPPhFK+ESk931wJp0120FIp3yrHwlYtWC4nnmyZYhr9nvenJychK739nXs34PEtEwCAy2f/FGgqlCQ6Xto726WWtQD34sh+pnyLkio7JPcWmfkeBYQLJcSam6IK0fXHer4ZULgwLgC2TUJMvjWM0J5vMWK0ClG3G0k1RQVOy0VlpzH51mEQtfbz2ErPII0I2DfpyKmQmA35rDekIxG850ALOzpDdAZoUYef8q3AkG9JRNjzTRcTGQOVwIVo+qVVlG8OGvRUjNEFuO8Vy6gELtSI7CBISb6B2itYs3kgl7UDFxr8Bpn69ZryjSHfqN0nEkIxU7I45VuyJG/Z6XWPbK3+fLAyGrhvCjoeXL+v001qA5j7aI5C9GgNTVZL8HdRwirfoqC2hE1GCcm3KHt5l6eAwh7hW6Lrj1O+UZUbGwKQ06M0AojJtxhdg3h1pwcNaROc4xGmncZlp52FW/lWGgdKE9WXonGATAP/RqCG5Kx8uTezDGQ39aAMmsI9cFYbeNJEkuSJIJTKOdGId5BVoj5lp1G8h3w8SSKtfAOtkIaVziGSBOJch1spVvmZ8umaIshJvlnAC88Bz20AnnoO2PgixMup/pBp3u10ZX6ebwT2Ih5Lvg1OrulG8zoOkQ+mnHCXnc5d5ZtozBPKEiG3Ddh1G5Dd0v5GNQBV4LMsQpTG4WLlW4TLTkcfBMZXAWV+AUF0VjSmb9ShosCWnQKx71uTiMm3GF2D6AETpc6YhV9iFoDY863j8O+6RIELUfLPcCMs+ear7Nv3CLD7LvvfrqPWJi0m36SDM2Bm1R+c5xuxoMCK5kKJD5HhKN/MKBJXlmUTOs4CxByelEYW7oCCChFHgeiWnU7tBkb31l6/tBpagyVYMpH3zniAMNNOWiG0CYCEpmAWGf7DhakOt67zCOU9KAP2Y8+3UAtD+x61/XXHH29/ozqAaHm+Nad8y5Ukv05L49wm0fxIE3i+sWNDALHyrUnE5FuM7kEgj44qKQL4ly4AAJnDkdRSgPN8q11HokW4qJadKiF7aN+JzfjjQH67PUjrKohHkROWRASirYaNEpxSEXaFUzTASsCIJinqY14/AJvgsOqkAkqJiVXA9Isubkfywf7+CNarilr2hC4E6aHISL7N8uVKC2ljJZgyPYP9Fk6ryjcCaIqKZ63D+Q9Pbetw61oDES0GM0iFUGDKgf1D+SYOowtxvNNrbCXT7LoOtCo8wt7bURlDUFDhQkkY5dspn7sDNz29sxPNag8EC46is8KWnRpQABCUSdq7Y0y+NYWYfIvRNVCLf5hEW/nmX3ZKYuVbZ9Eo+RbR60wY5iGA74qiPlPZocu+UISgWeVb1M7VbFHH1vFc5Nqt+CjfClRMvkVyoUQPClygMKNWdmoZgD5lG/pTZyIQsWPYH+Ckg+a32aVhlb4wFUb5ZkpIvgkUHyna2AKjTP2jn2WI6ZoSJTQFYxjhP1ySO6iANUoXIS47lQtCzzczxKKKowbs8WJ/WFWrYUbjWUWpT9mpWZ98002KL9+2thPNag8E5JuIFGWVbwZsn21d8ZaezsxOt7Fx+w9i8i1GR0Apxfq9sxidrQ0kd07ygxaZVkMbhdP0uOxUArgDFwTsW9Tm2A5Cl536Dn4akJy1FcQzomzE8y1KJM9zO6Zxwdfuwyv/4z687UePoqhHZ4LgDLjYQZZI+abBjKYi0Uf5phCKPpQkDCqpA2pU7qv9Y1IaXVA75dQsAuVpwDJDBy4oMqrmBb4+qQYJHLnKTu1/2YWHatkp0aBVHlo7KZNvWpY74ESkrlxjHeh5Hcmy0zms8BV6vgnECjx6Nb7zImw5qUwEfBBsiwD+HlFCkG8AsGemCF1aolGgfBOclhOVzZ7XZoV8KzPk24d/+SjufHEvYjSGmHyL0XZQSnHNdU/iom88gFd+9T7c9eJe/OaJ7fj8n3m5Pi1NRd4wmvUNAQASp512FuzTwpN2yiOqJG/YkFD55Pxe5VsjD5qoDNAA4Cu3r8W+rD0JfXzzBG59bnePWxQeTvJYPc83IMJlpz7KNwDoRyF6gQvcBJRG/vk5N0FRexKZADV8fYRYKDIq3wTkW8bKNfQVMj2DnZb4Kt8GDkaiQr7lKFNmJbnyTVQuN4s+z+sUdCQbkaP3AtwYb+6Sb0LlW5h+PWTQQacRWvkWobGdaKGkkcAFaRdi61xXKkx8Rvsp3qn92bO9v2LVwZadKkYBH7vx2fa2cT+A5L1vjCji8c0TuGuNzYQXdBMfvfFZfOzG5wAAR5Ht+Fri+/io9gv0owBzag0w9Vwvm9s0gpRvcdlpp8E+xGvnQBS4EEniAC0q33o5KXefA0qFniZ+2DKex5NbJyJBwj20YZ/n9Xfu3dCjljQO5+8bxvMtCWNOKd8AYJAUYEbO881J0bRqpY2x8k1uUBOgZujABTmVb/x9lIyw8s0ZD6jE2/dZVc83UiPf2NAFyZVvItIgS73HkCZRGJ9WrpfcViC72V54iHLaZABE49NwC0NykG9hifUojOkAW0CiEdG8rhHyTaJFMU9wSbDy7bXKY3iHdge3z5GK7WNXJl7lWwbl6gJ0jPDQet2AGHMPN63e5Xnt3JgJGLgh+UUsInaN+OFkF0z6AdsTZd7JXW9nq3AIBSH51mASWIxGEaB8E4xHZBr4hwaloZVvwkHN6IP2H6MnxKM7cIE21ISfrtyCn67cgnMOX4Ab3nWWsIw4RutwyiI45ZvA800jZqTKgasIUCAPIh9NUp7SSvdXucec/xS11y2L4YBWCFKgcn5M31ImFqqMyreSoOyUBo9xziRrcaSyE3eap2MMI3Ip3ypNYcMJHPINRMMB82y1WJZTvslNvonUlTMC5Zv0/lsz64CJJwGzAChJILOkstCQ6HXL2g6h8i0M+UYUKRZfwpJqUVG+UfCBAwCgRFb55v67iwIXHE/SMr6d/E7gN7Flpxki4WJRBBAr32K0HX7+TqeQDVXiDQAuUp+CIihniAr8BnBArHzrOALKTkWQaeAfHjR0VQE3+KFWLWyhVyhP2ivVDSrfHKzcOI4H1++rv6NMiNBllk7YZA3r+VYSTG4iW3YaRL6RQvQCF6p+b067K0o46lLCxZAAtNYXVNJOgXCeb6qUyjd+nJaGfzuvUFbiN6nP4YuJH+OO1IcxhCxk4nr80k4tx/Nt5ES86fQDAERD+eZ+/gvLTilLvpVhUckXJWfWAFYZKI4CIJWxhEyERvsg6rZpmMqFfBbYtgbITrW9TY2gkbGB1NecA8qPiwBAsQyEHeSVZerw3BAGLtj/vlF9sO7HR4tezZZTjhqjMcTkW4y2Q/VhDJaRCW6bIuFAJiycLpgt2wJi5Vvn4V92KhoIREXuziJ02Sl7zFVvqB6pxsqTQGkfUBxDo8o3N255Zlf9nWI0hVMPGgHAl17p0KBTr4oqCSOaoSWG/8BwEPnokW81Rkfwn/v9GL2FmyC1S4MpBVIkRNkpNYAwSYfdhIB8O4Juh9/19onE9dWf55Es/km7RSryvl7aKVETOP3geQCAAluGL+GCsdvcnQ1T0KmKArxqlXRFHafL3P+5y+qJWlP4zkGI7o1vPV7nWEfXAH/+MfDkncA9vwB2P9Oh1tVHIzxTFNRvtvJNfFBhw0ocT10p4L5vhGWndluvVu+s+1V7DS+RP4/YHpiRIFUlQky+xWg7FJ9aOZGMlwQYYssOSikUWFAI3+kosfKtu3A9UMQS/i62pV2gNDT5xj34em1ObORcJ6L5h3JeKun+3ILjjcgOMk0o1Vh5B3baaQQHVwH98BDJR3DAWCHanLJGCu+kdI5OTiMHdyIttar9cZiyUwCBXoU9QZlvz5voXfhe4psQ9e+LyZTn9RXqSqkWwPzSTqvKt8rrc49YgAL1Elci/7tew01osOpKHRqKjJrZSarVZSIIhHDKS5Sqd+JchN+zNfCeufcLtUVW0wCevq4DLQuHRu5tmfoBP1BKhco3AEiH9LqUK+20judb5V+R3y+LCTrkef2P2h8xHzPyKv0kRUy+xWg7/JRvA4QftKjlKYhq0KMACv8yEiVWvnUY/mWnomd7NMtOw4dZcauJ1ATMUmXA2otyNGbyGStypIOz2iki33TGDjYBI5oVjQEGyUPIRU/5ViV1KuQbQdVTzH4/YsczZ+Huc21ylNJwgQsAAF2yUh6f8u3L1FU4ldQPmRlCXqpJt2ODwCrfLOqdEmmKwqnGpFS+GbX7nr3GytBQZAhEp1RMbt831xiiSr7J3N7m4VyFb1QewNOpf8AjqffifOUZlIwAsnHNLd7Xj/9Px9pXD40szBkReOZS8MS8g0iSb57z4x+4MEpH6n7VOEO+AcA/aTdHQtEoE2LyLUbbofoo3wbBD1pIfieQ39HpJnUE1McXAACUBlJxYjSBQM83/iEQSdUOqK9/Igte+WYCo48BD98E3PRtYOUfgMJUuxtYB06bzKaJm6hFLUTxKmMVySZUlBnyLUki6vlm+ZMdh5Ld0SPfql5iDrlDwHvAxZADLuUvtUIHLgAILJfuCQK8E98QwifI9leUp/9wbntfz7fKgyehEkHZqXzKN3f5KBu4UEYCUxjwbBsmOftzUivf3Crfua18o5QigyL+PfG/mEeyWEYm8MXEj6FHRPk/95RvYjshIHxSsFxklFv5JrimKm/7zWcB4LvGFQCACQxy712j3So5kS8fYvItRtvhV3a6lEzy+xo6UNjb6SZ1BkHkW6x86zD8Pd/EZacyPQjDInzZKe/5pgPb1wKj2+zXo9uA1b9ob/OCUE1ktH9uNikzakmnUUoEdVrKKd+oWPkWSfVogHfW+epzKBkRGzBS14S0+l9cdiofXKodywJgBirlOUSIfKMhl0hkUoI4PZmv51uVfFMiUXbqJtHYa6wMDdO037NtBLbXsvQqJFpR9xLFLt2eo+SbRYGjyQ70uZIjDyD7oE9s7WGrwsNZmBtCDv9Pux5f1n6II4lYVCEXKSUGBRXaJAENKN+kGlsEk2/O+esn/s+dnxqXAODLTh1E4bzKhJh8i9F2+JWdvl3jzRxP3fp7YM/mTjepI6Dw9wVoJJI6RhPglG8UM0UdP7h/I361aju3exRW20Tw4bE5cMdn6cCzD3i3/flj7WlUKLjaY5lNK8ISYf8AMZqG0PON8p5vUhkIh0VAP3wA2Ye9E1EM/HGXnVaUb23wV4zRRrhL/V1lwSkSclwgG8ETSL6Fg0wqq1rggrfvow75ViEUNVVQdlrOdb6BDcLwBC4w5BvVMAUv+TbkKN8Mec4JD2dxAbDTTudw2SkFiOBOMnJ8SJ2McMafX098D9dot+KvtPvws+SXkREkYUZhITxQ+RaWfJPpOGkw+ea82xeQXDoKO4BmnPLKNyC6c6xeISbfYrQdovnyCGaF+yasMvDIzcBLtwIzL1XSEaOBwLLTWPnWYVQ6+sIuYGYdqJ7H277/IL5021rh3pFU7VDaAvnW4yATasFdCtfsn18LK/2L0TCccyIi39iy0wQMqZQroRFQdgoA5dxMlxrSLlB7EmoZ8JZlxco3ucB4vsEmfPoQsl+eg8o3mVRWfoELJnMsCSUiZaeuvpktbS4jIVC+5QBQ+dNOnT6OKADmbtmpRamwnNEsTDf2RT0a5zrjz4vUp6rblpMJ/IW6kts3CgopSgGV+CnfwqadynRv1SHfKtdNmOfTBGLlWzsQk28x2g5R2ekIqaMwuPtzwMw6YN+jHWpV+0EBJHw66Jh86wao7ReoT+HZl1bjhT3+g2KZx5j+aKDsVKR86yncIQtW03ocLazpXYyGUSs79fZhBlSu7DQJI3KDq1zJwNM7g/thsyBeFJIXFMhuBHLb7UAVEDiG/tX3Y8gBq1hJ23UCFyj6EZK4kY3gMfzvo9Dkm0zKt8p9wnu+VZ43lUPSVCIoO5UvcKEUELigQ+U83xLERD+KUp0TMSrHRRSgPAPMUU9Li1Kx6ihIZZkc4LcVGyTr2gTLne7swpFkJ7ctKgoptm9wENbzTa7FSm8lit+7fqW2bswwRL4DU/q+RC7EM5sYbYeo7LS/HqM+uqZDrekc7DhqsbJCjcm3DoN6VB47poKVApE0i0crZac9vv6clFXALjuN5p+/YUTxMEUTUAOislOZBpP18f5fPY1ndwffB5oeMfKNUsAsAKCAPotqknCcdioZKJDdApT22SrFiu9lP4mq8q118g26POWazvOILfWzqmWnNhKqIlC+yUe+lV3kW4Kwnm8JTFOeqBlGTjKCgIXLNxbE9nyro2SOKigFMqJyxlLA8yklUCDlx9vXqAZgWuIqIBGhGIVFPErb4PkmExnlKTvl7yHnbb9S2zGXz9ssMsJ9pFbRSoiYfIvRdoiUb6FXfAEhMy8jKOKy057BMRrX7EGlSoIfdJEsO0X4slO3v4RpUfzkcT7cpKvwrIRaVaVBo5DLtHZugVbOkUa8f2OR8i1BDLkGk3VQ1E3ctWYUiToruUk9ap5vlQmpbgDrngeeWwkUCzH5Jhssl/KXGnDSToM8dTyQTflmNka+lRnPSAA4sCC2hOgFnMelf9qp/W9C5PkmIfl254u10DKu7JQmkEUaJvWepxGSlZsIKc8C+Z0A1WsJGGaP7TQ6BEqBjIiYDyLfFI3fluuNbY9Jxf7XA4Tvx6KQMG7P7cTtTIUtO5XqOClQ3AtMvwCYRa482Sk79Su1/Zz+9urPJXYxogLT6HW1TbQQk28x2g5VwBj0BaSocIiIr0OQKafa87K/uQvLovjZ0wX8610abt8+DAAgdcoRomDy2grcJNWPHtyEz93TYy8raqLmQ+VewW4Mcq/M84gax8um/QH2BJT1fLPLTqNzLkZn7ImM3+KIA82QbyIdCmvWA1s3AZufB55+0qV0FV+AUSn1mTOgOjA1Cby0Bdi0CygXAEoD0+Q8iJDyTaQQ4QgrAEtLW9rZopbgLAYpzKKdySnfRGWnkhGjAL5738bqz6KyUwoF00zowjCRXPk2s9ZW+ZbGUZ2q9trLtgPIlw186dYXkBFUBynlgMUh0Rxj7KU2tiw8TNMSLnT1R1b55l+CmQpbdipVmEnFosfIAbmt3BzbaSk7n91iLcG/lv8Jt1hne7Z/xkXGObBKER1L9Qgx+Raj7Wiq7NSNqJBvCCg7pTH51in85snt+PQ9Bfx+nYp/vO9APLVvwHfFxkEkJ58NBC64iZEv+4ROdBXUsuUF2TxQyDZdjhkltVXU4KfcNaByaacJGBHwB6phdNYe9Gt1+gXNLEZLLUZNwNSBaRe5nssCezdV3hcfi9ST7LmIwhTw9BPA+AywZwJ48WkAPr5OIshEvlmWfc35gFVaAWK/pLQpj8rUL3CBVfFlklokAhfcYMm3EhIAwIUuSF126k5vtoxavzYHF7U/cdPzWLlpUlh2SsoBi6giNerMrja2LDwMiyIhmAuJFhuiMBanoP6eb6HTTiW6t2jFmoJaFeWbwb0N8ITjx4x34ffWKwCmX7zJPJf/FRKmQMuMmHyL0XYIy04F8mMO5Sl7ZSsi5BsofMuaYvKtc/jI757zvP7kE4dArTOBjqbnG4WAxxaizBAjooj3rsIygOfWAM9uAB78M87D0019TVnWycEcATv5BGz1B1t2qsGMFBE6mbf7X9GEwI2EVYyWjxA1AFF5R9bx+qFC5fnGMXmIj7mO6YKOn93ygDflZ892/OElEn4RUpeIfDOCx24pwl+PonFR0pRHGVEzGOeTnoFalWNfUuVVfGYZMOXtM5KETTu1+/JpJnRhhGQ9XnFSwfGyBLVPhjO+E/hVRR03PmWHEvQJyk5JcRKYesFWLLEQEeKF3tiN6KZP2anAbigK5BvgH7gwgizeqd6Ga7XfYgkmfD8v12JlJX07twWY3cCNeRwlMHsO33P8brzhCL7fFimbzbI8/XsUEJNvMdoOUUKjSH7MYWYtMP50ZMi3IM83LfZ86xpemBwA6pSXzXUOh/VG+1biOz1qSQV7NwDTFb8Sy8QH6C+a+hppV+Z9sG0ijyv/+2F86g/Po6hL3o9Rcf9lUoHnW8TKTp0Bfr2y04RVjMzzBoA9aDYEE1DHJ5Va0ATk268e397hhsVw8Ok/PI+1m3kFyjxrSkhUCVGH8OoqAvzeALEHkqhkK23Jo4xwPI7Ysvta4IJ9D/UnVb7sFJDS980Bq3wr+yjfRpBFvixr30fthNMq6Va5xqK0UNIg0gJiXs3tBLKbgPHH+Q+IyLegMtUOQjctJAl/bkQqsaiUnfqNHT6Y+C0+nfg5rtVuxC+SXxAqfwHZxq604j1q2PcSEzRVU7552/yKo1fgL49Lc99WQgIW4yEZmMwbg0NMvsVoO4Seb2FWfG/6DnDHT4EdT7S/UR0Apf5lTVqsfOsygh/oUSIOagg/SHE/6JPQcZH6VCcaFB4bV3leHkz2NPU1cg1gwmH19ilc98hWfPOu9b1uSl34Kd/KTNppMmKBC87kuh75lrT4EgypQU2x6sYhSKiFwTRvxJ0rRegYI46bVu9CjvITlgPIPt/PbLGWeDfIpHyrE4DFk298iAsApC15CCu/stNa4IL9Wlh2CgAzmzrZvJbAqn11avcHU5zyLYesrP0CtQCi1U5UtbJBVrKwdYjmSKRcIUlEwUCiEtwelUQbpiW04EkL/NGioHyjAFRBH8bicGU3LlUExCgks0xxAuoAABbnnVjzfGPuL1WDKmSJCPKM+o3GyreGEJNvMdoPQa2cKPVGiEIWuOeLbW5QZ2B7vvmUncL0lp3E6ChonbJTacsrgtCA55ubpApMFu5G+S2lgCpI4moCcpnWNobv37+x/k49hN1/ick3Q1B2akSICHXG9/XSTlNRU75RU2x+XyVrKFIanzR5worhzrYrhgei624JEZQoZTK4ffFVeIoe6d0uk/KtjtqIJd/8xkRyKt8Y8o16p0T9orJTAJh4tmNtaxVc2mmlL5+gg57tCzCNgrTKNwtQVFRpAecazO0AiqM9a1UnkREQVYpfP0Cp+L7sEflWNqmwzxOFSMhVjilGkPKNxTGKWFUu13iJ1sY5lgVkNwO5bdV3nUA6rtSWqMJKNkBQeiqxGlhGxORbjPZDMME/nmwJ//kdT0SCuKrbQc/RWHQZUe9yiYLUXYSQ3JvH8y0wUS/AOLt9cK+y1eAXThKE2POtc7ATvXyUb9RLvqVRjtQ9ZFWVb95rbpJ61R8pGjHPN1hi5Zsz6fJZhIim8je6YH23AGAxmeJ3fNVb8fyCC1GkCe/2KCnfmGP1NSqn8hyT05WpjLqcTTvNJNVqYIEHPSrvCwO/stMx6iXgF5JpeRclKYU9PaUAiK3UMXLA7EZg32M9blxnICw79Qte8RvH9Yi0N0xL6K86n/D3SRSUbwgIXOD3FEOqqg1quRYZqZ14OvkMM0elSLCVXArbQ9ZQoF5FcKx8awwx+RajPaAUKE8DlILvWynOV58TfcofMq38+oCijqG3EZNv3UI9YkCqB2FIGKaFR3aGo98Mj/ItYJLTjRQ9agknbCJvoHqQ+bzRSIZ4eCHyZjLBqz3SKEt9Llg4Z4YdTE4xvkcZWgSNFPkGsedbuaZ8E0GqEpj9ACwBAviQb2oKKqEosaWNMvnn1FW+eRU7fmOilCXPmM65G4hP2SmqgQsaKBTkGd+3b67UMVuU01rEL3BhHwTkm7R9ugW7xNQpOzUBq4hq2WmUEqpDQlR2mihPA1vuBHJ7vGMqv9TXHinfCrrpK0RYBG8IhBmBcZNFxWMjEeZhFgeQMW67Lh3J6EoQdu6f/C5gdgMo5f0vAQBEQc7H8jMPr7UCiZVvDSEm32K0B7MbgNEHgJm13KR0OcZ9PhQAyePcAXvyHax8i0MXuoV6c8v/vndDdxrSRty7Lvx9o4cl37pyTYqVb2Ej2t2QmfCJxgquP4KUb6yfR4aUI1Eu4sDP820aXvKtnxRRFqWHygrLCi47pZaQFJZW4TJHITLhXkIESYSEQFMhIN+mO9SyJtBg2amfYiQVNum1C3DuEbatbOCC41/M+r49tq2EXzy2DbLg1ccsrv7MK98qnm+M6ncQBXn7BUptrkAvA9t2AS8+AhRytXGFH/kUYYjGR5niBHDXz4CbPgOMuzxk/cZxPZo3zRYNX9L9r7W7Pa/NCKiw7blduHZepd2Lh1Lvxxe1H3m2S1V2Si2mIq0yLtr3CDC9BrQ4Kp7LKipOXMxvBviy05h8awwx+RajPZhZa/87u4FTvolKMOoiAjdy3bLTbqiMYgCoT4TsnSlhw6i8pSIifPzm8Ib9bmWLKLK+iq4o38TkW3PKN3kJnyis4NaDyFTYhIIiM9lMoxSp0kWn7JSdEEwzE9B+FFGUdQIqBAVEZKHu3PNx2akMECrfMMXvSBSoBCiypY0yKf8bDFzw81mUqey0FrjApp3aZJvjteqQdOxE8/3ajfjKbS92tpENIJOs+Txy5FulpDmLjGd7PynKrXyjFrBmI7BtN7D+aeCJ+2tEcJR8OkPCL7wNgO2F/fgPaq9F1gNAz+Ycs0WdL1ms4FrtRs/rKCziNaJ8c3CVdi+OIDuqr6Uau1ILHlV8dUHF3kb1rPh4FQWLR4aEX8mWncbkW2OIybcYbQfb5dQzvRYiAso3oB75Js9K71xHmDHkTU/v7HxD2oixbHiyqhy67LQb1yQVmvCJkq/qIV+WtyRQXrPqcKA+viYmFBSYMqtMxMpOncuPffaIlG8lXd5rjIclJt9yM/a/lAoLT6WaCOwHEHu+CZRvigYtsxBFZiKD9fd2qGVNoJ7yjfN8E/eLIvP1XsG5S9jABcfzLZWwyazjltsTT/b8vFxZgzer93e6maHhVruyqku9onzLMwm8fSjKrXwr5YBp14LpzCQw5YQtzI3+zH3e6s6TVv2k9rNv2WmXCRBqAVMvYCZfCLbgcSEKFQONKN/cuEJdWf1ZrvESheeeoV4S26JEfLxE9U2DZ6sjiC6RVUIEEJNvMdoOtuxFtApcFzJ5nviA0jqrVbHyrWsIM4bMSUzkiCCO+BZDd/0B+nrt+QZxElczZafZorznbDIf/dIXseebwpVZZVCWq4yiDiy/slPG860fRRiyTkBFsCy7FItFdrKqOBUJMqWdZM9RpARjnsOV3fyO80+HqqU5pantcSUJud9g2amfAiYTCeVbhXzT7H/7kjZxxarGAOA1ylMdbGFjcK91sSSIU3ZaUrzXWD8pwRD5R0oBC5jay2/OV8qx54jnm5uHaiiQSpay09w2ILsJs7lZXyHC/eZJntf/dMNTuPrHj0k9nrDjPhpv379oN+Gbie/gADIqjcKPUoqSzoxVLR1uexhKiK/yDUYeH7zoKO4ttk9UYvKtIcTkW4y2gx38i/xP6iICyjcKcbx2FbHyraMYQhYf027AV7UfoL/IG56yUEnY7FA5oDTQXo/nW1DaaTeuSUqFvlTNlJ3myibyZQNFXZKJqAsyq/LCQOT5RkFAoXBlVhlSlGwlNxjOM4id0EzBW3bahyIMWUiOULCAHVvFb83shX/gQnTO3VxAmDEPBQEUFQmVYJSO8DvM7ml/w5pBw55v4vupj5SkGRPV0k7FgQvuZ+8VJy/HBB3kvuNi9cnONbBBWG7lG+HTTgfTGn59Ge9RJ21CIbWAFwSppoVc7f05ALcKLLCKpvqByrkt+ViodHveZNq/r2D4iyw0wSryg+v3YeXGJrzAuwRKBcmfIXGluhL/mfieFM/c53ZM45wv34NjvvQ8PvfMMbU3qFnxgauQb35KP2IrgN965oE4cYU3sCVLveSbps+2t/FzHDH5FqPtsOoo30pUw0rzuOAviQL5Fnu+9RSfT/wv3q39CW/R7sdrtv4fl7rGImLcW0NwJytJUXYqUOc0U3YKAMd96s8498v3YOWGfa02rK2IQvlEPbADLovYQwK2zCqqyjd2AM0q31LEQLkUoX56aqewpBsAkN1nK98EBJwsq/D7C8KQbw7Rk1AJ/mydye+QFSh/eoE6RMcgKeAVyrM4jmwBUGdMNL6xjQ1rHs49Qoj3vnDKTt0eiQlVwSR48k0muB9F7LVXhgaFEAz293GfI7JWmFAfb8sdjg9udJ5FQbAaKTsFgMKE/e89/y5+3yjy6oeOwu7DDMv/vh9QxeO+f/+jPJ6JLEiL5O7LlJeQLAtsBrqMr9/5EnZPF0EB/GTDoXh2aoH9hqN8c91HYuWbCowcj8VDadz0z+dWvTABIAtvf6KWY/KtEcTkW4y2g52TJpiVuGkM4Cr9E3jC4qWsVUTAvJGijlQ8Jt86BgILV6iPVF+nrCLOV54N/kzE2LdGxlCestNA5VuXyk7bpHxzMJ4r4/N/WtNKo9oOI+Lkm6i0glaGBJzyLXKBC/a/9dJOAcDyUxHIiJ1P+7+Xn4TfpFSGVfj9AY7lRhirDauiKkhqBCZUzFCGHClLcl3WUb4BwM+TX8atqY/javWOQPLNGAsfItRJUB/lG4WCeX0JHLWkRrYlNQXjVGw6Lg9qzyK25LlMNXvSnOL7PmJISr7BskMGWEyP2+qvORB2BDShfMtVKjzW3S5+n1pdSrSvoLJYp1v+cyG/cZ/MzyTShkCPjD7Rhpa0hvte8lYEfWt9pQSYmhWbikrggkXF19/Cs4CBwwDYyc8LB2rjwplY+dYSYvItRtvBrryLVuIAPi3Fg0go3+qYckpSYjEXMQ/8wGyJyNDahagplcTW6WLoMgUu+Kxa11Mm1sOLu2ek8q6yInY9sRApdylxyDdG+UYiFrjg4/kmmkTT/FQ3mtQe6AH3dn7aDlwQeb5F6NxFGU6XECbh3SG6E4r9oRlGSeBbWtZthCDfHHxSux6vWeZfTmZM7fB9r5twSFJ28SGTJPj3vzgBCVepXFIlmBSUncoE96OI93xL2Mej9VfVlg4UWcfZ1PIvVZjePWfKTt2KZFakIERxuv4+3TynZgGYfgGGSblyZwd+4z6ZF8PVZnzKGWgSeqDlDXvubffpNeWbRSlEyfdIjXhejs7W5g+s55tmSPK8ighi8i1G20EZhQQ3GKB2B1Bk1BUeREb5Fped9gKi1TRSh6zqT2mdak77MPUcsOt2wCg0pnxzDeKkCFwQkAStKN8cyJQwGnXlGyBQvjnkG5N2mkY5UqWLzuSaffbM0D5+0acw1aVWtQFBZWKlLPyUb1E6d1GGQ1CHUb4591qyQr6xHjpRUr45SBIDHz5ug+/7hiREdy1wwXu/fP8y4PKTl3u2JTUFE9KXnfqnnZahIZNUAS0NgyQ87ymGpONss+yvbitMY66UnZaM2ngmVNlpKYS6qJvk2+w6wMjBMC3fuVCK+pBvnWxXq2gDuauZ8t1bNb7ThCdwgfqcv4S333P7vrHPq4S0Klo5EZNvMVoH01Gx5Bsng4c9AGDVFR5EgXyjdVarYuVbx5AS+IfVm/AYpjzEjS+yW2w/hvz2hsi3sidwIeC660ZJgp6vGQO70KznmxsylT5GTUnJQ6DcJQFlp0YE7p8K/MpODWj8RLrQe2+W0NAD7u1StuL5JvhYrHzrCmrkWwjPN4d8q6isckh7d5CVfFPU4P1nfAJBAFj5EMqdLsC5R9i0U9GxJVRFGLggEzyeb8yYVIeGtKYCahoGk3iqGJIq34IIpHJhzpSd5l2LiaHSTh3yLcH791XRzXNa6Rt0qnALXQ6SLVY89AJaG8i3RI/JNyq4R6r9hGV4AxfgU3bK9IenHzyv+jOrfEvEyreGEJNvMVoHc5NzgQvEr+w0QPkWCTWCT4flIFa+dQwiFVW9ssay7OSB+76hRgNFp97Jdc+Vb3kxmZFuwyBMJrWZTG1pFgrxUb4xCyMasTA6U8Bjm8Y9q/WygvqUnepQuYm0UowQ+WYGkG/FLPzSTuOy0+7AUSCHUb6BKEByGImBZQCAHGXIN2nKTpn7XatDvr34nP9XhSmb6wKcMSrr+eYsPriRUBVM0gFuu/1FcvSF1GPczy92p5MqoPbDVLzKN1VW8i2oXXoBc0X59simWol2KM+30ox9/EHihCBrgrbDCVwgvso9v4UIRZFX+0Zo62WniR6rSkXjU92q9N20UnZa8bYTer4pKlf6ndJq/eMsY5OQjJVvDSEm32K0AcwEjgaXneoO+RakfMvLG0PtoH7aaax86xSuVB/mtg2R4IGkLjtp4DZ5bXBl111W1nPPt4I4lbQdZacyEV6mRCq8ZiDsv3zKTgFANYt46w8fxWXffBC5UuuD007CvkwoUowKxIDK+TcpkVjoqSDo/i3N2so3wS0SK9+6A8eTMhXC880iGrD4fCSTtoKAVRJIq3xT65BvopRKB8WZ1tvTBtTKTpmbRUC+JTWFUwJXIUmFhrfslLd5SWsKkByBqXrJt51jvTeFFyKIQCrn54zn250v1hKNw5Sd5mYm68+Null2Sux7yaTEX/nmU3Yqc+WAMPmzQfRa+Saymig75FtpAphdXyPfYAkWIvh+3k2+cWWnZky+NYKYfIvROpgHIad84wYD9gAg0POtIOmgwAWKOg/MiCjfxrMl3Lt2FDunJF0FZfBy5UX8k3YLt30QwQ87+ZVv7vuksYGJe3IdXArdO+VbWPIthTKWYAKiv4EhEYkwF3y0/JQfooWRDGziZ9O+HH7y0OaOt60VWJTyx4YK+caUnSolOQiBUBCkCFdRysG+Z0T3TfSv1SigEc83Z3KTqExoIqN8I4qQpAoDaTzfKv+ynm9C8k1VsI0uEX9RkAdjF+FeB/L1fEsMo8BcYxlSEpan9RxBf1e9gEbHR7LigqMXVX8Oo3x7ZuP2+qEL3VQzUgrdIgAoPpr4lXCXBBWP+4q6vONxpQ1pp0mrt/MpkUVLmVb6t9IYUJ4CyvZYnVoWT54qvEd2KlEj5LjABWrEgpMGEJNvMVoH6/lWV/lm38D5oLLTiCjfgkv85O+Idk4VcMk3H8Q7f7oKl3zjATy7Y6rXTaqLVymrhduHSPBAuGzIrdbxKt8aa6u7rKznCbw+HlpBapCkag+mTyPrcH/qX/FY+r34ReILSMPbXrmUb/K0pRlQCFZ4FXtIIFoYybi8BL9+57pONq1l+KmSdWiYZVZslSiVSwR5NhazvoqQWPnWHZQb8HyjFT8dx/ONV76FMFfvBljlG1EAtbmpgy6L51s17TSM5xvBLPrwc+NC/otkId+qBBqv9i0jYXu+peajyKZYo4SsjCrmIEVhuTBnlG/JqpKIIkHqEz7rt+6o79u786nWGxYaFAYlOFt50XcPFaZQSZbU5KUfSBvKmlM9VoKxC27DyOJ1xgPAzu2AqduDJMt+TlEIFitF5FuA8g0AkBdXvcTgIe/VHyNCYMk3VvnmHYiWwgQuRIF8A8VAUKljBJRv3713A/Zl7Ul1tmTgC39a0+MW1ccrFLGnzFAd5ZsuO/nmnuQ0kDAHeCfXgZL5bpBvPmUPQZ5vycrA8wPab7CU2OTdOeqLeKf6Z89+Mil4Is69AfBXvpWhwaRev49MhIyTLUqFZTAGVTmvEkWXYwIdCgHKN1rK4g8v5LEvy+9TMubGZFV2OGWn4dJOK+Sb5hO4IKnyzVQS9UMXfJAx5TgmZ4gaxvMtWfG4+6TxTv6LJCHfnOMRVWKUoSGdUIDUQiwZ9D60+lDCVL51O4i2I0i9NYfKTp3FxFBJpwBOVDYLw6w82HQnUO4WyU1hWARvUe8L3Es09jth+bBgz96D0jpe3iGR6rnyzW1FU8CNyU/jfdb/AWteANa8BNvzzd6HWhY0lvwV9PFu5dssu1gEALndbWn7/oCYfIvROhiyjSXf+JU4x/MtqOxUfhNsSoEBBJFv8ivfbnhsm+f1Y5vlL/ed8jE/HiI18u0y5TH8MflxbElfhS3pq3Bd4ktIliQndFtQvulG7Z4LVr51gRD2ue6Dyk4d5dvRynbP9n/RbvR+tUQ+a2x5fdRABaWZpDrgIsgzZEAG8vdnDixf5ZvKKd9USXybQiEgcIFYBj5yq7iPi5Vv3UEjaafEKTt10k5ZJYGknm+bsgOgAlVEGCQMOdR8tKJ44xQuwsAFZxGCYIY9R5L0Hc6zSHTd6VTDkuE0oKaQTnnPW5qU5AzQqad8myOBC85iYqikUwCHkj1VtZL/l+aA6edbbVo4UFv5VqKJwN1E5Jus4ydKBaR8E0jTXpNvtWN4jfIUDldcxNi+CaBcAirXnZBwrKN8KyIJnTIEXZTCq3qM5p6gMWJ4wHi+WfXKTu3LjpXAe3eSY1ATBEqBfuJPZlh6MWa3O4BxDAm3D8FehZ6HGXw78W1oriTH89Xn0L/vOwBe340mNgf3am6DnhPuBy3nY+PZsQsEig/B56d8+3v1Vvw9uR0bE0uxiHj9tzLE+xm5lG/ytKVZcOSba/KZQxqDrsWFxWQqMlY7tvKNv4cMqLxXyRxRvgHACLLYI1jUipVv3UFV+Rbku1lBImlPWB3lW5ZTvsnhRajrZbin1jkzgSJSyKDx+yZpyEEoWg0p32rb8khjyNUn0lIWMmQ2BpFvZSQwr88eaytp79ipDyWUDQk79aDQAL3QcCCVrGhU+TaPZOsLE4qztqF+N0AtGBbhS+YZiBZedYnGcm5QhEyerQOrx8pl91j5SGUnv0N+GkjY/QKlFl8xo/L0UDrhJtvs8z4PruMsyGErEAXE3ECM1sF5vgWXnTqBC6JEvSq6mdjTJCgoBgI832gEjiGK8LtuHOXbGco6D/Hm4JTC4/Ul+z2F675pkHwruybXwQm8PVS+CTzfjiNb8MnE9ViOfXiF6rdaW/u7yOT5FgZSmllXEOT5BgDrrRWet05SNnWhVe2BX+mIAQ2z1Ft2qvU4lawh1CHf5hHxgD8m37qDRjzfSEVZ4Cir+MAFOci3UplZAIFatQ5pFAlalmJsVy07JfU935IufzvWp9gqyUHcO0chInFK0GqKlfQiz3sZlOVUxQZdI1EvO514Eph8BkAtQKohsqeeJU951jbT7waoAd0iMOroeNKEf27dv24U37xrHVZtkavaxqI0uHokJPpR7KmHtnusvIwI/sZ6uTrPsKjFH3Md5Rsg8H0rjDbX2P0QMfkWo3VwaafByrda2WmA8s0oeSOcJASldi297/t6dMq0ogTNR1UwD7NIwEC/DyGqwpLcELR58s29ihjo+VbPrLcdaKDs9BrtT3W/rs9V7ihT2mkY5ZvMoQyi8griIt+eo4d53juSCFZPJYVFxf2EDhUHzPMOexLdTIdrFXXu3xEf8q0cAfKNUorbntuN79yzHtvGI0SIuuD0w2E834haUb6pfp5vcpRomsyClQkFBmmOfAMAZHs/QaOgYlN1YdlpbRtrlWJKco6cx0xSsMClQ0Oq4luHPoZ8IyVPWJM0CFIjR7ns1CwC+V1AbhtglqoEiYh8+7N5Bv7PeBX/HfXSTid3A3ueaENjQ4AaMCyCVB0/WFHVg25SfPOu9XjrDx7BwxvkGZdTWqd6JCT6SRGf76GHtumaP49A0E+ZZYAaeH4M+NpDecFCbAjyjVU85uUiUmVGTL7FaAOYCSanfBOXnQZ6vgHdjcxuEkGBCzQCgQtRhN/ERiMWDiF76gR5SPxwoK2Qb2HTTjt/TZZK4QMXjiHbBHt6MeQqb5KJzAqzNmBKrHwDAJWw5FtN+bGLLvC8N0K8A7jtE/ISJEFlp2Wt37MtEaW00zrKtwUQq6Wk9HVicN0jW/FPNzyFr92xDq/91oOYykcn4MNBLXChvvJNqUxuaoELrOebHNelxZBvBlVhkRYcayQgrOwJtqBvFinfXBPOGertOyxJyqwchbVogauEZG3SnBrxvJdBCbqMxHyQolDPR7fs1BOqVaqWBorCgf5Vfw8+YvwDypyvVghF7J3XATu6QMBZJnRKAv18geCwLYsCv3tqR7tb1jSsNgUuDKCAx3vooe1ekO8X+fXqOjbNJPGm3xGs3Gbw4yWFX2Dxlp0KQhc2P9h0e/c3xORbjNZRR/nGrsZV006Dyk4BKcoTgmAHLgSVnUpKvlmmbdpqyDt5DkKQP8bpyrpgs9SCxOSbezJgGVAJcDDZg9cqj2Ihggf5hkVhWdQ20Q+KrO+C55vuQ76JBmhWiEeQO0hDl4l8CzEBkFm8a5edehuouJRvbLDJCOPx9M271nesba3CL3DBgIqCNuLZljazdilTFGAGT3KWiMpLYJNCMpdAA8Cnb36h+nO2ZOBHD0anzNmBvQhCuZApEYjmlJ06gQuM8k0S8i1b8I5jTChQrBYmpxL4+YrCZmzwzyO32mMKXvKN5uQYTzjPIpbkKFMVFhSkEg755k2Y7EMJJRmVb0FhI+Viw4uT0oC6+m/LqKqTuKRJ2M8qQCBSqKd8A+w52c3va7qZoWHkYWR3IiUoK3VDZDnixo1PyaWqb4fy7QRli1hx1iW4F6ozIm9ys4zfbT0ARcO2PWhK+caWnW56VJ6UbskRk28xWkddzzc/5VuAQgmQYpAWCLMU/FCRVfk29gCw42Zg9x29bklTCEqGOoTsCVZ+Sa188wYunIQNuD35UXw3+S3cnfogliNYmq9bVv2kpi5ck36ks2iApofI/PmfxNfwj+rNSEL3SOl7jTBchuzKN5agIooKVbEHY1NgyDdG+XbfS70vH/OFQPlmKwgIppPL+P0nN3enXa2CLTtNeQkbobcLbDIyan6Jj23yHku2ZOCbd63D5//4InZNybkwp5tWaNWEUlEWaAoBIYISHqNkL5T1GD9/eKPntQG1NSJXgnEdpQAJqXxbPlI7L1zSej3z+y7BeSyyC1ylyhh7wEk5TXkDF9KkHEHlWzG6nm/upFJqVBcTRco3vUK+sanj1sSL4X7XaMj9mgWlQHEXDIvWVb6xZakaDPyDegu+k/gWLlUehyJDakkF7fJ8A4C3qve15Xuagbsapk+kfDPKeGhscfVlOM83b/84IQq/2/ZoYw3dTxGTbzHaAFb5Fky+lWnIslPJlW+k3sp0N5IlG4VlAnoWMAuALl6VkXVi4yDIT2chmQn0PMtPy+MtwaN231DLwju026tpn8Mkj3/Sbg78tGFSoZrJu1Pnr0nLh3xLCwZo9QZtAHCQMoaPJn6Ff1D/KFVCFg0R/SlTmSwLSim/wkuUqgfVpFD5VjseItGAmYVF+QmNAQ0KAXJkAGPUO2j8w0NPR8IXjVO+ZbxKnBHi/0yKWugCO474yG+fxTfvWo//eWgz3vz9R6S8t0qGFdz/ulGZ3BBCkFAVXkUAAIWp9jWuSbCTMhMKzFamDhKM6yzfRSr+uJYM1ciPabDkmxyLec69wi4GFytVJoPpSglZ0ttf9KEo1TO1isCxNcVnbt2O/7prPfJlmQO0BPCUnRrVPoxdKDIpAa1ci2zIB518yfO6SFvwX2wF1AAsE6ZuYQTBaid27Pc36l34eOKXuFx9FN9PfhNnprZ2sqUNgVJAEQS2NYNL1VVt+Z5m4H4+9hER+VbArFG7djj1pSoqO/X2jy9YB/Pfm5N4UVYixORbjNbBKd+8rweYUALH26R+2WnvV0iDoOh15LUyKt/csncf8uDvftq7B0YYBCkLFmBaKOF3UJipkxTVU9TOh0WBv1BXet69Wrsr8NO6afmmPFbRDfLNx5dKZMo7SMLf4x9K/EaqCXeYpsjUXhH41U616nE0zZRYJYjpG2YiG+zVa5Z8U/GfbzgKOlTOu+nPT76Er9/pndRICfbeSnmTWwfhfz9Fglx04Zkd0/jAr1fjP+94CbNFHX96bnf1vZ1TBazeLofqyA3dtIQqFiFcJd5JVcEYhmFQZkg+vb2NrWsO7GKWCRUWbYF5l2BcR+FTdqryUyK359sU02/IonxzeGq27NRRvg2lKyqWhLe/6EMJZbP36koOdQja254bxzfuWocv3to7Q/um4C6XpUZVncSO2dzpoaxIQR33khszzHO6azCLwHMrcfLqX+E89YXAXdmx32cS13lev0O5re3Naxbt8nwDgMPIrrZ8TzNwk+p9onGboWNTtrYIyR2zSPnGeL79yXy54HujMUbsNWLyLUYb4J1gUqZUYohZjZ+BPQDIR1z5BrMOkSGj8q1KjFJf6f7aPbMYz0rY9goSAX46C8hMoPKgLIlHixCU2oMzI9tUuWLZtEIo3zr/YPQl34gOtq8YCiALRNAl8qeJetopIPA2UdSqrwdLUAHAMOTwoaoHi9pkoRuZpIIrT1mCvzhxETdhGSQF/OB+yT3GTIPrs3eY8z2v2YUuN6IQuuCGaVHc+NROfOueDfjgr5/h3h/PyhfIUG5E+UZqE5lsyYABjSv1RnGqfY1rEhqjAjGgYEvi8Oa/UIJxnV12KjpPfNkpAKyolJ5OYtCznRTlGE9YPoELJcoq37zXVz8pQjckfEbVGTs7QWfXP1o/sEkuuEO13Mo31pqndh3Ws+eZFSlmu4EN9wBbwy1Ypet4vp1lrW5Dg9oD0RiaEnG/UA+b6dI2tKg5eDzfRIEXhveccItGan3Pt1HMwz6miiAy/rk9Rky+xWgdbOACk441yEwIZqlNvtUvO5X8JrbqrHCbMq4AVDpkh+jxQVFilURQ4MICMhO4arV7z27f93oPCuS2ANMvwiqOCff4d+0n6EcB71ZvwQ2JL+CD2q+rq4q6SeXwfPMxhT+A7MOW9F9jS/oqXKk8BAIrkCwQwQjygukywvBqYQi6XoK7V0hN+TaLDExG4TLsWUiRt+5UpABNVPxKUulBzFCvAsSdqKubFv7rrvV4189W4fdP75AnqECQ/v27PYd5Xgelb0s5yQ6JO17cy20LOppcycBnb3kB7/rZE3hoffesBgxTnLIrhEBZwF6XoczVOwyWoDeh4s99r23+CyWYnPkGLgg83wDgPRfYZCOrfFMkIEcBN/kmVr4NZyrkW8pLHvajKGfgQp1gGfeiXVGP0qKCO1RLh25SpFDGFxI/9uzl9sKtVyE0i77A9zuGx38UetegtFMA6GtwHNhJUItX+9JEcwRnv9q7a1N3+SML1djMPcYRdAn+umLTTgHgKetI5hf3vn+PAlrIC48RowKHfFM0wDJAqfdG91O+WVBQogn/0AIJBmmBqDNAIDLKb52JJLUCyTdDxgFZBUFlPQsRTL71mRIn8VALKNllsVZeTBJerd2FM5R1OFaxV3zPxQso0CS+a14J3bAq5TRBZaddIN98lG9ufDP5XTxdOgIKaYwQILl9AI5qsmXtRRhSRmblG6XByjcKBTPoxzyXn8sIyQazHpJAWDqi2IELWiJdfQY5cEhFy6K47pGt+MZd6wAAd60ZxcEL+nHaQfO60exgCJ43E8yqcxCZXZa4T28GQSrYr9y+Ftc9YvsI3bN2Lx77+IVYNFhnsa8NMKw6/a8bAqKHKyGTwvONLYlTsEk9FO/X34vLlZUYJjm8TGmgZFuCyRkFoAg7MvGCwl+fdTAOWziA//qx18RekYAcBVxlp8xYuoQEFvapyCQr11qKUb6hCF1G8ooNlmEwQArV51DJsISkgJSgXvLNtCy8Wb0fxyre8nLDpXxjAxdYcIQ9+/s6Zc5Kwmt33qnejietI/E8PUz4vsgPuFcQlaTTRCY4gdcHadq7OaBZLTulnHoZALeYl2YD0QTkG6t8AwQVbJKkdMuOWPkWow2o3Nia/WC3mEkCOyFwp3oFpoVKMEgLArGCHxiKjOSb+6ESQL5JacJbQRC5liK6TRD4IKnLMVgWo/Y3D/rzO8Sbgw8nfg3A8XwL/vt0oxTaT/nG4mLliYa/W83LE5gRKu1UZvINglQvoiDpSrSaZpQeQ1EqO2VJ+gr5ltRU5Kh3QuOs+u6cKuDf/+idYH/6D8F+Nl2DQGnNnp/BAOVb1Dzf6qGk+x+PQ7wB9rXwvfs2+u7bTpiWxZU7+yIiyjd2ImpSFWVLwZ/py3CN/iF8Vn97Y18owbhIuPAACEutHJx9+ALkFK9yTC3PSJFI66d8K9IkRjIuYoopO1UIBZVxslxnbO2eU0SrX3MWvw1g7CEYhX24Wr2T28tddpqrUyFUQgIl6nPdOmMxarX/OtUC2sUQfocoe/GH5CdxvsLbB1QhicJcFMZCFRVlNB5skRaljHYJRkX55qvEnsp5Su+5tgrIN00hXDItGwgi+7xdFsTkW4zW4XSamj0RcM83CSwkmcGooQSv5FQh46DABWIGl50qRkGaB0oV1fZYgXHthiXvgKaeofVi+JsgJ/WZdjenjXAFLjT856d22alFoQaoyWg3fAjr3BcOFpHGJ5ZaQR7yLUxJqexlpyq7IqqonkSrKUaJ407TlDvt1Ef5VkmWZC0PMhVD4oJABfLSHnEqdNchIN9YBV8mYLAvk19iOyA6V37oVoK3aYEL+vCFQDnCnk+Uev+8EinfyiYBrajE6ilzOEjg+Wb3D4L7oY63U5Yh3wioFASp85ThAxcSGEy7rjOm7BQASEmS/s0NI5h8cwc1Ratfq5yp8gRgFEGNAo5WdnB7GdRFvtXxdNOh+Vv4OETI6IPAnjvbS8AFkW8J/j2VUFyX/Ar+lPyY+DOjcoRnCEvSFRVlpXHldIb2knyzrzVfJXbZwE8S/wHnmuTKTjX+uiOEcCrTAtv/y16xJgl6Sr498MADeP3rX4/ly5eDEIKbbrrJ8z6lFJ/5zGewfPlyZDIZvOpVr8ILL3hXoUulEt73vvdh4cKF6O/vxxVXXIEdO7yd2eTkJK6++moMDw9jeHgYV199Naampjp8dPsRHBKnMnBxzzeTooGoWuvEHreO9v9eCRl0Sim+cec6vOKr9+DTNz0buC+hZl35fPdRkyIHl53KSxokAwIXAGAJmfJ9j0ji0SKEiwxtdDz5PvX3FeVbnYlfF8i3eopQB0tI40lxanmq4c90CmFEbYbMyjcqGJgpKvqTtVX0SeqdrH0l8SOsgNiPUCYIFaCVMr+ESlBkTKwzlZKLQpnvE6VZiBCRb4xSyk41E19zc63sVHSu/NAtEty0GghcECjfuIl2qfc2CUOM37sFBWUTVfItS4PJN84QXgblGwQLD4DwnLhRUIcEG3ufeOobuIAEBlP+yjcAIHrvrzEOddTz7uCfSCnfqrYvFIDlO4Zwe77VI7cNqP7hdUbRHlfqM7aasJ2VHw2Sbw6OV7aK35jmSchewA5cYL1wlabItzRKPRNgOHO4IA/SC9RncALZDEDgy5cUlzOzpafctafLLZqRBT0l33K5HE4++WR85zvfEb7/1a9+Ff/5n/+J73znO1i1ahWWLl2Kiy66CLOztZWaa6+9Fr///e/xq1/9Cg899BCy2Swuv/xymK747KuuugqrV6/G7bffjttvvx2rV6/G1Vdf3fHj23/gkG8K0H+wp2SOlcEDgJqs3ay3mS/z/1oJGfT71o3hv+5ej+0TBWh1SCAAEqr3wgUuyLyaWC8GPIjU6bOy8vrZuR7SZoMT/n/SbrHJtzqqM2J2YTAQknxbhKmGv1ot914J4iCM55slMfkGCMI5FA39rsnaXsp7nd2V+jdkUMTYbAmbxiScuMGejHKDTkUDQJDQFM7E2ln1FZl3S3MKBRNS1mxbJZSbgDvQozRJDYF8Q+RbBxvigmE1ErhQu8+ufvnBAIAcpyLovSqJUFb5pqLsGuTVIwdkNOQWLjwAvoELDkgiU00QdbB63ZY2tqw5OMOFEcZfuYikl3zTktAJUz7XhJdVx8GOIZjzMp/U7otoLSq4005NWBTc9QR4Pd/qkds6VP9QBj3v/VsGjPkbhhqQwppsUA0LALNyhKFZQuWbAqMJ8k0jFoxybxYbnIXfekrs05T1AIAMYRbmNfE5TGmM8o0y14EEyuYooKfk22WXXYbPf/7zeMMb3sC9RynFN7/5Tfy///f/8IY3vAEnnHACfvaznyGfz+MXv/gFAGB6eho//vGP8fWvfx0XXnghTj31VFx//fV47rnncNdddwEA1qxZg9tvvx3/8z//g7PPPhtnn302fvSjH+GPf/wjXnqpAZPYGP6oTkIVILXAo9pJCW78+cM1NcXPzEvw2KF/Bxx3ETCwyLujBIM0Fk9sqUXLs4PsaZHxqWwDm+q5qqN8k2bGyaNe2WkQ+TaEHF7a0/syETGo56dJyq9S+6GPlFA2TNB6CbxAx9WY9QhAB4sDFIp+0CQi38KoaUyJy06FybhEQX+qtuq+Fzz5liFlvFm9HwDw6q/f39E2NguLUmis95bj+aYqKLDKt0q5pswpz6KSoVnBM8ev9DRak9T6yOuCfsbSgZn13OZuJdaatIHABVeJ45mHzgcAZFkiSwLlm8KME0yocPOevqqbCjbS5d4NugTKN9+002Bfp0xK40rxf3znUz1frKSUYhB5/L12m2d7iSZwwIi3ryspXiWiKqNShV1oyHgV2PPhIt9k7rNZOP0QUQBqK99KAi8x9xi3rvKNBpWdFm1/uervbyP5FjTWDFC++WJ6e/19ugEqUMUSBYbaBKEIQC/25v5yRAb1xAoLK/YvXOiFT8LrYNqrDi7GyremIG3a6ebNm7Fnzx5cfPHF1W2pVAqvfOUrsXLlSrz73e/Gk08+CV3XPfssX74cJ5xwAlauXIlLLrkEjzzyCIaHh3HWWWdV93n5y1+O4eFhrFy5EkcfLS57LJVKKJVqg9iZGXvSp+s6dF2eZJZW4BxHy8djlEBMA9Q0AcOslOnYA0tRoIKipYGKYaoFBc/NfxVOP8mCYuhQ1t1X3c8sZWFJ9remLlKK7dRm0YdheAlDPT8N9Et0DLp9rmDogSRMsSTvdc6SnpN0APNcIQtBXmIqoZidGoe+ODyxFQZtuZf0EpTKBLtsqkiFLV9yPp6bgl7kPV24/Yo5INXBdZeQgQvNkG9Wfgr/dedLMC2Kvz37IAxlGjfBbRcMs/5AVub7iFK+RM6CgnypNqgeoyPCz56tvIjrzEsAAOt2T+HQhf3C/ZpBO+4l07Q4kp4SFYZhgFCTm6w4SV+FkrhPlOIclovcNI1VvgF2guEU+H6gIPG12AzyRcHxzKwFyW4AGHLVsKyuHLuum6GVbxYUmJU2JSo+nVmmRNMqTlf3ab5Nrd1PROD5tnWiAGftntZZw2dDQaxyvuVjahV+5cGGRUED2pZJKJikgx5rC1KcxPPbJ3HCCkFJapdgWhQXKE/zb2hJvPnkIc+5LysZwHQtYpWmpesXNFP35M7SzCBIbqr6ej6ptT9fKnet/S0/m4yyPf42DcDUYVoUhuD+ybiSJzk1LPuVAWWnRnEWtJSv+lPTch7Q2vO3UvWi751vJdMNK3usyc097xcAoKTrfOACFJg+Sj86fyHIhL8XcSE7Ca1vuK1tDINSZXGq3vPoAGK3nQ1cMJWkcP69fCSN9aO1+RZ77VmlXOjz2DYOQhI0chzSkm979uwBACxZssSzfcmSJdi6dWt1n2QyiXnz5nH7OJ/fs2cPFi9ezH3/4sWLq/uI8KUvfQmf/exnue133HEH+voCop0jiDvv5NN2GsGgtRV91l7klF0okwHsG6cAbBVbUlACMz45DffgeOPWnXiivBMHj09imWu/nRtfxNO33tpS29qNTdsVOINOlnwrUw05pNDvku8+eu/tmBjY1M0mBiJJpzHPfAlpOoEEzQI4Wbjfykcfw8RaOVU7FzOT6j10nod8q4dnH7kXezfwfUI70Mq9NGBuxQpjAwBgb6kfZ4RVUFTw/GP3Y3w4DV5H7MVdt/8J5UTnJgrnhFTWDZHGla0T42P4xt323+jmVRvwryf2LmluzU4CILhM6f4HH8LW+nxoT7BvXOFUOnvHxvDC9B6gMvXZQRcKP+sui/nELx7EXx/RfvVBK/fSlq0KjmH6iZlcHg/cfjv2FJOCslO7z35s1ZMQndNbJXgODeW34gLXa52KJ10ZUhLavj32xJMob5azT7fR2HB03aatuPXWzZ5t880XkKA5AOd4to+OjnblHG7YzN9Tfti2cyeeqbRp7ZTdl+TgJd+m9mzDg21qd7P3EzENzy1h1unzWLD+imO7tuLRHt9P27Ypggk28PAjj2JKnRB/CEBxVsU0F0KTxb0PPoRtvePeUCiq+AftT9z2sxeO4cWnH8YLz6yrbjvNSmC+a5+pPdul6N/ceF255OkNpssUI67X7lTnBx9aid1d5jaavZfmmWswYm6ABQ1JzGBi8iDh/eRWL7PJ3CyCyk4fffA+zA68hHmmXeU1q4whrywR7tsozty1A8t93hsvmVjk854fJjetxkMSXIdTJX5ul8vnMWPy5+EB9RQc1Z/H0gDy7cF77wIG/f5SncOzu+1nClcBwOBgsheAl/AFgOde2oit4/z5yE/W5sAAX3Y6OzGK+xo8j61yELIgnw8/p5GWfHNAmEg1Sim3jQW7j2j/et/zsY99DB/4wAeqr2dmZnDggQfi4osvxtBQD5+ybYSu67jzzjtx0UUXIZFoQUEy9SzIzBrQzApg6FjcPPY4UBm/sIELFhQsX74Cz03XTLsXLj0AZ5yxDMqTW4HxWhT1AQtSWPba1zbfrg5g7V3rgR32gJ9PAVOxl87DYaRG6p597HLQEyU6huIoyMQgUNgJUpoAnhTvdurpZ+CCoxt9fHYJT3n/7nvofByL8JL1k45YjtPPvbj+jg2gLffS1DNQdtjXTiqbgrahMULj5COX47hjjgfqhEZd+KrzgOEDmmtjCOSf+Rc/z/eW0U9qJUtbsgSnnvtqLBturhygVWy7fxOwbUPgPmeedTbOPIQv3ZQBv9izCmree40tWbocJ85fiu3P2wOyx61jhZ91k28D85fgta89tW3tase99NBNL0Ab9/YTg8MjuPTSy7BjxsLTzz7hec/xfDvx5FOAdc9x3/daGZ5Dm+8CXE4ZJhSYUFGiCY/CvM+n7PSEk07Ba09eJnxPBrz/kTsa2n/BkmV47Wu9i0dkNAMYOWAVs+/CRXjta09vtYl1seqPa7BhdG2ofQ88+FCsuMy+rhZtmcT31qzi/J3m9aktX3ut3k9/fvJ7ntcipU4Q2BLvhcN9Pb+f7r/xeWT3Mcbviopzzz0PdP4Zvp/73b4nMbXFq5ofQQ7Hn3omXt3D8dLnnr0P42V+XrL8oIOx9FUXApkV1W171/8HkK2Z2y8YTPb8fLBQn/UOIIYWrwBmam0eQI18O/XMl+EVR4gXidqNVu8lsnEnSGExKFQQsgTDE/OQyvMCBXfyZCvKt5efcTLoihPsMT8AOng0MHikcN9Gof76OvjZ9i44+HBgbGND3ze/tB2vveQiQK3zdzVLgJLsWNz6rqkCNj1zt2db/+AQElgKjHoDH9XUABYeez6wfR388LLTTsLCIwO8zTuEvSu3AlteqmvTc1CFfGMDF0445UwcfxLfL9x8w9PAWG3+zpadDqWV0P1J2zgISeBUSIaBtOTb0qVLAdjKtWXLagPG0dHRqhpu6dKlKJfLmJyc9KjfRkdHcc4551T32bt3L/f9Y2NjnKrOjVQqhVSK79ASicScuEjcaPmYVBXIvgRYOWDkSLhZcTZwwVISyKS8v0u3FKweJVj9Ygbvcm1X9Fkosv2tSe3YePJNww66CIehRr5pMzsAmY7B0ABVAxQl0PGREkXO69yyAMKTb41ALU517NhaupdUpWosTIha1yiVhVaehhpiXpSA2dFrUm2w3Y2gH16/oKmiiYMW9uY6JUr9P7a09xEAgHAqHUXVcNVZh+DWCvmWRxpf19+EDyZ+69mPuoqC8rrZkWNs5V6iIFy5haJqUBJJ9KUtruzUMRs2qXhA3+tz+IfVO/Gr367FL10jNocAzSPlCVno81G+WZT0/DjaiaJBBcdjAMYUAFbZ3J1jt0Dqeuw4UNUE1EqbBjI2QcUq34iebVu7m72fWIWYSVtTvkHP9fw6JIRXvhGiQEskA5+NRZ1iivFinUdmMVuyenpMFMCMoARdTWSgat5jspJeKbZm5Ht+PjgwfmJKxkss9rvIt+d3ZfHqY7u7qND0s0mhgJUHSpNA/0GgVOzR6V5Mqad8M6D5km+aVbZVq+V9QHIeoJL2jf0CgrWUocbJUGKUkChPAUMBKrHyFLDvQaBvOTC/M4spqsaXnSqKBispWERVM9CGgheyqVHqyf1lVcZo9dK3F5EZ9KPAXYdaut/nWvGOkdjFFWIUGz7eucKrNHIMPQ1cCMKhhx6KpUuXeuSI5XIZ999/f5VYO/3005FIJDz77N69G88//3x1n7PPPhvT09N4/PHHq/s89thjmJ6eru4To0VYzk1LALPkSTvllG9KAumEd/BWNID/dy/BjgLzkNnqVSf0CpRSbBrLYu9MEabL8y3BpJ3qUHmPJAli6L1wp536d8qGKWl5kuCBLzKFD4KSH6u/Uy/gMsM1LdufrhH0T661vUTqwehsGpFGO0i+ES/5Nlvs3O+qhzAe7jKb3FMAKsvSKCpWzPMSAP9j8quYbuVBttS7c+AHi1KeBFE0gBCkNZUjBJyBpy5hv2eYFj57y4tcSrObfHNjfwlcKIjSTrMbgSxv8xAmHKUdME3BdecHpcakJiqrJpzKpdRb82pKqSBwIfy0wUoOosiUJVEJ0vAoBIELRAE7sWTx5LZJLnBhmOQwXei1hx3FDOOtB8AOaSHe82UmvOShZvQ+1MMDy+THpmkv+TbgGgf8553rsC8r7vOkAwVQ2A0Ys0B5Aio1kKhTFjgp8O90oxyYdloAZjcA+W3A9POhk+hDIcheZGCkue/M+Zdv2u9vBQq7gNnGVHWNQJiErCiw0vw8g6gqMLQYyPjPQcxib+4vZ64axoN0CZnkFXI+aadvPN1LNnLXngT9exTQU/Itm81i9erVWL16NQA7ZGH16tXYtm0bCCG49tpr8cUvfhG///3v8fzzz+Md73gH+vr6cNVVVwEAhoeH8fd///f44Ac/iLvvvhtPP/00/uZv/gYnnngiLrzwQgDAsccei0svvRTXXHMNHn30UTz66KO45pprcPnll/uGLcRoEFalEybETvBxp50ygQuWmkJK8152BQN4aYJgVGTuPbWtzY1tHB/+7bN49dfvx3lfuQc3PlWTvrODbBMKZpmVa5TkSWcE4BrU1CHfLEknagIz/720MfJNLdZ5wPcKzvkgKqwm0mYP3PFHYdppmVUqlDubIqx2knxjlG9FvXeeb2FOkS55EhvnB0JUHLKgD0e4AknmD6ZADzzcs9ugi3zbN9vZ9NxmYFkUGrM44qhKh/sSAs83+xh6nVoowqZ9OUzkyty5csg39lj8yk5lPLZWkGfvfWoBs9uB7c/hYOL18+0a+SYiff2g1PrlZGVMxAYu0A731fVgCSaijXi+FS/6Ckqs8k2CBHjhBJsoHFHF4uqXH4xpypadZjHTY/LNopQfewLA0BKwhCJllG8Jo7fXGAdD0H9lvKZu7Djgzhf56iY54fRDFmDqSFj1k3830WW+3quAnXbqm4iq54FyRQBATW/yaavwI98IAeYd39x35gPG5qV9wLbfAtnNwOSzzX1/CAhT4BUFVECwKYTYiyiXfAHQNGH/YRV7MwfUq2mn9c/5QkzzJLBPwMSrj/Gqylnlmwxp1lFAT8m3J554AqeeeipOPdX2i/nABz6AU089FZ/61KcAAB/+8Idx7bXX4j3veQ/OOOMM7Ny5E3fccQcGB2sPj2984xu48sor8Za3vAXnnnsu+vr6cMstt0BVawOEG264ASeeeCIuvvhiXHzxxTjppJPw85//vLsHO5dRXU0hgGUwyjfvoISqSU755lgeCP2F9vD+O93EhtFZ/OZJm3DTTYp92doDhx1k69AwSxnpf9E/ebM3cJRvFoS1SRXIqAABIHzg76ONue1qBX9D5Z6BUmDfY8DsugqB3TipVEyMgAo+N8Os1Hd08kNpXY+JVuAuNwGAot47QiHMhN5ogkTtGiigcINMFYQQfOuvTsX5Ry3CeUcsxA/+og9k/lLPboOusIw9M5XBVmE3sONmoNh7ZalJBSu+igZnInrJqYd63uojJQAUZYnJUtFiD8CrpfqIePAr87E1gxJLvk1sAu68DnjiXtyf+gBuTX6sOvHo1m1oWjR04IKbfDuskhbMnkti6YDRO3LbsCxoYBWXIacNh54EcsIbkGWPSQryjQpUv/WVb+9+5WGYAlt2mu2pAhuwhw9ENJ474HjOG4smve1Pmr1VV7J4ZusovzEz4nnZR0qeZ9foTFSUb5U2Vxa3E1b9dptQcW35PVhtHSZ834DK2ShUoddSie3f2wXyTU0Cy5v0EMwzY3NLr/3NxlcBZgHIbQYKOwLFA63AoiJVrApkeHsbJZG2y19Pegtw1X8Db/8+1tBDvN9Xmu1IO+vBUb6FWQxaQGb4cbsP+cbO37lrz9LDVeDs5+gp+faqV70KlFLuv5/+9KcA7KCEz3zmM9i9ezeKxSLuv/9+nHDCCZ7vSKfT+Pa3v43x8XHk83nccsstOPDAAz37zJ8/H9dffz1mZmYwMzOD66+/HiMjI106yv0AlqsTpiz55r0JqUD5ltftwcE+CEiUwlS7WtkU7l4jGAhUwHm+URWzrO+GrORbHbAlTrKACpRvXKlvHSRL421qTRth5IDiBPDCs8CdP8XCTQ82/BWp8qRwcDXLqClQ7uBgu42Duyct3hi4j3gHq71UvtEQ5JvsaiO+NNPum49bPoTr/u5luP5dZ+GEA5cBI8d4dhuC9xoaz5aAbb8Hdt8J7Op9Ypm47FSFM7k+bBmvJEhBl7o0kyV1qso3ZvA7jBw+oP0aW9JXYUv6Knwn8V8YQk7ea7E0AYw3bjFRYsnEVT8ESjVy/jhlK65R7WsxzL3aDhgWDVXmA8Ce0Dk/EoI3nnYAp3wD0FOlmGlRjqAXKd8+o7/du+GoM4BzrkYyleaez2o51/PSJApA5VS/9ZVvy4Yz2Ee9JZCHk53IFnp7PBYVXHdLDwGUBNhpnpLhPd9kwX0vjeKanzzMv5Ee4Ta51W9JradT2QbgPUdhlG8A8AQ9BleWP4+3lj7JvadDRd637DTnJV9pO8tOfb4rkQa0AWCZmCwMhLtSyDKAXbcDe5zwA8UeI09PA4Vpj01LO2HbcTB+kIoK0s+PGdTUiO0/RzQg2Q8k+lAk3nNBS73pv52F33plzQCwkExzc3U/8g0APv3646o/s7YC9i+PS0/rISo9VgyZYVYeIIQAVK96IZ1CNuD7yW96dqVqCilO+VYbGK80j/O8hx6tGoSBKO2ULzuVjHyjLtl7AMwuTVYahSVQAYzVUb7pxGuCmSxJqHyzSsDax4Ddu4DsNBbsaHwymtSnubJTkxLOxLuj5FuQD0iD+Kh+Da4o/btn20Iy45kMFg25y05lVhtR8BNrEEEGk5oG+r3hRIPEO7jKl01g5wPA9ueA7Xe1u6kNw7L8Pd8AQEny5uQZlOQlqABegVQpJ2cnXp9I3IB/0W6qvr5cfQz/kfgByrKqmSeesFWTDYIj3tfx191HEr8Cw67gyQAA7B9JREFU0D3lmyVQvhnUZ5iteO+1vz3nYGRFpYM9HAMZgvtIpHz7lXkB8iMH2y8GBoET/wLoPwSqQjBJRvgvXv+L9vpPNQhLVFoWwvMNAA47+XzP6yFSQP+Uf9phN2CK+rtUBgDhlG/pfu94KWlmm7K56AQ+duNzSIgIor4RbpNbBZ9QO5N82XY4lQnUAmAhZYlJiq/ofyXcLgrVMAPSTlHOewnlNo7PfMk3NWmTvse83A53A4BkCugL9q4D4O3r9MrcyZlf6nng0buAVY8AD90HbLq/6aYHwaKUJ+YVBUo/r3yrEluEAAvOBOafhiLx9uGZfb2p3jKqZadhyDeR8s0/POAd5xyC915wBADecxaAPccw5FLUyoaYfIvROqosd63sdASzuCn1KW5XqgmUb657nht8Sky+sSuNOlR+5bpHqx7+oMy/YsgyGGNhCR74E3UMaWc074pVuiwh+UZNYO3Klr4ipc9wyjMTCv9w7KSSopXB3XnXAMe9CoUDTsQrSt/AenoAb0AO4LXKY9Wfe1l2SkOoSKUt366AJXQgSnBV+4Ckt18bRB6ePmTvc8DDdwDPPg08dBswsbn9jW0Alqj82VXmp6b5PqMfRanJUtFiD+Az+GVwifqEvMdmNlcyxinfcv7lzt3yfDMsi1MaiCbMALjJzUkHjCCPFCw2cbeX5JtJoZL6yrciUtj2ik8Cf/kR4IpPAEtOAxa9HACQ04Yxw46LNt8N6L07LrvsVKD6raN8A4B/fP152EkXeLalco2Tx+0EpYJJtuosNnivp1Qfmxxa7Okilhu7p4tIsl6dAJAa4Da5w5e4vkBamLCfmxZALSQoP156yToAvzXP57YDwLQgVCMJnbe7caDnARD7XtOngJBKu1Dwq3LQkhUy6kDgnPOAU88AznklcMql9b/T3de5+2zLBNbfDcxUCDnLAu74RPNtD4DQ840oUAXkW8ZyEUyZpUDfCkwrI559Fu64G72A0UDZ6SuV1aHLTgFbqf2hS47GJy8/TlzyPPEMsOceIL+roTbvT4jJtxitg7o836gB0wIuVJ8S76umfD3fAMivHHOBnwxpPFkggb+JF6600wDI6lVFBWa8ZQTHO+eSXvIto8uVQEspxYax1ks/NFrmVG0GNOTZqHq9g2UmfquhYTCwCDjnXaCv/hC2U1tpJUpwe42rb5E9cOFrd7yE9//qaTy2Sb5SZyr0fBMo39KLgfknejZpxPKkag48+T3ArJwLXQdW/6LdzW0IpiUqqa2Vnaop/rrKEDmVb87U2c/zzTfpjoGpyxeM0Qo89z6lgaUu3fR8Y8/TFOWJAwDCe+0VRy6SagxRMkzf645FauQwYMGJwMKzgMXnAQmb5FGJgtXWEd6dp3cCPbR/EJWW2WXA9RVUI31J9A96CSyl2NsFPWGZvZqErXzzni+tjw8vyIuSg3sE1icagE1Uq977xZ24zfk/yoriOJDfbS9SUhNJARn2+vIXMIYR4cdFRH4ChjhsA7DHg6UpYOIpYHYz0M6wsSDlGwAoKSCVBhYsBBJJYChEGapnocHVaZdngYcYn/bRNQ01NzwotyhJFBUJgfoyafALCHvUZZ7XlhI8P+kUDDM8+XaKsgkas8gSRL45yCRUlETzr9HH7GtuovEKnv0FMfkWo3Xs2wLcfQPw208Dz/8RFiU4hWwQ7koTfZzybf1EbcDDKcd6lBQTBmyangGFb38nS/yaAbWA4h4guxlmwETTlJV8Y4w8LUp8JwMO8qlFntcDxlRd8rFboJTi3T9/Epf+9zNt+T6S9a7AG1CQ45RvkpadDh4CwH6gO5UyokHooaR2jL0cdIdR00zkyvjD6l14248exZ5p+VKguIGZSPlBCLDwZG6zO/F03obfe9984KvtaF7ToJQiIUo7rVxYqWQCBcarZABFX6ViL5XAU5UkRd7zzZ6MitShIshgdN9OFHWz5uWmFwKIf9o1zzcR+Tbpp8wWlPUMZxL8+eyher5sWL5egyySI0cA808FRrxE/WzJ4BPJ160GNvSuPJ1SfoINwhNVvp9Pe8m3RLm3C3oWpYLkakVYSptklG8DpIBntk91toENgPOeqtgFUM3bX7uVb8UoKN8oBQoVJZA+BcBCinrHBButZYGLyaK+PkkMTFKfPkbPA3tXAZt2AGueB8Y3Ntl4AXyVb5Xxppq0CTgASIwAg4vE+7tRYuZ75SlAzwJr/+TThvafd0uwKEkIQSrJk1GKwHduTcKb9Krp2cq53wvsuKVrarBGlG9CBJSdOlgwkASFwo2lsPUxYONTwKiPCCdGTL7FaAOe+D0wM26bYN7/31hhbMMxynbhriSR4ZRvbnBlpz0mr0jAQiifAqbykd/lvDREjw0K5LYBRhZGwGRMVuWbxSjfdNRfrS5lvH5VKkygONXmljWHxzZP4I4X92I+2lOCo0y+5HltQuWVb7KSb8NHAAvOAFlxKfqTtVXur+pv9ey2kNQGaN0cdG/el8Otz+3G2Kx9DTZyW1sU+N594gWJXoEC4X0+UkPcpoXEViUTP//Icu8WTkyRAbnr2JKawqUw9pGib/lSL8uy/uN2+572S530Tbpj8NALm9rbsB7Doq6y7oD+vA+lLpad8uRbiSYwLSoLEygihjMJ5Lj+unflmSXD4u4jx2uQRSqVBvoOECr62IRQAMBtn7XHRz2AWPUbTvkGAAqjHsvo0z0NqbKooC93iDeGUExmGPINBfz9z57A9+9vIzHTAjjlW0Xxpive+yJyyjdq1RI6Kz8PWt5725eod75CMGU3qIrn6GEYo/wzGuU88PifgD3jwOgk8MDPAb1Ni4B+KczOc1ZJAZkVQGoR0LcCGFoCLD068CtHx1wBd/ossOuPwM4/AFt8Asg60DcKS7gVFamEoF8b4o9nKsnMN6huLw5Nv2BvmHiyY0mtbjj9EdcvALjJPKf+F4RQvi0dsu9JTpH5/EPAM/cBt3+PT7CNASAm32K0A2NbPC8vLd2Jg8ke4a5aup9TvrmR45Rj8q7Wi8pO2QkdQHtOIHpQnYRQGJb/gOWlPbOYLfbOENkP1PC2SYegTI6B0beY35iTowzw90/tBAAsIu0pr1bHvcbPtvKNVVJ0cDIn8uTzK7tiseR4ILMMUBIepcqDlldJsQSTVcKnW2Wnq7ZM4JJvPID33PAULv3mA9gzXWxYDbV+VK6+zFaHsYNMH/JN1UCHDvBsOoZsAwAsEBHHqQyw5452NLMpWD4DaAcpTeFI6QEUfMtOe1mW9fgWe/DKKlsc7y3fpDsGVnEWkzl5S09JyCRuN0oOKRqQij6AQicEEkKYosAFqGJliso/u4YyCYHvbQ/LTnXL12uQRdC4Tlh6qxeAnU+21L5mIZxgh0g7dZBgzOOHkMNkvjfjJec5xJfREqHyTWH8Lu3UUIov37YW2VL70sqbBef5VrlPTNXbX7ttD3rp/Roelq0Wm5oFZvKAZWLI8i5QFdQB/O2xwYtWa1Pe8dBvzFdCh4Z/09/N77z3eWDSRWjN7gN2rmr6CDzwTSyu9ONan03EJ+cBqQXA4KHA67/ApQW7MTbuGpc/+TPgnjuA++8Ctj8u/kAHxrIWFQVRqUglEvih8brar6Ya1h3MB2OUNMHxFae8AQRdCCMwfZRvL1gH41r9vdhoLRN9rIYQ5NuKefazasJPeVkuAg/8R/3G7oeIybcYrcEocyz+weZ2LCLiB0gyMwASICeTqeSiHtgVBZ2q/Ko1IBn55pwrCiNANfT7p3figq/dj7V75Cr7pYyyypkIfEr/W9/PkPQgsux5CTDn7iYcRcYiMtWW7xtYd6vntSlUY3aSfGPOD1UwXieNFoD9oE/U2pl3kWqjdMSza4KYmAe7X+gW+fbl29aiXCFmxnNl3LR6Z8NUwcqN47jqR49KVeLTSMIVWeYd9B+nbAUALBARx6UCsGt1q81rGpYlUL65iMWUpnD3RV9A2mlBAk8kv9TJMIELADCAPH731I62t6tdoCFVR25UJ90ByrdBku+a8s0UXHcGVEyB9xgUEd19CcEYoocLkGWT93zzJ9/E2z9w0VGYFh0/AGR7cz2KJ9jh0k4BXj02SPI9I66ca5tX+lbOBzveTnknygliIlVRm935onjRvJtIscq3ipJSV72kdD9xkW+SBEYEwjKB1U8AL24G1u4G1j6HIUb5tnSeiv5M8GLl9QNvxwZrOWZoH76ovw27YHsa32edio/pf+/deVpQgbT90ZYOA4C9yCrwXwZQKwVNuUJJ1Ixdjr7sAryVfBX3midjgg5wC0flfOXvUZwGHvyu/V267l8u2wFbIrHyTUEqoeFrxlvwdf1N+I1xPt5S/hT05Dzu83pCQEQVprz9fRfCZnSHfGMW7fRK/y1M1nYjRNnpwgH7/PmWPQPA09fX/Z79ETH5FqM1sDX6AI4w/eXrimUiFzBI4c2G5U07FQ1Kc6IOTSr1niN7B+oFMe7LlvDtuyUrlfNRvv3GfCUes44RfiaZSPIrM/k2Gs+2AOcUtIt8Y2FA5ZUxXSw7NaD6mwG7cfDpnpcL+mttHge/kri48vfq1or3k1u9nj7fuWc9rCZKbFduHMc11z0hRZqwsOxUEU+gAQDzvabp84ndNy/wWWjBwzcARm987mwDcv9jS2kqp1IeIAXb40ohSMDAAWQUKdjn+PHNvS+d4BRV1O77CiE93wZIEVM9Uud0ClXyfdafxBlAoWvOD7byjbejmBIq3wTkW0qLrPItoYqJq/6UxnvhOij0xiuNwifpOchnxAWVU77le0bQO48Srr+rqviYaV6KvxZt9Rswket9/+Bfduq9hjJweb5Foex011PAhEvZtXMHVlhe/y8jMYRLjl2AIFy/cwUuLH8NJ5X+Bz80X+95L5QKeufToZvsiyDFmeMF139obZtzXyka9L6leKf+EZxW+gGn1quWEm+6P5yFSdeUbwo0TUUZCXzbfAP+zfhHPEOPwJIh/tmbTiaRY87Dxg3PApsfBp78JTC1EzA636ebllN2KlbM+/bJDkIo3wDg1INGMCEYo1cRUGG1PyMm32K0hiKveuBW4NzQ81W2XASuQ+hkiVyLEA1Ky9Cgs54oMh1D1SSVIqfXv/3/9Nzuuvt0E6zyzVnFKSCNt5U/IRx8pJJJjINRX0mmfBtCZ7xvTMorfDpKBjNlp2UkUGLNWEUY9PpkfPjSmpeGAQ2TTNnSvArxU+jRoNuyDNBcc6qN0dkSdk75JzN2E0G+aBwy3nvICVzw9SucnbAnHD2AyPie9Xxjy077UIRuWphPp3Bz8hN4KHUtbkt+FMuxDx/8zTNdM+33A6+osvtvdqDvhwEUoDQuLusKmv3TVstOZ7b47jNACl31fGODPnSomBR5nomUb0lV4HvbW883Vjlh+Ewb/Coa+pIBCzD7Xmypfc3CsigUNt2PqAg7JSIppi8k+d49i6iPsbrio3xL8tfiILHHHyUJFGTCwAUAuub1leqPWtnpOL+QfRQjVLC0fpy0PIXzjrDVbGqDHXYo/8/ZNozpBaKLKhzl27BrMVyv7d+XdOZHhOvrhpXKuCjswmaH5lZ8GIsCEBUXHbuwumlpn4Hzj+JDJDJJXoShrPoRcOe3gKf/BPz2I8CuVR33Ateraafs88i+n+or38KRb8uG09hGBdY+DvyCOfZzxORbjNYgIN8Coedx9uH+Kztd9acKARJQhiBeESYC9Z5EZaeVh4pFKf7ygQtCfYIW5CCqAAH5Rmu+ORYUPEv5OPNkIsH7TOQkUb5Vnr+OwqbdsNWYXSzlNlllooo/WCHMXTPzPS+H0t6J6RT1li0Nw76nglS0nYRu1hQHzcDP2L+boCKT7iDyjQldcFap0yTg2v3De5ttXkuwhH52tb4iJQhc6CcllAwLVygP41jF9rM7TNmDlel/QR96rxpjlW9mdeEhHPnWT4qBlg89QWVVvNlbaaZYuX4D+rQBdI98sxWX/HkSep4JPN/6koKy0x6OgUqGqOy0vs+qG31JFVlR4AQAPP7zjiQW1oNFeYViI55vYNJOh5DvmfqqRr4JPN8AcNO8RAYm9fYD96c+gEuUx6VQZPPKN/uZpCvea6jPVXYqA2lYF9M7uU18ia0KQg387O9eht/909m46wOvxJtOP4D7nB+4hVYRCm1QcQeVe7ptiNJL7X/7DqxtcgXusXYw/Y7yLUTJIwCg1B6vZDdMi0JliXnFJua//pZT8Q9HbsTbDlqPX/+lISRHk5qCWUZEcujUE96dfvUeoNjZEm/H840d45VpGPKNBFdBuLBwIIXNdKn/DjH5JkRMvsVoDUErICL0LYCqELz2RPHNyvudyERcecGvCPvU0stUdlp5MN4zugL7yuHKlSY3/MGO+5YA1BSv4jhYZ/EDlVQyyU1+rHxvyl1YOGqaQAKjBZhQeDVgsYPHzikTNfzePA9PWUf4fKAChthJJbyPpmlGOfIyZS2AHpJvFmmJfCtLQL4BIvItYLWTKVdy1BLcBMKN8Y09SXsWBi64yI6+pMYp3/pRQFE38ckE71HyXu2mnhOm7OTaUf2GmnDB9nyTjXtDdiOQ2wba5M20ettU5Xv81RyDpHtlp4ZJufNkQsUsCat803jrih4mc5eM8GWnfsgkBGo+N/ySDDsIcSBLeM83pL1eT0NEgrJTNqjAWWxgb3pCkCM8Gfq5xE9hmr2fKHOLJpV+u6x5F+D6PGWncjxPAxHC6oSqCYDapM7pB8/HoQv7kU6En6YXwlQZtCN9Muy8b+lFwIIzgSWvqm46cH7t2mP7hQyKgGVVSybrt6MzZafsQpcdXqJiKJPEx88Yw5fOHcdBPlbGI5kkv+AtwtSWltsaBKNKvvnMU0X+5A7UROgS/IUDKf/ABQCgESDGe4CYfIvRGhpVvp1tKyHe8yrxZJwbpOn5nqyMhgHbqTmTIZlWrjmYZWDHOjzxxCQOIOEUbbv2jQHlqc62KyxMr8mrzkwExgTm/slUCrNMFLaRn2p705qBM3BOBxEYLcAUKd/Kuc4ZvrLKN6qhhCSuLn8M7yh/2P9zzGTm9IPnIelKz5tmlG9/p92O08g6zPYwna2V+bwMK/UUgolO0GonQ745yjdOqcCi0QWaNsAuO2Uno96yU/a+6EPRt3TsPdrNPT9nfsq3sGmnAyjKNUmlFJh6FijuAW1SBTA6W7KNv5/8te8+r1ce6bLyzXvdve5oFe9+zVH8ziLPt6TKT4o6YCoeFkLyjTY2behLapgJIt92tcGDqkH4Bi6EVb5lvM+rQeR7ZvrvG7ig1Mr7WGhpfrK8hEwhU+x9lQP7PDGgwYKCcoDyLRKeb34BBS5QkgAs7/GnfYJMRAilgi7OtO7DFTSnOekvaz8PHwUccAWQqC2uvs4lvGBthhRQoDiJUqn+3wpAR/pGoSpWUWt9Q2LE/jcjTgu96qyDkKvnpwYA4+uab2QIGKbj+SYWLAj9yR2EVR4CmN/Pixti1EdMvsVoDWHJt0QKOO0NwJLjAMB3NUe4iq/LqX7zM8DuqsdWo1h1PbDqdnw08Sv8KvnvGEL9v+2LU/1ASY4yTb6s0at847zdYCvfZhjyzSy0X67eDJwpYQYhBxsNwoTC+yjqhc5FnVt82SlgP+jvs07Bs9ahok8BScbAOp3A+19zZNWjakrgmfQ+7ffIFntHvlnUnnR9WvsZ/i/5ObxZvS/0Z6VVvinhlW8DxCHf6pyDHpR4UypKO/X2FfPneUudB0gRr5/9je939lz55uO9FbbsdIAUeqYUFaI4WlVi03xz/omzRR1Y+8fAfU5RNrSkUm0EhiBwIalpSA2v4HdWfMpOufFD755VYuUb3+5Ljl/CbXOQSaqB5t5lEs5bqJ2wSVJRaVlI5dug93xmSBnFYm/CZZwqP3/PN36snRkcEX5XuiQf+bZyTxpvvRGYsbzXkFv51uu+ORTMEOSbogLJEc+2TDI8+RY2+bplQYAu9iiexgBwxCsDP/qqoxfj7MNs66ExjKBEvf2JvukhlMphPd/aT76ZFnxK0it9w9CRwLxTgdRC/sMAjlg8UN9PDQDGN7XY0mBUlW+cB2mFfKunfAuJBf1J/zTrGL6IybcYrSFE+d7ORacBl78bOP3N1W3uun83hFLYHqZ9UYG+RYOBd6u34DJ1lWe7MxnijkGW0llKYT792+rLA8g+vFZ9rO7HPvzY4SgV5SAQqcmuinqvo3GB/DmdTmOW8Zyhham2t60ZOKvW6SY939ZYB2GjJV6BA+xrkiOuynnA6EzAg6js1I1x1nvPgcAE+p8vOAKP/78LAfDKNwC4QH0G2R6SCRYF3qXdindqf8ZZylr8R+KHOFt5IdRnpZgsUMqTb1qQ5xtTdhpW+ZYfD36/AzBFx8YMKM8+zusPeTjZhbeVAsi3HpWVORB5iQECn1Qf9KOAnz+6tefBEVWMP14tSXE3SYOBD2n/h9v6PoH3qDfxJUAuzBYNYPUvAn8NAbqmfDMt0XWnAf0CckqofOPTTmkPlfNlIfnGTxv++QJ/WwG77NTH8w1AMd99ZZ9loTXlW/9y/jtn97ahZY3DrFzb3H1SJXd5QpEInrcAkJagwiHFelRBw6pdwJN7vfdwH+ag8i05DAyf4NnmN1cSgbVS8EWrpBVzLGWq4trye/BvA58C+sWklIN0QsX17zoLKz/6atzxoYvwND3S+9XbH0dZD1kJ0oG5oVj55uqrF5wJDBwMDBzu+x0L5s/zfa+KveHGis2ipnzzqdAKGjcILBH8ML8/iel6yjcJytllQ0y+xWgNISZW1BkEuFQVfg8UoRS2h8oxUzBH/krih/hY4pfcdsOl8vGgh+ShB0YJKvO3/HLif3x3X4px3Jb8CK5PfAG3Pz/a6daFQxPkjprsQ0FlyJtGy6U7hLCeb2WIH4ZlaPi88Te+n/M1+26H74fwFzauTATAETsOnGTkSYjfz5eNnplEl03gNYo3zfMDmj954/msBOQbhahUKcBMnUn4SxEdSehIsl5DLHqgfLMskRLEe2yLjjjN8/p4ZSuGiD8prRd7ax/ATgic5w0bRuKHwYpS8fHNHbr3GwVRaso31+Zrtd/hvdofcKy1CR9O/BpXqXf7fsVsUQe04AnnEMlDabXMKiRMgfINigb0C0Km/JRvzASalnq3eBc2cGHxoP85GExr3HPA83257vuvioIxnETDUEjzzzFran0bWtY4/MtOK75NIu8mn+dtxuj9uChJ+MR0ANhV8F5DfSRiyrcQ5BsyS7h+QWsg8TTsQkzL5ZqGV+X5DD0cN1nnIasNhyKwVYVg+UgGiwZT2GB5iWxzZg/n7eyLDgQuWJbA881tx5FZBsw/PdCiw0yEKMN88U67CqVD8AtccELqAq+VRpRvAyGUbz2wHpEdMfkWozWESM6hgk4q40O+6dA4GXIvPdPYFfMkdLxRfUi4rwGfTk2WjsdHKv4m9X5uWz8KeDT9PhyrbMd56gs4d9VHgVxzpUHtBDVYTzHvdTQBgbKKEOiadzuR5Jw4l1c9z7dZRawYM4kmVIU5MKCKH4yTa0O3sSHUUSZyqbMO0vPF2yt40jpSuH0ABV+frk4jpwMnKFs8204im0N9VpbJQkNpp4IJ5zBywYELQCij6XbDEpWdsmESB728tjAUAmaPfSI54+RK33fNhaeChpjw9FfKtD57y4vtb1wzSAzBSd92P2XfoHoN+N+aftT3K7IlA9Dql1qlre6MIUzLJ2VXpDQStLsvyYcT9JR8KxtQiXcMxPqsnnbQCJYO+0/kFg0Gn59eWEAIPd/cvk71kEjzhGKPgjFqaaeixQaf40mJyYFkufdBVKyNQbnyd2a9Ld3Kt4lcGfeuHZVbARei7BQqf6+s2R1+rJpHCjRM6XSrcyrDu1hcpva4QQUNfw/B7u/2MQuyNDsWPiGzA55vpp/nWyPfEYZ8A4AXbmroexuBbvqQb2HKTkM8Ux0s6E/5igOq6GFokKyIybcYrSHLx2dzEBi/Bkmpec+T3inHDNM78JwH/4eWf+CCHESP3yrLmwXk28WKNxp7ob4XeOH6niQXesA8lNlVeCG5U8rCZCY/SlmOEAxn4JyqU3Y6o4ll7BbROD87N0yqoIQkb8q+9s+NNTQsGGVimTk/vqlIAmLHjQesk3CL+XJu+2IyhVy5s5J2vzI9URViioQrlyibvZ8kUCFREDCIyvDX4DDJ1i87zXXfR8iilPNI444tNQhy0Fnhv7MHx+EGH7ig4F2nJ/DuVx0BEoZ8qyhFdkx2qOS8UVDTNv7WBqrsWwIGlhPvgt4Jpv9CwWzRCKUo6Te7098bliUI+tCAkYMBzUX+JtLAomO5z/clNc4fjfgsmnUDZZ1/LpmuacP5Ry3Cf/3VqYHfUa9sjvaEfOPTgxsqOwVQZNT0NN+b/sF5PPH9neZ/PD7PtJQE5Bu7mFOqJHiKAnLceOdPV+F133pQXgIuRD9lCRa/jlwSkCTJgEJBWQ3hN9Zy2an3b1+qkC8JTUUjtAIhBDltxLON5sZBw46POlDBIlQvk/CLdABAfcq6OXSw9NT0STsNlZIelHrPYDiTgFpPnSlJpZFMiMm3GM2DUqA0VX+35ACQXAAsrE10VIUgqYovPy4pZnJrK61sCWzk9TziTwT6evDIwvozD0wHZyn85GY5EZQTz+7jDPW7jjplpzMildfyU2ClvKScps9KEeRRTTutU3Y6m1gk/rySqKt8A4Ap9u+y+ubOPBAtscTdwbggjRYAkPAnEG0QvE//F5QZpeNiMoV8qbODbcOnrFWn4aX5LEoSpE5yJAHgJQhYqBpXrjSCEOTbTIgFmjZDmHaqCgbQh54X+jutXG9L71lly/x+BZ94Vb+dChxCKTAEm8SRxPENdkssQElW1RpLiFhJT9jJUAUi8q1w2tUoUO913Gd1ZwHMtASkjqLZZNupV9TKAF/2DiDJ93nphII88Y4fiFHq2aKXITA+NyvP3PdecASu+7uX4cD59fpu4COXHoM/mS8Tvkd6MDGzKIVK2POkoJEpUVH1TrDJ1merE95uwlf5pgaQbyMHCTcnJfB8Y58nDrHDBsu4004dbBzL4ebVuzrXuFYQpuxUsPj1V2ce2NCvKSohyLdWFWPcImuFfEukGyKwAcBIe0vylcJ4+HlGB4QNlAoCF0RjhwAQn7JuDiEqx5qFbgWnnQr91R00QL4pCsG8TD3lW0y+sYjJtxjNgxpcmZkQ804Ajr0WYKS4KZ/EUy4p5rYPN9nA1mEyg152tc2NAxfYBA9r7o9C9w3HhQhYQWcnqo4/kAeFKcDqTaJXFZynGLuqTvBtclXt5XGXAkPLMTTsNYFVqYErvvFnrNvVW/8jxxS1XuDCTHKRsCSBKgkx4ViBo1IwqEB9sIlXPLYMZlDGlZ36eb4l/Y/hmKW1gcx2utjz3mJMIVfqLCHMql8drNwmPmfnKs9hCYKvq7LITLLLUEWkWT2j3fSI5+VCMoNUXc+37huRW9THA4nFYa8O/6U9CI5wg50QWMRVVrbAJ0XYheHKwlF4B6EOg1r2f0qiqi491yewZAR2248jW/CP6s04jawDAMwUdW5Rycos4tTAGbM7Cy2mxQcUVCdup7wReMUF9n+nv034eUIIr3wD7VlokyEgDG685iQ89JEL8KFLjg79PYcv6sfXjbdgTLD4onTAt6keLCoIKGhQ+VZmlG9/pd2Hz/3s5nY0ryE4hB9/3SX9j+e0tws3pyQg31jlm3/ZqXgs+uOHwlk/dB1miFAtgfJtwUD4EkAAyJP6ZHinlG+aqog9BgNA+7xj82RpylZEh0FH0k5FqvnGyDc/T0UOHZwbmnXSTtulfAOA+QNJ/M4MWMiMyTcOMfkWo3lQKxz5lhT7PPn5vnGeBQNi1U83wM6R+4k/+ZQ1AIUAk2y6ZKfM7RtFgLnngcRbMjEAAVH3xG96PgGldZRvAPCrxBXA2a8EXnY2cMkXAADz5vOG17snCvj8n3rrfzSRt++feuTbnsyRQqUElARKSPA+iRU45JfQSL4Tq251yk59Pd8CyLdPXX5c9ee91Fv6uIhMIp/tbKmMH1Hm53V2Q/JLeDD1/sDkUy5woTgGjK0EjO5NsjUqIM3UOobN87wkzynKRq5kmj3nPQlcEBmqi/zsVpzJpwH74Jj1/uE03QBXIuw2iD/s3LqfX4BZABSkwclR50CBUg6493+Rue2/8VXtB3iF8pxwz0VkGpcoq3Br6uP4aOJXuDH1GVyoPIlsyQBl/IesRB+3ANZHu3NfGUKz7sr9kFoIJJP2fwn//k6kSKA9sq7Qy3wft2hkAAfMCzHBd2EgrWETXY7zSv+Fr+pv8byn6t23gLD8SssaIN8KSb4M/7Adf2i1aQ2Dukq2PVCT8J3iLeZLngEgrfe+7JQNXHCIHZYssD3f+IUxv0X9niOM8s3Hc/XCYxcLt4uQIyGIn7anndp9XFIFGqUVksPeJOikVQhfat8BP3BT6AfZGPmmpEOSbx2cGzqLxuw4yBEscCIXNxol3/qT+IbxZjxpHYlpVnwC2NYje+8Hctsa+t65DEl7qRiRQFjyLSG+yTNJMfl2t8V4iGR7V+7D+j0FKd+SqRTOOXwh72tVmOpAyxrD1vEcvvPnZ33f/6L2Y8/rAZHyDQDu+HQ7m9UwSB1Df3snBVhyIrDstCphNTjCk29DJIcHNk4jV+pdDPYB8+x7I1OHfNs8crbQJJmqSQDEV/3m/H1uMgWT8w6Y1bKR4nzggo/yLSCx8JwjFuLfrzwBADCKEc97i8kUcqXOJUYBNXUiiyDCNElMfETjE5EdlNhyrrGHgdkNwMTqZprYFITkWz2j3RXevvmN6gMe42sA2Gkx91oHSyv8YFqiwAXBxEZR8WfjjFDfOS+7qTP3TEiwpA4las1P9WXX1P18iujoR7Gh9LyOglrA038E9mwAMQ28Rbsfl6vicIXlZBw/SH7Ds+0a7U+gFDDK3vt/T573wRzoEvlmia67Kvm2AMgcaP+n+N9nosT3Yq43ygFd4PkmUmDXQ3/S/huUkMSz9HDPe4lekG9CU/XGyk6zAiuIgXL3x6r+gQtqcHrrIadxmzLliZ6lhwNAUiW88q1i78CSBRqxhM/geh6DPUML5NvHXismS0XYmg9xf7acduo9lqrnm4KGy06HFizjtmm53eE+XGq/HzilVGwd0AC0jM8iM4sOWhIZlbJTNsDEqYLJt6nsFLDVmTvoIryx/FmcXPofbBw42bvD1AZAnwEmn2noe+cyYvItRgsIR74Rn4m1n/Lt96x8VS+Ee3B1AKyHR38A+XbaIYsxkNIwyZJvPZbcZksGLv/2Q3h6k78XBuu1MwAfQuOFP3BJR12FyQ7M+IcicRQhigqo9iRswfAA5wN0d+rfcI7yPO5e2ztyd3ElCa6e51sxvViYmEcqJU0zotUm2OlXAPAb85X8m11QvrHKxHFRGi1Qt1ThjINtlcEoo3xbTKaQL3S2FNrP862eWvEUZRP8HLZK05tqfyvLsIm32fXA9AtAlyajqoh881koqeL4v/S8XESmcTDxlpXuot4ykl4ofykVeNr5DKAft44J/8V7n2+hVa2BJXUsxWVuPbAMOPsVdb9jKZnA4qE66sZuoLAHmNkGbHg81O4XKE9z22yvUoqZrHcCduv6EmYYH8whSKB8S44AWsb+T6CaciBKfM/N9GYMYYqe9Q1OzACgP1Ub67HPqpTRC/JN4OvkVpKGwNSi07ltpK53afvhPJ44wiAxEEyEnPm33KYFmMLGsd4FnPUnFY4scIgdkbftsOC+fnzzBD57ywu476XeenRyCFN2qojvrRUjIXzcKghUNDloc9lp1fNNRcPk28DIIhjU+xktH/LcGUVuwbdVmJaoJL0x8i3RFxwgVkUHF/OcuStLZhdhX2PZwLLTxvyMlwx6v2sMzPOtB76/siMm32I0j7DKNx81hd8K1SQVlAH1qHSTnXeLTF4dHLVsBINpDZNgyLdyPtzfqUP41ePbMFs0AtVVhyl7PK8HAsprMdtDQ1srhPINCjB8PDBykp2kB2Akk8SsIBX0vxLfwR+f2NiJloZC7QHpf26etI6EpmpAkpeya0n73pr2Ub4VaAoDKQ0v0EOx2jrM+2Yn7qk65BubThsWjnJilI54ti/GFL5w96hvImk7IDLRzqCITyeuq/tZv0l/ybAAJ1nOyAJbngCevR/Y9phNTHQBQvKtnqpl2SmA5h2YHa54V6l3UUb5lhvvev9nmgZUwpw3H9JgI10e/ovHX2qhVa2BKysjLmWLNgD01S91+a/Ef2N+f/NBIW3D+CpgxyOhdz9a2SHcvhhTmM1677Hn95Y45dsQyXe0j3BgBiUIJ+cBIyfb/2nBpc5s+4vTvSESDF1w3zZBvvUla/0++xzWqA7o3fWSpVREkjbm+XbIWa/jtqVpZ1XYItQ835j+QesLPp4DXga84o2eTcMkj2/d0bsFhr4EEdgY2PfPLPpgUe8i3YhPANr/PrwF7/jfVXhskyR+y0C4Z6AP6ZFOqDh+uXjhcjDtHVPNsoF1IrRKvjHjPI/yrUFaYaQ/zVn1aIUG+rs2l+SbQlVsY2rKoaGRcDt2UJihV8pOUz5l3EWkOEFCFQ328cuGveTbTpMh37IuW6Neh/ZJgph8i9ECaDjlW0LMsKd9vBmmMQCL9X3rQekSUJP0OwhSvs0fGcFQJsEr3wCg0DsvjTW77ZXlTABxyBKevso3ANhyC5Dd1Ja2NQwucEGgfFMIMP8UYMEZVdXBUEYTDkoWkRmcn97QkaaGgaOqClJR3Wi+AklNA9L84CuZtO8tVunhoIAUhitJRPdbp3jfzI3xH2gVXNppe0pAHOUES76dq76AnTMmrnukc4nIIvLt/drvcZm6qu5nl/mkN5ZNAGblHnv218DjtwEbnwEe+h2wQ1x6124I007reb4RAgwuDNxlM13q3UApsPmeBlvXIkSr4T7Kt910fvjvHV/fZINaB1tWRt1lZVoGUAiMOuUxJyhbQMsh/XQ6jenwQRwHEvFk7AAyxk0uykhw6qpB5LsScmIGeQ0SBTjwL4GD3lBX6TvBeGPqU2LysdMw2lx2CviotLvsaWcKPd/Uxsi3ZQtx/8BFnm39VvdVfJRSEFj8YoPiCmQRYfBI256DwY4d29vbwAaQSRAkiVj5ZkHBLKPqGqmjaP3K7Wvb28BWECpwwZ/0+NO/vAJHLeFJ+1MOHPG8Fi0ycyi0SPr4BC40U3baL6gWShQa8Ilts+8bFZFvDSrBRhbwJelmahB489e9G/VCxxYm/ZRvJdSuMV/1W6PKN4Z826EzcxW39ZLZ49A+SRCTbzGaB7VCPVCIn+ebj/LNgoIs+wDpmfKN8XwLUIQl0v0YSicwJVIh9TCoIKHaA/0ggmcYOY/J6KAocMHBRHe9qTywWGUVfw0REGDoaGCgZg4/nEn4Dkr6zd6VBZumbe6aZNQSvzBejXvMU/Al/W34hflqO0Wqj/eto5V7y0/5Nk37qyujrBdhdqoDaooQgRjNoD9lf88Y4/kGAF9PfA+fvtk/3KBVsIKZt6j34h+1W0J9dj4RDwxLBmrk28Pf9v6yZ3/bRCsbh0a9gzILSrgVz+EVgW9voUux2fKaKGOv2Ei/Y7BEpIH42P7hsrNg0pA+aJO9S9JjlW9UcRnEEwWgFIUDjqr7PfPKIf10OgVaec48+2Doj6wg4ufnAWQMSW5ywSdAD5E8CuWQCXpNwrJopdw5IClPCUfwsOSbMdsdNSwL02iP8s3t7yt8DnfZmkPo+dZg2imIhmMO9/pVDdCsr0dopyBMdgbqK/mUBDB8GFc9YMx0P53agaaKyIIaETDFLBL7Kd8cPLVtqm1taxmhyLfg8dIHLuIThgtls2pfAoALmxGiNFV/nyAwStVSRUFlT+ka8xTtT6qYYOxIEsUG5kvtVr6JiPkGPd+GFvJjpKnkYo48BgDaIU9wvdIPsfO+Iq3dT7eaZ4k/3GAfv5SxsthaCrBeisk3ADH5FqMVCMpOrQxPEPgp3/wCFwBB6WkElG9I9GE4o8GAxie+9GjwDAAJ1b7NM/BXvimEekrk5gUNaqY3ATNr2ta+RhAmcIEKfLaGMrwawoHa6kCkBRiW2DT4u+Zf4O/0D+MH5utBoSChESH5NjjfJjn8jm0cQ1XlG7u6OLmv/YNsNnlQSL7NP8D7+vDX1P3elGZfw6zyDQDeqD6IY0jnUpRqfQDFQWQvvpr4UejPzoNNvg0hi28lvo31qauxJX0V/mrnV4Ft99r9wiTT9rX3AVbnJ3Bs2amlqOEGmQv4CYAbRSSxjh7o3TjVOWWiCMQSqfrEA8o3vexQjLIeJRV8TX+zd8N4jxS/ECjfiOr1okkvxuBhy/Fw8gxstJbhv40r8MMVX+C+Z0jvcSkWNWsEXIs4kIwJDNo1bgI6hBxmi50N1jGq5X8+ZacNYJyxrqA9Cp1iPd8sKA1PRAEgqdWmGmUk+HKnLpNvVOT51mBpGRQNyX6vt9MIssiVOkvysrBEJbRAOKKXKChp3mttAZnGnuneTJCpBY5ML7vIAjaZeoh0Lx28ZYQqOw0mPc4/iled78uWMOAqPWVL1oVoOXChvco3dmFYaaQ0sc3KN1Po29lYH04EyrG7Jw/AmhmefBvb15m+3VG+8YtTtWvs+8YV4g+3WHa612TJN9c5snrj3y4bYvItRvOgFsCsjK7L8R2/4lt26j/Y4RJDe6R8Yxcxg9JOkRrAUIXo2MOWMu3rsvLDBWfgWy9Rc5DYarckdAyRAOXbsw8Ad/0vMN4DrzSrftmpaQrIt3TCd1CSKjYgcW8zTB/yrchMThKKAqT4cuYDjj4dQ2k+3c/BLroQI30V8o0ZuKaN9pf6UK4sWHCPn/Nu7+tT/7ru95JKmdZeKiZJTlQ6R4pYlCKDIm5IfBEPpP61oc86yrcvJn6CK9RHqn5QJxWfAW79MrDnSfEHN9/bUpvDgC07pUQLZzi+mC9VcqOIJHZQpuxiusulTKKJjo+qYCitCa+r/zNehWcp45M4vrkrxKgbC/qTOJ5sxjnqi943FM1LhBz0FmD4KLz8FYuw5oQrcPDpx+Dv//6fue8b1HvX3wGwxw1tmjCJlW9Jrj8cJjnMFDvrNeOQ9NzErY6ahcW/vPoITvlGCr0hTFnlGw2p3BPhn195SPVnTv3WwdQ/EUxKoZIWyTeiId3vVVgOkxz2znaXuBImOwPhyLf+A4GMl0BcRKaxfbI3penzrXEcq3ifFW7lGxu6MILehUM0BMsCrPqkLKlD8vQltepiqoNTDhzBYLq2LdsNzzc/8k2lTZBvKrbRxc23pc3kmzgJufEFhxtdwYEmJfih+Tr845+THuUZAMxOtv95TCmtLgb5eb4BwG4sgLWCqVIAgJnGfL0XD3mtCDjrpVIW2PcokN8ZK98qiMm3GM2DmpzH0zgzaAQClG8B5JssyjfWpLk/wDcN/YsxVHkIcpPPsd4oxQDg4AX2QDdTJ1FzqFJq6qh1AjE1Btz7RftnfRaYWRdqcNEyWHJHkHYq8vZJJ1Tkibg0M1Pu3WTUMKmYfIP3AZ1QCTByMLdf4pBz8Kd/eYUwCQwAttNFmNdnE3ksoT2CLF9T2SIok0rMkqP/fMHhwHFvAI4/EVi0BDjmJOA4b4KmH/7m5Qchiz5hieAACsiXO6NssShwpfowzlUbL22dh1kQWLhIEZBshWnghf8Tf3B7533fEqzyjVVS+WHRsYFvZ2kGO9jE0+kulzqKVs4VsVcVIYRfLAGQQxprrIO8G40SMLmlDQ0MD0opfpD8Bv+GonpX5BefCxz9PqhDR+Ly5Vtx+QkLoCoEUwtP8nysr+fkmwnk26N0Opjs5Ur2S9C48cMIsl1TvnFESIP+OVeffQgmGOWbVuyNZ6zFPG9pA2mgLD5w0VH4wqssHD2f8krtDqb+iSBUizU6wVYSSPfx19lHf/tMi61rDMJSZ6DSl9eZ4o2cjL4FXiX6Qszg0394ASWjuwo+APhg8bvctpJrDMHaa9QrO5UGZji1j0gxxeKCo2tzC1UheO+rj8Rgyh1oEoZ8a5Gw4tJO7d/frPJtnXVA/R390Oa+w6IQEPONk29f0t+GW82X4QXrYHzE+AdsoAdgokg4S4TCbPvntm6fYjbApMTMLch83p8O/YJtAUhpKhb01/5GHPlGKTD5IjD5VEy+VdAeQ54Y+ycM/oGSFxg4kqQP6RFEvjEqnd4p3xjPNz/lG1GA1ACG++yObjtLvk31zivIoSrSAWWngL1qCwosJCEfZs//FnjTj4HpNUBxr53aOP+01hpbB4TzFOOvobIhVqZMWhnhWLSv3JtrCwBMy0RaQIoW4VW+aaoCHPEaeyLnTIgOPRfom48D+4CSKk463EyX4pJ++7tYv5QEMUGL0yCZkdYPxAGrTKQafnGlhUd2ECxfvAxvPe9owCoCy1bY/ykJ25smBD79+uNx1JJB3PfEm/Ca8d943ltMprBnuojDFgWnCDYDSileraxu6rPzyazQFL6KUR/16OiL4u1thMYohiwlpPJt/uG+b2VpGuvpCiyhDFkwu8cegNUxmm8HhGUjAKD5l1KM0WFu2ywyGMMIxukgFri9+/asBhYcxu3fKcynkziA8ISZXXbKTNb6lgPzTgMGjrBVLQDI8EHAvmeruwzp4zBMy+5TegFqtW74XcFhCk/qlpDgEsfnkSw2dph8cxTXrZYsLRpMYeGCBYDrT5TokTUCNXSvhVPIvloEVdXw1ycAxyygmLmFJd+67PlmCcpOGyUWiQKSYUhSYmH99u4uNFiikA8gXHorISCD3oCcBWQaL+6ewa9XbcfVZx/SvobWQ3EaZ1jPcpvdZXLsGGZeHeWbX0Jo1yGYK4lAtfphJp+8/DhkkhpGZ4q45vzDcMTiAQy4ybcwnm/lXGvPY4ZMdDzfbCehxsm3l+hB9Xf0Q5v9tMWeb41bB4xhHt6jX8ttn6b9WEymqq9L2farmg3XvDXNjPPcVTUKAcjiAwAwCccneFOQw2DJYArjOfsZy83fAUDXAX06Jt8qiJVvMZqHwSdiFsBPcJQ0P7EBgj3fpljmvEdpoWzQoa/n28Wft9+vpHpxyrcemtg6x1Cv7NRRvl0oUukEobjXfpDndzbTvIZAGHLHEKwf+KXacddUBYNG75JoDYty50WnKndcCZUAg0uB130GWHoIcOhJwBt/Un2/qPHH9u/6X4NCwbxK2SmrpgAAfba9D35e+abiwCHggy+neNupI1AU4k3UbEB5l1AVvP3sQ/CaN/4N996iDvrUWBRNe8q9U/szbkl+wn+HabG8f2J35z3SVOqdsFlhy04Hl/lO6r5o/DUKSGM7W0aSnwKmtzTX0Aahm5ZPGZb/AFrkJWhPYgjWsuq3PfwEsZNgyyodED+PvpETgNR8O3QGgLbgUM/bi8kkpgqdLcEMBDXbRr4tJXzfXaYJbpI+jBxmC50d9JuVvixBWlRUAVD6vWXQKaP7KZoAYLLl22GUsX6oTPSHU3w6t9kh03E/0HYo3wAgPcJtGiZZrmKik/An30KWCA94QyNWVIj+T/6hcyFGQvhcA2VXdcM4Y8y/kAT3I6Kk8p4gTNgCABKiRH3BQApfesOJ+PE7zsTLD7N9gAddnm+sL54QlgmUW1AN6gz5VlFTDafQMKHXl1CxkS6rv6Mfcu2dWwnvp2b6Bh+wlgh6B5RvRkjlm0Jgj/le4fJdPvRk4IgLG/6dS1yhC0WkeF/PlQ8CTz4OzPQmuVs2xORbjOZh8INZkfG7khY/DII837iy024r38wSML0GlCmr5dJO+4aAc98KvPw99ssKociRb9keljZWOuJMUMksHPNain9N/C78l5eyQGEXMPEEoHehdISZDIhk+kVdTL5toMuF24et3pFvpmlxD0dW9QbUQjNw/FXAxR8EXvNvwEBtxVpP8PfYY5ZdHuiUnRaQQonxmzBy7b0uTZ0vO1WdsViiQsITAqQqPhOpxuTtAIDMfBRP9JaqLsIU9sx0ZnJtWhR7fQz5w2AkyBQ6J+7X8hOdD2jhPN/CBi6oGjDAn7f3mv+KX5j2IG4TXYYsZVTQWx5ouq2NQDct8WQ0wEQ4M5/vG7KV8p217Kr86NqW2tco2FRaB1TVAAHpjsEjgGWXAH124lp6njd5bTGZwg2PbqumoXUfFpDrnIdZCQlu/KAQitJMZ8cQRsULkE2lbbTsFACQ8fY3WisT5SZhWpQPLmlB+eZgKMWXxpWy3X0Gm5RCZYOZGvV8A4DUAFeKO4IsNo51LwjAohQaS/gClb48xPla5A3QOYr0aHLsE0jw8fNrz6QxZpFkUR3ybe2eWTkIuJDKt2aShAF4Ahe4kj8/tKIY8/F8m5cBGqUVNFVBESnkaH3VHwCss5gk0Xx7x7CWRaG0wfPtNUeJRSesRYzVZuUeUFNhK7AEtgy155FhAVCSQCoJvO7twIWXAi+7smGfUgA4ZKH3mSta7MfkBPDQDxr+7rmImHyL0Tx0frJ7h3WG5/VL1gFQfQY17tUaFtzqTQc6qEDMvATMboBZ8CbRDLIE1sv/BjjxbdXVnr6Ufaxc2Wl+NlzaUQdgViYFYZRvgWmuIux8Erj9m8At3wUe/CFghFvhaxas8o028FA89LRXY1ZgRjuPTrXd+ywsTItyZaes3xuAWolYaj6w4nXAsos974+rvGHtbroA33jryVXyDSDcA9FsMym8a8I7STSgQl18NjD/dCDt8gFbcTkwdDywtPEVNqgppOd576/FpHPkm70SWr9kbXrRycD517Tldy7GRMeN/VlSx1a+hRwSLDyS2/TGM2rnt4wEnraO8O4w9lLDbWwGhkk5AoQSJZA4uPBlJ3Hbyqr9DNpCGUPi2cbMiFtFwqffJooqnqwR4tmuDnlVBYsxhW/ctQ5/99NVbW1naFimHVxRB836i5UFZacAYHSgvMcN0y/tVA03qXQjMehNtp5HsoDZ2bJZFkXd7IgCZEigfDNyUy1/byOwqKg8uIljUxIgKe+xzCNZ7Mt2L9HPogLCF6iUnYYJ0DnO8/JgstdXbdtR+KjDDp5XOy+sQvmQVP0F37O+eDfW7+WVo5TS7ikUQyvfmiDqAU/ggrDkD5XnuxutLICwZacO+ZZG04EsIr9wEV6kjPdxuxeQRR6KTZCi/3juCiiEv75Y5RvtgOpXr4wd2YV9gPd8w8jxAKhdEgr4euPWw1mHeZ9ZrPq8io0rm/r+uYaYfIvRPARlp49Yx+N+057IFGgSXzbe5jvnYVN73OBu3G6nfRXsEkqLCRFYlGCOeeRYYNHZ1Ze+ZaegwEQP0kFRS2yt5/k2RHJICQZdBg3oJm79ADC+y0693bQaWH1dCy2tD5Z8Mxsog3nL+afi3/Eu7nhS0NuemBQWorTTkkD5llRdUv7UAm/pJoD7J0Zwp1nz27vDPB3jGMaVp6zAvH5/zxSzzRPSyVlvSpoODcND82wvKjcWnAGsuAxYcn7jv0RNA30jnk0LyRT2jHdG2UIpMIL6SoahhcuA4SPq7hcGSWICu+4Fxh4JbdbcKHjlWwOTz0PO4Tadf/QQVKV2nW5mS0m61P/plkD5pqgIGu4cdTh/3j5/ta3i45JQZ3YAxVFu/04h5aN8IwmxlyoHxtNpCZkEQPHg+n3YMNoLw3ILNATZQgebK0U684hlKCHJlb1YHVbPm36BC02QOiuWCZSYU921rigZgvuoCUUEi7QG5BTvBNTocmUDFSYaNkH2KhqQ9hK98zGDyVxnFyHdsIRpp8Qm3sIQIQu8Hp4asbAIUwBqBNUfVu/El25dgye3dlCh6ENQzRuozRNY5duwOYnFA8HEyL5sCd+7v/bsGZst4U3fW4lDP3YrrrnuCeRKXSC1QyjfdKpCaeYaBNDvsvARWbEAQI5VSbekfGM93+xzNL8F8m0C9cm3PXQeXrAO8W5s89zQVr6xqtjG+70zD52Hn19BoSne72KVbyQ/ygUXtgrnWSSazxXZctChY4GF5wBW5ZwOHc19JgwuOm4p/u7k2rGyAW8eCLiD/Q0x+RajeejeG8igCnRoeKf+YVxc+grOL30T91qnQvNh34LINz5woculgZUVQ1axnrSYTmP4SA8R4oRITKOfV1lte6jtzQwDR/mWJMEd/DDE5NtHjQA1z74N3td3f67h9jUEhnyzGngoHrF4AJ94xyvwwyM+y7+ZG2u1ZU3BEJBv3MMR8L2HHLz2xGV4j34tri2/Bx/S34336O/HX568CISQqucbwD8QrTaXfw1o3klAGZq4vDw1H1hwJpBowhBZzQBMSMQCzGJ0ojOl3RaloVLVyKl/Dyw6tW2/l469CJT2Abnm/ObqQeXSThtYdT/s1d7X6SGoy87CBy8+qrppM/WSPpjY0mALm4NhCjxbiBqsAll4NOAOBkoNou8gm8zmklBzUzYp2iUk/FQoYfs+hnzLkDIGYT/HNoz2YNGBWrDKIVSqw40n4JmU4IJjbdKOHUPQDqvn/ZVvjasmTj5iBbdtdl93jfxFyjfSJDlQxZJXAoOHw2T6fTPX3fGdJVK3NKXqU4CMt7xsIZnGzqnuTS4tKvCFVBO2AjYMEZIegcH0/Y4hfK5s4hePb8P7f7UaP3hgE97yg0fw5NYOEaU+lSFqIo3DFtp9MxuMo1g67nrvKXW/+sanan7Ev3x8G56okIh3rRnFn57rwn0VYgHNgNp0/oFfyJgbWcKSby2Ml1jyraKmGkmj8eASAP92ydF1lW8lmsCH9H/EBLtfm+eGpsjzrZlyYKLh3AOB567xTiLZtFPNyAGl9s4/HEsJ0XyOU771HwAMHAYsu9T+L9PcopeqEHzqFRTHLrSPN9B7cLozY9ooISbfYjQPw6tycW5qCwrW0QMxhhEA/tU+wco35kFRnOp4GZYHFUWVl3yjSLPkW4rxllFIhYAjeMpiSrO29IZ8M3xWQSYYFdQQySMlSN68xTwb95onh/tlbTLS9gMxBaVyDWBoYACXnriU85fQHWJgZh2w527u2u4UTIvy5JvI800L7qqvecVh0KHhJus8/NZ8JQxo+Ksz7MnrfJfyjSO120w6phh/idNWNCdhD4TaBwwu9GxSCAWZ7swg2jKNahgJi3Gnnzr8HODwVwN9C4T7NYPS5DZg5kXbU7EDaEn5tvxU4BCnVJMAr/kYMHw0FvbXzjenfJvqjpeQXXYqUL4FTQqSfcBFHwUG5gGD84FLP1Xt2znyjZpAoQv+lk7TqE/ZaUB6qwcDS7lNiytBBYleJJ5Ssy75VqIJkIVHBe4jQg5pvPXMgzDSl+DGEEqxswSPUVW+MYtcYc+TC319/ZhiFBKFie1Nt60Z2OSbd8wVxhA+EIkhYPg4gA3hKk619r0NwhT6OjVBLCaHgYyXDFhEZvD5P61poXWNgVIqJt+AcOQbIchqI55Niyrk20xBx60ucsq0KL5zD7Pg2i74lWZqKfzdeXZozD7wPlpDemNk4H/euc7z+sO/7UKATgg7Fh0alCbZt6DwOgcbCgxp1Wy5pmVxSq0SEkgqFINJNEW+LRxIBpJvPzcuxMmlH+Ih60R+DNvmMD6LivqGJsqBK3+HTAL4r9fVjo3t19NGFjDbS9ZXlW9ERL7VnkevO3EZMHy8/SK10P7Paq3SYrDy9YHKt+nuPstkREy+xWgeZW8pFseoV6D6PFAOX+zPjHOBC9QCSl2Moxco3y5QVvP7JfljcEIXHrW8XhoY79CgpQ6sykEkmUnBPmYV8SSyiSPoLEpQQgJ3W6chNMKayzYBtuzUavShSFT0pzPcsZfHNwFGzvb6M/LArGuAltsOTD5jX4NthmFaSDMPSFFicEIJHpSdetA8/OTNS3DmMooTF1Hc89cWzjrCJj+G3H4g7AOxzWa1ClMit3g47bNnC1AzQLIPZSZkIlPYY/tJtRmkPMt5d7y3/D4cWrweb0x+F/jrbwKv/5pdktU3X/wlTaA8uhHQs8BUZ1LnNFb51si9pCSBc/8GuPBq4HXXAMe9HoCX6OW80kpZ30S7dkK3LCRYlW+YMIljLgcufgdw8d8BR11S3TyOIViUuf8K0x0rB2bBnicHVAtJbCfSKGvee8VRtkz3IvWUWkA5eLJRggby/9k773g5qvr9v2dm+93bS25yU256JR1CQgihJiE0KdIRQQEFFUERUfwBKqigiIhKUSmi9N5CSSABEhLSQ3pvt/e7fXfm98fZvbszs3vr7k2+ep/Xa1/JnTk7O7szc87nPOf5PJ/yE7p8aKszG6dN4ZXvzDLFEEogs+SbGGc1c7XTbqgmJNlKo6SfjAYbM19NPBH+kGoi6HusfItCMdgGSMHeVWCKIgWG8bw7lVzdw0zkW6wCZ3VLZqvrxhDRNHNWQxtJ2rkpnseqH7cS+4fPduoVo0u2ZShLIBX55sjhiuOH8OZNs3nkqllohgVvWqsozclAnJFOdGKsCPaAfFs4sT+JIeKz4VN1+/8TPtmc1unppnVCku8SwMqA7Kj1dTfSTrPslnbTTvdp/fAjxjtTDJvmBX9VTVO104T3nDs+fs8a5x5Z4Sa0UHrtH2LKN+PCPsDlEy1YZI0R+XDzaSMFsVh0fLyBM3lhuk6h+ATsdpHx1Zis4EIMfeRbH/nWhx7AUIHLS/IBUElBHCSSAkYkNQ3tTV+Q6CAYSZhz/9Tyb3M7u3nAiBVd2G1UfjT3btpIDKlW5Bsk/SAwXK5oC7piEISqxAuRubwRmUmnUJu5aoCmggtdDZglCy6beQU1VL8HKhcnHDghMK9eBrUrwZt+5U51a6hzaaedUKicMjKHFy/QePNijWGDR7Tdw3LC82d8rqTWirT6TRhN/OVuqD46hKyAbCWUpS8y4fLX4POl38NKSaKY+VCdioZMtkMGZ1F8tdeR12Hw6dc6R3JJtQegpSFuhJtmWIxEe1fIN0kGWz5k54PNIQhRoDDBf+eQVmwmrer0qoNMQKSdJiHfOlqRt7ggbyLkThDkYhQRFOqMgaSvCUK9QxjYUhRcUG2drGoHhF2GAiWIe/qWF9azfFcv+6lGfKih9pUgAWww7jwoGNSlQzuyxHg8rNjNoAF68tcWaOzSsbqKYKoqu3I3+kDZQoshTSzUnPkKyIkIhCOmKppSdxQgSWDN0vsoWmPPUqAOIpknrTSNtFQ0RHFAwVjdpiJEf73hQO8sFqdMO4VOEyGKQUmeqHzrNSQh3yKyDSxibDlmYC6njeuHlGXwU26p4rb5cZ+qQppYIH/BDcob3G75D+MlUdwlompti3NO/Li6WlysJ+iE8i2CTAdrrCnRP9fJzxeOIydaxO7JyLw225tGLYt/RU43K5G6S76Fzb9bQLNR6KRbqjcQ5FttO8q3SAJVYaqiGQlCMH2ZKpGIhmIslNCttFNF9/8TR4pnrM4w98jTmjhYn964NRhO4fkmW/jFHNjxHY0Pr1QY2S/6WzqKhSVA0fHgNCvlOw17AYFoQYl2lW+9XLTqaEQf+daH7qNFbwDcmqSSJIDUzmrOyBTqNx/2NhPP+Mbe8QWpbvTw/PpWNtUkFsHUGCUnWXk2rsIR932rNBp1exuOSFXNiBZTvuk7YkdBP1PbebK+Al5MzRjEyvdD3+MPoQs7/sCVj3XzTDuGpBrVOl0cFGULWVZBDCQiWLlFyOk3L4LP/wHV0cqMagSat4B3P3j29eTUk+JQU8hUCCNp2qnSiagscfKQwkvNuGooe2ugaVPHx+4klN4g3wCKZ2HJ0ZNvg6VqFv7ly7R/lGRIiQpolrZr1Cbsi/32sgxOw3NvwHpteLv7Y8iu3Q4fPgMf/CMj1Z4tmn5irXV1Ym0vgqyhkDOmLTgtTEg7DWHhMIY03F4g30IR1ZR2KnWGfJOt0Zelre2kgSJQrjUYffPe78DfO4tB1hQFFyJ2cwpWKqgGorpMit9Pd7+ZGWVlSgSbk3rRJCKADawOuOxJGHt8u20TISUUadAc+ufQHmrsyll2GYGwmrzqZHcqGMo2PIq+D9fSXNWvI3gC5rTTdBRcAHBm65VW9ogH1V/PZ2s+Z+2Gj9PyGe0hoiYruNDN7+bWx1Ex5VtvVTxVNQ278b7rIvlWVKL/DrGCC72qjE1Cvu0depb5uhg8LGmt4tzJZdx82khOKAnylv1n/NX2ELdbn+MGy5u8bruTqdJ2nli2GyJeLlEWs85+PWvt13G58mEGv1ACDGqxkGYei5wE250rdYRrZg9lw13zuHpWOTu0gcwJPMiVwds5LfAAX2nlZjKktZtkfpLMlgDWHlU6ddst7ZI1YRRKs8U9bVK+QfeJxCRQ1ST3fLfIN1n3/2tnD8UiSyblWz6t1Naml4wKtnm+GZ6paL8gFIqGe9CaI0i4HmLlHhEXmbLXEtFyZIQoRxP6yLc+dB+7lun+bDIYSXYGty8Yk2KPlKToQuYnO/WeIAsfXspPPtI463mZj/aKwbCQFB4/SVJ/7BbRqVUbyTc10rvqvSgiUfmeMTUhNPQUU9uRBoLRmEq8QtWv8ibFnqVdPMPOQzakYGmypWsmtZIFWYJqu97MW244AGtfhc+fgc2L4eWbobVaqPiWvQgfPgmb3+7x+SfCHxIEgcPgs5es2mmnvJkSVYAGUrLInVyyLwdbRFptTxBqhqol4NlnSpGTrRlKB7HmYO8/QbfpOsvb7Knzpr16mRzQP/uiVLy46XKzskXAklUeb9AB+bZK7WI1qaZqWPFI197TCZg837qqIrW4xHe35kDUsLvQUHnugKonfXqj4mlY1cwkiGLpBPmWcO6yeF5+fpawDjAafQPw6e8zkuZsRDLl20p1NBFHF/wF88t1f95mfb5tgr21soVmfy9Osn0dj4FtXbqrP8y4rvPHTlDFSFl6NY870tj543QDgZCZ9AVA6YbvpWzDZ1hAkdNsEdARWgOhJArS9JBvufn6e9ehBRh11zIuf13ma89H+OMH29LyOamgahpKWgoukJJ8q/f2TsXTpJ5vbQspnZviWXL0WRqxDIj6Xqzamox8Ozz4NHO/bfi9aa1CkSVuPm0Uz45ZTn9J379YJJUbLG9y37tbad35Ib+xPoFdCmGXwtxheZYseqE4hoGwMvmIAm583Va+JeL0ceL3aSCHZerEtiwPo+KK1m5WT06mfMNKfg+UbwPynO2mnYZRWH7H6Tx9zXE04zJVsqZxT7c+NxkikTSplxNhcTN3dAlLbzuZ2y6YrT+0pHHzW760CjNiBThMnm+JiyfdJEo7wjFlsfutnQIaLb2r4j4a0Ue+9aHbCDTqH6C9atflqnNHl3DpcYPbfNISYWLOOxG09xTPrzpAjcfs7WVMxwRg9JlJjxHz+qhJYg7b7dWmHiCsJle+yc586D9Ct224pF+BMaoPN2jDOv7ApoqMFccwKt8isrVrfh9RgqE1S19NLr9ltyDfYgj5Yc1T8N5PobYCWpph6WPQlL7U05gvgxMj+WZWSnSdfNMf40+XTgagwSDZb0v3qVzc/cG/aXPUm2xj76SdxpDEkP1CZSl7aj1JGncfkiHY9CcU68jJyRdS/cSJWwdFFzyakxuD3+/aSWx4oWvtOwFT2mlXFTqOBGIt+v2N/fh+zUC+NaQvSE6FcCSJAkm2dOzppDhFO8UOUY+04ihpnbQv//I5aFyXhjNuH8mUb98O3orUheBZKR5p2vYn65/b/l/V1HspWKq/43S8LCk6IXb2h5yhMCzB8qBgKEy/MvkbBx7b9l/ZQCjkZJh823ioMXnaaTdVEwGbwZe0pYF739nCU5/vJRzJfPGpZn84SeGS9KSd5heYFRaXKEt4yXYXf7I+zIuffImWwSyB5Mq3bvrZGcigQpqRUGnoJeIqopr9fLuqfCNHvxgZi3dvf2VjD8+uCzAU09qklgsPNGO/nW2wc0kkkVY+mvTQZyirAbC+8j3d9iwpwER5d/fOtysI6wm+5mhqXiJkSeu251siZg0v5K7TixmWp39+KoyEX0t3yTez8i2IlRLzV+o0yvKcyRe4Yh+JgiRJWBQJkKgyChvSWD1TiyRTL3czji08DrKGQNZgQJCMp0wdR8Rgx7FQXYbXn77U2Rj5ZvJ8S4zHM0S+XT2rHEhOMLehu/fefxH6yLcuwuPx6IKCYDCIx+MhEAiY2nk8HtQEEiIUCuHxePD7/d1u6/V68Xg8OnY+HA7j8Xjw+Xzdbuvz+fB4PITD8Y4nEomkbLtm1yG0xjhRE1E13vBPQg3pz1cLi98nFIoPrLHjer1eFFnivvOPYfM983n88omoQX9b59eoZaNqGp6geCWmXgUCATweD8FgvHNRVbXtt0xEsraaprW1Tbye76zbHz2HkK5tXqgaT1DTX/szfpP02k8udaIG/YQ0uc3HIBgR3yFQqx8kenrtO9N2zX6RriurITxBDV9IfAfZ5oKS4fhC4twiqkaRJFQ+YVVsawrpAx9vCDxBrY3QA3HtPUENb/S4qCHwVLd7T3m9+oHG7/eb7pNk11NWQ/jD4vNCEQ1kK/eefwyapqIG/ahBP98/JU4omq69bEHTNHzOEnFPRaEQIRA9bjBm9LfjfbRdH7fdf1okDKufBDp+7jvTRzQ1tzIktIdrlbiiLhTRCGoymsEjJOj3dnyfRCdGXl8Ajy+ku0+OG5LHG9dPozaoDyJCnlY8Hh+RQDOEhe9El/uIVi8+XwC0uOIodk8l+oh15dp3qu3wU9CQdH3EQvkLlu4QhtDp6iN8rc2669kcsbb1ETnRis26/sQZDzranvtw/P2tONgaKBK/T+J9kqQtiOfN09Kc9j5CDfjbnnsQaacdXXvdWIILj9cvrr0cS2eQUEMB8fuokTbyra2PqNqb9LjGe8rv93e7jwhGVOSIP95HAChWVE1q/9qHVeh3CvQ7GU2S8Xg8SNF0oZpo2qmpj/AcSjmWpKOP8Hg8aEGv7j75KDiBhqCFUoPQvL2xRMsbqmvrDWlMjHxFiSrUVPWeYK/FESGPGGNifYQvEg9DY/eJFIoeV5KhYCr+eQ/gOeY8QhMWwmXPwIzriBSN0I87FgdM/HrbfaIlqOBUTSMrWM/eSv0CXjrjiH11njbyLfYsByNa24Snq/dJC25dH6H6mnl0yTbufGk1972tJ0UyEUe0+sNEQvo+AtnStT4iRduSokJTHHG38g/Ghrdxmvo5P5GewRdVhqc7joio4nMj4bC+j5Ct3bv2sp40UCNh3ME6apq85rYZ6CO8Hg+E9H1ECBmP148/oCe0Ut4nlhL8CeNOsdSEGvK39eNt30MVlYoz0ke0trTFpuI7WAgGw3h8IX1bVz/9cx9V0fj9hj4ffWwqoWKPLjYmxpBjJBGTd+Xad/k+aWnUzR+CWPV9RBQSXR8fkl3Piya4efeiIKcPj8dfBwNZ+pjD20goGld2qY9o1S+eNAVlwsEgA93hNq/k7vQR/cvK9W2j40NY1Th2mOjLZTTUoJ99Ib2qyle9J219hJpAvrXdJ6qctG0ikl57Rwke23A83oTfQVaoCLt11/426/Pc9sTbaesjWn3iO8fsHWLxsZpAZIfCWtJr39Ox5Oxj+qEG/VQG9QGKN2GeiacWNJVwOIzfb+5PuspH9OTa93ROCsmvfUfoI9+6iAEDBlBbG5f/33///bjdbm666SZdu5KSEtxuN/v3x8mWRx55BLfbzbXXXqtrW15ejtvtZsuWeHnyJ598ErfbzSWXXKJrO27cONxuN2vWrGnb9vzzz+N2uznnnHN0bY899ljcbjfLlsXTQ9966y3cbjennXaaru2cOXNwu90sWrSobdvixYtxu93MnKk32l+wYAHTRgzkza3xG23FwQj//v0vqfinYWVp2UO43W6effbZtm0bN27E7XYzcqR+Nf53t3+PAw9eSOv69wBhDr+rXsV9Xwtlf2jR5fVff/31uN1uHnroobZtFRUVuN1u8vLydMe95ZZbcLvd3HvvvW3bmpqacLvduN1u3UO7Z9HfOfDghTQufSZ+ADXCc7+/G/d9LTTF+r+CQdz7p3/gdru55ZZbdJ/39+vncuDBC4m01rdN2h5aEcR9XwvX336vrm1ZWRlut5tdu+LpWI899hhut5srr9Sv7o8cORK3283GjfHA+9lnn8XtdnPBBRfo2k6aNAm3282KFSvYcFAMlu9u9eK+r4UFz4pOxmpzQHZ/Zv7dg/u+FhbviXegi3aGcd/XwqVP6cnC6ud/jvu+Ft7aHv/Nlh2Scd/XwrGPJ3RILRWcc845uN1unn/++bbNa9aswe12M26cvhLsJZdcgtvt5sknn2zbtmXLFtxuN+Xl5WKDqqJoYa59w4f7vhYeWRUkLNuZM7KYr49xcuDBC6l45Aq+eUJ8onnTTTfhdru5//77xQbFSW19M3d850bc9+kN03/yYQD3fS3c/XF8kPOGwH1fC+77WvCGgIa9ANx999243W5+8pOf6I6Rn5+P2+3uVB8xauhAlv7he+xvig+ej6wKctmv36T23Yd0bedOn9BxH2ERg924U27EnVdi6iMmDevP+ree1h33+MebcI+5mGUrN7cZyHe5jxh6KjPPuw0Aa3SwX/CsuNc+XbG+re2KFStwu91MmjRJd9wLLrig033ElVdeidvt5rHHHoOcMqQBY3V9xCj5AL97bxuhiJq2PmLaOdcTThBJPLCktq2PyI2Sb+FwuK0/aVLi6W73LhP31C2L4kFLnZbD4j/eivu+Fipa4te+rY94Sx/glP2hBfcvDqS9j/jJI2/ivq+FFQfFc6/KVl599VXcbjcLFizQtZ05cyZut5vFi+NFSRZ9shr36K8z59Jf69r6X7+LAw9eiG/nSg5Eybdl+yOij7h7ua5tsj5i7dq1XHLJJab7pFN9BKLgwgdvv9vWRwAgK+w/cAi3201JiV6Np+sjFDvIVmpra8VxSwuRpXiFMlMf4W3A29LYdu0TA7hUfUSsbWfjiF8+8ISuj3jpy2oOPHghf/nNL3Vt24sjLrvjb7q24x5pxX1fC1nVawFo9IV6LY4I+UQ/E+sjntsaVwGsOCjuk+l/00/wLrj6FtwXPs2z+0tEamnuIDaOuBL3fS2M/GsQyibAgp9BVlFbH/Hih/H+b1e9yrjf7mbCSD0Jmc44otBpabN2+NlH4j752UdxYlrXRzTFv9+9996bNI649Md/1fURxTTS/OUbHHjwQn77s1t1hTLaiyOuvvpq3XE720e0+MP8+YmXdH0EiqVrfcSiRbjdbubMmaNre+XFF5rjiFgf8biHc5TltEZTodMdR8RUIXe+edDcR+zf33EfEUWsj3AP1vdTP/kwwKYHv8mS/8StArxeb8b6iItPmsAfHvizPo5YWod79Ne59gb9PZWyj5h+EZe8FJ/UFtHE4Se+y4EHLyRYFb+nPFuWcuDBCzn77Az0EbOvY+bfExZRsHDrj3+De9AsXn01npWwYncz7vtamPS3aNtmkY1wwfnn476vhWc3xifLG6tFbDDy4VbKpPhveeWrIoZ8bHWI0ZKw3di1axdut5uyMn1WRFr6iDk34b6vpS2OCGLR9xFRRCJd6yPy8vJwu91UVMQ9tB566CHcpeO5/vZHKHHG52iLHxGx+676WDCj8djDv+96HPEt/TlMe7SFAw9eyKGd2yCqJu1OH/HWH39CkxaXz532jLetj5g7RqgdN63+ggMPXsiVT+iLup1z29/T10ckpD+3zTX+ES+2160+wq3P4vrtp+a5xoQDz6etj3jonp8CcfKt5AExh9mf4KDyyD9ew+1OPx/x4osvcODBC9n98gO6tsc+LuaZy/ZHhP952MPbb7/NJZdcwvz583Vtu8pHuN1ufR+R7rlGFB31EX/961/pLPrItz5kDHNHFzO4oPNa5BynXmXVaEw7bc28SaMcdZuR0HDTjgzYlUdnzMaqjUbdwd6pkGeGZkohUWxOU7qBESrtf0dVtsIJ15h3ZCKn3yDdB5CsThRZ4saThdrNZpHJz2pHIm7L79R1A6Bup3mbITXiqILFBYXT2/Wn0KR20obCPay4pKomg+6Mpp0qDph5lW7TAKkeBwHW7m/M2MeGiacnxcg3HXJSl2rXFBsrO+ObmAxpvvckQ1pXl6qd6g6k77eHFsf7bVPaqRqGZGkdaURYVZExViuzdDutrDjbTmOy6tsADYeE52EvwmEV303pSoqSLfk4XIgYj5q8vdevqX79GOhNSONOCaOXkOKK9+O2LFhwOwyZoWtizzKnMWnG+yKNCEVUs0cagDV5IaquIuYlFsOlj69o8w3NBFoDIfPonybPt87A15g+E/VEBMLiNzP1ET1JqbWZr/HeOi+tafYfTYpkt7Qcndp1M43RKkWSp1BHEVEz9xzFENKU5OfvMqQceqqFZYahqIERp8urk24fIx/oFe/ORLSkKE4np8P0LQGXT4hfJy1ZLN8JCwDCvjZFG2D6rWJ7XDb07bqBfZq5CBxAca4Yf2N1xxJjMKDDa98VqMnirO6mpKeAkqRwzSiph97LCYi5Epg93xL6uAylnXYKQR/4ao7c5x8FkLRMGiv8F6G5uZnc3FwOHz5MaWlpW1WaYDBIKBTCYrFgt8eDyJgs0el0IkcHwlAoRDAYRFEUHA5Ht9p6vV40TcPhcKAookMIh8MEAgFkWcbpdHa6rcVi4Z133uHMM88kHA6jqip2ux2LRXQMsfQf43F9Ph9X3vkHnnP9Fkt0sKiLuJji+TNI8KsLp3HVzHJASDcjkQg2mw2r1ao7riRJuFzxSYHf7+flL/dzx+tbkBQLP7Y8x3eU14kVXMoaNxeueAMQMs9wOIzVasVmExN8VVXbJKlZWXHJa7K2mqa1rS64XK6263nJX5eyb+cWHnf8kQnWwyyOTOaG4A+4RfsXV1o+xGWNVm8deSLBi15Jeu0/33qQSx77Aslq4wHrY1xkWUowohGKgGXy+di//mTarn1n2g7/2XtYCbPFdiWBMMgSOK0Suy58j+G2CnxPXY2qgcMCSvR6hlWNQBi+UMdyDb9oO64aEumFU617mGXZxqmzJzJ53CD8L/8CqW4vLmt0dDzrj/jGX5Lynkp27Y33iel6eurg/mH4w5rwOVHgtsHP8+C3F3Tt2gfqWbyllh3/vp0bXB/F24Y1wipYFbBFR3lN04jNS11WkIafDFe9bnruQ6EQ77zzDieddBJWq1V3T6XqIzbvq2bIoyNwWmnz+ghFNN4tvJTvHZyPlEBcfXzzTIqz7T3uI77zr9U8cfg8bJIIoLwhDe34BTgmXoqSPRgKpqbsT3w+X/LreXAZcrAWp1WCJwUR6wtpqBpsO/tFps6c1+Vr3+m2B95CfeKyeB9hkzg1cD+XLTydK44dkJY+Yudbv2fi5gfarueS4Fi+4f8xkqLwyJXHcdbEAfr+ZOdbSK8Kk/i2514Ge24OnHQb5a8MRw36WWb/PoNsLW3XPhjReDE4kwuty7Fb4oFyLD3a+eOvkPMHdfnap2r78i/OZX54Sdtzv3foRQy8/G/tXvvOjDs+n4/jfvUBzSEolD2scdxARNXwh8VcynXdCzDoNJAtSe8pv9/P66+/zvz588nNjRMoneojgEVfVbL86Tv5sfI8NiVaKXjgRNRrPunW+HDpP9cSPrSed+x3mPuIIdPQLngMryJW5jvz3Mf6/M60bWhq4elff4vvOd9tu0/q+03APvsqlIHzcCQUUuhoLAk+NIUcn7CK8IY0NA1+p13BU9pCfrpgDNeeMKRbcUSn+oiEOKLx7VvJW/VEWx+xRR7OdIvwXdLdJ7+Ok5p+v5/I/jexWS1Yy04GWx6Rfa/hD4REH+G0C2+d/Inx+0QLYn1A/D6qpuELwb+mPMv1F53d7rXvbhzxx4/3seTTZXxov63tubcqYLvzANhyU8Ycqa790kX/ZtonN+jGh7GeR/FErEiygmSx8p9vH8/M4YXtXntVVVm8eDFnnnkmVqu1033E7S9voGjlb/mO8mY8Nhh1OuGvP5eWPiL8zzNxVq5uiyF1194qsfO8NxkxeU6791R34oiqZj8z7v2I9+QfMIjqeB9xzgOok6/t1rXPemya8LpFxBE/8F/Pu9IJSIqVPfcJb+CuXPuu9BEvrtjJ9pd/xU9dr8TjiAFTCM69EWXAKTjchabjmu6TQADlj2NxhOPP3J3ei3kqPA/JIu43EGmnWjjER7fOZWRZ/Lhp6SMWP4D88a9FHAEsjkzGcuoNTBszAXvR2Hjbwxvx//mEtvsEgOtfw++xE/nH/Pj1THJPtd0nCTFkSHbgumUZavbIDq+9JEm88847zJ8/vy1jplP3yeu3wMq/t80fXovMojls4wJpSdtY8nx4LrNv/Q95Nq3L90ni9QwGg4Q8NVjqv8But1L+Z7FdDfp51/YTxtqr4/fJ2X8hOOa81HGE5EGp/wKc/QnlTBJ9xJ5PcLx0aVvbXcE8Tvb/gdcuUZg6QIGBZ3d47ZPdJ996+ksuP/xrzlK+EG2j44PdApZLn4WxZ7P5UCPzf/8R37C8xy9dcR9cX+EY1GsWp6WP+NPrn/HT7Rfp75M79mF155vadqmPSGz7yGzChzbo5horIyO50PNTtvxyfo/7iDc2VPLT17dytfIed1mfjseQg8Yin/1zce0tRQSzJ2aEjzj7j0v4qqKFHzje5lbrS6JtNOZoG0uueRVf8UzeeOMNFixYQE5OPJW4M3FEZ9qmda7RiWvv8/koLi6mqalJ932SofeWsf5LkJWVpSsHbbPZ2h40YzsjrFZr20XsbtvEmyMGi8XSdtN1pW1iLnPizRyDoihJz83pdFJq87UFTQCNUi6yTTyUSsL2xAe1o+M6HA6+PnMEv3hnJxFVo0HLRpYk2oRM3jhTbrfbdR0RgCzLSY+brK0kSUnb+lWJG52LmGARk5RTlHVcZfmQgbKHLCX+vSiakPLalxbmtf0WVYgO26ZI2BTArzea7Om170zbsf1z2F9RhUWWdH6bFpsL8srbgp1ExNo65CwSBYCyVfyO6xjLushYRlhVpimQVTIMmvfFG7ZWdemeSnafmK5nVPnmSCAmZHtW8rZRJL329gJGDXbwkbVc39YiYdRgSIn3H6A1H0Ki/efeeD1StbU5nWTZ9L+9VZHIy89BqtS3LynIwWXTP+Pd6SPc7iyqyWcgQqruskqg+UFtbVO+pepPUl5Pl1Wk6wXjN0rsnrK7svVtO3ntO93WUYDsyCZLiqv2Bkh1bKloxm4fmpY+IktRdX1+RHG0Pd9ZdouuLQC5cTVp23M/6xsw5lQomASvfIVsc+C35iEnnLdNkfhUmUG+pHImK9u2t90jniqIkm/p6CPcNshK6Ks1xdqla99e22H9C1h/sIl6smnVHLhlf/w5qloPSggGLEh5TzkcDtN36VQfgUg7zbJAVmK/pli7PT70y3HwwcFyFkcmc4plnb6P2LcaaeMLZJ1wh+m4XYkNUrV1ulzk2PRG3FarlawsJzj1aryOxhLHxNPhi6eA+ES0f7gZwlDnCXY7jtCdbyf6/LxVT4i20XPwRNw8FT6db1g+QJFFf/ta3jc4L+EYDocDBs6CiA9sefHjuhIUCYoz3lb8IgQkB3bN3xZHWP11JCKdcUQoEleXtz33ktymFksVc6S69mNGjyJruX58KLZ48SlxdUissnN71z4xzoPO9xEtgTBDrBJZFv1zlK4+gqJSqI4fO3btY4g0HEx53J7EEYGQkIVkWfT9X0/6CFz5beSb3SJRavcjRcTvuXRHLSeNKu7Ste9KW5vDiduOvo+wW7G6HODUH6fdPmL4dNgWTwc80b6TZ+Rz9d9ZVpBsCh5VrwRKSx9hkyGhzw5hIdvpICs7BxKOo+QOMMVNPH89jnm/B8N24z0VQ2IMaSUAhz9FHjWkw2sfe5a6fJ9Ift25tWpOXuYkLrQuxyYFaNacPBQ+n1MsCllZZiVwl+8TOQ884v4bkquxr0lCtjloshYjS/F5lLVlD9Ykx2i7nvXRqsO+CqyF08V9ohizG+zINgf5rvj27vQRE8tL2H8o3rfp5iXRPtRusyDbHDTIeoWcM1ADTptOmdvtPiIh7bTtPnFkJW+bgK7MM+3HnIW9Ru/bOUBuQLY58GkWsrrJMcTaalEVbyzttO15scaPY7XZk177dPARBXnZyLVB/hY5B4cU5LzcbZR5DBWsG/dg6X8iDofDdF90lY/obNsezTXo+NonrZSbAn1pp33oFnIlveFgfUIVxS6lwxhgVWQG5ouHqUHTV2akpVqY+WcQ3kCEM6MrLzH80PISxcZqp7lDUh4jzxXv4Expp62ZSaVoD4psrnQKYLU7oGBMu/LjYf0LyHak5uhrvUD+ZMgt1+9ozkCKcMyEOwGKvXsllgYVuNihlnXc0Ig0ptP6Q8kl+uOLRdpzDGNKs03EW3fhtls4qBkqza35GLa/1ub51mVo0QEnbL7HYmRtxmBxQcLKPgjybVtl+tK7JUNKg5/48z2syDwQJ007zSoUqUCSwsXTBYFWp5lXxvzY+G7oZkb7nzQfo3FvV067Q1g0fUqU1k66clcxrC31VGrzfWtDSzT49x1K2+clIqyqbd5bbehutTJgSNQ64duhW9mrJkmLWfHPbh+7I6ia1hZAt0FWALnraSPHXm3aVCKJYjy1LelL22kXSapgl0uVPBM5vW2s3KP24/OiC83vdZVBdkJ1buP9miQ1yGM1pKi1pC+1x4hg0iq7SsdVdlOgpLhE19eA8H1LRL03cxU1W/3hJBVB07hen1XS7m6tKTPXKhidIMlSGr+bocJ1YorwU5/v7f5xOwFNA3uy6s7QtXtv0LG6P4dJFThJXgW5sskci/UYEf29HMKCLMnm7+DMN/fnjVXwzo+6/dHagY0Q7EQKZjcR8OiP3YKL9doI5gV/w3eCP2Bu4EEOU4StM1XtO4OEvnFoXnxzBYYKlA27aBeWhPgmFgcZqr8HEaRMtg2wtq/2aQ9XzSxPmXYau59jv4/JzsLTAP5647u6h2RzzK5Wgu8IE75m2lRKPQoRnZdndxGMptabYofE58Zo5ZBGxOxYQli4P3wJzw26BXIM17ZxT8Y+//8C+si3PnQLbslQcUmLs8RKD30LRpYI0m2PVqrf0VIL/tok70gfPIEQBQlqFBDlyGfIeoNPY3n5ROS74h11tbEktjdNA0QXkLQUPWB1ZAnywpW6JHRpQR5f3HEqkwflJd1f41Mga5C5/HvUBDetMJBvEU1KuiLUWeSWDevye6RAi07h1RP4Uvj1FJaW8f2ZWcgSFGbZuPOscUnbdQduu9VMvgF8tRKCjRBJHmy3C1XcW1oSctTiTF0+Pi1QXOAu0m0aINWyt1ZfBaonkA2/SSA6Ib70uEEMKUxCvuWXQ8Hg+N92N/SP+rzJVm6YOxyIq2ITEZtsB7CxQdIbwHYYKHcRRn8qTU4fUTqipB3ft5boAoQ/M54fQoGUPvJtbH8xoYig8GzkVHODlmrw9TxgTgZVw0wkyopOUdVpOPIJTb9Mt6kUMR69svZQRv3D2hDymDa14GKnNpBTAg+wMHAvpwfvR3LkdXys3ATvRNkKTvNiSsCuH9ssvszFD8GwavbJkpXuT3IUh8nfapCkf2ZqWzNHmrb4Q0meozROQrPbJ9+U5syQb7FFL/O16sF3yzKQb8TJlsVbqzP6bKmaZl5cjV2nrtx7hfp4aIR8mC2Oa3jGei929MTY4Ua/8P4KpycWAkzkWxBLtJ8zXBdZhmEnmt/fg4XR1m0rMubdqaoaK7brF6Njnm8HtH68q86gHjHGWJSezZ3akEBYnjUiHgcd1vSxEvW7OzpQ/L+h6D0d1vc5gRj55nJC7vgun2oMZXlO5LwUC+I2EWfFfh8TSaepULfF+K7uweD5FiGF92BPkDMQFuiLE1oklf5SHftre34fBqOmb3bJsDhjTVBzaZnrk4xeyE0RN+Qa5vN1e0HN3OLR0Y4+8q0PXYdnP7mKoewx8YfaZunZbTVugBiIdmhJigF8+kB6B3wDzgu+2bmGOalVU5Ik8dAlk4Ekyjdfc9LV/0xC0zSsxgkcYLPHUiZSk29YHLhsFv7w9UlJVT41nuh3yTYMhi2Hu3u6qWFYcfNhx9kDRZgjp4garRvkUEt6VH3Gst0AWO3Q/xh+eO7JbP3lAlbccSonjCgyt+sm3A4LB9Qk5FtzE7RWdi8ADbdC41eEvQ36zZqMYk9CTqUT1myT8m2gVEtLIExNmiamsuG+kyw2Pr/9FO792jHJ3yBJcM79MGgMDBgOC38Bjuh9Zs1haFEWT37zWPYnWeUNaPGgZb9qmJw27iOdMCrfVCV95NuofnHVsol8C0SDvlBmlAbhiJpkMtp98i02HgEcMk5eYji8Mvn2HkIo3wwBqiyLe6yrpI4lC2u2vq/vL8VJw4sfW5E2wjolAuaiLo+FFwLQiouvtHLCWHDZO/HdsgZD2UIYeDb0P0OkvhsQdur7BruvVkiFMoBgWDUVNUK29Ih8cxTon50fWF7W/V2TQcViayDDyre81NkDANbWDCzgAYFoyUnZ9N16Qr7px1RjcYy/fZLehZNEqFqSzAbFItRPXSEN8pMvRp6obOK7ltd126qaPNCwFio/gsavunrKyWEgPUKaBVkiuXpv4W/T85lRyI0HIJwZ8m3tgUYcqn7O0oKL48rNcbc1Xcq3hOtenhffvFs1LJI3dvCMqSEI1AqSJNgotoWNi5FW7BYZ+8DTwNGzWPXHl52WfEe0r7BEPciacNOoGWLLmsyQb2omFGKyDfIHgkXf58ySv8Lj6/n8NlbR2WHsFywJ5FsGs8hyjORbADASq40H4/fU/yD6yLc+dA0RPzSsJ0fWq1x8CU44dkvPOqvx0clOCy52GQeLja9CzWc9On57OFtd3HEjaLeiIcC5k0VHY5qsRcJQv6M7p9ZtRNQkqUuA3RlN2Qy1E8BHO+thxW4W/2guP543Wre7JhDNtzcq31r13nZpQUg/KPmx4bB2/14rdDvYm0rm3h6a05MuF/QmCfZOPL9t1dpmkdMXjEWRnSztNIaPn+jeYFi/GhrWoFat0m324MBqNfsmpBWOfpCtX1EbgCAUDtSnJzVGNlbSstgZkOfU+cCZUDgSTrgMTrgYBs+CkhOh38lCaYpQUx1MQuQEEtLM9kX0xAGN6VWCGCdsWg8IKiNG9UutfGut3suBZsQiSiT9K58hNZnyrfsT60QVn0k50LZjTbeP3x60JKplSZZBsnaLfDMS1UPlKk6XvwRg/YFGvtzXkOyd6UPQrHx7Tz3OtM1l6+R3i6XepkjBtRYO1v2dF6jE78tMxfFQRDUvcsk9UE3IDlOqzlC5in7E1fO1rZlTDrT4w+bqrWnsIxg6u93dDm8GKqYTr3ZqrMzdI1WfW9/HFRvIt0xW31ZVzZzZoFjB0sUqu9n9wZJ8AeYHllf5u/V+HrH+kXHSXlbsqgFfBah+aN7W4yqXQJK0U0U8OskIX2chXPZI+8ebdA47xn476a53I/oU26xIK1RtEn80b4P6tWkj6ffXe8hGH4u0ak4cSfo4a7qUbwmwJXSNuzTDvKWlDgLt9IeefdC6W/wmscUyw3UKaFbyXenpFwoKSni84EbdtsjgGZAr5lOJv48pdq9Lz7xKMpBSaiYqPEsWcJaCS5+m+zvr40Q8PVdnByPi3jUt3CU+3z1IEe4Ixvvh9e0SW0JG4vcQBDObyXY0o49860PXEO2YsiX96ocnIe3U3kPl2/gEpcHTkTP0O1vq4MCy7qXHdYB6T5ACOhGY55bpTNVTYVhRFlXk06QZfMkqkpc8zxQimjk4i2gStpj55sgzkrwrCgN5MiBP/3eNPzowGdNwvQ3pL98e0l/znpJvBe4smoyrZ51Bmsi3kC8J+ebK6bZHUGfgsitmJVIMdYehamVbYYtOIeiBz1+GJR9g//J93a5WnFgsaZysJYMkQ9kc3aYBkhjQayq2pSWAlgx9TVDqhEJMsYN7GOSOE5NoiwuscRIn12lll2om8A9pcXLERPSkOZXbpukDM9XSPf/EZBiY72obB4yeb+66TQx64QrWrNmcEfVbOJn3VopJZWeQSIBv1oaY1cwAVWlSfxgQSeb5ZnVGVS1d7PsUp4l8A3jc9gcGRtMZV+7JsC1CUK98C2pKm2dQIgqSmI53B/kD9anbI6RD7KzIjO+qSDtN4b3VHSg2KDKrkabIO9v+n0mvvlZ/OImSL41pp9YsOOsXKXdn+TOwgEdc+WZW9fWEfNPHP2WKnsTeWtmcMVWpqmnYJKMvpKWtAEmnoTggO8XCHHCqspaFykpest1NQ8Uegv5GaNioJ2a6i0gAfHqyNYQFSyrlm2IHVy6UjDDvi6FoCsOnn5101xfqWPPG578PhxdB83bwHoRAeqwE6lqDuNEvHFscWWQlId/aXdDrKqLHSvyY3ZqBAEGDyi9THyMQTXOP+CAYvadNyjcbea409QsWF984fRB/H3svLxVdTu2YOSjnPdi2O3Es3me0JWrc37XYNRWM5Fsm4nFJitoKmMfj8rqlPT58TPlmih0sTiiaCe5yyB7V489JhYll5oyiO9cblG/NtUi+3vdAP1rQR771oWuI5om7ZYPnm0751rPbqiwvHjT8K5JEhvzOQ7D+Pz36jGTYXdOq8+pIifMe7tRqdnG2HZDYqulX36nc0L0T7CbEyqhB0o8FOebNN/Hi1G926DvRYreBfGsJsGJ3Hde+Zkgz1VRoipIFvgqxgtZTGAZWv2bD2QPybfSAfLMZfGfQkB6j0Egy8s2Rn1HyLRBSWaeN0JE8OtTth+YuyPc3PA+VB5KmUns0R9KKV2lH/lDdn/2lOmRUbnitjpaO0io6AaPyLSh1glBM9E9LohaxW2Q2y6P4Qh3Ttu3dyLE0JhSuMV2jlpq0Eto29N9Ls6aPfFNkieHRogupTJSPWfNbaNiZdF9PEIqo2NNYcAHgjZtOAIS59HXBW8wN6vZ0v2BJO0hacME1IJp22sVnS5LBmZd01wJZFBnKpEIHMCnfPDixJVF7pGsKai/RTzCGyxXs2b01ReueIRhRkyiQetj/jTrZtGm4FB9r05Vab4SqarQGwyjGogQ9/T6JkC1QOgrGzU+6OyvcYPKXSgdi1U7Naac9+G65+hivUGtgrLSPYgRhUdUcYOmOzKg8RNppEuVbVwvoKHazKXoSuKQA31VeZ+2+Wgj6hO2Ev4eT6OatqP5G3SaRzkhyUjRGLOYayaQEZBUh909uDZHS2L8uwQMtnJ7+vKY1QLakj11PHFPMwon6cy/NSXeWgJl8a8VFlXHx6NDy1IdI/O1DTWKMS+L5ljbyTXFhs9q4dkwlF55UStHYyZAQl1jaU741HIDWXeDZ36NFV8ngQ6amc8EhEbINCstNm8s8m3usJG0j34ykvNUpUoPzjklaoChdmF5eQLZd35/u1Azkm6ZC3XYkLbNFFI9W9JFvfegaoubqWYYqSIkFF3q6eiNJElMG5wHC7HJxZLK50Ue/Srt3S1OrF1lq/5h7B86DgTM6dbyS6GC6RzWs0NRnzv8jGZIp33Rqg0HHwukpKkUZjK8FoRhHgzfEZY+v4KP9Ks2aYaW1frcgC+q+hIYNPS+WkUT55uxselISnDq2H0vUyV1/Y5qqTmoGjzSP5BQrU5mQuUdx6tgSQli4OHgna9Qkq8b1+7q24rv745S7xMS6F4YYg3eQTYq0KXnue6/nqQhGz7dQZ5VvMUjm4E2SJPwRuCF4M3eHruTu0JX8KHSDrs0hY3qwvwXS6INk1/RBtGRLrz9fLF0zlU+alQhsfDnpvp4g3QUXACYOzGPuCKHIXqeN4LrgD3X7tfr9aVNKJCKZqkWyWAWR1p1x1j0o6ebRsrivPtxSRTiSQU/SgH7BwYODgbnm52PiwDQVaikyr+4XbH0+I75vwbCaxGOnhwo+WzYMn67bNEKOK68PNfhQ1fR/F08wjJaM1EljReS2Y82+Gr6/llcn/E6/Gw1qN6bv86KIpZ2aVH098bws1CssJeBd+09Z5biR82WhZPnXivR6dsaQvOBCN5Rvsg2KO1eE6gJlGTOW3QVvPwbv/h12ftC1zzIi4kMNmxeI7QrJFxkkWSxC5LVj/+IqBFcBjZK5L6nQCtmiJukLGw4KlVfEmzY/qmZvCLch7fSsyQM4Y1wp04bEC6pcM7s8LZ/XBilWIVS/2aS4r1yXmuxRE57/kEco4UzVTi1pSztFVoSPL8QVaAk+ZVY5Hk9uN16/uv3Qshsa1oOn+wvkUsRQiCpTi+GKA4bNNG0uDh7usZI0VtHZYUw7tXaxT+gmbBaZC6frs8MayaYBfaqrVLMDu9bYK+d0tKGPfOtD1xD2QsNa7Jp+MElUvk0o63ku+fdOiRMDy9Uk1R49tdCcZlP/QBIlkgFhe26bb1NH6BclqkzG6o37u3xqPYGqYvKiMfkYTLwMTvuB+c39J+v+NJJvIFZeQTJ/z7rtwhMkhpiEvbtI6vnW/S7MqsjYh83isfBCGrUsNqnl/D50YcdvTJPxvWRY6fVKWSKVLIPKt1h1zoNaCecH7zEHoLW7REp3Z4uatFMtq1VzpK96V3vIKgJHtm7TaEn4o/17vU9MtHtgLqsY0k7DnSHf5IRV7BTeOyXZdhrI4Z+RBfwzsgAPTqYnBOP7tRIimuH3q1zb6fPuCObALL0r77GJRRArIS05Sa5Vp8kkOQHeYDjt5BvA/RdNafv/FoOaWQq0Qt22Hn+GEeGIWfkmKT0w8c+bBMPNXluDpLhyZXet2ZctbQjoJxVezY7DKvPtE+Pq1TGl2UwdbK4E3C1k9+ewS0+MFDdtyQhRGoyo5upyPSXfZDvk6sfVROWbLxThYEN6vC0T0ewXz4/JMyiN6tg2dbAahrxB5PXrj1cz/F5129P3eVHEVCHm1PQe9BGuIrAl/23usj6FnSCf76wllAFiW02yuIpsFbYHXYFsh5FzO9XUKiUQlwEfLO3Af63Dz7ahRfRkaEiziOJtqRYZ8qfCkNNTHzOa0he2mecjh7QiPlCnmbZXV7VA40ZRRCJNac9Bv0f/ewGyKw+bReaF62fy/HXH8+4PTuS6OcPT8nltyBWqervBn9qUiVOzM7VyMeSF+j2gKRD2iArlRuWblsa0UwBHf3CUgi0fskeKivZRyLLUdjts0sr17wt4oWkvePYKEq6b6BXPNxDkW7+R7MudqNs8IHywx5XgvUFxvzkN2Q1YM1wALQE/mT+GkQl+uQCrI/p7XKraisV4jv8j6CPf+tA1BKpADeHQzJUnQZAz2Y6ed8QDElJPk5JvALVpDsySGI/WaPqB29N/dkpzZyNKcsRvYpJHN2fGSDgVIknSTp12wzVyD4Op34HShFLhx1wgVHEJyHNaUeTkwZDpe9ZsEURO6x5o3trjAcW44ubXrLh6UO0U4OHLJnFv+HImBx7nrOC9rHGe0PGbGtJFvuknoj7ZFSXfMicHB+ifE59kPGtM666LEsOdTSPJSu0R48HZO+SbJEGBPvV0lBRXiDUfXAqH3xM+Lt2ArBqUb3JnlG82yBkNWUPAmpe0SeKqN4ivcd6UuDQ/gM3sz1edPiWIwxD0SOmcWAMXTouvfC5WpyRto9btS3v1al8wWfpfzz3EinPd/PA0sSh0UCum2ejleWB52iuI+UIRUwBts9u730fIChx3nWnzECk+0dxfl7lq4sYFLi8O7BaZny4Yy18un8qvvzaBl74zK26J0FNIVmqG6Pu4svABtG72Be1BKN/STL4pdpO6Z4R0GCkhZXLV3vT79DV6xfdI6jeYLiRWgg02UeKWOGxItVfr0p+WHgiryKjmLIee9BGyHXKSj4U5ko9x0j48wQgVjen3KlZVzZxeljO86wp6SYJ+U+C0b0H/kR23T0TjYfD2gNBWQ6jGaqdYsFvb+Q6SBINnkzJJPUq+FUw0pzW34OKfYfP27K+egyUvwaevwN7P0lIQSPMnWdS3CzWeIkvMGFbI2P4ZML93DYaS2dgKJug2r1MNJF/dYWjcbH5/OAjvPwSfvAlvPSIWZgM1pkVwkXaaRkWsNUtUss4eKQg4w30cEy3v10poMWbbHFwpYtfmrd33BTeM4VrG0k7FcXcMWajbnKu1QH3PFiV9UfItWzKM5YZMpkzCYVVYdPMcSrPi/ew6Q7aN1FBFq1RmfOv/BPrItz50DVH/I2PKUqzgwg0npWf1ZlC+qy1lbbNxhSOGmvQqDaSgfpAMazLfD32PSi0fVZN4OTKbhrJ2ihMYUJItfhOjv4TmaeqUyi5dEKbd+smo3WYYUCQJXP3h2o/gaw/AZU/ABf8wHUuWJSIp0lzMyrdtQrofqIFQs1iR6omXQchcYddt7xn55nDmsfKbGj+a7uX+U0LcetGJqEa1kRHNVUKC30MogUbd3wElSr5lMO0UICvhN/tKLdfvbKoGb3Vq8s17WFQbjvlbBVP7onhw6NIEMopi/WRhnLy3zeR4f030WavvnmrMqHwLdoZ8A8gZBfkTU67cP3zpFJ3f1ZrbZ3LiyCJdc5NPRs22tPm+OTTjqmh6UxKy7Ba+Hk09uD/8dTNZBchNFeBJTwGTGHyhSFoLLiTiypmC5NWQWWtM267cAq170/I5MfiCEVyS/jpZbD0g3wCGzILj9ArfUqkBZ9RKYm+dR6TuVLwv+u10wrDA5dEE+SbLEmce05/LZwzpcZ+ug2ylYJh+8S4LP5V7k0w2e4hQJBn51kM1qWyHEv35u6RAW0VngA0HG3v2GUnQ5BUTUIdRyZfutKUY4RVqpCQLE/nmq96jT31LAwLhJAVZoGfXSpIgJ7X/2DGyUOLMuX8JTb70EvRJPd+6+10cJTBgEpzwNRg+uWvvPbiie58JoIXRDGmnfqzYbR302zn9YcDE5PuiC4Py6Hm6zR9FxEJQAzn8LHSNbp+TgCASaw7A4kfTYvOgJYv1e4MEkSSw5ZsIzHWaYdwK+qByldkWZt2zgpgDQcSt/0iQkca4FSt5zjQSVBaDOitF+rSGzGZNbzlCY3QRKVjfbZ9pxeDxq6Zh4S45RKAn5xTj1wy/X/XWHnnI+oJhnPiZLBsUgI402Tl0ErIsMX9k/P4z3ntq7T6k4P9m0YU+8q0PXUO0YzKqJmLKt54WW4ghy27h7ElixVdF5tVIEkVSmgsXSIaJgVdyslwdz8zAw0wKPM6toe/S6O88eVSSIu1UQmPF6pU9P+FOIlnBhZRpWFYnTPo2jLoo5fHuvzB5sGM2QN0n/N5iCDb2zMvAQL4FsOmIpG5BkijJc3PT8Q4uGqcwfEAxB1N4VLVBU9NSsdYS1P8WwViQkcG0U4DChKIZW7TBhtRGDSrWQKA6uUdfy3YI1EOdMGhvr0y9B0f6FCwdoXi07s+Fyko2Ob7Fn6wPs78xMUWm66vzsmH1OySlJz3Toshs/9lk9t6ksvcmlfwsB0MKs7hjQbwSm4l8a9jf8/RtAE0zEQVyBlISThghnqWd2kCOD/yZK4O36/ZLaljcb2mELxjCZiy4kCbyrSDLxj+vENfnS9XgJ1a5TTw3aUQgHMFl8FfFau9hFU0HjDWrPgZHU093VzcK0+pIIO1kopGs9+DokXVAh5AkyvoXmapa79qxM+2Ky4wp37KKwKafgI5M8H1bdzD9FYMbowSROTU9vepYlGhf2rSFAoe5vwvX7RcT6TQiEE5CzoO+SE53kJfcTxFggrS37f9T7nk/ZbvuIKnnW3dJUotbqI1cg6FsesftE1G5ruM2qbwW1RCaQfkWwIatI/INYEgSD2abO040DD8NxpxAWLayWh3JHaFr25rtUNtR3YQDsGdJx5/fAYzziohkSf9z1A6Mvrv7tRLqNX06IIfXQ+MG/eL4ljf0bar3Rhdm9c9jAGtasp3aoCTEV/3PaDfTaIOqT61uqWpAcw0V6rWmLd0i7pWIfp6hprAN6TGyBoMk4Xa52aUZfPjqD/SoSJ03GOYGy1vmHb2ofIthwZR4UbH16nDdfEMhwoqthzJWCfpoRh/51oeuQQtC2Idd0wdlHkSH6ehB9Ukjrj8p3rHeF7rM3KAqvWa8smGQ9Eui09WQaUEMlsk8z1KhNFf8Ji24qDWkr769bFVPTrVLULUkaQk9mBRcND15kLnXWFiiqQLq18X/DjcL4qabUA3kmx8bbnsa7reEoDs3y021q53y9TGkwXvLaiDfQjEvwQwr3+48K66k8GNnt3Hg3/SJWOFsTqIOia3GhX1C1t8O+eaTesfcFYDiMUk3n6Msx7l3WXxDNwIak+dbTydpiUhc5Y0Gnd+eM4yrZ5UDsNM4Oag/IKoH9xThgDntypb+63XKmBIsUQLWi4Nl6kQzuV25Nq3pmj5vU5LFhvRds5PHDeaheTJfanrCV6vdKzxnDCvnPYEvqJp9Wyw9VL4pDuHv59KnPZdHU0/3VDfGNwbSXKHRqHzDgd2S2TR72eqkwqY3f5YqN6f9uwXDqlkplg7lmyRBnr4fGJ9A5qw/0MiB+vQSiY1R5Zs57TTNpEFCX6rIcNBqKJ5Tvzvt1ykQyoDyDSB/cMpdE+S9bf9XNfj3F+nz/U3q+dZdwkBxCLLDlgcDJnTYXIeO4vGwBw6/K/zUjNDCJi+xEBYsnSERy+eYt7kK4opzSYLZ30E+50Ye6/8Tqihoa7ZJG4rH6DOYiINfdPz5HUAyLDiEFUfGY7xEmBdAJb5U9WMXFTtFXNGwPr4t2bN+aL057VSzpncBxV4kxjdnadJxO9EX93N1vG6fvX434/+eS1BzgPcQNHc9O8oY72mZIt+sOdDvFLLzB5t8+LTqHdEFsO6lPfuCYX5gecW8w5kmL9UuYPrIIRS5hdijBRerNf2i5ZjgV2w41HuZYEcL+si3PnQNWz+E95+mELNxMtBWpTQdGNUvm2ll4rjV5HNV8Cf6BjXbRTWBNEExpNh4FTfnT4mnEgzItXP8sELj21JiUIGrbeJp9G6yNR8UXmi9AOH5lkZzYaAwy/z+LUYJuKpCzUFYuwjWfQSNFT0iDkIB/aDv09KgfAP9yppsYfisczp+z+Eve1wxz2KQlasWO9iLM658G2fwFzF5gNQcgH1fQLDJ7NMnyRDzG2rdixZoTfk5rfSeuSulk1LuOubwG9D0lUih81V0mRxRVH37SDrTEGy5oux7wRTdfTh5UB5gNvantV74gfSQrNJC5sm6Yk//any2w8qJI/Vk2xbV8J3q9oEvfcVzvH5/krTTNBaTkC0cN3k2q9VRuombhAYVW9NDjkbh9/uwGcy6e0y+xTxscvRK5aGSOO+tVV5WV0C1BzFhTqf6LajvL7yaA0cPKlZ3CooTT45eITGp8ZO0pjtrmkajL2SudtrTNM2YCsRQhfIkRa/6v/vN9KbRNvrEpC9WBbcNmVK+RVHtHqv72xmoh6r1pBOBsIrFWOkUeq5S7H9Myl1jpP0U09j29x2vpm/hOKJiXmzoZFEwEyQp/t6szse6ANTtan9c8lWAFoHW3WZSwVthsvKIyNbOqRHL55q3GTM7rDnIhdP421kO3vn+iSy77WROHVOCFwdPReaZ3x9DxVc9VshaQvo+L2J1ZjzG6whL1Mn6DVX7xcKk5wA0RfuSZBYxlbtM1y6INb0LKJYs6D8PCo9NuntQQfzeXqmO0RVzskkRLlGW8FbF8Lj3W2f9i2Mfb/SKy6RK0eIit3i0SUWvVu4Qz0pL96yVUsblrpLk2zMIRZY4Y3xcmLEkovf/PU1ZzY7Kxl4+qyOPPvKtD51H0AufPwMB8+TViwOXTWFYUXon3P+5Kh50bjVO2sJ+aNybts+SDRMDv+zi3vMncfuCMXxn7nBe/u4JKYsNJINVkQlH/dGMCpax8n68NZsyUnXNCFVLUrWsh9X/Hrx4smlbCy72qobU0+VvwN5tsOcrYWJb/1W3PasiBvLNn460UxArUAnIP+7rbLbF1WEr1dH8LXyW/j2Vm3uc/meNGHzjsvqJiXGGAzNZlshzxO/jZWqSScPmj6OD/474NjUkVuPqVosU4pZd7SrfmuUMmAingnsAOJP7WRSFq+HQQajZJALK1q5VwjJ7gKS3KijucnDplTmjS0X11m3aIPPKfOVWcR16AOOzBEIhlAnccrp+ld1EKNbtEwRPGlIPgmGVZftVrMbJdZp9W/rnZzNzZD+TgqB+z9YepYsYEfInCaKtjvQUZcnTe1TF1DnuQDWRN39J4Nkf8uV7bwqlSrqUiYYxtjeUbyguPMPm6ja5NS/a5jfS5p/Y5AvhDUbS7/kWu29L9ffZcfJWTpDjBM7SHTX4Q+n5LiA8386WPzfvSFP6dhsS72OLE2/+WHNK3MHVYiEoTQiEI+bFSOh5ReTCEaKgSRLIksZ8JTNWI6GIak6z70lfHqsuKUlQ0oksgBgaDgkSLSUkEe+qAfAb2u18H6dXr3CMyFYTOZsU9mzoZ1C+T71K/7ctDyRRKXPcgBwGFbi49DgxDj0VPiOpHykANbuFgqoHsBrIN83iOOLk22IDAULIB7W1osJryy5R8TVZoYjDOyCoj1sDpFn5BimfIwBrgk+uBydrNL3f7y+szzBswxOi0JUnan3TBQLOqvYi+QaUFuSzUdYvOijeOmitE+ffjTni4GCSQjUWm+ijjgDOOiYea3yoTtXtGyDV4ziYZKz5L0cf+daHzqN6s0kaHoMXOzedMgIpVVnwbsJmz+E7U8WkrJo8c2B2oAcmrwYY004DshuHVeGGk4bzk/lj6J/b9YBmzihh+mo0Bh0n7aO6xS+KEHgPiTS+DCG58q1nQfScUcV8eMsczp08gAUT4qsapvLfifB7YefSbpNWEb9+0PdjI6uH1U6BaEXKbGGOD2B1w9xvcn3oh1wf/CFXBO9gtdHfqXZ/j8qZA9gN5JsUS/vLcLVTgBxH/Hdbqibx8KvYCrVRcjim5FGD4tpJMvjEPSu1U0CjRe5Fc1fFBsOSeL/E8PkzsOhxaDgIrbs6P5nTNBRVP6HW0qmiSoFYifYIiqlClGf/JmjZ2SMj8kiSynSyLTNB5jEDcxkTJRMhSZGP6p0iHd1fRU/x/94QKU1mD6T0X7OvTR3MF6p+0uff9SV//jyJYrSbCCcj3yz2nk/eHMVQZFCDSbsAjYetD3OcvI1Bcg3TDz5PzY4NPZ6AtiGg7/O82LGn0aoiKRQn/QaWsSyiT6Nr+OrztNxzAIcaxfid9gIFikv0t/3HgaK/5t+3vNr2/2BYZWd1ahVyV9HoDTFP+dK8I90pWPYEdVXJSRTlOM3V7Q9tAu+BtH1kMKxiMapJAZQe+lZZs2BYcrUOwI2W14H0exuFImoS5VsP+rvExciZ1+v3uQpIiYAHqpLcMzF4D4mxt2G9vvJ4zVb4/A1Tc4fdZjbfT4VZ34unmbpyYeo39PuzR4GjHxTGfezGl4nvWUUBVwR/ytuR48zHDXrhcPfnGJqmYY0YnkubE+Q0VgftBqooYLus7//ZtUakwwYbxWKYJ4ka3VMP1bt0mwLpVr51AJvBV3xRxPzMTfatgqqo0tJ7AGq/gIYNnVIxWg2ZDmQoLopBliUsJaNpNPiSUntYLEjWr4ZQ1/r2IaEkc5PjL+r5AkM3cfywQgZEbZh2aAP5StXPh0cceu0InNWRRR/51ofOox2Vy6nHDOK6E4el3N9t2HK5elKM0JNYb0yR2704bR8lBxp0fwc7O/C3gx+dIUibzcbORjpITfV+EZDUr4G6FWlRfiSDqHbayYILXcCIkmweumQKN54cJwe+Uoe2/6ZDm+PKEO9B8FV2+vNUQ6pcRLZ1SYmYEhYX9JsrSDgA2c64gYWcOaOAReqxBLGaCBDCQTi0vEcViRwR/fdR7NGAuRf8QHKd8c9oJJtni280NzqwRQRiDevF9/RXQ+Vu2Lke1GzwN5jfk4DW3lS+AUy/qv39kRBsel88Z3UrO0d4R0LI6AnGSDo931LAkmCSvNqwsus/sF0Qoc3dLEcf9hCpWKbbFNQUFFvmSMXnrju+7f8mv5lwQCgMmrqvio3hvU2CKDYXXEi/qm/u6GJWGci3AVI9a1etw1+fnkrcajL1gdUZTx3tLvInQ/nJuk2D5BqOlbaZKqTVb1uTPvLDqHzTHLjSsYDSHiwu8h3wckTvDeWq3dbjBZQYDjcKtYRJYd7T+06SRLU/RzaMnqXbday8jRLiffCe2p5X4I6h0RvgLCUJ6ZBuzyBHCRRMg9JTQbZSnG1nucHHicOboHVf2tSXKaud9vSZUrJg+gVQPg4K+0G5flGrVGrgC/uNOAiQZUvf1CsYUdO7uOoeLq5L/iQYtQDmXAVDRsJpN8L8X7f/3n2fpyYKQgnxgq9KxBYAm83EG0BprtWUlZASEy6CM74NM+bDeXeDM0+/3+KEouPAGVfg9M91MqqfWOTaoA3nxtDNlPufpVXJ1r+3YmOXUxdj8IdU3Jo+zpNsWe0qu3oLL2n6/p8D68DjAzSxKNHOfC8RHs2JPZNFcwywGgpIvBmZmbzhxg/APVLYjHgPCKFD5UdQvUx4wfmqTBYkmqZh0/TKN9mWefuUYSU55kWHvV+K+z8SgJpPuzRXKlH192tD/hAYdnyK1pmHLEucPzWe3fFCZK5u/5CWNWJO9T+EPvKtD52HL7VZ/iWzRukmjGmDbKXf4Phq1UpVL89l32dp+yhLUD/RCVncKVp2HseU5XL9ScNMfmg2KcLkz+6Dw1HvllAreDLjARcMq9jSWHDBiH458Un7GnVkOy2B6gNQtwaCDVC/FupWdZrA0gzBQEjJ0IqUJIG9iHMnDeCcEeJ3qyGPA2qxvt3eFXF/jG7AYQjK5Bj50QspCXvq9QPdcvsMGDFb32jXahF0hluh6mNY+Qh89ipsWAxv3AO1qdUwQU3hoCW1AXVGkF8OX/sRzQWjUrfZthhkhygWUbOsY4VSEoIuYwa8BvzzarGia5yMFvoOQGM0VTNRQdBZtOxC9emfpRZcmem/o8hz2XjpKlGopY5ctqr6oi1q5Q6xKt3Y/QrWmqbRkMooPgPXLM9lI2foRCo1PSGxUPmClzc0pEX9pvr0Y5IfO8hyGogCBwxdYPL+/LvtflPTgsatYqKcjtQ/n56wb8SN05bGSnnJYMuj2AWfGZ4jh+YT3p0xEqAHaPCK/tRcHTQd9110UW7iPN31ktE4U4kbwrd406eeb/Cm8MXMy0Cf7hrQ5jNW7LabTNTxtUDdHpEOlwYI8s1A8kuyeK56AqsbXMUw5TSYczHMuECosBLQT2rkGuVdPEGViJqexdZg0G8m33qyuKrYoGiGqMZoL4BRZ8BpP4dRZ8K4r8GkkzmYNZLfhS7mg8g0/Xsrv9JbVSQiHIDWRggFIdQYb7fv06TNS/sN6VzaKYj07AHTYcSpkD+64/ZRPH2NUS0v8VnQ8P6q7YKs6cbieGsgjFvSP5eyoxe9cKMocpvj/Wd9s9B0inANVr0I1lzhRRvsHJnfghNHbyrfDHFKDXl8aEyjBajfDdWV4B4qvpOvAiI+0d83bxcLsBXvQ8UHIjW1ZSdhX62pwJGUYeUbCB+79yOG6sJ7lkL2BJEyrYbEXKnmc/E92lmkVFWNfpo+hVtz5Yrf4Ajigmlx8u31yCwCmpVN1gl8NvB67D9c12Mf8v9r6CPf+tB5eJOTb2FNxubMoMrF2Y8rjxdBnzHNh8bDUNdNBYgBsmHFLmzr+XeSJImfLhjLs98czT5Vb3Zp1UJEPngknorT+FW3V9hS4bOdohPOhPIthsIsG9nRNMY12si24htJEQkJD5faBP+T5q2d+hxTyXZrBoMYRzEodmzWdtIz96+Prqh1z38ry0C+2RzR360XlG83nKRXkLYGNBhuSLtoqoB9u8T3C3tg+yfxfSE/LH005fEfDn8NvyU75f6MwJoLziKaj7+M64M/TN2uoTm+oli7Qrx8lckDmpDfvC3dvkcpMHd0MVMH57FKNackhPauBVRoWNdlDzvCrWhB/YSgRXOlR0XaDqaPm8h354r7zrjK27pznSC9vQehaWO3Jjq+BM8rEwli6/lCSjLccMoEngmfrtt2oryBr6o0QST2IDUYzAsOfjlK5vSUfAORxlisJ6pzJDOBU+g/INKvWrb3/DM9+hiiRsvFmXHlWxaSs4TsvDx2qXqfOw5vForLHqrOm31ifDWTb2mYuLmjGQX2AijTX6+rlPeJkXOexv1pU883eUMc1gwphgWDwJ6Z5yiG4mwHu7X+7DcudO1ZIVIWQ0mUoF1EIBQxK9/SMeYqTpG6GlNGO4thoLkQ0EWKGEd9LelJeQ75GtNazV5/nOi4IykiBrA4YcICPh1+FX+JnMtKo4r58BZh2m+sah8Jw6IH4IOnYdE/RdVMX6V4GVVqUbiyu6iyzJ8qiJbc8R23jaI018EVx+sJ5bXGLIfq7YKw8ezt2vkA3mCYbPR9qiWTc6UUOGfSANM2D04CY+frNx5YA9tWCb+0cOeUpq29rHxLht+GL6VVS0LULv0TOIeJ9HbnADFu2vLBWSasZkAsxPoqoGkLgcoVJvJNzkAhKiMGFbj4SJ2iKx5BJARrn4biEyB7hFggCNQJorBikYhbm3eIRb4EBV+zP0SZpCff5JySzqdwZwhDi7K45gSRGdVINvP4Eznn3UZd0fHI9iN7bkcCfeRbHzqPJD5BAK04hT9DBpHnEsffoA0zG5Cv+2dagk4juWNN4yA5cVARWQPNZpdKyMubL77OlS8HWVNJp4mozuKtDcK3oVhq1O9IoweSLEv8+mvCtD+ExUyQGlGxE5o3i2qvnv1i4PN1HIjKxmpY1gySO9mjIGcU2TlxP7sPVMMqb30lVK8TaZldrNaoqhpuQ1BmbUs7zfwKULZDP3n3RixQPNBc4Wztq6AUQbAe6g2pZ0E9eXhIK+TUwP3MDvyRhyPnY1V6ObXClg+OUkosjSzTUleeEwHNbBGoS5IIXupWQcV7ULMcmraKSUHEnzw1tRc830AQ96989wTcTgcfqfqVXXX7FyI40zRB2lcvi1aT60T153ArmuHaNROvzJxJFESrJH9sqLaW07AFtDwAJM8+CtTN4p7rAlr88Qm1MYDGlpm+4tgR/Zl9ij6dsVhqRqrdLZR89as7d01SweRDGlNSpelaDZreYRMZTag/fJWd6qdTQlXB16jbVKPlZZ58AyiawaxBsjm1Z99qQRR0lcA2oI18M5IgaSHfhkLuWLC4YYiezBkmV3K6vBqAFq+nx98jhkZfiFwMypdZHaT1pwHF2XZA4kPjWLsv+hzVfdnlatVGJK122lO/NxCTY8Ul0jZdA8W/o04zNRsqV9GPenw1G8xVP7uBUCjJMdJcYAaIV+N29sflFgvJK4zPU2uD8HBrWKP/bns+hopoKn4oAGvfF4UXGtZBa/IiDfbc4qTbUyJnJPQ/Xai2uoBY4YUY1mmGOL2hQhQfaNrcZfP71kCYbMlgL3IEyLeFE/sn3d4y6iwwns+nD8NXn4n4ohNowYXd0ntUQiBsHk93aAM5L3iPyd6H5kPw+q2QO1UsqEsWkXWjBaHoeBiwAIpnQe44cPanKewwLaBYM7zgADAo30kzbhYb4jy++JtQjOaOFan52SMEAa5FRNzavFWQcBXvi1ftChqqttBf0sdOzuysI06+Afzi7HG88Y3+PDJf5ZWLfAxwq9i1rsV5/y3oI9/60Hl4apNuduHHYc1s6kiMfAtj4SNDtRS2f5ha6t4FWML6YNOe3Y65bFdhzaFoRPIVubP97/BMwzVsfO0pgs2VXcrt7wj/WXmAPFo4TzFUk+luKfoUOGfSAC6Myoo/Uc2rvToc2AbeamHe768UK6UNa1OvaqshaFiPYtxvzyD5JlsgZzRFeXltmz5Xx9OiJaYRabB7HbTuQapfTY66VxA27UFToXEjvqrVptVqh9MpPlfKfLfstOmJsZWHJbFifOK39A2DXlj1CjjKIJiEiEpAk+Zml1bGQU0E5plMY0wKixssTmxFkyl2W3gtMit5u52fQOUayJsA/U6G7OHRgEaFQK3oS+pWiXSEQx/o3qpqEi537yr6/v3tGbweOUG3zd58gA8+34GqZAlVQrDRsCK6DbyHRapgovpKDUEkgBYwK99643rF0l8+U8dTqxmC/i0fQOGxIFmwah6k2s+heqkoLhFq7nCBJUaAWAhjkQwBegZ9W2ZOm0yrq1S3bVLLZ+I59lcLs+duEgYhrz7VMxxLn02X7+CY+R23AdixXPzbuL77xYF89SYislbLxZnpggtRuJ0O89hUvRNaasXEujsp3FGkVL6l677LGirSIkecDjl6UuI31sfJxktrEPE9PPt6RPhqmkar10eWZLhnHZlPWyrJFve1aaGr4TAcXivUVzWf9ShVOBCOmJVi6SDfQBA/VrdQ2ShOGH8Zrxr6boCTlXX4AgHh9dtDAs7nS6bOTuMCXtFMMXEviF6Tgum4nOK+3qgNNSskd30qrERqP48b3O83+Ac2HIaaXWI8ajUT+n7NSn5RqWl7JjB+gP6+Xq8OI6AlLAhoKuz5AjQVqX4lDjX5PCgZvMGISfkm9cJzZMTUwXn8fOFY03av5IC53zG/4dMHO33sVhy91oeDeH6TYac2kDOD95oK67B/Ofx9PjS2Qu4EES/5a6DqExFX2AtFDFg4nUr7dJyGfs+ZlXnybUiheJ7+GTGMx82VsOROcQ8qjigJdxr0O0nEr64BcVItEgB/DQ01eyhEHzfYi0YcFeQbwMRh5SwcAQX2CGgqinHM/B9BH/nWh84jhfLNJkUyLjvOc8aDo7cjBuPIql2w78MeVWRTVc1EvrlzC1O07gYsWTBsFoGsopRNvmH5gIYX7obaL3ucrpSIC5Rl5o0ZCACunlUOtGOAGkPAC4d3A5JYcQq3igl29afxypqJ8OwHz34sBmLLnpX5ICam1AEIYuV1I6Gzay2EgkitO3FFKpCqPhIpta27xQTBeB29B6B1L95qsyG73eVKTzpZJ1CYZQ7O99Q0oA4/laaBhu+4Ywksf6HDYxpTI8vyescbrQ2SJAIp2cKwAoXHw2cR0JL9nhq8+2MINIrnMndcNKA5GfKOEV431hxxPIPyyIud1mBmCqOkwrgBeTQUTmS3qp+MlG35D7/8qAXsRZBVLoIzNRxdEd0uVFfVS+Hwu3B4kVDHVX0s3mwwt23pJeXb7JGi/wtj4S1jP77qCZCcaCVz8UnFgrwKNkHTFhEoH35XTLwbN4k+IVAv+o2K96FhPc0tjQA4kwVzafHeSgFbAaFBerLgLO0TmuWhgkwP1ELVYqGo7CJxFTF4vqnWLMgZpTMO7xH6T4fsToxzuz8HT0s0VbsbhWYiAdj/rmlzHTmmhYBMIdvl5BN1Ek2aYeFpV5QYqF8rKuJ1gwxpjvqtmdNO0zThkRXRJ8kWGGzwgJRauNv6JC2R6D3esEE8J4Z4prNo9oUpVZMoHNNdbCEJBuY7sVlkvlDHclAzxEpblgnlUdgjDMjro56kXSQaA2GVLAyEVToUiiDU1zHIVnAWc4/yHT6N6K/ZmfIX+FSb6N+qP4mqlrswroRaIVBHRNVYtjtJBcd0Kt8cRVB6ikh7BnANwF4Ss6iQTF5V2t6NopBJsFGMN83bIJTkHHd9Ie5rgxoWBAkxbmAa4+8O8L1T4mo3Hw6zAmn7pyALxVGuulssDHkPd1ggqDUQpkgyeGW6Us8BMgVJkrh29tC2grAx+ELA4ONg0ulJ36eDcWE2ilotF7ejF9TLUSRTvgEcW9wKSPwodIPJh5X6XfCvC+BfV8KerRAIiKJVtct1YoeqZr+ZLM3kIn8U/XLslOU5WaGOZZ2xqOCKf8KmJ/UFZ6w5QhFdME08mwPOhJITIX8S3qANRTL0JXnDMqOG7Q7sBcLHzl6M5izDI5cd6TM6Iugj3/rQeXiTr/hsVQdl3HAzN4F8+1idZC7LvPYlUTW0eUe3UlC93kZy0Xu+FRSkcZCUJMgqxX7mD/hl6PKUzfoFD8KGN4TCIE3+LafIa80bM6AEGT9AKFnqyOWNjgi4L9+DnXthy0qwlYmAumEtVC4WhEHrHhFgappIP9NUbIYS4C535sk3I0n1ZGSevkGgFb76HM1Riosaca7+qngq4OF3hYKq5jMxWWgQhvJ+rzkYdblc6VO0dICyfDMZccdHEYb9vpYzdl5mUPgBW97q8JgV6FfAJw3K68kpdg9uEbiUZcNXWjnnB+/iz+FzOaQZAvkDa+GDHwvyJjZ5s7rBXS6qvPU7CfovIOLUB0JeHJx5TO+syCdiQlkOT0QW6raNk/dRuvV5VF8VBKogbxKUzIkSiINEkBNLYVaDYjIUJbAlv548ae4FzzcQyreHLpkMwDOR01G1hM8MtsL7t4PioFkZitbvNPFdHP3EarUWiaYI7hGp3jWfCWIuEgDPfpqr1qEQ4T7rE+YPTtfkOhnsxbiPOZWwFg+nXFIA36oXRXqzLU+Qoi07oPJDMSGNEYjBxnYncJrhOuHIg5zRmGZR3T73PJh+UScaarB3k1CIhj2ib2va2nlFn78SmvXKsnrNTRgLWb2RdgrkZJcQxMrbEYPJ+sa3wRod6z37xDWqXysm1zEiTg23uyDWFO3PHZKRfEujasIRJVwnnANW/bh0vvIpI5pWi9QqEPdV9VKh5tO6VkG4qsXPnZZ/mXf0AvlmUWTGlGajIvPv8Kn6nXtW0lpVIwi4iE9cn9ovxBhbvUyMrS27BJEVak55vYJh1WT5kLZ4yJYwBkb73l/NKzJV95ujbGTlPkncHxG/UC1Xfyzi12AjDU11HNi6SFxDzwF9H6GGBPlY8zl/e3epudgCZNy8fHSCWuy1iL5Qk+Sph4pDYqGxzdx+o/kgOz4Dnxd8+rj7ifACaiZ8w2SNkUmcN0VPALwSOVHfoGYXHFyL5hwAyFEbjtXCqqL6UxHvte4VC19hr4gpgo14G/aZybccs/9ab0CSJFOl0GAE8SxNuwQmzkk9rigWGHE8jD5Jt3mtOoKgZO9d5VsoOfn2w+nima6igG8Gb6PGqKwHqNoIH94Nz1wLb90Lm96DQ0vavLYrm/zkSYZqvc40ZkClgCRJnDS6GJC4J3SlfqcahjfugDWPoAXq2VHVwhPLdnPrC+t5YNE2alsDgsS25UHWYAIB/bWIIIMzWyhxjxbkjAXZguSvwJlsoed/AL1HV/fh/z5SpJ2+oJ3CLzI8cbMmeAoEsPGvyGncZHk93mD3Ghi9JtqgBvImdinw9R9cQamkr8RmzU/zIGnNhdyhnH1OPz55ayMnKSkq+23+AI45E5DE9+iuGbAawmHRkEhC4g0yVnnqOSRJ4v+dPY6739zML0JXE0FmqFTJK5HZHNaKeML2e/0bNkav346PYeFPIVInTL39VWIwlO1i9VgNJTW+d+dkfjJQaKgStVMbyDuR4zhTSSgYsfUjpMJheKTSeCVNe4GY9EQC4m+Dai9o1XtTBDQrdrut1wZIt918Ty0/JJ7hKgr4QehGnrD+Htm4gtYODhuUCudOPgJBpr0ASubQL2cVEOArbShfhYfyWHghH9pvoyTR+/DLF2htbGBJv8vpVzaKY8eMQZITAhdZockX1lGKHs3O2P6979kytCSf30bmcpXyPmPkuPfe9Za32fa+jdGnnwd1XwgVXM5oQSLGoIbEhCDig5bD8NrN5Bxerzt+M1m9onwDOHdyGceWFzDrN4t5Vz2WhYnP0pp/I/WfCAwQk1d3uXhpmiB9Qk1iQhduEeqriF8QQrYCmoMVXK28zVnKCvOHZlL5ptiwjjiH96QXmc/yts0Fm56A078vCDh/pZicBWrFeRuVY4pdqDAtWaBE/7W4kAwVuBVHmu892QrjzgGtDj5+sf226/8Dc38i/Dpj6dmtOwXhYC8U45vFLSwNjKnzwQbw6SehNVGPv4IkKtxMINslvBr/FTmdyyxL4jsCLbDicTj9V+L7BJsEaRVLQ5WtoEUJDmuOUDdZsoVhtyUbJIXGVqEyMymq0nm9sgYJRbW7BI5fiLbsVZ3z31n1T0HBrYJob1gjiOr6tUiRCHmRHdA8FBz54CxtV2Fd1exnrrLevKOLXlrdxbj+OWw42MS/I6dwg+VNchI8sxoXPcqfhv2Sr0+CEQUBMd5GiY6kqaiyTcSBluy2f/3BMNdZ3ta3S9d1suWJeyTU3EbEnTl5OFv3Tadpi4vchO+irXiM8k+/yY6fjMTq28OBulYONG/lQPNWfvGJRCAicdLgZh44bR3FWRvEM2YrhHALHn+IN3fA/ctaGWRMoYWMq1xKsuO+p+u0EaxRRzBV3hn/bl++jDT4XjH2+KvB22A+SMgPnz5mIof/EV7A45MzH9slYnixG5tFJhhVVS1RJ+Ox5pIVSuizlj+JVDwUj1SKljUcwlGiLdggXkngaVIpMqQAklueoW/RMexK/DsChKyFQJ3wQhs1C3JLYMMyaDIQIqWjxcLEcRdR7dEoObiUvWo/fh66hiybBSldi0GdQKq001mjB/H9g/v508YStmhD+FrwHh62/pkpCfelDpWbxWvFv2DQFJj7M6paBpCHkXzLS+8XSIFvzR7KC6sOsEYdxWPhhfo+KuSDt/4fr771Mb/3n8ch4tYDz63az1vfO5HSXPFMhpv0/tONUi6Fknx0kW+OIqHgb9h8pM/kiKFP+fa/jHArstaFFIskaacPh8/jJemMNJ5UcuS79MHik+H5RHTG9Bp88g+o3y5Wn6o/EaqIDmThbe/ev1L3d0CzYi/toHBAVxFdlZ5c5sIzal7qdp562L9GpNFWfyIUEt1JQw01MywPBkiG6yYrMOjYrh+vEzh/qvB9aySbH4Zu5LzgL3k6Mo8P1ampCzHU74b3HwLHSMifLALl1r3RCpTR+9NvDm7cuXkZ+Q6JKHKbJ4b3hi/Db0hnVD57nAEVawCLSP+L+MBRCv1OgZLZUDgd8sYLw9SCaQT9euVbK06x6Cj1zgqivQOl6mJ1KreFrxOrZp3ENnVQ2/8LXQoD8zNfJSopbLmU9NdXBWzGzW2hb5uaund+wMxPv8/Kf/+W//foU0Q8+sClpVF/33klJwWu3i+JPqy0mAgKPwl9W+9HA4w+8CraW/fCwQ1iolPzmShJ768RDWSrmDg7S+GrRXDYPLGulQt7NYAekOekNMfOb8OX4tP0v6fy7s8YU/0ChBOIDCmqEnGVieeo6Hhhrl22UKQMF0ylxTGWM5TVyT8w00Uy7EW8aDtbt8kabIZ3fiT+cPaH4pnQf55IFXEPE0RpbAyLBARZ4jkgTJTrV6NVLUMO6icClqy8jJw75afD/OvBJVJsNkvDOC9wj76dtx5WPi6+R+F0QUJpmlAiNW8XPolVS+DwO0I9Vv2p2Fb7hfheXiP5Jsic3iLfJg4Un7dZK+fDiCGtbN0rsPEZsSJfMltcH2uUkFGjhU00TRBzrXuhcaN4xioWweF3ONyiAuYiOtjTSL4pDhgwT5zbsNPZXKK3ByiLHCTy8e8EGV00S5Dwsg3QsGuNSK27hMF9xaK4atRXIUjtBJV9VVMK31JbXvq+SzsYXyauUyPZPBw+T7dvoFTDBbt+xS2vNrCvJUowOfoJ/6PskaJ/sOXrFb+BekEcNH7Fzu0r2FXrxWJUi2WnUc1cfIJQTkfTNCVnCbeeM4NFsl4hdqmymNHSfkb+dheL6idy6rMKl70m85PFMoGI6Is/2S9xxesKvqDaZrAeaDnERa9I3L5EjM3JlW+ZV9D//qK4f+Ij4XN1+yRfI3z8mFhIcJSAL0Wa+p4vTJvqyKEoJ/M+W0bMHRUnNMJY+DzfMK9pOIi87Amy1INIwegCf+kpImZ1DxP3odWtW3gI+1rN/qM5hqIAvQiboTBCwDk8es4Kh8L9WOvPJTR9Fkw5DYpHinE3OweO+7qIZ1u383buQob6/8Xc4IN8pZX3asopwLgBKRYBimYxflg8U+GgVsIFwbu4PfQtk2WHDpoK+1fD0+dz+fqrzEVzekHxCzCs2M03TygH4LfhS1gaMRcNO58lfGL/IU9af8v58lLyaaa2Nchv34sX6vM36GNYjzVPLIjZepfQ7hA5o9GKTsAn9zvSZ3JE0Kd8+19FxI9Us5SiyCYInyFWrduDpoFPPxE9N3AP67URlLgzz+FOMHS4teSyb9h5DNuZ4EXlbYRFf4ZZF0HxMAg2g3e/SMdyGjrfYINILbHlQVY5nuoDCWsJsJ4RHOtMcwBgK2xLnzpz7kQ+2TuDkyLm4AOA1a9C+fFiZa1hvUhTsuboX5ZommKqSXPYQ16ohnLZsIp1yjUgZUbSn+u0kuu00uQzrsZK/Dx0De86foZFS7JSW7UJnv0mHHctDJ8urpemiiC6tQm+eF7XPKJJ5OVl3hPEqHwDMaj/PHwND1gf1W0fXPs52ktbYNx8GDwBClTwHRKVU91DdUFZxKMnRFslF4UgJg+9gGSkohEvRU7ikFbEfwoehVa96nVB4D5+VbaICTWfYpfCfBKZyCJVELqKpPHbr6WZuO4iSnLMZMvH6hTuCl3FXdandduLpGahoq16ncqHHqR08kkw+ZvQfyqeFn0lppDsQu4lhVgiZo8spjhLYb1nBL8If5PfWh/X7Zeqt8F7vwN3MQyeDKVjxGp1XrmYlDr6iX5i//Kkx29Uet+HZmz/HJY09+O34Ut010RSI4w+9Bbef5zB64XfZHFoKoGIxrfnDOP4YYZnPuGZavBGOEbaY/4gSU5fmmYqSBJ1WSN513csC5RV8e0bX4Kc/nDaL8U5KDZhkuxKUIWqIUGAhD1RhaL4v8fbistA5tizMpAC4+wPlu0w8EQ4wwFBHy9unsi6rQV8FhnPCcpX8bZL74fhJ8GAY8X7wh6hggvUR9WIrULJEvaBkYgK6D3IahFjemEn+qJ0YFhxfDz/TfhS5sgbsEnRxTlNg/fvF/5TE74GuWMEyauGhSepZIn699UJVVOoRXzfsJdQBKo8wu/NKhkW+9KtVAThURmooX7spWyqPMwEeW/bLmnp/TD2TOg/SSgLckah+RrwygfF5JmAOPdAvXi1vVEWqkUtTOO+JBkOMy7rNT/S08f2487XNgHC++sM5UuOlbe37R8tH+QF7Q5eefFUVow/jZIBGnMG16DkDBdp6rHzVMPRZ6oVQi1Egi3c8F4NoJmqAdLPYNLeE8gWkA3X3VXGa47zONe7pK3Yg1WK8Gfrw1wU/AW3vriJYCS5ynxbncZLh0Zx5WQrBBt4ZkUdm2vjMdRseZOuvSZb9QruDGF6eXwy/5E6lcWRyZyirIs3OLQO3votnHidSfWaCjvUMgLYyM/JS+u5dgb9c/Uxw+P++Zyesxia47GavHs5Y9yHYMxQUL2CYM0eJVSpiYgEQfUTUJeaPyidRG8XYUw7DWkyFM/muWVfcsd7MqrWjyGuFh6Z9gnjJtqQGSbmLKMvE0R9xMPGOjtawqJsb9hVJOIbM4fwp4/0BfYuOXYQWJyMHDEV+KRtu4rMc5FTeCEylxPljSyUV3CW7UtcanI/zMH+7eaN7fh0pxs/njeGbZUtLN1Ry7dDt/In/sw85UtdG4ukMldZz1xlPaomsVEbyrKNx3Bn5Ql4SqYweM9OHbMTcpUKP+NeKOTWZRxthGAvoo98+19FoE5U7yGM1LAG7HOEIioVgq0mI+I6RIAxJC/zwbMsS+Q4LDT746t8m/qdybCmlVCzN97QUw8fPApDJkP5aMgvgdpVYqKQOwaseUKS79krJghhD9R+RflOfcpNk61f+pUgsiJUBv4qkCRmXPotbn55HqsaCpkmb+dPtkfibRv2w+rX4eQfCe+MsCe5vF2SxIq44oy/LC7xr6+CO3x/NOtbswu7n8raCdx/4USue8asQNmhDeRHgW/zR9tfkr8x0AzLHoRPZRg8AwaOhYKBsOgBUXUzATXkUZSTeWWV227BYZXxG3wmXoqcxCCpmh9YXtVtl3wNsPo/sBrILoHSUdB/LAycBoNOFmXrP/kNE7a9p3tfvVLEkNJT016FNhUkSeKPF0/m5ufXtdtuuTqeReWXsWxtC2Ol/RzWCvlX5DSacHPBweso5iKKpGZ2aGWMG1jILacMZmiBjSGlRy7ABFG6PRmejMynFSe/svzDvMIJlAb3w8pnxCtvMOMa9+v2e229ZwKdCIdV4W9XTOeuV5bzfM3JyKj8yvIPs7Fua41IW98crdKa00+QcGVTYMyFUJ1c5n/QMjjD38CMsycNYMm2Gp6MzGOkdIjLLR/p9rtqNnNhzY+ZpvbjHXUG9+88lkduvZbSfLM/07IdNTz0wWa+a0+i5B4wMVNfQYfsLDf3VFzFbHkT2VIC8fTZw1CxBubdB/2SVIKWrWIRyKAsqqxuxc29um3O7AwEq9Ycocj17IPc0eCvYuzggbDVy+/CF/O68ot425Af/nMpnPtbKDtBqFqyhohXDBG/UP7GUu7VQJTYeVP3sTVaHgVZNly95PkGYuL21PJ97NQG8sfwBdxmTVi8i4Tg47/A9qUwcSGMOFUQWIkTBFcZkLBAokaoqqujQPuQ31gfM39gOpVvMUgSFM1i2GCF28OX8IztN227ZCLw6Bz4xlswNOpbZXHTIg9GK5gOVqsgeAO1Ik0z1CjIOE1tqzbubUhSWGvcqb1GvpXmOrj7nPH8vze+IoyFm4Lf52X7XQyU4qSgQwpxGe/BV++xcWM5XxQfw6xjx0H/cZA/Xix2yRah+I2my67dW8/O+mqy8OmfT4Bx52X8e7W6BvNEywJutLzRtm2kfIgXbffw/eBNbCG1Iurvyw9zwXEnElIG8ecv4ynTM6Qt3G19StdWcvRONe4hhVlMGpTH+gONgMTtoW/zhvxzvX1L7XZ49UedPuY6dTi5dg2bvfdV86W5+phhZbUTdcF85E+e02XQ5LXuR3vlDhh2HIw4AUorIasUskeLdDoQiyyKjaYagwpJySYrXZV1uwGj8i0YVvFHZH69uBk1Gkrs82Zz1rKzcCphrh6xlzyHheqGGs6dMoSJQ8fgUT7UHeNgQzerX3cThVHf2B88tw6A0hwHN5wkFG+DC1xk2RQ8Qf0iiIrMJ+okPlEn8bPwtcyWN3Kp/XNO1L7ESWrfUq+zFFcvVqe1WWT++c3jeObjL7l/SSU3hG7mm+oibrM8lzRelSWNSdJuJsm7oeF1WusduC165bI1f9DRSbz9j6OPfPtfRaIHVahRlAXPn5LaJy1JymmDJgb5EcW9YxI/tn8OX+yJr1h+/yMbNdN+xDe9dyJ7DKTUvnXi5cyB/uXQrxyKdgrJt7M/aIgyzgWjUDf+x8RPqdkZ8qvKGS3MWp0DcORl8+A5lQx9qpgKtZBr1XdFJxrD2udEgHzaXZBfChFvdNW9WazmRnxRLyRf0ip6wWBItyreBnu2WMnPEM4YX8pz10zk70vW88EePYH5mjqb6fkBLm9+BilVVTlNhX3LxSsFqrR8ygt7p3T2lccP4fFlZkXNg+GLqNHyuNPyr7bVbB1aqsVrx6fA4+b9CWi29+814i2Gk0YVd9wI+PH66TRHkt8vNeRTE60sNX5ADnPH9T6JkwzDi91MH5LPl/vM6covRU5irTqCn1r+zWlKkmIkMRiINwCf88hJ5KcNLeLN751IZOdTDH/6VLapg7jf+ijD5SQVgmNorhKv7UthyUNJm7wfmUZD/oik+zKJr00pY9OhZv7x2R7uDH8TDw6zFxMwVK7iRvkNbuQNAo/8DkadAsNPgWEnQ3Z/lm3YzpUv7GWg1GAmIwFmfbcXvg3kuBxUUMhPQt/mL7Y/6Xfu/gz+dhIMmgqjF8Dos6Gw/cIJ++o8JpLAlqkKz7ljxSvsBc9eJuWWwPtfsF4bwXPhuVxi+TjetqUGnvsOHLMAxs2DovHgLBOeVG2LQUnSfFsqdX/WarkML+6dPjyGxMJNf4mcy1z3Lo4LGBaKDm8SL+ffYNBkQd7mlEHRWKEONPhCHmpRuM/6RPK+JBPkG4Bio2z4iXyptPJw+Dy+Z3lNv/+pswid8COsp95hfq/FBZbBoqoziBgi4hWqRVS8Hr2qRBAG9o6zI9KIb8wqZ/3BRl5Zc4gqCrgs+HNez76X/GC1qe0x8l6o2wvvvSmuTfFwKJsIo86G4fPa/B43HBTqq36SeUwgN/PjltNm4U/h85krr2e8vK9t+0j5EG/b7uAt9Xiej8xluToe1RCR7q3zMu4Xi0zH/Hqid2EMmSwuY8CPzhjF1f9cRUTVqCafa4M/4l+2+8g3mtYbUTIAqg+bNq/RRiJLiHTVXsaUwXmmbZevPYX/HFcPXyzSVdWV1BDs/Ey8FJtYYO03CgZOheFnQk45gXCEqsP7SDRmDNuPrNLHqujHm1BEZeOhJloC5tRlX8TCX7fF4oK9/PPzvfztimks2qVv95vzzemRmca5k8s4YUQRu2s8jC7NbuvXLYrM5ccP4bGlu1O+N4SFJeoUlvim4MLPxcoSvm15mwFGNSzgGXoGvU0DK7LE1SdPY97gj/nPula21Mzl9sAELgq/wwzv51jUJHONKNyS2TKgeMiRzULpQ3L0kW//q8gejmYtpUFuFCuawUZRbcnZH7KGxsuKx2AInH2aDQ8iwB5R3DvdUzJvmF+uLuDvlnt5MeteygIHzG/yNcPuDeIlK1A8BAoGwZaoNNmejRww+1HYSoal+/SjB86FAfPF/zUVqWQmDks1/rDMz0LX8LLtLuxSwkD41XvCF2PsaTB2IQw4XsjcZUUEzWpAkHBhX1Rt4GszV/d99R7GX8xTPFIE0hlOwzp+1CCO79fKk5/u5K5l+kDy5xWncp8yh02X7kEqngUf3QvbP+7S8Q9ZBjHJ2TsriDedMpJlO2rZWmm+T/4VOZ3P1fH8zPIsp7ZH5HQAX/bQnpxit5DfSa+l5lDnhokzxh9ZtVsiJEnikcun8tTne2nwBrl8xhCu+PsXNHpF4LJLK+NboR8zJryfrysfc7byOcVSc/sHBbTcQR22yShseSjDLue5eS9xyaJRzAv+lq8pn3KN8i5j5ST9Xwe4NngrS9QpnJybXCmYSUiSxC/OHscPTh3BjHvf597w5XypjuJu61PmtLAo7OEW2Py6eEVxIvCxrR+btHLzG2afBMNOMm/PAHKi3jfvqMfzi1ATd1me1hcs0TThLbN/NXzwK3DkQv9joOw4GDgdBh4rzPSj2FfnZRaGqsi2DKtaLC7IHceoHI2yPCeHGn3cHb6KSfIu/f0VDsDa18SraCiUjIR+Y2DgDCibEa+6GcOS+2DPJ7pNVVo+o/r1jkonhhzdmCFxWdMPeKHoYaa2rjI39jXB9k/EKwZHtrhWQ0+G8tlQOomGyt3MT+Y1aHNlvOrkezfP4fT7A8yXVzFSPqTbZ/3sAT5d+i5vZX8dLXsgC1JVT5ekeLEPQGvWx3phezYUzRQFJnoRd58znjyHwv7Kg1w+uIX8/IU0rl9J1qGt5vTeGNQIVG0XrzUvoSlWpCGzYfzX2HugHEhCvlntYM+8x1hBlo0ANq4P3cJztl/qlHyypHGOspxzlOU0a05yJB9BTWG/1o+P1CksUaewTh2OHzv5NHO1ZRF5tHKB8qn5gwozFLsmwYkji3nh+uP52ye7+WBzFV9pQzkveA9/sT6kIxgTEcLCl+VXMDP7LdgVV2KHNIVPIpMIWy3tZ+FkCDOGFlCQZaPeE18UXl7ppLzySpYdZ2Pg9g+R/EnSFSNBOLhevFa/CNIdUDiUerWI+yS9l7Qzr8T8/l6EzeD1+9aGw4RTpDsboWokzWgZVdq7/UIMRW47RUlsYW44aXhS8s0mawRV/bzHi4N/Rhbwr8jpnKd8yg3Km22LmfXkUnjqDzJz8h1Bkuk/eBq3OD8DTQLKQPsWhC6Dfatg73q0QxuRwmayzQhnv1EdtulD76OPfPtfxYq/YvngF5yGAuW/h0EjRTqk97B4WXOEdN81UEhWm/WBXYVWQGxJZ2hh75Bv3mDygOtwOJeTmn7Nd21vc7P1ZeRIiuIEagSqdotXDEmIN4DBx56ddHtaIclQeCx/urSS655ZzSZtGD8LX2vyEsPbIAb11S+CKx9KRkD/iWKSM3i2WJU35s6HA+QuP8f0kfapc3rNOJncsZQNyYZlZoN3T8TKqztlztcWwaQTYHA57FwDB7dCuP0iIC2ak6X9vsGZGTptI3KdVt79wYlc+9SXLN5qXnnfrQ3g2tCPGR3ez7XOxZxvX4nF19ilz3ANzUwBjI7w5k2zOfvPSQL4LuKUMSU6w+KjAf1yHNw2P77qd/bEATyzQj8h2KoN5p7wVfwqfAXTpO3MV1YxT1mlmxjFoGoSBZMWZvy8O4SjiOkzLkJ5fzlhzcKLkbm8GJnLKOkAp8pruabfFopbtosKWe1gvTqMj9RpgCiAcKSQ67Lx03kj+H9v7+J99ViWBY7hQmUp1yjvMtToV5kC5XIV5RjaZmUJMsvSO5ODxCImT0fmcUgr4n7roxSkUoH4m2DPp+IVQ/5QUYl60HG0VAw0EwXu3pm8SZLEnFHF/Gflfnw4uCJ4B/+y3cdY2awGpXaPeG1+X/wtWyC/DErGQf9jUX2NyMv/ZHpbhVbIWb1cOTjXsGATxsL5tTdztryc37ieIiucwhg+Bn8L7FwiXoBmy2J+MLl/EPmZN1YfmO8Ci50fhr7D87ZfkiXpU6hmK18x2/v/aPY42fLAw0yYMAllyAlQfgLkDjQdzxMI4wrU6GYGcv7geDpdLyLbYeUX5xwD6lioz4eKRvKmHseOfuNZtbaR07UVHS6YSJEQ7F4Cu5fwC03mNOt4sozqkF7y4IoRBQe1Yi4J3smj1j8kJahyompXmxRhhHSYEfJhrudtQprCTm1Ax4ss4y9I+7m3h2lDCnj0inyG3fEOAPu0Us4J/opLlcV8S3nH5Dn8VmQGty6bxLdGFTCsZAslFetxSQEeCy/kMEX89OSRvXr+MUiSRK7TqiPfYjhx5cVMzjqJpwY+RfahDcipiGwQiyy1u+lPEgKo5MgSITaD8u2djZUpWnYOTqvC6F5eQOkIBVk2pg3JZ3VC1sPL104gT27gwaXVfLAzRMAwlQwh4qiXI3M4Sd7AqTnbWTh7MHLeEVxsteVC4bFQtzKqulTBYoERJ8LIuaJvqztI856tBHavpNigWAaiiw8n9P6596FD9JFv/4toPADv/xxJDWMFtDdugq8/DSNOgtY94D0oUhsb1kPLTmHw26yXiFdqcWXctCEZMIFOgk+216TcF8bCn4Ln8mTwNL6ufMzFysemleDO4vv2e/jT8N6T6p44Mk5avBQ5iZCm8Hvbo1hIQjZ6G2DvKvHi72KbqwD6T4YBU4R6YvBMUcDAgHfU4zkzb5BIEeolDCpKPbm688uhnD90lTAcz3LC2PEwehzUVkPVIajeB8F4oLxOHc4fwheyTh3BZYPH98bpt0GSJO45dzyr9tbTEvUdPGFEIav21hMMi0BsmzaY27xXc5v3G4yWDjBD3sIMeQtnZm1D8qc2HN6j9mPanF4ge5PgmIG5bL5nXtKUls4iy6bwl8un9mq1zO7gltNHsa2yhZV746qqY/trTC0J8Oh6B6u0MawKj+GX4SuYIO1hgbKS+fIqhssVNGtOnnVewg1Tph/BbxCHxVXI0CIXO2viBNt2bRDbI4P46+FzkFE5znGAh2dUU9y4GQ6uAY++//xP5JS2/y+YcGRVi984cQwbDzbw0vp6fDh4JnIGz0ROZ6K0mzOVLzhNXsMI2Zym1C7cRSK1zto7KUzNhiIzH6nTODnwB26yvMbFypK2SXW7aNgjXhue4wegS1kCICdDdghJcOG0gfxnpSDb6sjl/OBd3GH5N1daPmz/jWoY6vaJ15Z3U9ZLPkQhx5T1XiojGJVvMUi8qc7iw9apnK98yrW2RQzTOhc7SKmIN4ApV3TvJLsARZYoL3SxqWoY5wV/ye+sjzFF3mlqlyP5mBRcB2vWwZqoR1jeEBhyApRNFfFDv/FsOOijFL3q1Fnau2OtCbJFVDfOKoeqTxjprqCk+AD/2HkyK7e2coK8iVnyV0yUdpsrSybAIqnMUTaad+T3jlIs0W/roFbM14L38F3L61yrvGv2oEsCqxRhrNQB8TZiIky5sqen2mXIssQ5kwbwxnrRR0dQ+FfkdJ6NnMpMeTOny6sZK+9npzqA34UvRkXisW2DgcHAPN2xirN7x8YmGX513gQufyJ5EbR1nlKuqrueB4Y/wzC7jFKxB+orEB42nUQ6C3t0A8aCCz3Ft04cSpb96KMR/njxZH799hbqPAGunFnOtJEDgCH8eTh4A0G2Hqigoq4WJdKCJdKCRVKxqF4sUpjR+WXkR4JQMCVeNflIwVEMJSdC3ZfC91tSRKEfNSwKGxWVkVMyFGYsEErtim1wYB0cWgOKgnTi98X8sA9HHY6+p6YPmcfWt8XDG4WkqfD8lXD8d+GE7wvTWs9+aN0tHvi6VVC1RneISsQD/ch8lVx375QF//r0gbzw5cF22zSTxRORhTwRWchw6RDz5VVcnbuCYt8BsSLVAdapw3noh5kPmhPhsMpYZIlw1PH0dXU2mwJDucfypL7SXCp462HXYvECxIzN/F3fUuZyZtaQ1L5+GcCokmyK3DZqW82riZ6wQuuQG3AHdgjCVw2LCmz2HCgtA+kEaGzk/iUWWnDyYuQkfNFU5/EDelcxAUJl8ML1M3l3UyWTBuZy8ugS6jxBLn70c3bXJqaHSWzTBrMtMpinI/OgUWO0dIBZ8ldMlnfh0Ry8GDmJU5S1WInwtnMhb7qOnPLIZbPwm/OP4fZXkkxMDLh8xmB8wQhvbjjM6NJsHvz6ZEYeZSufqZCfZeP5649vMwiub6pngmsfy3fX86hOnCmxSRvGpvAw7udiCmihiSxe/3rRUUUwnjZuADs/2ZV0n4rMCv8Qjv1kCMeVTmJl3VUMlSqZLW9kpHSI9epwXlaFIfu9XzuGWSN6X9lixE/PnsoX+5ZyoDHWV0hs0IazITyc33AZ/aljtrKRE+WNzJY3plaUxVAyGopnZ/y8Y0gsBhRDE25+Hb6CP4QvZL68irnKembLGymUOlBYpUIvkm/ThuRz5fFD2tSiPhzcGb6GpyJn8G3lHRYoK8mRvB0cJTm2qQOxFpQzaWDvkm9G5VsifDh4NnIaz/pOY7BUxWnyGr5RvJl+gf04fKkX/oyoyxpA4fCBMP26dJxyhxhSmMX2qlZ2aAP5WvAeZkhbeNj2MCVSY/tvbNwnXuv/3bZpJjDTMCuw5JkVckcEzlIoWwANG8h1DeaHBQd4zu3k9pUXA5CFj2PlbRwvb2amvJkJ0p7kHpBGDJqZ4RMXKDVU4A5i5Y/hC3kyPI8LlaWcq3wm/Ou6C8UCE08/IimbICpOxsi3GDRkPlcn8LnaedJpYH7vF1uIYdbwQrLtlqQeaADrG/I4veF7DHb7+evJVYzNCfL7d6ooatnFVHkH46R9KVOiNUlCGnFaJk+/Q6w90NjufqsisfKO08jPsrF2fwN/XryTTYebqGo2FyUoctu45fSjM6VxUIGLv105Lek+l93G1BFDYERUmRzxR+e7e0CNxR6Fojje0RDvWXOg31xREKk1wXtaDQmRjBoUWVSyDEOOEYVAPPtFddpBp6Q8bB+OLCRN6wQj0Qeam5vJzc2lqamJnJzen/inE/4nFuI4mDzVTEOmsXAStqEnEBowld+sVllZ6+QR20OMbYn7F/wlfA5Nx1zMT0/QoGxhr1RT+XBzFd96+suOGybBR/O+YLh/J1TvJ1h5EJsviekusPn4+xg3v3cMuhMx9ZcfJJW7HyPt5hJlCScra5MagnYWNVouVzp/z3vfLIKCaaJD7yXsq/NwxoNLCYRTr0rPGpZPfauP0YVw07QwI92ismtNi5djXzSrELf+cj4O65EJMo3YXdPKKb//pOOGKfDX84pYcPyMNJ5R97ClopmqZj+luQ7m/3FZ0jYvf2cW04bkEwyrpspZ/1ehBRq4+fn1vL45tYrl8TMaOX36dFEw5ShBdYufBX9cRl2SfqMzuPOscVw7u/e9BttDTUuAvy7ewrqt2/juTAfHlslMetx8n0mojJP2MVHeTTFNTJJ36T0XZQW+8RKUzQRL7xDbi7dWcc2TnRmfNAZL1Rwj7eEYeQ8TpV1MkneZUgaN8OcNx3HzmnbbpBuapnH3m5t58vO9pn1WwkyXtzFV2sFkeRfHyLv1lQ5TYI/aj+tCt3LpwjO4ppfvv+1VLZzx4NJuvFOjjFpOdmxjjm0bw/xbTEpMVZN4PPtbXHeaG8ldBiO+nZ6T7gAPLNrGn5fo1W6XjvTyNfVD3Ie+YIy2V+892FV8/RkYZ7awOGLQNPBXi8mo9yDvbWvhho/Miwc5eJgjb+BM5QtOltfhlJL0k44s+P6mXlGHbDrUxFkPp7Z4OHVIhL+f3ABV26B6B/hbiERUaioqKA4cQOlIYVV+DMy5DoZdleYz7zyeWb6XF1cfbCtu0R3s/PUCLGlWaHUFTd4Qk+55v1vvdRDgGGkPU+UdjJIPMlbaT7HUSK4liG3mZXDaH9J8tl1D+e3mgkaJuOnkEfxonjnGCUdUPt5Ww7ee/pJcp5UfzxvN5TMGH1WLkT2GGgbvfmjZJby0C48T1byPNgQbwFcFgRrh1R6DFokW4QuL7RY39DsJ3L3nAdlVhEIh3nnnHc4880ys1iNXBThd6ApP1Ee+dRL/LeSbLxjhz/fezKnq50xNkp6QDLVaDkUGb42fh77JZRedyriyQiielYlTNaGyyc/x933Uo2NML/HyZbWLfJrx4iCAlVnyV0ySduMtGs3dP7wlTWfbNcx7cCnbqtpTQ2gMkyqYJO1isryTada9jFf2I4Xbn7DFcE/oStb2v4hXb+od8/FUmHnfR1Q0dWwSOnlgDk9dNpiT/rSZRr+etPvoBzMY3v/IK3UScf3Tq1i02ewH1x6+f6zGd6dpOIonQ9YRNvI3oMUf4pi79AGoy6aw/v+dkfbUhaMFda0BXli5m8aWZi6foFFibWB7TZjh+ZBlAwqmgqv3UrY7g2BYZXNFM6+uOchTy5MbXCfDuGKZd25dkMEz6z7aArJ5J2MNVXPD87t4b2cKH88obpyRxY9L34GdyyHQCKNOhTl/7JXzjSEYVrnob5+z/mATDqvMtCH5fLbTXCU8GRQijJYOMFXewXR5G7PlTaYxVz3jl8izvp+JU28X4YjKtF99SJMhrTYZ8mhhlHSQUfJBxkj7GSUfZLR0gFzJS0hTuDP8TZ6LnMLVxxXzi/OORZZ7d/IWiqhMvvt9PCn8Y7uCYho5Tt7KNHk7ubIX98iJzJ1zPHYFMWkr6p0FlR1VLSx4aFmbcv6KSVZ+dWIAJIkmZTA3Pr2JYU0rGCxVM0Sq5lh5K3lSO+myRty4EoqPnkUHHdQIBOsgUMtHXx3mw+3N5FiD3HhMNcGgn+e353D/hkG48HOyvI4Fykrm2dZijQTA4YBTboLj7uy10/1/r2/iqeX7KM1x8ODFk3nm0y2s3t/EpH4avzslQp7FK76TFhIVg93DIVgvvIlrdolCEnX7RDGPqVfB3k9gz0eQ0x9m3gC5w6DwyFsjPPnZHu56c3PHDQ24bs4w7jhzbAbOqGvQNI2Nh5qIqBrvfVXJo5+krp7ZEY7r5+eF0zZD/3lQdFwaz7LruOSx5azYnXwR/29XTGXe+NL/LkKtO9BUQcQpRzjltDNQQ4KMC9SLfjDYqKvKS/EsUYX8KEUf+daHDvHfQr4B/PrtzTy+bA/FNPK87R6GyV033Tw/cBcv3/VNJGuWqJbaSzjhN4s51NgJ75xu4K1vFDFh7JFRIF39z5V8vK3zqS0AMioT7YcZEt7PWGkfkyQhfbdL+klSQLMyN/AHauQidt7bW2UKkuOnr2zgPyu7XpUxhuPKC3jhht5JE+kKKhpaOeWBj/FFOg5c+rkV/nXVOEa6KgFNKBHlo88BYN2BRs575LO2v1Otiv7XQtMg1Aj+GhHQ5IzqFYVvd/Gbd7fytxRpqImYMcjOM9dMx+bMy/xJdQPGgMwXjPDz1zbw8prD2C0SF45TGJoT5Im1EjVeuHQ83HOyjGzLE+bE3oPCJ2Xgub1+7sGwyqbDTfTPddA/18mSrdW8taGC6mYvja1eNlb6yXdo3DRdY1xhmOHZrahhP2e+WkJ9IN4HSKhMlnZxkrKefjTQmDOI7/zwvl61DEjE9/6zljfXt++5V5YV4pDHHAsUOFSUiB+LIpPltHPXHI3Z0+f2evXMGK57+kve3xw3gbcqElMG5eu8ILsCh6Ly6vxtjB0yVFQFlS2iAFIvxkVf7K7jhS8PMrTIxbdml+No3Qhe4VsXVuHmV+t5q0IsWEmojJYOMkPewiR5FxOkPQyXDidN0QwXDsdy0+qjI/2qM1DDUbKqTryC9RDxU9PsIxwJUKrUI4XqofUwuMtgyEW9TlYFwhFkSYovYkUC0LpLpIqpsdgtOoGWFJAdQtWiBqNeTyHxr71ILAa1bAfJAu5yyB4pSLujAHe98VVSxWwiRpS4GZTvZO2BRk4aVczvLpyoK1xzNKC2NcDM+z4i1MmqoEbsuTEsCK2csZBzZIpJxNDoDTL5ng9M2z/58VyGFPaON2ofMghNFQRcsF70A66jxDIgBfrItz50iP8m8u1wo4/Zv11MdKGUwVIVNymvcabyBW5jJagkaNGcrLjgC06fmPlqXkaoqsa7myrZXdPKU8v3JvUSA7GClqzcdDJMGJDDPy4bQUlhvyM2ue4pKRWDnSCTpV3MVL5iurQNi6Tyt/DZfKxO5tLjBnPf+cek4Wy7jzfWH+b7/1nbccMUWHzrSQwrPjIT0PYQCoV49IV3qHQNpbzIzeyRRZz1p0/b1AgWWWLpbSeT47SSZVP+z6wuegJh3t1USUGWlZNHl/yfOe//RWiaxpr9jfiCEf76yU6T6irfZeWnC8ZyzuQBR03KdjJ0KiBTQ2j+OgLeGhyhSuHbAtFV66AgSvMn9d5JdwVqNC0k1Cg8W0JNbDrcylnPJx97LJLKi+e2MmXGxUdsfNp8uJnzHvmMYESvQj51ZDYLR1n52qgQkZCHZXvDrKuCIdkhTizzkm/1YyEoKs7acgBZWB6UzDlihM6mQ01c+fcvaPCGyHNZ+fs3puuKRm2rbOG2l9azvhOpcw4LPDwPTh+qCiKkYGomT73z0DTw7IGWXYSDraxc9SW/3X8866uT3z9O/IyV9lMuVTJSPsRw6TA2p5W5V/8CBvwfrpanhqPKkBpBRkb84rcJt4AlS3hCHoFKrkmhqULBEqiBUBMEmxI8qDqAJMOAM48qkvRQo48TfrPYtN1lU/AGI3z7xKHccebY/xMxxQ+fX8era7tWwG10kYW3LrNhVVsFiVpy4hFbcEjE/jovc+5f0vb36H7ZvHfzif8nrkMf/rvQR771oUP8N5FvAI+8v5b7F+tXsh0EOF7ewlR5O9Ol7UyQ9ySt0Paa6wLO/fHfj4rO+rW1h7j5+XWm7YtunsPKPXXc+XrqggVWRWLxrXMZVHDkDF5jeOjDHTz44faMfsYXd5xKv5wjuyoaiqjc+sJ6kzFvZzAw38mnPzk6DUSTDSKvrDnIo5/spjTXwc8Xjv0/U5igD//3oaoaH22t5tMdNVgUmRtOGn5Eq8h1BV0OyGIKRV8l+A4LJUnRjKM63cIENQzhFmob6jhY28CYPB9eXwsrD6nMLIPc3AIoPrIkyNsbKrjlhXUEwipFbjuPXDaFGcMMv7EaEkWawq0QahUkR7BRkB6yBUrmgmI/4grSmpYAWyubmTgwL2URBk3TOFDvIxCOUJLjYPPhZrZXtSDLEnaLjNOqML08n/45dvG9laPw+dI0Qt4alr3/AlOmTeFvX7Ty6Or2U7gBnBaVF8/zMWH8HFHo4L8BmhYl4Q4KNbN72BFXInWIiD/6PBlealD0b2pIfCfXoKNyseGsh5ex6VA8ff6hSyZzxjhxPzltR+8CkBFNvhA/fWUD72w0ZwmN65/Dny6dwuvrDlGS4+D8KWX6CqBqBNCOquyGpdtreHzZborddm4+bRSDC4/8HKgP/3voI9/60CH+28g3gLtfW8s/V5hJkDElDi6Z6MDva+XMogP89s19TJD3UCbVUucezsLrfkNJ/tFDJGytbGbhnz4lElUZFbntfH77KdgsMiv31PP1R5eb3uOwyiz98cmUHGEyKoYXvjzAbS9tMG0vL3Txx0umcKjBx/TyfGbc2z3Pu58vHMu3Tjx6jDcrm/wcavQRUTWeXr6XtfsbGVMq7qmPtpq90yYNzOXxb0ynJPvouF5G/LcNIn3ow5FCj58lTT3i5E5aoKlRZVwz2It7rXBEe2jxh9ha2cKkgXldK7gS9olrcjQSVP/lMD1Paoglm/ayam8N72xuwmHR2FqrUZatMSwPxhXBRWM1RhQApacIhVgfjl5o2lGleEvE9qoWrn1qFZVNfi6fMYT/d/a4o2LRvrsIhUL846V3uG+9INK+feJQbl8wFqWXvSv70If/Bvy3zZu6whMdPVR8H3odN58+hkUbDnHYGx84vjFzCLecMVq3GvzITKhtasZp0cjKyj0Sp9ouxpTm8KdLpvC7RVsBuOuc8W0Tg+OGFrD3NwsBaPAEOdDgpchtp3+u46gKAoakUN99e84wJg/KY/KgPAC2/Wo+8/+4jD21wjD5mLJcQhGVrZX6Yg3lhS4qmvxMHZzHWZMGcNlxgzN6/l1Faa6D0lxBpB03VF9p7EC9l4sfXc7hJj/9cx389Yppbd+/D33oQx/axX8D8Qbie9jyxOsoQbbDyrHl3agMeRQQh32IQrZy8sSRnDxxJLfFipiqIQi1CKViKPqy5fYRb/8XcBTFsUaM6pfN0h+fTCCsHtVWB11BqQt2/PKM/wqyoA996MORQR/59j8Ml83C98ZHsJdPYVChm+lD8lMSUkW5R7fab+HE/iyc2L/dNvlZNvKzjs4KNpMH51HktlPbGq9e+s0Tyk2kmd2isORHc2nyhciyKW0l2WNVtAB+PG80N548ovdOPs0YVOBi6W0ns6/ey9DCrF6viNeHPvShD33ow/8MZCvYC8SrD31IIyRJ+q8h3vrQhz70IR3oI9/+x+GywJkT+/et4hxh2C0K//rWcfx58U7CEY3vnzqScQNSE55Gn5q7zhnPFccPQZYlhh+FBQm6Cosi/1d8jz70oQ996EMf+tCHPvShD33oQx/6yLc+9OEowZjSHP58WfeqpUmS1Gfo34c+9KEPfehDH/rQhz70oQ996MNRiP8Sc5TO4S9/+QtDhw7F4XAwbdo0lv3/9u4+psr6/+P464BwQgMUDRDlm5RlNszb8qYbzSlDo5vVmpXDdNhC0zRtLrUNq6XlCp22UnOhtTbSZTcrojDQ0rQMQVHTyjRSQLzloCQc4PP7o3F+nS/m1/S6zoHD87HxB9d5n+t6vzdem3t7nXN9+62/WwIAAAAAAEAAazPLtw8++EAzZ87U/PnzVVRUpDvvvFNjxoxRaWmpv1sDAAAAAABAgGozy7fMzEylpaVp8uTJ6t27t5YuXar4+Hi99dZb/m4NAAAAAAAAAapNfOdbXV2dCgsL9dxzz3kdT0pK0nfffXfB99TW1qq29v+fPOlyuSRJbrdbbrfbvmZ9qGmOQJkH8BeyBFiDLAHWIU+ANcgSYJ1Ay9O/maNNLN9OnDihhoYGxcTEeB2PiYlRRUXFBd+zaNEivfDCC82Of/XVV2rfvr0tffpLXl6ev1sAAgJZAqxBlgDrkCfAGmQJsE6g5KmmpuaSa9vE8q2Jw+Hw+t0Y0+xYk7lz52rWrFme310ul+Lj45WUlKSIiAhb+/QVt9utvLw8jR49WiEhIf5uB2i1yBJgDbIEWIc8AdYgS4B1Ai1PTZ+QvBRtYvnWpUsXBQcHN7vLrbKystndcE2cTqecTmez4yEhIQHxR/J3gTgT4A9kCbAGWQKsQ54Aa5AlwDqBkqd/M0ObeOBCaGioBg4c2OzWxry8PA0bNsxPXQEAAAAAACDQtYk73yRp1qxZSk1N1aBBgzR06FCtWrVKpaWlSk9P93drAAAAAAAACFBtZvk2btw4nTx5Ui+++KLKy8uVmJionJwcXXvttf5uDQAAAAAAAAGqzSzfJGnq1KmaOnWqv9sAAAAAAABAG9EmvvMNAAAAAAAA8AeWbwAAAAAAAIBNWL4BAAAAAAAANmH5BgAAAAAAANiE5RsAAAAAAABgE5ZvAAAAAAAAgE3a+buB1sIYI0lyuVx+7sQ6brdbNTU1crlcCgkJ8Xc7QKtFlgBrkCXAOuQJsAZZAqwTaHlq2g817YsuhuXbJaqurpYkxcfH+7kTAAAAAAAAtATV1dWKjIy8aI3DXMqKDmpsbFRZWZnCw8PlcDj83Y4lXC6X4uPj9ccffygiIsLf7QCtFlkCrEGWAOuQJ8AaZAmwTqDlyRij6upqxcXFKSjo4t/qxp1vlygoKEjdu3f3dxu2iIiICIg/fMDfyBJgDbIEWIc8AdYgS4B1AilP/+uOtyY8cAEAAAAAAACwCcs3AAAAAAAAwCYs39owp9OpjIwMOZ1Of7cCtGpkCbAGWQKsQ54Aa5AlwDptOU88cAEAAAAAAACwCXe+AQAAAAAAADZh+QYAAAAAAADYhOUbAAAAAAAAYBOWbwAAAAAAAIBNWL61YosWLdKtt96q8PBwRUdH64EHHtCBAwe8aowxWrBggeLi4hQWFqYRI0Zo7969XjW1tbWaPn26unTpog4dOui+++7TkSNHvGpOnz6t1NRURUZGKjIyUqmpqTpz5ozdIwI+4css/b22X79+cjgcKi4utms0wOd8maeff/5Z999/v7p06aKIiAjdfvvtKigosH1GwBesytKqVas0YsQIRUREyOFwNPv32+HDh5WWlqaEhASFhYXp+uuvV0ZGhurq6uweEfAJX2Wpyeeff67BgwcrLCxMXbp00YMPPmjXaIDPWZGnU6dOafr06erVq5fat2+v//znP3r66adVVVXldZ5A20GwfGvFNm/erKeeekrbt29XXl6e6uvrlZSUpHPnznlqFi9erMzMTL3xxhvasWOHYmNjNXr0aFVXV3tqZs6cqY8++kjZ2dnasmWLzp49q5SUFDU0NHhqHnvsMRUXFys3N1e5ubkqLi5WamqqT+cF7OLLLDWZM2eO4uLifDIf4Eu+zNM999yj+vp65efnq7CwUP369VNKSooqKip8OjNgB6uyVFNTo+TkZM2bN++C19m/f78aGxu1cuVK7d27V0uWLNGKFSv+sR5obXyVJUn68MMPlZqaqkmTJmnXrl3aunWrHnvsMVvnA3zJijyVlZWprKxMr732mkpKSrRmzRrl5uYqLS3N61oBt4MwCBiVlZVGktm8ebMxxpjGxkYTGxtrXnnlFU/N+fPnTWRkpFmxYoUxxpgzZ86YkJAQk52d7ak5evSoCQoKMrm5ucYYY/bt22ckme3bt3tqtm3bZiSZ/fv3+2I0wKfsylKTnJwcc9NNN5m9e/caSaaoqMj+oQA/sStPx48fN5LMN99846lxuVxGktm4caMvRgN86nKy9HcFBQVGkjl9+vT/vNbixYtNQkKCZb0DLYldWXK73aZbt25m9erVtvYPtCRXmqcm69atM6GhocbtdhtjAnMHwZ1vAaTpNs2oqChJ0qFDh1RRUaGkpCRPjdPp1PDhw/Xdd99JkgoLC+V2u71q4uLilJiY6KnZtm2bIiMjNXjwYE/NkCFDFBkZ6akBAoldWZKkY8eO6YknntB7772n9u3b+2IcwK/sylPnzp3Vu3dvvfvuuzp37pzq6+u1cuVKxcTEaODAgb4aD/CZy8nSlVyr6TpAoLErSzt37tTRo0c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+      "text/plain": [
+       "<Figure size 1500x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for full evaluation period\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=evaluation_start,\n",
+    "    plot_end=validation_end_date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "b835010a-b272-46b7-9c20-b0db1a99506b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2024\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d017577d-79da-4a97-9522-81f4c307f3aa",
+   "metadata": {},
+   "source": [
+    "## 6. Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "dcc14e37-5aea-4b00-ae71-32b68ee03d4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_counter_ensemble(ensemble_data, start_date, end_date):\n",
+    "    \n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "    \n",
+    "        year = years[i]\n",
+    "    \n",
+    "        # Define start and end month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "    \n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)]\n",
+    "\n",
+    "        # Set zeros to count from\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = []\n",
+    "        modelmean_lowflow_days = 0\n",
+    "\n",
+    "        # Count observed lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "        # Count model mean lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "\n",
+    "            modelmean_q = year_data.iloc[j][\"Mean\"]\n",
+    "\n",
+    "            if modelmean_q < q_critical:\n",
+    "                modelmean_lowflow_days += 1\n",
+    "\n",
+    "        # Count modelled lowflow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "        \n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"observed\": observed_lowflow_days,\n",
+    "            \"modelmean\": modelmean_lowflow_days,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)})\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "7460b853-5619-44c9-ac89-3c6fc099bde6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>observed</th>\n",
+       "      <th>modelmean</th>\n",
+       "      <th>set_1</th>\n",
+       "      <th>set_2</th>\n",
+       "      <th>set_3</th>\n",
+       "      <th>set_4</th>\n",
+       "      <th>set_5</th>\n",
+       "      <th>set_avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2000</td>\n",
+       "      <td>20</td>\n",
+       "      <td>2</td>\n",
+       "      <td>9</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2001</td>\n",
+       "      <td>60</td>\n",
+       "      <td>59</td>\n",
+       "      <td>64</td>\n",
+       "      <td>64</td>\n",
+       "      <td>59</td>\n",
+       "      <td>59</td>\n",
+       "      <td>56</td>\n",
+       "      <td>60.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2002</td>\n",
+       "      <td>52</td>\n",
+       "      <td>27</td>\n",
+       "      <td>56</td>\n",
+       "      <td>38</td>\n",
+       "      <td>30</td>\n",
+       "      <td>27</td>\n",
+       "      <td>36</td>\n",
+       "      <td>37.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2003</td>\n",
+       "      <td>51</td>\n",
+       "      <td>40</td>\n",
+       "      <td>59</td>\n",
+       "      <td>36</td>\n",
+       "      <td>46</td>\n",
+       "      <td>45</td>\n",
+       "      <td>19</td>\n",
+       "      <td>41.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2004</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2005</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2006</td>\n",
+       "      <td>42</td>\n",
+       "      <td>21</td>\n",
+       "      <td>43</td>\n",
+       "      <td>18</td>\n",
+       "      <td>29</td>\n",
+       "      <td>22</td>\n",
+       "      <td>0</td>\n",
+       "      <td>22.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2007</td>\n",
+       "      <td>25</td>\n",
+       "      <td>5</td>\n",
+       "      <td>12</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>37</td>\n",
+       "      <td>19</td>\n",
+       "      <td>31</td>\n",
+       "      <td>16</td>\n",
+       "      <td>22</td>\n",
+       "      <td>19</td>\n",
+       "      <td>5</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2009</td>\n",
+       "      <td>42</td>\n",
+       "      <td>54</td>\n",
+       "      <td>64</td>\n",
+       "      <td>50</td>\n",
+       "      <td>53</td>\n",
+       "      <td>57</td>\n",
+       "      <td>45</td>\n",
+       "      <td>54.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2010</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>26</td>\n",
+       "      <td>6</td>\n",
+       "      <td>8</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6</td>\n",
+       "      <td>10.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2011</td>\n",
+       "      <td>36</td>\n",
+       "      <td>35</td>\n",
+       "      <td>46</td>\n",
+       "      <td>27</td>\n",
+       "      <td>34</td>\n",
+       "      <td>38</td>\n",
+       "      <td>25</td>\n",
+       "      <td>34.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2012</td>\n",
+       "      <td>13</td>\n",
+       "      <td>18</td>\n",
+       "      <td>25</td>\n",
+       "      <td>15</td>\n",
+       "      <td>18</td>\n",
+       "      <td>19</td>\n",
+       "      <td>9</td>\n",
+       "      <td>17.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2013</td>\n",
+       "      <td>21</td>\n",
+       "      <td>32</td>\n",
+       "      <td>39</td>\n",
+       "      <td>28</td>\n",
+       "      <td>31</td>\n",
+       "      <td>34</td>\n",
+       "      <td>27</td>\n",
+       "      <td>32.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>43</td>\n",
+       "      <td>59</td>\n",
+       "      <td>65</td>\n",
+       "      <td>54</td>\n",
+       "      <td>57</td>\n",
+       "      <td>61</td>\n",
+       "      <td>51</td>\n",
+       "      <td>58.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2015</td>\n",
+       "      <td>60</td>\n",
+       "      <td>105</td>\n",
+       "      <td>109</td>\n",
+       "      <td>126</td>\n",
+       "      <td>125</td>\n",
+       "      <td>104</td>\n",
+       "      <td>66</td>\n",
+       "      <td>106.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2016</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2017</td>\n",
+       "      <td>15</td>\n",
+       "      <td>15</td>\n",
+       "      <td>22</td>\n",
+       "      <td>10</td>\n",
+       "      <td>16</td>\n",
+       "      <td>19</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2018</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>9</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2019</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    year  observed  modelmean  set_1  set_2  set_3  set_4  set_5  set_avg\n",
+       "0   2000        20          2      9      0      1      1      0      2.0\n",
+       "1   2001        60         59     64     64     59     59     56     60.0\n",
+       "2   2002        52         27     56     38     30     27     36     37.0\n",
+       "3   2003        51         40     59     36     46     45     19     41.0\n",
+       "4   2004         5          0      1      0      0      0      0      0.0\n",
+       "5   2005         0          0      6      0      0      0      0      1.0\n",
+       "6   2006        42         21     43     18     29     22      0     22.0\n",
+       "7   2007        25          5     12      3      7      4      0      5.0\n",
+       "8   2008        37         19     31     16     22     19      5     19.0\n",
+       "9   2009        42         54     64     50     53     57     45     54.0\n",
+       "10  2010         6          6     26      6      8      3      6     10.0\n",
+       "11  2011        36         35     46     27     34     38     25     34.0\n",
+       "12  2012        13         18     25     15     18     19      9     17.0\n",
+       "13  2013        21         32     39     28     31     34     27     32.0\n",
+       "14  2014        43         59     65     54     57     61     51     58.0\n",
+       "15  2015        60        105    109    126    125    104     66    106.0\n",
+       "16  2016         7          3      0      5      5      5      5      4.0\n",
+       "17  2017        15         15     22     10     16     19      0     13.0\n",
+       "18  2018         0          4      9      1      6      3      0      4.0\n",
+       "19  2019         0          0      0      0      0      0      0      0.0"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "02d8a545-838c-4da5-9935-22f34d49f4ee",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4dd215db-3fbe-44fa-9c07-26f13e64d255",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a08ca3c-9f66-4797-b4eb-7943785f512d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "efc2756c-f047-4ae1-a491-583e46612a75",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step5_QDM_Experiment3.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step5_QDM_Experiment3.ipynb
new file mode 100644
index 00000000..5723493c
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step5_QDM_Experiment3.ipynb
@@ -0,0 +1,2057 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6dc674b5-d3fe-40e6-80e3-ed1f78221490",
+   "metadata": {},
+   "source": [
+    "# 2. Quantile delta mapping of CMIP6 forcing\n",
+    "\n",
+    "This notebook applies **monthly quantile delta mapping (QDM)** to historical CMIP6 forcing.\n",
+    "\n",
+    "For now, the target period is also historical CMIP6 **1995–2014**. This is useful for testing whether bias-corrected CMIP6 forcing improves the HBV discharge output.\n",
+    "\n",
+    "Inputs:\n",
+    "\n",
+    "- ERA5 forcing 1995–2014 = reference\n",
+    "- CMIP6 historical forcing 1995–2014 = historical model\n",
+    "- CMIP6 historical forcing 1995–2014 = target model for testing\n",
+    "\n",
+    "Output:\n",
+    "\n",
+    "- Corrected CMIP6 forcing folder: `CMIP6-QDM-historical-1995-2014`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7c03cdaf-99e5-46d8-ba07-2843f1c07fc2",
+   "metadata": {},
+   "source": [
+    "## 1. Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "id": "43b2105a-222a-467b-90ae-1733bd907045",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# pip install python-cmethods"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "id": "1fb67b48-9bc2-4150-b724-c1d26291db0b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import xarray as xr\n",
+    "import yaml\n",
+    "from cmethods import adjust\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "id": "6a8d479a-11bd-453b-b1fd-5a454f46770c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ewatercycle\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "id": "05206528-dd3b-45ef-a538-be2dcba07085",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "start_year = 1995\n",
+    "end_year = 2014\n",
+    "\n",
+    "Scenario = \"historical\""
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "56e6454a-306c-44fa-86c5-2ef6afcc389c",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "id": "eeedfb4b-e1f4-4fbb-b5ba-de342f59bddf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ERA5-1995-2014</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/\u001b[0m\u001b[95mERA5-1995-2014\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6-1995-2014</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/\u001b[0m\u001b[95mCMIP6-1995-2014\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">CMIP6-QDM-1995-2014</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/\u001b[0m\u001b[95mCMIP6-QDM-1995-2014\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Defining paths\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / f\"ERA5-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_CMIP = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"historical\" / f\"CMIP6-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_CMIP_target = forcing_path_CMIP\n",
+    "forcing_path_CMIP_hist = forcing_path_CMIP\n",
+    "\n",
+    "forcing_path_QDM = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / \"historical\" / f\"CMIP6-QDM-{start_year}-{end_year}\"\n",
+    "forcing_path_QDM.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "var_names = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "print(forcing_path_ERA5)\n",
+    "print(forcing_path_CMIP_hist)\n",
+    "print(forcing_path_QDM)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "540c0e8c-52ab-4f28-be4e-ccccb35d7d31",
+   "metadata": {},
+   "source": [
+    "## 2. Helper functions for loading forcing variables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "id": "2f524b1b-ee16-49d9-ba70-0bd783d18895",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_file_for_var(folder, var_name):\n",
+    "\n",
+    "    folder = Path(folder)\n",
+    "\n",
+    "    # First try exact final variable pattern, then broader search\n",
+    "    matches = list(folder.glob(f\"*_{var_name}.nc\"))\n",
+    "\n",
+    "    if len(matches) == 0:\n",
+    "        matches = list(folder.glob(f\"*{var_name}*.nc\"))\n",
+    "\n",
+    "    if len(matches) == 0:\n",
+    "        raise FileNotFoundError(f\"No NetCDF file found for {var_name} in {folder}\")\n",
+    "\n",
+    "    if len(matches) > 1:\n",
+    "        print(f\"Multiple files found for {var_name}, using first:\")\n",
+    "        for match in matches:\n",
+    "            print(\" -\", match.name)\n",
+    "\n",
+    "    return matches[0]\n",
+    "\n",
+    "\n",
+    "def get_dataarray(dataset, preferred_name):\n",
+    "\n",
+    "    if preferred_name in dataset.data_vars:\n",
+    "        return dataset[preferred_name]\n",
+    "\n",
+    "    first_var = list(dataset.data_vars)[0]\n",
+    "    print(f\"Variable {preferred_name} not found, using {first_var} instead.\")\n",
+    "    return dataset[first_var]\n",
+    "\n",
+    "\n",
+    "def load_variable(folder, var_name):\n",
+    "\n",
+    "    file_path = find_file_for_var(folder, var_name)\n",
+    "\n",
+    "    ds = xr.open_dataset(file_path)\n",
+    "    da = get_dataarray(ds, var_name).squeeze()\n",
+    "    \n",
+    "        # Normalize daily time coordinate: removes 11:30 / 12:00 differences\n",
+    "    da = da.assign_coords(time=pd.to_datetime(da.time.values).normalize())\n",
+    "\n",
+    "    if \"time\" not in da.dims:\n",
+    "        raise ValueError(f\"{file_path} does not contain a time dimension.\")\n",
+    "\n",
+    "    return da, ds, file_path\n",
+    "\n",
+    "\n",
+    "def check_variable_shapes():\n",
+    "\n",
+    "    for var_name in var_names:\n",
+    "\n",
+    "        era5_da, _, era5_file = load_variable(forcing_path_ERA5, var_name)\n",
+    "        cmip_da, _, cmip_file = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "\n",
+    "        print(\"\\n\", var_name)\n",
+    "        print(\"ERA5:\", era5_da.shape, era5_da.dims, era5_file.name)\n",
+    "        print(\"CMIP:\", cmip_da.shape, cmip_da.dims, cmip_file.name)\n",
+    "        print(\"ERA5 units:\", era5_da.attrs.get(\"units\"))\n",
+    "        print(\"CMIP units:\", cmip_da.attrs.get(\"units\"))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "id": "919cf33d-dd3f-4762-a858-414a00a798f6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       " pr\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       " pr\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_ERA5_1995_2014_pr.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_ERA5_1995_2014_pr.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_CMIP6_1995_2014_pr.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_CMIP6_1995_2014_pr.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5 units: kg m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> s-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5 units: kg m-\u001b[1;36m2\u001b[0m s-\u001b[1;36m1\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP units: kg m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> s-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP units: kg m-\u001b[1;36m2\u001b[0m s-\u001b[1;36m1\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       " tas\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       " tas\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_ERA5_1995_2014_tas.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_ERA5_1995_2014_tas.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_CMIP6_1995_2014_tas.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_CMIP6_1995_2014_tas.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5 units: K\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5 units: K\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP units: K\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP units: K\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       " rsds\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       " rsds\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_ERA5_1995_2014_rsds.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_ERA5_1995_2014_rsds.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_CMIP6_1995_2014_rsds.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_CMIP6_1995_2014_rsds.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5 units: W m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5 units: W m-\u001b[1;36m2\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP units: W m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP units: W m-\u001b[1;36m2\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       " evspsblpot\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       " evspsblpot\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_ERA5_1995_2014_evspsblpot.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_ERA5_1995_2014_evspsblpot.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP:\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7305</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "<span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'time'</span>,<span style=\"font-weight: bold\">)</span>\n",
+       "combined_CMIP6_1995_2014_evspsblpot.nc\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP:\n",
+       "\u001b[1m(\u001b[0m\u001b[1;36m7305\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "\u001b[1m(\u001b[0m\u001b[32m'time'\u001b[0m,\u001b[1m)\u001b[0m\n",
+       "combined_CMIP6_1995_2014_evspsblpot.nc\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">ERA5 units: kg m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> s-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "ERA5 units: kg m-\u001b[1;36m2\u001b[0m s-\u001b[1;36m1\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">CMIP units: kg m-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> s-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "CMIP units: kg m-\u001b[1;36m2\u001b[0m s-\u001b[1;36m1\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "check_variable_shapes()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "63b2e743-44cb-4605-b3fc-644720ec28e1",
+   "metadata": {},
+   "source": [
+    "## 4. Bias-correction settings\n",
+    "\n",
+    "For this version, the correction is done with `cmethods.adjust(method=\"quantile_delta_mapping\")`.\n",
+    "\n",
+    "- `tas`: additive correction (`kind=\"+\"`)\n",
+    "- `pr`, `rsds`, `evspsblpot`: multiplicative correction (`kind=\"*\"`)\n",
+    "- Negative corrected values are removed for non-temperature variables.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "id": "a04adad4-5518-4f51-a95e-2d9bb71cf397",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "method = \"quantile_delta_mapping\"\n",
+    "n_quantiles = 250\n",
+    "\n",
+    "def correction_kind(var_name):\n",
+    "    if var_name == \"tas\":\n",
+    "        return \"+\"\n",
+    "    else:\n",
+    "        return \"*\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "id": "cb6bfd86-81fe-4257-861f-a3a20c7a2627",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def monthly_qdm(obs_da, simh_da, simp_da, var_name):\n",
+    "\n",
+    "    corrected_months = []\n",
+    "\n",
+    "    kind = correction_kind(var_name)\n",
+    "\n",
+    "    for month in range(1, 13):\n",
+    "\n",
+    "        obs_m = obs_da.sel(time=obs_da.time.dt.month == month)\n",
+    "        simh_m = simh_da.sel(time=simh_da.time.dt.month == month)\n",
+    "        simp_m = simp_da.sel(time=simp_da.time.dt.month == month)\n",
+    "\n",
+    "        # Save original target time\n",
+    "        simp_time = simp_m.time\n",
+    "\n",
+    "        # Reset time index so cmethods does not require exact same dates\n",
+    "        obs_m = obs_m.assign_coords(time=np.arange(len(obs_m.time)))\n",
+    "        simh_m = simh_m.assign_coords(time=np.arange(len(simh_m.time)))\n",
+    "        simp_m = simp_m.assign_coords(time=np.arange(len(simp_m.time)))\n",
+    "\n",
+    "        corrected_m = adjust(\n",
+    "            method=method,\n",
+    "            obs=obs_m.astype(\"float64\"),\n",
+    "            simh=simh_m.astype(\"float64\"),\n",
+    "            simp=simp_m.astype(\"float64\"),\n",
+    "            n_quantiles=n_quantiles,\n",
+    "            kind=kind,\n",
+    "        )\n",
+    "\n",
+    "        if isinstance(corrected_m, xr.Dataset):\n",
+    "            corrected_m = corrected_m[var_name]\n",
+    "\n",
+    "        # Put original dates back\n",
+    "        corrected_m = corrected_m.assign_coords(time=simp_time)\n",
+    "\n",
+    "        corrected_months.append(corrected_m)\n",
+    "\n",
+    "    corrected_da = xr.concat(corrected_months, dim=\"time\")\n",
+    "    corrected_da = corrected_da.sortby(\"time\")\n",
+    "\n",
+    "    corrected_da.name = var_name\n",
+    "\n",
+    "    if var_name != \"tas\":\n",
+    "        corrected_da = corrected_da.clip(min=0)\n",
+    "\n",
+    "    return corrected_da.astype(\"float32\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "id": "d4e73e16-e4e6-4202-9901-2fe271f40390",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def derive_monthly_pr_thresholds(reference_pr, corrected_pr, dry_threshold_mm_day=0.1):\n",
+    "\n",
+    "    thresholds = {}\n",
+    "\n",
+    "    ref = to_series(reference_pr) * 86400\n",
+    "    qdm = to_series(corrected_pr) * 86400\n",
+    "\n",
+    "    for month in range(1, 13):\n",
+    "\n",
+    "        ref_m = ref[ref.index.month == month]\n",
+    "        qdm_m = qdm[qdm.index.month == month]\n",
+    "\n",
+    "        # Fraction of dry days in ERA5\n",
+    "        dry_fraction = (ref_m < dry_threshold_mm_day).mean()\n",
+    "\n",
+    "        # QDM precipitation threshold giving same dry-day fraction\n",
+    "        qdm_threshold_mm_day = qdm_m.quantile(dry_fraction)\n",
+    "\n",
+    "        # Convert back to kg m-2 s-1\n",
+    "        thresholds[month] = qdm_threshold_mm_day / 86400\n",
+    "\n",
+    "    return thresholds\n",
+    "\n",
+    "\n",
+    "def apply_monthly_pr_thresholds(pr_da, thresholds):\n",
+    "\n",
+    "    pr_new = pr_da.copy()\n",
+    "\n",
+    "    for month in range(1, 13):\n",
+    "\n",
+    "        month_mask = pr_new.time.dt.month == month\n",
+    "        threshold = thresholds[month]\n",
+    "\n",
+    "        pr_new = pr_new.where(\n",
+    "            ~(month_mask & (pr_new < threshold)),\n",
+    "            0\n",
+    "        )\n",
+    "\n",
+    "    return pr_new"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c21c46dd-a15a-4619-b917-00971ad9c576",
+   "metadata": {},
+   "source": [
+    "## 5. Apply bias correction and save NetCDF files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "id": "78bc5fe6-bc7e-4d1a-b9d2-5d654f49e9c4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def bias_correct_variable(var_name):\n",
+    "\n",
+    "    print(f\"\\nCorrecting {var_name}\")\n",
+    "\n",
+    "    # ERA5 = observed/reference historical period\n",
+    "    obs_da, obs_ds, obs_file = load_variable(forcing_path_ERA5, var_name)\n",
+    "\n",
+    "    # CMIP historical = model historical/control period\n",
+    "    simh_da, simh_ds, simh_file = load_variable(forcing_path_CMIP, var_name)\n",
+    "\n",
+    "    # CMIP target = data to correct\n",
+    "    simp_da, simp_ds, simp_file = load_variable(forcing_path_CMIP_target, var_name)\n",
+    "\n",
+    "    # cmethods works with xarray DataArray objects with a time dimension\n",
+    "    corrected_da = monthly_qdm(\n",
+    "        obs_da=obs_da,\n",
+    "        simh_da=simh_da,\n",
+    "        simp_da=simp_da,\n",
+    "        var_name=var_name\n",
+    "    )\n",
+    "\n",
+    "    # Additional dry-day correction for precipitation\n",
+    "    if var_name == \"pr\":\n",
+    "\n",
+    "        thresholds = derive_monthly_pr_thresholds(\n",
+    "            reference_pr=obs_da,\n",
+    "            corrected_pr=corrected_da,\n",
+    "            dry_threshold_mm_day=0.1\n",
+    "        )\n",
+    "    \n",
+    "        corrected_da = apply_monthly_pr_thresholds(\n",
+    "            pr_da=corrected_da,\n",
+    "            thresholds=thresholds\n",
+    "        )\n",
+    "\n",
+    "    # Sometimes cmethods returns a Dataset instead of DataArray\n",
+    "    if isinstance(corrected_da, xr.Dataset):\n",
+    "        corrected_da = corrected_da[var_name]\n",
+    "\n",
+    "    # Sometimes the output name is lost\n",
+    "    corrected_da.name = var_name\n",
+    "\n",
+    "    # Keep physically realistic bounds for non-temperature variables\n",
+    "    if var_name != \"tas\":\n",
+    "        corrected_da = corrected_da.where(corrected_da >= 0, 0)\n",
+    "\n",
+    "    # Copy metadata from the target data\n",
+    "    corrected_da.attrs = simp_da.attrs\n",
+    "\n",
+    "    # Cast back to original target dtype if possible\n",
+    "    try:\n",
+    "        corrected_da = corrected_da.astype(simp_da.dtype)\n",
+    "    except Exception:\n",
+    "        pass\n",
+    "\n",
+    "    corrected_ds = corrected_da.to_dataset(name=var_name)\n",
+    "    corrected_ds.attrs = simp_ds.attrs\n",
+    "\n",
+    "    output_file = (\n",
+    "        forcing_path_QDM\n",
+    "        / f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_{var_name}.nc\"\n",
+    "    )\n",
+    "\n",
+    "    corrected_ds.to_netcdf(output_file)\n",
+    "\n",
+    "    print(\"Saved:\", output_file)\n",
+    "\n",
+    "    return corrected_da\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "id": "acfa59d9-760d-4e9c-ba62-50632b8fd36f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "Correcting pr\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "Correcting pr\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">combined_CMIP6_QDM_historical_1995_2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">014_pr.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mcombined_CMIP6_QDM_historical_1995_2\u001b[0m\n",
+       "\u001b[95m014_pr.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "Correcting tas\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "Correcting tas\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">combined_CMIP6_QDM_historical_1995_2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">014_tas.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mcombined_CMIP6_QDM_historical_1995_2\u001b[0m\n",
+       "\u001b[95m014_tas.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "Correcting rsds\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "Correcting rsds\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">combined_CMIP6_QDM_historical_1995_2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">014_rsds.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mcombined_CMIP6_QDM_historical_1995_2\u001b[0m\n",
+       "\u001b[95m014_rsds.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "Correcting evspsblpot\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "Correcting evspsblpot\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: \n",
+       "<span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">combined_CMIP6_QDM_historical_1995_2</span>\n",
+       "<span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">014_evspsblpot.nc</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \n",
+       "\u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mcombined_CMIP6_QDM_historical_1995_2\u001b[0m\n",
+       "\u001b[95m014_evspsblpot.nc\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "corrected_data = {}\n",
+    "\n",
+    "for i in range(len(var_names)):\n",
+    "\n",
+    "    var_name = var_names[i]\n",
+    "    corrected_data[var_name] = bias_correct_variable(var_name)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "01e5d39b-b448-49e1-9a58-a13415143e1c",
+   "metadata": {},
+   "source": [
+    "## 6. Create eWaterCycle forcing YAML"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "id": "329c7270-3e6e-4894-bb4d-cbf349782651",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Saved: <span style=\"color: #800080; text-decoration-color: #800080\">/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">ewatercycle_forcing.yaml</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Saved: \u001b[35m/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014/\u001b[0m\u001b[95mewatercycle_forcing.yaml\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'start_time'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1995-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'end_time'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'shape'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span>,\n",
+       "    <span style=\"color: #008000; text-decoration-color: #008000\">'filenames'</span>: <span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_tas.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_evspsblpot.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">}</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\n",
+       "    \u001b[32m'start_time'\u001b[0m: \u001b[32m'1995-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[32m'end_time'\u001b[0m: \u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[32m'shape'\u001b[0m: \u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m,\n",
+       "    \u001b[32m'filenames'\u001b[0m: \u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_tas.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_evspsblpot.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "forcing_yaml = {\n",
+    "    \"start_time\": f\"{start_year}-01-01T00:00:00Z\",\n",
+    "    \"end_time\": f\"{end_year}-12-31T00:00:00Z\",\n",
+    "    \"shape\": str(shape_file),\n",
+    "    \"filenames\": {\n",
+    "        \"pr\": f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_pr.nc\",\n",
+    "        \"tas\": f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_tas.nc\",\n",
+    "        \"rsds\": f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_rsds.nc\",\n",
+    "        \"evspsblpot\": f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_evspsblpot.nc\",\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "yaml_file_path = forcing_path_QDM / \"ewatercycle_forcing.yaml\"\n",
+    "\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml.dump(forcing_yaml, yaml_file, default_flow_style=False)\n",
+    "\n",
+    "print(\"Saved:\", yaml_file_path)\n",
+    "print(forcing_yaml)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a79f375-f050-4652-92d8-6d85827d2212",
+   "metadata": {},
+   "source": [
+    "## 7. Test-load corrected forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 121,
+   "id": "c2b3c4b9-9565-483e-9f00-a1a617d1254f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1995-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_QDM_historical_1995_2014_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1995-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/forcings/CMIP6/historical/CMIP6-QDM-1995-2014'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/Workyard/Shapefiles/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_QDM_historical_1995_2014_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "CMIP_QDM_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_QDM)\n",
+    "\n",
+    "print(CMIP_QDM_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "929d8298-a9db-4e02-bef7-3de7e8025d0c",
+   "metadata": {},
+   "source": [
+    "## 8. Diagnostics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "id": "86a68f82-bae7-4407-ba9f-a9e2e5f0c2b6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>259.132385</td>\n",
+       "      <td>258.764984</td>\n",
+       "      <td>259.130676</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>262.616638</td>\n",
+       "      <td>260.584747</td>\n",
+       "      <td>262.619354</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>266.683990</td>\n",
+       "      <td>266.945068</td>\n",
+       "      <td>266.679565</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>275.085419</td>\n",
+       "      <td>275.355194</td>\n",
+       "      <td>275.084656</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>281.591614</td>\n",
+       "      <td>283.529388</td>\n",
+       "      <td>281.590942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>286.239655</td>\n",
+       "      <td>287.728638</td>\n",
+       "      <td>286.238739</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>288.825104</td>\n",
+       "      <td>289.488037</td>\n",
+       "      <td>288.840942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>287.475311</td>\n",
+       "      <td>287.564758</td>\n",
+       "      <td>287.473358</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>282.689728</td>\n",
+       "      <td>281.650360</td>\n",
+       "      <td>282.674805</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>275.483521</td>\n",
+       "      <td>275.246124</td>\n",
+       "      <td>275.485504</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>266.516418</td>\n",
+       "      <td>267.792389</td>\n",
+       "      <td>266.535553</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>260.348724</td>\n",
+       "      <td>261.863647</td>\n",
+       "      <td>260.350525</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          ERA5        CMIP         QDM\n",
+       "1   259.132385  258.764984  259.130676\n",
+       "2   262.616638  260.584747  262.619354\n",
+       "3   266.683990  266.945068  266.679565\n",
+       "4   275.085419  275.355194  275.084656\n",
+       "5   281.591614  283.529388  281.590942\n",
+       "6   286.239655  287.728638  286.238739\n",
+       "7   288.825104  289.488037  288.840942\n",
+       "8   287.475311  287.564758  287.473358\n",
+       "9   282.689728  281.650360  282.674805\n",
+       "10  275.483521  275.246124  275.485504\n",
+       "11  266.516418  267.792389  266.535553\n",
+       "12  260.348724  261.863647  260.350525"
+      ]
+     },
+     "execution_count": 122,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def to_series(da):\n",
+    "    return pd.Series(\n",
+    "        data=da.values.squeeze(),\n",
+    "        index=pd.to_datetime(da[\"time\"].values),\n",
+    "        name=da.name,\n",
+    "    )\n",
+    "\n",
+    "\n",
+    "def load_corrected_variable(var_name):\n",
+    "    file_path = (forcing_path_QDM / f\"combined_CMIP6_QDM_{Scenario}_{start_year}_{end_year}_{var_name}.nc\")\n",
+    "    ds = xr.open_dataset(file_path)\n",
+    "    da = get_dataarray(ds, var_name).squeeze()\n",
+    "    return da\n",
+    "\n",
+    "\n",
+    "def monthly_mean_table(var_name, convert_pr_to_mm_day=False):\n",
+    "\n",
+    "    era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "    cmip_da, _, _ = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "    qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "    era5 = to_series(era5_da)\n",
+    "    cmip = to_series(cmip_da)\n",
+    "    qdm = to_series(qdm_da)\n",
+    "\n",
+    "    factor = 86400 if convert_pr_to_mm_day else 1\n",
+    "\n",
+    "    table = pd.DataFrame({\n",
+    "        \"ERA5\": era5.groupby(era5.index.month).mean() * factor,\n",
+    "        \"CMIP\": cmip.groupby(cmip.index.month).mean() * factor,\n",
+    "        \"QDM\": qdm.groupby(qdm.index.month).mean() * factor,\n",
+    "    })\n",
+    "\n",
+    "    return table\n",
+    "\n",
+    "\n",
+    "monthly_mean_table(\"tas\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "44041a3b-9453-4212-819e-c6ecf7ab9bdd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.915469</td>\n",
+       "      <td>1.014411</td>\n",
+       "      <td>0.923202</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.647922</td>\n",
+       "      <td>0.886178</td>\n",
+       "      <td>0.639437</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.931562</td>\n",
+       "      <td>1.102054</td>\n",
+       "      <td>0.928657</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1.377950</td>\n",
+       "      <td>1.504056</td>\n",
+       "      <td>1.376870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1.892165</td>\n",
+       "      <td>1.992272</td>\n",
+       "      <td>1.889571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>3.134658</td>\n",
+       "      <td>3.328967</td>\n",
+       "      <td>3.145954</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>3.462940</td>\n",
+       "      <td>3.765053</td>\n",
+       "      <td>3.486110</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2.314942</td>\n",
+       "      <td>2.116627</td>\n",
+       "      <td>2.335796</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1.707162</td>\n",
+       "      <td>1.607128</td>\n",
+       "      <td>1.754936</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1.148419</td>\n",
+       "      <td>1.267420</td>\n",
+       "      <td>1.151219</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1.013025</td>\n",
+       "      <td>1.112656</td>\n",
+       "      <td>1.008303</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0.838748</td>\n",
+       "      <td>0.929316</td>\n",
+       "      <td>0.830903</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        ERA5      CMIP       QDM\n",
+       "1   0.915469  1.014411  0.923202\n",
+       "2   0.647922  0.886178  0.639437\n",
+       "3   0.931562  1.102054  0.928657\n",
+       "4   1.377950  1.504056  1.376870\n",
+       "5   1.892165  1.992272  1.889571\n",
+       "6   3.134658  3.328967  3.145954\n",
+       "7   3.462940  3.765053  3.486110\n",
+       "8   2.314942  2.116627  2.335796\n",
+       "9   1.707162  1.607128  1.754936\n",
+       "10  1.148419  1.267420  1.151219\n",
+       "11  1.013025  1.112656  1.008303\n",
+       "12  0.838748  0.929316  0.830903"
+      ]
+     },
+     "execution_count": 123,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Precipitation monthly means in mm/day\n",
+    "monthly_mean_table(\"pr\", convert_pr_to_mm_day=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "id": "ced18668-c114-44c2-ba16-f5f381d4d523",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1995</th>\n",
+       "      <td>79</td>\n",
+       "      <td>82</td>\n",
+       "      <td>84</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1996</th>\n",
+       "      <td>51</td>\n",
+       "      <td>79</td>\n",
+       "      <td>87</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1997</th>\n",
+       "      <td>68</td>\n",
+       "      <td>52</td>\n",
+       "      <td>54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1998</th>\n",
+       "      <td>72</td>\n",
+       "      <td>55</td>\n",
+       "      <td>60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1999</th>\n",
+       "      <td>66</td>\n",
+       "      <td>60</td>\n",
+       "      <td>65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000</th>\n",
+       "      <td>82</td>\n",
+       "      <td>49</td>\n",
+       "      <td>58</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2001</th>\n",
+       "      <td>87</td>\n",
+       "      <td>50</td>\n",
+       "      <td>54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2002</th>\n",
+       "      <td>71</td>\n",
+       "      <td>76</td>\n",
+       "      <td>84</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2003</th>\n",
+       "      <td>65</td>\n",
+       "      <td>69</td>\n",
+       "      <td>70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2004</th>\n",
+       "      <td>64</td>\n",
+       "      <td>55</td>\n",
+       "      <td>59</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2005</th>\n",
+       "      <td>77</td>\n",
+       "      <td>44</td>\n",
+       "      <td>54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2006</th>\n",
+       "      <td>66</td>\n",
+       "      <td>73</td>\n",
+       "      <td>76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2007</th>\n",
+       "      <td>44</td>\n",
+       "      <td>77</td>\n",
+       "      <td>75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2008</th>\n",
+       "      <td>70</td>\n",
+       "      <td>78</td>\n",
+       "      <td>82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2009</th>\n",
+       "      <td>69</td>\n",
+       "      <td>61</td>\n",
+       "      <td>65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2010</th>\n",
+       "      <td>75</td>\n",
+       "      <td>39</td>\n",
+       "      <td>49</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011</th>\n",
+       "      <td>51</td>\n",
+       "      <td>64</td>\n",
+       "      <td>67</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012</th>\n",
+       "      <td>67</td>\n",
+       "      <td>106</td>\n",
+       "      <td>113</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013</th>\n",
+       "      <td>53</td>\n",
+       "      <td>78</td>\n",
+       "      <td>77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2014</th>\n",
+       "      <td>59</td>\n",
+       "      <td>47</td>\n",
+       "      <td>46</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      ERA5  CMIP  QDM\n",
+       "1995    79    82   84\n",
+       "1996    51    79   87\n",
+       "1997    68    52   54\n",
+       "1998    72    55   60\n",
+       "1999    66    60   65\n",
+       "2000    82    49   58\n",
+       "2001    87    50   54\n",
+       "2002    71    76   84\n",
+       "2003    65    69   70\n",
+       "2004    64    55   59\n",
+       "2005    77    44   54\n",
+       "2006    66    73   76\n",
+       "2007    44    77   75\n",
+       "2008    70    78   82\n",
+       "2009    69    61   65\n",
+       "2010    75    39   49\n",
+       "2011    51    64   67\n",
+       "2012    67   106  113\n",
+       "2013    53    78   77\n",
+       "2014    59    47   46"
+      ]
+     },
+     "execution_count": 124,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Dry-day diagnostic for precipitation\n",
+    "era5_pr = to_series(load_variable(forcing_path_ERA5, \"pr\")[0])\n",
+    "cmip_pr = to_series(load_variable(forcing_path_CMIP_hist, \"pr\")[0])\n",
+    "qdm_pr = to_series(load_corrected_variable(\"pr\"))\n",
+    "\n",
+    "dry_days = pd.DataFrame({\n",
+    "    \"ERA5\": ((era5_pr * 86400) < 0.1).groupby(era5_pr.index.year).sum(),\n",
+    "    \"CMIP\": ((cmip_pr * 86400) < 0.1).groupby(cmip_pr.index.year).sum(),\n",
+    "    \"QDM\": ((qdm_pr * 86400) < 0.1).groupby(qdm_pr.index.year).sum(),\n",
+    "})\n",
+    "\n",
+    "dry_days\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 125,
+   "id": "4bdfafd5-39a5-41a0-9647-eeb44ce8b894",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_variable_timeseries(var_name, factor=1, start=None, end=None):\n",
+    "\n",
+    "    era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "    cmip_da, _, _ = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "    qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "    era5 = to_series(era5_da) * factor\n",
+    "    cmip = to_series(cmip_da) * factor\n",
+    "    qdm = to_series(qdm_da) * factor\n",
+    "\n",
+    "    if var_name == \"tas\":\n",
+    "        era5 = era5 - 273.15\n",
+    "        cmip = cmip - 273.15\n",
+    "        qdm = qdm - 273.15\n",
+    "\n",
+    "    # Select period\n",
+    "    if start is not None:\n",
+    "        era5 = era5[era5.index >= pd.to_datetime(start)]\n",
+    "        cmip = cmip[cmip.index >= pd.to_datetime(start)]\n",
+    "        qdm = qdm[qdm.index >= pd.to_datetime(start)]\n",
+    "\n",
+    "    if end is not None:\n",
+    "        era5 = era5[era5.index <= pd.to_datetime(end)]\n",
+    "        cmip = cmip[cmip.index <= pd.to_datetime(end)]\n",
+    "        qdm = qdm[qdm.index <= pd.to_datetime(end)]\n",
+    "\n",
+    "    plt.figure(figsize=(12, 5))\n",
+    "    plt.plot(era5.index, era5, label=\"ERA5\")\n",
+    "    plt.plot(cmip.index, cmip, label=\"CMIP\")\n",
+    "    plt.plot(qdm.index, qdm, label=\"QDM\")\n",
+    "    plt.title(var_name)\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 126,
+   "id": "3709b859-a101-4db2-8184-371c7600357a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_variable_timeseries(\n",
+    "    \"pr\",\n",
+    "    factor=86400,\n",
+    "    start=\"2012-05-01\",\n",
+    "    end=\"2012-08-31\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "id": "de19c038-8b47-473e-b6c0-cc9bdd9fe404",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def compare_stats(var_name, factor=1):\n",
+    "\n",
+    "    era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "    cmip_da, _, _ = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "    qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "    era5 = to_series(era5_da) * factor\n",
+    "    cmip = to_series(cmip_da) * factor\n",
+    "    qdm = to_series(qdm_da) * factor\n",
+    "\n",
+    "    stats = pd.DataFrame({\n",
+    "        \"ERA5\": era5.describe(),\n",
+    "        \"CMIP\": cmip.describe(),\n",
+    "        \"QDM\": qdm.describe()\n",
+    "    })\n",
+    "\n",
+    "    return stats"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "id": "d835a397-46ec-4aa5-bc27-edf79756ec00",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>7.305000e+03</td>\n",
+       "      <td>7.305000e+03</td>\n",
+       "      <td>7305.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>1.620587e+00</td>\n",
+       "      <td>1.723259e+00</td>\n",
+       "      <td>1.627803</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>2.418762e+00</td>\n",
+       "      <td>2.675928e+00</td>\n",
+       "      <td>2.508479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-1.665334e-13</td>\n",
+       "      <td>1.174351e-13</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>1.879302e-01</td>\n",
+       "      <td>1.873050e-01</td>\n",
+       "      <td>0.188148</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>7.593266e-01</td>\n",
+       "      <td>7.643056e-01</td>\n",
+       "      <td>0.762794</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>2.028109e+00</td>\n",
+       "      <td>2.214770e+00</td>\n",
+       "      <td>2.038388</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>2.548246e+01</td>\n",
+       "      <td>4.300434e+01</td>\n",
+       "      <td>43.004338</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               ERA5          CMIP          QDM\n",
+       "count  7.305000e+03  7.305000e+03  7305.000000\n",
+       "mean   1.620587e+00  1.723259e+00     1.627803\n",
+       "std    2.418762e+00  2.675928e+00     2.508479\n",
+       "min   -1.665334e-13  1.174351e-13     0.000000\n",
+       "25%    1.879302e-01  1.873050e-01     0.188148\n",
+       "50%    7.593266e-01  7.643056e-01     0.762794\n",
+       "75%    2.028109e+00  2.214770e+00     2.038388\n",
+       "max    2.548246e+01  4.300434e+01    43.004338"
+      ]
+     },
+     "execution_count": 128,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "compare_stats(\"pr\", factor=86400)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "id": "782e5335-f61a-4f59-842b-ca1cec86cdba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_variable_cdf_season(var_name, start_month=5, end_month=10):\n",
+    "\n",
+    "    era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "    cmip_da, _, _ = load_variable(forcing_path_CMIP, var_name)\n",
+    "    qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "    era5 = to_series(era5_da)\n",
+    "    cmip = to_series(cmip_da)\n",
+    "    qdm = to_series(qdm_da)\n",
+    "\n",
+    "    era5 = era5[era5.index.month.isin(range(start_month, end_month + 1))]\n",
+    "    cmip = cmip[cmip.index.month.isin(range(start_month, end_month + 1))]\n",
+    "    qdm = qdm[qdm.index.month.isin(range(start_month, end_month + 1))]\n",
+    "\n",
+    "    if var_name == \"tas\":\n",
+    "        era5 = era5 - 273.15\n",
+    "        cmip = cmip - 273.15\n",
+    "        qdm = qdm - 273.15\n",
+    "        xlabel = \"Temperature (°C)\"\n",
+    "\n",
+    "    elif var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "        era5 = era5 * 86400\n",
+    "        cmip = cmip * 86400\n",
+    "        qdm = qdm * 86400\n",
+    "        xlabel = f\"{var_name} (mm/day)\"\n",
+    "\n",
+    "    elif var_name == \"rsds\":\n",
+    "        xlabel = \"Shortwave radiation (W/m²)\"\n",
+    "    else:\n",
+    "        xlabel = var_name\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    # for name, data in {\"ERA5\": era5, \"CMIP\": cmip, \"QDM\": qdm}.items():\n",
+    "    for name, data in {\"CMIP\": cmip, \"QDM\": qdm, \"ERA5\": era5}.items():\n",
+    "\n",
+    "        values = np.sort(data.dropna().values)\n",
+    "        cdf = np.arange(1, len(values) + 1) / len(values)\n",
+    "\n",
+    "        plt.plot(values, cdf, label=name)\n",
+    "\n",
+    "    plt.xlabel(xlabel)\n",
+    "    plt.ylabel(\"Cumulative probability\")\n",
+    "    plt.title(f\"CDF of {var_name}, months {start_month}-{end_month}\")\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "id": "98ceeada-3d72-4b77-8259-43ed40148b24",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_variable_cdf_season(\"tas\", start_month=5, end_month=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 131,
+   "id": "cc847fac-bb44-41f3-ad17-ffeabc3a2baf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def forcing_summary_for_year(year):\n",
+    "\n",
+    "    variables = [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]\n",
+    "\n",
+    "    rows = []\n",
+    "\n",
+    "    for var_name in variables:\n",
+    "\n",
+    "        era5_da, _, _ = load_variable(forcing_path_ERA5, var_name)\n",
+    "        cmip_da, _, _ = load_variable(forcing_path_CMIP_hist, var_name)\n",
+    "        qdm_da = load_corrected_variable(var_name)\n",
+    "\n",
+    "        era5 = to_series(era5_da)\n",
+    "        cmip = to_series(cmip_da)\n",
+    "        qdm = to_series(qdm_da)\n",
+    "\n",
+    "        # Select year\n",
+    "        era5_y = era5[era5.index.year == year]\n",
+    "        cmip_y = cmip[cmip.index.year == year]\n",
+    "        qdm_y = qdm[qdm.index.year == year]\n",
+    "\n",
+    "        # Unit conversion\n",
+    "        if var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "            era5_y = era5_y * 86400\n",
+    "            cmip_y = cmip_y * 86400\n",
+    "            qdm_y = qdm_y * 86400\n",
+    "            statistic = \"sum mm/year\"\n",
+    "\n",
+    "            rows.append({\n",
+    "                \"variable\": var_name,\n",
+    "                \"statistic\": statistic,\n",
+    "                \"ERA5\": era5_y.sum(),\n",
+    "                \"CMIP\": cmip_y.sum(),\n",
+    "                \"QDM\": qdm_y.sum()\n",
+    "            })\n",
+    "\n",
+    "        elif var_name == \"tas\":\n",
+    "            era5_y = era5_y - 273.15\n",
+    "            cmip_y = cmip_y - 273.15\n",
+    "            qdm_y = qdm_y - 273.15\n",
+    "            statistic = \"mean °C\"\n",
+    "\n",
+    "            rows.append({\n",
+    "                \"variable\": var_name,\n",
+    "                \"statistic\": statistic,\n",
+    "                \"ERA5\": era5_y.mean(),\n",
+    "                \"CMIP\": cmip_y.mean(),\n",
+    "                \"QDM\": qdm_y.mean()\n",
+    "            })\n",
+    "\n",
+    "        elif var_name == \"rsds\":\n",
+    "            statistic = \"mean W/m²\"\n",
+    "\n",
+    "            rows.append({\n",
+    "                \"variable\": var_name,\n",
+    "                \"statistic\": statistic,\n",
+    "                \"ERA5\": era5_y.mean(),\n",
+    "                \"CMIP\": cmip_y.mean(),\n",
+    "                \"QDM\": qdm_y.mean()\n",
+    "            })\n",
+    "\n",
+    "    return pd.DataFrame(rows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 177,
+   "id": "7dfaa301-cb46-4891-9c6c-3af8c65964d4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>statistic</th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP</th>\n",
+       "      <th>QDM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>pr</td>\n",
+       "      <td>sum mm/year</td>\n",
+       "      <td>597.364853</td>\n",
+       "      <td>607.485192</td>\n",
+       "      <td>583.696337</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>tas</td>\n",
+       "      <td>mean °C</td>\n",
+       "      <td>1.458792</td>\n",
+       "      <td>1.674291</td>\n",
+       "      <td>1.379042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>rsds</td>\n",
+       "      <td>mean W/m²</td>\n",
+       "      <td>143.142471</td>\n",
+       "      <td>138.311142</td>\n",
+       "      <td>141.201462</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>evspsblpot</td>\n",
+       "      <td>sum mm/year</td>\n",
+       "      <td>605.052421</td>\n",
+       "      <td>603.664704</td>\n",
+       "      <td>603.770733</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     variable    statistic        ERA5        CMIP         QDM\n",
+       "0          pr  sum mm/year  597.364853  607.485192  583.696337\n",
+       "1         tas      mean °C    1.458792    1.674291    1.379042\n",
+       "2        rsds    mean W/m²  143.142471  138.311142  141.201462\n",
+       "3  evspsblpot  sum mm/year  605.052421  603.664704  603.770733"
+      ]
+     },
+     "execution_count": 177,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "forcing_summary_for_year(2011)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6fb3f02a-ee69-4d00-8d57-02a3eb2ea11c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d64afca3-3f52-430e-8f01-2f9799499a3a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step6_CMIP_History.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step6_CMIP_History.ipynb
new file mode 100644
index 00000000..58e0a532
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step6_CMIP_History.ipynb
@@ -0,0 +1,2946 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9ca8fd44-6292-4af4-9100-d3256fccd960",
+   "metadata": {},
+   "source": [
+    "# Ensemble validation\n",
+    "\n",
+    "The 5 parameter sets calculkated in Calibration_HBV.ipynb will be used for a validation period, in which the log NSE will be calculated, a mean will be calculated and total low flow days during the navigation season.\n",
+    "\n",
+    "The structure of this notebook is as follows:\n",
+    "\n",
+    "### 1. Startup\n",
+    "### 2. Model Setup\n",
+    "### 3. Running model\n",
+    "### 4. LNSE calculation\n",
+    "### 5. Display results\n",
+    "### 6. Lowflow calculation\n",
+    "### 7. Cumsum distribution"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdb4216e-a341-4c2b-a410-35170773a9a7",
+   "metadata": {},
+   "source": [
+    "## 1. Startup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "d197b8f0-0f85-4a41-b2fb-1b2a8cf3f9f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "from scipy.interpolate import interp1d\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "dd7b7d3f-1489-4723-bb51-f3cffcb7a85c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "1c8aee93-b2d6-4291-89ae-1d29e69268cd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "d7dce039-d1f3-44a0-b646-98c32ecffb28",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Choosing time period\n",
+    "\n",
+    "# experiment_start_date = \"2019-01-01T00:00:00Z\"\n",
+    "# experiment_end_date = \"2024-12-31T00:00:00Z\"\n",
+    "\n",
+    "start_year = 1989\n",
+    "end_year = 2014\n",
+    "\n",
+    "validation_start = f\"{start_year}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{end_year}-12-31T00:00:00Z\"\n",
+    "\n",
+    "# Choose CMIP Scenario: \n",
+    "Scenario = \"historical\"    # Options: historical, ssp119, ssp126, ssp245, ssp,370, ssp585\n",
+    "\n",
+    "# Attach colours to scenarios to make plotting easier \n",
+    "colours = {\"historical\": \"tab:blue\", \"ssp126\": \"green\", \"ssp245\": \"orange\", \"ssp370\": \"red\"}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "15ea4507-f559-4ef8-9756-60b8502064d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Create pathways for forcings\n",
+    "\n",
+    "forcing_path_ERA5 = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"forcings\" / \"ERA5\" / f\"ERA5-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_CMIP = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f\"CMIP6-{start_year}-{end_year}\"\n",
+    "\n",
+    "forcing_path_QDM = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / Scenario / f\"CMIP6-QDM-{start_year}-{end_year}\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "46ea8b1e-fb73-49ed-855c-4d95cd932748",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1957-10-01</td>\n",
+       "      <td>467.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1957-10-02</td>\n",
+       "      <td>467.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1957-10-03</td>\n",
+       "      <td>467.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1957-10-04</td>\n",
+       "      <td>476.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1957-10-05</td>\n",
+       "      <td>487.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Date  discharge_m3s\n",
+       "0 1957-10-01          467.0\n",
+       "1 1957-10-02          467.0\n",
+       "2 1957-10-03          467.0\n",
+       "3 1957-10-04          476.0\n",
+       "4 1957-10-05          487.0"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Load CSV discharge 07DA001\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})\n",
+    "\n",
+    "q_obs.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "8bb224ad-d23c-475f-b6af-4a6023a17044",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")\n",
+    "\n",
+    "# Align q_obs to relevant dates\n",
+    "q_obs = q_obs[(q_obs[\"Date\"] >= validation_start_date) & (q_obs[\"Date\"] <= validation_end_date)]\n",
+    "observed_output = pd.Series(data=q_obs[\"discharge_m3s\"].to_numpy(), name=\"Observed discharge\", index=q_obs[\"Date\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "fc27f6f8-e7ff-4be6-b073-05006d25426a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date\n",
+       "1989-01-01    137.0\n",
+       "1989-01-02    141.0\n",
+       "1989-01-03    141.0\n",
+       "1989-01-04    139.0\n",
+       "1989-01-05    135.0\n",
+       "Name: Observed discharge, dtype: float64"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "observed_output.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "7f6f57aa-9f39-4524-ba3a-34f55035ebab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot q_obs\n",
+    "\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "plt.plot(q_obs[\"Date\"], q_obs[\"discharge_m3s\"])\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Discharge (m³/s)\")\n",
+    "plt.title(\"Observed daily discharge at 07DA001\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a48b5085-6478-4cf2-bd02-75b75f82e90f",
+   "metadata": {},
+   "source": [
+    "### Generate/Load CMIP6 data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "77e79b20-3e4d-405a-bd88-16bdc50bdb39",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">LumpedMakkinkForcing</span><span style=\"font-weight: bold\">(</span>\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">start_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'1989-01-01T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">end_time</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2014-12-31T00:00:00Z'</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">directory</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">ngs/CMIP6/historical/CMIP6-1989-2014'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">PosixPath</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile</span>\n",
+       "<span style=\"color: #008000; text-decoration-color: #008000\">s/07DA001_basin.shp'</span><span style=\"font-weight: bold\">)</span>,\n",
+       "    <span style=\"color: #808000; text-decoration-color: #808000\">filenames</span>=<span style=\"font-weight: bold\">{</span>\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'evspsblpot'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1989_2014_evspsblpot.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'pr'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1989_2014_pr.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'rsds'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1989_2014_rsds.nc'</span>,\n",
+       "        <span style=\"color: #008000; text-decoration-color: #008000\">'tas'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'combined_CMIP6_1989_2014_tas.nc'</span>\n",
+       "    <span style=\"font-weight: bold\">}</span>\n",
+       "<span style=\"font-weight: bold\">)</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35mLumpedMakkinkForcing\u001b[0m\u001b[1m(\u001b[0m\n",
+       "    \u001b[33mstart_time\u001b[0m=\u001b[32m'1989-01-01T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mend_time\u001b[0m=\u001b[32m'2014-12-31T00:00:00Z'\u001b[0m,\n",
+       "    \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/forci\u001b[0m\n",
+       "\u001b[32mngs/CMIP6/historical/CMIP6-1989-2014'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/maxime/BEP-maxime/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Shapefile\u001b[0m\n",
+       "\u001b[32ms/07DA001_basin.shp'\u001b[0m\u001b[1m)\u001b[0m,\n",
+       "    \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\n",
+       "        \u001b[32m'evspsblpot'\u001b[0m: \u001b[32m'combined_CMIP6_1989_2014_evspsblpot.nc'\u001b[0m,\n",
+       "        \u001b[32m'pr'\u001b[0m: \u001b[32m'combined_CMIP6_1989_2014_pr.nc'\u001b[0m,\n",
+       "        \u001b[32m'rsds'\u001b[0m: \u001b[32m'combined_CMIP6_1989_2014_rsds.nc'\u001b[0m,\n",
+       "        \u001b[32m'tas'\u001b[0m: \u001b[32m'combined_CMIP6_1989_2014_tas.nc'\u001b[0m\n",
+       "    \u001b[1m}\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate data\n",
+    "# CMIP_dataset = {'dataset': 'MPI-ESM1-2-HR', 'project': 'CMIP6', 'grid' : 'gn', 'exp': 'historical', 'ensemble': 'r1i1p1f1'}\n",
+    "\n",
+    "# CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].generate(\n",
+    "#     dataset=CMIP_dataset,\n",
+    "#    start_time=validation_start,\n",
+    "#    end_time=validation_end,\n",
+    "#    shape=shape_file,\n",
+    "# )\n",
+    "# CMIP_forcing_QDM = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].generate(\n",
+    "#     dataset=CMIP_dataset,\n",
+    "#    start_time=validation_start,\n",
+    "#    end_time=validation_end,\n",
+    "#    shape=shape_file,\n",
+    "# )\n",
+    "\n",
+    "# Load data\n",
+    "\n",
+    "ERA5_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_ERA5)\n",
+    "\n",
+    "CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_CMIP)\n",
+    "\n",
+    "# QDM_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path_QDM)\n",
+    "\n",
+    "print(CMIP_forcing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "09f9dfb3-40c9-4689-98b8-fd1ea8fd72d1",
+   "metadata": {},
+   "source": [
+    "### Load parameter sets & initial storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "ca2be146-1112-4806-a44f-d57ebd4442c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load calibration constants\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]\n",
+    "]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"]          # Snowmelt factor\n",
+    "\n",
+    "# Initial: par_0 = [5.085, 0.55, 100.373, 1.612, 0.545, 3.801, 0.196, 0.00, 0.185]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "d5e5bcb4-bf90-470b-90ed-4a0b9d80c35d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "06c977b4-ba9d-4e82-8415-42180eac9f01",
+   "metadata": {},
+   "source": [
+    "## 2. Model setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "055bdbc8-af1f-41ac-ad1d-b4da4d6785f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config)\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\")\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "650daf1f-e90f-4b5b-aac5-eca8965de7cf",
+   "metadata": {},
+   "source": [
+    "## 3. Running model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "44092959-524a-4330-a274-77cfad0eacd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing)\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Filter observed data by day\n",
+    "    observed_daily = observed_output\n",
+    "    observed_daily.index = pd.to_datetime(observed_daily.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "    ensemble_data['Observed discharge'] = observed_daily\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "079368de-30cf-491f-8cc9-2021f6a4bfa6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ensemble_data_ERA5 = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=ERA5_forcing)\n",
+    "\n",
+    "ensemble_data_CMIP = run_hbv_ensemble(\n",
+    "    par_ensemble=par_ensemble,\n",
+    "    initial_storages=s_0,\n",
+    "    forcing=CMIP_forcing)\n",
+    "\n",
+    "# ensemble_data_QDM = run_hbv_ensemble(\n",
+    "#     par_ensemble=par_ensemble,\n",
+    "#     initial_storages=s_0,\n",
+    "#     forcing=QDM_forcing\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "3d246969-43f4-4702-9932-873cff874d17",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set 1</th>\n",
+       "      <th>Set 2</th>\n",
+       "      <th>Set 3</th>\n",
+       "      <th>Set 4</th>\n",
+       "      <th>Set 5</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Observed discharge</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1989-01-02</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>141.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1989-01-03</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>141.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1989-01-04</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>139.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1989-01-05</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>135.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1989-01-06</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>135.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Set 1  Set 2  Set 3  Set 4  Set 5  Mean  Observed discharge\n",
+       "1989-01-02    0.0    0.0    0.0    0.0    0.0   0.0               141.0\n",
+       "1989-01-03    0.0    0.0    0.0    0.0    0.0   0.0               141.0\n",
+       "1989-01-04    0.0    0.0    0.0    0.0    0.0   0.0               139.0\n",
+       "1989-01-05    0.0    0.0    0.0    0.0    0.0   0.0               135.0\n",
+       "1989-01-06    0.0    0.0    0.0    0.0    0.0   0.0               135.0"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ensemble_data_ERA5.head()\n",
+    "# ensemble_data_CMIP.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "96d6162f-f432-4dfc-9194-f522a2e6a6da",
+   "metadata": {},
+   "source": [
+    "## 4. LNSE Calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "37567a9e-dff3-4c80-84e0-572a6ed72b68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate log NSE\n",
+    "\n",
+    "def LNSE(sim, obs):\n",
+    "    \n",
+    "    sim = sim.to_numpy()\n",
+    "    obs = obs.to_numpy()\n",
+    "\n",
+    "    # Avoid log(0)\n",
+    "    eps = 0.00000000001\n",
+    "\n",
+    "    log_sim = np.log(sim + eps)\n",
+    "    log_obs = np.log(obs + eps)\n",
+    "\n",
+    "    return 1 - np.sum((log_obs - log_sim) ** 2) / np.sum((log_obs - np.mean(log_obs)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "dc7850a4-dc30-4aa7-8719-4f810760c320",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call log NSE for relevant timeperiod\n",
+    "\n",
+    "def lnse_ensemble(ensemble_data, lnse_start, lnse_end):\n",
+    "\n",
+    "    # Select evaluation period - skip first year for storages to fill\n",
+    "    combined_data = ensemble_data[\n",
+    "        (ensemble_data.index >= lnse_start) &\n",
+    "        (ensemble_data.index <= lnse_end)\n",
+    "    ].dropna()\n",
+    "\n",
+    "    # Exclude winter months\n",
+    "    combined_data = combined_data[\n",
+    "        ~combined_data.index.month.isin([12, 1, 2, 3, 4])\n",
+    "    ]\n",
+    "\n",
+    "    lnse_results = []\n",
+    "\n",
+    "    # Calculate LNSE for all sets\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        lnse_value = LNSE(\n",
+    "            combined_data[f\"Set {i+1}\"],\n",
+    "            combined_data[\"Observed discharge\"]\n",
+    "        )\n",
+    "\n",
+    "        # Append LNSE\n",
+    "        lnse_results.append({\n",
+    "            \"Set\": f\"Set {i+1}\",\n",
+    "            \"LNSE\": lnse_value\n",
+    "        })\n",
+    "\n",
+    "    # Calculate LNSE of ensemble mean\n",
+    "    mean_lnse = LNSE(\n",
+    "        combined_data[\"Mean\"],\n",
+    "        combined_data[\"Observed discharge\"]\n",
+    "    )\n",
+    "\n",
+    "    # Append LNSE\n",
+    "    lnse_results.append({\n",
+    "        \"Set\": \"Ensemble mean\",\n",
+    "        \"LNSE\": mean_lnse\n",
+    "    })\n",
+    "\n",
+    "    lnse_results = pd.DataFrame(lnse_results)\n",
+    "\n",
+    "    return lnse_results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "80962ebd-6ad7-48ce-b378-acd68ed03a1e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# lnse_results_ERA5 = lnse_ensemble(\n",
+    "#     ensemble_data=ensemble_data_ERA5,\n",
+    "#     lnse_start=evaluation_start,\n",
+    "#     lnse_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# lnse_results_CMIP = lnse_ensemble(\n",
+    "#     ensemble_data=ensemble_data_CMIP,\n",
+    "#     lnse_start=evaluation_start,\n",
+    "#     lnse_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# lnse_results_QDM = lnse_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     lnse_start=evaluation_start,\n",
+    "#     lnse_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# lnse_results_CMIP\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9b6a719-39c6-4872-87ff-cdb65d853e42",
+   "metadata": {},
+   "source": [
+    "## 5. Display results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "f519854a-a994-44fd-a428-4d0c6daa98e1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_ensemble(ensemble_data, plot_start, plot_end):\n",
+    "\n",
+    "    plot_start = pd.to_datetime(plot_start)\n",
+    "    plot_end = pd.to_datetime(plot_end)\n",
+    "\n",
+    "    # Filter data to start & end time\n",
+    "    plot_data = ensemble_data[\n",
+    "        (ensemble_data.index >= plot_start) &\n",
+    "        (ensemble_data.index <= plot_end)\n",
+    "    ].dropna()\n",
+    "\n",
+    "    # Define figure\n",
+    "    plt.figure()\n",
+    "    plt.figure(figsize=(20, 8))\n",
+    "\n",
+    "    # Plot sets, observed data, ensemble mean and axhline, respectively\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "        plt.plot(plot_data.index, plot_data[f\"Set {i+1}\"], color=\"orange\", alpha=0.3, label=\"Parameter sets\" if i == 0 else None)\n",
+    "\n",
+    "    plt.plot(plot_data.index, plot_data[\"Observed discharge\"], label=\"Observed discharge\", linewidth=3)\n",
+    "    plt.plot(plot_data.index, plot_data[\"Mean\"], label=\"Ensemble mean\", linewidth=3)\n",
+    "    plt.axhline(y=q_critical, linestyle=\":\", color=\"black\", label=f\"Critical discharge ({q_critical} m³/s)\")\n",
+    "\n",
+    "    # Extras\n",
+    "    plt.xlabel(\"Date\")\n",
+    "    plt.ylabel(\"Discharge (m³/s)\")\n",
+    "    plt.title(\"Observed vs modelled ensemble discharge at 07DA001\")\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "f1bb58f8-3dee-43eb-abc8-4af333b5d064",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Plot for full evaluation period\n",
+    "\n",
+    "# plot_ensemble_ERA5 = plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_ERA5,\n",
+    "#     plot_start=evaluation_start,\n",
+    "#     plot_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# plot_ensemble_CMIP = plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_CMIP,\n",
+    "#     plot_start=evaluation_start,\n",
+    "#     plot_end=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "# plot_ensemble_QDM = plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     plot_start=evaluation_start,\n",
+    "#     plot_end=validation_end_date\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "b835010a-b272-46b7-9c20-b0db1a99506b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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iIqqImNNLRERE9JQTHpfmkV79PnLkSNHysGHDIJfLceDAAQBAixYtoFQqMXHiRHz33Xe4ffu20b537NgBd3d3DBgwAGq12vDVokUL+Pn5GZXzCQkJQcOGDUXrvLy8MGDAAHz33XfQarUAgOTkZPz5558YPXq0oeRaUR9LP39zz68wzZo1Q6tWrURZIJGRkTh16pSobE/btm1x/vx5TJ48GX///TfS0tIK3Xd+/fv3Fy0HBwcDgFHT8+DgYCQlJRnKk+mzN6TZHkOHDoWTk5OhPFJxjsOOHTvQvXt3VK9eXXRs9T0lDh06VOTndfPmTVy9etXwuPn3169fP8TFxeHatWuGOfbo0QO+vr6G7W1tbfHSSy9Z9HH0nn/+edGy/kp8fVkla7zmW7RogRo1ahiW9d/nbt26wdHR0Wi9tMQTYPw9HDFiBIAn32NTduzYgaZNm6JFixaieYaFhZkstZXf8ePHkZOTY/S4HTp0EGU9mNO2bVts3LgRixYtwokTJ4xKzR07dgxpaWmYPHlygVk5gO5za8CAAaJ1ISEhRsdp//796NmzJ9zc3GBrawuFQoF58+YhMTERDx8+NNpe+jl06NAhNG3a1NBnRG/48OFGc09KSsKYMWNEx1Wr1aJPnz44ffp0oaXffv31V3Ts2BHOzs6Qy+VQKBRYt24dIiMjC9yuKMwdz4KO87p16+Dl5YUXXnih2I8nSEq/AcCGDRug1WpFn5fjxo1DZmamUS+ZwuaW/76ijiMiIiJ6GjEQQ0RERFRBeXt7w9HREVFRUQWOi46OhqOjIzw9PUXr/fz8RMtyuRxeXl6G8kH16tXD3r174ePjgylTphgaPOfvgfLgwQOkpKRAqVRCoVCIvuLj4/Ho0SPRY/j7+5uc47hx43Dv3j3s2bMHgK4MWG5urijYUNTH0s/f3PMrinHjxuH48eO4evUqAN2JRTs7O9FJ2dmzZ2P58uU4ceIE+vbtCy8vL/To0cNsnw8p6fdDqVQWuD4nJ8fw/ORyOapVqyYaJ5PJ4OfnZ3j+xTkODx48wF9//WV0XJs0aQIARt/Hgjx48AAAMHPmTKP9TZ48WbS/xMREo/mZmnNpH0dP+rz1Jdyys7MBWOc1X9Lvs56p75f++OQv9WXq+Fy4cMFoji4uLhAEocDvqbnXjrl1Uj///DPGjBmDb7/9Fu3bt4enpydGjx6N+Ph4ADD00jFXUjE/R0dH2Nvbi9bZ2dmJjtOpU6fQu3dvAMA333yDo0eP4vTp0/jwww8BPPn+6pn6HEpMTBQFBPWk6/SvuyFDhhgd288++wyCICApKcns89m6dSuGDRuGGjVq4Mcff8Tx48dx+vRpjBs3zuh7Xxz614ip10RSUpLR603vwoULOHPmDF555RXD+6E49AGx6tWrA9CVkNy4cSOqV6+OVq1aISUlBSkpKejZsyecnJywbt26Is9ZJpPB3d3dMDYnJ8dkb6SCnh8RERHR04I9YoiIiIgqKFtbW3Tv3h3h4eGIjY01eVIzNjYWZ8+eRd++fUX9YQBdX5D8V+qr1WokJiaKTvp27twZnTt3hkajwZkzZ7B69WpMnz4dvr6+ePnllw1Nz8PDw03O0cXFRbRs7qrlsLAwVK9eHRs2bEBYWBg2bNiAdu3aia5OL+pj6edv7vkVxfDhw/HOO+9g48aN+OSTT/DDDz9g0KBB8PDwMIyRy+V455138M477yAlJQV79+7FBx98gLCwMNy9e1eU7WBJXl5eUKvVSEhIEAVjBEFAfHw82rRpYxgHFO04eHt7IyQkBJ988onJx9SfZC0Kb29vALpA1eDBg02O0fcY8fLyMpycz8/UutI8TnFY+jVfWqbel/rjU1Bg0dvbGw4ODli/fr3Z+83J/9qRio+PR2BgYIFz9vb2xsqVK7Fy5UrExMRg+/bteP/99/Hw4UOEh4cbXrexsbEF7qeotmzZAoVCgR07doiCNvkbuOdn6nPIy8vLEGTJT3oM9Mdt9erVeOaZZ0zu31RAR+/HH39EnTp18PPPP4vmkZuba3abotD3Trl48aLoc1OtVuPq1atGmT16+sDIa6+9VqLH3b59O2QyGbp06QIA2Lt3ryE4Y+r1eeLECVy5cgWNGzdGvXr14ODggIsXLxqNu3jxIurXr2/4fuZ/fu3atTOM0wc/mzZtWqL5ExEREVUUDMQQERERVWCzZ8/Grl27MHnyZGzbtk0UbNFoNHjjjTcgCAJmz55ttO2mTZvQqlUrw/Ivv/wCtVqNbt26GY21tbVFu3bt0KhRI2zatAnnzp3Dyy+/jP79+2PLli3QaDSik2PFZWtri1GjRmHlypU4cuQIzpw5g6+//lo0pqiPpZ+/uedXFB4eHhg0aBC+//57tG/fHvHx8aIyO1Lu7u4YMmQI7t27h+nTpyM6OtqoxJGl9OjRA0uXLsWPP/6It99+27D+999/R2ZmpqFReHGOQ//+/bFz507Uq1dPFGwqiaCgIDRo0ADnz5/H4sWLCxzbvXt3bN++HQ8ePDCcvNZoNCbLF5XmcUrC2q/54ti0aROmTZtmWP7pp58AwOR7Va9///5YvHgxvLy8it2A/ZlnnoG9vT02bdqEF1980bD+2LFjuHPnTqGBmPxq166NqVOnYt++fTh69CgAXYkzNzc3rF27Fi+//HKpy0rJZDLI5XLR5192djZ++OGHIu+ja9euWL58uSFIoLdlyxbRuI4dO8Ld3R1XrlzB1KlTSzRXpVIpes7x8fH4888/jcba2dkZZfOY065dO/j7+2Pjxo2i0n6//fYbMjIyTAYrc3Nz8eOPP6Jt27YlCmRs2LABu3btwogRI1C7dm0AusCOjY0Ntm7dCjc3N9H42NhYjBo1CuvXr8fy5cshl8sxYMAAbN26FUuXLjUEMWNiYnDgwAHR51ufPn1gb2+PjRs3it53GzduhEwmw6BBg4o9fyIiIqKKhIEYIiIiogqsY8eOWLlyJaZPn45OnTph6tSpqF27NmJiYvDll1/i5MmTWLlyJTp06GC07datWyGXy9GrVy9cvnwZc+fORfPmzTFs2DAAwNq1a7F//34899xzqF27NnJycgxX1/fs2RMA8PLLL2PTpk3o168f3nrrLbRt2xYKhQKxsbE4cOAABg4cWOS+A+PGjcNnn32GESNGwMHBwahPSFEfKzg4GK+88gpWrlwJhUKBnj174tKlS1i+fDlcXV2LfGzHjRuHn3/+GVOnTkXNmjUNz1lvwIABaNq0KVq3bo1q1arhzp07WLlyJQICAtCgQYMiP05x9erVC2FhYZg1axbS0tLQsWNHXLhwAfPnz0doaChGjRoFAMU6Dh999BH27NmDDh06YNq0aQgKCkJOTg6io6Oxc+dOrF27tkhlpPS+/vpr9O3bF2FhYRg7dixq1KiBpKQkREZG4ty5c/j1118BAHPmzMH27dvx7LPPYt68eXB0dMSXX35ZaI+N4j5OUZX1a74olEolPv/8c2RkZKBNmzY4duwYFi1ahL59+6JTp05mt5s+fTp+//13dOnSBW+//TZCQkKg1WoRExOD3bt3Y8aMGWYDSR4eHpg5cyYWLVqE1157DUOHDsXdu3exYMGCQkuTpaamonv37hgxYgQaNWoEFxcXnD59GuHh4YZggLOzMz7//HO89tpr6NmzJyZMmABfX1/cvHkT58+fx3//+99iHaPnnnsO//nPfzBixAhMnDgRiYmJWL58ebFKbU2fPh3r169H37598dFHH8HX1xc//fSToTyhjY2NYe6rV6/GmDFjkJSUhCFDhsDHxwcJCQk4f/48EhISsGbNGrOP079/f2zduhWTJ0/GkCFDcPfuXXz88cfw9/fHjRs3RGObNWuGgwcP4q+//oK/vz9cXFzMZnnZ2tpi6dKlGDVqFCZNmoThw4fjxo0beO+999CrVy/06dPHaJs//vgDSUlJhWbDZGdn48SJE4bbt2/fxh9//IEdO3aga9euWLt2LQBdibE///wTYWFhGDhwoMl9rVixAt9//z2WLFkChUKBhQsXok2bNujfvz/ef/995OTkYN68efD29saMGTMM23l6emLOnDmYO3cuPD090bt3b5w+fRoLFizAa6+9ZhT4/u233wDA0OfpzJkzcHZ2BqArK0dERERU4QhEREREVOEdP35cGDJkiODr6yvI5XLBx8dHGDx4sHDs2DGjsfPnzxcACGfPnhUGDBggODs7Cy4uLsLw4cOFBw8eiPb5wgsvCAEBAYKdnZ3g5eUldO3aVdi+fbtofyqVSli+fLnQvHlzwd7eXnB2dhYaNWokTJo0Sbhx44ZhXEBAgPDcc88V+Dw6dOggABBGjhxp8v6iPlZubq4wY8YMwcfHR7C3txeeeeYZ4fjx40JAQIAwZsyYohxSQaPRCLVq1RIACB9++KHR/Z9//rnQoUMHwdvbW1AqlULt2rWF8ePHC9HR0QXu98CBAwIA4ddffxWt37BhgwBAOH36tGi9/vuVkJBgWJednS3MmjVLCAgIEBQKheDv7y+88cYbQnJysmjb4hyHhIQEYdq0aUKdOnUEhUIheHp6Cq1atRI+/PBDISMjwzAOgDB//nyj53PgwAHR/s6fPy8MGzZM8PHxERQKheDn5yc8++yzwtq1a0Xjjh49KjzzzDOCnZ2d4OfnJ7z77rvC//3f/wkAhKioqAKPZVEfx9yxlc69rF7zAIQpU6aI1kVFRQkAhGXLlhnWjRkzRnBychIuXLggdOvWTXBwcBA8PT2FN954Q/Q90T+W9HuakZEhzJkzRwgKChKUSqXg5uYmNGvWTHj77beF+Pj4Ao+rVqsVlixZItSqVUtQKpVCSEiI8Ndffwldu3YVunbtajTvDRs2CIIgCDk5OcLrr78uhISECK6uroKDg4MQFBQkzJ8/X8jMzBQ9xs6dO4WuXbsKTk5OgqOjo9C4cWPhs88+M3r+Uvr3RH7r168XgoKCBDs7O6Fu3brCkiVLhHXr1hm9jgr6HLp06ZLQs2dPwd7eXvD09BTGjx8vfPfddwIA4fz586Kxhw4dEp577jnB09NTUCgUQo0aNYTnnnvO6H1tyqeffioEBgYKdnZ2QnBwsPDNN9+YfE4RERFCx44dBUdHRwGA6Lib89NPPwkhISGCUqkU/Pz8hGnTpgnp6ekmx/bq1UtwcnIS0tLSzO6va9euAgDDl5OTk1C3bl1hyJAhwq+//ipoNBrD2JUrVwoAhD/++MPs/tauXSsAEH7//XfDujNnzgg9evQQHB0dBVdXV2HQoEHCzZs3TW7/xRdfCA0bNjR85s6fP1/Iy8szGpd/ztIvIiIioopIJgiCUAbxHiIiIiIiIqIKZeLEidi8eTMSExOhVCrLezpEREREVEmxNBkRERERERFVeh999BGqV6+OunXrIiMjAzt27MC3336LOXPmMAhDRERERFbFQAwRERERERFVegqFAsuWLUNsbCzUajUaNGiA//znP3jrrbfKe2pEREREVMmxNBkREREREREREREREZGV2JT3BIiIiIiIiIiIiIiIiCorBmKIiIiIiIiIiIiIiIishIEYIiIiIiIiIiIiIiIiK5GX9wSeFlqtFvfv34eLiwtkMll5T4eIiIiIiIiIiIiIiMqRIAhIT09H9erVYWNjPu+FgZgiun//PmrVqlXe0yAiIiIiIiIiIiIiogrk7t27qFmzptn7GYgpIhcXFwC6A+rq6lrOs6k4VCoVdu/ejd69e0OhUJT3dIiqPL4niZ4efL8SPT34fiV6evH9S/T04PuV6OnB9+sTaWlpqFWrliF+YA4DMUWkL0fm6urKQEw+KpUKjo6OcHV1rfJvOqKKgO9JoqcH369ETw++X4meXnz/Ej09+H4lenrw/WqssHYm5ouWERERERERERERERERUakwEENERERERERERERERGQlDMQQERERERERERERERFZCXvEEBEREREREREREVmARqOBSqUq72kQWZVKpYJcLkdOTg40Gk15T8eqbG1tIZfLC+0BUxgGYoiIiIiIiIiIiIhKKSMjA7GxsRAEobynQmRVgiDAz88Pd+/eLXWA4mng6OgIf39/KJXKEu+DgRgiIiIiIiIiIiKiUtBoNIiNjYWjoyOqVatWJU5OU9Wl1WqRkZEBZ2dn2NhU3u4ngiAgLy8PCQkJiIqKQoMGDUr8fBmIISIiIiIiIiIiIioFlUoFQRBQrVo1ODg4lPd0iKxKq9UiLy8P9vb2lToQAwAODg5QKBS4c+eO4TmXROU+SkRERERERERERERlhJkwRJWPJYJNDMQQERERERERERERERFZCQMxREREREREREREREREVsJADBERERERERERERERkZUwEENERERERERERERUBY0dOxYymQwymQwKhQJ169bFzJkzkZmZWd5TK7HAwECsXLmyvKdhUnR0NGQyGSIiIsp7KlTG5OU9ASIiIiIiIiIiIiIqH3369MGGDRugUqlw5MgRvPbaa8jMzMSaNWuKvS9BEKDRaCCXP/2nnfPy8qBUKst7GlRJMCOGiIiIiIiIiIiIyNK0mvL5KiY7Ozv4+fmhVq1aGDFiBEaOHIk//vgDAPDjjz+idevWcHFxgZ+fH0aMGIGHDx8atj148CBkMhn+/vtvtG7dGnZ2djhy5Ahu3bqFgQMHwtfXF87OzmjTpg327t0retzAwEAsWrQIo0ePhrOzMwICAvDnn38iISEBAwcOhLOzM5o1a4YzZ86Itjt27Bi6dOkCBwcH1KpVC9OmTTNk8HTr1g137tzB22+/bcj0Kcp2+eczduxYuLm5YcKECSaP12+//YZmzZrBwcEBXl5e6Nmzp2g/GzZsQHBwMOzt7dGoUSN89dVXhvvq1KkDAAgNDYVMJkO3bt0Mx7Ft27ZwcnKCu7s7OnbsiDt37hT1W0hPgac/NElERERERERERERUkWg1wP2d5fPY1fsBNrYl3tzBwQEqlQqALivk448/RlBQEB4+fIi3334bY8eOxc6d4uf23nvvYfny5ahbty7c3d0RGxuLfv36YdGiRbC3t8d3332HAQMG4Nq1a6hdu7ZhuxUrVmDx4sWYO3cuVqxYgVGjRqFjx44YN24cli1bhlmzZmH06NG4fPkyZDIZLl68iLCwMHz88cdYt24dEhISMHXqVEydOhUbNmzA1q1b0bx5c0ycOFEUSClsO71ly5Zh7ty5mDNnjsljExcXh+HDh2Pp0qV44YUXkJ6ejiNHjkAQBADAN998g/nz5+O///0vQkND8e+//2LChAlwcnLCmDFjcOrUKbRt2xZ79+5FkyZNoFQqoVarMWjQIEyYMAGbN29GXl4eTp06JQoi0dOPgRgiIiIiIiIiIiIiwqlTp/DTTz+hR48eAIBx48YZ7qtbty5WrVqFtm3bIiMjA87Ozob7PvroI/Tq1cuw7OXlhebNmxuWFy1ahG3btmH79u2YOnWqYX2/fv0wadIkAMC8efOwZs0atGnTBkOHDgUAzJo1C+3bt8eDBw/g5+eHZcuWYcSIEZg+fToAoEGDBli1ahW6du2KNWvWwNPTE7a2toYMHr3CtrO3twcAPPvss5g5c6bZ4xMXFwe1Wo3BgwcjICAAANCsWTPD/R9//DE+//xzDB48GIAuA+bKlSv4+uuvMWbMGFSrVs1wfPTzS0pKQmpqKvr374969eoBAIKDg83OgZ5ODMQQERERERERERERWZKNrS4zpbweuxh27NgBZ2dnqNVqqFQqDBw4EKtXrwYA/Pvvv1iwYAEiIiKQlJQErVYLAIiJiUHjxo0N+2jdurVon5mZmVi4cCF27NiB+/fvQ61WIzs7GzExMaJxISEhhtu+vr4AxIEN/bqHDx/Cz88PZ8+exc2bN7Fp0ybDGEEQoNVqERUVZTaAUdTtpM9Dqnnz5ujRoweaNWuGsLAw9O7dG0OGDIGHhwcSEhJw9+5djB8/XpSNo1ar4ebmZnafnp6eGDt2LMLCwtCrVy/07NkTw4YNg7+/f4FzoacLAzFEREREREREREREllaK8mBlqXv37lizZg0UCgWqV68OhUIBQBdM6d27N3r37o0ff/wR1apVQ0xMDMLCwpCXlyfah5OTk2j53Xffxd9//43ly5ejfv36cHBwwJAhQ4y20z8WAEMpLlPr9AEgrVaLSZMmYdq0aUbPI3/JM6mibid9HlK2trbYs2cPjh07ht27d2P16tX48MMPcfLkSTg6OgLQlSdr166d0XYF2bBhA6ZNm4bw8HD8/PPPmDNnDvbs2YNnnnmmwO3o6cFADBEREREREREREVEV5eTkhPr16xutv3r1Kh49eoRPP/0UtWrVAgCcOXOmSPs8cuQIxo4dixdeeAEAkJGRgejo6FLPtWXLlrh8+bLJ+eoplUpoNJpib1dUMpkMHTt2RMeOHTFv3jwEBARg27ZteOedd1CjRg3cvn0bI0eONDs3AEbzA4DQ0FCEhoZi9uzZaN++PX766ScGYioRm/KeABERERERERERERFVLLVr14ZSqcTq1atx+/ZtbN++HR9//HGRtq1fvz62bt2KiIgInD9/HiNGjDBktZTGrFmzcPz4cUyZMgURERG4ceMGtm/fjjfffNMwJjAwEIcPH8a9e/fw6NGjIm9XFCdPnsTixYtx5swZxMTEYOvWrUhISDCUNluwYAGWLFmCL774AtevX8fFixexYcMG/Oc//wEA+Pj4wMHBAeHh4Xjw4AFSU1MRFRWF2bNn4/jx47hz5w52796N69evs09MJcNADBERERERERERERGJVKtWDRs3bsSvv/6Kxo0b49NPP8Xy5cuLtO2KFSvg4eGBDh06YMCAAQgLC0PLli1LPaeQkBAcOnQIN27cQOfOnREaGoq5c+eK+ql89NFHiI6ORr169VCtWrUib1cUrq6uOHz4MPr164eGDRtizpw5+Pzzz9G3b18AwGuvvYZvv/0WGzduRLNmzdC1a1ds3LgRderUAQDI5XKsWrUKX3/9NapXr46BAwfC0dERV69exYsvvoiGDRti4sSJmDp1KiZNmlTq40UVh0wQBKG8J/E0SEtLg5ubG1JTU+Hq6lre06kwVCoVdu7ciX79+onqNxJR+eB7kujpwfcr0dOD71eipxffv0RPj6f9/ZqTk4OoqCjUqVMH9vb25T0dIqvSarVIS0uDq6srbGwqf65HQe/vosYNKv9RIiIiIiIqRFxqNg5fT0Bqtqq8p0JERERERESVjLy8J0BEREREVJ7O303ByG9PIiNXDT9Xe2x/syN8XHgVIxEREREREVkGM2KIiIiIqEr76WQMMnLVAID4tBxsj7hfzjMiIiIiIiKiyoSBGCIiIiKq0u4mZ4mWY5KyzIwkIiIiIiIiKj4GYoiIiIioSkvKzBMtP8rILaeZEBERERERUWXEQAwRERERVWnJWZJATHqemZFERERERERExcdADBERERFVWYIgIDlTJVrHjBgiIiIiIiKyJAZiiIiIiKjKyshVI0+jFa1LYCCGiIiIiIiILIiBGCIiIiKqsqTZMACQnqNGjkpTDrMhIiIiIiKiyoiBGCIiIiKqspKyTPeDScxknxgiIiIiovwCAwOxcuXK8p6GxZTk+YwdOxaDBg0yLHfr1g3Tp08v9Vyio6Mhk8kQERFR6n1RxcRADBERERFVWclmAi4J6SxPRkRERERVw927dzF+/HhUr14dSqUSAQEBeOutt5CYmFjeU6vwtm7dio8//ri8p0FPAXl5T4CIiIiIqLwkmQnEPGIghoiIiIhKSKsVkGwm87qseDgqYWMjK3Tc7du30b59ezRs2BCbN29GnTp1cPnyZbz77rvYtWsXTpw4AU9PzzKYsTGNRgOZTAYbm4qbS1Bex6ao8vLyoFQqy3saBAZiiIiIiKgKMxuIyWAghoiIiIhKJjkrD60W7S3XOZyd0xNeznaFjpsyZQqUSiV2794NBwcHAEDt2rURGhqKevXq4cMPP8SaNWsM49PT0zFixAhs374drq6umD17Nt58803D/QsWLMD69evx4MEDeHl5YciQIVi1ahUAXVBgzpw52LRpE1JSUtC0aVN89tln6NatGwBg48aNmD59On788Ue89957uH79Or788ku89dZbiI+Ph7u7u+Fxpk2bhvPnz+PQoUMAgGPHjuH999/H6dOn4e3tjRdeeAFLliyBk5MTAODhw4cYP3489u7dCz8/PyxatKjQY6PRaPDuu+9i/fr1sLW1xfjx4yEIgmhMt27d0KJFC0OJs6+++gorVqzA3bt34ebmhs6dO+O3334DAGi1WixbtgzffPMN7t69C19fX0yaNAkffvihYX+3b9/G22+/jZMnT6JBgwZYu3Yt2rdvDwBITEzE1KlTceTIESQlJaFevXr44IMPMHz4cNF8mjZtCqVSie+//x5NmjTBoUOHsH37dsyYMQOxsbF45plnMHbsWIwdOxbJycmG41rYMaTSqbjhRCIiIiIiKzPXI4aBGCIiIiKq7JKSkvD3339j8uTJhiCMnp+fH0aOHImff/5ZFHxYtmwZQkJCcO7cOcyePRtvv/029uzZAwD47bffsGLFCnz99de4ceMG/vjjDzRr1syw7auvvoqjR49iy5YtuHDhAoYOHYo+ffrgxo0bhjFZWVlYsmQJvv32W1y+fBmvvPIK3N3d8fvvvxvGaDQa/PLLLxg5ciQA4OLFiwgLC8PgwYNx4cIF/Pzzz/jnn38wdepUwzZjx45FdHQ09u/fj99++w1fffUVHj58WODx+fzzz7F+/XqsW7cO//zzD5KSkrBt2zaz48+cOYNp06bho48+wrVr1xAeHo4uXboY7p89ezY+++wzzJ07F1euXMFPP/0EX19f0T4+/PBDzJw5ExEREWjYsCGGDx8OtVoNAMjJyUGrVq2wY8cOXLp0CRMnTsSoUaNw8uRJ0T6+++47yOVyHD16FF9//TWio6MxZMgQDBo0CBEREUbBn6IeQyodZsQQERERUZVlrkfMo4zyLSVBRERERGRtN27cgCAICA4ONnl/cHAwkpOTkZCQAB8fHwBAx44d8f777wMAGjZsiKNHj2LFihXo1asXYmJi4Ofnh549e0KhUKB27dpo27YtAODWrVvYvHkzYmNjUb16dQDAzJkzER4ejg0bNmDx4sUAAJVKha+++grNmzc3zOOll17CTz/9hPHjxwMA9u3bh+TkZAwdOhSALjg0YsQITJ8+HQDQoEEDrFq1Cl27dsWaNWsQExNjKLPWrl07AMC6devMPm+9lStXYvbs2XjxxRcBAGvXrsXff/9tdnxMTAycnJzQv39/uLi4ICAgAKGhoQB0mURffPEF/vvf/2LMmDEAgHr16qFTp06ifcycORPPPfccAGDhwoVo0qQJbt68iUaNGqFGjRqYOXOmYeybb76J8PBw/Prrr4bnBQD169fH0qVLDcvvv/8+goKCsGzZMgBAUFAQLl26hE8++cQwprBjaG9vX+CxosIxI4aIiIiIqixzpckSmBFDRERERFWcPhNGJnvSa0ZfJiv/cmRkJABg6NChyM7ORt26dTFhwgRs27bNkM1x7tw5CIKAhg0bwtnZ2fB16NAh3Lp1y7A/pVKJkJAQ0WOMHDkSBw8exP379wEAmzZtQr9+/eDh4QEAOHv2LDZu3Cjab1hYGLRaLaKiohAZGQm5XI7WrVsb9tmoUSNRqTOp1NRUxMXFiZ6vdB9SvXr1QkBAAOrWrYtRo0Zh06ZNyMrKAgBERkYiNzcXPXr0MLs9ANFz9/f3BwBD5o5Go8Enn3yCkJAQeHl5wdnZGbt370ZMTIxoH9I5Xrt2DW3atBGt0wfI9Ao7hlR6zIghIiIioirLbI+YdAZiiIiIiKhkPByVODunZ7nPoTD169eHTCbDlStXMGjQIKP7r169Cg8PD3h7exe4H32gplatWrh27Rr27NmDvXv3YvLkyVi2bBkOHToErVYLW1tbnD17Fra2tqLtnZ2dDbcdHBxEgR9AFzSoV68etmzZgjfeeAPbtm3Dhg0bDPdrtVpMmjQJ06ZNM5pb7dq1ce3aNdE8rcXFxQXnzp3DwYMHsXv3bsybNw8LFizA6dOnjUq/maNQKAy39fPVarUAdKXSVqxYgZUrV6JZs2ZwcnLC9OnTkZcn/ptG2tNFEASj5y7tdVPYMaTSYyCGiIiIiKos9oghKr2UrDy8/XMETtxOQs/Gvvh8aHMo5Sy+QEREVZeNjQxeznblPY1CeXl5oVevXvjqq6/w9ttvi4IF8fHx2LRpE0aPHi06iX/ixAnRPk6cOIFGjRoZlh0cHPD888/j+eefx5QpU9CoUSNcvHgRoaGh0Gg0ePjwITp37lzsuY4YMQKbNm1CzZo1YWNjYyjfBQAtW7bE5cuXUb9+fZPbBgcHQ61W48yZM4ZMkGvXriElJcXs47m5ucHf3x8nTpww9HlRq9U4e/YsWrZsaXY7uVyOnj17omfPnpg/fz7c3d2xf/9+9OvXDw4ODti3bx9ee+21Yj9/ADhy5AgGDhyIV155BYAueHLjxo1CS6w1atQIO3fuFK07c+aMaLmwY0ilx9+OiYiIiKjKYo8YotIRBAFv/xyBA9cSkK3S4K/z9/Hz6ZjCNyQiIqIK4b///S9yc3MRFhaGw4cP4+7duwgPD0evXr1Qo0YNUR8RADh69CiWLl2K69ev48svv8Svv/6Kt956CwCwceNGrFu3DpcuXcLt27fxww8/wMHBAQEBAWjYsCFGjhyJ0aNHY+vWrYiKisLp06fx2WefGQUJTBk5ciTOnTuHTz75BEOGDBH1LJk1axaOHz+OKVOmICIiAjdu3MD27dvx5ptvAtD1ROnTpw8mTJiAkydP4uzZs3jttdcKzVJ566238Omnn2Lbtm24evUqJk+eXGDwZseOHVi1ahUiIiJw584dfP/999BqtQgKCoK9vT1mzZqF9957D99//z1u3bqFEydOYN26dYU+d7369etjz549OHbsGCIjIzFp0iTEx8cXut2kSZNw9epVzJo1C9evX8cvv/yCjRs3AniSdVPYMaTSYyCGiIiIiKokjVZASrbK5H2p2SrkqbVlPCOip88PJ+7gwLUE0TrpMhEREVVcDRo0wJkzZ1CvXj289NJLqFevHiZOnIju3bvj+PHj8PT0FI2fMWMGzp49i9DQUHz88cf4/PPPERYWBgBwd3fHN998g44dOyIkJAT79u3DX3/9BS8vLwDAhg0bMHr0aMyYMQNBQUF4/vnncfLkSdSqVatI82zTpg0uXLiAkSNHiu4LCQnBoUOHcOPGDXTu3BmhoaGYO3euoceK/rFr1aqFrl27YvDgwZg4cSJ8fHwKfMwZM2Zg9OjRGDt2LNq3bw8XFxe88MILZse7u7tj69atePbZZxEcHIy1a9di8+bNaNKkCQBg7ty5mDFjBubNm4fg4GC89NJLhv4vRTF37ly0bNkSYWFh6NatG/z8/EyWlJOqU6cOfvvtN2zduhUhISFYs2YNPvzwQwCAnZ0uc6sox5BKRyZIC8KRSWlpaXBzc0NqaipcXV3LezoVhkqlws6dO9GvXz9RDUMiKh98TxI9Pfh+LX9JmXlo+fEes/cfn/0s/N2KVsuZKje+X027/iAdA1b/g1xJ0NLVXo6Ieb1hY2PdOuxERcH3L9HT42l/v+bk5CAqKgp16tQRZWsQVUSffPIJ1q5di7t375Zoe61Wi7S0NLi6usLGpvLnehT0/i5q3KDyHyUiIiIiIhOSMgvuA/MoneXJiMzJVWswbfO/RkEYAEjLUePag/RymBURERERmfLVV1/h9OnThpJxy5Ytw5gxY8p7WlWKvLwnQERERERUHpIyTZcl03uUUXCghqgqWxZ+DVfjzQdbzkQnIdiflQSIiIiIKoIbN25g0aJFSEpKQu3atTFjxgzMnj27vKdVpTAQQ0RERERVUlJmwRkvCQzEEJkUGZeGb/+JKnDMqehkjGofWDYTIiIiIqICrVixAitWrCjvaVRpLE1GRERERFVSclbBgRhmxBCZtvvyA9GyUm6DsR0CRetORyWB7UiJiIiIiHQYiCEiIiKiKqmwjBj2iCEyTRqkfL55dbzyTIBoXXxaDmKTs8tyWkREREREFRYDMURERERUJRUaiGFGDJFJSZJsMh8XO9Sr5gRPJ6Vo/enopLKcFhERERFRhcVADBERERFVScmSQIzCViZaZiDGulQaLdJzVCxf9RRKkQRiPByVkMlkaB3gIVrPQAwRERERkQ4DMURERERUJUmv6q/r7SxaZiDGeq7Fp+PZzw+i2YLdmLzpHNQabXlPiYohOVMlWvZ4nAnTto6naP2pKAZiiIiIiIgABmKIiIiIqIqSZsQ08JUGYtgjxlpW77+Bu0m6/iG7LsXjyI1H5TwjKo5ko4wYBQCgdaA4EHMrIROJDGgSERERETEQQ0RERERVU6IkENPQ10W0nJyVx0wNK7kQmypavhqfXk4zoZKQBmLcHXUZMU2qu8JBYSu678yd5DKbFxEREVUd0dHRkMlkiIiIMDvm4MGDkMlkSElJKbN5EZnDQAwRERERVUnSjJiGkowYQQCSMpkVY2l5ai1ik7NE61gG7umRnadBjkocoPR8XJpMYWuDlgHuovtOszwZERFRhTZ27FjIZDKjrz59+pT31IgqFXl5T4CIiIiIqKzlqDTIzNOI1tWr5gwbGaDN1zv+YXoufFzty3h2lVtscpboGANg+aqniDQbBnhSmgwA2gR64ujNRMPyaWbEEBFRVaTVAtnlfDGCgydgU7Rr8Pv06YMNGzaI1tnZ2VljVkRVFjNiiIiIiKjKSclSGa3zdrYzXNmvx0wNy7uTmGW0jv14nh7SQIyNDHC1Fwdi8rt8LxVZeeoymRsREVGFkZ0ELKtXvl/FCATZ2dnBz89P9OXh4WG4XyaT4dtvv8ULL7wAR0dHNGjQANu3bzfcn5ycjJEjR6JatWpwcHBAgwYNRIGde/fu4aWXXoKHhwe8vLwwcOBAREdHG+4fO3YsBg0ahMWLF8PX1xfu7u5YuHAh1Go13n33XXh6eqJmzZpYv3690dyvXr2KDh06wN7eHk2aNMHBgwcLfK7Hjh1Dly5d4ODggFq1amHatGnIzMw0O37BggVo0aIF1q9fj9q1a8PZ2RlvvPEGNBoNli5dCj8/P/j4+OCTTz4RbZeamoqJEyfCx8cHrq6uePbZZ3H+/HnD/bdu3cLAgQPh6+sLZ2dntGnTBnv37hXtIzAwEIsXL8a4cePg4uKC2rVr4//+7/8KfH5UcTEQQ0RERERVTmKmOMBiIwPcHBTwdhZf+ccAgeVFJxr/ocuA19MjOVMcxHR3VMLGRmZYDq3tDnm+ZbVWwL8xKWU1PSIiIrKShQsXYtiwYbhw4QL69euHkSNHIilJF+yZO3curly5gl27diEyMhJr1qyBt7c3ACArKwvdu3eHs7MzDh8+jH/++QfOzs7o06cP8vKe/K69f/9+3L9/H4cPH8Z//vMfLFiwAP3794eHhwdOnjyJ119/Ha+//jru3r0rmte7776LGTNm4N9//0WHDh3w/PPPIzExEaZcvHgRYWFhGDx4MC5cuICff/4Z//zzD6ZOnVrgc7916xZ27dqF8PBwbN68GevXr8dzzz2H2NhYHDp0CJ999hnmzJmDEydOAAAEQcBzzz2H+Ph47Ny5E2fPnkXLli3Ro0cPwzHLyMhAv379sHfvXvz7778ICwvDgAEDEBMTI3rszz//HK1bt8a///6LyZMn44033sDVq1eL8Z2jioKBGCIiIiKqcqQnkz0en0w2DsQwQGBp0Y8YiHmaSTNi3POVJQMAR6UcTWq4idZdiE21+ryIiIio5Hbs2AFnZ2fR18cffywaM3bsWAwfPhz169fH4sWLkZmZiVOnTgEAYmJiEBoaitatWyMwMBA9e/bEgAEDAABbtmyBjY0Nvv32WzRr1gzBwcHYsGEDYmJiRNkrnp6eWLVqFYKCgjBu3DgEBQUhKysLH3zwARo0aIDZs2dDqVTi6NGjonlNnToVL774IoKDg7FmzRq4ublh3bp1Jp/nsmXLMGLECEyfPh0NGjRAhw4dsGrVKnz//ffIyckxe3y0Wi3Wr1+Pxo0bY8CAAejevTuuXbuGlStXIigoCK+++iqCgoIMz+fAgQO4ePEifv31V7Ru3RoNGjTA8uXL4e7ujt9++w0A0Lx5c0yaNAnNmjVDgwYNsGjRItStW1eUaQQA/fr1w+TJk1G/fn3MmjUL3t7ehWb9UMXEHjFEREREVOUkSU4mezwuSebtLClNls4AgaVFmyhNlpSZB41WgG2+TAqqmFIk7x1PR6XRmKbVXXH+boph+Wp8mrWnRURERKXQvXt3rFmzRrTO01NcbjQkJMRw28nJCS4uLnj48CEA4I033sCLL76Ic+fOoXfv3hg0aBA6dOgAADh79ixu3rwJFxcX0f5ycnJw69Ytw3KTJk1gk6+nja+vL5o2bWpYtrW1hZeXl+Ex9dq3b2+4LZfL0bp1a0RGRpp8nvq5bNq0ybBOEARotVpERUUhODjY5HaBgYGi+fv6+sLW1tZovvq5nT17FhkZGfDy8hLtJzs72/CcMzMzsXDhQuzYsQP379+HWq1Gdna2UUZM/uMuk8ng5+dndAzo6cBADBERERFVOcmZpk8mMyPG+kyVJtMKukwL6fGniifJRGkyqUZ+4hMt1+LTrTonIiKiCsfBE3j3VuHjrD2HInJyckL9+vULHKNQiLNgZTIZtFotAKBv3764c+cO/ve//2Hv3r3o0aMHpkyZguXLl0Or1aJVq1ai4IdetWrVCtx/QY9ZEJnM9MU9Wq0WkyZNwrRp04zuq127ttn9FXduWq0W/v7+JjNX3N3dAehKqv39999Yvnw56tevDwcHBwwZMkRUrs3cYxflGFDFw0AMEREREVU5SZnSjBjdHzjVXNgjxppUGi1ik7NN3vcoI5eBmKeAtDSZh6Q0GQA08ncVLd98mIE8tRZKOStjE1H5yVFpcDcpC9XdHeBkx9NhZGU2NoCTd3nPokxVq1YNY8eOxdixY9G5c2e8++67WL58OVq2bImff/7Z0LTe0k6cOIEuXboAANRqNc6ePWu250vLli1x+fLlQoNOpdWyZUvEx8dDLpcjMDDQ5JgjR45g7NixeOGFFwDoesZER0dbdV5UvvibMBERERFVOdJAjKeTLgDAjBjrupecDY1WMHnfo3QGvZ4GRqXJnIwzYhr6ijNi1FoBtx9lWHVeREQFeZieg36rjqDXisPoveIwYkyUySSqynJzcxEfHy/6evToUZG3nzdvHv7880/cvHkTly9fxo4dOwxlvkaOHAlvb28MHDgQR44cQVRUFA4dOoS33noLsbGxpZ77l19+iW3btuHq1auYMmUKkpOTMW7cOJNjZ82ahePHj2PKlCmIiIjAjRs3sH37drz55pulnkd+PXv2RPv27TFo0CD8/fffiI6OxrFjxzBnzhycOXMGAFC/fn1s3boVEREROH/+PEaMGMFMl0qOgRgiIiIiqnKkPWI8H2fEeBtlxDAQY0lRJsqS6fFYPx2SsgovTebmoEANdwfRuqtxLE9GROVn27l7uJ2g+xl0LyUbW07HFLIFUdUSHh4Of39/0VenTp2KvL1SqcTs2bMREhKCLl26wNbWFlu2bAEAODo64vDhw6hduzYGDx6M4OBgjBs3DtnZ2RbJkPn000/x2WefoXnz5jhy5Aj+/PNPeHubzkYKCQnBoUOHcOPGDXTu3BmhoaGYO3cu/P39Sz2P/GQyGXbu3IkuXbpg3LhxaNiwIV5++WVER0fD19cXALBixQp4eHigQ4cOGDBgAMLCwtCyZUuLzoMqFuZiEhEREVGVI+0R42HoESM+qcwm8pZ15xEDMU87aUaMqdJkABDk54J7KU/K0F1lnxgiKkd3krIKXCaqyjZu3IiNGzcWOEYQjDOaU1JSDLfnzJmDOXPmmN3ez88P3333XYFzkDLVXyV/6a7AwEDDvIYPH25yv926dTOae5s2bbB7926zc5FasGABFixYUOz5uri4YNWqVVi1apXJ/QYGBmL//v2idVOmTBEtmypVFhERUdiUqYJiRgwRERERVTnGpcl0AZhqktJkWsF4LJVcdAGlYNiP5+lg1CPGRGkyAGjkJy5PdjU+zWpzIiIqTHqOWrSclq0yM5KIiMg6GIghIiIioipHGlzRn0z2dFJCJkl+YaaG5USzNNlTLzlTfPLSw0RpMkCXEZPfNWbEEFE5Ss8Rf3alSQIzRERE1sZADBERERFVKYIgGF3V7/U4ECO3tTE6scwAgeXcKTAjhse5ostTa5GRKz55qe+vJBXsL675Hpeag9QsXoFOROVDmhEjDcwQERFZGwMxRERERFSlZOSqodKIa0XnD75I+8QwQGAZao0WdwuoyZ/I0mQVnrQ/DAC4m8mIqePtBIWtOL2M5cmIqLwYZcRkMyOGiIjKFgMxRERERFSlSEsrAU96xACAt6RPzKN0Bggs4V5KNtRa40avegx4VXzJJjJa3B1MZ8QobG1Q30faJ4blyYiofBj1iGFGDBERlTEGYoiIiIioSkmSXNWvlNvAUWlrWDYKxDBAYBFRj8z3hwF0GTGCYD5QQ+VPWtLP1V4Oua35Pykb+UkDMcyIIaLyIQ3E5Km1yFFpymk2RERUFTEQQ0RERERVSlKmOLDi6aiETPakhJI0EJPAQIxFSPvDSI9znkbLUjEVXHKmOBDj4WS6LJmecSCGGTFEVPY0WsGovxVgHJwhIiKyJgZiiIiIiKhKSZKUJvOUnEz2dpH2iGFpMkuIThRnxLQO8DAaw6BXxSYtTWauP4xekCQQcy0+HdoCytMREVmDqSAMwPJkRERUthiIISIiIqIqRXpVv1EgxqhHDIMDlhAtKU3W0M8FLnZy0bpEBmIqNGlpMk9H0/1h9IL9XUXLWXkaxCZnW3xeREQFSTcTcGFGDBERlSUGYoiIiIioSpGeTHaXnEyuxh4xViEtTRbo5QhvF+mxZvZRRWZUmqyQjBgfFzuj91ck+8QQURkzV/YyLZsZMUSldfDgQchkMqSkpBQ4LjAwECtXrrTY43br1g3Tp08v1jYLFixAixYtDMtjx47FoEGDLDIfmUyGP/74wyL7KkujRo3C4sWLy3sa5So3Nxe1a9fG2bNnrf5YDMQQERERUZWSq9aKlh0UtqJlaUZMYmYeyymVklqjRUySJBDj7QQvJ2kZOAa9KjJpabLCesTIZDKjPjHX2CeGiMqYuYwYliYjeiI+Ph5vvvkm6tatCzs7O9SqVQsDBgzAvn37CtyuQ4cOiIuLg5ubGwBg48aNcHd3Nxp3+vRpTJw40RpTL7EvvvgCGzduLO9plJsLFy7gf//7H958803DurFjx0Imk4m+nnnmGdF2ubm5ePPNN+Hj44MaNWpg4MCBiI2NFY1JTk7GqFGj4ObmBjc3N4waNarQYF1JrFy5En379kWvXr0wYcIECIL4b7axY8fi/fffL3AfdnZ2mDlzJmbNmmXx+UkxEENEREREVYpGElSR24p/JZb2iNFoBaTwqtlSuZ+SA7XkuAd6ORmXgWMgpkJLyZJmxBRcmgwAGvmJy5NdZUYMEZUxcyXIzGXKEFU10dHRaNWqFfbv34+lS5fi4sWLCA8PR/fu3TFlyhSz26lUKiiVSvj5+UEmkxX4GNWqVYOjo6Olp14qbm5uJoNGFUVennUzxf/73/9i6NChcHERXzTTp08fxMXFGb527twpun/69OnYtm0bfvrpJ+zatQuZmZno378/NBqNYcyIESMQERGB8PBwhIeHIyIiAqNGjbL4c5g+fTpq1KiBW7du4aeffkJ6+pMLfrRaLf73v/9h4MCBhe5n5MiROHLkCCIjIy0+x/wYiCEiIiKiKkWlEWfEyG3Efzh6OYmDAwCQwD4xpRKdKO4P42ovh4ejwijoxdJkFVuSUVm/gjNiABhlxFxlRgwRlbH0XHM9YniRBZWNzMxMZGZmiq7Wz8vLQ2ZmJnJzc02O1Wqf/L6qUqmQmZmJnJycIo0trsmTJ0Mmk+HUqVMYMmQIGjZsiCZNmuCdd97BiRMnDONkMhnWrl2LgQMHwsnJCYsWLRKVJjt48CBeffVVpKamGrIpFixYAMC4NFlKSgomTpwIX19f2Nvbo2nTptixYwcAIDExEcOHD0fNmjXh6OiIZs2aYfPmzcV+Xp9++il8fX3h4uKC8ePHGx0/aWmy3377Dc2aNYODgwO8vLzQs2dPZGY++R12/fr1aNKkCezs7ODv74+pU6eK9vfo0SO88MILcHR0RIMGDbB9+3bDfRqNBuPHj0edOnXg4OCAoKAgfPHFFybns2TJElSvXh0NGzYEABw7dgwtWrSAvb09WrdujT/++AMymQwRERGGba9cuYJ+/frB2dkZvr6+GDVqFB49emT22Gi1Wvz66694/vnnje6zs7ODn5+f4cvT09NwX2pqKtatW4fPP/8cPXv2REhICL7//ntcvHgRe/fuBQBERkYiPDwc3377Ldq3b4/27dvjm2++wY4dO3Dt2jWzcwoMDMSiRYswevRoODs7IyAgAH/++ScSEhIwcOBAODs7o1mzZjhz5oxou2+//Rb//vsv3n33XVFQ6ejRo7CxsUG7du2Ql5eHqVOnwt/fH/b29ggMDMSSJUsMY728vNChQ4cSvc6Kg4EYIiIiIqpSjDNixIEYpdzGqK8FMzVKRxqICfR2gkwmMwp68ThXbCmS0mSehZQmA4AgSSAm+lEmclQaM6OJiCzPbEYMAzFURpydneHs7Cw6Mb5s2TI4Ozsbncz38fGBs7MzYmJiDOu+/PJLODs7Y/z48aKxgYGBcHZ2Fl3FX9xSW0lJSQgPD8eUKVPg5ORkdL80Y2T+/PkYOHAgLl68iHHjxonu69ChA1auXAlXV1dDNsXMmTON9qnVatG3b18cO3YMP/74I65cuYJPP/0Utra6csE5OTlo1aoVduzYgUuXLmHixIkYNWoUTp48WeTn9csvv2D+/Pn45JNPcObMGfj7++Orr74yOz4uLg7Dhw/HuHHjEBkZiYMHD2Lw4MGG4NmaNWswZcoUTJw4ERcvXsT27dtRv3590T4WLlyIYcOG4cKFC+jXrx9GjhyJpKQkw3OuWbMmfvnlF1y5cgXz5s3DBx98gF9++UW0j3379iEyMhJ79uzBjh07kJ6ejgEDBqBZs2Y4d+4cPv74Y6MSWnFxcejatStatGiBM2fOIDw8HA8ePMCwYcPMPt8LFy4gJSUFrVu3Nrrv4MGD8PHxQcOGDTFhwgQ8fPjQcN/Zs2ehUqnQu3dvw7rq1aujadOmOHbsGADg+PHjcHNzQ7t27QxjnnnmGbi5uRnGmLNixQp07NgR//77L5577jmMGjUKo0ePxiuvvIJz586hfv36GD16tOH7og+u2dvb47vvvsP58+cN+9q+fTsGDBgAGxsbrFq1Ctu3b8cvv/yCa9eu4ccff0RgYKDosdu2bYsjR44UOL/Sklt170REREREFYxKIwnE2BiXUvB2thOddGaAoHSiH0n6w3jp/tD3dmEg5mmSlCnNiCm8NFlDXxfIZID+ImCtAETGpSG0toc1pkhEZISlyYjMu3nzJgRBQKNGjYo0fsSIEaIATFRUlOG2UqmEm5sbZDIZ/Pz8zO5j7969OHXqFCIjIw1ZH3Xr1jXcX6NGDVEA580330R4eDh+/fVX0cn9gqxcuRLjxo3Da6+9BgBYtGgR9u7da5QVoxcXFwe1Wo3BgwcjICAAANCsWTPD/YsWLcKMGTPw1ltvGda1adNGtI+xY8di+PDhAIDFixdj9erVOHXqFPr06QOFQoGFCxcaxtapUwfHjh3DL7/8IgqYODk54dtvv4VSqbvYZe3atZDJZPjmm29gb2+Pxo0b4969e5gwYYJhmzVr1qBly5ZYvHixYd369etRq1YtXL9+3XCM84uOjoatrS18fHxE6/v27YuhQ4ciICAAUVFRmDt3Lp599lmcPXsWdnZ2iI+Ph1KphIeHhygTy9fXF/Hx8QB0/Yak+wV0QUb9GHP69euHSZMmAQDmzZuHNWvWoE2bNhg6dCgAYNasWWjfvj0ePHgAPz8/DBs2DKmpqUhMTETPnj3RtGlTw762b9+O5cuXAwBiYmLQoEEDdOrUCTKZzPA9zq9GjRqIjo4ucH6lxUAMEREREVUpGq2kNJmtcZK4t7MSN59c/MXSZKV0L0UciKntqasRXs1ZWpqMx7mi0mgFo6vHPYpQmszJTo46Xk64/ehJVlT45XgGYoiozJjLfGFpMiorGRkZACDqkfLuu+9i+vTpkMvFp2b12QcODg6GdVOmTMGECRMMGSN6+pPG+ceOHTu2WHPTZxYU1uNFz1QGRXFFRESgZs2aJgMEgK6M16effoqff/4Z9+7dQ25uLnJzc01m7JgTGRmJ119/XbSuffv2OHDggMnxzZs3R48ePdCsWTOEhYWhd+/eGDJkCDw8PPDw4UPcv38fPXr0KPAxQ0JCDLednJzg4uIiyiZZu3Ytvv32W9y5cwfZ2dnIy8tDixYtRPto1qyZIQgDANeuXUNISAjs7e0N69q2bSva5uzZszhw4ACcnZ2N5nTr1i2Txzk7Oxt2dnZG3/eXXnrJcLtp06Zo3bo1AgIC8L///Q+DBw82+9wFQRDty9TrSTrGlPzH0NfXF4A4IKZf9/DhQ/j5+YnKv+UXGRmJ2NhY9OzZE4DufdGrVy8EBQWhT58+6N+/vyirB9C9j7KyskztzmJYmoyIiIiIqhSVpDSZwkxGTH7sXVI68aniqw+ru+tOGEiPcyKPc4WVmq2CIH7rFKk0GQD0auIrWv4r4j60kvchEZG1mC9NxowYKhtOTk5wcnISnYRWKpVwcnKCnZ2dybE2Nk9O2SoUCjg5OYlOxhc0tjgaNGgAmUxW5CblxQmGmJM/cGTK559/jhUrVuC9997D/v37ERERgbCwMKs2r7e1tcWePXuwa9cuNG7cGKtXr0ZQUBCioqIKna+e9NjLZDJD1sgvv/yCt99+G+PGjcPu3bsRERGBV1991eg5SY+vqeCFIPmFTKvVYsCAAYiIiBB93bhxA126dDE5V29vb2RlZRV6TP39/REQEIAbN24AAPz8/JCXl4fk5GTRuIcPHxqCJH5+fnjw4IHRvhISEgxjzMl/DPXP29Q6reTCOqnt27ejV69ehu9dy5YtERUVhY8//hjZ2dkYNmwYhgwZItomKSkJ1apVK3C/pcVADBERERFVKRpJaTJbG1MZMSyZZUlxkkCMv5vuRIKX5Dhn5WmQlccTYxWRtCwZULTSZAAwqEUN0fL91Bycik6yyLyIiApjvjQZM2KIPD09ERYWhi+//FLUmF4vJSWlWPtTKpXQaAruBRcSEoLY2Fhcv37d5P1HjhzBwIED8corr6B58+aoW7euIRBQVMHBwThx4oRonXRZSiaToWPHjli4cCH+/fdfKJVKbNu2DS4uLggMDMS+ffuKNYf8jhw5gg4dOmDy5MkIDQ1F/fr1cevWrUK3a9SoES5cuIDc3Cd/i0ib1bds2RKXL19GYGAg6tevL/oyFzjTZ+JcuXKlwMdPTEzE3bt34e/vDwBo1aoVFAoF9uzZYxgTFxeHS5cuoUOHDgB0mUepqak4deqUYczJkyeRmppqGGNtf/75J55//nnROldXV7z00kv45ptv8PPPP+P333839PABgEuXLiE0NNSq82IghoiIiIiqFLVRaTLjjJhq7F1iMSqNFgmS4+f3OBDj7WycUfEonVkxFVFKluSKTaUt7OS2ZkaLBfu7IsjXRbTuz4h7FpsbEVFBzJUgMxegIapqvvrqK2g0GrRt2xa///47bty4gcjISKxatQrt27cv1r4CAwORkZGBffv24dGjRyZLPXXt2hVdunTBiy++iD179iAqKgq7du1CeHg4AKB+/frYs2cPjh07hsjISEyaNKnQ3iJSb731FtavX4/169fj+vXrmD9/Pi5fvmx2/MmTJ7F48WKcOXMGMTEx2Lp1KxISEhAcHAwAWLBgAT7//HOsWrUKN27cwLlz57B69eoiz6d+/fo4c+YM/v77b1y/fh1z587F6dOnC91uxIgR0Gq1mDhxIiIjI/H3338b+p7os0OmTJmCpKQkDB8+HKdOncLt27exe/dujBs3zmxQrFq1amjZsiX++ecfw7qMjAzMnDkTx48fR3R0NA4ePIgBAwbA29sbL7zwAgDAzc0N48ePx4wZM7Bv3z5cuHABo0ePRrNmzQxlwIKDg9GnTx9MmDABJ06cwIkTJzBhwgT0798fQUFBRT5mJfXw4UOcPn0a/fv3N6xbsWIFtmzZgqtXr+L69ev49ddf4efnB3d3d8OYI0eOGJUrszQGYoiIiIioSlFJMmLkJkuTsXeJpTxMzzUqaaXPiHG2k8NOLv6TRBq0oYohOUt8ItO9CP1h8hsYWl20/L8LcchVF3zFLBGRJZgvTcaMGCJA1zj+3Llz6N69O2bMmIGmTZuiV69e2LdvH9asWVOsfXXo0AGvv/46XnrpJVSrVg1Lly41Oe73339HmzZtMHz4cDRu3BjvvfeeIWgwd+5ctGzZEmFhYejWrRv8/PwwaNCgYs3jpZdewrx58zBr1iy0atUKd+7cwRtvvGF2vKurKw4fPox+/fqhYcOGmDNnDj7//HP07dsXADBmzBisXLkSX331FZo0aYL+/fsXK0vn9ddfx+DBg/HSSy+hXbt2SExMxOTJkwvdztXVFX/99RciIiLQokULfPjhh5g3bx4AGErVVa9eHUePHoVGo0FYWBiaNm2Kt956C25ubqKydVITJ07Epk2bDMu2tra4ePEiBg4ciIYNG2LMmDFo2LAhjh8/DheXJxfUrFixAoMGDcLLL7+MPn36wMHBAX/99Zeoh9GmTZvQrFkz9O7dG71790ZISAh++OGHIh+v0vjrr7/Qrl07+Pj4GNY5Ozvjs88+Q+vWrdGmTRtER0dj586dhuNz/PhxpKamGpUrszSZIC0sRyalpaXBzc0NqampcHV1Le/pVBgqlQo7d+5Ev379il2Hkogsj+9JoqcH36/l55VvT+Kfm48My3P7N8b4TnVEY/ZFPsD4756k/fu52uPEBwU36CTTzt5JwotrjhuW7RU2iPyoj+Eqvo6f7se9lGzD/V+PaoWwJn5lPs+C8P0K/HL6Lt77/YJhuWkNV+x4s3ORt49NzkKnz8QNcivi95oqH75/qfeKQ7j+IMNovZPSFpc/6lMOMyJznvb3a05ODqKiolCnTh2jfi5ElrJp0ya8+uqrSE1NLXL/GlNycnIQFBSELVu2FDvzCdD1aUlLS4Orq2uBAZ+y9vzzz6NTp0547733irzN0KFDERoaig8++MDsmILe30WNG1Sco0REREREVAZUGklpMpMZMZIm8pm5Ro0xqWiM+8M4iJqOSrOPEjNYmqwiSpaUJvMoZkZMTQ9HtA30FK1jeTIiKgvmMmIy8zRQawpu+ExEVN6+//57/PPPP4iKisIff/yBWbNmYdiwYaUKwgC6jJrvv/8ejx49KnzwU6RTp04YPnx4kcfn5uaiefPmePvtt604Kx251R+BiIiIiKgC0WglpclM9IjxlvSIUWkEpGaril2OiYC4FHEgxs9VfAWZNOjFMnAVk7Q0WXEDMYCuPNmp6CdNUfdGPkRajgqu9k/fVc9E9PQoqBdMRq6aP9uJqEKLj4/HvHnzEB8fD39/fwwdOhSffPKJRfbdtWtXi+ynIilOJgwA2NnZYc6cOVaajRgzYoiIiIioSlFJAzEmMmK8nEw0kWeAoESMM2IYiHkaJWdKM2KKHzzp19QfinyBzzy1FuGXitd8l4ioODRaARm55gMxadnm7yMiqgjee+89REdHG0pjrVixAo6OjuU9LSoBBmKIiIiIqErRaKWlyYx/JbZX2MLFXpw8npDOklklEZ+WLVr2kwRivCSlyRiIqZiMSpOZCFYWxsNJia4Nq4nWsTwZEVlTQUEYAEjLURV4PxERkaUwEENEREREVYpaU3hpMgCoxkwNiyh+RgwDXhVRaXvE6A1sUUO0fOxWolG2DRGRpaQXEmhhIIasgX0FiSofS7yvGYghIiIioipFbVSazPSvxCyZZRnxkkCMn5u4sai0Hw+Pc8Vk1COmBBkxANAz2BdK+ZP3nCAANx5mlGpuRGSCVqX7quIK6g8DsDQZWZatrS0AIC+PFxgQVTZZWVkAAIWi5L0N5YUPISIiIiKqPNQacWkyWxM9YgDA24Uls0pLrdHiYbr4uBlnxEiOczqPc0WUYpQRU7I/Qh2Utqjt6Yib+YIvdxIz0baOZ6nmR1TlqbOA3AQgLxnITQLUmbr1MhvA1g6wsQecagFOAeU7zzJWaCCGGTFkQXK5HI6OjkhISIBCoYCNmYt9iCoDrVaLvLw85OTkVOrXuiAIyMrKwsOHD+Hu7m4IuJZEuQZiDh8+jGXLluHs2bOIi4vDtm3bMGjQIMP9giBg4cKF+L//+z8kJyejXbt2+PLLL9GkSRPDmNzcXMycORObN29GdnY2evToga+++go1a9Y0jElOTsa0adOwfft2AMDzzz+P1atXw93dvayeKhERERFVENKMGIWZ0mRGGTHsEVNsjzLyoJEcb2mPGOlxTstRI1etgZ285H/kkGUJgmCcEVPC0mQAEOglDcRklXhfRFWeoAXSbwHp13W3Td2vzgaQ/ThIkwi4NwdsqsZnbFp2wYGWwgI1RMUhk8ng7++PqKgo3Llzp7ynQ2RVgiAgOzsbDg4OkMlM/z1Vmbi7u8PPz69U+yjXQExmZiaaN2+OV199FS+++KLR/UuXLsV//vMfbNy4EQ0bNsSiRYvQq1cvXLt2DS4uLgCA6dOn46+//sKWLVvg5eWFGTNmoH///jh79qwhQjVixAjExsYiPDwcADBx4kSMGjUKf/31V9k9WSIiIiKqEKQ9YsxmxLA0WanFpWaLlpW2NvCUnMCXHmcASMzIQ3V3B6P1ZSE1W4Utp2Kg0mgR1sQPDXxdymUeFUlajtoooFbS0mQAUNvTSbR8J4mBGKISUaUByRFAXqpuWekB2HkDdp662zJbQJMLaHN0AZi0q0DWPUCVDni1BuROBe6+MkjPLaRHTCGBGqLiUiqVaNCgAcuTUaWnUqlw+PBhdOnSpVTlup4GCoWiVJkweuUaiOnbty/69u1r8j5BELBy5Up8+OGHGDx4MADgu+++g6+vL3766SdMmjQJqampWLduHX744Qf07NkTAPDjjz+iVq1a2Lt3L8LCwhAZGYnw8HCcOHEC7dq1AwB88803aN++Pa5du4agoCCTj5+bm4vc3Cd/bKelpQHQvchUKv6g1tMfCx4TooqB70mipwffr+VHrRVfMSwTtCa/Dx4O4l+VE9Jz+P0qptikTNGyj6sdNBo1NJon65zkumBY/hP9D1KyUM2p7P9UEQQBb/x4FsduJQEAlu++jg51PfFy6+rQCFX3/ZqQZhwocVaU/HjUdBcH3+48yqiyx5asr9L+vM24DVn6VV3Gi40CgltTwKHGk/s1+n/kgMwZsHcGZM6QJZ8DcpKAuAMQPNsAyspdFjAls+CLKFKycivfa+MpVpner5Y4aUtUkWm1WqjVatja2lb617tWq4VWayLr9LGifmZV2B4xUVFRiI+PR+/evQ3r7Ozs0LVrVxw7dgyTJk3C2bNnoVKpRGOqV6+Opk2b4tixYwgLC8Px48fh5uZmCMIAwDPPPAM3NzccO3bMbCBmyZIlWLhwodH63bt3w9HR0YLPtHLYs2dPeU+BiPLhe5Lo6cH3a9nLyrEF8CQL5sypk0i5ZjzuTpIMwJM/Ku4mpGLnzp3Wn2AlcjBOfAzt1Fkmj6GTrS3StE++J7sOHkWMh2A0ztpupMpw7Jb4D8ljt5Nw7HYSvOxsEZOxB3WqYIJMdDqQ/09HuUzAgT27UdIqFA+Txa+Lm/F8b5H1Vaaft3IhA16aKwCAXJkH0mwCoZWdB3C+0G1thDy4a29CIWRAI4vAI5umKPGbGYBMUMNDex1ayJFi06BU+7KGM7HizxupyJvR2LnzdtlNiIqkMr1fiSo7vl+BrKyiZXdX2EBMfHw8AMDX11e03tfX11BnMT4+HkqlEh4eHkZj9NvHx8fDx8fHaP8+Pj6GMabMnj0b77zzjmE5LS0NtWrVQu/eveHq6lqyJ1UJqVQq7NmzB7169ar0aWhETwO+J4meHny/lp8Pz+0H1E9qwnfq2AEta7sbjat+NwXfXjtlWM7U2qJv397lWgNZEARcf5ABAUAjv4ofEbgQfg2IflIjPTjQH/36hRiN+/LWMaTl6xnSoElz9GtRvUzmmN+kH/8FkGDyvsRcGbbed8He6Z2qRB3s/A5eTwAu/WtY9nKxx3PPdS3x/honZmLt1aOG5SyNDB2794KbAz8LyfIq3c9bQYDs0T+AyhGCQw3AI7T4+9CqIXu4D9CqIHi0EGfSFFfyOciydU2aBfcQwLFWyfdlBZf+vg7cjTZ7v5u3H/r1a1Fm86GCVbr3K1ElxvfrE/pKWoWpsIEYPekfOYIgFPqHj3SMqfGF7cfOzg52dsb1qhUKRZV/cZnC40JUsfA9SfT04Pu17ElLk9krTX8P/NzFtfPz1FrkaGVwtS+/79eiHVfw7T9RAICJXerig37B5TaXoniYIU7Tr+HhaPJYezorgYdPltNytWX+vridkIH910wHYfRikrJx41E2mlR3K6NZVQzpueL3jIejslTfnwBvV9jIgPxtZ+6n5cHblZUHyHoqzc/bjChAmwkoHACv5oBtSZ6TAnALetwz5jbgElCyTJbMGCDvIWD7+NRS1i3dvmwqTomaTJWkHKkMEPJ99qTnqivH66KSqTTvV6IqgO9XFPn521h5HiXm5+cHAEZZKw8fPjRkyfj5+SEvLw/JyckFjnnw4IHR/hMSEoyybYiIiIio8pM2Hbe1MX3yqZqL8UU5j9ILrjVvTZfupRqCMADwf4dvIza5Yjc5j0/NFi37udmbHOfhKG78npJV9g1u1x+NEi272sux9MUQeEma0u+PfIiqJlXSzNrdsXR/bCvlNqjh4SBaF51YsV/LRBWCJkcXPAEAt2DA1vjnVJE51wFslIA6E8i+V/ztVelAyiXdbddGgNxRN7+MilXmKz1HLVr2dRH/HErLFt9PRERkLRU2EFOnTh34+fmJ6szl5eXh0KFD6NChAwCgVatWUCgUojFxcXG4dOmSYUz79u2RmpqKU6eelJU4efIkUlNTDWOIiIiIqGoQBAEqjTgQo7A1/SuxvcIWznbiBPKEcgzErDl0y2jdrovmS+1WBHGpOaJlf3OBGEmwIymzbAMxKVl5+O1srGjdiHYBGNamFgY0F5dI23e16gVipCcqLZEVFuApzjiLScws9T6JKr3Uy4BWDSg9AMfapduXjRxwqae7nXZdnCZSGK0GSDoLCBrAvhrgUl8XjAGAjJuApvx+Vkql50gzM8VB4PTcp78pPBERPR3KNRCTkZGBiIgIREREAACioqIQERGBmJgYyGQyTJ8+HYsXL8a2bdtw6dIljB07Fo6OjhgxYgQAwM3NDePHj8eMGTOwb98+/Pvvv3jllVfQrFkz9OzZEwAQHByMPn36YMKECThx4gROnDiBCRMmoH///ggKCiqvp05ERERE5UCaDQOYz4gBAG9ncYDgUUbZZ2oAurJZOy/GGa3fceF+OcymaLRaAQ/SxIEYPzcHk2M9JBkWKVlle2Js08kY5OQrXyO3kWFMhwAAQI9gcb/J87Ep5RqQKw/SjBhXC/Ryqe0lLkPGjBiiQuQkAFn3dbW13JuVrJSYlFPgk6yYrNhChxukXtZlxNja6XrUyGSAQ3VA6a4LFKVfL/3cLESaEVPdXfxziBkxRERUVso1EHPmzBmEhoYiNFTXXO6dd95BaGgo5s2bBwB47733MH36dEyePBmtW7fGvXv3sHv3bri4PGlMumLFCgwaNAjDhg1Dx44d4ejoiL/++gu2tk9qkm7atAnNmjVD79690bt3b4SEhOCHH34o2ydLREREROVObSIQo7AtKBAjLvvyKKN8TsB/fei2yYuVz8emIqaCnsBOzMwzyj4ymxHjWH4ZMXlqLb47Fi1a1z/EH/6Pg0Zt63jCSfnkbwtBAA5eq1pZMWmSK8rdLBCICZQEYirq65iowkiL1P3vVAdQWqhPlY1cl80C6IIngrbg8QCgygAy7+hue4Q+KY8mkwFujXW3M+/oxlUARhkxkkBMeo4KQnGygYiIiEpIXvgQ6+nWrVuBP/BkMhkWLFiABQsWmB1jb2+P1atXY/Xq1WbHeHp64scffyzNVImIiIioEjAViCk4I6b8AzFxqdnY+q/5K5V3XLyPyd3ql+GMiiZeUpbM1kZmdDz1pIGY5DLsEbPjwn08lGS4jO9U13DbTm6LjvW9sPvKk+DL/qsPMbR1rTKbY3lLk2bEWKA0WW1JabI7SSxNRmSWKh3ISwVkNoBLA8vu2ykQyLgFqLOArLuAU0DB4zNu6v538NOVJcvPzku3Pjte18vGq7Vl51oC0owYaWkyrQBk5mmMSpESERFZWoXtEUNEREREZGkajamMGPO/Enu7SEuTlX0g5pvDUUaZJfn974JxybKKIC41W7Ts62JnNujl4VR+pcm+P35HtNyujiea1RRfbd49SHyy8fD1BOSpi3DleCUhLU3m5lD6E5YBkoyYB2m5yM7TlHq/RJWSvmyYvQ9gqyx4bHHZ2D7Jikm7ruv/Yo46G8i6p7vtYuYCANfHJeBzHhYtw8bKjAIx7saZmdJgMxERkTUwEENEREREVYZKa3xSqDgZMQnpZdsjJikzD5tPxYjWNa3hKlq+fD8NUY8qXjZBvFF/GNNlyQATpcmy8sqkVExajgrnY1NE68Z1qmM0rltDb9FyZp4Gp6KSrDm1CiVNciLTEj1ipIEYAIhJYnkyIiOC8CQQ41jTOo/hFAjIHQFNDpBx2/y4jNu64IqdF6D0MD1G7gLYKABBo8vkKUcarYCMXPHnl7+bg1F7HWn5RSIiImtgIIaIiIiIqgyNqR4xNgVkxJRzabKNR6OQrXpydbKtjQxfjmgJb2dx4GLH+ftlOq+iiJOUJtP3XDFFGojJU2tFz9ta/o1JEfXeUdraoGvDakbjvJ3tEOAsfu3sv1p1+sRYozSZo1KOai7i99edxIoXUCQqd7mJugCJjQKw97XOY8hsANdGutsZNwGNiZ91mrwnvWHMZcMAul4xSnfd7bxki06zuKRBGEDX40pahkyaNUNERGQNDMQQERERUZWh0pjIiLGtmD1iBEHAz2fuitYNbF4dAV5O6NvUX7T+fxfLvzxZTGIWvj50C3uvPABg3COmOBkxAJBcBuXJzt4RnyRsWsMV9gpbk2Mbu4tfO/uuPqgyDZ6lgRg3x9IHYgAgUJIVcyeRGTFERrIflwJz8NcFTKzFobougKJVA+nXje/PjNZluShcdSXSCqLPlinnQEy6iUwXF3u5UTCZpcmIiKgsMBBDRERERFWGqYwYeQGlyaqZ6BFTViffE9Jz8SBN0kS+s65sVv8QcSDmanw6bj4svxIw91Ky8cJXR7Fk11W89v0ZfHngplGPGP8CAjEu9nKjEnHJmdYvA3f2jri8WOtAT7Njm3iIv+93ErNwuwKWhLM0jVZAuuSqcktkxABAbU8n0fKdpMp/PImKRasBsh9nPFqrLJmeTAa4ButuZ94B1Pnej1oNkBGlu11QNoxehQnEiD+7ZDLASSmHi704I4alyYiIqCwwEENEREREVYappvcFBWKkGTE5Ki0yy6ih+JW4NNGyk9IWwX66/jBtAj3h6yqe21/nyy8rZvnf15CYL3CyYs91XLkvnn9BGTE2NjK4S/qOJGdZNxCj1mjxb0yKaF2rADM9DwDUdAJ8JaW09kdW/vJkpq4od7NAjxjAuE8MM2KIJHIe6DJU5A6A0nyg2GLsvXXlzwQBSL0CqLN0pdHSIgFtnq6PjEP1wvejcNf9r84EtOUX5JAGYpzt5LCxkRn1uUrLZmkyIiKyPgZiiIiIiKjKMJURI83EyE8aiAGAR+llU54sMk6c4RLk5wKbx3O1sZGhXzNxVsxfF+6XS6msS/dSse3fe6J1aq1g1OC9oIwYAPBwEmcfJVk5I+ZqfDqyJEG1ggIxMhnQLchbtG7f1QdWmVtFYuoEpauD3MTI4mMghqgQWbG6/x1qwqjDvLW4BeseKzseiN8HJBwTZ8MUZR62SkD+OOOtHLNipIFkfTafq720RwwzYoiIyPoYiCEiIiKiKkPaI0ZuI4OsgJNKTnZyOCrFPUOiy6ih+NV4cUZJI39X0bK0PNnthExclmShWJsgCFiyK7JIY/3cHAq830PSdyTFyj1ipP1hAr0cTQbe8uvWsJrRPkw1g65MpCV75DYyOJjpo1NcAV7i0mT3UrJN9nEiqpI0eUDu46w7xxpl97gKF8BJVwYTMhtdQMXOG3CpBzjWKvp+KkB5MmlGjL4kmVGPmJzK/TlOREQVAwMxRERERFRlSDNi5LaFX9nb0NdFtLz/atmUo4qUlCYLlgRiWtb2QE0PcXDjD0lmirUdvvEIR28mFjpOJgN8XAoOcrg7ijNirF2a7IwkENMqoPCyP8/U9RSVslNpBJy8Xfjzf5qlSppYuzkoCgxeFkeApzgjRqMVcD8l28xooiom+76uRJjSTRccKUvuTYDqfYAazwF+zwLV2gNujXWBmaKqAIEYaSDZEIgxKk3GjBgiIrI+BmKIiIiIqMpQa6UZMYX/Otyrsa9oee+VB1YvAZaj0uBWgjjzprG/+EScTCbDwBbiWv3bz983WX7NGjRaAUt2irNh3B0VJqvWVHO2g8K24GPtKQ3EWLk02dnoJNFy60DzZcn0nO3kRuXLjtx4ZNF5VTTSE5TSE5il4e6oMCoRFM3yZEQ62Y/7fjnWLJ/Htynle90QiEnRBZTKgXFGjLnSZMyIISIi62MghoiIiIiqDLWm+Bkx0kDM/dQcq5cAu/kwwyigEuTnajRuUAtxuZqH6bk4UUYZGtv+vYer8eI+Nh/2C8boZwKMxhbWHwYA3J3EJ/2SrVia7H5KNu6n5ojWtS6gP0x+XSTlyQ7fSLDYvCoiaUaMJQMxMpnMqDxZTBmV/iOq0AQtkPc4WGznU7RttBrddhWFwkWXQaNVAeryeV+by4hxMSpNxowYIiKyPgZiiIiIiKjKUEtLkxUhI6aBj7NRU/HdV6zbpF1alqy2pyOc7YwbpDfwdUFjScmysihPptJo8fnua6J1jfxcMLhlTbzbpxGqSwIv1d0L7g8DAB5lWJpM2h/G1V6OetWci7Rt5wbeouXbCZmITa68WRzSE5TSK8lLq7bkvXWHGTFEQG6SLqhiaw8ozHw2aXKAjGggOQJ4cBCI2wXcDwcSzwBZ93QBkPIkswGU7rrb5VSezGyPGAfx5xhLkxERUVlgIIaIiIiIqgzjQEzhGTEymQy9gsVZMbsvx1t0XlKRceJMk2B/8/0BBoWKy5OFX4pHjkpjlXnpXbyXijhJRsn7fRvB1kYGZzs5Pn0xRHRsn29eXboLI0alycowENMqwAM2RXgtAECT6m7wcBRfTf1PJS5PlpYtPpFpyYwYAAiUBGJYmowIQO7jzxQ7b9P3a3KAh4eBlItA5l1Ala4r/yVodCXNks4Bcbt1QZryDMiUc58Y86XJFAWOIyIisgYGYoiIiIioylBrJD1iilCaDDAuT3Y1Ph13k6x3wliaERPsb1yWTO/55jVEfVnSc9XYf/WhtaYGAHiYlitaruHugK75SnZ1aVgNWyY+g8nd6uHb0a3Rt5l/oft0lwQ3kjOtd/JQGohpHehZ5G1tbWToWF98crQy94mRliZzs3AgJsBTUposiaXJiAoMxAiCLsCiyQXkToBrQ8CrLeDfC/DpArg00GXRCFpdkObBQSDHuj8TzCr3QAxLkxERUcXBQAwRERERVRklyYgBdBkT0iyIPVYqTyYIAq7GiwMxjUz0h9Hzc7PHM3W8ROusXZ4sRZKt4u2shEwmPpatAz3xXp9G6CkJYpnj6STOiJE+hqVk5qpxRRLoalXE/jB6XRqI+8T8c/ORUU+fysK4NJmFAzGSjJiYpCxoK+mxJCoSrQpQpehumwrEZNwGchIAma0uAOMaBDj46sqYKd0At0aAb3fAp5MuIKPJAR6dBJLPA9oyzvzQB2LU6boeNmXMbEaMUWkyNQSBnztERGRdDMQQERERUZWh1kgCMbZF+3VYbmuDZxuJAwrWCsQ8SMs1alQv7QMjJS1PdvBaAlKt2OxeOj93SVmxkpDuIzNPg1y15U/cnb+bIgqayG1kaF7TvVj76CTpE5OarcLFe6mWmF6FY/WMGC9xRkyOSouH6blmRhNVAblJuqwXuRMgl/TXyksF0q7qbrs3Nd8/BtAFQap1AZzr6pYzY4DEU7p9lxVbe92XIDwJLpUhaUaMvseVNKCcp9EiVy3OmCUiIrI0BmKIiIiIqMpQayWlyYqYEQMAvZuIAzGnopOskrUhLUvmbCdHTY+Cm933aeoPZb6gUp5Gi52X4iw+Nz3p85ZmC5WEqX2kWCGYJC1L1qS6KxyUtsXaR3V3B9T3EZ8APXI9odRzq4ikTaylV5KXlo+LHezk4j9L7ySyPBlVYebKkmnVQNJZXckxB3/AqXbh+7KxBdybANU6ADZyIDcRyIyy/JwLUo7lyYwzYh4HYkwElFmejIiIrI2BGCIiIiKqMowzYooeiOncwFt0wlijFXDgmuXr7kdKypIF+bkU2kjezUGBZxv5iNZZszxZsiQQY4mMGDcHBSTVzZCUaflA19kY8cnAVgFF7w+TX+cGVaNPTJrkRKalS5PZ2MiMypPdsWL/JaIKz1wgJi0SUGfqMkw8mhdvn3ZegFtj3e3Uq7r9lJUKFYhRPP7fOKCcll3GZduIiKjKYSCGiIiIiKoMaUaMrU3Rfx12VMqNTr5bozxZZFy6aDnY36VI20nLk52MSsL9lGyLzSs/aWkyDwsEYuS2NkYn+aUBn9ISBAHn76aI1rUMcC/RvqR9Ys7FJBuVwakMrF2aDABqe4rLkzEjhqosTS6gehyMzx+I0aqBzLu62x4tAJsSvA+dAnT7FDRAckTZlShTuuv+V6UVOMzSNFoBGbmmA8kKWxs4KMSZkMyIISIia2MghoiIiIiqDLWkCbiiGKXJAKCXpPH8oWsJFu9jIi1NFlxIfxi9bkE+Rlf5bj9/32Lzys+oNJmTZU7OezqJAzqWLk0Wm5xtFEQqbn8YvXZ1PaHIl1Gl1go4fiuxNNOrkIxLk1k+EGOUEZPIjBiqovTZMApXwDbf52FOvC6AIncC7KuZ3rYoPJo/LlGWVHYlyhSPf4apswBt2QU7pEEYQJwJIy2zKM2eISIisjQGYoiIiIioypCWJrMtZiCmR7A4EJOZp8G1+HQzo4svR6XB7YQM0bpGfkULxNgrbNGvqb9onbXKk0mDGZYoTabbj/gkv6VLk128lypa9nBUFNp/xxxHpRytJWXNZvx6Ht8cvm3x4Fx5yVFpjBpYu5oo6VNagZJATAxLk1FVZa4sWVas7n/HmqXbv9yx7EuU2SgA+ePP2TLMijGVoZg/EOMiycCUBp2JiIgsjYEYIiIiIqoyjDJibIv367C3sx3qVhOXUboQm2pmdPHdeJCB/FOUyYBGfkUrTQYAAyXlya7Gp1s0UKRnlBHjaJksCWmJM+njlJb0e9Wspjtk0sY0xdC5ofhkaXqOGp/sjESv/xzGnxH3oNJozWz5dDBVqscqpcm8xO+p6EcsTUZVlKlAjCb3yXrHGsXfp6AFVOlA9gNdVkr+EmVp10o/Z60GSL4ApF4xX+5M4ab7v0wDMeIMF5kMcFLmy4iRBJVZmoyIiKyNgRgiIiIiqjLUGmmPmOKfhA+p4SZavmjBQIy0LFmApyOc7IqegfBMHS/4udqL1v0RYdmsGEEQjEqGWaJHjKn9SDNvSuvivRTRsvR7WVxDWtWEl5Pxc49JysJbWyLQ6bP9WLXvBh6m55TqccqLqebVVilN5inOiEnLUVs8CEdU4amzdF8yGWDn9WR99j1dgEPpoStNVhhBAHISgKSzQPx+4P5O4MFBIPEUEL8PSDgGKJx1gZjseF0gpaQEAUg+B2TeAdJvmQ/s6MuTqSz387Iw0kCMs50cNvl+5ks/y0x93hEREVkSAzFEREREVGUYZ8QUPxDTTNJT5MI9y51YuiIJxBS1LJmejY0Mz7cQZ8Vsj7gPrdZyTZnTc9VGx1FaUqykpJk1yRYsTSYIgomMmNIFYnxc7LFjWicMkhxzvQdpufjPnuvo+Ol+fLH3BoSyao5tIamSUj2OSttiZ5EVRQ0PB6OgKPvEUJWjz3pReuj6uOhlPQ6mF5YNo8kF0m8CD/YDj04AWfd1pccEQbc/xePsytxEICNal8GSHQ/kPCj5nFMu6PYhe/y5kH7jyXzzMwRiyq80maukFJk0u0/6eUdERGRpDMQQERERUZVR2h4xABAiOXl//UE6clSW6QlyNV58kirYv3iBGAAYKAkK3EvJxpk7yaWaV34pmcYnqyyWEeMkzYixXCDmTmKW0RXS0u9lSfi7OWDly6H4Y0pHtA7wMDlGpRGwYu91bDoZU+rHK0vSUj3SE5mWorC1QQ13ca+e6ESWJ6MqJjdR978yXzaMOhPIS9FlyTiYDvgC0AVdHuwHUiN1WTU2CsC5DuDdHvDvBVTvC/h20912C9ZlxCg9gMxo3TYlkXoVyIzRzc2zFeBSX7c+OUI35/wMpcnSdaXSyoD0895FUorM3SgQwyw8IiKyLgZiiIiIiKjK0GjFJ4DkJbi6v7G/K/LHbzRawSiTpaTuJmWLlhv6Ohd7H439XdHAR7ydJcuTSYMjSlsbOCptLbJvaUAnyYKlyaSZS97OdkZl3EqjRS13/Pp6e6x9paXZgMzKvdeRkfv0lL+RNq92dSh6mbziCvASlyeLYUYMVTV5Sbr/85cly4p9vK4aYGtnvI2+P0vSWUCr1mWeeLQA/HoB7k0Be2/ANt/nnK29LmDi2x1wbwJAAB4dA1QZxZtrRpQu+wUA3EMABz/AtRFg76sLtCSeBjT5SjLaOuiycgQtoC7mY5VQeq5xabL83KSlME1cZEBERGRJDMQQERERUZWhkpTUkpcgI8bJTo76kkCHJfrEaLWCUS8Rf0mWQFHIZDIMChWXsNl5MQ55astchSwNxLg5KkrV8D4/aWkyS/YJuRibIloOqelmsXnryWQy9Gnqj9/e6IAdb3bC0FY1Rfc/ysjD/x2+bdHHtCZpIEZayseSpIGYaAZiqCrR5OoyWQBA6f5kvaEsWU2jTaDKABL+0fVnAQCXBoBPF8CpFmBThOC4d0dd0EebB8TvLnqmiiodSL2su+3aCHCqrbstkwGeLXUl0DQ5QNK/T7aRycq8PFmuJFPVQXLBgNHPG2bEEBGRlTEQQ0RERERVhsYoEFOyX4eb1XAXLUt7j5REclYeVJLSaSXN2Hi+ubiETUqWCoeuJ5R4btJ95Sc9mVUaRqXJLNgjxqg/TI3SlyUrSNMablg2tDl6NPIRrf/m8G08TMsxs1XFkiYp7WOt0mQAEOApbkIek8TSZFSF6LNhFK66smIAkJesK00mswXs/cTjNbmPM1nSdJky3s8Abo10AQ91HpBwHbj+t+7r7mkg8RaQLSlRaWML+HTV7T89Cki5VLS5plzU9Z1x8ANcG0j2KQe82uhu5z4SZ8UYypOVUSBGcvGBUpIBK+1tJv3ZRkREZGnWyy0nIiIiIqpgVBpJabISZMQAumyK38/FGpYv3kspzbQAAPGSk/MyGeDtXLLeK7U8HdE6wEPUG2bXxTj0auxbqjkCxhkx7hbqDwMYlyZLy1FDrdGWqIRcflqtgEuS0mSW6A9TFLP6NsKBaw+hjwFmqzRYsfcGlgxuViaPXxrS5tVlmRFzhxkxVJXk6suSeT5Zp8+GcfAzznBJuaALxihcdH1g7p4GTs0A4i4AKXfMZ7f4hQB9lgCBnXTLLg0A53q6MmMZt3TZOPoMF1OyYnW9bGS2gFtT02PkTrr95KUAOQ8ApwDden1GTF7pL1woCmkWqFIuCcQ4iH/eMBBDRETWxowYIiIiIqoyjDJibEsWiGkmOYl/82EGMkvZ++NhWq5o2dvZrlQBiOdC/EXLl+5b5uRXsjUzYkzsKyW79CfHbj/KRGaeuEyNtTNi9Br6umBY61qidT+fjsHNh+ll8vilYdwjxpqBGHFGzMP0XGTlPT39dIhKRZ8Ro8wXiMl9pPvfQZzhiMy7QHY8ILMB8uyAzSOAjc8BV/4EkqMKLjEWfwH4bgBw8FNdfxmFsy7w4lhDl4GTckEXaDFFqwJSr+huuzQA5I9LZwqCbn36rSdj9Rk82Q+erCvjjJg8TSGBGJYmIyKiMsZADBERERFVGdLSX4oSBjoa+7vCNl82jVYArsSV7uSSNCOmtI3kpRkftxIykSOpmV8S0r4t0iyW0jCVXWOJPjHSjCU/V3v4lPL4FsfbvRrCXvHktaYVgE93XSuzxy+ptBxJIMbeegUVans6Gq2LSWJWDFUBWg2gehwoV3ro/tfk6XqxAOLgjDobSL0E5GYC//wArOsD3NxbvMcTtMDBJcD3A4G0OF2gx6G6LstFEIDE07qSaFJp13RZOHInwKWeeH36LV0wRr+dw+NATG4CoH0cUFW46FI9tXnikmVWkqsqrDSZ+OdNjkprkZ+RRERE5jAQQ0RERFTZaFW6LzKi0YpPzNiWsDSZvcIWDX1dROtK2yfmgSQQ4+tqV6r9Bfm5ipY1WgE3H2aUap+AcUaMJUuTKeU2cLYTn+xPyiz9a9moP0wZlSXT83W1x2ud6orW7Y18gKvxZXNleElJS5NZMyPGQWlr9JpneTKqElQpugCIrT0gfxyQNPSMcQFsH3/GCgKQ/C+gygb+Xg5E7ip4v07VANcagNxM0Dn6CPB1ZyDn8c8epTsgd9b9/vDopPj3iLxUIDNad9u9mS4bBwByHgI3/gL+txgIXwbEHn0yb7mjLuijz+yR2ej2r9+fleVpxEEVaUaMyQxMlicjIiIrYiCGiIiIqDLRaoAHB4D4vbrSJSSi1limNBkAhEhKW12ITSnxvgDggaQ0mW8pMzac7eRGWQaRpczaAUxlxFj25LyHk3h/0p40JXFREoiRfu/KwqSudeHpJA5aRcSklPk8iiMtW1wazJqBGAAI8BSXJ7uTaOKqfKLKxlR/GH15MDuvJ+syo3TrT20BHt4w3o+TDxC2BJhwAHg/Bnj3JvDOFWDOA+CDOKDHfF3WS36ZCcDO2Y/7t9joMmPkDrrMlkcngaSzQPx+4OFhXSDIsTpgX023rTob+PcbYOcSIO4KEHse+PV1IO/x+1Zfniwn3+8i+j4xZVCerLAeMS72CsgkvwKwPBkREVkTAzFERERElUnOA13pEK1aV14kNVJ38oQAACppj5gSZsQAxlkV0pP9xWWcEVP60lnB/uKsnci40vclkQZGLFmazNT+SluaTK3R4vJ98Um/ss6IAXQn/VoHeIjWxSZnl/k8ikOaEeNm5UBMbS9x4JAZMVQlGPrD5Pt8yHsciNGXJdNqgLTrQNRp4PLf4u3tXIFn5wBvRQDtJwM1WgL2ks84pSPQ+R3g1Z2Aa03xfdFHgAd3dLdzEwCvtrqATV4ykHX/SbkxpRvg1kR3W9ACEV8De/6jm5teZiJw7D+62/a+uv+zHzz5PcTQJ6YMMmIKCcTY2sjgai8J/FsgA5OIiMgcBmKIiIiIKpPse7r/5Y+vLE+/CTw6oQvOkFFpMrlNyX8dlvZguf0o06inRnFYujQZAAT7i8uTWSIjRnqiStrwuLSkpc5KW5rsVkImsiV1/5uVQ0YMANT0EAcaYpMrdqDBuEeMdQMxgZJADHvEUKUnCLqABwAoH2e/aNVPMkb0GTHZsUDKPeDIN+Lt5fbAq7uALu8CSnFGmUm1nwFeP2IcjPlnDQD9XGwA73aAUy3ALRjwfgbwDwN8uujKpwHAxe+BXYue9H/J7/haIDtZl+Fjo9D1hNE/x7LMiNGIf97byW2NxkgzOlOZEUNERFbEQAwRERFRZaFV6+q1A4BXa8Czle6q1txHuuwYgkpamqwUGTFBfi5QSEqbXbpX8qt8LV2aDAAaSfrEXI1Pg1DKDCmj0mROls2I8ZScGCttRoy0ZFwNdwd4OZc+yFUSNT0cRMsVOSNGEASkGfWIkZsZbRm1vcQnkqNZmowqO3WGrheLzPZJkCIvSRegkTvpAh+CAKReAw78F8iTBCf7fgb4NS3eYzp6At0/EK97eAWIvqi7nRWrCwB5tABc6utKkdnm+5y/fQD4811AYyZInpsB/LNS1xPG3ke3Tl+eTJ8Ro840HcSxIGlGjJ3c+PSXmyTwL+2BRkREZEkMxBARERFVFjnxunIhCmfdCR3H6oBPZ919ecnMioGuYX1+ctuS/zpsJ7c1yjgpaXkylUaLxEzLB2IaS+aXnKUyCvgUR55ai8w8cXaJpXvEGGfElC4Qc1ESHJNmMpWlpykQk5GrhuTtYvXSZAGSnkb3U3KgklzVTlSp5C9Lpm9YIu0Zk5sAnPoRSLgt3rbZUKDlmJI9bvOXAZ/G4nWnfgDUeUDWXfMlTdW5wLZJgEbyuSwthXZyLZAe/6RPjL5nna3ySVaNlbNicqWlyUz8vJf+/EphIIaIiKyIgRgiIiKiyiLrvu5/h+pP1ilcnlxlq2/+W4VJT+qWJiMGMC5xdaGEGTEJ6blG570sEYip6eEAZztxFkNpypOZyk6RBk5KS9rQvrRXKEdL+oxIg1NlSVqa7EF6DnLVGjOjy1dajvHV6q5WDsQESjJiNFoB9ypwsIqo1KRBFyBff5jHZcmSLhn3hfGqD/RfAaNu80VlYwv0XCBelxYHXD0IaHJ0mbSm/PsDkP5AvK7pi8D4PbqsHj11DnBoqS4jRmajy4BRZejuK6PyZIX1iAEAd8lnWgpLkxERkRUxEENERERUGWhVQO7jsmQONcT36WvM66+8rcKMM2JKF4iRZldIy2AVlbQ/jNLWxiKZJjY2MgT5uYjWRcaX/OSXqaCI9ERWaRlfoVy6E2NxKeIT+TUkWSllSfrYggDEpeSYGV2+UiXfaxsZ4Ky0bmkyN0eFUdYNy5NRpWbIiHkciNFqgLwU3W07T0CVDlzcBqjyfU7IbIAhGwA78Wd7sTXoDQR0FK+L+ENX/iwr1ni8RgUc+Vy8rtYzwAtfA9WCgNBXxPed+w5IvvPkdxBpeTJVyUt5FoW0R4zJQIzkQoKUUvYkIyIiKggDMURERESVQXac7qyuwlVXmiw//QkeZsRAbcEeMQDQVJIRczcpG+k5xT+RIw3E+LjaQVbSK50lgv0lgZi49BLvK1kSFHGxl5eqvJspRqXJShuISRUfW3+38gvEuDko4GovDmZU1PJkaZLXsYu9AjalfL8URaCXOGsoJinLzEiip5wmB1A/fn0r3XX/q1J0JUZt7XU9YtJvAVd2i7cL6gf4h5T+8WUyoOdC8bqcNODs77rfKaQ9XM5vAdLui9d1/wCwfRw87ToLkOfL5NSqH2fFPC5PlvM4k0b/XPUBJysxyogx8bPKXRr4Z0YMERFZEQMxRERERJVBtomyZHr6q1FVabrMmSpMrZWUJitlEKG+jzNsJSenrz/IKPZ+pH1b/CxQlkxP2sfGkqXJPCxclgwwLk1Wmpr9aTkqZOSKTyZWd7fcsS0JaXmy2OSKGWhIyxYfd1cH62bD6NWWlCe7k1gxjw9RqeUl6/5XuAI2jwMC+gsm7Lx0fViu7wRS48XbtZtkuTnUagMEDxCvu7IHSLj55PcKANCogSPLJNu2A+p0ebLsVgNoO1E8JvIvXf8bQBd40WryBZ3SjIM9FlSi0mTsEUNERFbEQAwRERHR006T+6Seu6OJQIytne7KWuBJPfoqSi0pTSYNohSXndwWdb3FJ46vPyh+xkm8JCPGEv1h9KSBmNsJGchRlawvibQ0mSXKp0kZXaGclQettGt8EZkq++XnVt6BGHFGTkXNiEmVBGKkJcOsJcBTHKi6w9JkVFmZ7A+Tr1RZ5h3gcrh4G5/GQGBny86j10e63xP0BC3wz3og486TdZe36sqM5dflXeMeNe2nipdVmUDCLUDuoNtvXtLjbJ/Hn4NWzIopSmkyDwsG/omIiArDQAwRERHR005flkzp/iTgIsU+MQCMS5MpStkjBgAaSnqwXIsvfiDGVGkySwnydRGdK9MKwI0SZO0AxqXJpGXELEGaZaMVjMtkFdX9VHGQw9tZCTu5rZnRZeOpyYjJEV+p7mpfRoEYSWmyaGbEUGUl7Q8jaPMFZ7yAuFPA3fPibdpOMA5+lJZnXV1QJb9HUUDEL0D6TSDnEXDoM/H91UOB+j2N9+XiC3g1EK+LOQ7Yeetu6y8aMWTJJJd+/mYUJSNGGmBmaTIiIrImBmKIiIiInnYFlSXTY58YAMalyWxtSv/rcCPf0gdiHlqxNJmTndwoy6Ck5cmkDdytkREjLU0GAEmZJTs5Js2IKc/+MHrMiClYoLe0NFkm1JIr24meelrNk2b1+p/PqlRA0OjKlAkCcOFP8Tb2bkDIS9aZT8dpgHdD8bozvwAXfwK2jQcSb4rvM5UNoxfQXrx851iFCMTYmewRI/55k5ylgiCULAOTiIioMAzEEBERET3NtJonV9U6+JsfZ+gTk6rbpoqSliZTWKD5uFFGzIP0Yp/IsWZpMsBEn5j4kgViyiIjxl5hCyelOGvlUUbJAjHxkowY/3IuSwY8PYEYox4xZZQRU7+as2hZpREQk8SsGKpkVCm6YEv+Ml35s2HSbgLXD4u3CR0FKM1kvZaW3A7ov0Iyxxxg9+fAtYPi9b5NgaB+5vdVu4N4OeY4oMz/O4jqSSBGlVKaWReoKBkx0osJ8tRa5KgY+CUiIutgIIaIiIjoaaZKfXwyxw6QO5ofJ3fUnfARtFa9ArWik5YmK22PGEBX+iu/pMy8YgcOpKXJLB2IaeQnCcSUMCPGuEeM5QMxAODtIi7N9igj18zIgt1PFR/X6u4VISNG/D59kJ6DXHXFC45Ky8G5OsjL5HE9nJTwkmRF3XxYslJ6RBWWyf4wj382Kz2B81sAVf4grUxXlsyaAjsBLUYWPq7LzILLo0kzYrISgeQYQOGs+30lNxFQuAEyG12PO7V1Aq25RegR4+5g/DOM5cmIiMhaGIghIiIieprprybVX11aEPaJgUaaEWOiVElx1fZ0hL1CvJ/rD4peniwrT410ST8OXwv2iAGAYH9xsCgyrvhZOwCQIsmI8XCyTpZENWfLBGLiKmBGTA1JRowgGJdQqwikGTFlVZoMAOr5iLNibjAQQ5WNtD8M8OTnuY0cuLZfPD6oL+ARaP159foYcCjg94mmQ4DggQXvwz0AcPETr5OWJ5PZAIrHFwhY4eIQQRCKlBHjYi+H9HqM5MyS9SQjIiIqDAMxRERERE+zvBTd/wr3wseyTwxUkitk5balz4ixsZGhoSQr5mox+sQ8SDMOMli7NFlqtsqoHFpRSDNirFGaDAC8JYGYhPQSBmKkPWIqQEaMm4MCrvbi7JKKWJ4sLVscHHQtw0BMA0kg5hYDMVSZCII4+wV4nBny+HMg9S7wUNKTpdWrZTM3Jy/g+f/qsmz1fJoAXWcBkw4DQ9YBhfVWk8mA2pKsmJjjZdonJs9EXymliQsvbGxkRkFmZsQQEZG1lE1+ORERERFZh+Fkjvv/s/feYY6k5bn3XaUcWlLnMNOTc9ydzbPL5gC7YGyMScZggz+DMfhwjMEc+9gGTDLYsLAYODbgJS3gJRoDy+Yws3FyzjM90zlKamWpqr4/HlWX3pLULamlbnXP87uuviSVSlUlqVRV/dzvfT8zzzvliJmgiDLp8huTY3bEVCOaDKB4skO9oanHp8oSYkSxoMFhhcdR3cv0pY0uNDismEwaxfXjA+Gym9fnOWLctSnOtzSIAk8ljhhN09Bfh44YgOLJjuXEw/VO1F8PFHM02Vw6YtaYhJgzIyzEMIuIzCT1SZEsOa6QIN3aGoATvwWQc66ye4FVt5S5jjhFl0IDJCu5bCQbYPVMHysGABtfC7x3FzB+DmhdBzStKm/dALD8RuDoz4zHPbl9YiZJeLI3AjhfGyEmU0CIKeCIAWhAQe4gg2CMHTEMwzBMbWAhhmEYhmEYZqGipIxs9VKEGKsXkG1UAEqHSoszW2SYHTHViCYDgPUdJkdMGdFkZiGmrcqxZAAgSRI2dDbglQtGwev4wCRu39Be8jI0TcsrUBXK168G+Y6Y8kcoB2PpvKbL9SPEuAQhpi9Yf46YkCmazOecS0eM+Hs6MxyBqmqQqyScMsy8MjWAotEQRaZiyRzAud3i/KtvB6wznBfUDBA5T26TdIjO84WweQH/VsDZMv3yWtfRX6Us3yk+Dl0EIsMkPKXD5MzVr0HS4aoPDilPiDE5YliIYRiGYWrE5TcMkmEYhmEYZrGgF25sWYFlJiTJcMUkL88+MZkaOWLM0WSnhyahqqX1YDELMR01EgvM8WQny3DtAMBkMpP3+ZkLWNWitcEkxFTgiDG7YSSp+pFvlbK00S08rs9oMpMQ45q7MXxmR0wspWCggig9hqlL9POvI6c/jO6ISYaAviPi/OvvLb4sVQEmzwKDTwDhEyTEqGk64Nl8tA6bD7C6yIGTjgCjLwDjewGlhr+p1o2AQzwvoscUT2Z1A7KdRJh0KH8Zs6BQNJnDYik4b4CjyRiGYZg5gh0xDMMwDMMwC5Vy+sPo2JuA+CCNRm1YXYutqmvMQoJtpqz7EtlgcsTEUgr6gnF0N7mLvMLA3COmvaE2YsFak1h0qgzXDgAECzQwbvTMjSNmtIIeMeb+MG0Njqo5oGbL0kYxEq7eosnSiopoShGmzWU0WbvPAa/DikhOlN6Z4QiW1EGPH4aZNamsEGPPFWKyLplLe4BMzvFOkoG1dxdeTnwACB4xBBWbF/CuomsCW0O+w0RNA+GTQPQCEOsH4kNA0w7A1TG796NmgOBBij4LbCURSJaBpTuAs88Y8118Hlh7MxA5J/aJSQzR+6+iS7ccR0yjqdcZO2IYhmGYWlEf/4kwDMMwDMMw5VNOfxgdfQRuDTLZFwIZ0yjZajliWhscee6QEyU6TgbzoslqI8SsNwkx50aieZ/HdEyY+sPYLBI89sIjjGdLnhATSULTSnMY6Qzk9YepnyJ+vhBTX46YyUQmb9pcRpNJkpTnijldpnDIMHWJkqBIUUkyhIdMjEQSNQX07BHnX3YD4GnOX05i1HC1WF1A4xVA262AZzlg9xeO+ZJtQGAL0HYzXQtoCjBxYHbOGE0FxveQsBPtASbPiNueS88L5MqVJCATpT42+mdQ5WuScoQYf140GTtiGIZhmNrAQgzDMAzDMMxCRXfElDOK1OanIoiaoiLIZYSqajCnhdks1RFiJEnKEzpKdZwMm6PJatAjBgDWtYuF7ZSi4sJY6U4MsxATcNshzdT0uULaTNFkyYyKyWS+ODAd/SHxc+0K1EcsGZAfTTYYThQsHM4X5lgyAPDNoSMGyI8nOzsSmdP1M0xN0AUHawMgZwNK9HO5kgAu7hfnX/+a/GVk4iTCaBrgXgq03w54uo1+MzNh8wEtO0mwUdNA8HBFbwWaRkJOYsQQfiZPGu9n5a3i/CPHgUTYcPEmR3OEmGBl21CEpOl4apWlogMvzL3O2BHDMAzD1AoWYhiGYRiGYRYimRiJKZJMRZVSyZ3/MnPFmGPJgOo5YgBgvSmerFRHTF402WwdMUqS+gaYCLjteb1XynEZmItTjTXqDwPkO2KA8uPJBk1CTD05YpaYHDGalu/gmU9CJiHGbpXhtNXG/VQMsxBzZpiFGGYRULA/TPZcPHIOiAXF+c39YXQHipoiISWwrbIm95JELhpJorjSWH/5ywgfB2J9tIzmawB3Fx3MxvdRXFnXVYDVFF958cWcPjEjhqM3E6NzV5Uw94gp5oYBgEaP2RHDQgzDMAxTG1iIYRiGYRiGWYjohRubr/wijD4aNR2s5hbVPUoBIaaaPUPWmR0xJQgxmqZVN5osegkYfAwY+C0wtoeKZKpRVDK7dk6WIcQUcsTUCpfdkhd7NhopLy6mP2iOJqsfR4zfZUODU2zXWU/xZGNRsSBqbmY9F6w1R5MNR8qOp2OYuqNQf5h0kI7Tlw6J87asA5pNvdyCR8g9ItuApqsBeRYCqc0HNKyl+6EjgFLGMTZyDpg8S/cD2wFnG4lCVhfFjoWOkAjTvlF83cXnaV4ASAwDkoX62QBVHRxidhhOJ8SY+18F4xxNxjAMw9QGFmIYhmEYhmEWIpXEkunoI1CrHAVS76TV/OinajpiNpgcMWdHIjPGTYXi6bx5OioVDKIXKSZG0yj7Pz5AI5MHHqUGzQDWtpv7bpTuMpiYQ0cMgDz3zkiZjpiBvGiy+nHEAPnxZL0TpcfE1Zrharu0KsDsiAnG0hiLcoGUWcCoCpAO0X1diNE0IBWi6b1HxfnNsWTRS9SHBQCargKs4jGkIhrWkhCiJIHQ0ZnnB4B0BAgdo/u+DRSLBpA41HglOWSil8hls3SH+NqLL9F1i2wj8Sk1YVzHJEdm/36y5Akx0wy6aDQNKjCf6xiGYRimWrAQwzAMwzAMsxDR3Sy6qFIOetEjHaIi0GWCouS/V2uVesQAwFqT2ySjajg/Gp32NWY3DAC0FojlmpHoRWDiIN33rgTaXpUtsHkpyiZ8Chjfh3Wm4napfWyA/AbG5uJVtTHHk41GShdiVFXLiyarWOCqEUtN8WT15IjJj8urTd+i6Vja6M4bxV6OcMgwdUdqgs65Fic5RwAgM0nCefAiMNEnzp8bS6YqOeLHesDZWp1tkmQjoizWC8SHZn5N6Ai9D2c74FsrPudoBrxr6H74GNB9nfj8wEFASee4YoYAVyfdjw9U7ZqkHEdMwDSoIBRLs/uOYRiGqQksxDAMwzAMwyw0NJVG0AJGzFg5WL0UB6JmgMzlU9gs5IixytW7HPa7bOgyFftniv4yF7xbvPZpC0YFMYswgS0k0Pk3AO23AY3bs0W2Pqxz9ggvPT8aLblJvHmUcC2jyYDZCTFj0VRej4CuOuoRA9S5EDNZxbi8CrHIEla3mvrEjFw+xytmEZIao1tHc860IJ3Te4+J87qbgaXXGI9jl6gvjNVtxIlVC3sA8K6i+8GD0/dqiQ8BiREScAKbC8/TsJaez8SBzi3ic0oSGD5KIg5AQoyjhRwyShJIjs367QDl9YgJuMRzWUpREU/n91ljGIZhmNnCQgzDMAzDMMxCIxOhEbSyDbB6yn+9JF2W8WSFesRU0xEDAOtM8WQnB8PTzj9k7g/TUGbBOz2ZL8KY8SwDmq8DZCvWekPCU6W4dnTyHTH1G01mbnxvlaW85c03CymarG2ePjtzPNnZYRZimAVMsogQk4kAQ+fFedfeY/R/0TQgku3H4l1N5/Bq49tgRJTp5xQzmmrEl3lXFb/+kC3Ge7TZAX+H+HzvHnLESBKdw5REjiumf/bvBeVFkwU8+ecyjidjGIZhagELMQzDMAzDMAsNvaGtPVB5QUYXYvSIs8uATKFosir2iAGA9XlCzPSF4yFTfFbZEVCRbPHO2V5YhNFxtgKtN8LndqLTK34OpcaTTSygaLL+oPlzdVa1H1A1qGdHzPBk/uc3H6wxOWJOD5cepccwdYWm5py7c4SYdBBIjAHDJiFmzR3G/Xg/kIkBsh1wd9dm+yQZaNpBt4khIHIhf57IOSATBSyOmV05jmx0WioItK0Tn+vbSwNJ9D45iSHA1UX3qxRPZhZiHNM4Yhoc1rzzg3ngAcMwDMNUAxZiGIZhGIZhFhq6i6WSWDId/bV6YegyIFPIEVPFaDIAWG/qE3N8YAZHzOQs+pioacr0B4CG1TPPb/MBrTdhXbNYcCpZiImao8lq64hpaRCFnpFI6YUxsyOms876wwD5QsxgOFFyTFytyXdqzY8jZm27KZqMHTHMQiU1QWKMxUG9uwB6nA4Dg8eAjOn4tvIW4/7kGbr1rjRcMrXA5gP8G+l+6BiQzvm9KQlg8jTd920EZOv0y9J72CTHgA5ThFnf3uw85ngyO8WvJUdn9z4AJMuIJpMkCX6XeD4LsiOGYRiGqQEsxDAMwzAMwyw0ch0xlTLliJmkYtBlQEYp1COmui6JTV0+4XFfMI7xaHEBoc/kgigrmix6kSLqbD4x6mY6rC6s62oXJpUqxORFk3lq64hpNTtiyoomE4WEzkB99YcB8qPJNC1fQJoPFFXDqEn0mjdHjCmabCicRDjBBVJmATIVS9ZiTEuHqI/K8AVx3vatgDcrZCRGSKyRLIBnRe2307OSRBRNAcb3AMHDwOjLwMgu6itnDwDupTMvx+YDLE5aTtsa8bnRU0A8aAgxyTGar4rxZHnRZDP0XjMPLGAhhmEYhqkFLMQwDMMwDMMsJNQMiSfA7IQYq5tGn2oqFYMuA8yOGFkC5CoLMWtavXDaxEvsw33FP99jJsfMypYSe/5oGhC9QPe9K8vZRKxdIgoxp4emd+0AVNSKpsTmxbXuEdNi7hETSUIrMbLGLMR01aEjxu+yocEhjio3R6rNB2PRZF4/pbZyI/OqxIpmT15kELtimAWJ7vIw94dJBYGRXnHeVQXcMJ7lgKW24jcAijttvIKuD9KTFFGWGCLBSLYCga2lR6LqrpjGJfkOmv795Ayyuuk6JDkKuJfQc/GBWQ8QKadHDAAEzI6YOEeTMQzDMNWHhRiGYRiGYZiFhC6aWF002nQ26EKOHnW2yDH3iLHOUJipBKtFxuYuvzDtcG+w4LzDkwkMmZqib1niLzhvHomhbM8AG+BaUtY2muPTLozFkUhOX3QyR1UBQKDGPWLMjphURsVkMlPSaweC9R9NBgCtvsr74NSKYdM+KUtAs2d+hBi7VcbyZtE5xEIMs+Ao1h8mFQRiw8BYnzj/qluzz4dIoJAkwLtqLraUsDiB5msATzf1gmncBrRcD7TfXt4AEL1PDNJA83Lxub49dJsbT2Zvoug2NU1OoFlQriPG3POMHTEMwzBMLWAhhmEYhmEYZiFRjf4wOvZGcZmLnIwqFmaqHUums9UkphzqLeyIOWJyynjsFqwq1RGju2E8y8vuGWCOe1I14OzF09O+ZvcZMbO/wWlFU42FmBZvfvF/pMR4soUQTQbki02lvr9aMmzqW9Ta4Mhzpcwla1rF/fUsCzHMQqNQfxiARJbBE6L7Q7YBy26g+5FzdOtaQoMv5hJHEzlj/BvoPONspe0vaxlZIUZNA60rxOf69tFtrhADAK4uup1lPFkyIzo47dbpz5P+vGgydsQwDMMw1YeFGIZhGIZhmIVENfrD6Ez1iQnOflkLAHM0Wa2EmG1LTY6YItFkR/rESLBNXb7SotLSkzRaWJIq6hngcVjzGsWf7uuluLMiPHFiWHh887rWqse6mXHZLfCaortK6ROjqBoGw+ZosjoVYgrEr803ZpfWfPWH0VnbLgoxpfY0Ypi6Yao/TI4bRk0DsT5g+KI479JrAIcXUBUgMUjTvCvmZDOrjsUO2P0Uc9Zkcm727qFzjqOZYsuUJDl+dSEmMTireLLyo8nYEcMwDMPUHhZiGIZhGIZhFhK6aKK7WWaD7qpJR6gotMhJKyZHTA2iyYB8IWYglMhzGQD5Ak3JsWS6G8bZXvEoaXM82cnhNOXyFyCRVvIcMXdsaKtoveXS4hWLY+Ym8oUYmczvcdJRr9FkZiGmHhwxJiGmrWF+Ysl01pn2VXNfJYape6aEmBZjWipE5/NRc3+YW7OvGaGecFZXdc73tUBVgOQ49bEZ2wOECzgrHdlzRWOnOD06DIR6AUk2nDOxPnqvFie998mzFW9aSik3mkx0xEywEMMwDMPUABZiGIZhGIZhFgpKghrmAoCtxKL9dFjs1CgXoKLQIsdcnK+VI2ZlixceuxiDYo4hA4CjpmlbO0oQVZQUEL1E9z0rK97Gtabi9ulxGDE4Jl46P45Yyoh5kSTg1vVzI8TkCxUzN7PvD4n9YewWGc2eOWhyXQH1KMQMmT7jtnl2xGzu8gmPh8LJgsImw9Qlmgqkxum+0B9mAgj3AyFR5J4SYvRoLqdJwKgXJg4CA78BRnYDoeMk5IdPAGmTUOrMiiyeBsBuit7U+8S4u+k2dhHQFOpLA9DyoibHUImYHTGOGYSYgEmICcU5moxhGIapPizEMAzDMAzDLBSm+sM0UJRHNbiM4skyytwIMRZZwuYZ+sSMRZLoN/Ux2eK5OHMUy+RpKlTZ/YCzZfp5p2GdOe5pXKLCoB59l8OTx4eExzuWNaJpjoQNc5+YUhwxA0Hxc+3wO2seo1YpddkjxhTr1t4wv0LMyhYv3CZh82gfu2KYBUKx/jDRi8DwBXFeuxdYsoOcJvFsLJm7a842tWTSYdp+TaP35eowriUiF8R57Y10vSJbgZbl4nO9WSHG2UafjZohMca7AmhYQ88FDxV1a05HXjTZjEKMeE5jRwzDMAxTC1iIYRiGYRiGWSjoQkw1Y0r0ZSVHp59vEZDXI6ZG0WQAsM0kxBw2CTFH+sVCstOqYbV3EgifKr5QJWHEkvk2zGr7zHFPF8NALA0gcl6YrmlaXn+Y2+colgwoJMTMLFQMmBwxnXUaSwbUZ4+YYZMY1Oab32gyiyxhU6foiinkMGOYuqRQfxgAiPUAI5fEaStuAiw2iiXTlPqNJdPFFncX0Hk30HwN4N9E02K9YtSpJFMkm8UJNJtEpb592XkkwLs6u+xzJFz5NwKeZST2jO8jMSYxTM9PHAJCx6hfWhGSyuwcMdwjhmEYhqkFLMQwDMMwDMMsFKb6wwSqt0w9vz05tuj7xGTMPWJq6JLYauoTc6gvBE0zhKAjZ8Xs+00dXlhkkONFL9yZCZ+iApWjiUYQz4I1bV6Y3/6ZcVAcjmI4Ik4PR9A7IQobcynEVBLd1RcUt7crUFkfnbnA/P7GIvn9beaaIbMjZp6FGCC/f5K5vxLD1C368Tw3lkxJArFBYNgkxJhjyVxVcsNoGg3kiJwDEiOzW5aaIbEFADwrjOmOZnLragoQM70vRysJMX6TGDVwAFAydN+9lNw1mbjhgAlsA1yddN4b2wOMvgQEjwLRHuofM/Q0MLyL4jpVRVh0niNmhoEXAZfoiAnFU8I5m2EYhmGqAQsxDMMwDMMwCwG9kAIAtkD1lmvzZosnKo02XcTkO2JqJ8RsWxoQHo9MJjGkN0GP9eJIr+hA2trdQqN/AWBif74ololSZAsA+DbOevucNguWNbmFaceCXtrPclwxT5rcMF1+JzZ0iG6aWlKJI+bSeEx43N24cIQYVQPGo/PXm0BRtTyxq22eo8kAYKtJiGFHDLMgyO0P48iJkowPAOEBIG5ydKy8RYwlc82iP4ySovVMHAQGHwOGnyMRY/RFEjCiJURhFiLWS2KLzZvv8vFm+5ZFLtC5RMfRDMgOwG/qbZeOASPH6b4kG8JOJDtQQZKAph2As52etzXQZ9KwluLQpGyk5sQBYPR5YZ3lR5OJjpi0oiGaUorMzTAMwzCVwUIMwzAMwzDMQiATpeK8XoyoJs4OutVH4S5SMqpYmLHItbsUXt7kRoNT7ONzqDdIdxJDOGzSvDYv8QP+zYDVQyOCg4fEQlb4FD12tpEjpgpsMjVBf+JithAV7ZkaXfzkcVMs2cY2SNLc9Vtp8YqjlEvpEXNpXHTEdJsEp3qi2ePIcybNZ5+YsWgSZkPOfEeTAfmOmP5QAmN1EOPGLEJSQTreZmIzzjojybHC/WEiZ/NjyTxtQNtGIDlceSxZYhgIHiahZeC35CKJXiQHjmyl84dspUiviYPA4OPlO2SiPdntXZ7/nGsJINvoeiWZs1yrF7C6AYcH8Jp6m+l9YgASYiQLkAoZTiJJBlquBZbcB7TfCjRfDfg3UBxax10UYSZb6XvLWedshRgACMbmTxRnGIZhFicsxDAMwzAMwywEcmPJpCpfwunNgBMjefEei4mMIlaYbTV0xMiylDeKX49TmghNoHdSXPfWJX4qJjXtoFG+sX4qkoWO0+hoPQpmlr1hcrl9Q7vw+Nmzk4iqLhL8ksMIxlLY0zMuzHOH6TW1plA02XRxMZqm4aLJEWN2/tQTFllCk6d++sQMh8V1W2QJzZ75F2JWt3rgtInHPXOfJYapGE0j98jIbnKOhE/S/Ux0dsvVBzfogx10IheA4YvitFW30rG/kliy5DhFdI2+RMvWe6fYGsil0nI90HkP0HId0HEn9XOxOEmgGd9H7plS15MOk1ji7s5/XrYa0/U+MgC9L3sTYHEBzUvF1+QKMRY74Mm+flKM7yyIxQE0rAHcy/LWmVLKE2K8DmteXCn3iWEYhmGqDQsxDMMwDMMwC4FaxJLp2Hw0WlVTaDTuIsUcTWapYY8YoECfmN4QoKZxdFB0bDisMta2ZUdL2wNAYDsg26lXy+QZYOwVes7VCdhN0S6z4K6N7ULhKZlR8VRf1m2VGMEzp0YEd4TTJuOG1aYomhpjjiZLKSrCiUzR+UcjKcTTophYz44YIF9sGp1HR4y5P0yr11Hz30kpWC0yNnaKDi6OJ2OqQiYGDD1F7pHkOA10sDjp+Dv6QuXOGE3LiRjLEVXUDPVQGekT5191azaWbCj/NcVIR4DRl0k0Sk2QQOJdQW6RznvIQRLYAjhbjQEcsg1oWA103EHnfjUFhI6U9p50N4y7i5ZTCO8Kuk0MiUKWo4mEkyaTmN+zy/T6Vcbrk+JAgKII66Tvq9weMZIk5bliWIhhGIZhqg0LMQzDMAzDMAuB1ATd2gO1Wb6eRa83yV2EmIUYWw2jyQBg25KA8PhwXwhaciIvlmxDpw/W3CKRpxvovIsiWJztNJpYslTVDQMAfrctT1h55ExWxEiO4glTLNmNq1vgtFmqug0zYRYpgOn7xJjdMHaLjHbf/Pc4mQ5z/Nq8OmLM/WHqIJZMh/vEMDUhdJQEA9lGvUc67gDabqYosUyceo9UIsYkR0nkkO1iL5XoRWB8AEiLoidW3WKKJQvMsPwxYOQ5Eh8kiaLCOm4HAlupf4rFPv3rJRlo3J51YPYZAlAxlJTh1tF7uRTC6qEINMAQboCsI8YJNLaJ809cAII5MW1Wj+HSHX2xtN51Vg+JTTnrLDeaDAD8LlGImeBoMoZhGKbKsBDDMAzDMAxT72gqxYEA5WfGl4ouxCSGKmvguwDIKOYeMbUd6b/N5IgZj6bQNzaGIyPmWDJxpD8AKpK5Oikbv+MuKrDl9hioEq/eIkbmPHU6jIQiYSQcxRPHxcLc7RtNBbQ5wGmzoMEh9tqZrodK74RYMF3a6KoLR8d0FIpfmy/Mjpi2hvoRsbZ0FY76Y5iKSQUN10rrjdR7xOIk50bLDUbPrtEXyCFTDvqgBr2pvE7kLDBiiiVrXgP4l+a8ZgY3TGKYRAo1QyJP261A4zba9nKwBwwHSugwLa8YsUt0bWD3zywS6UJNrNfodWYPABY34AsADtO5rGe3+DiwnYQVTQHGXgaipn46060zehHQ1LxoMkcJQkyzyYE5nejPMAzDMJXAQgzDMAzDMEy9kw5TAUS2U4RYLbAFqIijZmgk7yJEMTlirDXsEQOQCGCOOjl8cQxHTL2RzQXmPCyO8gtsJXL3pg6hRhhNKXiu340vvyIhmjIiviRp7vvD6LSYo7umc8SMmYSYOo8lA+pNiBHX3V5HjpgtJkdM70Scm2kzsyN8gm7dS6mfSi4WJ9C6MyvGxKhfV6noPWcAUVTRNOpjMmISFlbdSs/p7g/nNMfa+CDFVWoqzddy/exE+ob1dF2RiQPhIu9RSZGABEzvhtFxtlK/GCUJpLOCqSQbDs+21eL8F54TH8tWoPla+l40DZg4AASPkttF/0sMGyIPQMu2usiFFO+vyBFjPhabHYIMwzAMM1tYiGEYhmEYhql3ah1LBlBxxJV1RyzSeLK0YhJicp0SyXEqblXaD6AAkiTlxSl9/rkwekKiAGQuMM8lrQ0OXLOiSZj2H/s0PGRqGfD7O5aiwz8/7ghzdNd0PVTM0WTLmlw12aZq0uqtHyFmZLJ+HTFr2715xdQjfeF52hpmwZMcAxIjJBD41heex+IEmq6i+7Few5layrLVFMWd5caSpUNZN0u/OP/KW+g8r6bpNXbxmDxFrB8Y30MijLuL4iulWZZ0ZAs5UAASiRKmkQKaBkzsJ1HF5gVcS2ZepiQDjmxUWG60mDv72haT4+e8SYjRl9F0JdCwJrtt54CJQ8bf6EvA4ONA6ASdtyUJcC+feh/JvB4xM8dqtpmFmDALMQzDMEx1YSGGYRiGYRim3kkF6baWQgwAOPU+MYPiSNNFgqKKhZmpviyaBgQP0vvWR0hXCXM82bkJ8XO1W2SsazeNxJ5jXmOKJ3v5UgKKZohFDquMv7pr3Vxv1hR5jpEyesQsW4iOmHmMw6lnR4zNImNjh/hbOdLP8WRMhejHes+y6Z2mdr/RsyRU4vkhobthOkWhJD4ADJ0FVCVnZglY+SqKBQWov4pUwK2pJOg8pWnUR6xxx+xFGB1nC30OAEWB5Yon0fP0WJJJlJJL7BOm94nJXZazjYSmZlPMZbAHCJri2nT8G0mQcXVm/zroT7bTZzJ5Ghh8gsQZzzLaztQEUhkxZq0UR4xZeB6eLDOOjmEYhmFmgIUYhmEYhmGYekeP9rAFarseRzMVN9QUjehdZJgdMTY9miwxDKQjdD8+QCN/q8Q9mzumfX59R0NJBaJaMtM2vuumlegKzJ+zpMWc2z9ZPI6qdyIuPO5uXIBCTB31iGn31Y8jBsh3j3GfGKYi4kPkgpRkoGHtzPP7NpA4ksi+bjqEWLJO8bnIGWC4R5zWdSXgapw5lix0nKJD7QFysBQSa2ZDYCutW1PJHRofoEEgeiRbYAtgK9DPrBi6EJOaoGgzgHrcWRyA1wc4TU7QC6Y+Mbm4l5L7p/lqoPka+uu8i4QhZ9Z5E+2ha6XsZ15JNJnZETOfx2KGYRhmccJCDMMwDMMwTD2jKkAmKxLYaxxhlRtPNnlq0blizD1iLHL2UjhyxpioqdSUuEpsWxrAA2+9Et1FIrK2d89fLJlOV8CF7d2Bgs81uiz481tXF3xursgTYoo4RlIZFf0hkxCzABwx5uJfKJ5GMqMUmbt2KKqW99maRaL5xizEHGEhhikXTTPcMN6VpfXfsnoAd9YxUqyPik5qnMR82QY4Wozp6UmK/crrD3ML9WdJh+kcrEd65ZIcp2g0gASTaoswAIlSzVeT+0dTgfG95I7RVBI3PMvLW57FaQg3yWzcmWwD7C20/Z2bxPkv7Cp/e91d1CPHu4qmhY4Drm5oGpBS8t2nM9Hm4x4xDMMwTG1hIYZhGIZhGKaeSYeocGRx1qxhu0DDGkCykCMmcq7265tD0qZoMpssUYFLHxnt20BPRHuqKkK9bnsXnv7r2/CtNwRwyzJjuW67BX9y48qqrWc2mOPJdD5wgws+p22Ot0ak1OiuvmA872tb1lz/QkyrN/93PRqZ+yb0Y5EkTFpl3TlizD2XesZiCMXT87Q1zIIkNU6ih2wFvGtKf51vHZ0nkuPkqCnGlBumIz+WLDoMBIfF+VfdasSS2RsBi9gTi6IzD9N9z/Ia94qTKfLMs4zWqyQBqwto3F7Z8qbiyXI+L32wR5tJ2LlQoE9MqTSspe8zHQbUBDKanHcsqySabDyaynPWMAzDMMxsYCGGYRiGYRimnpmKJZsj54TVQxEkAI0aLrU58QJAUcyOGAmInKUH7qU0qla2UePfxHCBJVSORZZw+7IEvv07Gp79y+349z+6Cs98+DasbvVWdT2V8uoC8WTLfBrevjE2786o/GiywkKMuT9MwG2bdxGpFHwua95o7fmIxDH3h7HIEpo99iJzzw/r2huMSMEsR7lPDFMOerSYsy1f9JgOi9NwXoSPFz4uqmkg3k/3XaaG9PEBYOCE+DqrE+i+Pqc/TIFYsuiFrHBkMwYL1BJJAgLbSNyweYGmq2ndlaC/n8SI8b71z6XJ5PyZrk/MTFjshqg2eQopOf96yVFBNBlQ3IHJMAzDMJXAQgzDMAzDMEw9owsxtY4ly8WzzMiKH99Pt4uAjGmIrFVSgPggPfCupibEesPi6IXqrlxJkcADYFlHO+7e3FFXsU8rWjx5boMP75RhlzLGPjhPtHjFYuloJAXVPNwZwCWTELMQ+sMAgCRJddEnxtyYutXrgCzXIAJpFtitMtZ3NAjTDlwKzs/GMAuT1ATd2hvLf23DGhIl0pNA6Jj4nKZRnJfuIsmNJctEyWU6dFZ8Tfd1gMUGJEfpsVmIUZJA+CTd928sTziaDZIE+DcA7bfNzoFjb6TPS00B6SBNcy+hW6cVcDWJ80/XJ2YmvKtILMvEkEol8p4uxRETcNvyRHGOJ2MYhmGqCQsxDMMwDMMw9UwqSLdz5YjRadwOyHYaiasXghY4aUUUlKxK1u3j6qCRv4CRg58YnhJOqrPyrJhh9VQ+urjGfOr3tmBJwAWrLOFdN67Ea7dkC4l6kXCe6AqI/XVSiopLE/nfjVmIWbYA+sPotNSBEGN2xLT76kcozMUsGH7tqbM4NxKZp61hFhy6IFCJECPbDMdo5JwoxoSOkvNDsgBN1+THkmWiwEifuLxVt9LxVVNJvLGJIiMmT5HLxu43etQsJCQJcGadL7rL1N5M1xZQgO6rxPlnE08mWwDfegBAKhHMe7qUHjGFRPHhcL6owzAMwzCVwkIMwzAMwzBMvaIqQCZbYKxlLnwhLA6gcRvdnzxjjCJewChmR4wapTvenGb0Vo9ROIr2VG/luqA2l86mXJQkjciO9gChE0CsjxpE57BtaQDPfuQ2HPn4PfiH122CpH8O8yzEtDU48iKyDhdo0m6OJuteQEJMq3f+hRizI6atzvrD6Ny9SYzRm0xm8J7v7kU0mZmnLWIWDJkYHQslufLBDe6lOefGs3Q8jZynPwBo2pF/nI8PAOE+YHJMnJ7bH8bshlHTQPQS3fdtIlFjIeLQ+8RkhRjZAjizIn/7OnHe2QgxAODuBmxepJA/2KEURwyQ35OMHTEMwzBMNWEhhmEYhmEYpl7JhCnuxOKgyI25xtVJRSeAmgXPc6+Q2ZJWzNFkGuBoor9cPCvoNnqxerFsU71+AtVZXiloGo3aHniU/kaeByYOAZOngfF9wODj9DdxgIqToL4gTpuFXq9H6yTH5jWeTpIkbDa5II705fcuyhdiXHnz1Ct50WSRuR+FbXbEFOqXUA/cur4Vv7Nd7L9xejiCj/zkELQFfoxiakw6O6DA5hMdK+XiWW44YyZPA8EjdN+/0WhGr5OJkxDfe1ic7vQDnduLCzGxS4Cm0LY6W7BgcWaFmFRw6jwDZ/YzaukU5w1eBCZmMQBCkgDfBiSV/O+2lB4xQP5xj4UYhmEYppqwEMMwDMMwDFOvzFcsWS7+TYBsBVIhINY7f9tRBRTVFE0mA3C05s/obKeYGDVlFMlmix6HM1ffZXIcGH4WCB41il9WN703zzIasS1JVCSMXgJGX6A+NrnYGkgE1FRjX5wnti7xCY+PFHDELORosrroEWOK4GmvU0eMJEn47O9vxQZTr5hfHRrAFx8/zc4Ypjiz6Q9jxruSzo86nm7qIWMmMQhAAwZN/WFW3gIoUUBJUJxZbk8ZTQMiF7LrWTH7bZ1PLA7DIZQcodupPjEWwN0szn/+2dmtz9mBlCo6YmQJsJYQTQYAbT7zsZijyRiGYZjqYZ3vDWAYhmEYhmGKMOWimEchxuIAGtZRFn74OLlk5IV5CZk2R5PJIHHCjCSRYBG5QIKGqzN/nnJQUkYMWK2jyTQVCB4yIm1ke3aU9hKKhMlFzVBhcuIANZ8efQFo3Sn2sLE3AvFBms/sHJpDtnSZHDH9IWiaBikb1xOKpRFOiAV4FmLKwzzyu157xACA227F//ujq/C6B3YJ3/uXnziNrz19Blcvb8Kt61vxlmuXwe+qz55MzNwjTUVE5ggxapr6oGkKIFnp/CbbKOZqpn5eDavpHJmOAL51heeJD9DzwxfE6WvvAuJZod/RIjp0kqPUU0a20bF7oeNoo8EciSFy2TpaAdkBqAlg6dXAqd8a8x76EbDjjypflyQhZW0GMDw1qdRYMgBoaxAF6OEwO2IYhmGY6sGOGIZhGIZhmHollRVi5ro/jBnvSuqdoiQphmWBopijyWQNsBQp1tuzokNqfPYr1gU1q2fmwt5sCZ8yRBjPcqD9NnLAmEUYgAqOzlYSXywOIB0GRl+kwqRONT+HWbDFFE0WjKXRO2H0uDHHkskS0BVYQNFk5h4xkbkv/g2ZHDHmgmS9sbzZgy+99cq81hlpRcML58bwmd+cwKvvfxYRdsgwAInUmWykYa4QEzpG/V2iFynKMXyKnIQTB0tbrnsp4N9QOOpMSVC048ARICX25MKaOw3HpcsUS6b3m3F3L9iBDwL6+0sM0/dgbaDINSUGrN4pznvhOWD0zKxWl7KKgwbsJbphAI4mYxiGYWoLCzEMwzAMwzD1iKoAmUm6P5+OGIAKTP7NdD9yjkbqLkAyhaLJCjliAEOASIfou5gNuhBTazdMehKIZAtYTVdRQ2mLffrXACQQtdxA7plUEBh9yXjPesFSj/SZJ5Y2uhBwiyLW0X4jnswsxHT6XbCVUXybbwo5Yuay34miahg1iT/miJ565Lb1bfjQXUWcCAAGQgn894H+Odwipl6xIUYigGw3jvupEAkwALlbGtaQgC1J5GRJzlKA1pfdf0qc3r4F8LQYx9Xc/jCZmCHQLPRYMh1bgPrcqRly+9ga6LpGSQJL1ufHk+17cFarS8libKG9wDiEYtSDO5FhGIZZvCyc/04YhmEYhmHqmcRotrl7lYqnmTAtS7ZTv5L5xtVOTXc1lUYLL0Ay5mgyi0zxKIWwuqhwpGmzFyEykewyG6afbzZoGkWSaRo1i3Z3zfyaXGwNQOsN5NhJTVCjaICKZZJEBbNMbPpl1BBJkvLiyQ7n9Im5NLFw+8MA+aOwE2l1Tp0cY5EkTD+PunfE6Lz/9rX42h/uwA2rmmGzSHnPv3x+bB62iqk3bFr2OCy4YbLnMvcS6vfi30gCtrs7+/yxyleoqUD0At0fOCk+t+YOIJmNzrL56FyjE802q3e2kki+GJAkOi8BJHBZHPT+IAGZILDtTeL8Bx4CMpULICmT+9VhKf26zHzcG40koZoPjgzDMAxTISzEMAzDMAzDzAZNA0InqL/GxEHKmq8G9RJLlot/MxVUEkPz7pCohIypOGOx2JCXa5SLo0qxXGnd2VRDISZ2kUZvy1bAv6WyZdh8gG893Y+cywqBFsORNc/fuTme7HBfeOq+2RHT3VQH4mUZtHjzBcG5HIk9Fk0JjyUJaPKU4KaqE16ztRM/+LPrsf8f7saf37paeO6VCwvvWMVUnzwhJtZPsWGSBfBtFGf2rafpqQmarxLiAyRgx8PA2EXxuTV3Ga6XXDeMqhguGs+KytZbrzh1IWaQzi32xmzkaRzYfK84b2wMOPE/Fa8qlRHdr3ZZLTJnPmYnYEbVMB5LFZmbYRiGYcqDhRiGYRiGYZhKUdPA2Mti35TJ00aPjtmgx1nNdyxZLjYv4Mo6LeKD87stFWCOJrNZZ+jXUq3+KFOOGO/sllMMJQmEjtN93/rZOaj0ngSZKJAcoWl1Ek+2ZYlPeHy0LzQV33VpfGE7Ylx2CxocYi+IuRRiJkxCTMBlg0WeRqSsU7wOK37vSrG5eV8wjv5gvMgrmMsFO7KRmvZGEjzCWbdLwxrjmKmm6Vg6/BygKYCaAsLHyd1SLlNuGFO/E3sD0H0t9UsBxP4w8X5ap9UlCjSLAUczOS7VFJ1LbD76y8QBjwdY8Spx/j3/WfGqknlCTIbWUwLNHnve+IzhMMeTMQzDMNWBhRiGYRiGYZhKSEeoWJMYph4qTTuAhrX0XPAQjbSdDakg3da6r0i5OHOa7i4w8hwx1hlG/E8JMROVR84pCcrFl6TaxcyEjlIB0e4HPCtntyzZCriX0f3IObqtEyFmq8kRMxZNYSBEDebNQkz3AhNigAK9CSJzV/wzj/heSG4YM2tavfC7RJH1lQuzFFOZhY2ShKxlf0/2ABA5S4V5qwvwriahJXIBGHwSmDxDx21NAcInyOU6eWq6peeTCpFDUZKB3oPic6tuof5vaoaiR20B47l4H926l0/v1lyISLJx/RAfyOkTE6No1x3vFOe/8BwweiZ/OSWQ54iRMkCqtGsyq0VGs0c8Fg9PJiraDoZhGIYxU9dCTCaTwf/9v/8XK1euhMvlwqpVq/CJT3wCas5oRk3T8LGPfQxdXV1wuVy49dZbcfSomFueTCbxgQ98AC0tLfB4PPid3/kd9Pb2zvXbYRiGYRhmMTG+l1wDVhfQehNlzPvWU28OTQXGXqm8qb2mUqEGEIs09YCjlQpE6XDJI0zrBXOPGJt1hmbkNh8JE2rG+D7KRY8ls3qoEFVtUiEg1kffSWB7dYp33qyYkxghwVEXpNIhGkk+TyxrcqPBKbpGjvSFoKgaeifiefMuNFrmsUm02RGzkIUYWZZwzYpGYRoLMZc56ayIbG0ggWUyW+D3bQLUJDD8DBA8TG4NmxcIbAUcLYCrk0SDnofptlSi5+nW0Qb0vCw+t+ZOI5bM1W4cs9U0NbIHyu/xtVBwddJtIivEWD30maspYM0tgKtJnH/ftytaTUoxCzHpsgbHmHt2Dc/hsZhhGIZZ3NS1EPPP//zP+PrXv46vfOUrOH78OD73uc/h85//PB544IGpeT73uc/hC1/4Ar7yla/glVdeQUdHB+666y5MThr/LH/wgx/Ez372M/zwhz/Erl27EIlE8NrXvhaKMn//SDIMwzAMs4BJjJAQIVmA1lcZrhVJAgJXZKNP0sDoS5UVrtPhbH8O++xipmqBxW44JJILyxVjjiaz2mYQYiQp571WWMjVBZxaxZLFsv0EXJ3Vc09Z3UZj5cg52gctTton08HqrKMCJEnCli7xPR7pC2EgFM8T2RaFI2Yee8Q0uheuEAMA16wQC7qvnOc+MZc1WTefZg+Q2KEpJLS7u8jBmo7Q+TawFWi7BfCuANpuAjrvJUFGTQF9v6b5ZkJJkTgOAKEgkDSJ+GvvMs6djjZjemKIjrG6QLEYcbTSdVMmDqgqDU6wuOh6SQkDV7xNnP/A94FkCZ+5ifweMYrxnZSAuU/MXB6LGYZhmMVNXQsxL7zwAl7/+tfjvvvuw4oVK/DGN74Rd999N/bs2QOA3DD3338//u7v/g5veMMbsGXLFnz7299GLBbDQw89BAAIhUL45je/iX/913/FnXfeiSuvvBLf+973cPjwYTz++OPz+fYYhmEYhlmo6JFNnmWAxVTMly1A8zVUuM5Ey480AYz+MPUWS6ajF4/iQ/O7HWVijiazzhRNBsy+T4xeuLM2VPb66VBzikt6nFi10CPOYr3Z2LM6iSdbahJi+sO4aIolc9staF6Ajo5WLztiqsXVJiHm5NAkgtxw+7JFmor6bDRiPx3NQKyfBlZIMgkv3hWic9HdASz9XRLSE4PA2EsktExH7CK5Wu1+4Nwz4nOtGwFPI50XJAlwthrP6Y4b3TWyGJEtxntOjZLob/MBSpy+h6v+WJw/Ngb852uAcH9Zq8kTYiwaEL1I7tYSyHPEhDmajGEYhqkO1plnmT9uuukmfP3rX8epU6ewbt06HDx4ELt27cL9998PADh//jwGBwdx9913T73G4XDglltuwfPPP4/3vOc92Lt3L9LptDBPV1cXtmzZgueffx733HNPwXUnk0kkk8Y/P+FwGACQTqeRTqdr8G4XJvpnwZ8Jw9QH/JtkmDkgPQkpSkUBzbEUKPh7kwHvRkjjrwDBk9BsbVRsyF3MdL/XyUuQYsPQHEuKLH+esTZBUjJAbBBaKkEjXBcAaVNciSTbZj5eyt7sex2G1lD+dyElJgAlA01yVv+7jPdBSscBiwua7K/u8i1+SLIbSIehhc7mfA4j0JzLq7eeMtnQLo4UP9QbxFefEvsIdDe6kMmUVnArlbk4vza7xX/NhsOJOTufj5r60fid1gV9LbGhzQ2nTUYibfzmXzw7gjs2tE3zKmZRomlQ4hT5lYYXUryXjsmaA9L4QbrfsA7Q7IWPobZWSJ7VkEJHoUUHAe0FaM3XF46aVJKQQqdpmY6lsJx+TBj5qqy+HepkLx1LHS3QFABKGtAUSNEBQFOgWVvq87xfLawtkJReYPISCTGyhyI248PQOq6EZflNkHt2GfMPHoL277ch86bvA44GSL0vQxo4CNg90NbdC23JjrxVxJLi52eTNWQSo9BioyTAzUCzR+wxNRiKL+jj4UKD/59lmIUD/14NSv0M6lqI+Zu/+RuEQiFs2LABFosFiqLgU5/6FN761rcCAAYHBwEA7e3twuva29vR09MzNY/dbkdjY2PePPrrC/GZz3wGH//4x/OmP/roo3C7F17UQa157LHH5nsTGIbJgX+TDFM7fMp5uLQRJKUmBC3Tm4sDyjk4tHGkpWMYlzcV7N+h/15tWgRObQIOLQi/chpWLY6QfApD1vPQpPq7ZGtVDkHWUpiwTCAlBeZ7c0oiPGkBYHwHBw4ehtZ7eNrXSJqCNmUfAA0jlkmoUnlOgbbMPkjIYMwSR0aqbtxMo3ISdi2EqLwEEbn67gmXOgKfeh6qdBhBaSWa1BNQYcOIdf4i6cbiQO6/MKORFHadEbP/26Uwfv3rX9dk/bU8v/YPSwAMUfNs/0jN3oeZ0xdl5IYlDF08g1//+vScrLtWLHXJOJM23tPDT+1D8pw6zSuYxYhFS6BFOQQNMh578nm0qfsgQUVSOgOHFoQiOTEqA7J2DM2Rk2gPH4Q7OYKxhg0413o3NMmCgNIDlxqBHbuRkBqRkPYhJK8UzumylkajegJWLQ5VciCshHDP8AlhW14c9UJ56hewayFMyssQk8lp6VAnEFBPQ5EcGJ3humKhI2kZtCn7AWiIS81waWNwahNISJcwYQnC4boPN1n2w64YPfakyCBs37ojf2HP348R7yac6ngdRr3GNdZx0/EsGYvgzIlD6D3zMKKWmd2jI4PisfjUpaE5OxYzBvz/LMMsHPj3CsRisZlnQp0LMT/60Y/wve99Dw899BA2b96MAwcO4IMf/CC6urrwzne+c2o+yVTU0DQtb5qZmeb5P//n/+Cv/uqvph6Hw2F0d3fj7rvvhs/nK/q6y410Oo3HHnsMd911F2w228wvYBimpvBvkmFqjJKENPwEoC2H1rLTiK0qOn8C0vDTgJaB5t9kxD0h5/d65x2wxU5Cil0E4AawBNIEjZDVfBsBV4BG38p1FhUUXAopdhGaZzng3zrfW1MSnz/+LJAwIkauu/Ya3L6+dZpXENJIAEiHoDXuAFxlNFFWkpCGqPCrdb6mus6hTAzScHbZbbfTyOJqoymQhp4A1BS0pmsgTfgATYXWdmtt1lcCqqrh/uNPIpos3HupxWvHp//oerT7nFVd71ycXz2nRvCDs/unHqdkJ+6995aarMvM186/AISMXhY7r9qOe69c2A3DT9rP4Mwz56Yej1sace+9183jFjHzQnIE6pAFrxw8gbtu3wl7EICSAGQn6fIRFfL+hyD17IKUNoooneH92NQsQXntl4DkEKTxPYCSBGQHvc7mg+bfTNcBagrS2ItAejNgcUJrvgHynm9COmpshmbz4Nrfex+ksWeyx9HbjF4wE/shxf3QPCsB/+Y5/HDmB2msHUiOQLM3QkpNUOSlvRGaawnQeCUwdhu0/3obpPFzMy6rNXIMrWeOQe26Csprvwy0rsehR04CfT1T8zQ3t2Ht2jVY07QcWtdrZlym5egQfnz+4NTjtNWNe+99VWVvlikb/n+WYRYO/Hs10JO0ZqKuhZgPf/jD+OhHP4q3vOUtAICtW7eip6cHn/nMZ/DOd74THR3URHRwcBCdnUaW6vDw8JRLpqOjA6lUChMTE4IrZnh4GDt37iy6bofDAYcjv4GrzWa77HeuQvDnwjD1Bf8mGaZGxM8BskyFF0/7zPPbbEDTViB4GIidBRqWUe+YLJKWgX1yP6yZIGCxAu4ltGwJ1BzY5gPUGBB8BWi5XnjtvONdCiT7gcw4vc8FgCk2Hg6btbRjpbsNiEQBdbK896qG6Xu1ugF7lb+7+CAt29ECuGrVS8gGeLuBaA+QGQWczVQw0yKAbf76F23u8uPl8/k9e6yyhK+9/Sosba5BP54stTy/dgREx9RYNAXZYoVFnn6AWTUIxsQ4hVafa8FfR1y/ugVfzRFijvSHoUCG07YwohSZKpHKIGO1QIUDNsRglS1AcgJwdwPBMeAnfwXKCMtHPvQQZE8TcNcngEkXHXM9K4B4H6BGgYmXAfdSIB2mc7XdC7TuJIHl8H8Jy5I23AebHKdrCGsD4ArQE5pK51GLla4RFvjvriQauoHMBH2GFit9bhYrkB4BZA3o2Aj86RPAj/4IyI0pmwa5fy/kn/wx8BcvQdHEY6bT5YNFtgCp/pI+385G8Vg8MpmE1WqdcbAvU134/1mGWTjw7xUlv/+69r3GYjHIsriJFosFqkr/Ra9cuRIdHR2CBSqVSuGZZ56ZElmuuuoq2Gw2YZ6BgQEcOXJkWiGGYRiGYRhGQFWAyAW6711d+us8y6lBsJoBRl8CwiepKW06hGb1OJAcJadE87VA0w7A1gDIVsDZArTfTOJLehIYeZ5G8dYLjhbKyM/EafsWABlVEx7bSo2A0Z1Pqfzi/7Ton4u1ysKApgGxS3TfM3PMyqxwL6Hb+KAhvpT7OVSZLV2FRaC/f+0mXLNiBpdaHdNqahCtqBrGo7VvMK9pGsZNjewbPXXmwKuAK5cFkKthpRUNBy4F5217mHlCidONZAfSQRJNNA1QVeDJLxUVYaZ44SvAri8CLn3gpwq032Yce2O9tEyLA2i5gUSYoWOAKZYM298CxAfovqvDmJ4cA9Q0vd4uxqkvWlxddN2jZYBMBLC46FpHU4HYRZrH3QT80c+AK98uvtbTCqy/F/AWGAwzdho4/SiSplEXdmc20SQ+DGRmvo5qMx2LkxkV4UR1+44xDMMwlyd17Yh53eteh0996lNYtmwZNm/ejP379+MLX/gC3vWudwGgSLIPfvCD+PSnP421a9di7dq1+PSnPw232423ve1tAAC/3493v/vd+NCHPoTm5mY0NTXhr//6r7F161bceeed8/n2GIZhGIaZb6IXSUxwdpD4MR2xS+RSsbpyCjIlIElA4zZgeBcVa9JkW5aUDCxanIoPbTeS+wUQi/dWD9B6IzD6PJCJAhMHyBlTD8gWEmMSw0BiiASkOiejisWZkp0GjmxxPx0mQW2mfWVqhRG6tXlL3MISSY6SACbbaN+tJfYm2keVhFGwTE3Udp0zsHVpfkzwG65cgnfcsHwetqZ6tHgdsMgSlBzBcCicyBNoqk0spSBlKlw2uRe+ENPgtGFTlw9H+oyoiFfOj+P6VTM362YWEboQAzukdBhIh8ilePA3QF70lQR0XQkMHBQFmif/iZwU3auAeD8Q2Ao0bqeBFqFjgJoEmq4xjvUHvi8utqETWHkzMPQ4Pc69htDFGWdHwT5yixLZBri7gOgluraxeul6ItYLRC/QYBdJAqx24PX/Buz4YyDcB3RsBZpW0XPpBH3Oz/wzEBkylv3S15FyfkJYnd3hoeupTJTW4Vsz7eYVOuaOTCbgd13eo70ZhmGY2VPXQswDDzyAv//7v8f73vc+DA8Po6urC+95z3vwD//wD1PzfOQjH0E8Hsf73vc+TExM4LrrrsOjjz6KhgajGPDFL34RVqsVb3rTmxCPx3HHHXfgwQcfhMXCtnSGYRiGuWxJjAAT2QxwyUKFEXc34GjOL4akQlRsAQDvqvKLJTYf0H4riRZ6HroSQlpqgNZykyhiZLJCjD7N6gaarweGn6FtjvZQ8acecLZlhZhhoGH6wkY9oChmR0yJ36PFSQJcJk7fnXPmvjIAaueI0d0w7iUkiNUSSaLRy5FzUwXNsgWpKnPz2la47RbEUlQo3dTpw6d+b+uCj42xyBLaGhwYCBkjtgdCCWxZUtsYuEKumybvwhdiAOCaFU2CEPPyhfl1czHzQIb6viianUSYdJCiJvf9SJxvyVXA2x4GPM3AwR8BP/sz8fnf/iPw+k8ArStp8IGrE7AHKIosF1UBDpmWve1NQHqCjpsWJ2AL0HRNAxKDdL+cAR6LAfcyEmKUGH0uVjcJNJl49vPNGWTQfQ2Aa8TX25zANe8GrA7gF39hTD/3NJpWnAVgiCkOm4Ui5MIngcjZGYUYp80Cn9MquGCGw0msaav/AScMwzBMfVPX0WQNDQ24//770dPTg3g8jrNnz+KTn/wk7HbjHwNJkvCxj30MAwMDSCQSeOaZZ7BlyxZhOU6nEw888ADGxsYQi8Xwy1/+Et3d3XP9dhiGYRiGqScSw3QryTTyNdYLjL5Af0rSmE9JAGMv0zzONsCzsrL1Wd2AdwXQdCXQcTu0ztdg3LIxv+9L2iTEADTK1r+R7geP0qjOesCZjQZJjVO0Sp2TznPElHEpXEk8WS0cMUrKGEHtrnEsmY4eT5aayMbHaBSnM080ex34xjuvxh0b2vDWa5fh+396HVz2xTHAqsMvHg8GQ/Gar9MsxNgtMjyL5PM0R9Xt65lARlGLzM0sSrICsiRpJMpkEsCu71AMlo5sI+eFJ+uW2v5m4NX/bFqQBjz/XYo0i/UWX9+5p4HoiDhtmymWTBeNUxN0vSHbaBDI5YSjic6NsoPOq5mYEfcWvVD6cra8EXCLn91N4z8RHtstFrr+AoBYT0mLbfOJx+LhyWSRORmGYRimdOpaiGEYhmEYhqkZyWyhpPFKiv/yLCdnTHKM3CfJMRrZOvYKiTE2L/Vwqdaoe6lIoVMv3ltNxXvPSoru0BRgfD8Vw+cbq5v+NA1IBed7a2ZEMfWIsZbTBH1KiCkxlktNGz19qumIifZQAdHup7+5wB7Ifs8KgOxnlhydm3UXYefqFnzzj6/BZ96wdVH0M9HpNAkxue6YWpHfH8a24N1FOmYhJppScHxgYfS0YqqApk0dhyUtRY6Y0weAiUvifLd8BGjbKE67/r3AzR8Wp42cAk4/SwM5ig0+OPgD8XHndlp2POt8yY2TjPdnp7XToJDLDc9y6g+TGCanpWcFTU+MlD7gxOYErvoTYdL1k4/Bj8jUY7tVBjyr6EF8kBw4M2DuEzM8WUc9+hiGYZgFy2V4tmcYhmEY5rJHSRjOE0cLjcxs3Aa03UxOFCWZdcfsJoFBtgPN19Ko1ZpuV8pw45iFGEkCGq+gOKjUBMVr1AP2AN2mQ/O6GTOhaRrSpmgya6nRZIDRJyY5XpoIpgtqFmf1Irw01Rgp7F1VnWWWiivrilGzRft5FmIWKx0+l/B4cA6EmAmTI6ZxEfSH0WltcGBli0eY9uK5+XNzMXOMmsw6XyRYkAbCl4Dju8V52rcCN/3vwq+/5aNA6wZx2p6HgWSE4hrNJMLA8V+K07a/LesaTYnOF00zhBjddXi54VpK1zpKjOLILC7DaRu5UPpyrnm3cJ51aEm82fLU1GO7VSYnksVJAlrs4oyLzBNiwuyIYRiGYWYPCzEMwzAMw1x+6EVkux+w5BQdbV6g9VVUFNE06g0jyUDz1dTotdbo/WGs7sLFe6sL8GcjWMMnjXi1+cSWdWXUuSNGLaCdWMuJJrM20HeiKTRydyYKRczNlvgAiYgWB/VtmUvc2fWpKRpNnA6LEX5MVZgXR4xJiGlaRA4jALh+lRhb9AILMZcPel8rixM2LQL50mFyuupIFuD1XwEsRQZZWKzAPZ8Wp8VDwIH/BibPUD+TXI7/N0Wf6chWYMvv57hhcpwvybGcWLKWyt/jQsZiz8aRySTEZKKANxv/GrtYknMFAODrAja9Xpj0DutjsIC+a7tVps/dnY2nn5x5IAtHkzEMwzC1gIUYhmEYhmEuPxLZWDJHgabrsoUiyBq3URG98Yq5y24vFkuWi6ebiuKaSr1ropeKzzsX6E2H69wRky7QF6KsaDJJKq9PzNR3WUUhRh+B7Vk59zE2Nh/9HiQLoGWLY/PYJ2axktcjJsxCzGy5YbV4/H75/Dj3iblcyMToVnbCpY1DGjb1B9nyBqDriumXseYOYN2rxWlHHgFCA0D4mDFN04B93zG99i7A2wok9P4wncZzuhvG1Xl5xpLpeFbQ4JPkGLl9HS008EXNUDRsqf3nrvtz4eFSaRR3ynsBAA5L9vP1LKfbaAWOGI4mYxiGYarAZXzGZxiGYRjmskV3xBQSYnQ8y4H2W+c2MqRUF0XjlYB7KRV+Jg4A4dM137Si6H1KMjGKVqtTzP1hgDKjyYDyhJip73IaUa0ckuPkOpJko5g01+guHL0wxvFkVSffEROHVuN+UBOxxS3EXL9K7BMTSWZwpL8EVxuz8Mk6YjSosKphYLRXfH7NXaUt5+5PiS5VNQO89AMg2mcI0k9/Frj0kvi67W8hZ20mTiK2fs2hqeRwBObe3VhvOJoBeyO5TcPHszGs2+nzTo4CI88b/damY+nVQNcOYdIfWR4DkHXEANkeNBItd4YeNK0mIWaEHTEMwzBMFWAhhmEYhmGYy4v0JP1TL8lG3496QS/ez+SikGRy6jSsocfhE8DEITFyZa6QbUZsWx27YjJKASGmnGgygIpFAIkiM66wyo6Y6Hm6dS8V4/TmEl2U1BSKKGMhpuqYHTGJtIpQvMQR4RVidsQsph4xANDW4MSaNlEQff4s77uXBXo0mZaBP9YLKWP6La26tbTltKwBrn2POK1nD/DM14HRvcCRnwDPfFZ83tMGrH+NIbg428hxC5B4o6ao/9zlGkumI0lAYCvdH99P10GOZqBlJ/V0SYeB4efoM0uMkpsldBwInyKRK3c5171XWPR18gm4kTCEGGcLOY4zUSA+NO1mtTVwNBnDMAxTfViIYRiGYRjm8iKpx5I1118cSKaMviKSBPg3AoFsz5hoDzD8jBG7Npforph6FmLUAtFkZTtiGulzVxL5vQFyURUjEme6mLlSycSNYp6en18umgZER4H+A8C5p4FgBZF2Vg+Jl7YGY0TxdJ8DUzZtDU5Ipt2y1n1iJqJicXqxOWIA4AZzn5izHKt3WaAfnzJRNEQGxefatwIN2cbwqkICe+QciQEju/ML9bd8BHCZBm+c2Q385EPAz0UBAJIM/O5XAasDSGTXK8SS9dGtuwt5P/jLkcYdFH+ZiZADRlXouqL1JnKVKgmaPvoCMHGQ+vOETwLDzwIDjwHBwyTgbLiPBodksUkKrpOPw65Hk1k9WeFLM6I+i9DmEx0xk4kMEul5GOzCMAzDLCoKdIFlGIZhGIZZxEzXH2Y+UdNG8/NyivfelYDFDQQPUWF89EVyLvg3U1P3ucAWANBP0Vl1SqZANJmtXEeMbAFsfnqfqXHAWiS2ThfUZHt13CuRcySkOFqoWFUq4QHgxX8DTj4CBC8a+5eObwnQfR2wfCew7U2A0z/zMj3LqWCZidM2JUcA67Ly3g9TFLtVRovXIcTgDIYS2NhZxvdeJmNRcb9YlELM6mZ890WjP8ieCxNIZVRjpDyzOMk6YqTECDxRk/i2+ja6TYwA43vyG8OnXgEC27LN5AG4AsB9/wL8+F3ifOMF+o3c82lg7V3k5khPktjibKPnNBWI6+LMZR5LpmN1UG++kd0kUoUOk+vX6iIxZnw/nWssLhK54oN0PrMHSKSJXABifUD77UD3tUDP7qlFv0o+LP7OvSvIYRq7SN+5XLgkZu4RAwDD4SSWNbur+tYZhmGYywu+8mQYhmEY5vJBU408d2edCTFTsWSuooWBorjagfbbDLdErI9Gis5VzxbbAnDEKPkjWS3lOmKA0vrE6GKfPVD+8nNRksD4PmPkrndVaa+buAD8z/8GvrQNeP4BYOx0vggDAOE+4OhPgV//NfDlHUD//pmX7eqiEccWB5AOcjxZDcjvE1NjR0xs8Ttirjc5YuJpBYd6g/OzMczcocQBqECkF8646fy0+nYq4o/vo4K8xQE42wHfehrMoGmG+0Jny+8Db/kBYJ/GtXrVHxsRWZELdOvsMJwaiWEaeGFxGucTBnAtAbyrSbyKXgJi2X4+sg1ouRboeg3g7qYBJ7o70+oC/JvINaOmgchZYNVtwmJvMgsx7iWA7KD1JIs7iL0OK1w2izBtMFzbYzHDMAyz+GEhhmEYhmGYy4fUBPW3sDiq17ujWmRK7A9TDNlKMWVtr6IihZIAQkert33ToUeTZWJzJ/6USSaVH6FllSsQYvS+QtP1iZmKoukobZnpSSB0DJg8SxFk6TAV8IaeIlENIBFGH1FdDE0DnvwkiSp7vlXedxEbBb79eqB37/TzSTKNELf5SHBiIabqdPhEIWYwVLv4N0XVEIwt7h4xAIlLGzrEYyvHky1y1DT9ZRKQBk9CONpbncCy67MiTIqOZx13UsHft47cGXoPttBxOj7rbLgX+NPHgcYCMZErXgXc+y/kgFHThpiQGykZ76dbF8eSCThb6XuwNgDIimAju4HxvUDwCEWvhk/QgBpHS/Y6JwlMngLs2T47kfPAihuFxa6T++BJDhsT7E0UM5qJAInifWIkSUJXQDwW907EqvVuGYZhmMsUFmIYhmEYhrl8mIola6m/Akhab+4+y54i9gDQdCXdj/XS6NtaI9uoKALUrSsmk84voFQkxNgb6TYdpkJb3oriRkSbswQhRlOBsVdIhAkdA8b2AEPPUOa9miaRq+1VQGDzzPvsi18Fnv08iY3FkGTA5in8XDIEfPd3gUsvT78ez3IagZwJA6mw4eZiqsJcOmLC8TTMqX2L0RED5LtiXjjHQsyiJhtLBiUOadgUH7b8RiB+kRyyshVovjq/Z5x/I7ktADo+T541nmvbAPx/T4rui5b1wJu+A1iyzpfYJToW2xqoJx1AvU/0WDI3x5IJ2Bvpu3C0AhZP1sE8DsT6SWBJR2gQTdMOoPUGOi86WsjNFOuh71tTAJ8XYU2MD2sc3C2ux9FIIk70Eg1gKMLSRnE5vRPcE41hGIaZHdwjhmEYhmGYywd99H699YcBDEeMrQpOHXsjOSgi52hUaftt5cedlb3OAEWGpIL1F/sGIJPOL2ZbKhFiLE7A6ib3T2oi36WSGKBbR3NpPXrCp+hzszioqJSJAUpWNGpYR6JHKaJhz/PAo39fYHvtwBV/CGx7MxDoBrwdVHAcOw1cfBE48BBw6UVj/mQY+O7vAX/4MPWOKYTVAzjaSDRMZl0x1dhvGQBAh98lPK5lHM54LN811eixFZhz4XPD6mY8+PyFqcd7eyaQzChwWC3FX8QsXDLZormagjR8SXxu+bV07AWoD4y1iDjdsJqOl8Ej1Bze1UnHfwBwNwFv/ylw+lEgPg5sej1gzy5H04xYslw3THKYxAKr2xD1GUKS6RwYH6QIMlcrfYdqgkQTyUr9XfSIN9kGtFxHgxaiFwE1CUgWKJFLeF7djFdbXplatG9gN4A/zb7OSjFo4VMkxKUmDKerie4m8Vh8aZwdMQzDMMzsYCGGYRiGYZjLAzVDPS2AuhQKplwF1Spo+zZQ7EYmSk6Lxm3VWW4xbH4AfXXriEmnxR4pVlmCVKkryt5EgklyPF+IiZcRS5aeBCLZ/gOBrVTkq4TJIeDhP8l3wlz/PmDnBwBfgZHXrevpb9ubgB+9HTjzuPFcKgL84C3AX7wCNLQXXqdnORA8RPtYYlgsNjKzYi4dMeNRUYjxOqyLVpi4fmUzJMkYAJ/MqNh/MZjnlGEWCbojJtgPKW5y7TVno6w8y6hnyHR4V9JxPTlKx7yW643nZBlY/+r81yRH6Nwr2wDXUmO6HjXpYjdMQRyt9FmnRgH/upnFKkkGGrcb10/pSaRgxy51iyDEuHt30Q9fP+c7WrKDRyYpSrSYEMOOGIZhGKbKcDQZwzAMwzCXB5ko/SNucZCroZ5Q09TTBZh9NJmObKECBQBEe2jkZy3RG9PrYledoShijJjVMotoOr1ok5owrSRpfM7OGUQVvRG0ppFoU6kIo2SAH/8JEBkUp9/8EeDVnykswuRicwFv/j6w9h5xeiIEvPhvxV/n6iBXjJoGJk+T0MlUhQ6TEDM4h0LMYnXDAIDfbcOmTp8wjfvELGJ0IWbguDjd0wr42sgF499S2rIat1HRPzFi9H2Zjsh5unV307kYoGOk3pOEhZjC6INkUuPlnVO8K+jWYkdK0fCculV42hobBoZz+vw4mgBbI8WdxU3nzhzM0WSXuEcMwzAMM0tYiGEYhmEY5vJAFzrqTYQBjNGcFqcRu1ENHM3kXAAovqOW2LIFzky8vCbxc0QmYxJi5FlcBttzhJjcPjGJbEHHHgCsrryXCUR76PWyldwwlfLEx4Ge3eK01bcDt3609GXYnMCbvwusuUuc/sq3gHiw8GskGfBvoH02PgDE+8rabKY4ZkdMJJnBZKJAP6IqMGESYprci7M/jM4N3Cfm8mFKiDktTu++kpwR7iWGSDITVg9FRQJA8Oj057hM1OjNpgsEAIkwmkrLsvtLW+/lhtVDf5pW3uARVxddO8kOJBUJPVo7Lqkm5/PZp4z79ib6DpQ4uXj1Hn0mzNFkA6EEMopa+nYxDMMwjAkWYhiGYRiGuTxQdSFmhgL5fJDJFgFq0WfDv5GK5ulJajBfK2SbkbNfh/FkmYxYOJuVI8bqzRaLFGB8v5F1FM/2h3HOEEumJIBwdpS2b2Pl4uDISeD5B8RpvqXAG75RuMCoZmj0b/gkED5NPYSiF2mUt8UOvOafxYbVqUlgzzeLr9+znJwx6TAwtrey98Dk0e7L3x9q5Yox94hp9CxyIWa1KMQcuBhEPKUUmZtZ0GRiQCYNjFwUp3dlBRVzrORMNKymAQdqCggdLT6f3hvG2S72ntFjyWaKQrvc0V0xyeHSXyPJFDMHIKVZAUjYpZrcTudyhBiLg75LWwOJMInCrhizI0ZRtZpGRTIMwzCLHxZiGIZhGIa5PNAb99ajI0YXYqw1EGJkm1Fw0oWCWqHHk6WCtV1PBWTM0WTyLIQYSQKarspG1QwBkbPkjEmO0vPuGWJnIudJFLE3Go6lSnjxqwA047FsA970HcCTU2xW09SUeGQ3MPAIMPYKPQ6foJHdEweB0RfpL7CEGk4L6/gakC6Si291A83XAZDIcaW/f2ZWOG0WNJkEkVoV/8Yj8+iIUVLkClOSM89bJa5d2QRLzm8/pajY0zM+Z+tn5hAlDoxfIDEml86NgGwHbIHylqf3IwEonixyLn+exCi5HQHRDaOmqW8MwLFkM+HICjGJkfJelz2XptL0fe8yxZPhwm4gk3OscTTTOTgzaUTGmWh02+Cxi4MauE8MwzAMMxtYiGEYhmEY5vJAd8TIdSjE6LEYtir1hzGj9x+ZKyGmDvvEVDWaDKBYk0B2xG34BBA6Ts4YW4M4CroQqWzh17PcaB5cLtEx4OAPxWk73w8svcp4HOsDBp8kB0xynLbP6qGRw55lJBg52wDJQiLK0DPA1e8wrWcEOPD94tvh3wR4lgJaBhh8orL3wuTR4ZubPjFmR4xZAKoZ8UFg6AlgeBcw8CjQ/xva/8KnDIdZDWhw2rB1iRgLtfsMx5MtOjSVnIfBS+LkhnbA5SfXRSXHXnsAaFhL94NH6U/fX2N9wNhL5JR0tBiCAkD7u6bS+aEWztfFhKOFvptMlFxNpWL1AM5WpBT6Xnerm6FqOd9xJg5cetl4bG8yhJjkeEFBWJIk7hPDMAzDVBUWYhiGYRiGuTzQHTEz9e6YDzLZHjHWGgkxzvaceLLJ2qwDAGzZAmddRpOJjX8ts3HE6HiWA+6lVIjTR0HrolcxNNVwDDmaKl/3nm8BmZzivGwDrn0P3c9EyeEyvo9idGwNNJK74w6g43a637idXD0t1wHtt5CwpKYAWxRYdq24rt1fBpQijZMlGWi/A4BEYlSUe8VUA3OfmFo5Ysw9YuYkmix8mpxZasboiaVmKOIufLLm/axuWtMiPN59hp1ciw69J1xIPB5pvna6U24sWS7+DSRAA+SKGd8LTJ6h462mksDdcp0o9Og9tFwcSzYjstXowzZdBFwhPMuhJw0G0YAj2grx+dx4MkcTOaM0AFCLumLMfWLYEcMwDMPMBhZiGIZhGIa5PKhXR4ymGqM+ayXEyDYaZQrU1hWjCzGZ+PTNjOcaNYOMKjbYtc2mR0wugW3iCOeZhJh0mL5z2T6zc6YYmSTwyn+I07b8PuDrJJFn6BmKdZFkwLcBaLuZHDBWd8HFweoBWm+iHggAsOVO8flgD3Ds58W3x7uKYng0BRh5mmJ4mFnRYRJiBsO1Kf6Nx8TvqqaOGFWhonX4BD32rgQ67waW3Ae030YOM0kiUbOGYszONWKfmCP9IQRjdXS8YmaPkv29hE19RrzZAr/D1Mi9XBpWA0076BgbHyARGqBjYeMOsdeWkio9tpIh/Juyn+0giVyl4mxHCsYxLC+e7Pyzxn2rh3rF2APkSo4VHkRgdsT0jrMjhmEYhqkcFmIYhmEYhrk8qFdHjN4fRrZRUaBW6Ln0tRRiZKtR7M/U0HlTLmoKGVGHqY4jBgBkC9B0NQkr9gA1AJ4OPZbM3lj5Oo/8BIiYRu/e8L5soXtfNhqnCWi/FfCtFYuCxZBkKn4FNlMPhdY14vO7vlg8MkqSgJYbqf9SrLf8UcxMHvPmiKlVjxglBYw+D8T6jV4bgS10X5IpltG7Emi8guaPXKDYpxqwY1kjnDbjN6FpwIvnOJ5sUaELMZOi20nztZP7rxrnWvcSoOV6w9WlHz/NkWeJAdrJ7P7KxffLDXtAjP5MlOhak2SkbIbb6Xl1s/h8/34glSOkOJoBezNdhyVHDSdVDksb2RHDMAzDVA8WYhiGYRiGWfyoaSpOA/XniNGFmFq5YXSc7VQgSocpuqpW6EJEOly7dZSLmswTYmyWKl4G27xAx53kKpmJ1ATdVirEaBrwwlfFaSteBXRuJwEkEyVBpPnayop+nhWAvQHYfp84fegIcPGF4q/zLqfR4OkI9fmodT+iRU6HXyz+1axHTHQOesQoCWB0N7m1ZDvQcgM5tArhXmo0RI+cA0Inqr45TpsF16wQYwF3cTzZ4kJ3mU6aBDZfB+CYRSyZGUczubnabzUchWZiHEtWEZ7lgKebznnje+k4oirk9gydoPNMJl8USVqN6MF96lpkckteagbo22M8tjdlRbmseFbAFcM9YhiGYZhqwkIMwzAMwzCLH32Uo2wjB0M9oQsxthoLMRb7HMWT1aEQo9TQEaMjW0pr/jxbIeb8s8CQKbbphr8A4kNGn5rGK41R2uUiyYBvE7D8KsBvilnb/73ir7M4gYY15LxKjAATBwuOLmZKYy4cMcmMgkhS7P1TlhATvQT0P0JF0nSk8DyZKDCyi563OIHWG2fujeRZBjRuo/uTp4FU9XtO3WjqE/P8GXbELCqUOJAIA0mxaK752mfXH6YQFocYTylsRwJIZvctF8eSlY1/K11TqCmK3Bx4hPqfTZ6mflJDTwBje4Dk+NRLUppx7ovBiTPSCnGZPTkDCvReNBY7AI0cnSbMPWIGwwmkzBcUDMMwDFMiLMQwDMMwDLP40QvCljqLJQMMd0qtHTGA0b/kchNi1BQUU93EWk1HTKkoCRrBK0kUvVIJL/yb+LhpNbD6NiB4kB57VwHOlvzXlYMrW6xcf4s4/ejPgOQ0kXPuZVRsVGL0XicOFI8zY6bF3CMmFE8jlsoUmbsygrH8Xj4lCzGTZ+n7VdMUNzb8NIlvmRj9JUYpXmxkN+3zeh+iUgVnz3KKfgKA4KGq70c3rhZ/I+dGo+gPcuTQokGJA8FLwiQNoD5as4mFLJdodhscTfUXi7oQkC1A8zU0sEBNUX81q4ucc44WOi7EB+g4M74XAPJEkiOW9eIyLz5v3Lf5spGqfkBN0nWL6drF7IjRNPCxgmEYhqkYFmIYhmEYhln86HnxljqLJQMgzVU0GQA4O0gESAULRnpUhSkhZrJ+ivBqEmlzNFm1HTGloLthrA1U/CmX4ePA6d+K067/cyB0GFCSNCrbv3H22wlQv4M1N4n9ZdIx4MhPi7/G2UaFds9yIB0kZ0z0QnW25zKjw5d/rKp2PJk5lkySAL+rBCdV6DgQOkb3vSso9lDTgOhFYPAJ+ht9AQjq+6WPnDDlFqL9m+h3kgoCsUszzl4Om7p8ee91N8eTLR6UOBASY6ZStgZoniWlORergaYBsYt037N8bta5GLG66fjRdCXQcQfFgDZdCbTeALTfQg46SSJBOD2ZJ8ScsJqEmEuvAEpWhJYkEuZkKyBljwemeDK/ywafUzxfc58YhmEYplJYiGEYhmEYZvEz5YipMyFG03KiyYpEm1QTi8OI4kjUyBVjcQOShXryKHWSpV7AEVP1aLJS0ONTZopmKsau+8XHzgCw4R4gPkiCSdMOUTiZDXY/0LoV6L5CnD5dPJkkUcN1i8voxRQ6RqIcUxYehzWv+FdrISbgsk3/u9A0YOIQMHmGHvs3AoGtQMu12cixZpouySTIOduBhrVA687KmqNbnIAvW0QNHQOU1PTzl7NoWcLO1c3CNBZiFhGZOBASz3FxRwBwtM7dNiTHyB0mWwFn58zzM8WxNZALxuo2TfdRTym970+sDynTyf601dS7Jx0FBg4Zj/V9Qo/zjPXmDSLhPjEMwzBMtWAhhmEYhmGYxc+UI6a+okFkpEiwkOS527Zax5NJkiEq1aC3Q0WoqXxHzHxEk82mP0zwInD4YXHade8BUoN037PMcCNVC98GYMNt4rTel4GRk8Vf4+7ORr14qLClqeSgYMqm0y8eE6rdJ8YsxMwYS5YYpj5EkkTFz4Y1xnOOJhJcul4NdN1LDcxbrgX8GyrvVwQAnpXZHhFpIFzd/WinqU/M7rNj0OrFxcdUjpqm82p4SJictPvnVojR3TDupfXXm26xoccYxvvzHDEJqxvwm/rz5MaT6T2DNJWuxXL7+mQx94npZSGGYRiGqRAWYhiGYRiGWfzUqSPGiux2Wd3VczLMhF50SAUBVanNOuqtT4ySnH9HjKYC6awwVYkQ8/wDVFzUsbmBHW8HEtlio3fV7LfRjMUJrH8d4PKL0/d/t/hrZBuJMQAgZ4tXiSEaGc6UhblPzGC4ukLMRKxMISaVLU66u0n4K4Rsq270kySR6wag6DNdzKwCN5mEmJHJJM4MR6q2fGaeUJJ0OykW02OO5rm7BlBSxmAHd5HfClM9nO3kxM1EkUxEhafssgZ0rBPn73nBuG9rMPYLS9b5EhfjyfIcMeMcTcYwDMNUBgsxDMMwDMMsfqaEmPpyxFi17D/z1jmIJZtaqYd6NWgqkBqvzTp0ISZTJ5FUBR0xcyzEpEP0mct2+g7KITIC7PuOOG3HOwEtK+y4OspfZqn411GvmFwO/tDI2C+EdyXdZsJGc/boxdps3yKm0yTEDISqW/wzO2Ia3TMJMbqjq8JoPTOZGO0X4VPAxEFg9CUgeMQ4Xus4mgBPVtzTe9NUgRXNbnSZPuNdHE+28FGTJFpHxPNbVI+vmgvivXS8t/vpj6ktshVwtQMAUomg8JTDagFaTT16Lr4AqDkXBfoAFd29F+8XBqp0N7IjhmEYhqkOLMQwDMMwDLP4mYomq1dHjHduV2zP9kZI1qjoWG+OGDUFxZQ4NOeOGL2IXUl/mJe+DmRyitOyFbjuz4BotoF5LdwwOlYPsO0N4rToCHD60elfoxe2kP2coz1UmGRKJs8RU+Vosolyosk01YgarMTRZSbWCww9RQJM+CQJMolhIHIeGHyS4uzUHLHPt4Fcg8lxIFGd45YkSbjRHE92ZqzI3MyCQUkC8QkgKQqXEUfH3G2DLjyzG2bucFE8WSohXnfYbVag0RRJFx8HRk8Zj50k4kBJ0kAVNQMkBqeezu8Rw44YhmEYpjJYiGEYhmEYZnGjKkZBr86EGIuWLaza5liIcWSLj8kaFR2nHDExsZg6XyhJZFRReLHOdY+YZHZ0drlF7EQYeOU/xGnb3gxYFRr1bfcbTdIrZSaBpPtWoG2tOG3fNPFkgCEOZWI0ylhN1a4v0SIl3xFTXSFmzOyImU6ISU/S/ibbZue+0lQgeBQY3591DAQo5sy3niLIHE20nskzwOATRkHb4jTi0CZPFV18uZiFmJfOjSFjzjFkFhZqAgj2CpM0SULE3lXkBfrr0nSMmjgIDD8LxAenn78YqQn6vUgWo3cJU3ucbYBsQzIjRq7aLTLgdAAe03kyt0+Mo4ViEJWYcX0UOT/1dHeTKMSMTCaRSNco2pVhGIZZ1LAQwzAMwzDM4kbNFi9l6+yaRtcAI5psnoSYdJBGflYb2WaIXul5jidTSbAw10ys8+WIKUeIUVXguX8BEqGciRKw8wNA9AI9rMQNoypAfAgIHgYGHwf6fkWFx9AJEozMDcudLcCmV4vTTv8WGDtbfB3OVhIY9eI9YGwzUxIdfjEOp9pCjLlHTPN0QszU/huovAeMkqL4scg5euxbB7TeBDRup/veFUDrjUDzNdS3QU1TUVwviHrXZF0xY4awOUt2rhGLs5PJDA71hYrMzSwIlCQQEnt8wNOMtKXIeTYTBUZeAAZ+C4ztyfYiCgHjeysbrDDlhumqu2uORY0kA64OpEznertVouuR9tXiE7l9YmSrEbkoO2lZqYmp497SxvxY2152xTAMwzAVwEIMwzAMwzCLm0x9xpJBTUNG1i0y10KM1QVY3VRwr3WfmPmOJ1Op2KxoJkeMPIeXwZk49b2QJMAWEJ/TNODgj4DffBR45RvAxAWaPnYW+M7vALu/JM6/4T7A20DLszgB1wyjvHNR09RjY+ARYOxlIHLB+H2kQsDkaWBkN4kzZgFt+9sBW85vSFOB3fdPvz7Piuwdid57cnz+94cFxJKAeMwaj6YQilfPYTYeFZc1bY+YSoTEXDJRYOQ5ikOUrSS2+NYXFnVcHUDbLUDDGnocPEL7qtUFuJfStCq5YtoanFjXLh5/d5/mPjELGjUJhEQ3i+ZrRwYFrgEycWD0BdovNY3EY+8qiqrSVGDslfIGEyhJIJYVgTiWbO5xLckXYuwuuh5pNp0rL74gPtbjNNMhw8mUFYE9DmtedCP3iWEYhmEqgYUYhmEYhmEWN1OOmDoTYjIRurU4qTA510zFky3yPjFqkjZDEy9759QRoxexbT5AthjTNQ341YeAn/0Z8NLX6P6XtgMPXAV8bSdw4bn8Zd30V4ajwLOCRu7OhKbRKO3BJ4HJs1RgtLrIgdB8LdBxJ9B0JRWfZBuJPGMvk4NBJ7AO2HSPuNwDP8gfeZ6LM9uTQYkBjmxGf+TCzNvLAACWNXnyehmdG4lUbfll9YhJB+m2EiEmOQ4M76KYOqubXDCuGfp1SBLg3wg0ZEexBw9Tn6GGtfRcYgRIBcvflgLsXG3qE3OWhZgFjZIEJkfEab52qDDt30oCGH2exBibF+i4HWi/DQhsBpquopg8NQ2MvkjzlsLk6ZzIyAr6gTGzw9GClCqeE+0ODznsAqbvI3QJCF4yHutCTHIMcC+n+/GBqe/e7IrhPjEMwzBMJbAQwzAMwzDM4kYf8W/Nj5aYV3QhZq7dMDp6X5FaCzGZ+Y4m0x0xFmGy1TKHQkw6G3VkdsM88Qlgzzfz5x87A2QKFP5u/VugpZvcK5IF8CwvYd0RciJMHKTPwuYFWq4j8SWwFXC1G06Dph1A++3UAyQTA8ZfMfrHSDJw/XsAS07UjpoGnn+g+LqtLiqAaZrRVyTWWx99gxYAdquMZabeBOdGolVZtqpqGDcJMQF3kRglNU37EZC/D89EfIAcB2qKYs1ab6J9olT8m4z4vYlD5ODTXTHh6rhibjL1idnXE0TcPKyeWTgoCWBSjBTTAstE95WSpP1SFwdbbhB7H8kWEqlt3qxg8+LMx61MjMRCAPBtrNKbYcpCkpCCeK3ncDYAFgfgawYcpv5Wua4Ym48GxmgKoGWy/arUqe+0u1E8FrMjhmEYhqkEFmIYhmEYhlnc1LkjRptN4+vZMNUnJlybwniuI8bcc2QuyQox8+qI0YUYu9+YtvtLwK4vlPZ6/zLg7T8Bbv0bIHySpnlXAJZpHAwAOXFGdpFwI9topHfbLcbI30JY7FSAlK3kZAgeMp5ruxpYf6s4/94Hgeg0Yp6+LjWdFWUUI7qHmZHVreLx4WyVHDFDkwmkTE3plwSKiNW6o8vqyd/n0pMUO5b7G9d7EE0coJ4bmkpRTy07qSBaLoHNOWLMQcDRlnXFDNG+PUuuW9UkOI9SiopXLtQospGpPelJIBIUpzWuNO6rGRJW0hEqvLfcUDi6VLYBzdfTc+lJYHz/9Oey8Insvt5Kf8y8kDJF0NmtVrresfuBVtPgBbPrVD9fJYYBT3afifYAmprniOkdZ0cMwzAMUz4sxDAMwzAMs7jRI0XqzBEjZbIj2+fLEWNxUmFV0yprSDwTVg+5KNQMoMxjwUKhaDLFLMRY5vAyWC8W27JCzN4Hgcf+QZxHkgG32DgckIDr3gu87wVgzZ1U3E4FyQ3jXTP9OuND1IBaTZMTof02KmaXEmVm8wJNV1OxO3qJ4swAKqLf8Oe0fp1MHHjxa8WX5Wyn28Qw4Mo6GRJDM28DAwBY1SoeH6rliLkwKo7mdtksaG0oIpLoEWC5sWSaSs3Mh56myLv+3wDDz1KBe+C3FG0Xzcb+eFdQT5jcWD5VBc49DRz7BTB+bmaxNrCZ4sw0FQgfz4m6O1PiOy5Og9OG7Uv9wjSOJ1ugaBoQGwJS4jlHbco5Xk6eogECFgfQupMcMcWwukiYlmQ6bk0W2d/SYUNgZjfMvJJSRfer3SpTLzVrA9BsikQ894z4eEqIGaLjjcVJ1xDxfixtYkcMwzAMM3vmIZCcYRiGYRhmDtFFgLpzxGQju6xlxPRUG0cLjWZPjs3cs6FcJJlEpnSY/qYrdtWSrCMmo86TI0ZJ0DZIEn3XffuAX34wf77XfQm44u3AwAHg7JNAbBzY+vvAkquMeSZ1N8zK6d0w0YvkZNE0Kiw1XS0WwUvB2Qr4N1Oj9NAxirKzB4CuVwFrbwROPWvM+/J/ADf+JeD05y/H3kjuGjVluCGSo+SaKHebLkNq5YjpGRMFneXNbkhSkd+E7ojRhRg1TU3Mk2PZuCeJnE657hSri3oEOTsApxj9hdHTwC/eD1x60ZjmbqZ9ffUdwFXvBGwFhPPGK4D0sxQBpQuK8QESA2cptN+4pgX7LganHu8+w0LMgkRNA0GT406SgOa1AE5k3TLZHluNV4hxZMWw+ynGceIguV7sgXzHS+g43bqXiM5HZs5JKaKo67DKdByy+/OFmGAPCcFNWcedo5X2l0yUzt2eFfSdR85haeMG4aXcI4ZhGIaphLKFmAsXLuC5557DhQsXEIvF0NraiiuvvBI33HADnM46K3AwDMMwDMPojphC0SPzhaZSMRGYP0cMQMX1aE9t+8ToQky1hZ5S0YWYPEfMHAkxenHa6iXh4ZVvAjCN/r/7U8COd9D9JTvoz0x8MBsxZgW8q4uvLz5IBUMA8CwDAtvE3gjl4F1JRfhYHwk7ra8iAWjnXwKnnjPeRzIEvPTvwC0fzl+GJFNxKz5AoqjVTft+cpT60zDTYnbE9IzFkFHUWTu6esbF0dzLm6cRSnOFmEwcGMvGOslWoOkaOo4oMSpyK3HA3lS4GK0qwAtfAZ76dH4PpNgYcPpR+tv/PYriazDtH7KNRMWRXbR+JUHH9eh56iUzC25c04IHnjTcDkf7w5iIptDomSH+j6kv1CQQ7BeneVsARwAAIIWOkEDt6pw+otGMZxn9DqIXgfF9QNvNhviXGCXHnyQBvvXVeR9MxSQzYuSi3SrTecvZDjQuBZxeIJEjaJ99yhBiZCsdv5JjdM7yLCcHVSqEbo8Y4ToeTSGazMDj4LHNDMMwTOmUfAX/0EMP4frrr8eqVavw4Q9/GD//+c/x3HPP4Rvf+AZe/epXo729He973/vQ09NTy+1lGIZhGIYpHU2diqaCpY6iyTIxABo0WKovEA0eAZ78FPDUZ4DoDJFjuX1ilNT081ZCbp+Y+SL7/Wc0UYywyHMUTaa/d5ufCoDnnhafv/59wM73T78MTTN6w3imccOoGSB4mO57VwCN2ysXYXT8m6kAngoZjaiX3Qasuk6c79nPAZdeLryM3LgX/X5yeHbbdZmw2iTEpBQVvVUYiW12xKxoLuIMyETJZSDJtB/oIojFCbTeSG4XSSJngauDxLtCIszEBeCbd1Ekn1mEMTN0GPjWPcD4+fzn7H7aJwESYtKTVBxXMzO/6Wm4clkATptxTNA04IVzNYhsZGqLkgDCpuhDXztg9cKpjgKpMYpW1Pehcghspf1PTZEYOfoixfKNZZ1dnuWlOWyYmpIyCzG6aO3qpO+vzdQnxnxOdnXRbbyPzrVuitRcah+A2Uh7erg6DkWGYRjm8qGk/0B37NiBL3zhC3j729+OCxcuYHBwEHv37sWuXbtw7NgxhMNh/OIXv4Cqqrj66qvx8MMP13q7GYZhGIZhZkZ3w0jyzI3N55JscT4jVUmE0TTgzBPAd34X+PqNVBR/5rPA/7uZYjeKYXFQA3WAClTVph6EmCKOGNtcRZOl9f4wPvouwr3iyOJSJQABAABJREFU8zveOfMyEoP0GcpWo2l5IcInaJ+3egDf7BwCU1gcgG9DzvKTtB03flCcT0kBP/xDINSXt4gp8SUVNPrkcJ+Ykmjy2NHotgnTqhFPZu4Rs7yYEDPlhgkA8X5j/2q5AYj1Um+Y8f2G4F2Ivr3AN+6gWzOyLX8aAEycJzFm8Ej+c94VRgRUfIC2KXap+PpLwGG14NqVYo8mjidbgKhJYHJEnObvAiChQc3uI751lUXZSXI25tFGYmRihIRKTaPlNayb9eYzsydPiLHmCDE2H9DSKb7g/LPk1tNxdZG4nArR9+tdCQBwpgexwuQcPD4wj9c2DMMwzIKkJCHmn/7pn7Bnzx68//3vx7Jly/KedzgcuPXWW/H1r38dx48fx4oVK6q9nQzDMAzDMOVTj7FkAJAO0o1UhdGzF18Evv4q4HtvAM49JT4X7gX+817qyVAMR7b4mKyhEJOJioWOuWSqR4w42TJX0WRTQow///vxdgCtM0TZxPqpTwswvRsmNQFEsg6CwNbq9l/xLM+OBE9TvxgAWHUPsO114nzRYeCHbwPSJseGxZnjktCooJmJk5uBmRFzPNm5kWiROUtD07SCPWIKkhtLlsi6mCwuYPBp4IV/A37zz8CzXwQu/JycKWZOPkLHoKhZ1JDIDfbRHuB/HQTe8A2gcaU4S2QI+M/XAL178pcb2EYxd3Y/RedFzlNBfBbcuFoUYp4/y46YBYeSBCZN31vjcmDyBGSkKSJyOjF7JqxuEiF966nHTOtOoONOoP0OowcWM6+kFJMQI2XdchYn4F4GtHWLL0gEgf4DxmOLneI0ATq22Hx0naRp2NgqXjecYCGGYRiGKZOShJj77ruv5AW2tLTgmmuuqXiDGIZhGIZhqsaUEFNHsWTAVHEzjVkIMUoaePKTVKgcOlx8vskB4MH7gOEThZ/X48lq0SfG4jCKU5l5Krqr2WgyVSyg2OYimkxNG72A7H7g3DPi86tuMaLDlATNrxeTU0FgZDcwvtdwITQU6Q2jqcDEIbrvXprfSHq2SBKJOwC5IJJjJKbc/SlgyRZx3oEDwH9/IL8o7tAjycaMfS7B8WSlsLpVPE7M1hEzFk0hmhKF0RmFGGsDOQCCx4CDPwJ++AHgxe8Bl/YDB34B/OADwKN/C1z6DTB+ADj/CPDkPwA/fGt+FFnzGuBdjwB3/C2gJYHGFcC2PwDe9Vugfas4bzIM/Nc7gHhQnC5bgcB22peSI9QbaZYuqxvXtAiPz49G0RfkhtwLCiUBRCbEaYGlkLIioebfQseu2WD3k6vG000Feqtr9hGQTNXIc8Qgx/3n6Qa87UCDKLrmDZLIjScDpsS7TQHxeHB8gAcTMAzDMOVR9lXIvn37cPiw8c/+L37xC/zu7/4u/vZv/xapVA2yxRmGYRiGYSpFyf7TXE+OGE2bauCekbwzzFyEsbMU2/Ps56kIn4epKBQZKi7G2LMFifTk9PFClTKf8WSaOtU7wizEWOfCEaO/Z6sLgEwRKLmsvIVug4eBgceA/keAvv+huKfh54DkOPUz8K0H2m4pHuMUOZeNLrNX1vugFOyN5IzRt1dTqYH1fZ+kHgy5HH4Y2P0lcdpUn5hhY7Qxx5OVRLUdMWY3jN0io9NfQKxWFWMfVjNA7yvAo/8O7PpPIDouzptJAgd/CXz7ncBX7gC+/Wbg2S/lH59W3Qr86eOA3wcMP0Ni4/AuID4ENLQDf/w/wLKd4mvCfcAjH83fPmcrxQY52+g3MDmN868ENnX6EDDFwHE82QIjOgCkTOKZrw2ARg5UR0vBlzGLhzwhRssRYvR4stal4ovy+sR0kmCXjtAx0NkOWF3Y0CT2ojo+GIY2SycewzAMc3lRthDznve8B6dOnQIAnDt3Dm95y1vgdrvx8MMP4yMf+UjVN5BhGIZhGKZi6jGaLDMJaAogWZFBGduVCNFI9B+8DfjqDYX7LTSvAV57P/ChE0DXDvG52Cjw8/fmOxUsdkMsqUU8mTXbg2Y+hJhsLBkkCRnT27bORY+Y3FiywUMUgZLLqluysUoXxOl643H3UqDjdhp9XSxqTEkA4ZN0P7C5tr2Q/BvJ4ZSepIgySQI6bwFe+ynAZtqXH/8YcOpR47G9kYQkNU2CEQCkxukxMy2rTULMbB0x5v4wS5tcsBT6PWQm6XhhcQDjJ4HHvgqEZxAmMklj/zWz7S3A738NCO0DJs/SsiWZXDdjLwNDzwBSGvijnwLLbxJfe/AHwLH/zl+mfxPFDakpcoXN4jgjyxJ2ruY+MQuaUIF4PDed31KSr+BL/v3Zs7jzC8/gAz/Yj3CCj0cLnbxoMi1HeLa6Ac/S/HiySy8BqZz5ZCuJLwCdoyUJ8KzERpOON5nIsGuOYRiGKYuyhZhTp07hiiuuAAA8/PDDuPnmm/HQQw/hwQcfxE9+8pNqbx/DMAzDMEzlTDli6iiaLBWkW3ugtDiT0TPAf70T+Nxq4Gd/Bpz8Vb5zRbYCd/wD8BcvA1f/CdDQAbzj58DSa8X5+vfTn5laxpPNpyNGF2JkOzKm4ozVYroMTkeoF0s1t1Nfls2XP+K2eQ3gaQSC2UixhrXAkvuAzntIfOm8C2i6cmYRMXKeXAeOJhJuaolso74I+nrjQ1RIX/MG4O6PQnRiacBP3g2M0AAuSJLhilGigM1Lhfha7HOLDHM02Vg0hWCs8iSCnnFRiFnRXCQiUY/Vs3qAo/9duM9TU3dpx7FXfQi47S+Aib20XIsTaL6W+ms0rKFjWDpMggzSwO99HXCYCue//F/ApMlFJduAlmtp/08MAmP7Zt6WaTDHkz1xfBiRZBFhiak/Qr3iY7sbkOjYn5Ia8mbf2zOBT//6BM4MR/DLg/34wEP72eGwwEmmxeOUA1FxAIpvA9CyVDxuKSmg5wVxQe4ldKvHk3mWobNBht8h7h8cT8YwDMOUQ9lCjKZpUFW6mHn88cdx7733AgC6u7sxOsr/SDEMwzAMU0fUoyMmK8RoNv/088WDwG//Dvjq9cCxnxd3DjStBt79GBU6c10TTj+NLPcvE+ff/938ZTiyo8BTNXDEzKcQowtWsh2KKhZP8hwAwYMkLgw/B0yemXXjbwBTEXSwFegPs/JmYHwfuQccTRQ/JsnkaLF6SttnVQWI9tB9b5H+MdXG2WY0u544QL8x2QJc9QHguj8S502GgR+8BYjrDd+b6DY1YfSM4XiyGelucuc5uM7OIp7MHE1WtD+MLmRrKnBpj/icvxP4vfuBP38ZeMtXgNU7kReJ6GkFVt0GvOnbwNbbcvbVFUD7bYCrndw2/o3U7NzZlu13dADwLwHu/by4vPg48MsC/YecbUDTVXR/9AUgLQpN5XDb+jbkftSRZAY/299X8fKYOSZs+q7cgWw8noQ08oWY502Op2dOjeDnB/j7XsjkOWIkBcjkHPPcywB3C9DYIb7Q3CfG0UYCcSZO5yzZBsnTneeKOT4wD9c2DMMwzIKlbCHm6quvxic/+Ul897vfxTPPPIP77rsPAHD+/Hm0t7fP8GqGYRiGYZg5RNWFmDlwxIRPU2P19AyxQXrza1ug+Dx7/gP48nbgha8UF2BkK3DNnwLvfQ5YsqPwPI4G4Mq3i9MO/xhImQqVuhCTjhjiVbWwNdDIUzVd/WXPxJQjxoG0IhZvbbk9YtJh6scCUNEudBwYfd5wBFSCplK0EwBIDuDii+LzHWtIlJNtQOOOypo9xy7R52p1GzEqc4F/IzWsVlPA+H4qjMtW4O5/BdbcLM47fhb48btJNLI30rRUUOwZwyPQp8VmkfPEktnEk10YK9ERo2Tni08AQ2fE5+76BLD9TwCbG1jzRuCuDwNv/gJwz0eBN38T+F97KSLxTf8OBJzGvt5yHRDYSvtLLhY70Lid5kmFKLps25uBja8T5zv1W+DA9/O3teV6Oo4pMWD4qfznS6Qr4MLtG8Tf0ndfuMAuiYWApgGREXGaO0B9tuwBaFJ+vGOhWKmP//IYRiM16JfG1BxV1fLO9XYLgHTQmGB1AZ6V+fFkZteqbAGcWbEmlhXnvCuxQUwvxIlBFmIYhmGY0ilbiLn//vuxb98+vP/978ff/d3fYc2aNQCAH//4x9i5c+cMr2YYhmEY5rJG04DwKWqsPBfrmitHTPAIED4BxPqpAXX4VH6TaoCK0Xpx3h7Ifz45Duz6JPA/f02OGDMWO7Du1cDvfg348Bngvn8F7EWKqDpXvA3CSPVkGDjxP+I8so0K60D1+8RIMmDN9riYa1eMmi2mWezIqOL3YZFzLoP1Hi2uTorekq30XQw/M7OwVox0tr+GbAMGDtOo2ikkIJB1hzReQYWhctE043fkXVWZkFMpkkwOBMlC0WJ6jxqLHfiD7wGtJnfO2SeAF7+WFeXkbJ8YB33OSnJ+3FILjFWmPjHnquiIWVbMEaPvs337xFgyyQKsebXx2OIEWncCjSuA7i1AgwOIHgf6fwOMvkTftz0AtN1iCHCFsDiBwBa6P3kKyESA134J8Jhe8/jHgKQpDki2Ae230/2xvUCi8qSGd9ywXHh8aiiCl86PV7w8Zo5Qk0AsKE7L9ofRdDeeiUJCTDCWxsd/eazaW8fMAWY3DJAVYvRIWJ3AFqDN5BYeOgJEhsVpU/Fk/XTOtTVgU4d4zcXRZAzDMEw5lCzEnDpF+c7btm3D4cOHEQqF8I//+I9Tz3/+85/Ht7/97epvIcMwDMMwi4fwCSraBo/mNyivNmraGGmvNwevBcHDFGkF0Ih/TaX3OPyM4bLQSYeM5te5Lp1MHBh9Eej5FfDcV/PXIVuBq98O/NUJ4G0/InHF1Vja9gW6gdW3idP2fSd/vsXYJ0YxHDEZUzSZTc8fUjM5GfArAE83FYztAXpu8lRl605PE0vWtg5wegHPMsDVkf/aUkgMU9yKbAXc3TPPX22sHnI2AMDkaWBsD/3mHH7gbT8FXAFx/ucfAJS0IUCmQzn7nGkUO5PHapMQU6kjJhRLIxgTXXbTOmI0Bbh0QJy+5ArAaerfYnECrTcCvnXkzsoVvz3L6blSBEf3Unq9HlHmbgJ+5wFxnugI7U9mAlupcKqlgcHHC4vhJXDTmhasbBE/k+++0FPRspg5REkCsZA4zZX93Tha8ucH0DdRuNH6Lw/24/FjHJu40ChZiGlYA7QsB6w2cfpZczxZC10/Ksmpa6ONy8RebBfGooiluI8UwzAMUxolCzFXXnklNm7ciL/5m7/BCy+8kPe80+mEzWYr8EqGYRiGYRhQtMNkTrxN6Gj+P8fVZCqWykqj8KuNpmVFmAv0uPEKoO0mcgpYHOSkGH0eiA8Yr9HjMXJjyTIxmi8xArz4XSBpGum+6kbgjf8MXPFqIHaieFTZdJjjyS48B4yfF6fZs3kb1XbEAPMnxKhGj5iMKa5kqkdMvI8EF5sXcGaLdVY3xSQBNBK2kogy/b3afPmRJ50b6NYtFnTKQnfDeJbnxzzNFZ5uILCZfl/xAWD4WfpNN64A/sA0QCsyCBx+2Nj308Hain+LjNWtojBwrkIhpmdcPL5YZAlLAkUEEiVO+3G/yR2w+s7C81sc1Ouo5Vqg8y6g826g406gcVt5x+DGbdmIsiAQOQusfzWw9h5xnue/DIQHxGmSRL1nJBv9PsKViaiyLOHt14uumN8eHcRQuHC0Ys9YFL8+PMBxVvONEgfipnOMy0/7RQFHjKZpBR0xOv/350cQTlRwvmXmjVSmiBCjD4LRka2Afz3QYjoHn/yV+FiSAXcX3Y/1AgDWLlsh9JHSNODkILtiGIZhmNIo+Yp4bGwMn/vc5zA2Nobf+73fQ3t7O9797nfjv//7v5FIzHHeN8MwDMMwC4tUkEY3AzQS0dVBo5XH9xiuhWqT0x+kJoRPiiKMJ+tKcHdlG1F30n/o43spsgwwhKdsrwyLFoc0lu1F0nsUOPeSuI4tbwTe8Wtg1e9QYTI5Ts2oy/3M1t8HOAPitAMPiY8dzVSwykRNMVpVYN6EGH0fsEMxO2Is2ctg/Tv0iIVX2HyAszUbAXa2/HXrjhhNBvr3ic91bsj2LSjR1ZS37DCJF5JEWffziXdV1u3gpv14ZDf191h5C7DcFFv8/APkEAKoV9KUEDNesXvhcsEcTdYzFkO6wOjvmTD3h+kKOGG3FviXUE2TQDnRA4RMzoC1d5e2Moujstg9ixPwb6b7k6dpW+76hCjmpOPAU5/Kf613FdCwmory43srFvvfeNVSuGxGT5GMquGhly4K86QyKj73yAnc+i9P433f34e7v/gsjvVzzN68kQoDCdNABm8LHWcL9IcZi6aQLFC41xkMJ9gJtcAoKMTYLGLPNh3/ZqDDdP48/Vh+Dz19wER8AFAVOO02rGoSByBzPBnDMAxTKiULMU6nE6973evwjW98AwMDA/jZz36G1tZWfPSjH0VzczNe//rX41vf+haGh4dnXhjDMAzDMJcPShIYe4X+EXa2A74N2b4YHir4T+yvTbPunCJ81VGSRnG+cbshwujINnLGuJfSe5vYR46gKSEmAKTDaFJOUB8bzQLsflBchqsRePVn6b6zjXowyHZqZD36fHmN721Oanydy4Hvi30fZGtOkbzKrhhdiMlE5rbgru8DFkde0doiSyQApMPZUa8F4r0a1tJt9CJ956WiaYbo1H9MfM8WO9CxPit8VejU0t0wrs7KCt3Vxh4A2m7Oio8qEDpGguH1fy7ON3ICuJgVpdJhwOKmYr2mkDDDFMXsiMmoGi6Nl+/UumjqD1M8liwrxg6Y3DAOL9B1ZdnrLRtPN/UUUjP0+2vbAOx4hzjPge8DQ0fFabKNzi/2ZiqcThyo6Jjjd9nwu1d2CdMeevniVKH3zPAk3vC13fjq02enTl/j0RT+5MGXp3VZMDUkOQYkTL8Jb7vh9jRhjiWzyBJuWiNGmD17imMTFxKFhBiHPgglL55sPbB0A4QeeukY9TTLxd5I16uaAiQGAQAbuwLCLMcHWIBlGIZhSqOi//4kScLOnTvx2c9+FseOHcOBAwdw880348EHH0R3dzf+7d/+rdrbyTAMwzDMQmViP4kGNi/QdCWN4pdtQPPVVIhODIuRZdUiJ5aq6kQvUHHPHqA+H4WQJMMpo2kkRgUPZXvkHII0ugsy0iRSHHwMmDTF7NzzGcDbajy2+ch5YHFSI/iR3UC8jAx7czxZuA84VyAPHah+VJTFSd+5ppEYM1coxj5gdsRYLRIQzY52di+h7TPjaDb6/kTO5z9fdL0xKiBLMtB/SHyuYyNgtZPbphKUBIl6AI3+rxf033TjdhL1kmOAzwI0m7bxxf+XFV80U58YjiebjoDbjmaPeCw7OxItMndxzI6Y5c3uwjNmYiTGDJ4Tpy+7FpDz3QU1Qd+/I+foN3jr3wK2HOFIU4FH/77A61bQcTkTpfNLhRFlf3T9CuHxyGQSWz72W9z5hWdw35d34UhffvF1KJzEO7/1MoKxGjk9meKELgIwDerwttFxvABmwazD58Qf71whTDvYG6zIecbMDwV7xOj9ysxCjMUGNG8BWkTBFcf+O3/B7iV0G7sEANjQJUbdnRhkIYZhGIYpjaoEpq9duxYf+tCH8Oyzz6K/vx93312iXZ1hGIZhmMWNmqHeJwDQdI1Y7Lb5cpp9nwQSVS7EKoYboqqoilGUb1gz/bySBAS2Z4uCESpOqwkqcmoq0lIDkHIBe/5TfN2q24Dtb8lfns0rxkCNvUx9OeKDM2935zagY5s4bf/3xMe1LIrPRzxZjivKXEyzQqH+LwDgWVF8Gfp3HL1A+3Mp6J+fzZ8fS9aajUIp0jx6RibPUAHa0VR5tFkt8SwD2m6h7dNUYPMd4vM9u4CJrIAoxJOxEDMTq03xZJX0iekp2RETA1IRYPiCOH3VbWWvs2LcS+n4rSTI3dLQDtz4l+I8Z5/Ib7Bt9ZAA7llBx8bIGXISlsmmLh+uWSH+xlIZFWeGI9NGWp0ZjuDPvrMXibRSdB6mBoTE6DhyOgYK9ocB8h0xSxpduGq5+H0n0irHzS0gzI4Ym0WCbA/Qg0LXHoFNQJfpOu7UI0DG5IDV48mSo4CSwKZOn/D0iYFJaLVwdjMMwzCLjpKFmJ/+9Kd4xzvegUceeQQ7duzAT37yk4LzNTc3Y+3atVXbQIZhGIZhFjB6JrfFSSKCGc8ywzEysa+8uK2ZqFU0Wewi9SywegBnx8zzSxIQ2Aa4lwGuLqDxSqDlOmitt2Bc3gB595cgjOK1uoDXfpFeVwirG2h9FQkEkoUKjGOvAENPA6ET2X4bRQoC5mifU48C6ZzP3N6Y7RMTr6xB/XTMtRCjqfQ9AYDsyHfEpEezriY/OZuK4WynfVdNGw6amYhn3U3ONqD/gPhcywraJ60NpS0rFyVhbEPDuvJfP1dY3UDLTsC/EVi9k4qhuRz4Od2mg4YQk5oQo/KYPFa3iaLJ2QqEGLMjZllTMUdMHBg9C6RMx+R1ryl7nRUjyUYPJD0K8ob3U9xULk9+Iv+Y511NYiA0EuUrjCh7140z92Ba0+bFmjbx/PbyhXF86L8OcnF2LpnsFx87PbQPFHFwmR0xSwMuNHrseTGAe3o4NnGhYBZI7RZZvPYodJzo3mJaSBg494w4zerJumM1IN6PjSYhZjKZQe8ERxIyDMMwM1OyEPPVr34Vv/zlL2GxWPDZz34WH//4x2u5XQzDMAzDLAbSWSHGNk3R2b+V/lFWktRcuVo9RGoRTaZpRn8O76riYokZSSIxyr2UitPONsDWAF/iEuTTj4jz3vJhoGmG4p/FTsvpuJMEGdlKn/XkaYosG/gtEDyaX3TY9LsQ89CjwPmcgoNsNVwW1XYozLUQo4swACDbkDYLMWrWGTCTmCZJVKwBjIik6VBSxmcXj1NRJ5fWVRRLVuq+k8vk2ax41Fh5tNlcIUm0b/rXApvvEZ87/SQQHiLxxeqmP02rfm+iRcaqFrHYf3KoPCEmlspgZFIc6b2iZZoeMf2m/jCBLqB5jgfceZYbgnNilHrU3Pa34jx9+4Azpr4OjiYSWN3dtJ+lw3R8LJNXb+nAX96+Bj6nteDzf7xzBf7nAzfh2++6Fu0+0X35q8MD+M2REtyKTHWImKI63Q3TOg/NQsySRuq3ZXbF7O0Zr872LWKeOjmMe774LF77wHPYd3H+hCuzI8ZulUlEkWTq8aKYBpjYfEDzBqDJdB1wvFA8WdYVE+tFu8+BgFuMMz3GfWIYhmGYEihZiJFlGZs3b8Zdd92Fu+++G42NdRiFwDAMwzBMfaELMdON/pct1FtCtpKbI3yiOuuuhSMmPkBOEdleuLn7dKSDdGsLTE1aO/hLcR5XI3Dte0pfZq4g03Sl0etETZNoEDwoijHeVqD7OnEZJ34lPp6Kiqpyk+I5F2JyhDhJynfEaNki3HQioY57KQlpSgKI9U4/b2KQPnO7Hxg07cvuRvqrJJZMSRpuGF8du2HM+DYBW18H2JzGNE0FTj5NrgslwfFkJbK+Q9xXD/cGMR4tvRdJz1i+y62oI0aJAQOm3irLril5XVXDYifXJGC4Yq74Q6BxhTjfU/9UYLT7KjoeWt0AVBJi9HNSiUiShL+6ez0O/uPdeOXv7sSP33sD/uUPtuOjr9mAn71vJz72O5vhtFmwJODCg39yLRocomBz/+OnoKrsipkTIqbjh8sP2Av3hwEKRJMFSIi5erkYZba3Z4KdTdPQH4zjz7+3FyeHJnGkL4w//fYehBPpmV9YA8w9YuxWmQYF6Of5Qtcf/s3AEtM59cSvAMUURerqIkEnFYKUiWBjhymerJ+dUwzDMMzMlCzEtLS04Dvf+c7UY0Xh6ACGYRiGYWYgU4IjBqARi41X0P3Js8DEIeqFEb1EzZZTISrYluOWUWvQIyZyhm69K8prWJ2JUiFdkqhvCACMncGS4MvifNf9OY34LhfZRmJB0w6g8x66lST6/EJHxXk33Cc+PvkbQM35XJ1tdJsYrp47CTDEOCVJf7VmqkeQHZqm5QsxuiPGWsLnLck5jcPPFo9+A3JiyTqB/v3icy0r6XupRIiJnKURvfaA8R0tBGQL0HkLsN7UW+TC3qwLJshCTIlcu7IJLptx3FE14InjQ9O8QsTcH6bT74TTVuQ4Fh0DxkxRT6tuLnldVUX/7SWGSUix2ICbPyzO038AOP2YOM3VSVGPVi8Amfa34OGKNkGSJLQ2OHD1iia88aqleO8tq3HlMnFg4sZOHz71hq3CtFNDEfzq8EBF62TKQM0AsaA4zTN9H62ijhhTX6ChcJJjp6bhXx89hUTauFYYj6bw9afPzsu2xJKieDJ1vJwaCFJAiHUvBVZdL06LjwM9u8VpFrtx7o315sWTHe+r8uAVhmEYZlFSshDzjW98A6tW0UVwKpXCF7/4xZptFMMwDMMwi4RSosl0XJ1AQzYCKtoDhI5Trv/oS9SQfuAxoO9XwODjQKKEf3iVKkeTJUZJEJIsRt+CUtGdDI7WKQHH8vyXIeX2hrE3ANf92ey3U5LIGaMLW5HzQPik8bxZiIkOA317jMe2AIlXagZIVjEqSraQ4AbMjStmyhHjQKbAiHQrFPqsrEWimcx4lpPglY6Q66XgOtOGk8jdBfTvE59vXUnrsxZxIRRDSQGRC3S/mr1hNI1Ewlp/HzYfsP0PxWmhfmCil2KjHNlR66mQGCnHCDhtFty8ThTxHjtWjhBTYn8YVQGGjohCrGQBVtxa8rqqitUDuLLRQXo05La3AI2m47DZFZPbY0a20ePkGBAzCUxV5LVbO7HB5Fy6//FTeUIwU2VSQSAuCo3wthcdMBFJZhCKi8ca3RGzqsWDRlPs1F7uE1OQY/1h/HR/vkv0m7vOYyA09+LVREz8TgPu7PXfdI5cZyvQug0ImAY4zBBPtqFDHMRxfKD8nl0MwzDM5UfJQozbbVyo2+12XHPNPFjTGYZhGIZZOKhpcrEApTcm920kN0fDGoqjcbZRxJPFafTUyMSB8T1UEJ92/VWMJlMVw1ni6aaRkaWiqeRMAaiYDwDBi5CO/Jc437V/StFk1cK9FAhkR2eHTxkFzObVQMt6cd7ceDJJogb1AJAovchbEnoxJFNePFBF6EKMxYGMkl8EtVlgZMcDgJIGxs8Xd7vIVsCzgu5Pnik8TzwbS2bzAZIDGDgkPt+yapZuGD/gap95/mJoGm3j+D5g6Bmg/9fA4JN0f2R3bQWZ1fcBDaZC1/mXqYBqcQK2bFGrmuLfIuTuTWIvg2dPjyCeKi2p4IJJiFnRXKw/TAwImoqrjUuAhqUlb2fV0V0xsT4SiS1W4JaPiPMMHAJOPypO8yyj366aNmKqQkdpGTVAliV88E5RLD07EsUvD9ZO/GFA0Z8J0zWBv/j+ao4lA4CurBAjSVJen5g9ZfSJ0TTtsomj++wjJwqeMpMZFV949FT+EzUmGBejGqf6uFinEWIkma6XureJ04//j+gWBujaSLYBSgKbWsU+bz0hDSMT3E+IYRiGmZ6ShRidRCKBz3/+87j33ntx9dVXY8eOHcIfwzAMwzAMgJz+MC4qhJWC7ubwbyRHR8t1QNvNQOddQNd9QOfd1IRZzQBjLxcfPa9mjNHcchWiycLH6B942V6+IyHeT6KQ1WUIHLu/BCm3EGh1Adf/xey304x3BeDbQPdDx424LrMrxtwnptZCzFw4YvT3KjuQMRdTAFgkGLFkY2eBL10BfPkK4P/dTIJMIbwrsxnxQXJImdFjyVydwMhxEg1zaV1Fo2/LIXLeEH4qdcOoaYr8G3oSGHuFitnpMP1GJDnrFBgn51nwcG1cKbIMbPwdcdr5l6mAqmnkFgM4nmwGbt/QBotsFAATaRW7zpT2mV0YFR0Dy1uK9YeJAyFTnJa/kwSz+cLRTMKpphi/s61vAppWifM9+QlRTJVtgHtZ9oFCbjQlUVxMrQL3bG7H5i4xtuhLT5xGRsk/DjFVIhnMd8T4lxedvS8oipItXrsQ03dVXp+YYEmb8cuD/djxT49hxycfw+d/ewKRZG0Ev3rgudMjePZUcXfyj/f14sTg3DawD5kdMa6sEKO7sjNRGlhjxtUFrL1FnBYZBC69KE6T5Knrow2+ELymnlAvnpifSDaGYRhm4VC2EPOud70Ln/vc57B8+XK89rWvxetf/3rhj2EYhmEYBoDherD6pp+vVCSJIrOariHhIhMFxvcWdjDobhhJLq+XSyHiA0YsVNOO8nvO6K91L6f3MHIK2PddcZ6r3gl4yyzQl4pvLTkpNBWIZZ05ZiFm7DRtl46jlT67TKzs5tbTogsxqVD1llmM3GiyAo4Yqwxyamka8Iu/AMJZB8DgIeA/XyN+HjoWB42wB4x+QVPry4klc3UCfaZYsoZWwNkwbfNoAU0DgkeB4BF67FluxDOViqqQG2rgMSB0jL5P2UYRgM3XAh13AF33Au23U5SaptH+OvQU/b6qzZY/EB8H+4Dxi3Ss4D4xJdHoseNq02j9x44VicrLYSAUzxvVX9wREwfCw6YVFy9qV4SqALFe2t9K7Rnl7qbb2EW6tViBm02umMEjwMlfi9O82d5MyXHDlRg5W5t9HOSo+N8mV8z50Sh+tr+vJutjAEQHyNWYS2BV4XmR74jRY8l0rjb1iTk5GMbkDA3oXzw3hg/+6AAmYmkEY2n821Nncevnn8JDL11cdCKcqmr4zK9PCNNaGxzw2I3rLU0DPvubE+aX1pSJmNkRk3UvWxzGtVshR66zFWhZB/hM12HmazWAzu8ArKlBXGPaT144Ozp9DzmGYRjmsqdsIeZXv/oVfv7zn+NrX/saPvaxj+Ef//EfhT+GYRiGYRgAhuuhlP4w5WCxUxFZslCvmNCx/Hl0IaZc0cRMJgZMHKT7DWvKdzOkw9QDQ5KpgB8PAj98q1B41GQbsPMvZ7edM6H3SYheoCJB1w7Aayrqn8xxxcgWozBeTVeMzU+3mUmx/0QtUHKiyQr1iJFBcVgnfw1cfEF8cnKAxBhztBgAeFdTUTcxIgpKiSF6T7YG+jP3h2lZlY3ZKyHWTlUofk+Pk/NvBBq3Tf8aM/FBYPhp6g+kKSSCNW4HOu4C/Jso4szqzvbJcQFNVwGtO+kzUZLGfl9Nll4LeM3xZK+Qw0jvE5OeNCINmYLctUmMp3vi+PCMPUj+49nzSOcIknarjOtWNhWeORMDIiZBrGlNRduah5IEQieo19f4fnJgDT4GjO0BEsPTFzE93YagoosoW/8AaFotzvfEx8RIIavbcPkpCYq81FRD5KwBd2xsw7alfmHal59kV0zNCF3MnxaYzhEjHmOWNIpCzNYlftgshvNM1YD9F4NFlzcYSuD9D+3L+x2ORlL4258dxn1f3oUzw3MQyTlH/OJgH44NiG6XD921Du+5RfwtPn1yBI8cMbnrakgwr0dMTq+f6Ry5kkwDHdbeJE4/+jO6bsvF0UrXn5k4blguitkv9io8mIBhGIaZlrKFmCVLlqChocoFFYZhGIZhFh+6k6LaQgxA/1A3XUn3I+eogJeLXoSfTX8YNU29NNQ0YG8EfOtnfo0Z3Q3j6gAkK/DT/w8YE50U6o53Av4llW9nKbi6yAmRidFnJcvA+teI85wwjSKvRTyZ1UXboWnVddoUQjX2gULRZFYZgOQEHisykCg2Cnz7tcClV0wvdNPnCQDh4yTIpCNGA/DsaNk8R0zrqundMJpG/VEmDlGROj5IxaGmq0gELBUlCYy+RBFkmRjFSTVdBbTfku2XMY1DzNEMNF9HRabkGBAtUNycDbIMbDQ56C+8DKRDtF/Ys4VrLmRNi7lPzFg0hf0XJ5BWVHz9mbN4x7dexjeeOzfVp2I8msIPXha/yzdf3Y1mbxGhOh0BIqbm5K0bZr/h4VO0b0+eNuIa7YFs76IB2m+HnybxuhAWpxFhp/fdsliBWz8qzjdyCjj6E3Ga7oSJ9VIvMkmmY2F8ZjdRJUiShP99l+iKuTQex8HeYE3Wd9kTNrmNbA7AVfx42xec3hHjtFmwZYkopO3tKbxfJjMK3vu9vRiNpAo+DwAnhybx9m+8jJHJEt1fdYyqavjiY6eFaWvbvHjjVUvxp69aidYG8bjy3u/tw3u/uxc9Y7VxoOWSJ8S4ShRiADqvr7/T6BsHULzo4YfF+WTLVK+2G7rE9Z0LShga6qlo2xmGYZjLg7KFmH/913/F3/zN36Cnh08wDMMwDMNMw1SPmBoN4HB1UuQMQP0vctEdMeUIMWqG3AOjL1KUU/8jVBCUbRRJJk1z2dR/APjaTcBnltHtw38CPPlJ4PB/AWM9gL2dHpsaSQddK6DePgeOYtliFCKj2f4nG14rztP7CjCZI7roQkxqwui3Ug10V0y6xvFkOa6ootFkh39OsWzFSISA7/8+EDaN6NWFkcQI7S9DTxmClasTSCeAYZNTq3UV9TcquJ5hKlCPPA9Ee2jbLU6g5QaKDCuV9CQw8hwtT5KBhrVA+23lLcPqBvx6X6Gj1XenbDL1iRnrAUay8TWOrFvGLKwyAsua3VjfLh5Xf7y3F3/8ny/js785gWdPjeCTvzqOT/zPMWiahgd3n0c8bfRFsMgS/uzm4rFNCJ4DFFNvi9ats9voyPmsO0slYbvpKqD9DqDtVSQSelfRsTYdAYZ3USxfoV4OejRg7JLhntny+0DrRnG+J/9JfA+OVtq31TQde7zZkfuhIuupAreua8WaNq8w7cClOYhlvByZNAlqLi/1FCpC34TYI8YsxADIiwAsJsR8/JfHcOBSUJhmFiMAYDBMrpn0AndFPXdmFBfHxc/vo6/ZAKtFhttuxV+ZBEgAeOToIO78wjP4zK+PI5mpze8NAIJx8Vql0ZNzDahfixYTYhwtgLcFWGZyn+79dr5TLzsYY5NvFD6n2CfmhbNDdD3JMAzDMAUoW4i5+uqrkUgksGrVKjQ0NKCpqUn4YxiGYRiGgZI0CuFW7/TzzgY9Jio5KjospoSYEqPJNI3cL+FTVFzXi89WDxUMrUWaWgMkXnz/jcDQYSAZotujPwWe/Tzw5APAz/4O+JfNwK4viKt0t+DlVX8J2PILQDVBF2J0B8fKVwH23GKuBpz6jfHQ6qIRpJoGJKtYGJ9pVGq1mHJFFYkmgwY881lxYsc2YMWrxGmJEPD8A+I0mw8IbKGoOlsDIGcLMY4mem7oiKkQIwHNK6gAnbedCdr3lAQVoj3dQMv1QMedxYWbQiSGgZFdNILX6gHabiZBRbbO/FoznpXkVFAzFB1VTZbtBNymkepnnqQCvVMXYkY4Z38GzPFkP3zlEnafGROmPfj8Bdz/+Gk8+PwFYfrrt3ehu2maY9qoqT+SxQ4EVlS+sYlhEjwAwLcBaLuJxEEpG/1k8wGBzdSzyL2UpkXOAcPP5LtjnO0ksCsJoyeTbAFu/ztxvoke4MD3jMeSBLizIk60h0RKizMbw1abBtuSJOGqZeJv/qCpYM9UATUDRE0uOpePjqdFyHPENOb/Hq5aLh5/91+cyIuWe3jPJTz0kug2W9bkxmP/+2Z8/0+vw7p28frnpfPjeb1VFho/NLnrNnb6cPsGI3LyD65aijs2tJlfhrSi4f89ew4feGj/jFGKlWJ2xPjLccTo8WQb7xanDx3Ojxp1tAGSBRY1jmtXiH0QX+jNOvwYhmEYpgBlCzFvfetb0dfXh09/+tN44IEH8MUvflH4YxiGYRiGMdwwnumjkGaL1QU4szE9ej8NoHxHTPg4ORokGQhspUJh12uAjtun7wujKhQ3Fh0pb7tlK5Tf/xbi9pbyXjcbrG6j2Xv0AmB1AGvuEOc59gvxse6KqWZ8j30OHDFqhvqiACTEFBiBbDv6SP73ds+ngD98GFh9uzh974NA3FQQ9q4kwaT9VtpXul4DtN5Iz5ljyQJdgLuJCr9mJg5m4+8CQOfdQOMVtM/pRepSiJwHxl6m9+1o/v/ZO+vwRs5zfd8jtszstZeZGbLZMHMxaVJKCmmbtGnT5pT59HfKkLanmFNO03DShrNh2M0yM6/tNbPFML8/XsmjkWRb8tqbhe++Ll+SPs1II2lmJL/P9zwvlJ9zfJGAmibboVnks4/Hrg0HVluqG+vgWxDulffAYpPjd6QdU6c4l82qHHwh4Jcv7qPbb56d/akLJvWzNCKIdRwyjxVWS6zcUAh1Q/sGEdZyx0DBlP6XtdglcrJ0aUwk8YhLzJ9wnGoWcMeiHBOj86ZfA9ULzI/3yg8gnBAFlTtW9u1gB0Q8UDhLxnv2iSAzAswbU2S6vVVFkw0/4V7wJp0v8vqPJQuGozQnRYRVF6WemxclOWI8wQi7G40JHy09Af77CbPz0WW38PsPLqLI7WDF5DL+detZVBeaH/vPbx7i35uTotROEVp6AqzcaY4rvWnpGLSE7yub1cLvP7SI/37HLIrdqWLY8zub+M5/dqAPs9iu63qKEFPsTvgNaM+X4z8a6t/pmVMNNbNT958NfzPftlj7Jg4srzF/V6+uQxx7CoVCoVCkIetf1KtWreKhhx7iy1/+Mrfccgs333yz6U+hUCgUCoWC8Aj2h0kmLxax460zIrQS+oMMiueoEW1WvADyxotzIRMnwRu/gEOvZr3JXPFD9LFnZ7/e8ZI7Xi69tVK0n3Gt+f6Dr5jjyeLCTaBFCrTDQV80WffIuR7iQpxmBYs1xRFTqbWjbU7qITHlcphwnjiUrvmFOYou5IF1fxr4ORP3l+TZs+UTwJHG3eKpNWLE4sJHtvhbpem4rkuhuewscTAcL/Z8I4Kta7sUr4aL5HiyloPQtltef7wHiIonG5A5NYVUFaQR9gbh0pmVTK0c4Lwc8UF3Ul+ootEJ9wczPxdEAgkCYRkUzR18HZD+C5UXiBCsR+UxfAnbFI8n8zcZ53xNg4u+aX6cnkZYd49x2+o0ejh5jogrx1kmzxF37Awzc0eb+4wcbvPS6R3GqEeFCHbeJJdDflX6ZYGGLl/KV8/oolRHTHm+k3Gl5vH7EtwgP352Nz0Bs8j5o/fMZWa14ZAozXPy+w8twmEzn9u//MhWdh4bYVdolhxp8/Doxjo2HOno17HyyMY60/epy27hHfNTe9zZrRY+vHw8r/zXhdx67gTsVrNY8Y+3jvC7V4fXieYLRQgmTbooShSCNIvh0B4onszqhGkXmse3PwKBpL52sXPJ8lHm3jdHuzXqW9vEnapQKBQKRRJZ/7c3ffp0fD71paJQKBQKhWIA4v/kjlR/mEScJeKy0KNSXAOjOGcdJJos0AadW+V6wbTsemkcfQte/r55LL8arvopzLkWRs9JXwxadhss+XjmzzOcOMvAnieFUW8dTLsS7Ak5+npUYtXi2AvlPYyG5b0aDmx5UhCJhiEyMrPQ+4S42Oef3CPmButrEE6YEatZ4NLvGreLx8Osd5kfc83vIZThb+BkR0zZxNRYsog/Ia5p2tBES12H7tiM7NyxUDxvaGJOf+RPkf0lEpDYvuFiwvngKjKP7X5aLuPxZIEsXWZnGJqmccnM1Pif6VX53DaA4+X2gdwwIMXD7qT3vjgmfPgaofF5aHgeOrZCoL1/MdV7TKLFwj7Zh0oXZ7dvWuyyTs4oOS+1rzPifuwFxjnfl+AsmHQRjDvH/Div/wyCCYVSdyyi0Vsn56Ci2SLi+BrNzpthYlpVPs6kIvzWOuX2GlYC7eDvNY8VjOl38eRYsjynjYKc9BMvzp5kdkbct+YoL+xsYtPRDh7aUGe6753zq9OKEnNHF/H/3jHbNOYPRfnoX9dxLGlb2j1BXt7dzOHWkW9sn8jWuk4u+fmrfOHBLbznd6tY+L2VfOa+jTy0vhZvUMQmXdd5YJ3Z6XHVnFHm+K8kCt12vn71TP7xsWU4rObj4MfP7uHRjXX9rJk9Hd7UyQJFOUmTEuLfswPGk1XD1PPM56tgr4gxibgqQbMwvdBLsTupT0wdco5RKBQKhSKJrP9T++EPf8hdd93FK6+8QltbG93d3aY/hUKhUCgUir5oshPhiAHDFeM5LMW5TKLJIkFoWyeFRHc1FKQ2mO0Xbzs8/DEj/grkn/b3/J+IMMveB1d9He7cBl87Bp98DW74O3xsJVz5w+xip4YTTTNcMZ4j4MiF6Vebl9n6oHn5vniyYYqn0jQjqz04QgXJhP4wAOGoeZbsPOtB8/JzboCKpGbfKz5nvu1pgS3/Gvy5Az2pPTbKJ6Y6YhIjyfIGKY73h69e3kOLDQpmDL58tmgWKIwVED2HzH2YjgerXUTARPa/KJdxR0ywY3hdOKchHzprvGmm/SUzKnj4trP50uXTuOXs8SnLnz2plAVJPUtSiHihN0l0LZkggkrHZjlfRkNy/mh5E5pelH3ZUyvOhLAHWt+SOLJIICbCLB2wX0e/aBbp0eWuifXx2mCIMe5YoT2x2KlpcHGSK8bbDqt/Zdx2lkpkZjQs5zR7vvREAumHNMxNtu1WC7MSHBKg+sQMO6F28CUJMUUT+128viOpP0xRjilaK5FPnDeJHLs5XvVLj2zla49tN43lOqx87ar+z8E3LBnD+5eNNY01dvu55S9r6fKF0HWdf645woofvsRH/rqOC376Cuf/5GW+9e/tvLiriVCaeM3h5LcvHyCUMGGhyxfiya0NfPHhrVz001fZWtfJWwfbOZQkEN20dGzyQ6XlrIml/Px981LGv/TwVl5IijobKslOM4sG+a4kgc2WQY+63HGQWwJjk6IOU+LJbOAsx6LBsjHmST+r6zUVT6ZQKBSKtGQtxFxxxRWsXr2aiy++mIqKCoqLiykuLqaoqIji4kF+2CsUCoVCoTgz6IsmKxh4ueEip1rcDxG/zGzORIgJtEhB0ZYLRfOze74X/xu6k2Y7nv8VGL8CuvfI7dwJEhHlyIVR82DmO2DM0uyeZyTIqZGCZahb+iLMvcF8/7GN0HbAvDxIAXTY48lGSIhJiqZLjiabzhHz8hMvSH2MUfNgYlI8yapfS1+ggahbByQ8n2aF0glmUdJ7LCmSbAjCXDQCXbvkev6U4YkjS4erXCLqdH1445umXm6+fWyHiFi2HHmvdB0CrenXVQDitvjnx5fx0RUT+PVNC/jDhxaT57ShaRrfvGYmV80xHHk2i8bnL81AbA60Q2+neaxkEnRsNITDsrOk34vFJgKN56iINI0vyZ+/RfbtgmlQcb6cY4eKpklkpHu07BMdm0XsyamO9XvplNtxxp4Fky81P8aq34Cv03i83JgrxnNYLgumGj1pOrcNfVv7IblPzBbliBlefM0QSHJXlvS/ryc7YmqKc/pddkJZLt+6dqZprN0TZFeDuZB/5yVTqRgkKvDb185kyXhzvWRvUy+3/n09H//ber7+2HZ8IeP75Uibl7+vPsLH/raeq3/1Ol2+kRGmvcEwr+ztPwqysdvPDX9Yzf97ytwPZ3JFHovHZV7/uWZuNd+42ixWhaM6t/1zA8/tOP4+dF1JjpjCHDsWS9J3a/w36UCTChyFcp6bdoF5/NhGaEw6P8TjyarNz/1WvYYe8siEAoVCoVAoEshaiHn55Zd5+eWXeemll0x/8TGFQqFQKBRnOGGfzCrWtOMrwGWDZjGcHr0HU6Kp0hIXAVzl0ng1U0I+2PaweWz8uXDef4kIFOqWAmVe/zNy31asDsOd4W8UscFdZl4m0RXjLI3Fk4WGrzDuGGEhJimaLjGarAAPo7WkCKKqOTJ7v/eQ4aaBVFdM+0HY9cTAz73jcfPtsnHgrjDHnMRn8edNGrprrPegCI+2nJHf1wpnyfb7W2QfHw4mXWzuqxONwN6n5LrqE5MxS8aX8K1rZ3LtvGqsCUVHq0Xjlzcu4FvXzOQ9C0fzxw8vYsn4NH2KkunYD5EkV4jLIQKNxSYOFVe5CIhVl4nbJX+yRETG93FXufR4KZg6PFF5mibP5yyV75b2jeKwccbOW96kxucXfcN8O9ADr//EuO0eI9sV7BIhx2KX16Vpcmx6hncm+7zRRabbm2s7h71R+RmLrqdOigAomdzvKukcMQNx45IxXDazst/7J5XncnMaB1oyTpuVez68mEnl5t9Faw+18+Lugc91e5t6+e0r+wd9jqHw2t4W/KGBJ1n4Q1F2JPW0uXHJmH6dRP3x8XMn8vFzJpjGQhGdT/9zI89sa8jqsZJJjiYrdqeZnBAXYsI9A08syR0Po+eKMyaRZFdMThVoGsur/Kbh+h6o7WbYzyUKhUKhOPXJ+pfx+eefP+CfQqFQKBSKM5y4GybeC+REkTsuVlxrMyKvBnLEBDvlMu7OyJR9KyGYOJtSg3f+VsScZDfMyUq8YbWvAaw2mP1u8/3bHjR6P2iazD6H1ILnULFnEA9yPET7jyaboR01L2t1QNlUKe52boemV4z4o4kXQFVSg/E3f9l/X4xwEHb+2zw2fok5liwaMQStbHoSJRIJQG+sKFcwY+SPM5vbiE/r2jE8zihXAYxbYR7bGetPFO8To4SY48JutfDRcybwsxvmcdH0/gvJJlr3mG9b7WCJuQ2K5sm+EMdihZxKKJwB5Sug+koYdak4ZoZbhI87Yyx2OXd37xWXDJj7xABUzxcHYiLr/gSe2HFndRjntLgrxlkC+dPkeue24YvhI9UR09oboKHLn35hRXZE/NCTdJ6wWCA/tVdLnGwcMSD9mH74nrlU5Kef2PGd62aZIgIHosjt4K8fWUp5P481EH9fdYSWnsDgC2bJM9vN4vqiccX88N1zWDC2qN91HFYL7144ekjP97WrZnDDYvO64ajOZ/61iSe3Dj0CtdNnjiYrdKeJQ7TliKCs6xDuTb0/Tk412FzSKyaRrQ9AMMF9ZbGDo4QpJVCWa57Qs7oeiT8cLiexQqFQKE4LMvrFcPTo0cEXSqC+fpj+SVcoFAqFQnHqcaL7w8SxOmV2YryxvKaBlr4BL7puuDEcRdk9T2Ize4Dx50DR2FPDDRPHFYssCrRLUX9OUjxZ+0Fzw3l3rKjlbxw8misTbAXy+UQCUkgbbvocUanRZDMth83Llk+HSK8hjkSD0LZehBk9DOfcaV7+2EY4+Er65z3wEvg7zWMTl4MjIb4l2Ca9hayuoUf3de+R/dxRZBSUR5r8KbH4Ji/0HBh8+UyYeoX59qE3IRoV54NmlX1jGAviigxoP2S+nVsggmbu2MGFQ80i+8hIYcuBopgw2rMPNLs8Z6g3td/UhV83C5QhH7zy/4zbeePl0ltvOOjyJ4ubR49IP5rhONcB40vdFCT1qtha1zksj33GE/aAJ6mnkSt3wLjHZCGmehBHDEBJroOf3ZDa4+TK2VWcO6U8s22NMabEzV8/soQ8Z+rvk7I8B3+6eTFP3nEOX7x8msnl5gtF+MOrw3TujREIR3hpl1nIeuf8am5cOpYHPrGc9y0ek3a9y2dXUZI7tMkmFovGD989l5uWmh87EtX53P2bh3xsdCY5Yopy+ulLlUk8mcUqzrmpFwAJ+1KgG3Y+bl7WVYmmwbLRSULMMZs4iYfLRapQKBSK04KMhJglS5Zw6623snbt2n6X6erq4p577mH27Nk8+uij/S6nUCgUCoXiNKfPEXOChRiAnNFSPA+0xYp0/RRjIt5YfJpFnDuZEuiFPc+ax2a9Sy57Yg6Fk90NA1LQjAtQ/kYYvRiKzXEhbEuIJ3MUyzrRMASGwaVgsRrve3IBdTiIJDliEqLJZmpJ/WGq5kLPXrmeO0YEB02TAm3TKzD1UigaZ17n9Z+lf97tSZF1FVMgv8wsxMRdHnHXR7ZE/OCNTZIqnDW0/jJDwWKFwlivhJ69w+OOSu4T4++Fo2/IceksjY0pV8wJQ9ehK+lzzS0Cex4Uzn5bNikFd7UcpwCdW414smRXTPk0mHujeWzjvdAVi7FyFEtEoh41jqe468bqlCJt5+Zhmc2uaVqKK2ZzreoTMyyEe8GT1Icjp3+BOxrVaeg0i/+DRZPFOXdKOZ+50Ig8q8h38vWknieZMqu6kN9/cBEOq1GOuWRGBc/eeR4Xz6hkdk0hn75wMu9ZaHb2/OOtIzR3D9/khTf3t9ITMKIINQ0unyUTNRw2Cz98zxy+ftWMlK+Z9y8de1zPa7Fo/M875/DBs8yPE4nq/OrFoUWwdXrNjpi00WSQIMQMcgzmjpPv79FzzOPr/2y+7RK34fJR5udfVaeJedabJjpPoVAoFGcsGQkxu3btorCwkCuuuILKykquvvpqbr31Vu644w4++MEPsnDhQioqKvjrX//KT37yE+64446R3m6FQqFQKBQnK2+XIwZkNjOAHhKxpT/6YskKsot12vus9MCJo1klAicaMpqyxmdan+zEXTG+Bqm+zLnefP/2R8y9InJiBaFTIZ4sKZoskhBNNtOSJMSUT4o1F9cgfyoUTpeYJVuuiB69+1JdMYdfhyOrzWNBL+x+2jw2abkUsROFOX+TXLoyjIpKpvewFMydpRKndCJx18ifHhXHUO+hwdcZiNJJUDrFPLYjJmapeLITT8QPPUn9k/JLpWdPNn20RprC2cbxGT/veutTIwMv+LJEB8WJhOCl7xq3c2Pis+ewsa7VCcULY2LsMWhdbe4bNUTmjjZHYCpHzDAR7gVvp3ksua9HAq2eIMGIWVwbPUg0WSL/dfk0/nTzYr5z7Uwe//QKRhe7B1+pH86ZUsYTd5zDXZdO5c+3LOaeDy+mLM8cWXbHRVOwJbhiAuEov31l+FwxzybHko0tpqLAcLVpmsat503kng8tZnypG5fdwh0XTWb5pNLjfm6LReN775idIsa8uLuJQ62erB8v2RGTNpoMjDjawSaB2PPke3bahebxunXQvNu8nC2X5TXm/aq5N8LBTmTyyjCcQxQKhUJxepBR5aGkpISf/vSnHDt2jN/97ndMnTqV1tZW9u3bB8AHPvABNmzYwJtvvsmVV145ohusUCgUCoXiJCccE0CGu0dAJmgWY4b0QP9kDzWWbHuS63fiBZBbJg4ciBXdRzCaZziJ94kJtImQNDcpnszTAodeMW73xZM1iTPmeIkXQwablToU4lFDVilqhWKOGDthpmhJs1PzYoKhe4zR/8JRDKWL5br3GMy8GvKTYple/6n59t5nIJRQPNIsMGGZ2Q0T6pXjI3E/zYbE2ft5EwZedqQoXmA8d+d26Np1fI83LSme7MCLsn/FhZhg+/Dsb4rBCXZAb5K7IL88+/PkSGOxQUlMLIkGZLsjftlXEikeD4tuNo9tewQ6Dsv1nGoRasI+s+DnKoPSZXJfoB1aXj9uwXje6CLzZtR1EY3202tKkTnhXvAmfYfk9S9yJ8eSOawWyvOy69dy8YxKblkxIaNIs8GYVpXPHRdP4aLplWkb348pcXN9UjzYfWuP0tDlS1k2W8KRKCt3NpnGrphdlXbZS2ZW8tJdF7D125dz12XTjvu542iaxlevnGGK7tN1+Mub2Yv8HUlCTL+OmPj5LNTVf7+3OLnjYdwCyCkyj2/4k/m2q5KJRVCRZy6vrW50y3MkO/YUCoVCccaSVWdPl8vFu9/9bn7xi1/w2GOP8eyzz3Lvvfdy1113MXv2SWJXVygUCoVC8fahR6XHBoDlbRIk4gXucFf/Bdy4SGMvTH9/OnydsH+leSze5D5eAHScYIfC8WDPkz89KkXIsikwar55mbX3JCxfkLD8MGSej5QQY9oH444YKbZM1upxaEl9H/Jj/WryJ5vH7QVGM3DPAVjxOfP9+18w99HZ9oj5/pp54C407xPxWDdnqRSTs8XXIDNrra6hO2qOF02DotlQMF1u9+yH5tegY4v0jvE3Z9dbI7lPTHsdNK0XIdeWG9vfmtKvqxhe/K3Q22keK6gwi4knC46i2D5oEZEk4k/v1jv3v6TpdpxoBF7/iVy3WKX3DYAnqfDrKofyc2QfDPug+Y2YG21oUWXJ0WQ9gTAHhzDrX5FEsEsiDRMpqEm/LLC/2fyeVxe5sFhSBZCTic9cNBm71djGYDjKb18+flfMmkPtKeJFPJYsHRaLhsOWVfkoI3KdNm5aZnbFPLS+LiVqbDC6fObli/pzxNjyZDJEdBDnNEjfQZsbpp5rHt9yP4QSIuJifWKW15iFndUNMTHIU5vJS1AoFArFGcDwf5MqFAqFQqE4c4k3Xtcsb1+fFIszVoC39C8YDMURs/spw2kBMlt6+jVyPe6IcR5/XMcJxRVzxfga5HL+B8z3730WmnYat4cznswRE2LCXimIDBdxEUbT+mKJQrEompT+MAVV4HCL4JLOwVUwXfblQBvMuhJyk5oyvxZzxaQT6SYukcvh7A/jOSyXuWOzi9QbCQqmQPE8eZ+DXeA5Cl07oXUNtLwm7p9MGLMMXEmC6K7HZRZxTsyFFN8/FSNL5z5zHCFAYfXb0+8rE/ImifDuKBZB0FuXKpQUjILFHzWPbX0QPK1yPXe8XPpbpPF7IvY8qDhXRBk9Ap3boPFF6D2YndgIVBa4qCowT07YUtuZ1WMoktCjEOoEX9K5JrnfWQI7G8zOppnV/feTOVmoKcrhxiVmoeL+dUfZcKSjnzUyIzmWbE5NIWNKhh61djzccvZ4UwSbLxThvrVHs3qMlGiynH6EGM2SEE/WOfCDahb5vp12gXnc3y3fU3GcJWCxs7zafF5Yc8SPHheLRyKGVaFQKBSnHEqIUSgUCoVCMXzEhZi3M54rGpTinMWWvklq2COFf81iNIzPhB1JsWRTLpW4img4Qdg5xYSYeDxZ3MWw4AOQkzT7/c1fJiwfK4wHWsyi1FCw2MEWi3YZzgJFnxvG0dfIPu6ISekPUzw65oZJ6lMSx5ZjxHB5D8Hyz5jv3/MU1K2HnY+b3w+rA8Ytir3G2D4WDRuC3VDcLKFuiUnSNGkifDKQOxYqL5KYqIKp0kjd6hQRpuV18GXgZLHaYfIl5rFDq8QF447tb8MVh6cYmNa95tsWK5RMIqVT98mCpkHJAnGd6SERKv0tqcuddbvZgRYOwuq75brNbQijvYdT17XYoXSpuMCsLvmO69wBjS+I8BjviZYByX1itqg+McdH2CMOwWQhpmhiv6tsP2b+rplVnYUr9m3k9gsnmdwooYjOx/+2joMtGQreSUSjOs/tMAsx/cWSnQhGFeZw1ZxRprG/rTpMMJy5Ay3jaDIwJuEMJsSAfN8WVEL1TPP4ugTHsGYBVwXLR5sXafUE2eeJ/S5M93tUoVAoFGccSohRKBQKhUIxfJxMQoxml6JcxG++vy+WrCBzV4GnDQ68bB6bFY8l65DZ+7YcQ1g4VXAUyjbrERFXHLmw9JPmZbY9BJ2xman2PFlH18E/DC6FkYgnizfFtRi5//06YkrHiRg1UD+j/ClSjA31wKwrUoWq/7sYnkiKLRu3DJy5sf0wVsQOtMoM7njkVrbEi8SuqpOrD5HNLf2DCqZBySKoOF9mB0fD0LYWuvcOnsOfHE92bCd07pZjVMWTnTg6kuK5cgvfvgi8TLG6oGS+iOC+BujalrpM0RiY/V7z2Pq/QTAWS9Qnth5N787TLLJM1cXiArO55Xum5wA0vSLRfL2HBnXJJMeTbakbgf5YZxLhXvB2pL7vxePTLh7RYXejWTibU3NqCDGjCnP4yIrxprEOb4ib/7KW5h5/+pUGYOPRDpp7zA3k304hBuDj55qdTE3dAZ7eltnvDF3XM48mg4Q+MZ2DP3hcrJ12kXm8dr3RbwrAVcnYAqjONwvXqxtjLiNv3eDfhQqFQqE47VFCjEKhUCgUiuEjepIIMVYnOGMxUskxWvF/vLPpD7Pr3yJWxLHlwLQr5Xrc5XCquWHixOPJ4jFuSz9hFpT0CKz+jXE77orxHjv+5+6LBxnGgmQ0VlyyGkJMtz8M6My0HDYvWzrW6CnUHxa74Zjx18KyTw2+DRMWymVuQpxMXEgYSixZNGzMpo1HKZ2sWJ1Qttwobnfvkb+BmHyJWRSNhODgq+IC6osnG4b9TTEwHUl9DPKKIOckF2JAxNTi+XK9+U3jnJzIis+ab/u7Yd3v5bqzXES/aFjElf6IxxRVXgSlS6R/hGaR81fndmh+Nb0jJ8a80UWm27uOdeMNKqfXkAn1Qk+SQKtpUDA67eJNPvCHzA6L2aeIEAPwX5dN4/yp5njM2nYfH/3rOl7d28Jrsb8DGbhk/rXWfKxPrcxjUnkWDuERYO7oIpaON/fZ+783DqJnIF54ghFCEfNyAzpiEn97ZCKO5I6D8YvAmfQebfq7cd1VgWbROKvavI+tPhoUh24kIBNeFAqFQnFGo4QYhUKhUCgUw0fYJ5fWt9EZEi/Ex4vgyXEQ8aJ/Nv1htj1svj31cuMf8uAp2h8mTk5sFqyvUZwHuaWw6GbzMhv+Jq4gMPrEBFpT3UbZMqKOGKMI0+0LUUMrhVpSY97ScVKAHYy8CSJORfww63JwDlC8s7th9BxZ3plQNOvrDzOEwra3TgQxex64BhGOTgY0i0Q5Fc+V270HpBdQf7hLYOxy89ih1eIy6Isna1bxZCNJJAg9SUXC3EJDqD3ZKV8uIqcehmPPpZ6bKmfB5EvNY2v+ID1xNE0cXSD9XyJmp0AKmibnzdIlUHWpEVsW9kDrW9C+KW1045zRhST2hQ9Gojy5VfU/GjIRT+o+m5PXrzO1rtfsVKgpyqEk923qZTcE7FYLv/3AwhQXz/b6bm7+81o+HPu7+Gev8qNnd/f7OM3dfv6zxTxB5bp51SOyzdny0XPMrpjt9d28sb910PU6vanHW+FAjhhbnsQV6hFxVg2GqxIc+TBhmXl828OGkGOxg6OE5aPNws5bh9qJ9k1gSRK7FQqFQnHGMSQh5h//+AcrVqygurqaI0ck4uHuu+/m3//+97BunEKhUCgUilOMk8EREy+AxRuaJzdJjRf9M3XEdByBI2+ax2a/Ry71qJExfqoKMY4SES2iIelBArD806BZjWXCPlj7R7luy5HoKTh+l0JfPEjP8BXZ+3rEGI6YLl8otT+MM1dEJ1sGQoxmgYLpsW1tgvf+X/qG0JoFzrsd7C5wjzViyULdUhjWrNnvJ3pUisNw8rthkskdF2t0HoXuXQMvO+M68+0jm6DnMFhcKp7sRBBsh95O81hBuYh/pwKaBSovlu8eX53E4iWfU86503y7uxG23ivXc6rkfKRHoGdf5s9rdYhQW3lhQsRZHTS9nNL7qjDHznlJjob7s2xIrkgg1Au9Se4nd5FJhE+k1mMWYmZVZ3DuP8nIddr48y1LGFMy8GSX371ygGe3pxf5/r76iMk94rRZuGnp2LTLnmgunVnJ2BK3aeyHz+wmGh3YtdKZ1B/GatHId9r6WRr5bu5zxXQOvmHx3myTV5jHO45A/QbjtquS5TWp27a7J/6bqTF9/KFCoVAozhiyFmJ+97vf8YUvfIGrrrqKzs5OIhGJ6SgqKuLuu+8e7u1TKBQKhUJxKhGfhWx5m4QYXTcK8bY8w33gic1CDHvkn2DNAvb8zB5z24Pm264iccSA/AOvRyWOaSh9P04G4rO7wej7UjQW5lxvXm7tHyDokevDFU9mdRqi3XC5YtJFk/lCqf1hSsZJkdliJSNyamLxRSEor4HPbYavN8Jde+D2NfCxlfCF7TBhvizvHmOsG3fDOMsy70sUp2e/7LdWp/kxTxUKYw2Ovcekn1J/zLjWfDvkh2PbwXNExZOdCPytqUJM0bi3ZVOGTN4EyJ8mwrG/Gdo3mmOHxq2AmkXmdd78lbFMXGz1HDHcnZlisYkzpuLc2HkiKGJQkjPmxiXmgvfGo53sbTL3LVFkSLxHTCJ5pfJZpCFZiDlV+sMkU57v5O8fXTaom+crj26jscvsDPMFI9y7xvxd+O6FoynNc3IyYLVo3HbBJNPYjmPd/GfLwOf+ZCGmKMeOpmn9LB2jz5HbmdnG5Y6FqqmQZxZT2fRX47qrktEFMCZJ41t9NCi/OfWo9LJSKBQKxRlL1kLMr3/9a+655x6+/vWvY7Ua/7guXryYbdvSNEdUKBQKhUJx5hB5mx0xiTMNLXajcO2ti7lX4m6YgswK4roOWx4wj816F9hiRYvAKR5LFicnFj/kazSKkiuSGtD7OmD9n2PLV4uAE+wYOHIqE/pcMcMkxKSNJgukOmJKx4Iji0KcpkHhDLnuOSyv254D+VVQMR3GLIVorKDqqjDH48T3k2xjxUI9xuz8wtn9FhhPauwFRkxg547+lyusSS2SH3gTPIcShEIVTzZidO6X3jyJlE5+e7ZlqNhyJMouf6q4+/xNZneLpqWe11oPwM5H5LqrXM7lehR69g5tGxxFUH62CPNhH7Svl8eLcfGMCsqSit7/OgVdMbqus/FoBw+ur6XDkxoLNeJEgvJ97+k0jxekbzgfierUe8xjs0efmkIMwISyXO67dRlnTSyhqsBFVYGLinzzftXpDXHXQ5tNbpJHN9WliBYfO2f8idjkjLl+0WgmV5ideD95bg/+UKSfNaDTZ94HB4wlixP/7ZGJIwbkd23OKJiUFKO56ymJOASZ3GHLZXmN2cGz+kBbwu9RFU+mUCgUZzJZCzGHDh1iwYIFKeNOpxOPx5NmDYVCoVAoFGcMfULM29Qjpi+Wyi5Ci6tCnATRoBRxs40lO7YR2pJiaubdaFyP94dxmBvMnnI4y6TIH/Ebs0MrZ8LUK8zLvflLCHrlPXXExKfjdSnYi+Qy02LIYMQdMYnRZN5gqiOmdFxmsWSJuCrkvdKjqQ3odR28sYJqbsKsdz2aINhlIcToOnRskfVdlUavlFORgmkSyxbsGNhFNfOd5ttHN0HIK+vZ81Q82UiSfJ7TLFAy5e3ZluPBPVr2lXiRtWev2Yk1/RooMc+457WfpLpivLXiRBsKFrv0j7HY5Njv2tl3l91q4frF5mbyj22qH7DIfLKxvb6L99+zhnf/dhVfengrl/z8Vbp8JzhuKdwr/YC8SW6iflxch1o9BKNmh8Ts6lNXiAGYXlXA/Z9Yzltfu5i3vnYxa752MVfPNfd0enN/G3964xAA0ajedz3OBdPKmVyRoTv4BGGzWvjKFdNNY/WdPv6++nC/63SkccQMSt8kkG6TWDog6eLJvO2w72njtqsypU/MmkNtRFyxCSyB9qGfWxQKhUJxypO1EDNhwgQ2b96cMv7MM88wc+bM4dgmhUKhUCgUpyKRoPHPrPVtirmIJrkhNE0KcyCFtXixP/4P+GAku2GKxsGYWLNWXTd6qpzqjpi4aAXiiolz3hfNy3laDFeMOxaE7jU3/c2abGelDkYkNZos6utkjCWpqXPJOHFrZEtf1FaduQeEv0me2+o0IvFAxD89IsVZWxYFL88RKSBbbEbT+1MVqwvyY+6K7l39F71mJvWJCXihcZe4GuLvqYonGxk6zAVa3PmGE+lUImeUnM+sOXJ867pElMWdVBYrnHuXeZ2m3bAn1uvUWSL7mq6bBJSssedDcWzyYu8hIx4TuHGJOWKw0xviuR2NnOw0dfv54kNbuPZ/32D1QaM3S5snyMMb6k7sxoR7xRGToRCz45i5X09VgYvy/JMjjmu40DSN779zDqMKzY7kHz+3m9+/eoB71xzhYItZAPj4ORNP5CZmzMUzKlg6wTzB5X9f2k+nN737qitpvNg9cGwbIK41i12+j0IZxgM6y6B8ikzkSGTrP43rafrE9PjD7GwKGpMxvCf4eFEoFArFSUPWQswXv/hFPv3pT/PAAw+g6zpr167lf/7nf/ja177GF7/4xcEfQKFQKBQKxelJJJapb3Vm3wdjuIg7YhKFIHfMneBvgkCsGJ+JIyYSgu2PmMfmvi+hAfsQC+wnK654PFlCfvnoxTD5UvNyb94trph4wTPUnXkRIx1xISbev+d46XNFGftAlf+AeRHNBkXVQxNiHIWGCNW+Cbr3SZG196CMuUeb939/q1w6S419J9gJzW9A82ty2fImtK6BzlhPFF+T0dy+YMbbF/U3nORNktcR9sprTEfxeKicYR47uFYErrjI6m82xDbF8BANQXdS34K8YrC50y9/MmOxGwKSvVDiysJe6NpuLDP3BumDlchrPzGuF06XY9XXKMf3UMmpEjcYQOfWvvPkuNJczp5kFu/vW3Nyx5Ptb+7lirtf46ENdaa2O3E2HR2g/9NIEPaAv0t6SSVSlL6P1o4G83fU7JohnPtPAQrddn5+w3wS26OEIjo/fGY33/q3ORpyelU+KyafnJNINE3ja1eZvwu6/WF+8/L+tMsnx61lFE0GCa6Yzkw3TL7jJ51tHt/3KgRijmtnCVUFdiYUJsWTHWw1fo96jpL2QFIoFArFaU/WVZKPfOQjfPvb3+ZLX/oSXq+X97///fz+97/nl7/8JTfeeOPgD6BQKBQKheL05O3uDwMJRfiE2ZD2PHAUy/b5GqVIbs9AODnwEnhbzWOJsWSBhFiywZrCngq4KuS9CXvMwsoFXzEvF3fFWOzgjDWtPR6XgsVuFHyP1xUTDRlui9g+oOs6o0PmImegoEb6u9iGGKFXMN0Qobp3Q8dmY39wJxV4g2liybp2itsl2CWXgXYRGHoPQcdWafIdDcvs/NxTrGF6f1isUDBVrvce7L8INeNa8+2jGyEaFXHKFosn85zcRetTjnAv9LaZx/LKT10BMCfmggw0Q9ECOT97ag2R2WqHc75gXufYdtj7hFy3F0DRHLnevXvgOL3ByJ8i51Y9Cp1GP9WblprPE2sOtXOwpXfozzMUwl4Rg+ufgvqn4dgzcOw56eWU5Fq7960jKfFPiWyu7RzhjU0i3As9aWIKC2pSx4DtSY6Y2TWndizZQCyfVMqnzp806HIfPWfC4A3t30bmjynimqSotb+tOkJ9py9l2eR9MyNHDAwtGtU9JtYnJlHt8sH2++W6ZgFXOWeZEwhZc7BdxFmLQ36P+pszf06FQqFQnDYMabrqrbfeypEjR2hubqaxsZHa2lo+9rGPDfe2KRQKhUKhOJWIxoQYy9tYvEvTqB2A3DESnRZoleJiJo6dLfebb9cshtKE4kbwNIkli2OxJQgrya6YS8zLxl0xwx1PFu/hM1T6hDibFP4BTzBCtWaOJdMLRg3NDRPH5oay5SIs5I6VJt/2fMifJMJf3xNFE+LrYkJMqFtEG02D0sXSS6J0MRTPk/VdFfL4thwomnd6iHxxckaL8Bb29t/rZfb15tveTmirFZEtftx6Dmee6a8YnFAP9CY5Ggoq375eX8eLqzxW7AwAEciLxeJ1bDG+I+a/P7Von9grJncc5MVimzo2DV0k1jQRdTSrHPexSKLLZlVSnDRr/4F1J7CJdzQMbetEDNaj4u6MhuUc2ntQHHoJDsX9zWaRyGEzf4fWdfho7T1BTjVdl/eyJylu0ukGR+oki2hUZ2dDkhBziveHGYzPXzI1JdorkbI8J++Yf/L3Hfvi5dOwW43vwGAkyv++lOqK6fKZo8ky6hED4nCF7I5vmxtKJkN1knsz0UHtqmJZtXmywZa6LnQ0+T0K/TtDFQqFQnFac1y5IWVlZVRUVAzXtigUCoVCoTiVCcejyU4GR0xS9ntOtTT2jfiMXgED4e+CPU+bx+YlOX/jrpFMYs5OFeKRPr6kmKLz07hiNvxFeiloVnHRBI9DRBnKrNR09Alxxuff5QsxOkmIsRaUHf/n5iyR2KHieVB2FlReYPSPiRPsjMXXOQwXVm+sF0fOqNhflVzmjpX1y5ZB1cVQdYlZ1DkdsFghd7xcj0e5JVM2FUrHm8eObJLLcK+IMXF3m2J4CPWAp9M8VlBz6jpiNEuCSFwngqmjUISFeN8XmxPO+bx5vbotsO8/xu3CmbF+MVFxqYVTZ+JnhM0tzhiQ54+GcNqsvGehecr8IxvrCEdOgMCo6yIuhbolxrPy/Ng55yIoWSRCdqAVml/vaype2+E1PcQP3jUHt8NqGtt8tHPktx3ERRgNgafdPO4uStuf7nCbB08gYhqbM/o0+t5Og8Nm4b6PL+OPH1rETUvHUp3UN+ZLl0/DabP2s/bJw7jSXN6f5B57aH0tte3m/THZEVOUaTRZ/LdHuAeikQEXNeEeA5NWmMeObIDumLjiLGdelXkSRWtvgGNdfsM1G2g2nOQKhUKhOGPIWohZsGABCxcuTPlbtGgRK1as4Oabb+bll18eiW1VKBQKhUJxMhN3xLyds6j7esQkOWIsdqPwnkkW+KZ7IZzwD7LFBrPebdzWdYjECgG23CFv7kmHq0pmcIe6xbUQZ8ySVFfMG3dDOAg58Sbqx+GKyTanvT/ifUQSinHdvhCjNXPEnL2w/PgcMZkSjyuLu6YiQaNJb+6EkX/+k5G88bKPBdr6F++mJu1r+14RIUuPArFZxp5DyWsphoqvCXzJTc9rUgXtUwl3TOTwNcp+UzRXbnvrDJfagg9BXpV5vVd/YggumgYlC2XfiwSg5fWhC4Bxt1wkIHFnwI1JBebW3iBv7G9Nt/bw0r3HiOksXSLnQptbvsvc1VC+ItZbxwPNrxPxtXEsKQ5qQnkuc5PEjBMWTxaPdPKZG8+TV5LqhgW21ZvPM+X5TioLTlGRMQtsVguXzariB++ew5tfuYgXvnAed79vPo9/egU3LEnfS+dk5PYLJ+NMcGCFo3qKK6bTm+SIyTSazJYjvxd0HcLdgy8fJ2cUTFwmvw3jRMOw40G5bnUwvryIAmeSK6a2U84DzlJ5ThWzqVAoFGccWQsxV1xxBQcPHiQ3N5cLL7yQCy64gLy8PA4cOMCSJUtoaGjgkksu4d///vdIbK9CoVAoFIqTlZO1R0wcRyymI9g18MzH9kPw0v8zj025DHITIsgiPvknWrOcurPG02F1GO/ToK6YZtj2oLiNQPrEDLX5bFwkC/uOrxF7mmi6Lo8/xRFjyS87QUJMrKgajyXzHJGisKNIHDVnIlaXsc/0J6bMeIf5tqcV2mKfYTQk55pA+/G5sBQG7ftTj93CmlM7Fs9RJMKCHpFzmaNIXGcAXdvl9dpdsOKz5vXqt8G6Xxu3LTYoXWaIMW3rJOIsE2dlIpoFCmN9Z3oPQ7CLyRV5KWLGvzcfRz+aTPDWQ88+uV48T/qnJWMvgPJz5b5oiKajawlFzPvH6OIc5o8xr7upNinebqSIxxp6kwrn+ZVpv/t3JPeHqT4B5/6TDE3TmFyRzzsX1DB/TNHbvTlZUVng4oNnmXulPbyxjiNthhDX5RuiIwaM3x/ZOHItdiicBDVzzOO7n+07N2g5o5iXFB6zpS72HPHeb96jQ//dpFAoFIpTkqyFmNbWVu666y5ef/11fvazn/Hzn/+c1157jf/6r//C4/Hw/PPP841vfIPvfe97I7G9CoVCoVAoTlZOBiEmTTRVH1aXFGk0C/j7mdUcjcK/PwMhc+wFyz9jvh2La8HmPrWLlemIF8njzo04Y5bApIvMY2v+AI5yKVaGfRIZMxQsNiOG63j6xERTP39PdwulWtJs/4IKIypspNCjCX2EymJN5g/L7bwz1A0TJ957w1ufXnirXgLFSZ2OtzwQi8KzyT6iR5UrZjiIhqEzqVeBzQ65lW/P9gwn7tis//i5rGC6FFCDXVIABVj0kTSumF9Dx27jti0HKs4TVwvILPbmV7J3x7jKjMi0zq2g67xjvrlPzXM7GvEGsxR5MiXiFxEJIH+y4RpKh9UpfbAcxdR1mbfHabNQnudMKehvre0iGh3honLEL45NAE9yX6OqtN/92+rM3ylzak7vWLLTkU+dPwmX3ShdRaI6v3pRXDG6rtOZFE1WnKkjBozJJ3EHa6a4x8CEJeaxui3QtVeuuyqZl3Qa3RJ3jeWMivVL80EgqdeRQqFQKE5rshZiHnzwQW666aaU8RtvvJEHHxQr5k033cSePXuOf+sUCoVCoVCcOpwMQsxAjpioX5rRWxz9N0ld939w5A3z2OKPwvikLPB4LJl16LFkPf4wI12zGhLuGhGrQt1GwSvOWZ82327eCUdXSaQZiCtmqAxHn5hIajRZpC1Nsb5onNH4faQIdohYYHWKyORrkGPE6jTErjOVuCMoUZxKxJYDMy41j+17GRyx4pUtV97P/oSct5OwV4rdx56Fjq0n3/YlE+6FnibzWF6pfAanOnHRI9BqHHsFU2Wsa7e4qxxuuOrH5vX83fDc10zN6sXRMjMW2+WWAmrbOumj4s+ikFo4S4TnYCd4DnPtvFFYErR8bzDCyp1N/a5+XPQcEIeQo1hEqcGwWKF0KbW9ZnFjdHEOmqaxYGyR+eEDYQ609A7jBqch7oax50NvUoxbfiVYnTT3+Pnxs7u54Q+rWfb9F1h90Fxgn6WEmFOO8nwnNy8fbxp7bFMdB1t66Q2ECSf9mCrMycIR44o5VgOt2blTnGUw8Ww5TuJEQrDzUbluz2PeKPOxs72+m0g05qaOC8X9/R5VKBQKxWlJ1v+BulwuVq1alTK+atUqXC4pvESjUZzOUzhTWKFQKBQKRXZEI0bR6kT3iEmMiEnTI6SPiB9c5TJjNtAGoaSCUfsheOHb5rHCsXDpf6c+Vp8jJnshJhrV+eqj21j0/Zf45gYrm05Urn6mWOzSQB7AU2u+b9JFUDrZPLbmD8MTTxbvE3M8QkyfEJfw+SfN9u/UCiGnfOjPkSnJsWS9MUEod/zIi0CnAvEeOb2HY71fkpj9DrAmFNOiYdj0DyiaA7Y8ccWEek+ejP24ANP0kmxTNCQFtqaXoHtfdo2gTyThXuhJEhLyyk6PyEWb24gA7OvNNF6K+NFgX68WZlwHU680r7v7Rdj+j9TzmbMEKs6H/CmgWeV81foWtKwyvhcGwuqEghlyvXs3FTk6KyaXmRYZkXiyiN8QPQumZe7ktDqoC5uF4zHFbkAio0YlNYEf8e+zeH8YzQ3epOfKr2DrMQ/X/OoNfvvKAdYeaqepO1UIVY6YU5NPnDcRt8MQPaI6/OrFfSluGBhCNJlmlXN2uGfw5eNoGhRPh+rZ5vF9r/RNYpk3zpxN1hsIczAuVsajEv1NxkQmhUKhUJz2ZP1f4B133MGnPvUpPve5z3Hvvffyz3/+k8997nPcdtttfPazkrH73HPPsWDBgmHZwPr6ej74wQ9SWlqK2+1m/vz5bNiwoe9+Xdf5zne+Q3V1NTk5OVxwwQXs2LHD9BiBQIA77riDsrIycnNzue6666irq0t+KoVCoVAoFEMlGvsn0mIzNy8daTq2QMNzRuEzXjRLdsToUflH1+IwZkl7Ewq40Qj8547USLJ3/C8400RYJUaTZcnDG+r419qj6Dr0hjTuuH8L3f7UQsLbSk4sssZbZy6SWyyw9JPmZfc8DT6vCDiRQPbxHnHiOe2hzqGtDwnRZMbnb+sx/+Zrt52o/jCx98FZKsXaYIcIMPFs+DOdnFHiuogGxdmSTME4GJ8U+7L5PhH9cqokpqz3IPTsNzsX3g58DdD0spyHdF32L1e5CLXRsBT8m14ymsSfTIR6oCfpmM0vPz2EGDDit+L7mGaBwljh1HMkdlxqcPVPwZFnXvfFH0PLmlSh0GKDwulQdbHE7GkWOd6b38gsnjF3nAg60TB0bU+JJ3ttbwvtnmA/Kw+RngOx/lTFsm9mQW2XWUQcnWdsW3I82eaRFGL0qOE+8qeKXs+3VXHDH1bT3NO/C21qRV6KeKQ4NSjNc3LL2eNNY//Zcoz9zeZJNTaLRp4zi9+hmkW+p8GYQJEp7tEwcal5rHZzX7RhRVkNo/LMYu6WeFSePT/mDNVTJ70oFAqF4rQlayHmG9/4Bvfccw9r167ls5/9LHfccQdr167lnnvu4etf/zoAn/rUp3jiiSeOe+M6OjpYsWIFdrudZ555hp07d/Kzn/2MoqKivmV+/OMf8/Of/5z//d//Zd26dVRVVXHppZfS02PMZrjzzjt57LHHuP/++3njjTfo7e3lmmuuIRI5SWemKRQKhUJxqhH2yeWJLN4F2mKFz6gIMj0HZNxiT3UcxOOBNAvkxXP+a2XdaAQevw0Ov25eZ/FHYeL56Z87HBNssnTEdPlC/OjZ3aaxpu4AP3xmdz9rvE24KmTmdjRozECOM/8mcCSIU3oU1v9JCusw9Hgye6EURCOBoc8OTRNN5vQ0mBbpdpQbos9IEY0YBVlnmRGnkzMqvVvrTETTElwxB1PvdxTDtAvMYx21cOglKJoLOZWALrP8u9/G48ffCu0bE4rclSLU+ltkrGC6CE4Rvzgnko+nt5tQD3iShJiCqhPvbBwpcqpToxZdZVJA1XVo3yTHa+FouOib5nW7GuClH0HrmvSOJqsTimZB5UXgKJTzZcsqEeYGQtNkH9Ys4Gvk8knSdyVOOKrz1NZhdMVEAkb8UcG0rFev6zBPUBiT09l3fksRYo52DmEDMyTQJtFqVldKLFnA4uITzznwh9K462KMzdX5wbtmoZ1ufd3OIG49N9UV89gms5Bf5LZn/xn3CTFZTiSx58OkC8RREycSgj1PyjnDWcrcSvPv0S2JYmV8Yobn8NDdxAqFQqE4pchKiAmHw3z3u9/lvPPOY/Xq1bS3t9Pe3s7q1at5//vf37dcTk5OX0zZ8fCjH/2IMWPG8Je//IWlS5cyfvx4Lr74YiZNkgKKruvcfffdfP3rX+fd7343s2fP5m9/+xter5f77rsPgK6uLv70pz/xs5/9jEsuuYQFCxZw7733sm3bNl544YXj3kaFQqFQKBQkOGJOkBCj69AVc8DGexm0b5TZjOn6w0QShKKcKrmMBsFTD//+NGx9wLx8f5FkcYYYTfaLlXtpSzPT+b41R3nr4BCdJCOBpiXMJE+aqenMhwUfNI9t/DtYi+W671j6qKnBsFjBFhN4hhpPliaaLNdvbqjtdZaPvCMm2BbrD+OSfSTuhIgXexRC7lgpYIW6RdBIxF4I1bNEFEhk3R9jBfB5UsTyHYOWt6QB+4km2AXt6+Sz1iwi0PqbpFisWeS84zkEJYtE3NQj0LbWiMk6GQj3Qm+neayg6vRxxFjsIo6B+X0vmi2vMeyB7p0ytvRWqF5oXn/3S7DyB9DyZv/OK1sOlJ0tz6NHoW19enExEXt+36SAfN8uLplhdqk8PpzxZD37jd4wWbphAGrbfabbo/N1+b6Nhlgwtth03+7GbrzBMCNCXMR0VaRETh4Mp76usyaW8PsPLuLZO89lyzcv4q65EeaOVrFkpzLFuQ4umGb+rJ/bYf6OL3Kn+Q04GPEI0UBb9oJI8TSomWkeO7havps0jXmjza7qrXWdxo2cavnNGvEbEzYUCoVCcVqTVXaIzWbjJz/5CTfffPNIbY+J//znP1x++eVcf/31vPrqq9TU1HD77bdz6623AnDo0CEaGxu57LLL+tZxOp2cf/75rFq1ik9+8pNs2LCBUChkWqa6uprZs2ezatUqLr/88rTPHQgECAQMW3N3t8ygCoVChEInWXzI20j8vVDviUJxcqCOScXbRqAHLRJG161wIvY/71E0XxtY7OhFZ0HPHjTfZrTeg+jWAvTkbYhtH1YbejgMjiq0nr1YnrgTyx7zxAzd6iRy3W/QLa70ryXiRwsHAA09asv49e5p7OEfb/XflPXLD2/lyc8sx2WPZZX7G4wCLxpoNinkpxOaRgJ7FVpkD/TWo+fNND/vwo9gW/N7NGIFC38XkZ3PodfUQMiH3tsgxbJsseSiRdrRvc1gy1K00KNoIV/sqqXvcykImh0I/pxyQlFLalE1GgJ/o7zfml3ih6zuIRWkta79EAmju8ohGETztYIeRtfyT8zxcSrhrELzHIGuvehWc5FUsxWiTT0P6/oH+8b0vS8R7joG7nIomIvmbUTrPYRe/yx6zbsy732RJSnfr2EvWuubEocXjz3UgmB1oxdMB0cJWvtaCHZD4xvoxYsgqqH56qFlHXqBR2Kt3k4iAbSeRmwBs+Mh7C5Bj56gc/mJwFGJ1lsLPUfQcyYb+0j+bLS2t6BrP7qtFJzlcNXPsf35ErTE3mN7XyUa9BG94NPoBVOlz4wlTQ+KgvnAdtmf27bIe5hTnbpcnJwJaL1HIdjLtRPdPLXNuGvDkQ4ONnf19WMZMpEAWvcB0CPoOROy/kzDkSiN3WaHYnW+nXCgG711E9Mr5mK1aNKAHHEobDrSxtLxJce33WnQPPVyXrUWY2k/TIIHgXrd3GfnfYtr+PY1M7BbZd6p+n18+nDe5FKe3maIL4GweeJHocs2hM/ZjRYFIj50X1t2rll7OZZxi7HWGQewfnQzkbYd6I4qZtWUAt199+1s6KbXFzBccM5RaL0HjPOQQh2vCsUphDpeDTJ9D7IOcb/kkkt45ZVXuOWWW7JdNWsOHjzI7373O77whS/wta99rS8Ozel08uEPf5jGRvkCrqysNK1XWVnJkSNS6GhsbMThcFBcXJyyTHz9dPzgBz/gu9/9bsr4888/j9t9nD+IT0NWrlz5dm+CQqFIQB2TihNNfvQI7mgTHssxei2DxLIcJ5oeoSyyFQsheixj8VpeBF2nInyE4ug+QloDRzeHCGtGtI472kB+tBa/VkqXtROrHmDx0V9S1b7d9NgRzcba8XfQvL0Dtj+d9vnteg8lkV1ENCet1syKvroO/7vTSiTa//JH2r3c+X8rec/YboqiB7Do6XLuNYJaPn6tmKBWgE5MpEFDI4KVAFY9iJUAEez4tTL0xMiMLCmN7MKme+ixNOO1mH9vLSuYS1X3lr7bnld+wfqpn8StN+PXDtNlzb7InBNtoSB6iJC2h3broazWteoByiJbAAtNCTE/54fMQkydx8rTT6d+tkWR/Tj15B4eGt2W8fgsmc8iN7YDWq0BNHZSGtmBjpVmqzZiQsGpilX3URaRAlartZaIZghfudEGigN5LMCCBSm2aZEgBx/8IrsrbgCgIGJhVPggsJ+mTUfotGYfvZQNK1euxKoHKI7uwar70bFi0cPomobHUk2vVg1sxI6XsO6gWD+AXe8B1tJumYKLLtzRRmA9Yc2NRxuFXys24hR1XY5jAlj0IFbCWAgRwo1fKx3W/ccVbaXau5o5SeMb99XScOQlc9zOqYwepSKyGY0wHdYWgppRZM2P1uKONhHVttJqmY2u2age+wkWHf4DFow4MsvhtXQ90sSB0ZcQsuXjsVTi0yqIaqmCTH60Hne0gai2lRbLnAHfR4feTXFkN3lRjVzbMjxh49z1s4de5bLRxxdXJK+vgZCWS7s161Ry2vwQiZpLBvsOthM4vBNYT5dlK1WuKuq9xn75wMo1tNYcf8ySLww5sae26n7KIlsBC81WnaVHtpDolYsLMRo67xgXZbntCCufS534oH4fn/qEgqBhRSf9uTDQ0572O34wiiJ7ceqd9Fia8FpGZbVuRSCPs9D6JqdokSAHX/gL+0o66Ak7AcOlG4ro/PnRZxkXa0ll0QOU9/1mqCOinSaxkMOAOl4VilMHdbyC1+sdfCGGIMRceeWVfPWrX2X79u0sWrSI3FxzJMd1112X7UP2SzQaZfHixXz/+98HYMGCBezYsYPf/e53fPjDH+5bLjkDVNf1QXNBB1vmq1/9Kl/4whf6bnd3dzNmzBguu+wyCgpOQIPXU4RQKMTKlSu59NJLsdvTzAxTKBQnFHVMKt4utPb14G9EL5wts4VHku5daL0a2HLRy883Cpjdk7E0PIVucTC9bCIULzDW6dqB5qlEz5sEBTPQjryBbbNZhNGtDvT3/o3Fky8d+Pm9tWidueAsRy9dNujm+kMR7l9fx/7uPabx284dxzObDnO41/g98nKDhU8uy2Nh1RxxY9gLAV2cMREfhHvoHyuQ5Jax2NHdY6UXx1Cihjwz0Lp2gL0Qvfxc013awRz41/V9twv89Zw3awq4xoJmQ6+6LLVXz2CEPWjNL4NmQa+6Irv1/c1o7Xaw5aNXxHr7+DuxbzK/Z5XTFnLRJVeZ1w11obVEgYngKAU9LA6ZiPyg1ovmGlFtg9G9G63XbuwfnsNoXTkZ7y9nIlrbGAg0o+eONxqpQ+xzeR382+Dwur7hqd4tTLz0N2CP/R/SMAlL21tM0TxEx06VyKdhFrz6vl/PW4CjdytEZxsReNEAuKrQSxaD7xhazx4IA45i9KJL0bp3SuyM1YVe/l5x9PXsk/0MwJqD7ixDC/dKTJvuIOVYBjkOC2dJxNRw0LEJy87dsM8Y0p1uFi4/H70qfWrAKUvXODTPEfScGvN3gx6RfSzcK59h8SLQriK6dznaox9DixhRksU9R1i0/19E51yJPmsG2MSlqLtHg6vKEFz0CFrzqxDxoudNlj5BA9GzF61nL9f5dP610xjeFyjk7qvOHvprjvjkfKrXoJcsHZJL8a2D7bBpfd/tXIeVd77jvWi9+2U/16y8HK7i/g1GrFIgbxRXXTV/yJvtD0W49R8beetQB9Mr8/jTzYuo0OrQuh3gLEMvPQvrn35iWicuxHz1yul85OxxKY+pfh+fXjzctMZoep/E1PGjueqq2WnvG5DeaWjdu8BViV6yJOt19c6X0I7t6BuabGlnwjnToHAO9xx8kQPthrCbP242Vy0b23dbax8N/ib03AlQOCv7bT/NUMerQnHqoI5Xg3iS1mBkLcTcdtttAPz85z9PuU/TNCKRNI0Mh8ioUaOYOdOctzljxgweeeQRAKqqZB5MY2Mjo0YZsxaam5v7XDJVVVUEg0E6OjpMrpjm5mbOPrv/H7ZOpxOnM7WZqt1uP+N3rnSo90WhOLlQx6TihKNJ7BfOfBjJfS/sAX+tPFfJPHAkfFdbdcgbK/1FQs1giRjiQ/L2rfql+XEtdrQb/oFt2hUZbEQw9lgFKa/VH4pwtN3L4VYPB1s9rD7QxlsH21KiM0YX53D7hZMp6j7AT7fbCUWMWJePPWXlbzdUsHDm4tT4m7AHfI3SDDrUDeixPwAL2NzSZNuaI/1ywh7wHZH3LH9y9o2a88eDZx9EPYDP3Ftl6qVQOhna9vcN2fY8B0uukaimSIf048kGexE4cqW5tO4BRxbxNoGAfC6uIuNzaT6cspirbGLq+bH7kKzrroGShB4Rndug9zD07gCHC3IGmSWrRyFwTB6rcLJsR7Qn9tgVI3tsnMoUTYXWdgg0gHW2sd/bSsGeA9MvMgkxWkct9u1/haV3ysDoqyHYDJ4jWJufhdACKJoz7D153NFGHN0bsVmtkFMmYqnvmOyzBROgY01fE3OsNoj0QOdaKJoPul+OR88u6RlTOCm2bx2U3kaBmJPQooHmAFue9MKxuqTA762DaK88R+4YKJgh9x8PkU7wtJiGtLwybI68029fLZgA/noItYLVIj2pALBD+RJoeUPu69kin8+s68D1INz/fggZMxy1kBfrxkdgzysw7xqYfA6EO6B3lwguueMl2rB0HrStA/9RKJw4cD+xklmghXjntFqTELO3uZfazgATy/OG9pq7t4DFIpFr+TVDeoiGbnNPs9HFbhwOBxTPkP0n0MbCsl7uT1hma333cf0GvefNI7x1SI6j3U29fPs/W/m/SzvlmMobDZYIvR2tJL4r9Xo5504q4OPnTsJi6V+EVb+PTw8umVHZrxBTkusc2mecO0p+70S6RGTNRszPHwcTl0GCEGOp24LFexRK5jJvdAEH2jv67tt+rNe8jYWTIdQGwUawzkk4P53ZqONVoTh1UMcrGb/+rP3J0Wi037/hFGEAVqxYwZ495tmje/fuZdw4meUyYcIEqqqqTBaoYDDIq6++2ieyLFq0CLvdblqmoaGB7du3DyjEKBQKhUKhyIJILEN+pBs89x6UYrerHHLMUVlEAlK8dJVLFlhis+S+7cuB+o1w8GXzuhd8HjISYehzSSQW1vY09vCO/32D6d98lst+8Rqf+McGfvjMbl7d25IiwgB885qZuOxWqtxw+3njTff1BDU+/FA3G2rTuF9suZA/CSrOgZqroOZqqLkm9ncVVF4AZcugeC5UXgilS8BZIu9Z914RcLLB6jAaXXuSYl40DebdZB7b8Zg4SgB89dk9V5y4+BJMjgkbhFDs/bIllOc6zA2zW/QC8gqSxJ1gl4hbAPlTzfcVzpaitx5rTu03x5yl4GuQorrVZbxv8cJ8NqLSmYarXJqX6xHwHDXGNU3uq5kFJePN66y+B/xtct1ihdHvgtxx8nl2bJbCett68NRKA+awT46DsA8C7eCth95D0HMAuvfJ8dG9D7zH5DGiIYgEwd8KvYfQ2teRHz0K6OKOyp8iIgyI06BtnXzWmlUEz8rzRbiMBKB9rYhCmiaP760TsalgClRdAsXzRCgtWSjHcPVVsn7ZWVA8X0SlyotkXwR5TS1vyvYNlVC3bFtvq3k8v3zkz+NvB45iOX/qEem/ZbqvCEoWiwPP1witb8nnP+lC+NDj4EzTL8LTBqv+Bv/6LLzxV2jaAx3boG2NfN/kVMW+i6LQuSN1/WSK5rJ4fCllbnOk1zPb+4/SHhB/q5yPNA2KBnAH6DpEw7IvRfxyfCRQ12GO2RhTEotN0jTZbzULC0rN31UNXX4au8x9ZbLhyS3mz+eF3R2srY/IcZY7joPH6nHEj/0Y3Y5SfvbuqQOKMIrTh4tm9O/uKs4dYh89e4Gcl6NhCKUXefrFliOTUxLFm3AAjmwE3zHmjTP/Xt1S12le31ku56doaOi/nRQKhUJxSpB9UOwJ5POf/zxvvfUW3//+99m/fz/33Xcff/zjH/n0pz8NiAPnzjvv5Pvf/z6PPfYY27dv55ZbbsHtdvP+978fgMLCQj72sY9x11138eKLL7Jp0yY++MEPMmfOHC655JK38+UpFAqFQnF6oOsSzQMjX8ALxIov6eLPorGiZN4UufQckX+oQWK9QLbvjSRXb04hTFworyMTwh65jAkx4UiU2+7d0O/szGQumVHJZTNj/5TrUT41u43zxpqfuzcQ5sN/Wsu6w1mKEYlomhQDy1dIkRegY4shSmVK/L321hnvZ5y574PEnPZAF9TGio6+JogOYZKOMyZYBNoGXi6ZcK9c2vP7hiLt5j4z9Xo5BUmxuvTslUt3DdiTZp5rGhTNk/v0qBTbB9ouz2G5zB0n60b8EPbKdUdRdq/nTCPeuN5zyHwsOsulQL74RvPyHXWw4Q/GbVepCJLF80UM6TkoBa2OzdCyChpfgPqn5LLlTRHWOrdD107o3g3de+SyfQM0vwbHnoWG56B1tSznbwI09IKZUDhD3FIgxXZvTJBx10DVRVAwVYp65efE9h1dBCZL7PzYuU32CxARKXesPKa7RvbfdDOxrU55bRXnSNEv7IG2tUM7xgD8MSeMJ+m8lV95egoxYMQLeutS78upEuHLYpNjvHW1CFVjl8Ftb8KcG9I/ZsgHu1+Af38bnv4BtO2BpldE6CucLZ+lv2lwEVezYC1fwuWTzbMpn9sxBCFG16ErFr2ZO97sZEwk4pfj4dgzsq83rJTbrWvlfAfUdpiFmdHFCb1SbbmQP5VJxZCfVPtef2Ro311H27zsbEiN9vj+Kjt68SK8oSjfvH8dDs28339sRSkVhfkp6ylOT2aOKqCqIP15qjBniDOyNc1wUQZaB142HSUzYNQM89ihNeA5zNwx5okYB1p66fEnNHXWNPndADJBQKFQKBSnLUMSYjweD08//TS///3v+dWvfmX6G06WLFnCY489xr/+9S9mz57N9773Pe6++24+8IEP9C3zpS99iTvvvJPbb7+dxYsXU19fz/PPP09+vvFD7Be/+AXvfOc7ueGGG1ixYgVut5snnngCq1VZPhUKhUKhOG6iASn8aJrRM2FEnidkuB7S9UiIi0Hxgno0LGKMHjXEh/Za2PWEeb051wBhY3b7YPQJMVKQemxTPQdbPQOuYtFg0bhivnrldH5103zpU6frFEUPYA+38serNc6fXGRaxxOMcPOf17I1eebkUCiYBo5CeQ87NmcuOgG4yoz301trvq9oDEww945h+78TZp4PoYgYd9QEO7LbzlBMiElwxATbzC6eOr2cwtyEYl3cDaNpqW6YOJomBfCcqpgYs1bWS3n+bnFaaJoU1uOvAcCWLwVeRf/k1IDFITPyE49Fp/R+YOwsqEzKzl/zV0MEgVgxfbmIOjnVEIrF29lyjX5DWizCz1kK7mopzueOhbzxct1ZYo78srkhpwo9fwpt1pnyuC2r5JxijQkiekQEmeIFZhHDYhWXS7xHSFyUi4ZFCNJT3XKD4iiG0rNk5nawAzo2ZnecxAnEhJjepIJ5QaUhGJ1uuGPxXIHW9IK0sxTKzpb9MNgFTS9Dz34oqIb33AOffA0mXtj/4zfshMe/BXWb5fMNdRkCY+f2wT9vi50rF5r38a11XSmulEHxHJbvSotj4DjKrp3m9yEuAPqb+r4nkp97dHFSI/H8SVgc+SysMu+Dqw9kKaTHeGZ7etfm5sYIT+9o4SuPbMPXbl4mhI0LphecvgKiIgVN0/p1xRS5jyMa53iEmJxRMCGpD9zRTeBtYUapjj3BraXrsK0+6XdE7lj5for/llAoFArFaUnW/xFu2rSJq666Cq/Xi8fjoaSkhNbWVtxuNxUVFXz2s58d1g285ppruOaaa/q9X9M0vvOd7/Cd73yn32VcLhe//vWv+fWvfz2s26ZQKBQKhQKz22SYG2Sb6Ctq56bvjRCJu3Kc0qy7Y4vEk7lifUo0C6z+jXkdVyEsuRUCdVJwixfq+iMakj8Aay6hSJRfvbQvZbGKfAfjS3OZVJHPOZPLOGdyGYWJxYFoGDo349Q7QLPgqljGH28p5vZ7N/LibmPmtDcY4VP/2MATd5xDad5xiFyaBYoXQvOrMhPecxjyJmS+fu4EmcWfbr1574dDrxm3D7wIF94JeKSgPth7moy9QESLaAjCPf3P5k4kEjQcUQlCTLTTPPO9Ti/nkrwER0x3LAI3pzrVDZOIZpG+Ea1vxWbLvxVzJiQ8Vu/h2GONMgqC8WKK0zwbVpEGi1WK1t27xaWUUy3nE5tb3uewB1Z8Bh69zVinuwnW/i+c912jr0xOJZQuFcFMj0ox3FUhQpuzNCYWJ/RW6k8gi4YBzcjqD4WIsgut7S3p92LLkX3N3xJzqyyQ6tqBl2Dj36FxG0w8Hy75rkSQRbziiolGgKicz1relEgsW076begPe568xtbVIiR2bZf4skzRo4azqzepYJ5fcfoWtG25ImQFO+TcFBdJEnEUyrHdtk7EjK5d8j2SPxWq5sCHH4eDr8CaP8LeZ0WES8TXCc/8CBa9BxZYoeI8ceCEPeKSicfL9cOyKdUU5eyk02fMln92/RY+fslZmX2/RoLGea1wemqfsTjxeD6Q12svirl3WiRezVsPFie17QM4YkDOjUVzWT76TV49amzf6oNDFWL6F++/+PAWvMEI11nMRXJrXqEcg9qQ5pgqTlEunl7BfWuOpowXu4cYTQaG8B9ol/NkNvuU1QVTL4NVfzXE8XAA6rbiKpzM9Ko8th0zYvy21HZx9qQyY32LXSYDeI6KM1T9blAoFIrTkqx/rXz+85/n2muvpb29nZycHN566y2OHDnCokWL+OlPfzoS26hQKBQKheJkJj6jdqRnUQ9U1NajhkBicco/s1anbJsn1ifE2w3bHjKvt/QTUDpbirGh7sHjY+JuGKsTLFYe2VCXUqj68zVR1t7s58FrO/jBOZ1cPb6XQnvsPYoEoGs3NL6A5qsHNPTiheAqw2mJ8rv3juXSqeborGNdfu741ybCkSHMnk/EngeFsdnWXTsNd1EmuEfH3qNeI9IozoxrwZ6wzXoUDr4l1/3NxueSKZpmOJ4ynRUajveHcZua3Grd5pnTDVoZLnvs/mCXzPzWtIFnjfc9mEWK345CEX1aV0OwU4om7RsMt1BibJ7qD5MdeROkGBXqTe+KGTMHqhea11l/P7SsMbtCXOVQukz2Bz0ivTI6NsVimJ6CY09LHNOxZ6D+aWh8SUSRjs0ibEQjsr8nNkyO+CmJ7pEIPFsOuMfJsaBpkDMZVv8Wfr0A7n037Hwc2g/A+j/D364FT6sIJY7iWGFPk8tgp4ijvibjeXRdXEHBThFL/M2yTckODmeJuG1ARMDEnliDEWiLiVQBCJrPX6dtj5g48XgyT23/y9hyoeJ8KFkg+1AkIEJ0w/Mi8NfMgRv/CZ/fDhd+A/JHmdfXo7D+IXjhF7J8XPDJ4DOyWy1cEo+ujPHszjbpeRQ/n/RHNAydW+Scay8A99j0y+k6dMUiJHPHxvbLmIgSd3YBga6DNHWb97u+HjGJOEtYPrnKNHSwxZOy7mA0dHjYXNvZ7/3eoIheNZpZiLHklaafnKE4rTl7UhlOW2o5a8jRZBBzrzrkeyPYmf36ZbOgarp57NBa8NYzb4y519Smo2mO5/hEF19DSr8mhUKhUJweZC3EbN68mbvuugur1YrVaiUQCDBmzBh+/OMf87WvfW0ktlGhUCgUCsXJTLxAONLFu3jz9nRF7bgbQtOkkKtZxMUB0oQbYOtT5h4ndjcsu02Wj2dz9+wfeBsS+sMEw1F+/eIe090LRtm4cHK+PL8elX/ku3dLz4DGF6UQ3LNPCmW2XDotk8Wx42uEhpU4Otfym4t7WFptjnlZdaCNnzxnfq4hkTde3AF6VAqEmWKxJRQwD5vvc+bBzHeYx7Y9Km4BPSqvLVvin3EwUyEmNZYMwOZpMt3usCVEmcT7RORUm50tA2GxxQr8uVIkaX5d3kfvMXmtrgoj2iQaMRr+povSU6RisYmbDcQVExdXXOVyGWyFi75hXqe3DTY/YLgA4rjKoOpicSTkT+7/M9YjclwH2qU437ZO+mW0b5DHjPWY0Vpew6r7JI6sYIYcxwAUwF/fCS98BzoOpz5+w2b48+XQVQ+li2Mz963SM8geiwtsWyt9OZpfF3Go8QW53rIKWtfINjW9nNqfKGcUFCWIq/4M43TisTue5F4cGuSVnt5CTE61Ef8zkBitaXLOq7xQRDRbjnxWnqNGz6FIs/Qu+sQLMOXy1Mc4tBY2/DMW3WmNif2Df0ZXzjaLGhsaNJo7OqH5Ddkf4+7PRALtMVEvFrVYNAcdeGprAw+sO4o/lODc8dbJd5PFZsTmJeKugcKZHOvp8431keKIiTFrytyUPjFvZeOKCXt4bs2bpqF8l415Y4pSFq3RkiYD5FeMbCyq4qQkx2FlxeSylPHjiibTNPnugFhfsCxxjYKJaeLJQj4WVpon02w40oGeHCtpL5CJB7qe+ltLoVAoFKcFWQsxdrtdcs2ByspKjh4VO2hhYWHfdYVCoVAoFGcQfUJMlvE62aBHB3YXxIUYi8OY2Zs3XopfgXbwNMHO58zrLLwZcmNF87yJUpwLtA3swog32Lbl8uAbG6jvCpruvuuqRWhVF0D1VVIELp4Hrkp57LBXXoejGEqXoJdfQMASi8lp3yAFYZsbR/5ofnPDdCrzzZFJf3jtIE9tHuS3VjQsxT5fo1ymo3hebDZ+R6q7ZSDiwpa/KXWm5vybzLebd0BvTBzJtPdOIvHPOLnw3B9p+sMQ6MURNL8H3c6EmeZxkcdlnn0+KFan9CGx5cSa+5aIo6biHHHM9G1Tl3zeVldfPyFFBqRzxTjL5L0O9cL4s2HcCvM66x+EutfN/WLiOAqhcAZUXQSjLpe/6iuh5urYcXoRlK+Q6Lm8ifK56hF5rO69Is4E2iAaJKo50fOnQudWWcZeBM/8N3QeSX3eRNr2w58ug7bDEkWmabF+QlYRU0COq2CnPK5mke2w58n229xybLe+JTOlTe/XRBEMdF3OI+l6nyQTd/71JIkC7kKw2k9vIcbqEMEUDDF2IDSLfJdUXgzlZ4uDxGKPuS1rRRjp2gQXfgzOuzM1ymj9Q1D/hlHc7T0w6FOeM6WMPKdx/teB5+pjYq6nFppeEuGua5dEiHXthtZV8h1jc0PZ2eiOYr748FY+fd9GvvzINt7121V4AmHZj7p3yWPlT5XtjQRS+wzlT6IuZHb6FLhs/boNbHYnS8ebZ/xn3Ccm7IGWVTyz1/x9eumMSr5+1YyUxZMdMeRXnt77rKJfLpqe2ifmuKLJQMQUSD3XZoLVAVMvBxJiBEM+qN/G4lLz8dDmCXK4LU3/p7grxnMkFmWpUCgUitOJrIWYBQsWsH79egAuvPBCvvWtb/HPf/6TO++8kzlzssgmVigUCoVCcXqQ2CNmpIgXtS2O9L084jOEE2fFWuySxx8NwtE1kp3fd58Nzv6McdvqMhwfXTv6/+c3Io4Yf28rv3nDPFty6fgSVkyOCTvx3ha5Y6FsqRR/S5dCxblSsM+pAk3DqgfQ2tfF3BSVUHkRlCygvGoyv/vQUuxWc0+ALz6ylbqDa0RAiUakQNy9V2ZoH3tWZtM3vSoz6JtfTx+1ZnUZ8Vk9e9O/znTY8/qfqTnuHChM6n2w9xW5DLSY3/tMiEflRPyG+DUQ8Wgye74x1pFa8PS5YwUWk1tlCLFhthyouBBGXSFF/IKp5ngfSHBwKTdMVqRzxVjs4h4BcXMku2JCfnjp19C6TiLn+sPqkD+LTQrQFqs4ZZwl4K4Wd0nVJXKc5k8Rp1zBdChZgF52Nl3aOLSu7VLMdpbBpqehbl3q81TMSj0eeo7BX66E3g6JftKsso8EWuQ8UTBdHDMV54uLp2SJ9HUqmieXcSdb+wZxZSRSNFdmUkeD0LZ+4KbwkYAh0vYmnR/yYmKB5TgLmSc78XO9ty5VgOgPTRO3W/E8GHUZlC0Tp5WzRPalaBCmLobrfmReLxKE1/8IgU5Al3PyILGQTps1pcD87EGbfHc4CmX/8zeJg7N9o7izdF1eV8X54Czhme2NPLzBEJp2NXTz30/slGMqEojt96Vw+HE48CDUPwkNK6H5tT6BqjZYbtqG/twwcZZPqTbdXn0gA4dW2Autq2nt8bOuwfx9d8XsKpZOKOFSU1Sbznx70v6fX64cMWcoF8+owGYx9puaohzcDusAa2SAqyI2ecaTXYRrnLI5UJUUd3poPWPcPsrzzELm+sNpJv64KmPiewh8GYjFCoVCoTilyFqI+f73v8+oUfJP7Pe+9z1KS0u57bbbaG5u5o9//OOwb6BCoVAoFIqTnBMRTdbnhumnqJ3oiEkkbyJEA3Bsl3l83AooHG0ey58iBd9gJ3RsTF+gC3vA38IDm1pp6DUXjT5/6dQ+13AKFps0EXcUJWxziOLoXtl2R6H0e0hYf+HYYr5z3SzTw3hDGv9c3yIz4489LQJM957YjP14jxxHrDdGVASZdK6S/EkxB1B75nFGkDBT86i52GuxwNz3mZfd/jhYc+V99Gc5s9RiFbcBZBZPli6arN0sxLToBbhyYveHOmW7rK7sG6UnbmN/jd5h4J5GioFJ64qJFYUDLTDubJj/QfM6bUfgrXull0bX7uxmEuu6FMzjgqGjSBqdF8+FgimQUxM7XveLY8VVDq2t8NZvzY9TPB4+thJuexM+9jyUJ83m97XD/e8HawFUni/ns2hYjidfPXRul3ipplekIB7/a3lDBCZHsWxrxxZzvxGLVUQci13OlfH+H+mIx5LZC6AzqU9KQcWZ0fTcVWm4WjJ13SWiWaRYWzhDhNhRV8g5FaB8FMy+2rz8sZ2w6znjfc2gV0xyPNlbB9vpCOVC+bnynEVzRCh0lshnWbJIetpYbHR6g3zr39tTHvOB9bU8s/mQ3MifBv+5Hf7+cbjvM/C3W+HRL8PKH8GmP4GnjroOs/NxTOHA+8VZE0tNt4+0+zjWMYCQHvbGnDw+nj/iIprwlet2WDlvqhzzP3z3HBaMLQLgxrFtFEeTemuUT1Q9Ys5QRhXm8PWrZ+CyW8hz2vj2tTP7/x2WKRab8X0zFFdMThVMSI4n24gWDbFolHnbNqbrE6Npxm+tbHp/KRQKheKUYID/HtOzePHivuvl5eU8/fTTw7pBCoVCoVAoTjFOhBAzWFE7GnPEJBdjbLny15JUcJx0Yepj2NziWmldLdFeXTugaLZ5GU8teu8h/rFriWl4+TgXywv3Q/sRKJw5+HuhR9Ha1xs9J0qXpi3qv3/pWNYf7uCxTfV9Y08esPOlFVE0PSyv11kqs/MdxWB1y+PoUZkZ72+S/hNly80ikNUlRbzeQzJDOh6bMxiuShEuwj4pkLsTxKz574fXf2rc9rZCSx2UFEt8TrwPT6Y4S6SoHGg3P08y0bARlWZyxBwyLVavl1Poju0fJ0IkGUw8VPRP3BXTvVv2z5xqET969omQoOtw1Y+hfj207DbW2/k8VM+A8VERNormxGLNYgVkXRf3VKBNBL5Qt4gvesgQXq1Oadgc35dCXRDsQgsHgJhzzVIBj99g3marA67/G1TPl9sF1fCRp+G+G8yumZbd8PhtcMM/pKDes19eY+LMa80qQkEcPSLnuFBYjuNgp8RSuSqN3je2XHHatK2F3sNyO94kPhF/rGeTowQ6k2ZbnykRT5pF9inPEZlxnun5rz8sVjnvO0qgYxMsfCccegs8CSLPmvugZpb04PHWiQNqAPHg/GnluOwW/CERvCNRnZW7mrhh8Rg5bw1w7vp/T+2itTe9C/ErL+nMH53PqDW/g+1PGXeEfNByQP72vQFHNlAX+bJp3dE53SL4W+ykY+aoAgpz7HT5Qn1jq3ds4z0rlprdggD+FlrqN9Pl9YM1hycOuQFjmy+cVoHLLs6G0jwnj92+grCvE+uaH0OikcuRA4VVyhFzBvORFRO4aelYHFYLFstxijBxckbJ7ydfgzhes8Fih2lXwOq/09dlKeiB+u0srljAs/sMQTOtIwbAPUYm2YR6xQHtKk+/nEKhUChOOU7z6U4KhUKhUChGnBPiiInHPPVTfOqLJksTqRPUobfTPDbxgvSP4yyRYiaISNF7UF6f9xi0b4GunezpymF/hzn64o4FXomc8dbL7PWB4ix0XeJkgm3oWNFLlvT73mmaxkdXTDCN1XaF2RZZJhFKoy6TmdC542RWdFzM0SwyQ95ZZvSWSO4Zkz85oS9OhrPCNQ3c44z3J5HSSVCzyDy291W5DLRl1rsikfhnPZgjJu6GsTrNBcKkvh11ejkFOS7zYw4lliwTwh5xOmkWI1JLkR15E+R4DvXKcegojrkYAvL5OXLh+r+mOppe/wt0t8Rm26+B+qckdunYM0Z0X+d2OaZDvfI5JbrfIgERe3oPyV+gPda3xYpPK0d3T4WHboFAUgTaFT8wRJg47hL40ONQmSTo7npCREtNE8dN5QWxWLJz5ZiuuQpGXWr8VV0shTg9IiJMNChia+c28+PmVEq/IoDOHfIXf216VPqZxPvo2HKgJymaLL8cLGeAEAOGuOtrGL4+DDlVEiuXWwnnfNR8X9ALq+8VIUOPigg00OY5bJw/1Vx8/d0rB/CHBt7W1/a2mCLJkukKaPzmiR3or/+232UA2Psql9X+kr5CMjAmLywCYD9YLBrLJpjPqav3t0DzK30uyoC/l8dee513/m4NS+4Jcsk/LVzy9wCrD5qdAVckOYIAbNEutOZ95sGysXKePRMEREW/uOzW4RNhINbbT5PfTZnEoyZTMQ8qp5jHjmxmkbntEvuaPXR604imFruIMaBcMQqFQnGakbUQ09TUxIc+9CGqq6ux2WxYrVbTn0KhUCgUijOIaEiKgzByBbywR4qjmsXs6jBtRzyaLGlWrK5DU1KvkJxiqJrb//O5q2V2M0ghs2Gl9GXo2QPoPFlvdnZU52ucNW2czL635Yo7o+XN/sWNzq1S/NMsdFqniIAyALNrChhXas7mf3J70+CRWpoFSpfE4o9CElOWGCdmdUlvCpA+M5mSO04eO9gpf4nMSXIJ7HkGLLFtj0dMZUpcJAn1DNxjJl0sGaTELtXpZRS4nbJP9LlVRkiIiffmcRSf/jFPI4XFJtFPIDODI36jsb035hCrmCHOmEQC3fDYN6B2j9kJEw3LucpiE1GjYDqUnSURYaMug5qrofoqEUOK50vUVN5EiQysvBC96gq8VGF94CZo2GJ+ztnvgcUfS/86nHnwvnvBVWQef+l/YO9zct2WK6/NUZTeJWGxQ+kyaRoPchx762WmtK/RvGzBVON96z0o565YM3Q8tVJcLJoVEwOSRM78ijOnoO0sifVhCBsuoeHAlisOx3GLYPI55vuObIBjO4CoiHyDCEDXzasx3T7U6uHuF/b1szR4AmG++qhZnMt32rhgmiHoFNDLpzp+jqYPLj5dE3yOL9ge6rs9ugARkAYQ7pdPMseTra7XINRLV+MWfvroc5z9o1f5/NPdbG7qv2jusFm4ME0TdoKdkCzEVMbcCiqaTDGcWB3giO3LQzk/uCphYlI82aG3mFUcxJlUMtt0tDP9Y8TjyfzNMmlAoVAoFKcFWf9neMstt7Bx40a++c1v8vDDD/Poo4+a/hQKhUKhUJxBxF0OFrvEs4wE8RgpR1H/Re24Iya5GBPxQ33SrPEJ5w++rfmTjH+CNU16uLgq0HMn89RRc9TUVfPGYymeK0XS8nOkwBcNiQul97BZROjaJTODNQ29eCFBbWARRp5e45q55mmUT21tQM+kybTFJk2lrU6Z1elNmimdF3fFtBrv82BYHRLrA6mumFnvMn9GIQ8ci4k83iyFGKsD7DFxZSBXTKgfIaa73nSzTi+nMMcuwk00JPFPg4hgQ8bfJJeuyoGXUwxM7liJ3tMj4v7IiRWmfccMUXHBh2DO9eb1Qh547nuw7kkoOzfmKrkIKi+Ufh5lZ4kTxVUu+0C8L4rFKueZ3DEixhbNAneN7IfBXs468FMsdWvNz1U6Ga79ZWr0UiIlE+D6vySdv3T4103w9BfBm7B/6zq0H4Jjm6BxGzTthJa9Em1TNEe2yeqS9UPd0LU9taCfPznWc8oiom/jSyI+9gk6E6FxK0TC5vWKRp05QgwYrpjk8+LxYsuR/eesD4Ar6Ryz+WkRl6NB8NamXz/GFbOr+nqjxLnn9YNsrze7sXRd58VdTVz7v29Q32nu6/KVq6bzy/ctoLrABuj82H4Po7WkvmDLPwMffAQu+mZKROZnbY9zq/VJAMZUxr6HunaQtocaqUJMfQ+81DyWax6w8L/rorT50q5m4rKZleQ50ySoexqkF1QiVbFJEyqaTDHc5MRcWUPpE2OxwfRrgITvhaAHR+NO5lWaj531h1rSP4Yt19iG3gPpl1EoFArFKUfWPWLeeOMNXn/9debPnz8Cm6NQKBQKheKUIhKrqliH2PA8E/pipAbotRHtJ5os4oX6pMbVYxZm9rxFs8X9Yc2Rf6p7DrDjWA+HOs3/RF8zr9q4YXVA6VnSJ8DXIMXjzm0i5Fjdxj/0RXPBkRq90h9Xz6nmNy8b/4jXd/rYVNvJwrEZ9B+x2KUw27lDelG4RxsFYVuOxF94jojroHx5ZhuUN0GKl75jEJklrxukx8TEC+DAS8aye16Cqg9LITjslVnomeKsMBq25/TzfoVjMXCJ/WEAus2zWOv0Mmbl2M37U2LxPOyRmd451Wn79WRMNGQ0RO9vmxWZUzRXGtj7myFntIgmkYC4QXJi8THX/AJa90HDZvO6m++Dnf+BsilQNg2KxoC3DbqPiVAX6AFnvrhVXIWQWw7jzhaxNj8mouk6dNVifeRWSj1Js/Fzy+HGf8ljDMaki+CS78DKbxljegTW/hG2PgDzPwjtB6FurWxjMjYXXPFDWPwROSb0iBzPtlzpnVM43by8u0ZElbZ1sk/a88UhF+8pU7vGvHxeGeQUnnlCTPdeCLTIPjWcrgr3WCg8BgvfBav+Zow37oaGPTBmkRRXc8f1K+JZLRo/fs9crv7VGwQjRq+YLz28lX9/ZgU2i8bm2k5++vwe3tyfus8sm1DCTUvGYrFo/PxyO88++iRXWNeZltmgT6cu9x28Y9ISmHyJiIYPf4zESLKv2++jUS9h9OivQ2cLBLtiPcJqSGZqRT4luQ7aPcYEhI8+mJnQZdFg2YRSvn3trNQ7oxERJhNdnZoFKqbI+5cullShOB5yRkmMZaB9aOeHinnSs+zYTmPs8EYWVS1gbcK8lPWHmoE0+zxIrzRfY0Z9pRQKhUJxapD1f5ljxozJbAamQqFQKBSK058T0h8mgxipeDRZ8j+pDVvBn9QbpWJM5s+dWNyPeHlyn7lgNro4h3mjk3qAWKzSt6X3gPzzHOqRwhWxWcyFM2WmfyhEpswYlc/E8lwOtnj6xp7c0pCZEAPS16Vnv8SmeeuMSDKA/CngPWq4YjJpYO8oMpqGe46IuyDOnOvNQsyBl+C8j4MWlOJd/uTMthkkJq73oDhMopH0TqZ00WRBL/jMs8b7HDGBmEATf53BLilkx0UyzxFxDViHWNjzt0jx3p5nFL0VQ8eeJ/tM917o3iHinLcWfPUixIAIIR99Fp79Cmz4q3n9YK+4S45tyuz5NvxFLstnQG4ZNG0HX0dqjIC7DG5+AsqzaOR89mflnLT9YfO4vwve+s3A64b98OSdIiCd/2UINIOrSo5ni11cPMn7m7NUotYCreImiguM0bAUtRMpnySXZ5IQY8s1zmO+enEKDReaBsXzYHozbHnCHAO39TmonCiuvH4EjThTKvP59IWT+cULRnzkzoZu3n/PWxxu89LSE0i7Xp7Txg/fM1f6ZoR6OKuomUXO+yFBx2jX8/h04NM0PtlCS89LfPzSsyVmL9ADT3zO9Hjfd/yJ3J73iYuye7f85YxKcalaLBrLJ5by1LaBXQTLJ5Zy89njuXhGBdYEIarfPh+hLmhKitAsGQN2l7hhBnKkKRRDweqSCRvBDoknyx03+DqJOCtg0gqzEHPwTZad+35+hzEhZcsxL6FIFLs1jePbWWJsQ++hVMFdoVAoFKccWUeT3X333XzlK1/h8OHDI7A5CoVCoVAoTilGWoiJhozG9wMJMZF+HDGHXjXfzq8Apz21t0kG6CEPT+6NmsaunjsKLV0BSNOkeFx5gcQilSwU8aNojsSeZYnEk1Wbxp7e1kA0muHkGIvVEEB69ppnFcddMfH7MiV3vFx6j5hjaqZfI7P340TDcDRW9M26T0yxbF80LIXnZPSoOFnALJq1p8Z41OtlFLjshrBnzZVm7s2vGSKMZpV9o+UNEa2GQjxP3qXcMMNG/hQpmkcChvDmazRHctlzJCLsPX8CR176x8mGll1w+HXwdaTeFxdhKmK9WPzNcOwZ6SfVsgo6tkosYTQp+kvT4F2/h/O+OPSZza/9RASZgllyfER8IiZ27ki/vC1XCoiJLq9QN7QeNi9XHhMhziQhBkYungzE/VcyD+ZdZx5v3AMNe2Oupv2DPsxtF0xiWqXZdbXucEe/IsycmkLu/8RZTCiLCXPeetj3GvZo0LTcF0K30YhEif3kDR9NB1+RCMlFt7Bm8udNy+bjg8c/Ca7Rso+EveA5nPb5z0qKJ0tk3pginrvzPP71ibO4YnYVdqsFi0Xr++uXYAc0JTnSqufJpXIJKEaK44ons8KMa80TSCIBlmA+5v1h2FnbTzwZGL8ZPYcH7SulUCgUipOfjISY4uJiSkpKKCkp4cYbb+SVV15h0qRJ5Ofn943H/xQKhUKhUJxB9AkxIxRNFu9bYsvt36EQjUhBC1Jz4g+vNt8eF2uemkHxK5mt9R7qes2OjGuTxJG0WF0y47l4ntFsewgk94lp7Paz4WiaInF/uMfFesX4UouO+bF4F3+LIVQM+ng1InyFfUZPFJCeCFOvMC+75wV5/GBX9k1n4/1o0ok4YY+IQBabuYDcbi7Yten5+HBR4NAN4cbfJAV0TZPXUnk+VJwnwk/YI2JMXATMFD0qjwmqP8xwolnk+IFYxF2PHPPpmijPeS988jUYt2JENkV3l4oIUxnrTRHsgrb1IrpE/BJv5zkikYRta8yiJ4DVDhd9A+5YL+6D/rDYRRhMx6Z74bHPgaNcRBbPITk+Mu3z5G2CzibzWFyIOdN6beTUDP3clAm542DuuyA3SZzY9gL4mkUU86cRmRNw2Cz86L1zGUinABhV6OIX75vHvz+9gtk1CU5Nbx3setG07Ja8c3gluqDvdiCi8dt1EWjfgL91G1+oO5dHI+eYn6BhJ7zyLSiYJre798pkiSSWT0wvxFw9dxQPfOIsplVlEOWXiB6VY6o56Xt79CK5PNP2WcWJIyf2uyvQmnZfH5TiaTB6nmko98gqJhUn9Yk5MEC/KFeV/AaOhsS9rFAoFIpTmoyiye6+++4R3gyFQqFQKBSnJH09YkZoFnUwlnvv7H+GbV9/GM1invUdDkD9ZvOyU6+WS1+DFN3smc+cf3JnB2AITuNK3cyqHqFm72mYWpnP1Mo89jYZxcIntxxjyfgMJ8LEXTFpe8W4Y71ijkpxrWzZ4I+nWcTl07NfIjMS+6HMuR52Pm7cProagp8GO1IwtmcR55RTAz0HwNckxW7TZ5wmlgxSHDG1ejkAhTaPtD6w50lfCIDSpeCqMBYuPwda3xIRpuVNuZ3pfhJol2KJxTFwTyNF9jhLoWCq7J/BLohG+491Kp0EH3kauuqgZY/0j2ndA73N4C6FghooqIacYolh8neJ86VxKxx6HYKpApzuLOBYznQqbvo19spYPEzYB21rRRRylUuGf7hXzi2ew7I/dGwWR1wyRWPhvX+GZZ+CN34hfWGq5sKYZTBmCRTFeofousStPfUFs6iz7zkRPc9+H9jyJVqraydUnJP6XMnUJwtEGpSOj51Dz7BeG1aHRAj5m0SwGO7oH02D0oUw/zp48y/GeNNe+RtXJufQxHNQGuaPKeKjKybwf28cSrlvbImb9y0Zw0dXTCDHkSTeBTvh2GboMouW8971X9y0pZR/rTUKwP/aqfHJhTpPbjxMfaeFb3MLS7Q9jLEkzNZf/SeYfAXk5ss5smc/FM4wPfak8lxmjCpgV4MRC/rZi6dw58VTBna99EfPAWg7AP6k43LUPKBXOWIUI4ctF+wFIpj6GiUCMhtcFTDlXDi60Rg7/AYXjL+ZAx3G78kNh9v4WH+PoWkSm9i5TaJac8erKD6FQqE4hclIiLn55ptHejsUCoVCoVCciox0NJk/VgBylvW/TFyISS7G1K6Vvgp9aDD5cvAdkH+oew8Ys+wHIRoK8tR+c4Hrmv5iyUaQa+ZW8/OVRnzYU9sa+cY1M9Nni6djwF4xk6X3hr9ZineOosEfL3e8vI+BVrOwNeVSaX7uT+jTcmgjTF0oBeOCLIQYR6EUQ8IeKZYmFt5D/QgxHYdNN2t1KXIWWLohghShoyHZb53l5nWtLihfIbFlwQ7o2ChijJbBexx3BsWbyCuGl4Jpsh9EfCI6WJ1QPF/cI+koHC1/ky/O/DkiYeknc3QVhINQMR2q5hLOHcX6Z57hqpJYTEw0LCJMxC+xeCWLZDvix42zVBwx3nrZf+MugmTGLIWb/tX/9mgaLP4I5FXAwx81n9O2PQRTLoKiGinS+Y7JuS1RFE1H7Rrz7ZKx4MiR9/NM3G/do2NCTK18TsP9HtgLYMGHYMt/oLfNGN/2MlRMkP0m2DGoePvlK6djsWi8ub+Vinwn508t54JpFYyPR5Clw1sPO583jxVPgAnn85nSAI9sqCcYEVEuGIEfrC/m1f2dAPTg5s7Q7Tzk/B6WeHMZPQL//gx85AkI7TIKwzajqKxpGne/bz4/enY3Pf4QHz93IpfPGmJUY9grPbyS+8PkFEF+GXh6wXKGxekpTiw51TEh5lj2QoxmgWlXwau/l8lBAHqUq507+BOL+xZbXx9CD/agOfpxi7nHQPceOR58DdI/T6FQKBSnJFn3iHn66ad57rnnUsaff/55nnnmmWHZKIVCoVAoFKcIIynERPzyzy+kFstNy8Vy75PjSQ6+Yr49ah64S4xeKd46Y/sHYdO+nRzzmmeKJ/dsORFcnRRP1tob4KN/XUeXL8PIDFOvmH3m3i62XKNfQneGvWJsOUYEV2K/AJsTZr7DvOye56UoEeo1PtdM6S+eLBybIW1PKl50mmM+4kJMvhYThsJeuXSPTl90tdihdHGsQNqV+fuh+sOMPMXzY7F4TmkY3pvqEDgurDZxpKz4HJz/Rcn4Lx5n3k/0KLSvl/3Y6oTSZalikKsciubK9e69x9+DZPrV8OF/gzPJhff8d8FSJMeh5wh07zIf18lEI9C00zxWNUsuz9SCdk6VfI4Rf/Z9rDKleA4seLd5rHk/1O2QyQQZxGXarRa+dtUMnvrsufzlI0u5ZcWEgUUYPQqde+DQBvP4opvBYqGmKIcbl5oLy0/s6KI7YOzrG/RpNM//jHn9rmPw5q9EbNSjIsYnMa0qnz/fsoSHPnX20EUYgM7tIv60JR0/NfNBj333K0eMYiSJix6BFuP3ZjYUTIRxi0xDMzvM/QubvRp1DYf7fwyL1Yi2TXO8KRQKheLUIWsh5itf+QqRSGqTsGg0yle+8pVh2SiFQqFQKBSnAHoU4s1/R6JHTNwN4yjqvz8MGI6Y5EidZCFm0oWxxytOKCAdzGhT/rPJXNifWJ7L9Gxz7oeBSeV5zK4xF2Jf39fKe363iqNt3swexD0u1tvFm9pjo69XTJO4YjIhd7xcemvNzcnnXG9ermk7eGLb6M2y2BkvhPibzTnt/UWTddebbtbq5eQ5rdgi3bJ+fJ+JC0/psLqMQnrv/sF754R65D3VLAMLh4rjQ7NAyRLIHS3nn4bnRqa3x0B0bJHzk2YVEcbWz/kvd6whfMbXOR7GngVX/sg81tsIa+8XsTLshd4jciz2R7gb2pL6DFTNlsuRcjae7GgWyJ0g14fQPywjrA5YfCvkJZ0btr4IvUfFyeRrSr/uUPE3we6V5vOyxQbzP9B38/YLJuOw9V8SuGaKTtW574CaxeY71t8L/lhNwHMEIoHh3HLB1yivQbNAS5LgOuYsYyKF6hGjGEni8WS6nr4v2WA4y2DKeaYhV9MGZue0mcZW7x/kd1HueDkWgp3gb81+OxQKhUJxUpC1ELNv3z5mzpyZMj59+nT27x+hH64KhUKhUChOPuJFEM3SfzTQ8RCINz0fODu/rwCUOCs20APHNpqXm3iBcT1eHPUcGbQBq6frGI/uNo9dM7f6hMeSxfnudbNSCmf7m3t5x2/e4HtP7uQfqw/z6t4WdhzrYuex7r4/bzBWjEucWZlcdLTlSk8WkOinTHCVSyRZNGye9T9uBeQnuYYOrpNLn1koGRR7gTyHHpXiXDQCXbsMZ02yI6arwXSzVq+gwGWV9cO9UrhzFKaul4y7WsQaXYf2TeaCZjK+WIHGWS7vsWLksDpg1JUiKPqb4djTEtdyIujeJfu5pkkcmaNw4OULpst+pEclyiyT7dSjso+nY95NMPlS89jWB6GtTcQY71E5dvtbv+sI9LSbxypj/9udqUIMyDnRYpNzir95ZJ6jYAos+6B5rKsRDm2WuL3OrUNrCN4fPYdg50rz2PRrJOYuRlWhiw8sG0s67BaNLy1H9tlLv2SeEKFHYOV3wF4Ym9QwzM60aFji9gDsldCc9CU8/vyE7/4zeL9VnBjikahDccxpFonFdZonjHysaJPp9j82h9ADSefmRKxOyB0n13v2Zb8dCoVCoTgpyFqIKSws5ODB1Nmj+/fvJzd3AGu0QqFQKBSK04u+WLIRcMPoekJ/mEHcBdE00WT1G8zNqC12aYIdx1Uhxf1oeNAC0uPrdtMTMn4yaRpcv2gAJ8UIs2hcCfd/4izK8swOoA5viD+9cYhv/nsHN/95LVf/6g2u+tXrfX/zv7uSp7fFisCJMyuT//EvmCb3BdoyL27HXTGehPfSYoXZSVE8u58BLDJzP1PHTZy4QNR7EJpfFRFJ18V1YEv4DerrgKDHtGqtXk6BMyacxffbgdwwiRTNlkJf2DOwOJXYH0Yx8rjKYNQV0qjecwTa1svnM1As13HijjaixWNhiub1/1nruuwvICeM4gWGGNO+of+YskgAunaLy+fY09D0CnRsjjkO/MbjXfvL1IiyF38M9nJAk3NaTz9xekdfN9+22KE0diycyc4Ciz2hyDlCkws1Cyy+DUrHm8e3vwI9sajMTAXwwQh7pM9Rd5ILa9EtKYvedsEkXPbUssCHlo9n7LhYHzVbEBZ9wLzA0fVQt0uuew4PLFRng65DxyZ5P2xu6OoEEo5riw2qF/bfH06hGG7i8aiB1qG5v/LGwoSlpqFLwy+TuF9va9FYt3eQ2LG8SfIdEGgd3KWrUCgUipOSrIWY6667jjvvvJMDB4wvif3793PXXXdx3XXXDevGKRQKhUKhOImJ+ORysNmoHZuh+Q2jMJkJoU6ZGWyxD9rAOG00We1a8zKj5oE9STDq65Wyv9+eJbq/lX9sMkd+XTitgjEl7kFewMiycGwxj396RVbxaMFIlC8+tIWmbr8Urtyx3gAprhi38d507eh/Zn0i7jGx2eS95siM5HiyzqPQFYvj8GbpiokXQkLdsi9ZXVC6BIrnmZdrM7+eqK5xTC+jwKnLPqtHpJARF3YGw2KXQjpIQbwnTaHE12gURVxKiDlhFM2CwulgdYvTqecANL0Ya2qcdL7Ro7J/+hqkZ0v7BmhZDR1bofewCI8DuRG8deRHY5FehTP6b9rsb4Xm16DxJYkjAynAFy+UdeLuqp79Ijb7W8SB0bkNGl+Qmc7xgnaoBzy1so1Nr8ptgMIauOz/mZ+3pwE2Pw3usfIaO7cZLq04oW6oW20eq5gKxI7x/iLWzhTyJhoi9EgVOXMq4bzPmsd8XbBvvYi5nqPHH2EHsk9v/495rHgCTDg/ZdGKfBcfOmucaSzfZeOOiybLPls4QwZnrIC8pPPbKz8FHHLsJPYJGyq6Lr8ZfI2x42Y+HHrFvEzlNOnlFD9OzmQBUXFisLklJlfXh+a+dJbCtAtNQ3k9h7is0CzK/9/qFvMkopTtyDEmkYyUYKxQKBSKESVrIeYnP/kJubm5TJ8+nQkTJjBhwgRmzJhBaWkpP/3pT0diGxUKhUKhUJyM9DliBhBiQr1SSAx2QPPrUuDKhD43TFn6ZuqJ9PWpSSjG1K4xL5PohomTUy2xWnpEZtOnKcKu272L3W3m5//w8nEpy70djC528/BtZ3PR9EGi2xLwBCP84OnYDOa8iXLpb0rtsZE3Wf7hD/syawxrsRnFgcRi3Kh5UDbVvOyBt+TSdyw794I9T/YHkJnrlRdIk+1k2s2RHQ2UEMJGoSMq+581B5wV2c2idpWJUwhkxnp3gtvAUyuN20HeAxWTc+KwucURlTtWHG4Wu+yz3XtFCGl+Xf4anof6p6DpZTnWu/dIn6JAq4hrndugZZU4UVreNMTZYJc4VBpfQuvcDICeO94QKhMJ9ULbOmhdbQi7nqPQHdsfNU1cNPHjrmsXtL4V+1sjhXM9KsW+0iUw6lIoXSp9m+x5cp5rfcsQmBZ+GCaaC3tsfgC8UREDe/bJ9sSP7bBX1m9OOp6rF6heG3GsrhNT5JxzC4xN6rmy4wXwtIqg2Lnl+Nwl0Qi0boej28zji24GS/p//2+7YDJjEyYYfPPqmRTnxiY35E+W/dbugqVJ4npPM2x5Qq73HsxMuB+Izm3m6L+2o/DW78zL1Cw2JmBoVvn+UShGmvhkkCHFk2kw/kIoMP9e+3z5BtPtlQejHD7Wj2MyTl7s+8fXaIjzCoVCoThlGFI02apVq3jqqae4/fbbueuuu3jxxRd56aWXKCoqGoFNVCgUCoVCcVKSiRAT7wWiaSJ0tK6W4uRgxDP6B+sPA0ZMRLyIGI1C7TrzMmPMkRB921S8UIq5YQ+0bzQLA74m/r6hy7TK+BIn5005eRqx5zlt/Onmxdz7sWXccdFkrp1XzdzRhRS4bFgtGlaLlqJjPb75GGsPtUtxNy5kJIstFisUxPpG9OyT4vZgxOPJ/I3G8pqW6orZ/axcRvzZzzovXQqjLoPiuf33JWo3v5ZaXfahAnsYgq0ixGQaS5ZIwVTp9wFSyO/aJYXHjs2xiLQxMntbcWLJnyL7mR4VAaNkoQismibxd8FO4xyhWUXoyB0DhTOhZIEUmV2VIjzqukT1de0SB0rza7H93wOaBa+lEgpmpW6Dv1Xi8nyN8rx54w0XQfduEX0gJsbMkue2Fxh/jkI5FsuWQ8W5ct3qEvdE4XQoP0eWi/jlHBr2yWNd9yuwJ7nzXv9DLHrQLv1s2tbI9reuFsdQe5ITbfSyzM7lZwp5k+TS15gqUA8XFitc8RPzJINwALa/Dt5aKa52bR/64/sbRJSLJsVzzv9Av6uU5Dp4/NMr+MX75vH4p1dww5Ikx1fhTOmTMWEZjErqF7vxfvB0yXHmrR36dnftFGEUxIVozYdHPm4WpTQNFnxI9YdRnHj64snajHNmNrhrYPK5pqHprSspcRrHqY7GX94cZPKLPQ9yRsl11StGoVAoTjmGNH1E0zQuu+wyLrvsMgA6OzuHc5sUCoVCoVCcCkQzKN7F46eK5srsc2+9xPWEvVJgTPu4IYkmg8H7w0BCj5jY7N3WvRAwCyhphRiQ5sMli6HlDRF/evaK+NO9h+a2Fp49YFYxPrhsNBbLIA6dE4ymaZwzpYxzppSlvb+tN8CFP32Fbr9RzPrWv7fz5B3nYMubJAVHb52IDIkuEXe1uFsCbdC9U2YnD4Q9XxwrcZdB/POd/R54+X+M5bxt0FIP5TUi1DlLMn+xFitgHXiZjiOmm7VR2YcKbAGIhKSIMdT4sIIpsg2dO8wz5vMmSqFyMPeWYvix5UrMnLdOhIaypVLwivjFWWexi/hmzTE3G09H2CcOMX+z7Mcg54OcUejWEnosz6d+xtGIOBj0qOz/RXNkHwMpFvcelH4XthwjZjF/kvxlisUOZWeJWycuqpSvgKKxcMFXYeU3jWWbd8HB7TBxhoiEndvkdXkOQVc9+JJmUNcshlCs8KeK2oZA7WuU74OShSPzPNULYc57YetDxti+N6B8PIyxgWYTMa0ojfA3GF37YO+b5rE574W8gSc2lOQ6eNeCfkTquKMr2AnLPwSPfd2IUIqEYONjcO4tIurnjsv+XOipNWIfi+fJMfzE51KiJpn/TqhZYsRDqf4wihNF/Bwe7JD9L29Cdus7imHaRbDxkb4hzd/B16fUctd2w2n94FYvX7jaT2HuAOfj/CmyDb5jEJ4uE4oUCoVCcUqQtSPmRz/6EQ888EDf7RtuuIHS0lJqamrYsmXLsG6cQqFQKBSKk5i+WdT99BUIdvXNJCenWgpa8Xinnn395+D7W2Rmuj1/8J4Fup7asDc5lix/FBRUs7ephy88uJmvP7aN5p6E2YyOQqPPSPde6Wfjb+G+HRbCUaOY5LLpXL8ky3+8TwJK85x84VJzPNjuxh7uW3tURBBHsRTUeg+lrlw0Wwpq3mOZ9S3IGy+XniNGka50khR7E9m/Si59DcPfXL3TPCM77ogptPtjLoNRMUFniORNFEdOnILpUixVIszbR8FUef/9TVIoBvmsc8dIUd1ROLgIA3K+yRsvYk71FfJXuliKwv3FH/XsFWHZliOOnLgIAyLO5VTJsdC6NjNnWX9YnVB+tuHga1sjj3vWbVA527zsa78A2xjInyoOn84tEOgAf9K/fnY3lMScD5q1f5fZmUb+FLn01ovAN1Jc8r3U3mVrHoDubimw9h4U0TcbQt2w9T4IJs3YP+v249tWkPNmyQIoHQszLjHft/dF6GqSY8Gbges1kYhf+pGB/EbIHQu7noQNfzUvVzYeln/KWAdUnJ7ixOI+zniyqoVQZZ6EdFX0FawJPx98YfjXqp0DP5ajUCYJ6LrqFaNQKBSnGFkLMX/4wx8YM0Z+sK9cuZKVK1fyzDPPcOWVV/LFL35x2DdQoVAoFArFSUokVlTsbxZ1/B9VV6VRxCyYaswi7NyWvilpIN4fJgM3jB42CvlxR0ztWvMyNQvwBMJ8+E9reXRjPf9cc5Qbfr+aLl9CTxj3aGO7NI2QazT37TIXbt8x1UKh+9Qs+nzwrHFMr8o3jf30uT209QaMfhe9B424lzj2AiNyrHPr4H0LXLFIpWjQXKhIjifb+wJEovJ8cefBcNFlLpzW6nFHjF9EQ3vh8T9H7jhxJJSdJS4ZxdtL3BUD0Ll94GbHmaJZ5G8gQt1GrF/h7FSxRtMkYslRKMfE8cRNgRxbZcvlXBfskuK11Q7X3A0kxlz54MUfyLJ5k6RYXThdKnyJVM00emMpN4yBo0i+qwA6tho9f4abglFwzS/NY5EQvPY3CPhF0Og9IFF5mdJzAHasNI+NPxdGzU2/fLY4iqVHxYJ3gC3h+1DXYeOjcr1rd9qea/3SsVWWdxSJCNawBf5zh3kZmwMu/Ay4Y3GakaQJGArFiaAvnqx9iPFko2HKOeaHPPwi188wC7J/XdNIKDLI91ifYFx7fCK/QqFQKE4oWQsxDQ0NfULMk08+yQ033MBll13Gl770JdatWzfI2gqFQqFQKE4LdD1hRmqaAp6uG/1h3DXm+wqmS9Ev7Emfbz2k/jB2o2ia7IgZs4SHN9TR2G3803y4zcsXHthMNJrgxiicJbPfKy/kiaPlNPcETQ/zoYWDuHNOYmxWC9+9zhxx0+0P88sX98UcA0WgR9J/HgXTZbZ/2Cv9LgZC0wzhpvewMT773eaidsgDDbEC9lBmlvZHNAo9TaahuBBTaPeLm8BeMDzP5SyRXiSKk4OCaXIeCHZI/OFIo+tSQNZ1cVnF+y0lY7GJGKNpEneVibNsIGxucSWAHGPeehizBBZ/xLzcvudg5/NQcQ6ULoKSZXDgDfMy1QtVf5j+yJ8am3EegbZ12QkL2TDvfbDsNvOYpx3evA+wyWz3nr0xsSIy8GP1HoRdD0B3Uu+t4XDDJFIwFQrGwOwrzOMH3oTORhEdM+1d4a0XJ5tmkR5bWx+AP10GvnbzcmffDJVzxS0DhhM23e8PhWKksLqMiEl/08DLpsNeAFMvEQE9TjTMZyrM31mNvTortw3Sb8lZAs7SmKNZuWIUCoXiVCFrIaa4uJjaWvlSePbZZ7nkErEl67pOJDLIj0OFQqFQKBSnB9GgFCA1Lf2M1GCHzNCz2MCZJKhYbBJ5BVJkSmyI7G+WwqBmAUcGvUP6ijEx94qnDdrMBaDI6GX8+c3U2K0Xdzfzq5cSltU0yBlFR8DO/zxlnoG8sEpn9qg8TmWWTSzlHfOrTWOPbqzHGwwbTeg9R1JnVlps0hsAJL4s0DbwE+WOlc8v2GHEROVVwMQLzMvtf10ufQ3D42AA6G2SGeUJxKPJCqzD6IhRnHzY3NLHSNMkTqp7hJsYe47IPp54PusPez7kxhx3XcPg2HFVGLOhO7bIOfTib0Nu0rn26S/CoY1Qdi488SVoToq5GrM8s15fZyKaJnGaNreI0O2bhj9GMc5l34OxZ5vHGnaLGKO5RADv2Q8tr0OoJ/1jeOugfTNs+Y95vGQiTL0i7SpDRrPIezP3GnAk9aZY96Bc9h6SyRYDEQmIMxbAPRFWfg8e+ySEk5wG45fArOukn1tc0O8TEJUjRnGCifeY8w1BiAEomgrjzXGto488zqJxRaaxR9aniYtNJh736zmqXDEKhUJxipC1EPPud7+b97///Vx66aW0tbVx5ZVXArB582YmT5487BuoUCgUCoXiJCQxnz1dfE9fLFlV+n4cOaNis42jUoiJBKWxdGvMzeKqzKyPRzTmWokXY+qS3LlWBy921XCkzZt29btf2MeLu8z/TH/vyZ20ecxumE8u1PvvhXMK8eUrpmNJSDDqDYR5bkejODucZfJ59OxJXdFVbsxE7tgy8Mxsq1M+XwDPYWM8OZ7s4GvSxyAaOn6XQJx2c/E9oNtppgiAAkdYnD+Z9ApRnJq4yqFojlzv3i29jUaCsBe6Y2Jt3OE3GAVTRTAO9YqIc7wUTIvNho5A+3pw5sNVP05aSIfHPwX/fA/sfdZ8V34FTL9a9doYCIvdKP77m+S7ajBXylCw2uH6v0o/s0SObIYXfgsRp+zPvYeg+TVxQiVuh69RXDuH/gPN9ebHOOt2sGT9L//g2POhfCHMuyZpm9dCW0xcHyxSrXObnP81F/znS7D2D6nLVE6Bi+6UGMjE3wRxkceqmpQrTjA5MSEm0DK084F7NEw5zzzWsJlbp5t/d75ywENLT1JcbDLOUuWKUSgUilOMrH+V/eIXv+Azn/kMM2fOZOXKleTlyezQhoYGbr99mG3PCoVCoVAoTk4G6g+j64YQkxxLlkjRHClwBVqh8QXwxGIYcsdC8bwMtyPuiIkVEZNjySom8X+rGgZ8iDsf2Mzm2k4AXtnTzKObzIWsy6Y4uWwCp8WM8eqiHM6dYo7TenhDrKdKYcwV461LP+u6cKYRKTdYRFm83463XkQ2gBnXSsRZnGgYjsZ6ZviSiodDpd1ciKjTy9BjP3cLHRFwVg7P8yhOXnLHQd5Eud6xSWYKD2fxPBqCtjWy/zqKjCi+wbDYjWOse49xXAyVuGPD6pTjtXMzzHwnXPDVpO0Nw8FXzGMON1z7A+nxERdibKe+0DwiOAqN7yPPEWh5TfrzDDf5lXDDP1KF4tZaePYX4PWLGNS1E9rXwbGnoWEltLwJrauh8SXYmdQfzVUI824a/m2NkzcR5r0XcpJchmvvlUtfQ/8Oyq6dcr+mwfrH4NBrqcvMvBSu/W+ovtj8vkQjhhBjz09dT6EYSewF4pTTo0ZPw2ywOsUh7C4yDV/kW0mO3RAbIzr8e30Gzs5EV8xQ+tYoFAqF4oSStRBjt9v5r//6L375y1+yYMGCvvE777yTj3/848O6cQqFQqFQKE5SBuorEGgTgcRiF5dFf9jcksMPMqvbXiD9DIrnybqZkBxNluSIac6fwdrD5qz5syeVmm73+MO88zdv8oUHN/P1x8zNtPNdNr53kQtN47RwxAC8d9Fo0+1VB9qo7/RJ7nlOlQhp3WlcMRa7UZDsPSjNavvDUSwFTD0qDadBZuzPSJo9vedlufQ1SsH4eGk/aLoZjyUDKHDZZZsUpz+FM8VVp0fFwdW4Ejp3SNP1iD/hL0sxRI+ita8XV4vVBaVLpJCcKe6xcp6LhgYXMzPB6kqIYzsmxe3zv5zac8S0jgMuuwuqYseycsQMjns0lC2LiV69EhHWvXf4IhXjjFkCN/4LHEkxmJ5OeOGPcGCDxHZ17oDO7eIoad8Ija/AltehKUnQXnQLOEcwUlOzQMVSmHedebx+C9TF9u/ObeaIMl2XY7In1iOs7hBs+qd5fYsNLv4CXPotqDo/VSQMxyYKWJ0qmkzx9hCPJxtKnxiAvHEwaYVpyLH9fq6Zbf59+tCGevTBIhETXTGZ9mZSKBQKxduGLZOF/vOf/3DllVdit9v5z3/+M+Cy11133YD3KxQKhUKhOA0YSIiJuxtyqtPHliWSPwmIyuO4x2ZX1ARzNFkkBPUbTHc/3jnVdLuywMlfP7KULzy4mSe3mp0yj25MdWV8/aoZVObsgzCnjRBz6cxK8l02evwifOg6PLaxjs9cNEVilvxNMlM52Ckz/hNxVUDuGHEvdWyGivP7j5DLnQDBzRJPljdJPtu5N8K2h4xlGrZATwfkF8tz5o45vhfXcdh0s1Y33D+FbiXEnDFomggUvQdFCAx75XrvwdRlLTaw5cb+CqTons4dousURg9BELC7YoX5LF1ymib9ZFpWibvCVWnE3AwVZ6k0OW/fJK/PlgOXfx/8XbDlvqTnt8BFn4aqaUbD6YHO5QoDVwVUXACdW+Vc1b0HvLUymcBdM/h3XaZMuQQ++izc9z7oTvhOCvpg4/NwdBfMuwCKyiHYK5Metr8lgkYijjxY9qnh2aaBcBTD4o/AtqelR1ucV38N1/9crje9LMdV3mSJvvQek2MhlAMv/I/58ew5cPNTMHpR/88Z6o4tWzC8r0WhyBRXlUQF+puMfonZrj/jYtj2lDHmbePj5bt5CKM/4p7WMDvqOpg9ZpCeiflTIbBaXDH5U9T5XKFQKE5iMhJi3vnOd9LY2EhFRQXvfOc7+11O0zQikRHIzVUoFAqFQnFyEW/wbOnHEQNGn5CB0CxGrMJQSIwma9oOIXMvmHvqxptu33z2eBw2Cz9+71zqOnx9kWTpWD6xlPctHg0NsWbCp4kQ47JbuXZeNfetOdo39vCGOj594WQ0e74UzDy1UnAsPze1wFA4S3q6hD1SVCucmf6Jcqqha4c0kPU3idtm4gXSUNzTbCx3aCPMvVgi0Y5XiOmsNd2MCzFWTcftdKnC3ZmExQoFUyB/ssTHeI6AvxlImF2s6+LECnbF4qaOyT7trJCIM2eJxDCGfdBbi0tvAyZK35Ch7kvOUkPMbF8HxQsGjnDMBPdoEVS6dolbwuKE634NgW7Y/aSx3HmfgnGLYj2hSuX1DxQzqTBjdUDpYjlXde4Qga9jM/TsjQkyo7MvyKajag58/EW47wZo3Gq+r7UWXvqn9E5x5kDID8eS3FVWB1z/NyioPv5tyYSSubD8w/DCL4wxX5dEjl30OTn/e2qN+FHNArlT4e/XQyipwfi1vxpYhAFDiLGpWDLF24SzRET8SABCnYawnSkWK4xaLKJ4o+FAnlr/GDVFnxGXcoyH1+1j9phlAz+eq0zO6YE2ccXEe6UpFAqF4qQjo6k70WiUioqKvuv9/SkRRqFQKBSKM4T++groOkRiYsiJyG7vm83thFpzPn6bYxQtUaNYmmO38v6l0nDe7bBx/yfO4stXTCfPmTovxWW38MP3zEHTQ0b8zGkUgZIcT3a4zcuGIx1yo2CGxJAFu/pxENihaK5c7z0IwY70T2KxSjEbxBUDYLXBnOvNy+1+Ppa13ioF7+Oh29ycPR5NVmAPoznyVWPnMxFNEzdD6RKouRpqrkn4uxoqL5T7Cmca4oS/CdrWwrFnoelVaFuL5pUisl40V4SM46Forogvui7RUr2HzffrUYlNiwTkHJfJcZE/2ejN1LEZAk3w3r/AJd+F2e+B634MU86WGMfi+fK+RLzyXJpFHRvZ4B4NVZfIPmNx/H/27jrMrftK+Pj3imEYPWNmtmNInDjgMCelFFNIadstbLtb2m27b9t9C9tut7Cld7tlzJYhDYNDTmzHFDOzPcwjlu77x5FGczUa0vDM+TyPHklXP11dzYw0997zO+ekAzJNO4avXFlBFbz9IVj+6p6PmQk5eXt6d88gjM0Br/2JZNaMFpsT1rwbZq21Lj/wADS3QsXV8hkEMOxQvBYe/BQ0ZWTxrH8HrHpd/6+X6mGmgXU1Vgxb+m86mGN5Mt9MWHytdbXHn+S+5dYs4z+93EA4NoDzbKlSv53JLFCllFLj0jDlUCullFJqSknNos7MiImHkmUabKPTc6BrNrcXzm61PPRcZKHl/mvXz6DIl27463Ha+ftr57P5Y9dy74ZZ2LpNZP7UHcuYXeq3zhYfrtIz48CamUXMK/dblv1+5zm5YXens1zaDlvr+6d4K+VkpGnKCcjeTj6mAjGpDBqA1a+3jmk7D43JMnHBnuXhBiwehY4Gy6JURkylLyJloIZjtrqaPAwbOPMkWyt/PpRvlMBM3rx0nyqbS0raeabRapsvJ8+G43WL10DeHLnfsldKizVulzJOFx6Ei4/AxUelIXvN41D3jPSW6UvhcvBVy+exaSe0vgxX/D3c+WWoSGZHFK9OZ790ndDO18/GYNns8jcz7UYoXCq/0+BFaHix/9/TQLnz4LU/hjf9Fopm9z/esMGr/weW3DE8rz8Y/ulww8ekbF93f/0g4JRSfpWboOQy+MP74cgj1nFVq+GWLw3stbQ0mRoPPNPkOlST2/NdxbDgWinH18XktfanLcNaQvDU/nMD2J4ymSRgJiRLTyml1Lg0qDMKiUSCH/3oR9x5552sWLGClStXcvfdd/Ozn/2s/yZiSimllJo8eusrkDrZbveO/Ik9M9FtO7xwxhqIeSFq7Q/z1ivmZF1NWZ6bL7xqJY/90yb+z53L+NW7N/CWy5MnvboHeiYRwzB4zVprVswDey4SjCRnXfpngbsMzDg0v5xlDUivi1Tz6rZeDvodvnRT29Ss/2mroHypddzx5O8uMICTDb1pPdsjIHQmmRGzujQg5aaU6o8zD4qWQ9UtUH07VN8CFddglqwnZCvt//kDZRhSPqYg+T0VOAfBGvk8dT+uMgy5RFqhYSsk+pgZbRgS4ClYLLeDF6F2MzTvksfz5kjQKSUViNEST7mz2SUbqXSDZKOEG6H++aFn93W36GZ4/1a45mPpAGEPBrziu7AiSwZNb1IBu7pnJfOrdrNcOs/098zsZt4MV7zDuqztIvziLjj8AERj8MvXw7EnrGM8hfC6n/UM4mQTD0lvOMMAR15u26nUcPBUJHsdteeWgWIYULgAFmy0LC46/Bs2zLb2s/vd9qMDW2fBErkOnEt/vyullBpXBhyIMU2Tu+++m3e9612cP3+elStXsnz5ck6fPs19993Hq171qpHcTqWUUkqNF4mYXKBnICZVlsxhzbYYEakgjGGTkz1t1pP4OxLpQEyBx8H88r63aX55Hu+4ai4b55d1e43kybRszbsnuFevnW6JlbWHYzyyv9vMzuJV8rMNN6Rr+3dnKVF2DCIt2V8oNes/cFZOIhtGz6yYI49BPCYnDiKtub2hRuuJijbTRxtyom5VWUSyGpQaKMOQk+wjrWAxlKyTsmJFK6Dscqi6CWbcJZfpd0LFpmS5wGbpK9NX+SvDJsGdimskYyCRLHHmzIOCjH5OsW4ZMWpoPGVQfqX8T4y2Q/1z6f9Rw8Hphes/DR/eC6/6b7j583DVP8G6+2Dt2+Ctf4ZL3ji4dXaegsB5+e6Otsl2R9uheU9u5ZZsDrjm/0BVxt/ZmR3w63vhqwvh3EvWxxweuOdHUDxnYK/RFTz0j87nU6ne2JzgKpHbuWbFZClPRutZ3jfbuj/71PEQ9W0D+D5xFUl/RtOEtkP9DldKKTX6BhyI+clPfsIzzzzDE088wa5du/j1r3/N/fffz549e3j88cd58skn+dnPfjaS26qUUkqp8SB1csnmkEt3qVmBjlHoN9A9W+X0C5aHgo58jprpBtjzK/IwcsnQ6Xqvk6+RdVWhl6sWlFmW/WTLqXSWs8Ofnl3Zul9O5mbyTkuWQuqjRJm7XP4eEtF06bGVrwO6/T7C7XDxuNzONSum4aDlbqosGcDqigQ4NRCjxilftQRh8uZKaZnMALczX0o7GXYp89e825o1k42zQHpzFCyWxtIl63ueuNam58PLWQDlV0nQKx6C1oP9P2ewCqpg9Rtg4wfhxs/AXd+Eu/8L5m0a3HoScWg/JrfzF0oAsOwKyYYEyaLKVpayPw4vvPL/gT1L5k5qAkeKpxDe8kdYMIh+NlqWTI0nqQzDXPvEOLww4zIotZYevLLtb3id6e/ruGnw5217B7bOrozImt57+CmllBozAw7E/PrXv+aTn/wk1113XY/Hrr/+ev75n/+ZX/7yl8O6cUoppZQah7qXA+vxWDIQMxqNny2BmOctDx13L6b7if4F5TmWMJnEGTEAr1tv7Xex+2wLL5xoTC/ImyeZJIkotPRSoqxwpfTRiLZDe5byGYYB/jlyuyPZnLlwOsy9xjru8Ga5Dp7v/yRzNo3HLHfPJsuSue0JFpc7dNa/mthcxVB6qWS8BM4PbLZzKjum/Mqef/9mIn2iXU9qDx+HV8rDQbI8UNvYbk9vAqcluO7wyt+Ip1yyeopWyt9aIgqNL/VdCq83lavhFd8CRx994vKr4O0PweyNvY/JRoOHajxJlV6NNPYMNA6Ub1aPrBjHkYe4Z4k1IP+7nRcG1g7AmS89/ABaNStGKaXGmwEHYl5++WVuvfXWXh+/7bbb2LNnz7BslFJKKaXGsUQv/WFgdDNiYt2CJKe3WB56yVxiuT+/IsdATGxy9ohJuW3FNGYUW9/bd586nr5jGFB8SbIRdU32bBW7S07egQRisp149M2UdUTb0jM0V2eU0Tn1PATa5eRgqG7wb6bltOVuKiNmeXEnTm+5vL5SE5mnXD6PAB3Hc+tLkBLrlGCMzTFpA81jxlUEvmRGZuuBMd2UrCzZMIus342GDUrXJ/t/tfUegO/PqjfCP+yA6/8ZyhdbHytdCO98FCqXD369mhGjxhOHXy6mKWVcc+GdBguvsWaRJaK8M886wehQk4P9pwaYMZz6XIcbJItSKaXUuDHgI9KmpiYqKyt7fbyyspLmZk19VEoppSa9ruBElkDMqGbEJF8rGICm45aHHgtkBGKGmhEzSQMxDruN92yab1n23LEGXj7Xkl7gLJCDeoCWfdn7Hviq03XJm3b1LFFmd6VPTHackutld4Or26xmMwGndsvtwCCbRSfi0HresigViFlV0pGetarUROebLgEZ04T2I7mvp6vXhmYWjIiCJXIiNFSfW2B5JHXPhknNnO/O7pG+RYYhwffOQX4fpxTMhGv+Bd63Ff7uabju09Lb5t1PQtGswa/PNCHWIbc1EKPGC49k3+b8OTdsULwE5m6wLJ598n+ZXuCyLPvdC7sHtk6HD/zJcmdtB3PLMlZKKTUiBhyIicfjOByOXh+32+3EYjmmYyqllFJq4kj00jclEU/3ERnNHjEX91kWm648XgjNsSxbkEtGjGlCIvl+sgWdJonXrptBWZ61hIwlKwYgf4HM8k5EpT9FNkWpEmVt6dnW3aXKkwUvQDwCLj+seLV1zMFHJCATqk0H/AYi2grt1lmfqdJkl5QGwFsx8HUpNd6lejcFzkG0I7d1xJKBGC3ZNzIcvvR3XuuB8XMitK9smO7cpd16hB2Q7/5cGQZUXwKbPia9bTw5BlFiHeksrkk6OUJNQO5kP7rwEDJP/LNg6Q2WRUbLaf5pvjUD5s+HE0RCA+zdlL9IPiuRVgiczX3blFJKDaveIysZTNPkvvvuw+3OXus1HM7SwFUppZRSk0+qr4DDb12eylCxOeUy0lKBmPPW0qitpatItKVPLrnsNmYW53DSJh6Sk2eGDWx91Lqf4DxOO++6ei7//lC6lvjD+2s4VtfOgorkSVrDkL4HdU/LDO/OM+mmzil2tzQcb9opJcq8VdaTvK4iuURaJOMlfwGseQvs/Gl6TPMpaLwIZdNlTEFGSZvedJyDkLUk2plkIGZVRRwcOntaTSKuIilnE6yB9sOSvTBYUQ3EjLiCRXICNNou15nfmWOhKxvGlz0bpru8+clgXzu0HYGiHEqJDafuWVyG0fdYpUaLu0z2E2MBCYw7c5j44yyAGeugZBY0pTPQbgs+wEd4R9f95rCDp3a8yC1X3pBtLVZ2lwRjWg9ITzFvtQRmlFJKjakBZ8S87W1vo6KigsLCwqyXiooK3vrWt47ktiqllFJqPOitD8xo9oeBdMbE2Zcsi0/5llnuzynz4bDn0B8k3q0E2yQ/6XPvhlkUeKwH6N/bfMI6yJnXbYb0/uwZK77pUgbMTEhvgcxZ4KkZ4p2n5LEZ66EsI9hyNNnvp/N0zxJnvanp2afwnFlOgTPGnGInuAoHth6lJopUkDJwIbeG8DEtTTbibE7IXyi32w7n1vh+OJmJbtkwC/vvm2UYUJgMvnSezD37arh09YfRv1k1jtjskkEGEB5CGUL/bFh2o2WR79QT3DYzYln2u90N6ezz/uTNlUlT8XD2TGWllFKjbsAh8R//+McjuR1KKaWUmghMs1uAIiPgEu/MvnwkxCNgxiHUDvWHLA/tNq0n9ofeH2byliVLyfc4edvGOXzryfSB+p93n+cfb1rIjOJuv8+8eRCqgXCTBFrKNvRcWdFKqG2QMYEz6TrlIDMyU0GcUB14K2HNm+Gxf02POfwoXPZqICwz/n3V/b+Bc9std48mphPGxaUlLdg8JaOToaXUaHIWyGcjcEFO8pdeOvDnmol0ZqOe1B5ZeXMliBELQvD82GbFhJvkhKzd3X82TIqnXILroVqZWV922chuY1+6AjGa4ajGGXd5sh9Uvewn5cI3HRZcBVt/BdFULz6TDxY8z0Nc1zXsqXM+Gs7voWzWZcQTJjYDjN4mCxk2KFwGjduh47h8/4zWZCmllFJZ5TA9VCmllFJTVjwkJ/EMW88ARVdGjL/n84Z9O5JBkrrMrA0fzwWtJ5hy6g8D6ab0U6QW/X0b5+BxpncNYwmT/3km4+drGFC0OtmEug4C53uuyOGFwlTmzEHrzE2bPX0isvOUXK9+g7VcRiwIZw9bx/Ql1gk1By2LdiRkFvrq0k7wTOt/HUpNRPmL5TMZrJGSfwMV65Cgus05JQLNY8qwgX+u3B7I99lICtXKtaey/2yY7gqXyd9ZqFZONI+Vrr5GGohR44wn2Ycu3Jh75pvNCQXzYOHVlsVLLv6JfGc6Ozhm2nj9Ly9wxZceZ8GnHuTyLz3BI/trel+vd5pk7JgJaDvY+zillFKjQgMxSimllBq41Cxqu7dnua7RLE2WCsTUHrEun3EpR5qs2zX0jJipEYgpzXPzhkuts7Xv336Who6MEhjOvHS5ndb92Zs4++dKObBEFFr3ZTyWzJAJ1cnfU14FLLrVOubgw/L3FW7svxxOqBFqj1oW7TAXAclATKqRrlKTjTMvndnQdnjgz9P+MKPLN1MCH5FWiDSP3XaEkidrPZWDe54zLx1Mat3fs+TkaEjE0vsYGohR440zX4LaZhwiTbmvxz8bllr7v9gC9Xx0pvX7/Xirk4utYUwTatvCvOfnO/ju5mOYvX02i1bIdeCCZMYppZQaM9qta5A6OzvJz8/vSv+MRCJEo1EcDgdut9syDsDr9WKzSbwrGo0SiUSw2+14PJ6cxgYCAUzTxOPxYLfbAYjFYoTDYWw2G16vN6exwWCQRCKB2+3G4ZA/i3g8TigU6nNsSjweJxKJYBgGPl/6BFwoFCIej+NyuXA6nZb1DmRsIpEgGJQTYX5/eoZ1OBwmFovhdDpxuVyDHmuaJoGA7Mz7fL4ev8/BjB3I7344/k6y/T6H4+8k9fsc6t9J5u9zMGMH87sf6t9J99/nUP9Oevt95vp3MlzfEamfUernM5bfEbn87vU7Ypx/R8QDxGJxwnEbtmDQOrajmUQkhLvI1bWDMWLfEdEOgoEQnNpH9/yb9sr1nN4TALsDwy7rnVvq6/pZDuo7olsgZqS+I6LRKJ2dnXi93nGxH/F318zjFy+eJpYwSURDBCPwg6eP8c93LLeOdUzH6zwvQZLWAwQ9i6y/T8Mgnr+C0LknsQVP4vXN7JoxGozaSMTzcZstODpPQ+Ey4qveSOjlv2IY4HMacH4ndAYJ2WzE6w7gqljT+3dE4yEINBOKmcQT4LLDzmRGzMrSCJ1RB3R26neE7kcMemz3333q92aaZk7fJyO2H+Gfjy1wDkJ1RAONRExP/98R0Tai0RgR7NhDoXF9rDFp9iN806HzLJGmo0Tzl4/+d4Qjji0WAMNG1FZIpLNzcN8Rrll4bGcliBc4S8AoG93viNaLGMEwvrzCrlKTg/07CYVCXd/Pff0+9VhjYp2PGDffEZ4KEu2nCDaegiJfbr97dwmRooVEixfibDiCyy6/41dEHuJfIxIMNZzu9P+jeBQzHsew2fnKw4c5XtfJF1+9glg4ZP19OguIOKuItp7EUfsS7pk3dmXFjdf9iHg8TmdnJ263e9LsR+h3xBT/jhjk2IlyrJH6vfX2+5yKxxr9MtWAtLa2moAJmHV1dV3LP//5z5uA+a53vcsy3ufzmYB58uTJrmVf//rXTcB805veZBlbVlZmAua+ffu6ln3/+983AfMVr3iFZezs2bNNwNy2bVvXsl/84hcmYN54442WscuWLTMB86mnnupa9sc//tEEzI0bN1rGrl+/3gTMBx54oGvZo48+agLm6tWrLWM3bdpkAuZvfvMbMxKJmH/605/MzZs3m4C5YMECy9jbb7/dBMwf//jHXct27dplAmZ1dbVl7D333GMC5re//e2uZUeOHDEBs7Cw0DL2bW97mwmYX/nKV7qWnTt3zgRMh8NhGfu+973PBMzPfOYzXcuam5u7fp+RSKRr+Uc/+lETMD/60Y92LYtEIl1jm5ubu5Z/5jOfMQHzfe97n+X1HA6HCZjnzp3rWvaVr3zFBMy3ve1tlrGFhYUmYB45cqRr2be//W0TMO+55x7L2OrqahMwd+3a1bXsxz/+sQmYt99+u2XsggULTMB87rnnupb95je/MQFz06ZNlrGrV682AfPRRx/tWvbAAw+YgLl+/XrL2I0bN5qA+cc//rFr2VNPPWUC5rJlyyxjb7zxRhMwf/GLX3Qt27ZtmwmYs2fPtox9xSteYQLm97///a5l+/btMwGzrKzMMvZNb3qTCZhf//rXu5adPHnSBEyfz2cZ+653vcsEzM9//vNdy+rq6rp+n9196EMfMgHzk5/8ZNeyjo6OrrEdHR1dyz/5yU+agPmhD33Iso7x9B2xZcuWrmVj+R2R8txzz+l3RNKE/45oOWg+8JN/zf4dsX6pfEf87tddy0bsO2LLn+Q7wmeY5mcKui6vuPU6EzCLr3+3OfsTD5izP/GAuf/Q0dy+I2qfNs2zfzHNQM2IfEdEIhHz3nvvHXf7ER/9zW5z9iceMJ2ls0zAnPPWL5utQfkcWL4jQo3y8zn7F3P92kt6/45YNtc0Lz5mmvGYaZrdviO+93HTPP+QacZj5nNPJ/cjSmzp3+ef32/efr189/z4hz/sWm+P74hnP2eanykw71kmn62v3FZozvnEX8wNn/uDeeShT+l3RJLuR4hc9yNS+7znz58ff/sRjS+Z5tm/mF//wkcG9h1Rv9X8/pffn/N3RIruR4gBfUeEm03z7F/Mj77n1WPzHbHzMfm+rn8h9++I9uOyjouPj813xKKZpln/YtfywXxH3HXXXSZgfu973+tapscaaRP5fETKmH9HBC6Y57b9eOj7Ef/wbvmOuMLVtT8U+XR+19iZH7q/a/+28Mo3moCZt+aOrmWv/d6W7N8R//5F+Y6453rTbE3vM4zH/YhIJGJ++tOfnnT7ESn6HZE2pb4jzMl5rJHaP45EIlP+WCMVN2htbTX7oqXJlFJKKTVw8UAvy8PI/h9gc438diRCPZfZXbRgLUNWXejB584xATjVI8YxNUqTpbz32vmWqnPBaJxfvHi650B3CeTNkdup7KFsDEP6vrRnlE6yu6V0WfAC2LP8jvb+oetPikgvfQkSUbiw17LorFmOiY1VJR3a/0JNDalSgdHWgY1P9dpQo8dVJJeuL7VRFmmQ66H0zPLNlu/tWADM2PBs12BpWTI1XrnLepbszUWqZKTTnfXh16yt5hMbgnzvqiNsnN6zH822U00ksn3NdO/F134kXWpYKaXUqDJM0xyjvcGJpa2tjcLCQi5cuMC0adM0zS851jRNHnzwQW655Rbi8bim+fXy+9SSIpoKPFrfEa2trTz88MO84hWv6FquqcD6HTGs3xF1zxILNBLOW4XNX5UeG2kmePoJEnY37lm3jfx3RM3TBJ/6Hux9EL8reeA76wr+o/wLfOupUxjJ0mRXLyzjp2+/dPC/ezOBv2WzDKy6hXDMHPbviGg0yp///GduvPHGcVOaLPX7fN8vd/DAzlNgguFwUl7g5blPXI/DMK1jE1Go3Uywo5VE3gLc5St6fkdEGvB2viwnKMqvJhh3ye8+chZH51FwFREv3Uio5hjGdy/H160pbeiKDxKfuxqXy41z5s1g91j/Tmwd8IOboeFkV2my/0q8lv/m1Xxs1Rn+/ooSghV3Duh3r98Ruh/R1+/eMAwefPBBbrvtNqLRaJ9jx2Q/omEr0fYLRJxV2Msu6f07AhMuPCilyUqvxe7yjutjjUm1H9F5lkjtdqI4cU6/GVfy9zni3xHxCN7WZ7EZBky7kajpyP07ov04tB4gELFjVlyDx+sd+e+IcBuhM49iAL7ZN4CreNB/J+3t7Tz44IPcddddXcv1WGNynI8YV98Rtc8SbK2BopX4K5bk/ruv24nzxe/g2veX9NiEGz74Er7yWRjNu6HmMSIxOw83r+Pjj7QRSqTLA/ltMbb88/Xk5/l7fke07MBttkrgqPyKcbkfEY1G+etf/8r111+vpcn0O2JAv88J8x0xCY817HY7Dz74ILfffjvRaHRKH2uk4gatra0UFPQ+cUQDMQM00B/oVBONRrs+dKk/RqXU2NHPpBpxFx6BRAQqN1lnpgbOQ9NOcJdC+caR346Lj8IfPgH1J9LLrv4IH7hwEw/sTzcivW/jHD579/LBrz/WCTVPgmGH6bcPwwb3NJ4/r/vOt3Lnt56zLPu3VyznrVfM6Tk4cAGadki98crrwOHrOaZph4xzFUL51RKUiUeg5jEwE1BxtcwW/+19sP+P6ecVzIA3fRdibeCrhpJ11vU27ILvXC/rSHp9+F/Zai7lF9cd4KrVl8K0a3P9MSjVZTx/XgFpwFz/vHwOp93QezZYpAXqnpXMhqqbR3UTpzwzARcfk/+hpZeCdwjZKYOR+v/sLJD/3UORiEHN4xKEL1kLvunDs419adop78FTAWUbclrFuP/8qsmh7Qi0HQZvFZSuz309kVY49Re4/0OQ6Jb1cv2n4ZqPQaQZzj8or1Wylr2JK7jrey9ZVvGb91zBZXNLeq471gm1m+X7qGQN+Gbkvp0jRD+vSk0c+nlNG2jcQEuTKaWUUmpgElE5gQRgzzjZHkuWLMt2En7YtyMO7XXWIAzAnKs53mAtnbagwlqqbMBSZcmmaGmrFdMLuWZRuWXZfz99gmg80XOwr1pmVpoJaNmXfYWFK6TBcqQVOk/KMrsLvNVyuyO57PL3W5/Xdg5qzkrgJnABQg3Wx8++aAnCxEwbe8x5AKwsi4G7aCBvV6mJz10iFzMBHSd6HxdNliVz5I/Odqk0wwb+WXK789TovW6oRq49lUNfl80BefPldvtRGOk5ndF2CcIAFCzpe6xSY81TIdfhesu+yaC5CqFoNsy7wrp8+w8hHpWsMP9MKWMWqmVl/gWWVVlP+m0+XJd93Q4/FCyW2y37ZVKMUkqpUaOBGKWUUkoNTKoPiM1lrTUN6d4xmQGakZAIwbk91mWuPOKzNnKiMWxZPL8810BM8r3ap1Z/mO7ed+18y/3zLUH+uOt89sFFK+UkY6gWgrU9H7e7oXCp3G49JD1jAPLmynXwgvQZmnkpzLjU+tyXfgL+2cnn7pOTG4koNL8M53ZYhu435xDCzez8CIU+Dzhy/P0rNRHlLZDrztPyGckm1R/GqYGYMZH6LgvVQ7Rj5F/PTMhrAXiHIRAD0hvM5pAgSSrIM1Lakr3FvFVyclqp8cxZKPvIiZhkHw6Ffw6suMW6rP0iHPhz8vG5ks0SqoPOs2xaYP18bD7cS289gLx5kiGXiEDLnt7HKaWUGnYaiFFKKaXUwKQaezr8g3ts2LcjAGd3W5fNu5YL7XHCMevs3PkVOW5PKlDgmLqBmA1zS1g3u9iy7FtPHs2eFePMkwN7kGBJomcDWXyzkjP249CyV5a5imRmp5lIzxC//O+tzzu3Hdo65ORGtB2ad0PtU3Kyue6IZejOhDQtX1EckOwsDcSoqcRbmTy5FpNshWwirXKtgZix4fClS5L1lbk0XMJNEpSzucBZNDzrtDnlJDD0/nc2HCKtELwot1Mz+JUazwwDPMls4lAvGSkD5Z0OFQuhcpF1+YvflWvfdHCVyH53pIlrp7dbhh242EZdW6iX7bRB8SVyHayR/SmllFKjQgMxSimllBqYvsqPdWXEjELgItIG5/Zaly26lWN11tnFBR4H5XlucqIZMRiGwQevX2BZdrYpyO93nMv+hPyFUsotFoCOY9lWCEWrumXOJE+wpQI4naclILP0FdIbprut309n1ATOS/aM3Qv1pyzDdiTkhMWy4g7JztJAjJpqUuWb2o/3LOUXOA/h5DJXlt4BanSkvvMC50a+LFAomaHorZTv4OGSN096qEVah37CuTdth+TaN10Dh2ri6CpPNsTPhc0Ovpmw4lbr8vM74Ox22ZfKm5PMiqllbXET+W67ZejTR/rIinEVpv9ftOwfnQw9pZRSGohRSiml1AD1Vn7MTKR7qoxGRsyZFyAatC5beDPH660HkfMr8jByPfHU1SNm6gZiADYtKmftrCLLsm89eYxILEtWjM0BRSvkdvuxdJZUd858yE8Gd1r2yUxt7zQJ4MTDcqLY7oANf2d93oE/QzguM00NGxQsAvt0CLVahqUCMcuL2iVLZzR6Fik1nngr0+WvmnelS5RFO6DlZbmdv1BPbI8ld6mcBDXjIz8TPRWIGY7+MN3ZXem/s5HI7Ak3SoDHMDQbRk0s7mRGTKRV9muGIm8uzF4HeaXW5Vu/J9f+ObLfbffgTLRz1SxrIGZzX4EYkICqp1y+i5p3Dq2vjVJKqQHRQIxSSimlBqar/FjGye14UBr2GnbpBTLSjj9tvV91CeRX9siIWZBrfxjolhHjyX0dk4BhGPzTTdaTYOdbgvzvS2ezP8FblTyoT0igJZv8hXLiIB6SGc+GLd0rJnVCb+3bwNktqGfG4a8fgpLLoPo2OTF3brtltRfMEi4iJyuWl0SkVruhu7pqCipcnv6MNe+RUoFNO6RkmbtUT2yPB6mG950nR+7kZ7RN/m8btvTJ4eGU+t4e7n438YgEEUEyAkZjgodSw8XuTvczCvcTCOmPww++abDsJuvy/X+CljPyWr4ZkjUWruPamdZSZM8eqSeWrZxsimFIiTKbSwJHqSw0pZRSI0aPTpVSSik1MF2lyfy9LB+l7IOTW6z3F0nZhmwZMTnT0mRdrlxQymVzrGWMvvPkMULRLH1gAIpWJsuP1Unt8UyGTUqUAXSckh4GvlkSyIu2yUxobxGsu8/6vJNPw86fpoMrZ7daHt6ZzIap9MUpz3fpjH81ddnsULJWTrIFL0L9c/LZsrvTy9XY8lZZMwFHQmq9ngrJWBxuDl860ybV42uoTFOChrGg7GsULhue9So1mtzJ8mTDUbbPPxcWXweObhOdzDi8mMyKyZsHNjcYTq6Zbs3AaQvF2HOupe/12z1QvFputx/Pvt+mlFJq2GggRimllFL9M83eS5P1tnwkNB6HloweJYtuBuBkg7UU1ryyHGfRJmLpcj4aiMEwDP7xJmuz2Jq2EPdvO5P9CQ5/erZ36z6ZjZ/JUwb+mXK75WU5SehL9oVJZcVc+wkomG593qP/Ci1noXY/HHnU8tCOxEIAlpeEZRt0FrWaylxF6fr/0Ta5Ll475bP8xo1smYDDLXhBrr3T+x43FKn3EDgr/zuHqu2Q9DEy7FB6KdicQ1+nUqPNk8xAC9XL/vOQ1lUB/nJYtMm6fMdPIdgsk0485eCtospZz5JS6+ttPjyArBzvNOk3A9C0M/0/Qyml1LDTQIxSSiml+hcPJcuP2XqeyBvNjJgjj1jv+yugag3ReILGTmvT4xnFOW5Pqj+MzTEys4gnoCvml3LFPGuN8u9sPt57Vkz+QnB4ZVZz+9HsYwqWSTmMaLvMwuwqc1Mrf1OeQrjrv6zPibTDr14H/3M9dFpnmnb1hynulACaYwgZUUpNBnnzpRQZSDkyT9nYbo+y8s9OZwKGGoZ33ZEW+R417MPfH6Y7T7n040rEJBgzFMEa6S8GUi5JsxrVROUqlv3HRASirf2P74thyP7Rylut5VajnbD9h3I7b74ELW0ONs2yliIbUCAGpKSlu0yybRq3Db2/jVJKqaw0EKOUUkqp/qX6w9i9PcvaxEcxEHP0Yev9hTeDzUZDR7jHpMPKghz71WhZsqwys2Lq28P8ZfeF7INtdihcIbc7jmfvH2B3QVFyTPsRufaUS8AvNUN84Y1wyZutz6s7ADFrHfTjiSr2mRLIWV7cnsyI0UCMmuIMA0o3QPmVULCo//FqdNmc4J8ltzuOD++6u7JhKuX7eCT5U5k9J3Of/R8LpPvC5M0DX/XwbJtSY8GwSVADJCtmqHwzoaAK5l5mXb71vyEaSgZE88FdzrXTrftbe8+3Ut8+gKCKYYPS9RJYjQUlGJMto1kppdSQaCBGKaWUUv2L99IfBuSADUY+cBFuh9MvWJcly5LVtlkPMp12g2KfK7fX0UBMVpfNLeHKBdasmJ++cAqztxNv3mlSUsNMSImybHzTZba2mZCm4v5UA+vT6cykW74A+VW9bteexDzeGvlnEsnd2uVF7VIvXQMxSslJeHdJ/+PU2MibKwGzUJ308xkOptktEDMKAQ3fDAkqxTpzb07edlCyatwlULh0eLdPqbHgSfaJCQ9DnxibUz5nq+6wLu+sg5fvl9t588Cws26aSZ7Tul/2zJEBfi5tTii9TK4jLdCye+il1ZRSSlloIEYppZRS/eur/NhoBS5ObIZ4t/JjNifMuw6A2jZrhkRFvgebLceG1BqI6dXbN8613N9/oY2dZ1p6f0LRCpllGaqHQC/ZM8WrpIRHpBlibXIizkykS9R4i+Cub2Z96ukFb+a1kc9wHqnHXuAymVHsl6bk9hwDcUopNVocfshbILdb9qb7kw1FpFkmSNgc6abhI8nmkBn7IFkxgxVpSf9/KFppLb+k1ETlTvaJiTQPz+c6by6UzYXq5dblW74FiYQEauweXJ58Ns6wZrI8eXgQwSCHX/ozGTb5XDZuHZ7tV0opBWggRimllFIDEU+VJssIxJgmJJLZKCMduDjwF+v92RvBUwBAXWYgJteyZJDOxNBATA/XLalgepH15/LzF071/gSHH/KTJxlb92dv5mz3SG1ykEbNqcbS3bNiFt0C696efo4rH+75Mb+v/BAR0s2cl5dGMdylUlpDKaUmgoJF8p0VD0NLL9mDg5HKrPGMQlmylFSj71Bd9lKUfWk9INf+meAsGNbNUmrMOHzyuTZNCA9DDyhnvpQ7y8yKaTwGhx+UwEn+fMDg+tnWLJbNh+p67+mXjbsUStZJj6lQPdQ/l56QpZRSakg0EKOUUkqp/sV6KU0WD8lBpmGTxusjJdAEB/5sXbb4tq6bmaXJKvM9ub9WV0bMENYxSdltBm+5YrZl2YN7a2jo6KP+eN4COSERD6V7wWTyz0r2h0lA8Lw0ujUT0N6tb8IdX4NXfR9u/By8/0VY8WoOXLA2wV1eGpETeVqWTCk1URg2aU4PEDgnwYxcWcqSTR/ypg2Ywy/lKAHaDw/8eaE6CDcmTyIvHpltU2qspDLShvKZ7i5/PkxfCSWzrMuf/4Z89n2zwebixnl2bEY6GNMZifPs0UEGg7zTpL+Y3SPB1bpnITQMASWllJriNBCjlFJKqf71Vpqse9DCyLEU2EC8/BuZLZxic8DK13bdzSxNVjmkjBgtTdaX162ficuR3oWMxBP87/azvT/BZofCFXK74wRE27OPK1olsy/DTVJaDKDzVPr3brPB6tfDVR+GwhmAlEbrbnmlQ/4ONRCjlJpIXMXS4wGkX1aupYAiTRL0tjkluD2aCpKBlMAFiLT2PRbkxHEqGyZvLjj0f66aZFJ9YkK1w9NrxV0uGcErb7cuP7cdTj0r+1t58yjzwaXV1n3yh/bl0IPKVQgVV8t1IgINL0D9C8MXWFJKqSlIAzFKKaWU6lsiKgdg0LM0WVcZrxHMHjFN2PET67Ilt4O/rOtubbs1I6OiYAjbE0sGYvSkUFYlfhd3rbI2gP7li6eJxRO9P8lbKbMrTbP30jsOHxQlS5SF6sBwWHvFZGjqjHCx1RqAW1GZLFOmgRil1ERTsEQyS+IhaHk5txO3Xdkw00a/14qzAHzJLJy2Q/2PD5yTwLzNCfkLR3bblBoL7lKZOBQPQ3QAwcn+GIYEbOdfDnkZgdZn/kOu8+aAzcGt86z7ZI8fqCUS62M/rTd2D5RdKZnLhiFl1hq2Qu3T0hNqsKUIlVJqitNAjFJKKaX6lsoQsbnkgDLbYyOZPXJ2G9QftC5b/y7L3bq2oOV+Za6BmEQUzGQdbZuWJuvNWzPKk11oDfHEoX5mSBYulxOD4QYInM8+xj8bvFUSgIkHpKdM914x3ezPKEvmccC8ouSurfaIUUpNNDY7FK+Wk52BC9C0Q74LByraBp1n5PZoliXrrmCxbH+q5FhvEvF0CbP8BRKMUWqyMWzprJhgzfCs0ztDJq6svtO6/OQzcGarfJb8c7h1vvXhtlCMF0/08ZnsS+q7qfIGCQTZHPJ907IPap+Cmsclky/clNv6lVJqCtFAjFJKKaX6FuuU68z+MDD4QEy4A/bcD/t+D/EsjduzycyGKayGOVdbFg1baTJL0GmUmhxPQKtnFrF6RqFl2c9fON33kxw+yF8kt1sPSJAlm+LVMtbmgkijBMaad/eYHb7vvLUs2ZJyB3Zbsl9RZuaWUkpNBO5SKFkv32PBi9C4rffvyu4ScWjaKYEb77TRL0uW4vCDL9m/oq+smJbdkn3q8IJ/7qhsmlJjwpPsnRSqHZ712eyS9bLwavCVWB979qtynTePqnwbl1Ra95seevnc0F7b4ZXM5Wk3yrW7TL6rYkEJAtc/L6XL+grCKqXUFKeBGKWUUkr1rSsQk+Xk9mAa2x98AL5zGfzxPfC7d8Av74Foz0wHi2Az7P+Dddmq10i/kKRwLE5zwHqiKueMGC1LNmBvuWKO5f5zxxrYfqqf2ZD589Old9p6aehsc0LJOjm4dxZIBk2oHtqPWobtP99sub98WvJ37ioa2X5FSik1krzToHSD9MwK1UPDixCP9P2ctkNS5svuhqLVo7OdvSlYlMx+bIJglpPPbUck48ewQfFanfSgJjdPheyTRNvS/RaHyj8HnB5YeZt1+dFH4cJu+R7wz+K2+dZAzGMHaognhqFXjc0pmTHlV0DVrVB2ebJ0WTLruX6LXHrrCaiUUlOYBmKUUkop1bdUXWtnQc/HunrE9BG4aDkLv34j/O+90NatJNWJp+D37+w7M+bl30KsW7DGZodL3mwZUtcWJlNlfq6lyQbwfhQAd66qosTvsiz7zJ/3932Qb9igaIXc7jwpJyaycRVB4VL5PRg2Gdd2WE5KAkQ7OHDOWgpteUWybJ6rNId3o5RS44inTE5y2pwQaYa6zdJTJZtQPXSckNvFl4DdlX3caLF7IC+Z5dJ2wPo9H7yYDsIXrQR3Sc/nKzWZ2JzgSv6dD1dWjN0t/ZiWXAcea3Yyz/6nXOcv5NYF1tN9DYEE24+cGJ5tSLHZJQOveDVUXi/ZOoZNsmLqn4dIy/C+nlJKTXAaiFFKKaVU31InUZyFPR/rrzTZ4YfhOxvg8IPZHz/0ADzw4exNiU2zZ1my2eugeIFlUV27NavG7bBR4M3oZTNQsUFk+ExxHqedD15v/V0cuNjGr7ad6eeJFck+MCa07O19XN48mRnuKpETkeFGKb0TOE/r2Wc52WztnbCiJDnTVE/sKaUmA1cxlF8pPa/iYWjaJSc2o21SriwegkirlG4ECX6k+lGMtbxk35dohzT1rt8CHafkPYB8v/tnjekmKjVqvMnyZMPVJwbkM+T0wMpbrMsP/gXqDoLdw+zqOSwts+5fP7z76MDKHebC4ZUAa+X18v2ViELDC9o7RimlutFAjFJKKaV6l4jJiRTomRFjJuTkEGQPxCQS8NcPQbSz79fY9XN4/DM9lx95GOr2W5ctv0OahHZTm5ERM63Qg5FraarB9ryZ4t5y+WwWV+Zbln31kcM0dfZTRqdwuZTdCTf1PssbpESZtwr8MyF0UWqQN+1k26lWTNK/Y7fDYHFRSMp/uDQQo5SaJJz5ULFJMgRT35m1T8OFh+DiY1D3jARknHlQsHSstzbN7pIgkm+6fC+HGyXwbsZl9nzhsrHeQqVGj6dSriONEpwYDs4CCbwuvRHcedbHnkn2islfyG0ZWTEPH42RaNk3PNvQG4dXypW5S+U4ouHFdEazUkpNcRqIUUoppVTvYsn6znaPlELoLlWWzLBlL4VS8zJ0ZMz+85fDtZ/sua7nvwl/+yhEk4GQ40/Bb++zjskvh3nX9niZ2jZrRkzOZclAAzGD5LDb+Ozdyy3LWoNR/uORXvq/dD3RK30EAFoP9H5iwrBJMCZvHuQvhOB5aHmZbeet49fO8OO2IycmbDlmQyml1Hhk2CB/AVReJ4HpruVGsuxREZSsH3+9Vpz5ULJWGnvnJzNknAXJHmDax0tNIQ6/fB5ME0J1/Y8fqPwF4PLB8puty/f9HmoPgN3FbStnWh6q6TTYc+LsyAdGbA7pdeWpkABs4zYNxiilFBqIUUoppVRfIkPoD3Pyaev9wlnwge1w7SfgtT+Wk0vdbf8f+P61sP2H8Os3WHvDACy/VWbXZcjMiKkocPcYM2AaiBm0K+aXctfqasuy+7efYe+51r6fmDcvXXKn7VDv4wxDSl0UrYai5eCbydb6YsuQy6Yn/5a0P4xSarJyeKF0PVTfBtW3w/Q7ofpWqLhaTvKOV3aPZPRU3woV10hARqmpJpUVM1x9YkD2iV3FsOxmcPm7PWDCU18AYOHcJcy37jLxX9sNzKZdw5ed0xubHUovTZajTUh52VQJYKWUmqI0EKOUUkqp3kVTgZi++sP0koFyIiMQs+AG8CaPBpfcAXd/q+dz6g/B3/6pZxBm/hWw7CY54MxQl5kRU5BjRoxp9h9cUll98vYleJ3p2dimCZ/9637MbL1/UgwbFK6U2x2npA9MXwoWQvlVtOetY1+9dTb1hqpkKTTtD6OUmuxsjvGX/TJQmgmjpqpUn5hQnQQlhkv+AvDkwcrbrMsPPQAXdoHNyZ0rrJNUnjpt8JeDYclIHmmGTTLjXEWQiEDTS8P7/pVSaoLRQIxSSimlehdtk+usGTF9ZI/EInDmBeuyeZus99e8WYIxjn4CJ8vuhk3vBYdbyjtkqG2zzq6rzDUjJhFJHxxmlk5Tfaoq9PLBGxZYlu043cxLp/sJrnjKwDdDbje/3P/BubeKl5rLSXSL77jsBmvLAsk7GohRSiml1DjjLJJ9y0R0eJvXeyolu3j5zeDJmDT15OcBeMe1l1Dusz702WcNGhvOQDCjhPBIMGzJ8okuiLRIvyillJqiNBCjlFJKqexMMx2IcfWVEZMlEHNuO0QD1mVzruk5bu1b4e+ehmkrs2/D8lfDrZ+R2b+u4qyzaXv0iMk1I6Z7hk9m2TTVr3deNZfpRda/hR88e6L/JxYul4PzaBt09D9+6wnrCYzV0/14HMiJCA2gKaWUUmq8MYxu5cmGMfhhGJCX7BWz+k7rY8ceh9MvUOj38H/vmGV5qDlk8G/PGtC8e3TKhTm8khkD0HlGLkopNQXpWQallFJKZRfrkAwFmwPsvp6Pd5XxyhL4yOwPM20l+EsluNN2FDpOph+rWALvegKu/BDQLdCy/FXw6v+BWCoY1LMsGWTpEZOfayBGy5INhdth5x1XzbUse/RALacbO/t+ot0lvV8A2g5DrO/xW082Wu5fNiNZokezYZRSSik1XnmS5cmCF2V/eLj4psu++JLrwJfRK+/Jz4NpcuvaFdy20GF56M9HDJ44HoWmHaNTLsxTDgVL5HbL3nQfSqWUmkI0EKOUUkqp7Lr6wxRkr+veV0ZMZn+YucmyZK0HpDF7yz5o2Z9+3OGGm/5NAjJXfADu+i94zQ/B7pAyBpA1EBOIxGgPxy3Lci5NFk9m8Dg0EJOr162fQb47faBvmvDj50/1/0TfDHCXyYmAPkpWBCIx9p6zHrhvmJZsNusuzfIMpZRSSqlxwFMuk5viof774g2GYYP8+eD0wJpXWh87/Ryc2AyGwedeeQkFbmsA6FObbbS2N8u++WjIXyCZQWZCAkCJ2Oi8rlJKjRMaiFFKKaVUdl39YbKUJYN0KYPMwEW4A86/ZF0271rJguleeqrjBLQetI6bsQ5u+QKse5uUI4tH0hkSrqIem1CXkQ0DUJFrabJYMhCTLftHDUi+x8kbLptpWfabl87SGoID7pYAAMN2SURBVIz2/+TiVXIyIVQPnWezDtl5uoVYtwYxdpvBuvLU34dmxCillFJqnDJs1qyY4eSbLWVeF10F+dOsjz32r5CIU1Fayaevt+4r1XTCPz5qkGg7DsHa4d2mbAwDStZIBk+sU/vFKKWmHA3EKKWUUiq7SLeMmExmQprbQ8+MmNNbrDPcbA6omAetyQyYgiVQlOwJ035MylH1ug3JGYPOPLA5ezyc2R8mz+0gz+3oMW5AUoEYhwZihuJtG+dg65ZAFYjEuX/bAGqBO/xQsFhut+yFaHuPIZllyVZW+fA7TQkG6u9NKaWUUuOZt0qugxeGtzyZzS5ZMXYnrHmV9bGavbD7VwC89sp1XGWdL8OTpw3+azvQvKvf8rDDs61OKFknQZnAObkopdQUoYEYpZRSSmXXVZosS0ZMqiyZYe8ZIMnsD1O9BjoOywGnfxYULIS8Od36ghyRvjGZErF0qQRX9rJTte0Z/WFyLUsG6dJkmhEzJDOKfdy2ssqy7CdbThGND6D+eN58Kd1hxpMlK6xl57aeaLLc3zAz+ben2TBKKaWUGu88FenyZNGW4V23f45kxSy4HMoWWB974t8g3I7hcPMfr1pEqdcaBPrGNpv0i2nYKtnoI81dAvmL5HbL3tEJACml1DiggRillFJK9RQLQiIqs9Wc+T0f72psn6UMWGZ/mMq5cmLdU57OhAHImweFy+R22yEJyKSYpszMi7aB3Q0Fi7JuZl1GRkxlfo5lyUAzYobRu66aa7l/sTXEg3sHUIbDMKA4WbIi2g6t6ZIVoWic3WdbLMM3VCUzr7Q/jFJKKaXGO8MmPVJg+MuT2Ryyb22zw+X3Wh/rrIPnvg5AVdUCvn2nD7thDcZ8+DEbJxs6oXFbj4kwIyJ/oey/JWIy+cYcwIQdpZSa4DQQo5RSSqmeUtkwjnw5aMyUyojJLEvW2QC1GfWeqxbJOkrW9VxX/nwoXCq32w5DazIDpv0IBGtkfOml2QM+9CxNVplrRkw8LMEiw+j5ntSgrZlVzLrZxZZl337yGJHYAA6y7W4oWSu/i86zXf1idp9tIdItq8ZmwPryDrmjGTFKKaWUmgi81XIdvDD8686bK5nq0xbCvGusj235NrScAcPgilXr+ZcrDcvD7RF470M2Ojuak4GRYSydlo1hyP6ezSnlkFsPjOzrKaXUOKCBGKWUUkr1FG2T62z9YUAyZkB6c3R38hnrfacXyhdIebMsPV4AyF+QLlPWfhQatqWzY4pWgas4+/OA2tag5X5lQY4ZMamSCHZP9sCTGrTMrJijdR18b/PxgT3ZXQr53frFhOp7lCVbVgYFroTUW8+WtaWUUkopNd64y6W0bywIkZbhXbfNIWVeAS57nbxOSjwMj31GbjsLeOc1i7lroTXYcrgRPv6kDTNYK/tfIx2MsXskExqg4yQERiA4pZRS44ieaVBKKaVUT6mMGFeW/jAAiWQmii0j8NGjP8wqsDv6DKYAUkqhaIXcDtWml/ln9v4coLbNGoipyDUQ05Xho2XJhsvNy6exvNoayPv2U0c5Wts+sBXkL5Ba6mYcGl5ky5Ezlocvqzbl7yp1AK+UUkopNd7Z7OBNlScbiayYOTL5Ka8I1rzB+tj+P8DpFwAw8ufz5dtKWFJqDbb87Rj8YDfQeRoaXkyXIx4p3kopUwbQsgdiHSP7ekopNYY0EKOUUkqpnlKBGGcvgZjeMmJOb7Her072gOkvEANSTqFopZQq8FSm+8f0oUePmFxLk6UyYhz+3J6verDbDL78mlXYbenSF9G4ycd//zLxxABmWBoGlKwH/2xeroWtZ6y/6w0z3VB6mZzQUEoppZSaKLrKkw1znxhIBmHmye1VN4OnyPr4X/8BoiEwDHwVa/jvO+wUuK37ZV/aYmPLORuEG6D2aQjVDf92dlewuKtfjNG0QybhKKXUJKSBGKWUUkpZJaLpQEtvpcmy9YiJRaAxo/RU+Wy5dg+wh0feHKi6BcoukxPxfTBNk9r2qGVZzqXJ4gG51oyYYbVieiHvvnqeZdmuMy38dMupga3AZofiVXx9V5FlcbEHrl67Aeyu4dlQpZRSSqnR4q5IlicLSH+U4ZY3D2wucNhh43usjzUcgWe/KrcdXmbPWc03bzIxSAdjEiZ84FEn54N5kIhAw1Zo3gOhBjAH0O9vsAxDekna3RBrpzBxevhfQymlxgENxCillFLKKnVA6PD13tclWyCm+WTPGWyFVZI1Yx9EgKS318zQEY4RiFoPBivzc+0RkwzEODQQM9w+fONC5pZZM43+45HDnG0KDOj5O88089SxNsuy914zG5+vlyChUkoppdR4ZilPdn4E1u+AgkVye/4aqM4o4/rc16Fmn9z2VXPd8pl8+DJrVkxTIMr7HnES8yUnVXWegYYX4OKj0LRL+rnEI8O3zXa3BGMw8JgN0HFs+NatlFLjhAZilFJKKWUVaZZrV1H2xxNxyZoBa4Cl4Yh1nL8U3P6BlSXLQW1buMeyilxLk8U1EDNSPE47//7qlZZlwWic//PnfQN6/tcfs/5dleW5eMtVS4Zt+5RSSimlRp13ulwHzoM5gJKtg+WfLfu1Zgxu+LgEZ1ISMfjLByAek/tFq/jgVaXcOMe6HXvOtfLDvX4ouwL8syTLJhGFwDlo2gEXH4G6Z6D1YHpS01C4SzGTpYmNtkMS7FFKqUlEAzFKKaWUsoo0yrWrl3JiiWSvDpvDmr1Sf9g6rmhGcj0jE4jJ7A9T6HXicebQL8RMpEuxaWmyEbFhXilv2jDLsuypw/U8cbC2z+dtP9XEs0cbLMveu2k+Ppejl2copZRSSk0AngrZj46HINw4/Os3bFCQnLjiNWDjP1gfv7ALtn6va6yt7FK+dnsecwutwZivPXaEkx1eKF4NVTdD+ZWQPz9dvjjSCu3HJCAzHL1k/HMJ2KbJ7eZdEG4a+jqVUmqc0ECMUkoppdJMs1tGTC+BmK6gRUYZsIaj1vsFFcn1jFBGTLs1EFOZczZM8v0YdimLoEbEP9+2hPJ868/3c389QCjae0PWzGyY8nw3926YPSLbp5RSSik1agwbeKvl9kiUJwNZv6tQMmAuuRvKFlkff/ILUJ/c17I5KZh+OV+9xWnpFxOOJfjn379MImFKLxd3CRQug8pNUHUTlKyRff1EVHrJtA+9pFi7MRM802SyVOM2iHUOeZ1KKTUeaCBGKaWUUmnRNjlYsznSM90yZesPAz1LkxVOk4NMZ+HwbydQ2xq03K8s0P4w41mBx8m/3GYtKXamKcAPnj2RdfwLxxvZctw6Q/R9187H68oh60kppZRSarzxJcuTBS9I0GG4GQYULJXb4Qtwx1cBI/14LAi/fRtEkvvCdg/rVl7BfZcYltVsPdnE/dvP9ly/3QO+GVC+UUqhgZQpa9ohpYyHsN1m8Ropk5yISm+aaEfu61NKqXFCAzFKKaWUSosk0/9dJXLwlk22QIxp9syIKaqWAyhjZHY3alutB2QV+TkGYlL9YbQs2Yh71ZrprJ9tzZD69lPHON8S7DH2v56w/j1VFrh542WzeoxTSimllJqQXCXg8MokqFDf5Vpz5imXi5mAAj9c9nfWx+sOwIMfS993FvDRO69keoH1OOBLDx6gpiVLHxjTlO0vWgnFq+T4IXBBgjFD6X1j2KH0MnD4JWBU/5yWKVNKTXgaiFFKKaVUWrif/jCQPRDTXgORduu4oqoRK0sGUNdqPRjMuTRZqtyBZsSMOMMw+NwrlmPrdmwfiib4wt8OWMbtPNPMCyes2TDvv25Bbj2AlFJKKaXGI8MAbzIrJnBu5F6ncJm8VvAiXP0BqFxhfXz3L2DXL7vu+vOK+NJr1luGtIfj/Ov/Pgk1j0P9Fqh/Xm5f+BtcfAQuPizrd5dDtB2CNdCeMUlrsOxuKL+qW+mzFyTIo5RSE5QGYpRSSimVlsqIcfcRiMkWuMgsS+Zwg79kRAMxFzNKk1Xk5xqI0dJko2l5dSFv2mDNbHlwbw3PHKnvuv/dp45bHq/Id/P6S2eOyvYppZRSSo0a3wy5DtVJsGEkOAvAP1dudx6D1/4YXHnWMX/7CNSmJ8Zcs7iC16ydYRny2EmDp44FZeJWuEkyVVJZL4kYhOqT7yME7YehZb/cHwq7C8quAG+yZ0zTDmg7PDKl3JRSaoRpIEYppZRSItYJ8bCUEusrgJIq5eXwp5f11h9mBAMxp5sjlvszS3IMpHSVJvP3PU4Nm4/evJhin9Oy7OO/e5mWQITDNe08ftBanuNdV8/F7dBsGKWUUkpNMs58CZSYCekVM1IKFktPl1gnuIC7vml9PBaE37wFAunyX/9651LK8lyWYZ/b4iNcsBpK1kHFVTDtRph+B1RukvJkvungmQY2N7QdgvoX05OecmWzQ8l6yEsGk9qOQO1mCI5QOTellBohEyoQ86UvfQnDMPjwhz/ctcw0TT772c9SXV2N1+vl2muvZf/+/ZbnhcNhPvjBD1JWVobf7+fuu+/m3LkRTPtUSimlJqJU3eW++rqYCTlQA2vgIjMQUzRdal7bc+zb0o+2UJTGgLXu9OzSHAMpmhEz6op8Lj52yxLLspq2EP/yh718b/Mxy/JCr5M3bZg9mpunlFJKKTV6UlkxI1mezOaAwuVyu/0oLL0N1r/TOqbxGPzi1RBqA2R/7Z9vW2oZcqopxA92RMBXLROuHF45bnAWQN4cKFkL5VdCwSJZ3rJbgiaJ+NC23zCgaIWsPxVQatwGDVulFJpSSk0AEyYQs337dr7//e+zatUqy/KvfOUrfO1rX+Pb3/4227dvZ9q0adx00020t6e/iD/84Q/zxz/+kfvvv5/nnnuOjo4O7rzzTuLxIf4jUEoppSaTyAD6w6SCFjaHlApI6RGIqep7PUN0uqHDct9mwMwSby+j+5CIpstA2DUQM5recOlMrl5YZln20L4a/rTbOhv0bRvnkOd2jOamKaWUUkqNHl+yT0y4aejZI32+TjV4ymViVcs+uOWLMM16jo0Lu+DXb4SoTLx69ZrprJlVZBny7SePcaHFWiLYwlUIFddA8SVSuqxxGzS+OEzvYTpUXgf5CyTQE6qTQE/TToh29Pt0pZQaSxMiENPR0cG9997L//zP/1BcnC5xYpom3/jGN/jUpz7Fq1/9alasWMFPf/pTAoEAv/rVrwBobW3lhz/8If/5n//JjTfeyJo1a/jFL37B3r17efzxx8fqLSmllFLjTyojxl3a+5iu/jAZ2ScNGc04C6tHtCzZqbpmy/3qIm9upatSB7t2t5Q9UKPGZjP46mtX9yhR1p3PZeftG+eM3kYppZRSSo02uwfcyckpI5kVA1I+LBXAiDbCG34FBdZeMJx+Dn57H8Sj2GwG/3b3Cgwj/XAwGueLDx7s+3UcPph2PZSuAzMONU9C4PzwvAebAwqXQuW14K2SZYHzUPuUBGRGMpillFJDMCGmF77//e/njjvu4MYbb+Tzn/981/KTJ09SU1PDzTff3LXM7XazadMmtmzZwnve8x527NhBNBq1jKmurmbFihVs2bKFW265JetrhsNhwuFw1/22NknNjEajRKMj1EBtAkr9LPRnotT4oJ9JlbN4GCPcCoBp5EFvf0OhFox4DEwXZmpMuB1nm/XAKpZfgWn4e1/PEJ2obbLcn1Xize3vPtQq78een34/o0Q/r1DitfOFVyznfb/enfXx16+fQZ7LmNI/IzU+6OdVqYlLP79qQnBXYQRqoO0EpmcOlsjHsHKBdw5G+xFo3IVZvgne9FscP7sLI9CQHnbkYRK/fB3x27/GksoZvH79DO7fng4SPfDyRV6/rpbL5/WTAV92A0bHBYzAKcxTv8Wc/26wuXodPrjPqwsKVoN3rryfUA20n4aOc5j5i8A/bwR/jkop/f+aNtCfwbgPxNx///3s3LmT7du393ispqYGgMrKSsvyyspKTp8+3TXG5XJZMmlSY1LPz+ZLX/oSn/vc53osf/TRR/H5tHRJpscee2ysN0Ep1Y1+JtVguRNNFCWOETN8NNp7T5jNT5zGl6il01ZFh00aZBYGTnJttzEmsOPYeWpPP4tpjMyuxtajISCv677R0cCDDz446PX4EhfJT5wlZJTSam8dxi0cOP28wsYKG1vqrH93dsNkTug4Dz54fIy2Sqme9POq1MSln181rplxKuJ7MIjRbK8jYhSO4GslKEkcxGl2EjH202xbTOHMf+DKY/+OM57OJrGdeJLEdzdwsOo1rC66ib/YXQTi6cDGB36xnQ+vjFPi7vvlHAkfc2JnsZvHaD1QS43z8n43MZfPq8MMkp84i8tsA7YSM/y02uYQM3LsI6mUGhD9/wqBwMAy8cZ1IObs2bN86EMf4tFHH8Xj6b3Zr5ER4TZNs8eyTP2N+Zd/+Rf+6Z/+qet+W1sbM2fO5Oabb6agoGCA72Dyi0ajPPbYY9x00004nb2XFlFKjQ79TKqcte7D6CzC9M+GwpW9DjMat0G4DrNoFfhmybK9v4HD3Qbll7Pu8k2Y024asc392feeBGJd969Zs4Tbr5wz+BW17sXorMTMWwAFS/ofP4z085p2bSTGK7/7Iicb0zuwr1k7gze9cvkYbpVSafp5VWri0s+vmjBa52B0nsb0VkPx2pF9rdh1GPXPgBnHLFgCeXdgnF2H+at7MGLp/i+ORJiV53/FiuhuVs9bxf0n3Jw0qwiYbrzxCCdPGLzmhtl4py2EypW9Z6C0LMN27vcAJGbOgsIVWYcN+fNqmhA8i9F2MNkH0sDMnw95izQ7Rqlhpv9f01KVtPozrgMxO3bsoK6ujnXr1nUti8fjPPPMM3z729/m8GE561NTU0NVVVXXmLq6uq4smWnTphGJRGhubrZkxdTV1bFx48ZeX9vtduN29wzrO53OKf/HlY3+XJQaX/QzqQYt0Q52B/imQZ9/O2EZ5y5Mj2s+YRlhFE3H4SnsZz1Dc7olbrk/v6Igx7/5iLyfEd7evujnFQqdTr5z7zre+qNtNHSEmVHs5aO3LpnyPxc1/ujnVamJSz+/atwrmA+h8xBtAJsJ9t5LeA2ZswhKV0PzyxA4DnnVMO8quPc38Lt3QmedZbhRd4BlHODfMj9CIeBvydtFs2DZK2DZq2D6Wmvgo3wthE5D007sNQ9BwVxwFfW+eUP5vLrmQ94MaN0HgQsQOAnxViheI71rlFLDSv+/MuD333vtkXHghhtuYO/evezevbvrsn79eu699152797NvHnzmDZtmiUFKhKJ8PTTT3cFWdatW4fT6bSMuXjxIvv27eszEKOUUkpNGYkYRJMzONx91Hk2TYgnZ8g5uqX4NxyxjiuqBkceI6U9GKEhYFqWzSnL8aAq1czTrgdlY21ZdQFPfXQTf/nAlTz5kWupyO89G1oppZRSatJxFcrFTEBwmBrb98U/GzyV8npNOyERh7nXwAe2wbr7Br++ljOw5Vvwg+vh+5ugMaO8bPUd4C6X44mzf5DXHSl2N5Ssg5K1YHNAuAnqnobAKPxclVKqF+M6EJOfn8+KFSssF7/fT2lpKStWrMAwDD784Q/zxS9+kT/+8Y/s27eP++67D5/Px5ve9CYACgsLeec738lHPvIRnnjiCXbt2sWb3/xmVq5cyY033jjG71AppZQaB8KNEmRx+MDex8nveFAOmAybdVzDUeu4wqoRDcScrm+23DcMmFGcQyClt8CSGjP5HierZhThcozrXVSllFJKqZGRLP1L55nReb3i1RK0iLZD8y7ZP/YWw13fhLc/DGWLc1vvxT3wo1uhZm96md0FM18Dhh06TkLdc8PzHvrimw4Vm2SyWSImAafGlyAeGvnXVkqpDOO6NNlAfPzjHycYDPK+972P5uZmNmzYwKOPPkp+fn7XmK9//es4HA5e97rXEQwGueGGG/jJT36C3W4fwy1XSimlxolwsvSAu7zvcbFOuXb40qUG4jFoypjtNsIZMafqrIGY6kIvHmcO/9MT4WRgyeg7AKWUUkoppdRo8E2H1v2SrR5p6bN817Cwu6FkPTS8AMGL0HYQCpfJY7OvgPc+B8ceh5qXofGYXJpOEI8naIw4CJguXEaUaqOp57o76+DHd0i5s1mXyzL/dKi8Dmoeh9rNkD9f3vNIcvigbCO0H4H2o/I+ww3yPv2zRva1lVKqmwkXiNm8ebPlvmEYfPazn+Wzn/1sr8/xeDx861vf4lvf+tbIbpxSSik1EYXq5dpT0fe4eKqMV7fskZbTEI9YxxVVg3MEM2IaWi33cy9Llgws2b3avFMppZRSSo09mxO8VVJCq/PMyAdiQLJFii+RbJH245Ip7p8tjzlcsOR2uXRjB44ea+BtP9pGLJFgqXGG2+1beY1zC9Vmt/4y4Vb42Svh9T+HhTfJsoqroeO4ZMWc+xPMf5cEhEaSYUDBYvnZNu+RIFfzHvk5Fy6TknBKKTXCtO6DUkopNZXFAhKQMAxwl/UzNpUR00d/GHceeAsluDFCTjYELPfnlOZYVizWIdcjmL2jlFJKKaXUoKTKkwXPS9+WUXnN6RKoAGjZC6G6vscDVy4o4yM3LwYMDpqz+c/Y67g5+EWOeldbB8aC8Os3wKnn5b5hg+mvlEyVYA1cfExKoo0GZwGUXyXBF8MumTF1z0gQKnWso5RSI0QDMUoppdRUljrIchVLI8u+dC9NlpIZiCmqTpYuG7ldjNPNYcv9nAMxUQ3EKKWUUkqpccZdKvvTiZgEY0ZLwSLwz5SgSONL0Hm236f83TXzuHxeSdf9Dnzc2fyPXJx2rXVgIga/ewd0JI89PCVQdQtgQNNL0Hpg+N5HfwxDSqJVXpsuixY4D7VPQcs+SERHb1uUUlOKBmKUUkqpqSycLEvm7qcsGUj2DPSdETPC/WEATjZbZwbOLs21NFkyEDOCZdSUUkoppZQaFMMA/xy53XFydF+7aJWUKzbj0Lwbmnb0GZiw2wy+9rpLKPCkJ3SFcXHbxb/j/KxXWAd31MDv35nO8im+BIpWymtdfAhCjcP/fvri8EHJWqi4BjzlEoDqOAk1T0pZuNHK0lFKTRkaiFFKKaWmKjMh6fggBx/9yVqa7Kh1TOHIBmI6Ap1kVCZjbpmWJlNKKaWUUpOIf5ZkmEfbINw0eq9r2KD0MihYIgGhwAWoexqCtb2WSasu8vKlV6+yLGsJw1VHXstu1zrr4JPPwNNfTr9W9W1yHBJphQsPQCKj9+RocBVC2eVQdgU482UbmvdA/XPSS0YppYaJBmKUUkqpqSrSImUCbC5w9tOgMh6W2WqGke7/YppQf9g6rqjKGqgZZqdrGyz3DQNmluSQEWMmIB6U2xqIUUoppZRS44nNCb4Zcrvz1Oi+tmFAwUIov1KyRmJBaNwmWSt1z0kZsY6T0HEKOk9D5xnuWOrnnnUzLKsxsfGOtndz0Syxrv/pr8CxJ+S2Mw+q7wS7B9qPY9Q9M3aZKJ4yyY4pWi4lmyMtEozpODE226OUmnQ0EKOUUkpNVan+MJ5yOeDqSyobxu5N938JNEKoxTpuhEuTnaq3vl51oReP0z74FcU65SDP5gS7e3g2TimllFJKqeGSKk8WvCiTokabqxgqNkHeHAmUmCZEmqH9uPRSadkLzS9L9kjt03xuQwPXzPVaVtFEAR+IfJCY2f30owl/eDe0XZS7+fOg/CrAwGjaTl7i3Gi9w54MG+TNg8rrwVsl77llv/TM0d4xSqkh0kCMUkopNVV19YcZRFkye7fsk8xsGLsT8spHNhDT0G65P+T+MJoNo5RSSimlxiNXoQRDzIT0LBkLNof0cam6CabdACVrwD8bfNUSqPBOA3cZGDb8tgA/vb2Tb9+SYEZheqLUDnMx/x57o3W9gUb403shkZD75RuhYBEkQpTHd0OoZvTeYzZ2N5Suh6IVEpwJXoS6Z6VUnFJK5UgDMUoppdRUFI+kax7n3B/miHVMwTRwuMHuGpZNzKZnICbHMmjRVCBm5MqoKaWUUkopNSR5c+S689TYN493+KRcWvEqKFkngYrSS6H8Cqi6BUrWYfinc+cig8ffGOWfr/GR73YA8IP47Twaz+gXc2IzvPhduW1zQvWtmO5yXGYbRs2j0jdmrOXNlSCRwyvHQ/XPp6sKKKXUIGkgRimllJqKUtkwzgIpNdCfeECuLYGYo9YxRVXS4HKkRFo53WJtEjq3TDNilFJKKaXUJOWtln6O8dDYZ4n0xeaQLJmStVB6GR6nnfeu6uCpd/h484YZ2G02PhZ9T49+MfHHPgsXX5Y77lLMypuJGT6MjhNQ+6T0pxlrrmIov0YyfxIx6ZczVhlKSqkJTQMxSiml1FSUCsQMJBsGumXEdAt8ZGbEFFWPbIZJqJaTLdZFOWfEpAIxIxk4UkoppZRSaigMm5QCA+g4NaabMmCeCii7HGxOyuwtfH5jCw9/cANrF8/ln6J/T8JM96a0m1Gafv5WiCQnfeUvpMm2VPpStuyH+ufGR28WuwvKNkhGkGlKX5y2w/0/TymlutFAjFJKKTUVhQbRHwYGVpqssHpEM0w62y5SHzAsy+aWDTEQo6XJlFJKKaXUeOafDYYB4YaJ06PEXSIlvexuiLax0HGEH993Kdfc/Bq+H7/TMrQkcJK9P/mg3DEMWuwLMItWAwlo3g0N28ZHMMawSY+cgkVyv+0INO2SHj5KKTUAGohRSimlpppIi5Q3MOzgLu1/fCKaPvixJzNiokFoyUjJL6oauUBMPMTphp4HnrNKcihNFg9JWQHD0ECMUkoppZQa3xxe8FbJ7fbjY7stg+EsgLKNcswRboD2Y/z9tfNx3Php9ibmWIauvPA7djz0UwBMw4FZthEKlkpfx5aXJTMmNTFsrBUshuLVciwROAcNW8dHoEgpNe5pIEYppZSaaoIX5dpbKTO7+pM66LG7pf4zQOMxIKNhaOEIBmKCNZxqsS6qKvTgcdoHv65oMhvG7hvY+1dKKaWUUmos5c2X6+B5mVQ0UTjzoGil3G4/DOEm3nXtEg5f+Q2CpssydOGL/8ypYweSzyuA8iugcKmUVG47CnXPprP6x5p/FpReJsdG4Qaof3589LNRSo1revZBKaWUmmqCF+TaUzWw8bFkzea+ypLllYLLa+0hM5xCNZxqtS6aM9T+MCNYRk0ppZRSSqlh4yqSTHbThI4TY701g+OfCb7pyd4qOyER5Z5bruOlpZ+wDCswAiR++3bCkWR2iW8GlKyFwhUQaYbOM9C4VYIyifgYvJEMngrJ+LG7IdouWTsTpXScUmpMaCBGKaWUmkoirRJYMezgqRzYc2Ltcm0JxBy1jimsHrkMk0QMwo2carH2h5lTlmPQJ5Xh49RAjFJKKaWUmiBSWTGdp2X/eCIpWiXHErGgNLoHrnrdP7Gz8CbLsMWJ43gO/S+JRDLzvmARFK2AwiUQD0DgArQdgtonJCA11gEZVyGUXw3OfMlUqn9+/GTtKKXGHQ3EKKWUUlNJqiyZpwJsAyzrFWmRa2dhellmRsxg+sN0nJIZbabZ71BAyhGYCY42W3db5pblmhGTCixpIEYppZRSSk0QngqZSJSIQeBM/+PHE5sDStbJpK3gReg8g2Gzsezvfsg52wzL0Lvjj/Kd732DHz9/khP1HZj5C6VfTN58sDmlFFgsCC37ofbJwR1XjASHF8qvlIylREyydjrPjt32KKXGLQ3EKKWUUlNJqiyZt3rgz0kFYlxF6WWZgZjC6oFlmLTsg5a9MhOucTvEI/0/J1iDacKxZuvihZX5/T83m1RGjAZilFJKKaXURGEY6ayYjhNgJsZ2ewbLVQgFS+R2636IBfH4C3G+8WeEsPaLeXfz1/jVA49y/X8+zW3ffJaX2yqgYDG4y8BdItkxiZBkoTTvgfpnIdw0Bm8qyeaEssu7lWDbDW1H+n2aUmpq0UCMUkopNVVE2yQIYdhkRt1AxIKQiMiBXyojJpGAhmPWcUXV/Qc2WvZDx0m5bdggVAv1z0jN596YJoRqudgB7WHrTLdFuQRiEvFuPW80EKOUUkoppSYQ3wzpSRILpjPdJ5K8eRJIScQkWAFULlzHuQ2ftQzLN4L8wPlVimnjUE079/5gKycj06VnjN0n+/E2F5hxCcaEW6QsWNNOiIdH/W0BcnxTvAbyF8j9tsOyPWNdPk0pNW5oIEYppZSaKgLJbBhPhZQHGIhoi1w7C9L9X1rPysFfd/0FYloPphuLFq+GiqvTdaLrt6QDNJnCjZCIcqTZur15bgfVhZ6BvYfu4slsGJsT7K6+xyqllFJKKTWeGDbwz5Xb7cf6HjseGQYUXyL9KsMN0u8GWHDr+zgz427L0Nm2Or7r/C8cxGgPxXjvz3fQaa+Eyusgf76sI3UJnoP2o9C0Cy4+Jn0xx4JhQOFSKF4ltwPnof659EQwpdSUpoEYpZRSaqoYSlkyZ1F6WcNR6xiXD7yFvQdi2o6kDxSLVoJ/lgR2Kq4Gb5WUVWjZJ2UFupdYCNVD00sAHG23rntBRR6GYQz8faREO5LvJ8eyZkoppZRSSo0l/2yZVBVtg2DtWG/N4Dn8EqwAyZiPBcAwmPW27xOdtsYy9Ar7AT7n+Clgcri2nU/8/mVMww6Fy6Bik5QCc/jAN1OOcUI10qPlyHeh5kkI1Y1NCTf/bCjbKNlL0Taoe0aObZRSU5oGYpRSSqmpINrerSxZ5cCfN6D+MFXg8GTPMEnEZHYaQNEKyJuTfszmhNL1ULRcZox1npHsmHgI2o/LQVQiCq5ijrT6LatdVJljWbFYMhDj8Pc9TimllFJKqfHI7gL/HLndPkH7kPjnSHN7My4lykwTnF543c8JOostQ+91PME77Q8C8MDLF/nBs8lMeme+lCqrukUmeJWshfKr5LglHoDap+DM7+Hi4zIxLB4a1beIuwQqrpHtSUTl2GYiZjEppYaNBmKUUkqpqSCYQ1ky00yXJusrEFNUDY5eMkzCjTILzeGHvLnZx+TNg9INEpiJNMvstdYD8vr+WVC+kaP11lJoCytyzGjpCsRofxillFJKKTVB5c2TklyRlomZaWEpUdYIncngSv40ts37EKbDWoL4X52/5AP2PwImX3roIH97+aJ1Xa4iKFgElZtg0Qdh2o3gLpefTes+ObaoeRyadsjrjRa7B8qvlGMa05RyzU07tG+MUlOUBmKUUkqpqaCrLFnVwJ8TD0hGi2GzBi4yS5MVVYGzl8BGOHlg6Cnv+7U85TKTzZknM+MMQ8qYFa/GxOBYXYdl+MIhZ8RoIEYppZRSSk1QdreUvwJpCj8ROXySGQ8SoIi2AdDim0f8rm/1GP5R52/5tOMXmGaC9/9qJx//3R46wrGe67W7JCAz81VQsgZcJRA4JxkxgQuSgV+7GTpOybHOSDNs0iOzaGWyb8wF7Ruj1BSlgRillFJqsou0SG+UXMuSOQvluSk9SpP1lRGTDMS4+wnEgGTNlF8tNaPLr+wqY3ahNdTjIGtRZY4ZMVENxCillFJKqUkgf77so0eaIdQw1luTG/9s8E6TDPqmnV39XMxlr4IbP9dj+LscD/EVx/dxEOM3L53j9m8+y47Tzb2seyZUXAW+6mTQygauQsnCibZDy16oeUx6VUY7sq9jOOXN6dk3Jlgz8q+rlBo3NBCjlFJKTXaBc3LtrZLyXwOVrT9MsBk666zjiqqzBzZiwWQAyJAa0ANhc0D+AnCla0MfqW23DMl3O6gq9GQ+s3+xYDrbxuEb/POVUkoppZQaL+yedFbMRO0VA1C0OhmcaIe2g+nlV30Ybv8qYFiGv9bxDI+4PsH1tp2caerkdf/9Ao8dqM2+bldxsk9LoRwHRdvANwMKlsgksEQMOk5KP5n6FyQwYpoj9lbTfWOKk31jtktASEuVKTUlaCBGKaWUmszMRDoQ45s5uOdm7Q+TUZbMsENBhTTLzJTKhnEVDy4AlOFoRiBmQWUehmH0MroPyXIHOPKtGT5KKaWUUkpNRPkLZL823Di6vU+Gk90l/WIAo/MkLrM1/dhl74ZX/48cc3Qz33aRH7m+ys+dX2KxeZKP/GY3F1qsPSXT6/dA2ZXgmy5Bls7TEDgNhcuh7HLJyDEMCDdIYKTuGSkfNlIBGbsHyjfK7w6kRFr9sxKIUkpNanoWQimllJrMQrUy28ruAXfZwJ9nmhBJHgQ5i9LLM8uSFVSCwyuz2DJ1lSUbxOtmcaTWWipgUUWuZcmSgRhnwZC2RymllFJKqXHB7pFG8DBxe8UAeCq6yhIXJk5CPJx+bNVr4Q2/AkfPjPir7ft40P1Jfp34GE/+6FPEm89kX7/NDiVrofRSOXaJBaFxG3SegsJlUHkD5C+U7PxoGzTtgLqnR650mGGTcsxll6ezgeqekSCRUmrS0kCMUkopNZl1ZcPMkJleAxVrlzJeNoek7afUZxzgFVVlz4YxTQgNoj9MH47WWQMxCytz7O8S00CMUkoppZSaZPK6ZcWE6vofP14VLANHHjYzgtGy25qRsvhWePtDUL0m61OX207z5rYfYv/mSvjxHbD71xDp7DnQOw0qrktmEhkSaKndDB0npOfOtBuhYFGyjFl7unRYsnfNsPOUQ8UmCUSZCWh+GRpfkol0SqlJRwMxSiml1GQVD0tGDAy+LFmqP4yzyBrAqdlrHddbf5hoqxxA2ByWfi+DZZomxzJKky2szDEjpivDRwMxSimllFJqknB4IW+u3G49OLI9TkaSzY5ZvA4Tm2TWtx+zPj59LbzrSXjVf0N+de/rOf0c/Om98NXF8Jd/gIt7erwOhUutAZCOE1DzBATOQ8FimHaDBGZASofVPSu9L0eC3Q2ll0HRcgmoBS9KNk64aWReTyk1ZjQQo5RSSk1WwfNyIOYqAucgs0hSgRhXYXqZacKFXdZxZXOzZ8SEupUly6WfS9L5liCdEWvzykW5ZMQk4hBLzorTQIxSSimllJpM8hemm9EHz4/11uTOmU+bbbbcbj/cs++NzQar3wAffAmu+xQRbx+Z95F22PlT+O9r4GevgONPWYNUznwo2yAXZ75MImvZKxkpGFKyrOxysLnk51r3jARqRoJhQN48KL9SqhHEglD/PLTsl+MYpdSkoIEYpZRSarLqPCvXg82GAYi2yHX3/jBNJyDUYh1XPg8cWQIx4WEqS5bRHybf7WBaQc/60P1KlSWzu7P3s1FKKaWUUmqisjnTzd/bDo1cKa1RELKVY/pmSNCkaYe1X0yKyw+bPo7rY4f532Xf4f7YtbSavt5XemIz/PyV8P1NsO/3EI+lH/NUSHaMJSPlGQm+eMqhcpNMLjPj0LQT2o8P91vu9r6KoOIa8CeP3zpOaHaMUpOIBmKUUkqpySjaJhfDBr7pg3uumZCayCAHAymZ2TDeAvCX9ixNlohBpFlue4YWiDnSoyxZHkYuGTZR7Q+jlFJKKaUmMf9csHskm6Lz1FhvzdAUrpQslXhYgh+9BZZsdl79mjfxq2kf49Lw9/j7yIfYHF9NwuzleOHiHvjdO+Db62D7DyAalOVdGSkbpdRbrBPqnpMMGLtHMmPy5snY1gNyGSk2BxRfIpk6do9si2bHKDUpaCBGKaWUmoxS2TCeSpkhNxjRNjnYsbnA0W1mWbayZHanHKx0F26U5zt8klo/BEcyMmIW5dofpisQU9j3OKWUUkoppSYim136mwC0HZnYDd8NO5Ssk+twAzTv6rX3jdNu45tvWIPd6eGhxAbui36CK8P/xXeN1xP3lWVff/Mp+NtH4Bsr4ckvQNsFWe4qhvJrZDJZKgOm46QEaoqWS28ZkKyY5t0jm3nkqYDKa8E/S+5rdoxSE54GYpRSSqnJxjTTtaFzKUuWqsXsKrYuP7/Ter9sXs9sGJCDJRhyWTKAY3WZGTFDDcRoRoxSSimllJqkfDPT/U7aj4711gyNMx9KL5UM/8AF6d/Si7llfj5797Ku+xcp5SvBV/Du4h+TuOPrUDw3+xM76+GZr8DXV8D/vgVOPiOT2Eo3pDNgWvZBW/Jnmb9AslUMQya+Nb40slkqNicUr9bsGKUmCQ3EKKWUUpNNuFHS+G3O3EqDpfq7dH9uIi6p/N2Vz5MDpB7Pb+j5/BwkEiZH6zIzYrIEfvpjmhqIUUoppZRSk59hQEEya6PjRLrc8ETlKYfiNXK78zS0Hup16OvWz+TW5dMsy5483s6PQtfCB3fAa38CVZdkf7IZh4N/gZ/eBT+6Fc5ulQyYrgyjQ+nX9s+EkmSAKFQLDS+MfPZR1uyYpyBYM7Kvq5QaVhqIUUoppSabVDaMt0oOEAYjEU9nxHTPaGk4AtFO69hsGTGJOMRS/WUyMmoG6XxLkEDEOtNrYUUOGTHxgPStMWzZM3iUUkoppZSaLLyV4J0mk5FaXu61pNeE4auG4lVyu/2oZKdkeU+GYfClV6+kssBtWf6Vhw9zrCEIy18Ff7cZ3vpnmH9976939kX40S3w6zdB2ITCZenXbtknt72VUHaFTHyLNEuWSjw0DG+2D92zYxxe6QXUuB0atkEsMLKvrZQaFhqIUUoppSYTMwHBi3LbO33wz480Jfu7eMHZLWiRWZYsrwx8heDICIzE2uXAyOaS9PkhOJpRlizf4+hxYDUgXdkw+TJLUCmllFJKqcmscEWyv0oTBM6O9dYMnX82FCyR222HoHFr1sBHsd/F1153iWVZJJ7gp1tOyR3DgHnXwlv+CO99HtbdB04fWR3+G3z3CtjxWyhcLss6TkJzMrjlLoHyK+WYJ9oO9c9BtCP7uoaTpwIqroP8hemsnNqnpC/QSPasUUoNmQZilFJKqckkVC+p8XY3uEtzeH6dXGf2d7mwy3q/LFlnObM0WSro4Soc/GtnOFKbWZYsHyOXQIqWJVNKKaWUUlOJwwuFycBF6wGIR8Z2e4ZDwULJjDHscsxTuzk9Aa2bKxeUcd/GOZZlf9lzgXAso6fKtBVw1zfhI4fgtq9A0ayer2nGYfOX4E8fAfdsWdZ5Glr2SDDGmQ/lV8kEtlhQgjGR5uF5v32x2eX3W7EJ3GUSgGk7LD+TUP3Iv75SKicaiFFKKaUmk+AFufZW55b9keoP0yMQk5ERUzZXZmDZvdbl0Va5Hoagx5Faa0ZMTv1hQAMxSimllFJq6vHPlf3fRBTaDoz11gwP/2youEYmfSWi0PgS1L8AgfOW5vXvvGqu5WmtwShPHKzLvk5PIWx4D3zgJbj1y+DLMpnt+JPw8zdAyC7HWJ1noXmXBGMcXii7ElxFsk31L6Qnt400Zx6UXwElayUzJ9YJDS9C0w4tV6bUOKSBGKWUUmqySMQhlGzY6MuhLFk8lG7o6S5LL49FoGavdWx5sj9MZrCnK+gx9IyYY3XWjJic+sPAsG6TUkoppZRSE4JhpHurdJ6FUMPYbs9wceZJFkr+QnmP4QZo2gk1j0LzHgg3MbPEx4a5JZan/W7Hua7b8YTJ73ec43+eOcH5lqAsdLjh8vfCP+yGqz8imTfdtZ2HX70Fzp2S1w2ch+adko1id0nPGE+5ZNE0bpPHR4tvOlReB3nzktt2QcqVtR6U4JBSalzQQIxSSik1WYTrpCm9wwuu4hyenzw4cxXJwURKXZZyBmVze5YlM81hyz5JJEyOZilNNvgVRdOzwTQjRimllFJKTSWuYskiAcngmAwlykAy8wuXQOX1ULAYHD45Duo8A/XPQ82T3LPcaXnK00fqqWsLYZomH/3tHj7y2z184cGDXPfVzXz54UO0h5IBC08B3PB/4L4HIG+a9XUTMXjoU3BoO5AMeDTtkGCMzQGll0lQxDQlONR2dHR+HiCvX7RcMoZS5craj0HNk9LbRvvHKDXmNBCjlFJKTRapWVfeHLJhoI/+MBllyQqng9sPjozASDwgByeGTbJlhuB8S5Bg1FrHOafSZKkMH4cXbM6+xyqllFJKKTXZFC6TLJJ4KF1Oa7Jw+KBgkQRkyjeCf6ZkssQ6ub36Ij5n+r3GEyZ/2n2e3+88zx93pbNVIrEE39t8nGv/YzO/3HqaeCL5nNkb4T3PwJyre77us9+AnQ+CCQRroHG7BDoMGxSvkcwUgLZDEpAZzSCIs0DKlZVtkIlziQi07Ou1p45SavRoIEYppZSaDBIxCNXKbW/14J9vmumMGE9GIOZ8RiCmPFlzOTPrJtKtP0wu/Wm6yewPU+BxUJ7vHvyKUj1rHJoNo5RSSimlpiCbA0rWSZAgVAcdx8d6i4afYYC7FIovgaqboWQN/vxSbptvHfbzF07xmT/vy7qKxs4In/rjPj722z3phfmV8JY/wcYP9nzCzl/Ccz+HeFx+ro3bpFS0YUhmSvGqdAmz+i0QDw/b2x0QTwVUbJLtsLulf0zjS5IxFGke3W1RSgEaiFFKKaUmh1CtzLRy+KV55WDF2uXgwLD3DLBc2G29XzpbDipcRdblw1SWDOBIlrJkRi7BnWHcJqWUUkoppSYkZwEUrZTbbYcg3DS22zOSbA7wzYDyjdyzcZXlobPNIToj8V6eKP6w6zxnm7o1urc74ObPw61fBjKORw4/Ao9/ByIhCNVD44vpniz+2VB6uWTlR5qh7hmItAz9/Q2GYch2VF4vmUOGXX73dc9Bw7b0RDql1KjQQIxSSik1GQQvyLVvqGXJymS2XEokID1iuiufKwdzNod1eSr7xJlDICjD0YyMmIW59IcBDcQopZRSSikF4J/VrX/JjsnTL6YPGxbMZEaxt9fH71hexo1LK3ss33ykvufgy98L9/zI2ksT4Ow2eOg/INguQY765yAWlMc8ZVBxdbo0XP3z0sdmtNkc0ktn2vXJ8m2GTOSre0bKqmlARqlRoYEYpZRSaqJLxGUGFoC3Krd1pJ6fWZasZi+Y3WaNGTYonQOukp7rSAU9csnIyXCkzhqIyak/jJkY1m1SSimllFJqQitaJRn08ZA1e2OSstkMXrN2RtbH5haafOXKOn5wp8ndK63HQE8frsu+whWvhnt/B66MSWL1h+Gv/xfaGiDaIcGYrl6Vfii/CrzT5PikeY9cRrNvTIrdI+XbKq+TrCHDkB43qYBM6thJKTUiNBCjlFJKTXSRRgmW2D25ZX4k4hBJlidwZwRizm233i+eAU5Pz/Jl8bAc0AE4csxeSW1OwuRYXc/SZIMWbZMDHJsT7L4hbZNSSimllFITns0BpZeBzSVZEI3bpNfkJJYtEOOwGXzj7jL8bglEXD+t1vL4luONhGO9lDCbtwne/iDkZWTStF2Av3wWGs+ls19SJeBsTihZDwVL5H7nGXk8FmBMOPxQsgYqrk1XVAjWQO3T0kdGAzJKjQgNxCillFITXSh54ODpmVY/IOGGZH8Zr6TNd3fkYev98nlynRmISe2sO/w9S5YN0rnmIKGodYbYwlwyYlJNKF3FMttLKaWUUkqpqc6ZB+VXSHAg3CSZEEPJzoiH5CR+6yFoeBFqnoTWg+MmwDOr1MfG+aWWZf940yJWL788GYiYwdWzDQzMrscDkTjbT/bR0L5qFbzzMShdYF0eaoG/fhbOH5Zso4YX5GcDcjxSsBDKUn1jWiQTJXhxON5mbpx5ULIWKq8FX7UsC16UgEzDVgg3jt22KTUJaSBGKaWUmuiGGojp7fmBJji9xbps1hrJvHFkZJik+sMMR1myjP4wRT4n5Xnuwa8oleWTrYyaUkoppZRSU5WzAMo2yASqcINkQST6bmLfQyIOLfuh5nEJ5rQflXLHsU5oPwa1T0Hgwshs/yB9/pUrWFCRh9Nu8JbLZ/PeTfPlAWcelKyhdM51rJpm7f3y9L7Dff9MimfDOx6F6euty2MhePgLcHyHBLiaXrL2hfGUQ8UmmSyWiMrPvmXv2JQqS3HmQ8k6qNwkARnDkB6i9Vug7jkJzphm/+tRSvVJAzFKKaXURBZtk2aQhh3cZbmto7dAzLHHrf1hHG6oXt4zGya1HQCOHEqjZcjsD7OwIg8jl4yW7hkxSimllFJKqTRXsZQpM2xyPFD/zMBLUoXqoW4zdJyQE/TOAvDPguJVkmHh8EmmTNMOyZJJlTAeI/PK83jsH6/h0P+9jf/7yhXYbRnHFg4/m5bPsSzafLQZ6p5O93rJxl8Kb/sLLLzZutxMwFNfh71PQCLZF6btSLfX80L5RshPZtR0nIK6Z/t+rdHgLEgGZK4D/2z524g0S7Co9ikJKI1lwEipCU4DMUoppdREFkwGUdxlYLMP/vnRNjkwMuzgsqbsc+hv1vsz12bvDwPDmhFztNbaH2ZhLv1hYsFkgMoAV9GQt0kppZRSSqlJx10qpbLsHmkyX/dsOriSTbQNmnZJcCUWkIBC2QbJpCheLSfvfdPlRH7B4mSQp17KXI1xqTLDMHoGYLq5drG1V+bRJoPzzZ1Q/1y6vFg2Lj+84Vdwyb09H9v6Y3j+FxCLQNthaN6dDmQYNihcmsxMcsnPtu6Zvn/+o8Xhl6DatBshf6GUUot1SkCp5nEJKsXDY7uNSk1AGohRSimlJrJUNos3x7JkvQVyYmE49oR17MxVybEZpb4ScdkxB3AOf2myRRVD6A/jLBhyzxqllFJKKaUmLXeplMryTpMgQct+aSTfehAC5yVAEDgnJapqn5bbAHlzpceKp6LnOg0bFCyS3iN2dzKAs2PsAwx9WD2jiGKf07Js8/k8CSA1bpdASm/bb3fCK74DV3+052OHHoGH/xMCLdB5VvrGxCPpxz0VEsjyVKR//o1bxzyLCJDfXeESCcgULZfAWzwsP4uax6Fpp/QZUkoNiAZilFJKqYkqHk4HHIbaHyYzkHPqWYh0D4gYMGOlHFRlBlti7XJQYnfLZQjiCZNjddaMmEW5ZMRofxillFJKKaUGxu6C0kuhaGW6HFX7MTnRXvu0ZMFEmiXb3FsFFVdB0Yr+Jzw5/N3Kn9VB677ReT85sNsMrl5ozYrZfCEf8ubJnbYjyWBSL6W5DANu+Fe4/atARuZNzX74y/+FhtMSuKjPKENm90hmTOrnH6qH2s3poNdYsznk51B5vZSec5fIzyFwXoJ2dc9I2bLB9hlSaorRQIxSSik1UYXq5NpVKDvvgxWP9B7IOfyQ9X71KvAVSRDGyNh9SJUlcw69P8y55gDhmPXgJqfSZNofRimllFJKqcHJmyNlxYpXyW13iZyEd/igIJkZUbp+cPvYriI5eQ/SC6XjxPBv9zDJLE+25VgDkbylULJGjoGCFyU7pq+Aw2Xvhjf9L7gyjmE6auGv/wbHXpCybvXPpasTpOTNkewkVxEkoskycNvGR3YMyM/ANx3Kr4SKa6QvkGGDSGuybNlj0HogXS1BKWWhgRillFJqokpls+SaDRPuJZBjmj0DMXM2yHVmWTKQHW8YprJk1myYYp+TsjzX4FaSiHfrWaMZMUoppZRSSg2Ywye9XopWygn36ttg2g1QsDC3yV8gWTSFy+R2y/70hLJxJjMjpjMS56XTTeCbkczsscu2N27rOxiz6BZ41+NQPNe6PB6Gzd+BLb+EaFDWkxmYcuZB+VXSP8awyTFf7WbJOBlPXIXSF2jaTfK7dfgkeNR+HGqelEyZzrNj3htIqfFEAzFKKaXURGQmIFwvt4dalizz+Rf3QNt567JUf5hss9+iwxmIsfaHWViZj2H03lQzq2hLslSaR+oYK6WUUkoppcZW/nzJoADJ9IgFx3Z7sijPd7NyuvWY5unDqWOucikfZnNAuAEaX+w7yFCxBN79JMy5uudjBx6CB78MHQ0SmGreYy15ZhiQv0CyTlLZMc17oH4LRDt6rm8s2V3yu628XoJVnkrZ/nATNO+WLJnmPemKBUpNYRqIUUoppSaicKPs+NvduQVAzER6JlqPsmQPWu8Xz4W85GtkBmLMhDTfBJkVNURHMwMxFXmDX0mqYWS27B2llFJKKaXU2ChaKccMiQg07+y938oYyixP9tjBWkzTlDvuUii7HGxOOeZoeEGCJL3xlcBb/ggb/r7nY7WH4E+fgbO7Jdul4UXJmOnOmZ/Mjlkm2TjhRqh7GtoOj7+fnWFI39Gyy6SEXcES6RGUiMn7q3sOap+SjJnxUmpNqVGmgRillFJqIuqezTLYjBGQA4feAjmZgZgF18lrOHw9yxHEOuQgwOaUHe0hyixNtkj7wyillFJKKTU5GDYoWZ8OZLQdGust6iEzEHOivpNH9nfr5eIqhrIr5D1EWiRLJR7pfYV2J9z27/CaH4LTZ30s1AqPfBW2/RoCtdL0PjWpLMUwkhkn18mxn5mAtiMS1AjWDO3NjhS7R0rZTbseyjdKaTfDLtk8rQfg4mPyc+s83XcgS6lJRgMxSiml1EQUSu50D7ksWYU1kNNyBmr2WsfOWSfX2QIbkRa5HoayZPGEyfF6ayBmYeUgM2JMEyLJgxftD6OUUkoppdT44vBB8SVyu/34uAsmrJlZzPxy6wSzbzx+hETCTC9wFUqAwe6W6gANW3pms2RaeY/0jSmZ1/Oxl/8Gf/uiHIs1bOnZNwak5HLZZVC6XgIdsQA0bof6F9IVCsYjdymUrIGqm6B4VbpqQbgRml+Gi4/K+whc6LvvjlKTgAZilFJKqYkm0io1lQ07uMv7H59Nb/1h9v7Wet9bDMXJ1/BWZdmWFrl2FeW2Hd2cbQoQjllT7AedERPrlFlVhh2cBUPeJqWUUkoppdQw806DvGRAonm37MOPEzabwYdvXGRZdqimnYf2ZQSMnAVQtlGCItF2aU7fX8mtyuXw7qdg6d09H6s7An/4NBx5Fpr3QdOO7D1ovFWSHZO/UDKMwg2SSdP8ct+ZOWPN5gT/bCi/UkqXFS6Vn6GZkGBc0w6oeRSadkLwogZl1KSkgRillFJqounKhikHm33wz4+2y8GOYbMGckwTdv3COnbRTVLD2eYAd0WWdbXK9TBkxBzJ6A9T4ndRluce3Eq6smGK5P0ppZRSSimlxp/CpZJxn4hC47a+G9+PsjtWVrEoIzP/G48fId49KwbAmSeZMQ6vHF/VPy+ZKn3xFsHrfga3f1Ua3XcXDcDT/w+e+g40H4X6Z6WcVyabAwqXSEDGVy3HcZ2nofZJyaYZb/1jMjm8kL8AKjdB5bUSVHL45G8gcB4aX4KLDyczZc5p+TI1aegZCqWUUmqiSaXvZ8tQGdDzL8i1u1x24lNOPw9NGWnwi6+Xa09lz6CPmUinwQ9DRszOMy2W+5kHPwPS1R9Gy5IppZRSSik1bhm2dJmtaIdkQphm/88bBTabwT9mZMUcrevggZcv9Bzs8EPZlXIdC0hpsf4yfAwDLnt376XKTrwIf/gknHxBgjGBLK8LErwoWSfBIGeBBCxa9kPd05JVMhE48yWoNO0GqLhK+uE4fN0yZXbBxUeg4UUJNvWXdaTUOKaBGKWUUmoiiXVK8MMwcu8PkwrE+Kqty3f+3Hq/bBEUJQMa3uk91xNtlx1km1N2lofopVPWxpTrZ+cQTAk3ynW2fjZKKaWUUkqp8cPugdJLJSgTqoX2Q2O9RV1uWT6NpVXWUsfffPwosXiWbBOHNxkMyZMS0vVb5FipP1Wr4T3PwCX39nyssxEe/jJs/h5cfAZa9vWe6eIuhYproHg12FwS2Gp8SUqWheoG8G7HCVcxFC6ToEzlJihYJIEa04RQfbKnzGPyvtoOS5nscRK8U2ogNBCjlFJKTSSp3i6uUgmADFa0XXbMDZs1kBNqhQN/to5d9ZpkWTKnlEHrsa5kWbJhyIYJReO8fK7Vsmz9nEEGU6Id3UqulQ55m5RSSimllFIjzFUExZcAYHQcx5NoHNPNSZGsmIWWZScaOvnLnl6yU+we6RnjLJCsjfot0tuzP+58eOV34bU/BU9Rz8ePPA2//wTs/x3UPdt7gMcwwD8Lpl0vAQybQ16/YSvUPQehhv63ZTxxFkDBYildVnkdFCxJH3dGWqHtiPw8ah6TPkPBi1rCTI17GohRSimlJpJUirl3Wo7P716WrFsgZ+/vZPZWis0B869IvlZV9n4rkRa5Hob+MHvOthDpNrvMZsC62YMMxKR+Nu4ya8k1pZRSSiml1Pjlmy49Q4DCxMl038cxdtOySlZMt2bF/PzF070/we6GsivAVSgT2hq2SCbHQCx/Jfz9Fpi7qedjgRZ47Ovw6Jfg9ANSoqs3NmcygHGDlPky7FK+ueEFqH8BwuPjZzsozjwoWAgVV0PVzRK481bJMV88DJ1nk31lHpE+PW1H5H1qtowaZzQQo5RSSk0U8XC6B4pniIGYzLJkuzLKki26FYxk/V1vxtiUaItcD0NGzEunmy33l1YVkO8ZZMZPKNU7J8efjVJKKaWUUmpsFCxJHuMkMJq2Z29SP8oMw+AD11mzYvZfaMtenizF7pJgjLtUms83bpMG9ANROB3e8ie442vgyu/5+PEX4Hcfg5f+Gxq2QTzS93YULpMMmby5MrEu3CCBioYX0yWdJxq7G/wzpb9Q1S3ys86bJz16TFMCMG2H5X1efBgat0PHqf779ig1CnS6qFJKKTVRhGpl59JVKHWIB6u3smQ1++DCLuvYFXcny5K5JMMkk5lIp8UPQ0bMtpPWmVmXzhlkf5h4KJ2hk2uQSimllFJKKTU2DAOzeA1RY7OUmGp8EcqvkpJfY+jyedbjkkgswYmGThZVZgmUpNicUHY5NO+CwAVo2gmJsAQM+mOzwaXvhEW3wF8/DMcesz4eaoenviNBmaveBbNuAU+W47UUuweKVkDefGg/AoGzkqUTqpeeLPnz5fjJMPrftvHGsMl795QByyEWgHDyvYUb5O8oWCMXkJ+Fu1SOb92lErxRahRpRoxSSik1UaR2ID1VOT6/l7Jkmdkw+VVQNV9u+6qz75RH2yUYY3OCw5fb9iTFEyY7MzJiBh2ISf1sXMUyS0oppZRSSik1sRh2mm0L5QR5LCj9TRKxMd2kIp+LqkJrMOjgxbb+n2jYoHitZKMAtOyXy0DLZRXOgHt/C6/8f9l7x5zZCf/7IXj0Y9C4S47N+uLwQvFq6bfiny3bF2mWkl61T0Hnmf7XMd45fPLeUtkyFVdLppW7TN5vPCTZSc17oOZJuPgYNO2QjJneeu8oNYw0EKOUUkpNBImYzO6BofeH6V6WLBqCl//XOm71G7u91vTs6xrGsmSHatpoD1sPsC6dM8j+MFqWTCmllFJKqQnPNJyYJRtkclW0TUp7jXEwZsk0a/bLwYsDPGlvGJKNUrhU7neckFJZA30/hgGXvBHevw2W3tXz8XgUdv4BfvxaePEr0sS+Pw4/FK+CaTdC/kKZWBfrTAYnHof2Y5Oj6b1hyLFqwUIovwKqbpUyZgWLJBumKzBzAVr2Qu1muPCIlHxrOyql2xLxsX4XapLRQIxSSik1EYTqZIaSww/OPtLgexNty16WbN/vIWjNRmHZrXJwYPdIhkk2qTJgzqLBb0uG7RllyWaX+qgoGEQJgkQ0XePYm2O2kFJKKaWUUmp8cPigdIM0Yw83Sr+PeGjMNmdpVYHl/oAyYrrLXwAl6+RYLFQLDVsG937yK+H1v4DX/hT85T0f76iHR74EP70dTj06sMwWuxsKl0hApmi5HPvFw9B6UDJFmvfIMeRkYbNLCbOCxVC+Eapvk+uCxcmMGbuU5g7VQtshqN8CFx+CumckUBM4LwGrgWY0KZWF9ohRSimlJoKOE3Ltre57XG+CF+XaU5EuS2aasPV71nFzrwFnHMKAb2bvtYKjydlWrqH3h9l+aohlyVJBKmee1vlVSimllFJqMnAVQtlGaNwqAYG6Z6FsAzgL+n/uMMsMxByqySFA4auW8mAN2yRzpe5ZKL1scMdTy18J8zbBU1+E7T/oGXA5vw9++gZYdRfc9EXI66W6QXc2h/Su8c+RCgrtx+Xn3XlGLu4SecxbJYGkycKwJfvFlMp9MyHvO9IkJdsizVIeL9KazDQ6JeNsTumR6iqUSYmuQj0GVQOmgRillFJqvAs3yo6gYUvXGB6swHm57p4xcvp5qNlrHbf+Pnk9w5D6utmYiXQN3SFmxJimyfZT1oyYywYdiBli7xyllFJKKaXU+OMqhPKrk8GYdsmMKVolk9NGsbn80iprRYLatjBNnRFK/K7BrchVLH1LGrdKtYL656D4EvANIGCS4i2G2/8D1r4NHvq4HNN1Z8Zhz5/g8JNw+bvhyo+B09v/eg0b+GbIJdwInadkMl+4SS42lxwf+mdLQGmyMWxSyqx76e14SN57KjATbU1WY2iQS0pXcKYofT3EPqpqctJAjFJKKTXetR+Xa9/M3BrRh+oljdrmAE+3HiovZmTDFM+FqvkQOCvjetvBjrZJMMbmGvJO+JmmAHXtYcuy9YPpD2MmJCMGtD+MUkoppZRSk43DC+VXSm+VcCM07QTHIcnS8M9KZ/unJKIStIl1yDFQIgpmLNmXJSElqLouDjm+snvA5pYS0PaeJZLnlPpxO2yEY+kMlIMX27hyQVkO78cH5VdB0y4pg9W0U46vCpYMLrg0bQXc9zcpNf3op6H9ovXxUBts/k/Y8XO47pNwyVulPNdApDJF4qFkZsxpud1+FDqOgbtcjk290yZXlkwmu0cymVI9Vs2E/F1FWiQoE2mR312vwZl8yeByFoAjedump+KnMv3tK6WUUuNZtF120AHy5+e2jo6Tcu2bmd7xazoJh/5mHbfh7yQdHfrOvBnGsmTbMvrDlOW5mFs2iNTucEO6n41z6NujlFJKKaWUGmdsTii7PBkIOAWxALQegLbDycCJKZdEXPp8DIUzTwIN7nLpHWKz47DbWDwtn5fPtXYNyzkQk3o/pZdKL5L2Y3KJtkHJ2p6Bpb4YBqy8BxbdCs9+FbZ8W4IC3bXXwV8+DFu+BTd+HhbfNvCAj90jze3zF0oVgo5TcvwVqpOLzSnZPL6Z1kySycqwpQMrKalqEV2BmRa5n4ims4m6c/jSQZlUoMbhn9wBLdVFAzFKKaXUeNZ+TK69VbnVno11pgM53YMr2/4HOWBJchfAoqshcEp2CFO1crNJ7UzmWpYsWCsBIXcpL2XpD2MMZiZYqveNd9qolidQSimllFJKjSLDJo3V8xZA8Lz00Iy2y/FOJodXTnY7/JLFb3NI9othkxPnZkyCNmZUGtTHQ5AIybqiHXLpOCnZMgVLwDeTJT0CMe1DfD8GFC6VE/HNuyWwUfeMBGgG2wfHnQc3fhbWvAUe+RQceajnmIbjcP8bYcY6uPmLMOvywW2rt0ousU7oPAvBc9JDpeOUXJx5EpDxzciaVTRpGTaZoOgqlAwtSGfORNuSl3a5jockiBgLpI/RU+tw+MGRJxdnXvq2ZtBMKvrbVEoppbqLdsgOuc2dvAwwfXskxIJykAGQvyC3daSyYTyV6UBOqA12/sw6bs2bIVIvt/vKhjFNCCfHuQc5AyzcJDPXIsngi3822081WoasH0x/mFgAAufktrd6cNuilFJKKaWUmnhsdjnh7Z+VLAsVS07IMuSEtt2X+8nrVImpUL2cKI+HoHkPdJ5iabl1otrBi21Dfy8gGSWOPGh6SY5v6p6VPjj+mYNfV+l8eNP9cPoFePyzcPbFnmPO7YAf3QLzr4NrPg6zNw7uNRx+KFwiQbFwo5S1Dl6U4+jWg3Jxl8r78lSBfZB9dCaDbJkzkCyblxGcibXL33C0Pd2HtTu7p2dwxpEny3Ui4oSjgRillFIqEZUT+oGzEGm1PmbYZQfKXSqBB1fx6M1K6TghgQ93aW6p3omYvCewBld2/woi3XbyDBtccg/ELkh6uXdG7+uMtcusMcMO7gEGTVKlA1LZK4YdzDj19ac50WBNwb5sMIGYtsMy28hd1ncGj1JKKaWUUmryGWzmSH9sznTmh5mQhvVthyHSylJPK5A+djlW10E0nsBpH4aSUq5CqLhG+sWE6iRDJtIEhStymxg4+wp4x8Nw5BF44nNQd6DnmONPyWX2Rrj6ozD/+sGd2DcM8JTJJbFSSlwHzibLcTXKxdgrx2reaulBOhWDMt3ZnOn+OymmCfFgsqdRMhsrdTuVrRUPWfvPQDKLxieBR4c/eTt5raXOxi0NxCillJq6TBNa90kDQjPZeNGwyeySeBjMuFwizXJpPyY7nM6ikQ/MxEMQOCO3c82GCZyRYIwzDzzlyfXGYOv/s45bfDs4YhAj2Uemj539UJ1cu8sGtnOXiEP98/J+DEPWX7AYoh08/PQO5EWF32VnaVX+wN5btC2dDVO4bGDPUUoppZRSSqmBMGyQNw+806HtMEtLT1sejsQTnKjvZPG0AR6/9MfmhNLLpA9O22E5Ro00Qcm63AJOhgGLb4WFN8He38JTX4CWMz3Hnd4Cp18N1Wvhmo9JvxnbIE/i2xzpLKVYUIIywQvSMyVULxfjZem7462Sag129+Df02RkGMngiQ+osD6WiHYLznTKpMhYh0x0NBPpMnrZ2D3dAjTJ9du9yYtHAzVjRAMxSimlpibThOZdEEiW/nIWyI6jd3p6pk4iJgGESDNEkrN6YoEsgZkCcJVIUMZVIjWJhyIWgIYXk0GUAvBU9P+cbO+v45TczpuXXr73t9B80jr20renAyx5c/pebyhZliwV2OlP8Jz8DO0eKNuQPoiwe/j9MT+QzkDaNM+LY6AzyloPyrVvuswgU0oppZRSSqnhZndD8SoKvdVU523lQrfz3gcvtg1fIAbk2LJgkRxXNu+Sk+x1z8rEs77KR/fFZofVb4Dlr4IdP4Fn/gM663uOu7BTeshULIer/wmWvRLsOZw2dnghf75cYp1SFSFwXibSheq6TewrkYCMZ5pMHFQ92ZzJcwzF1uWmmew30wnxQDJI0+126jxGPCTnMDIZhpRh7x6csQRqvNqbZoToT1UppdTU0z0IY9hklpF3Ws9xNgfYkvVYUzV6YwHZmbEEZlqTJc2SAQ67R3aW3MngjLNw4DNOou0ShImHZGeodH1u7zFUJzth3UuNxaPw9Jet46rXQFGJ9KLxTkv3kckmEZNZWTCw4JBpQvtxuZ0/3zKT61hdO7vPWsvA3bOgTcqxdQ8cZX1vDfL+DEOya5RSSimllFJqJHnKWDq9lAuH0ye2D54+zSsvqR7+Xh2ecqi4Vo5ZQ3XQsk8mxBVfknt5L4cbNrwH1r5V+oU+/01oO99zXN1++P074bHPwIa/k/He4p7jBvSafqnukL9Ajk0DFyB0UY6dw03JHqIHZZx3mgRlXMXa+6Q/hiEBr94mgMYjEO+UcxWxzmTps4Bcx4OSTZMK1PTG5pDzGqkMGptHXs/mkYmQds/IvLdJTgMxSimlphbTlJq7gfOyA9NbEKY3qbThrsBMMJkh0yTX0VbZoQle7NYTxSY9XlKzWRz5ybqt3XYwTVPW0bhdUpCd+VB2ee47OJ3JoJB/VrrU2J77e2bDXPMRCF2Q2/kL+15nuFF22lJ1Z/sTqk0Hg3yzLA/9bod1p7/Mb+eaWQlo2Q9GMrU9G9OEtmQ2jH/OwLZDKaWUUkoppYZoaXUxT3QPxFxogqaXoHjN8GcQ2F1SUaDjhAQrQrVQ97S8lqcs9/U6vRKQWfd22PNreO7rPY8RAdrOwWP/Bzb/O6x+I2x4L5Qvyv11HX4oWCiXeAiCNRCqSU5u7JQJfO3H5djRUy5lzDwVesI/F3aXXDIzaUCOpxORZPZMMB2c6R6oSURlEmail9Jnxat7P15XfdJAjFJKqaml5WXpLWIYULJ+cEGYbFIzUXzVcj8Rh2hLunxZuEl2dFIzflIMGzjyZIc9HpSdUdOUx1zFstNtc+a2TdG2ZB1eA/zJFPZ4FJ75inXc9PVQMUt6yXjKJVjUl3Ayhd09wLJkHclsGP8cy4FJPGHyx13nLENftXYWjkJk57t5j/zM/HOt/WrMhNRMjrTI+voLHCmllFJKKaXUMFmS0c/yYIMhAYXoM1B6qUymG25586Q/Z9MOOSne8IIcBxUsGlqfD4cL1r0NLrkX9v8Bnv1PqD/Uc1w0AC/9UC4LboLL/x7mXz+0rBW7R0pi582RE/6hOgk0hWolCBC4IBeQn2kqKOMq6bufqeqfYUi5Pbs7e6AG5JxGIiSBmu7X8ZCcu7D7RnebJxENxCillJo6Os9K08NcMmEGymYHd6lcUmKd6aBMtFXKj5lxCZh0ZxjSvLDokqHtYHackGtvVTpdefcvezZn3PQx6eECkD+A2U2per4DKUuWCjwZth59Z549Wk9tW9iy7DXrZkBhgfxcOk7JrK+OE5LG7pspzR7bjqTTp/MWaINHpZRSSiml1KhZWlVguV8fgIawmzI6pZdLyRo5BhtuzgIovwZa98nxbPtRCNdJqTJnQb9P75PdAateByvugUMPSMmy8y9lH3vsMbmULpQgzuo3gb80+9iBsjlkUqOvWiYmRluSgZl6uR1tl0vHiWSliRIJTLlLZSKhNp0ffjY72PxafWIEaCBGKaXU1BBth5a9cjt/8cjsIPfGkdyJ8SV7tZimzCSJtiVLfaUa4rmHXg83HpKyawB58+U6FoZnvmodN3MDlM+QEmbuUuln05dUfVnDsAaZepPKhvHN6JFO/rsd1myYldMLWTIteQBRuEJ66rQfkZk3Lfuh9UA6W8jukdlfPk2FVkoppZRSSo2eOaV+PE4boWiia9mh2AquKjgN4QZofEl6YxYsHf4+Jza7lIRyl0uVh0gr1D0j2TH5C4cekLDZYNndcjn3ErzwbTj4F8mOyNR4FB79NDz+OVh6lwRl5lwj6xgKw0iX8y5YLNkxoXqpzBCqSzafb5ALgGGX49hUYMZZpP1l1LimgRillFKTXyImtXvNuJTgyl8wtttjGOleM8Ot45QEd9wl6VJju34OrWet4zZ9TEqSwcBKfKXKkrmK+y+ZFuuUFH1IB4OSWoNRHj1Qa1l2z7oZ6TuGIfVmfTOkhFz7UQkC2d2ynf7ZOutJKaWUUkopNersNoPFlfnsOdfatezvf7UXj8uOy3CytjLGm1cc57K5LRil66VPx3DzVcuxXsteOeZqOyLXxZdIE/XhMGM9vPYn0Hoetn4HdvwMwu09xyWiUtZs/x+geC6sfauUOsuvHJ7tsDnT2TIgkyvDjclgTKOUsw7VywUku8ZVLFkzqYDOcPfuUWoI9K9RDU08jGFmiY4rpdR40rJX6unaPVC8dvLOkknEofOU3E4FQMLt8PR/WMfNvhLKpkvWiqtYglP9SZUlcw+gLFl7MhvGUwnOPMtDD7x8gUgsPYPMaTe4e3V1z3UYtnRAJtYBdr/WA1ZKKaWUUkqNqaVVBZZATHs4Rns4BsD5NoO/HjVYUtrEWy95ilddvhZv/gD7aw6G3SM9aQIXkse6bVD/rJRvHmrvmO4Kp8PNX4RrPw07fwhb/xuaz2Yf23wSnvgcPPUF6SWz+vWw6FZweodnW0D6xTjzpfS1aUIsMzATtQZmDENKt3UFZkrSpbuVGgMaiFFDYjS/REV8B8YFm3y52pxgc/VznbxtJG9P1hOiSqnxofOMZFak+sKMxKyk8SJwVnY+HX4JggA8+zXoqLGO2/QxCJyW2wPJhjET6fTv/oI2ZgKCydJo+fN7PJxZluzGpZUU+/v4nRi2odc9VkoppZRSSqlhsGpGEfdv7yUYkXSo0eCTT8T49tat/Ofd1Vyx8pKRyer3VUtZrta9EpRpPwqhi8nsmF4asefC5YPLPwgbPvD/27vzODnqOn/8r6q+j5me+8xkJsdkcpKEKxAg4QiHgIKuJwjiqqsuuLLq1+8q7ldwd0FZxQNFZRVwdRHdn1yKIFFIAiQQAoHcd2Yyydxnz/TdXZ/fH5/qc7pneo6e8/V8PD6P6q6qrq7umerpqVd93h/gyLPArl8AJ3YAkdDQdbUwcOR52Sz5stTZWR8Bai8ef+myRNGQxZQPOBckBDM9QFBvYZ8s4RbsB3BSPs5gkSXMzHozFczucwQ0rTCIofHRwvoNIbsEakEAntFtIxbORAMaox7Q6FPVqIc2xoR5+nLFyCukiSgzX5usnwvIcWFGGgdlJhNCDmAIyC+iigL0nAR2/CR5vcWbgMIiGVCZCwBbFt3Gg33y8141y/FbhuPvkOsarPKKowSH2tzYfaovaV5SWTIiIiIiIqJp7L2rK/Gr7Y043J6mVFeKlkEFNz3egn84twtfum4dLLYJKh2WyGCWFxzaquX/vqFBoPM1WdI5f+nIZaVHQ1GAhhuAJe8DuvfJXjIHNwO9p9OvH3ADu38jW341sOqDwKoPA+UrJv6i7MRgBnVyXsSfHMyE3EAkAETaAX9CuWyjPR7KmAvk/7wsaUY5wN8qGhdRthHtBjdE+SbAAD2MCSVM9dsilDI/GA9xouuNlaKmhDYpQY5iiAc20fBGMSSsa4yvoxjYQ4dotgh0Az1vyYDCUTP148Lkmr9djs2imuID2W/+V/lFM0o1AlfcJUMYAHCtyG7bvhY5tZaO/BkZXddWNWTdX+9oSrpf4rRgw5IcdNUnIiIiIiLKgTyrCc9+4SLsb3HDG4iX6j/U5sZvXm9CY7c3aX0BBT/fFcK2xlfxow/UoX7Bstz0jrFVyAHr+/bJihCDjbKXjGsZYK+Z2HNdigKUrAI2fQ+4sBE49jxw4AXgxBtAJJj+Me4zwGs/lK24Hlh+g2wVq3J3Hs5gTR5jRosAYbe80DDYB4T6ZHAV9sqGlvhjTXl6sOOKBzwGS272k+YMBjE0fopBfriZRpmyC02GMSJNQKOFADHCNBrkCA0Q0d44E/R6EsOZ1KBGTQhzMjU10zIOME00KYJ9QPdO+flgqwAKVs/+kNWjhxyOWvkZdHIbcPCPyeuc/w+AMQBEEB/kcSRaWJY8A+QX+GHXjcSvLLInj/vi9ofw1O4zSfM+dn4NTAZ+LhIRERER0cxhMRpw9vzk0l8X15fg7y9agG1HO/HQy8exs7EnafnBLuCGR0/iR9e2Y9M55wDmHPSOUU1A0Vr5f1v/Pjm4fe+78kK8glUT/5yqQZajXv15oP46oHsPcPxV4NhrQMsBACL947qPAq98V7bCungoU5Xj8VxVgz5WTMLPTgvJ0mWhvng4E/bJ9y40ACDhf1iDJR7KRJvRyXN9lDUGMTR1FFWvw2gG4Bj944UARGTksEZE5H0R0e+HU+5Hl+t/IEQEiESGf+6xUpThA5zhgh2oeu+fxFBHTVhmSFiuMvihuSvYC3TtlMe3pUR2057tIYwWAgL6gISO+UAkDLzwteR17MXAutsAzxH52ZC/PLtt+1rke2l0yPdzOIFOfV3bkJrET751Gt5g/LPVoCq4ad387PaBiIiIiIhomlNVBZc2lGFDfSkeee0k7n/hMIIRLbbcG1LwmWe8+HrXK/j0JQug5C/NTbl9awlg2QB4GgH3Yfk/csc2edGea9nElisD5GtwLpDbL14NLL8a6D8DHN8BHN8OdDdlfmxvY7ynjKsGWPZeYMk1wPwLAeMkjN2imuT7ZU34XzcS0EMZt96Dpl9Wn4gEgEgn4O+Mr6uoMowx5cteNMY8OTXYZv95CBo1BjE0cylKvMfKRIj10MkQ1Gip88N6b5xIFi0a8gj5OISH3ZUJlS6cUVLDmzQBT6ZgRzEAUJIfGwuJUm7H1uUfH5oEoUHAfQjwtcr75gKg+Ly5EUj62uTniylfBiZv/hJo35e8zmV3AQH9ah7nIhmWZGNQH9TQWZd9WTJrZdJsIQR+/Xryl++rlpej0pXlPhAREREREc0Qqqrg05csxEWLS3DnE+8kjScjoOA/XgOO957Ety4/A3PRyiHVBCaEogLOhbJkdP8BwHtGVlHwtQKupbKc9YSP06LK/xsd84G804BrHnDWdUBPswxlTrwBDLRnfnx/M/D6Q7JZ8oFFl8tQpv5KwDHCRYETyWCRY6kmjqeqRYDwgAxnQv361C3PD0ZvJ1IM8n/zxHDG6JTzeI5szmIQQxSV1ENngmUKbLSRAhwtHv4ILb4daAnz0kyHPLeWdrcmjaJCBjLqKAOcxJ49icsT7xsSts9waFoTmryKJDwoQ5OIL+H3W/+9jZUDTDfmU8q4TlpIDr4X8csrfHxnZBihKIB9nhz/ZK4MsBcbl6USCAwCW76dvLx8JbDkEmDgsPxSme14OcFe+YVSUbMrS+Zrk7dT/pHYfrwbxzs9SfNuubA2u30gIiIiIiKagZZV5uOZOy7C15/aiyffTi7T/MQBBWcGgnj42rdgczYBBSvlyfqJZrACRWfL3ip9e/VyZXvkBXf5y5LDhomiqDKMsc+TwY8pHyiqAc79INB1Emg+AJzYDvQ1Z95GwA0ceFo2KEDN+cCSq4HFV8r/b9VJvuBSNciLPc0FyfPD3ngQEx6U7294UJ7jSBvQqDKMiYYyibc5Bs2sN0fOUBFNsVggMMHdPzNJDG3ShjdactgzYrCjyZOsqduAlrC9lPup+wPo2wpNznswkqzDISUlGBou5Blm2YjrKQnzZklIFAkAwR4g0COnof5477BcsVUA+Utz8wV2utJCQKBL3rZVATt+Cng6kte56h7Ac1zezl+WfUA12Cin9uqRu68HOuQxnqYs2X/vaEy6X1/mxIULi7PbByIiIiIiohnKajLgex9ajUWlTvznXw4nLXulWcHfP6fgl9d1wR7cKnup5Dfk5oS8pRgoi5YrOyIDg+6dcr5r2ZD/4SaEosr/Je3VspzX4HGgVAVKFwFrrwcG+oDm/cDhzUDP8WE2JIDmN2T727cARymw8FJg4WXAosuA/Bz0KMqW0S6brSI+Twgg4o2HMolTEUkYfyaFaoyHMwYHYHLGbxsmoUwb5RyDGKLZKHaCfwoP8SEBTbYBTmpglG75WLedsn/A9AqHopJCmWwCnoSwKBJBntYI9O8HTJbRhUVZPU/KVSdCAFoQ0AL6gHb9sgX7ZE+VVKpRv9pD/0IR7d2i6HVxtYRxnpLGeoreTygRqBjl1T0Gq6y/aq/OzZfH6c7XJn+fTXlAKAi89qPk5fVXA4VFsiu6uUBelZSNSDDe08ZRl8V+6CXhbMlfglv6fNh8ILn7+S0X1kKZLYEjERERERHRMBRFwe2XLcbCEgf++ffvwB+Kn5/YcRq47TkLHr02AIdoArynZQUD58KJr/AQLVdmrwEGjgGDJ4BAN9Dxqqyu4Fom/0/PBWupbMF+Gcj4WoD8QmDFxcBZVwH+MND4FnB0M9Dy9vDb8nQCe/9XNgAoXaqHMpcDtRcClim+MFNR4oFKIiHkeZKwHsyEPQnNK893BPtlS6WaUnrQ2AGDHgKpltlzQe8sxyCGiHIjdgJ/GhlVgCP0kEaMIkDKYhk0+cd3yLYT91MASCjXNQpKJAy71gHFcxIw5OgjPjGcEaHhe7mY8gFLEWAukiGJ0Z6bfZrLEgOQV78vu3AnuvgOGcIoClBwVvZf0Lyn5O9muu7XqRLLkqUEMY+/cQpawq+Iw2zA+9dWZ7cPREREREREs8R7VlWiqsCGWx/ZiX5f/ILQnadD+MQLLjz2PgVO0Qe4D8ueK3mLAXutLIs1kVSTDF0cdbJ8tadZ/l/pb5MlzPKW5K5MltklS6WFl8kgyHtK9h4xAViyBlj7XkDYgZPbgSMvAMdfBkKe4bfZeUi2N34qL/KsXA3UXQTUXQLMvwCwunLzWkZLUWQFCaMNQFnyMqHJMGZIQDMowxstJC94Dfal2a6aHMxEp0aHvGh1pOoWNGkYxBDR3DEdw6Go0QY8GQIiEQrAo7ZCOBcBBkN22xouiEo3vlC68MhgkVdhmPLlFyuT3ubKGC1TRQsBgU55OySAnQ8nL1/1QcASBsKQX7LNWX4BFUIO5Ahk1xsmqSxZQWx2ryeI37zRlLTqB86ehzwrvwgSEREREdHcs7qmAI9/Zh0+/os30OuNhzG7Tg3gyy+X4+d/twhwH5In4fv2y54refUyIJno8xlGG1C4RvaS6T8I+DtkeWpPM+CsA5yLchfIGG1AwQpZis13Ro5ZExqIl8euWQws+x5gdAFNrwGHXwCO/RXoPTn8dkVE9qhpeRvY/qB8zypWAbUXy3CmZh3gKMnNaxoPRZWlyEzOocu0CBDxDO1BE/HqY+9qchze0GD6baumhIBGD2cMNn2ejedtJhHfaSKi6WCiQqJQCIPqUTkOiGmCTnYLkTm4UU3sBjuV/O16WTIn8NpPgHBCOTjVCJx3s/ySZrDIL7ij2W7YK3++tizq7Xr1gSdT1v3ui4fR500u/XfLhbXZ7wcREREREdEss6LKhcc/cwFu/sUb6PEEY/P/sr8dje9ZhrryS2WJsoEjsgR43z5g4KgMTBx1E3/i3JQPlKwD/F2A+6DsdTFwXIYijlogb5EsCZ4LqlE+h6NWPr/npPx/NNAlm8EKlM0H6v4NuO67QM9J4MTLsqfMya2AP00Zr0RCA1rfle31n8h5RYuAmvP1tk6WNpvoXkcTSTUAar78OaUSQoYx0WAmcRr26KXkQ3q5swzvlWpKDmZSb+cqjJuDpnUQc9999+HJJ5/EoUOHYLPZsH79enznO99BQ0P8ZJIQAvfccw8efvhh9Pb2Yt26dfjJT36CFStWxNYJBAL4yle+gt/+9rfw+Xy44oor8NBDD2HevCzr5BMRzWWxMWim8ReTuSpalswfAnb/JnnZ2psBgw8QAFwrRtcdeeCInDrqRv5CGgnILuxA0vgz+8704/Gdp5JWve6sSiwpn+J6vURERERERFNsWWU+fvuZC/DBn23HgD8cm7/5QDs+s2Eh4Jgv/7/yNssQJuyTvVYGjsnQwrlg4sMRawlgvUT2jHEfAYK9snyYp1EPZBbnLpCJPX+JfK2eRsBzSpblch+RzVoq9+Oc24Bz/172FGnZLUOZEy8DzTtl6DCSnuOyvftbed+SD8w7F5h3HlC1FqhcA+RX5u51TiRF0cuQZSgDr4WHBjSx4Manj8urt5A7/TYUNTmcsdfIEvQ0atM6iNm6dStuv/12nHfeeQiHw7jrrrtw1VVX4cCBA3A45IBH999/Px544AE89thjWLJkCf793/8dV155JQ4fPoy8PHmy584778Qf//hHPPHEEyguLsaXv/xlXH/99XjrrbdgMPDEIhERzUBaWH5BBoBdTySPKWS0AWe9BxBh+WXVPooxWXxt8moZ1SivuBqJt1lehWMujF2ho2kC/++ZfUnDB9lMBtx17bLs94OIiIiIiGgWa6jIw7UrK/G7Xc2xebEgBpAnwB218sS3r0WGMKEBOR08Adgq5f9sI43pOVrWMtn8nfIivUCPLB3maZIBkXOxPs5Jjhhtcgyb/Ab5/6mnSfaO8XfKppoBRw1gn68HKOcCG/8PEPQCp9+UpcwaXwVO75IXDo4k4AaOvyRblLNChjKxtgZwlmXcxLSlGjP3pgH0oCYhmIm22H2/Pn6NXhINACzFABjEjMW0DmJeeOGFpPuPPvooysrK8NZbb2HDhg0QQuAHP/gB7rrrLnzgAx8AAPzqV79CeXk5Hn/8cXz2s59Ff38/fvnLX+LXv/41Nm3aBAD4zW9+g5qaGvz1r3/F1VdfPemvi4iIaNyiZckCAWD/M8nLzvskYAjLq2NcK0e33VhvmAWAwTz8ukljycRLjj25+wzePtWXtOodly9GVUEOv6wTERERERHNMFcuL08KYnY19aDHE0SRI+F/MUWVvWNs1fL/wMHjMhzxnpHNXCj/H7NVTWyJLWupbEmBTKP8H9BWlZsQKJGiAvYq2cIeOXaNt1mGAwPHZTMXylDGVgWY7cDCjbIBQMgPnNkFNL4GNL0KnH4LCHmye+7BNuDI87JF5c+TgUzVGhnOlK+S4cxMLtWuGgE1DzBlqFwhND2YSQhpTAWTuouzybQOYlL198tadkVFMnU7efIk2tracNVVV8XWsVgs2LhxI7Zv347PfvazeOuttxAKhZLWqaqqwsqVK7F9+/aMQUwgEEAgEE9N3W7ZPSsUCiEUyqKb2xwRfS/4nhBNDzwm55DB01AiYSgHtsCgxbuyC6MNkfr1QCQMYZ8PwAJk+/vgb4Pi6wYUI4S1ZuTHBTqhBNyAaoIwlQKhEAb8IXz7+YNJq9UW2fGJC2r4e5mCxyvRzMHjlWjm4vFLNHPMxeN1XZ0LNpMKX0gDAGgCeHFfC/7u7AxVDYzFQEExEOoHBk9A8bcCvk7ZFCOErVL2FDEXTtxOGgqAgvOBQBeUwWOyd8pAk2zmYgjnAsBSnuNAwgzYFwG2hUCgHYq3WVaIiL32dwBLOYS9GrCU6WPwGoDqdbJd9CXZ+6PjANTTb0I5vRPK6Teh9J8a6Ynj3KdlO/Sn2CxhL4EoWwZRthyidDlQthyitAEwZSgVNiOZ5UWaBld8VsL58bl0vGaS7XswY4IYIQS+9KUv4eKLL8bKlfLq3rY2WZO+vLw8ad3y8nI0NTXF1jGbzSgsLByyTvTx6dx333245557hsx/8cUXYbfPpoNpYmzevHmqd4GIEvCYnOWEQFlkNwyaD2sO/SFp9J5m19lo2f06ABWdhjA05XTWmy2O7IdReOBRqzCo/nXE9QsiR2ERvfCq5RhQ/wJNAL8+qqJrUE1a7+qyAfztxRcybIV4vBLNHDxeiWYuHr9EM8dcO17r81Ts6Yn/D/U/W/bC1vZuVo9VRQg20Qmb6IJB+GPzw4oNPqUEfqUEmjKK8UKzYBR+OLQ2WEU35KCkQESxwqNUwKcU62PM5p4qQrCKbthEN4zCG5uvwQS/Wgi/UoKQ4kzzyErAfAOw8AZYQn0o8hxFoecYCryNKPCehEnzp3lMeoq3C0rjK0DjK7F5Ago8lnK4bTVwW+fFpl5LKcQkvTeTaa4dr+l4vd6RV8IMCmLuuOMO7NmzB6+++uqQZUpK4iqEGDIv1UjrfO1rX8OXvvSl2H23242amhpcddVVyM/PUFdvDgqFQti8eTOuvPJKmEwT+8FORKPHY3KOCPZC6RJQDm2BIZL8B7/qio+iypEH4VwI5C/Pfpv+Nig9mryKqvxyWXd3OBE/lHYBQECUbkRYdeCrT+7D293JFzlc3lCK/3Pz2uz3Yw7h8Uo0c/B4JZq5ePwSzRxz9Xj1V57Bnif3x+4fHTTisk2XwWYe5Un7QDfgPQXF35YwhqgCWMtkTxlLuSxFNVEifsBzEor3lBzsHQBUM4S9BrDXZh5APhdCbsB3GoqvRe5XlMEiX7utGjC5Mj8+SmgI9RyH0vqO3t6F0rYXSrYlzQAoEHAG2uAMtKEKb8Y3bTADRQshiuv1thiITi0ZSoNNY3P1eE0nWklrJDMiiPnCF76AZ599Ftu2bcO8efNi8ysqKgDIXi+VlZWx+R0dHbFeMhUVFQgGg+jt7U3qFdPR0YH169dnfE6LxQKLxTJkvslkmvO/XOnwfSGaXnhMznK+XkBVgQMpV54suhTG/EL55bpgGWAYxe9A70nAYATy6gGLI4t9aAQMBsBShLClAP/nd+/gT3uSQxirScU337eCv4sj4PFKNHPweCWauXj8Es0cc+14vXJFFb721H5osnMJ/CENbzT148rl5cM/MJWpQg4yr4UAXwvgOQUE+4BQl2zKfsBaBtgqAWs5oI7zPTaZAOtZQOFywHsKGDwpB3n3NclmLZNj11hzXbYMgKkYsBcD4ixZOs3bDPjaABECfKdkMzrkWDL2qsyD1wNAxXLZ1t4k72sRoOso0LJbb28D7fuBUHa9IKKUSBDoPASl89DQhfnVQEk9ULJEtqKFsrlq5P/p09hcO17Tyfb1T+ufpBACX/jCF/DUU09hy5YtWLBgQdLyBQsWoKKiAps3b8batfJq22AwiK1bt+I73/kOAOCcc86ByWTC5s2b8eEPfxgA0Nrain379uH++++f3BdEREQ0EfydwKndQP+Z5PnLL5dT52JZwzVb3hYg2C+7kDsXjry+EIBXlgANWefji0/sxp/3JocwZoOKn958DmqLswh1iIiIiIiI5qgihxnn1hVh58me2LzNB9pGH8REqSYZgDhqgdAA4D0jg5mwR4YTvjY5hoqlRAYT1vLR/f845PmM8v9IxwLA3w54GuX/rP4O2Yw22UPGMR8wDL3ofUIpCmAtlU2LAIEO+dp97fL1DxyVzeQErJUylDKP0FNGNQBlS2Vb8zE5T9PkxYzt+4GOA0D7PqD9ANBzAtFybaPiPiPbiS0pz20ECuYDhQvi4UyRfrugFjBZR/9cNGWmdRBz++234/HHH8czzzyDvLy82JguLpcLNpsNiqLgzjvvxL333ov6+nrU19fj3nvvhd1ux0033RRb91Of+hS+/OUvo7i4GEVFRfjKV76CVatWYdOmTVP58oiIiEYvEgSCvcDe55Pnly0FyhbIkmLOBekfm47QAPdBeTsvywAn0AmEfRCKEf/3z11DQhiLUcXDt56LjUtKs98PIiIiIiKiOeqq5eVJQczfDnYgogkY1HH2JDHlAa6lsoUG9FCiVd6OBiUAYC7UA4wywFQwth4sigLYKmQLewBPE+BpBsI+wH0IGDgMWCsAe418nlz3klENMmixVQJaWIZEvhb5mkODQEgPZYw2uV+2SsBclN1+qSpQvEi25e+Lzw96gM5DMpRp3w907JdTb/fYXoMWluFOzwng+N9SFiqyJ03RAtlzpqBGhjbR2/nzAOM4AjaacNM6iPnpT38KALj00kuT5j/66KO47bbbAABf/epX4fP58I//+I/o7e3FunXr8OKLLyIvL15b7/vf/z6MRiM+/OEPw+fz4YorrsBjjz0Gg2H2DZBERESzXKAT6DoJtKV0Z155tfzCmF8/urq/gydk93GDFXAuGnl9oQH9Mrj57q48PLm7JWmx1aTiF7eeh4vrS7LfByIiIiIiojnsyuXl+PfnDsbud3uC2H2qF+fWFU3ck5jyAFMDkN8ggwhfqwwmQm55sV+wF3AfkT1qrKWARQ9mDGPodWF0AK7lQP5SvUxaExDo0Z+zVfaMsVUDjprhy4RNFNUI2Ktl08KAX+8Z5O+QQdHgSdlUkwySrBXy9aujPHdsdgDV58iWyNMNdB1JaEfltK9J/o89JgJwn5YtLQXIq0gT0iSENWZWsJhM0zqIEWLkrlyKouDuu+/G3XffnXEdq9WKBx98EA8++OAE7h0BACJ+qCI0jg8NIiIaFX/H0N4wzlKgdq380mivzX5bkYC8AgiQX5Cz+ZI5cBQIufHrfUb8ZEd/0iKrScUjt52H9YsYwhAREREREWWrttiBhvI8HG4fiM178UD7xAYxiUxOwFQvL+SL+OX/mYFOWVJMC8ny1d6W+LrmIsBSLKdGe/bPo6iAfZ5sIbfsIeM9Lf8XHTwhm9kle8nYqsdXIi1bqjG+T1pEf91tsnyZFpT76GnWy7cVy9Jt1vLRve5UjmLAcSFQe2Hy/JBf9nZJDGe6jgA9J4FAf/ptZU0AA62ynd6ZfhVbEeCqlj1r8irlNL8SyK8C8qrk1DoJQdkcMa2DGJr+lJ5dKI3shtJqkN3dVJNsikl+sKkmQDEmzDMlz0u6zV9HIqJhCQF0HwJOvJE8f8W1cgA/R93ortgZOCKvBjK75JfQkYTcwMBR/OUE8M2tyQG8QVXw0M1nM4QhIiIiIiIagyuXlycFMZsPtOPr1y7L/RMbrHL8Fsd8+T9nqE8vW9Ype8mEBmXznIqvHw1lLMWA0ZldOS9TPlCwAnAtk9v2NstyYcF+2fr3A5YywF4le6RMxnlC1RAvp1YggGCP3lOmVfaU8evhFPbp48qUy320FMmgZrxMVqB8uWyJhAB8vXpZspNy2nsyXqbM0zn+5wYAX49sbXszr2N26iFNVbwt2ADUXDQx+zCH8Mw3jVNCryWhyUQ7EhjbphQlIbRJCGoyBTexYMcYD34m4kOQiGi6CrmBvX8CRCQ+z2gF6i+Qn3/OulFsa0B2DwcA14qRvzgLDeh9B9ubBf7pRRVaSqfVe9+/EpcvHeNgkkRERERERHPclcvL8eOXj8Xun+zyoKnbg9riSSwfpShyvBhzoSxhpoVkSbFgt5yG+mQPGu8Z2QB5Ps7kAswF8alxmH1WVMBWLlskCPjOyFAm2C+DGX+7XMdaJnvJWMtHXyJsrK/dUiwbVujj6LTLUCrYEw+kBo7L12wp0cu3lQ7/ese6L/Yi2eadO3R5YCAe0PQ1AX3NQH+znPadAoIDQx8zVsFBoPuobIkYxIwagxgaF1F6CdoNboiKqwCDAoiQ/JDWQoAIj3w7el9oMu2NPn6sFMMIvW5Sw5zEdUyT88FORDRW7kbg0EvJ85ZdBVjzAFvV6Gr39h+Qn7u2Cv2L5ggGjuPV4/349HMqAuHkRXduqsdHzpuf/XMTERERERFRklXVLpQ4zegaDMbmbTnciU+sn8JxPFRTPDQBZCmvYK8MJgLd8rYWlrcD3cmPiwYzpnw5Po3ROfQCaoMZcC6QLTQgx5PxngHCHtkzxdcmz/XZyuX/vJayyTt3Z8qTLW+xPFfp7wQCHfESZtH9AwCjTYYyllIZ0OS6xJolD6g8S7ZUQgD+vuRwpl8PaKL3vV3je/68yvE9fo5iEEPjpyjyA9ZoAmAb2za0iB7ChONTLZQQ7IRHCHn0s4IiAkQiMp0f62sZ0tNmuNsJ5dhUM3vkEFFuvftbIOhNnrd0g5w6F2a/HW+LvKpHUeQAiiMJ9mLLviP4h+cUBCPJiz56Xg2+eEV99s9NREREREREQ6iqgg31pXhy95nYvK1HOvGJ9XVTt1OpVANgLZENkCf9w4NAsE/2lgn2yUoO0eDCn1BCS1FkGGPKA4z58aDDYJfLTHmAqUH2xAm5ZSDjawHC3viYNYpB9kCxVsieMpMxpgygj8daJVuBAEL9ejDTJUOpsA8In4qXbzO7ZCBjLpZlzFTT5OwnIN9LW6Fs6YIaAAh6gP7TMpQZaAHcrYD7jBxPxt0im68n83PkV+dm32c5BjE0PagGAAZgrKG2EOl72sTCnCyCHSH0FpTJ9ljEeuSkBDTRHjcGsx7imFPW46FIRCMI+4F3n0yet/BiwFWhf8FzZbedSBDo3ydvOxeP3IXaewYv734Hn31OIKglly+7blUl/v3GlVCyqQdMREREREREw9rYkBzEbD/eBX8oAqtpmlZwiQUoeQBq5Dyhyd4toT5Zbiw8IO9rIX3+AICWhG2ogNEuQxqjIz51LpTjyQT7ZCDja5GBR6ynjF5GzaqP8TLR5cGGe83mAtlQr/cS6taDmU75+qLj3uC4fIwpXy9lpo+tM1kBUiZmB1DaIFsmIV9CMNOqBzZ6K148efs6i/DsL80OiT1ZxkoLj1xCLSnYCSYsC+khzhh75ET3P2NQE72d2qbpH2Iimnj7/xdwtyfPW365nI6mN0z/fjmWlykPyF+SeT0hAPdhvHvsKD77nDIkhHnv6ip8/8OrYTSwJyAREREREdFE2FBfClVBbExOf0jDzpM92LCkdGp3bDQUVV4oaHYBidlI2KeHMm49kHHL3jRCi4+/MmRbBln2y2CXZcnMEfmYkFueewvoY9f0H5D/41rL5HqWosmrWqMa5PNay+T92H51yWnYo79mNzB4Qq5jyo+PR2MunvpgJh2TDShaKFs6oXEMLTFHMYghilKNAIyjG2MhakiPnGDyVKSZF70dGx9nDD1xFDU5mDEkhjQmQLWkCXF42BPNSG/8PPl+2VKgvF5e9RP9wjcSfwfgPS1vF67O/MVUCwG978DT34Yvvjg0hHn/2mr85wfPYghDREREREQ0gQodZqyuKcDuU32xeVsOd86sICYTo022xP9fhZDBRXhQBhaJ04hPXvCcKaQRQvZCiXgBLQAoZsAQrUhj08eVmQfY5wEm5+S9ToMVsFfLBiQEM92y50xoMCGYOSnXMTll755oM+bJi7ZpVuEZWaKJMJ4eObHxcYJpgpzo7WDK7WiAo8kP9NH0wEkKb0zDBDmJ60xiLUsiGqrxVaBlb/K8lVfJz568Rdl9QdPCQN8eedu5UH65S8ffCfS+A0T8+NarKhr7kxf/3dnzcP8Hz4JB5ZdCIiIiIiKiiXbpkrLkIOZIB/4fshjbcyZSlHhAg5SwSWgyjAn7ZNgS8cnxYiL6fUUBDBa5rhaW47aE+oFgpzzP5j4U35bRGe+1Yi2TQYfBrF/AnOPqM0OCmUA8lAl0672D9LDJ0yzXUY2AqSA5nJmOvWZoVBjEEE212Pg4o+yJk1QeLZi+RYITFN4oQ/8wGaJ/rCxp5pmZ3BNNlJAfePaO5HmOUqD2bHnM2Wuy2477oPwCa7QD+UuHLtcich39ipznT1rxuwPJvfTWzi/Ad/5uFUMYIiIiIiKiHNnYUIrv//VI7P6JTg+ae7yoKbJP4V5NAUXVx4zJMPZL7PxWQkCjBeI9UPzt8kLDaAm0wcF4aTCDXZYHM+XLkmaKIfl5053nUk2AYoxfsJx0Wx//OZtyaAYLYK+SDZDn7oK98Rbqk+f8Al2yRRkdCcFMgdz3ySq/RhOCQQyNnacL0CA/+GjyqcbRlxnTIhlCmwxhTiQou4EKIRP7SGAU+5fYw8aS5g+YJfnqAwY3ROltuRfoOZk876zrAIMRcC7K7ouXvwsYbJS3C1YPvcIn0A30viu7gANo1ebhX17qTFrFYTbghx9Zy3JkREREREREOXRWtQtFDjN6PPEL47Yc6cQtF9RO4V5NQ4oqLzQ02uVYK+kIIUMafwvgbQF8bXrQEZJDBPjbAN9pQLUBRitgcMjeM9GQZ7TDoCgGPZwxxivnREMbxaDPN+ghTuJtkwxmHDUADDJUCvXLfQ32yt4yYY9s0XLjiiJ79phdeu8ZF2DM53jS0xiDGBq7J26Gqfl13ABAHMwDLC7A6gKs+YAlP37b6tLvR2+nWc9k44n4yaAa5B8X2LJ/jNDS9LAJ6PcDCcFNIL4ciM/Pet9MQ4Oa1PDGYGFwQxMvEgY6DwJn3gZa3gba9sqrT5zlsuVVAIV1QMUqoHQpYLRM3r6d3gVsfzB5XsVKYNll8phxZPFFXAsBfe/I2846wFoSXxYJAu4D8e7PBisataX45z+dQr8v+Rvnt25YifnFc+wKLCIiIiIiokmmqgo21Jfg6XdaYvO2Hu5gEDMWigKYHICpHsirl/NiY7boPU7C3vj6IiLHgFbM8d44RicARR9WICTPF8Ruh/Qxo8Pxx0ciQGSi9l8Pb1QzEPHIfQ3rU6EBqir3Daoe6qhyf80FgMkVnxrM+nJ9HahymnpbMcjt8ZxbTjCIobELuGM3lcAAEBgA3KfHti3VGA9sLE7AnKdPnaO/b3bwA2MiKaosm2awAtkMFSNESq+aQObwJhKQf7yEiP8By2qflHhYY7DIfYveVi3Jt1lDkzLRIsDOh4Gt9wO+nuweoxqBkgYZylSskqFIxVmAvWji9y/kB57+fHKvQ4MZ2PBZGao6F2bXK67/QEJJsmVynhDyKpr+A7HAtN9Qgx/tMuK/X9+LUEQkbeL6syrxgbOrJ+qVERERERER0TAubShLCmK2H+9GIByBxcjeDuOWOmZL2CsDmWAPEOiRQYfQ9LFbBuQ6RpssCRYdt8XkSu55IoQeyKQGNCE9tAnHQ57E2yKS/n5su3qwA8geNiaXbIBeucYb7ykT9srnSke1yHMCBpssy2a0Aao18/lTRQ94lISAJxra5DcAtooxvvlzG4MYGju/e+R1sqWFAW+3bOOmJAQ0idM8wGSXQY3Zod+2y2TcbI8vS5omLDfa9KSZhhUdLM2QZa+BWAgTGCa8ifa40e8nlkobKbuJ1vaMBTMpoU3SNJukiWaFrqPAM7cDzW+M7nFaGOjYL9ueJ+Lz86uB8pXxcKZsOVC0EDCM8XdKCOBv9wBdR5LnX3QHkF8ovwg5F4y8HV874DklbxeulcGNv0v2ggn2AwA6gk789mgxHn2jDX3eoQdUlcuK/7hxFRQG3ERERERERJNiw5JSKIr81xAAvMEI3jzZi4vrS4Z/4CwnhEDnYABN3V64fSE0VORhXuE4KzcY7YBxPuCYL+9HAvFQJtitjzHjkw16OBYrC1agt0J53zgB55WE0Md4TglohKZPU28n3A/79HJm/fp+u/UxojX9vJoPQHf8gk+DVYYzqj412uW5sehyEcGQE29iorr7zD0MYmjs/P1TvQcZCCA4INtEM9lHCHAS54+0PNqscmqYo+W2FEW+9mx7rgiREMpkmvr1aShh8DZ/FvtiiPf+SWxqyn0OhjZzaRHg9YeAl/4dCGfxO5Et9xnZjv4lPk81AkWLgNIGvS0FSpYAJfWyHGMmLbuBP38VOL0zeX7lamDFZbJOrLNu5OBQCwF978rbeYtkINm1E/C3Qwjg7Q4DfnUgD88fGkAo0px2EyVOM35+y7lw2RlSEhERERERTZYihxlnzSvAu819sXlbDnfMySBmMBDGL145gRf3t6Ox2wNvMDkIWFzmxMYlpbikvgTLKvNRlmcZ34WEBgtgq5QNkBdkBvv0sVr65O2IXwYdIXf84kfFkDBeSwFgypdlwka7L4qilwiboN5PkWA8lAkN6Ps9kBKoCNmEBkDRwymHHs449IDGLJeb8iZmv+YgBjE0dl/aj9BgD17563PYcP5qGEMeWa7M3x9vAbfsORO73R+/H/ZN9SsYvZBXNu/Iq46aourBjE32vjFFmz3hdsq8Ydezx6dGa8Jty8wOfBQlHoiMRGiZAxstoAc00fv6FQbRLp3DUU3DBzXRXjcz+X2ejcIB4A+fBg4+m355YR1QtRaoOluWShzsAAbbAXcL0HEA6D05uufTwkDXYdkOJi5QgMJaGcyUNgDOChmaREJA9zHg3ScgvwQlUE3AtfcBoR75WeFcOPLz9+2Tv9+qWU47tsAfEnj2qIJf7bNgf3sQQPqejWaDik9eVId/vGwxXDaGMERERERERJNt45LSpCDmxQPtuOu6ZXOmWkFEE/j9rmZ878XD6BrMPAbxsY5BHOsYxC9flf+zW00qaoscWFTmwIULi7FxSdn4xjtVjXKs1aTxVv16ONMXD2i0sOxFE0gofa6oMrgwuWQwE22TWZHFYAYMJQAS9l8IWdYsGiZFA5qwB4BIf25MNcpgKa+epcnGiEEMjZ3VBRjsGLDVQNRcAJhG+SESDsbDmcSQJjgIBAZlj5bAYJr7nqHzsh1bZDoTmnxdwcEcP5GS3BMnMbgxppmXtF40AEozb0hINEytycmiqDKswjC9D6K0iN6TJqXF5uldOIUWr/cZGqbXVSwwsqW0xHkcv2bSBL3A7z4OHP/b0GWFtcBV/w8oXyy7HQe65dUnNQsAc5H8WZnyAWEAOg4D7fuAtj1A216g/YD83RgVAfQ2ynbkhewecumXAaNHDvjnqB05iAz0AJ4mwN8OmIvQ7w3iobcV/O6AAX1+ASDzl9jrzqrEv1yzFDVF4+zeTURERERERGO2aVkZfvS3o7H7p3q82N3ch7PnF07hXk2OV4524j+eO4hDbaOvduMPaTjcPoDD7QP48942APuxsMSBCxcVY1GpE3UldtQWO1BoNyPxrFWe1QijIcsKKAarDCOigYTQw4tQnwxmoqXBRETeDqZUFTLaksMZY57seTJZ59EURe/p4oj3/AHkubHwoGyhASA8oN/3xHsGJY5jS6PCIIamjtEMGEsAxwR0qwwHMoQ3KUFO0CNPyIaiU6+cF/IOnR/KRbeX6UDI1xnyAJiIMXmGkXWAkynUSbcsYR2jbeJ6+KgGQNX/CA1HCw0T1kTvB/Q/wr7he35FS6EZ7ZlDm2wGY6fh+fuBxz8KnNqeskAB1n4IWLQECO0Fmt8d+ljFIH8nTE7AmC+/oCxZD6y6XoY0MMheLG17ZTjTvg9o3y970kyE/DLggtuA+g0yXDHlAfnLhn+MEEDna0D/PsCYj+2tVnz5rwa0DupdjdOwGFXcuKYat66vxYoq18TsOxEREREREY3ZqmoX6ortaOyOn596ZveZWR3EHG0fwL1/PoiXD3cOu57ZqMJiVDHgDw+7XtSJLg9OdA1f/cSoKphXaENtsQN1xXasmleADfUlKMvPoiKLosjzBiYnYJ8n56X2Ogn2y/Jg0XNFYR/ga0vYhqqHI075v3/idLJK5Kt6eTVzynkBoem9ZAb1cyE0FjzDR7OD0SKbo3jitqlp8kMxY3DjSb6dLswZbn6GE6KzSizQymXgo4wQ7gwX6qQr4ZZhmcEk/7CqJtmGq4kZG8dG/8MaSW16D5tsSqGppviAaQa7DJ8Mdv2+bXK7s85EA+3A4x8GWt9Jnm92AJvuBKx+IOKWX5YMdvmFwlIka6gGuvRgLQj4uwGtBXAf0n8e+hcsawVgqwIWrQOWXROv/+rrBbqOAp2HgM7DsnUdBvpOZbffJjuw5r3AymsAi0uGMIoBKDpXfjHKRGhA20tA904ENCO+t38R/ms3IDJ83tQU2XDLBbX48Lk1KLCzhxYREREREdF0oSgKblhTjR8m9Ir5055WfOP65TBl23Njhuj1BPHA5iN4fOcpRLT0/79esbQMn7xoARaWOlCRb4UAsPdMP7Ye7sTWIx040OqGPzT23hphTaCx24vGbi+2AgCaAADLK/OxsaEUG5eU4uz5hTAbs3zvM/Y6CSWUBHPLcWBDg/IcUWhANl9r8rZiAY0z3nvG6JDj2UyGWIk1jg8zHgxiaHyCPTCLfnnCUjMDUPTeCao+VRLmKXqCmzIvafk0qnOpqvJkrdkBoHRity2E7MUT8soBw0M+PbSITv3J90dcJ3G9lHmzvstgYg+fHFIMCcGMFTDpvxtmO2B2ytumhNsZ57sAc7XchsGg/86H0gc2WjihDFr6sTyGBDXCCIvWK9c3THLd0emm8VXg//v7ob1TrC7g0lsBywAgFKBgBVB5NWBOuapICP2qlV4g2AP42mWpr7D+xSjQCQyejPeaMTpkl2JbteyeXDIfqDoruYxY0KMHNHow03kYCAzIoE81AQYjULwYqF0C2PQvV9GgrvAs+aUrk5Ab6NoJdL6GtzqduGv3ShzKkIFuWFKKT1xYi0sbymBQp9HnLhEREREREcXcuDY5iOn2BPHqsS5c1lA2hXs1sfad6cdn/nsXWvv9aZcvrcjDv16/HBctHlpRZ01NAdbUFOCLm+qhaQIdAwE0dXtwssuDnSd7sO1o57Djy2TjQKsbB1rd+OmW43CYDVi/uAQbl5Ti6hUVKM0bQxCimgBLsWxRQsgLQaOlwEIJUy0Uv4jXn3J+QzXKc0EmJ2BwyHNDRme88gpNKwxiaFyU/n0ojByG0p0nTyBOyEb1sCYpqFGHWTZM8DMk5Ml0O2X76Z4rw+P7/BE09YRgNqpYUmaDQc20j6mBFACTGTBbALhG8RpGQQg5AHhSgONLCWwSgxtfynq+kdeJBT6R0e3bTCMienm70dcnHZHRGg/9YgGPIyH0scgT9Ua9qSpgUOUxZ7TE1zNboagmFIYPQel0yeVpe9TooYHRPnndWyeTpgGv/QB46d+GBpGOUuCiGwGbIq8cKd8ElJyf/n1QlIQuuXVyXiSgBzO9gL8T8DbHr17xt8urVtyHk8MZc5HsmmyrBMwFQMUqoGpNhn0PA52vyi7LWhDQ9M9Vx/x49+Z0PKeAvr1obm3Gt3cuxHOn0ncVvmhxMb51w0osKh0m0CEiIiIiIqJpYUGJA6vnufDu6fgYI8/sPjNrgpgX97fhi0+8A19o6Dml0jwLvnLVEnzwnJqsLiBUVQUVLisqXFasW1iMj54/H5omcKDVjW1HO3GsfRCN3R40dXvR7RlbOOMJRrD5QDs2H2jHPX/cj+tWVeLW9XVYW1MAZTwXlyuKXn7fBiDlZxsJJIcz0TFbwl79Al53+ot3Y+cl7MmVVaL3WQp/0vEdp3ERRifCil3vFmeQJ/4h9JOfIn4/7e1MG9VPnE5g5S4hgNMDQOLnrKIA8/IARxbVeDxB4FA30NgPNPUraOwDmvrl/f5A/IPWZRG4ZD6wcb7ABdVAdR4w4RebjytwUuQOWRTAYgSQDygupA27km5nsd1IRAY84YD8IxEKyNvhgB78RKf+hHn+5Gn0diws8unLEgKg2djDJ/raveMv4WYEsA6AOPhwQok1ayyoid/Xp5Z82UPEWgBYCwFbMWArkc1aAFicMhxSxxHYhPxAwA343XK8lkA/PO5e9A+4IVQThMEEoZphdzhRXFIB2Arlc5tHOVBd0AMcfh546zGg8ZWhy13VwCUfA0xBOSjegpuTuwdnw2CJD8jnWiZ/H0MDMowJ9AL+FlnjNTQgvxj52mQ4078/4UuQE7CUyG1YK+V9LSDHGvK2AANHgWA3/LYlON0XRqPHgcaQE009+3Cmz4dwYjdtIeQVMxE/tEgEO1urEdSG/qzMBhVfvaYBf3/RAqjsAUNERERERDRj3Li2OimIefFAO7zBMOzmmXtaVwiBh7edwLdfODTkFKHFqOIfNizEZzcugtMyvteoqgpWVruwsjp5zJPBQBi+YDz80YRAa78fjV0eNHZ7cKDFjR3HuzEQyDwGTSgi8PQ7LXj6nRYsrchLGksmz2rEBQuKsGFJKWqLRxiLeCQGi2yWlOEYhCbDmLAHiHjivWbCHlllRUTi5c/SUU3xcCYxqIk1li+faDP3iKXpofBsdBvaIMo2AqZRlEASmcKZkYIcLcNjo+GNFpvX7wtj+8kBbD0+gK3HBtA6MPTD06gC586zYeNC2ZaWmfS+MXIbB9v9+O+3PXj6gBe+0MjJUH9AwZ+OAn86Kk90mg3AfJeCugIVtS6grkBBbYGCOhcwL18kPVc8YBgpqEoYcHs6DzNj0hssepsAQsi0PxzUW0BOIwm3wwHZCygcjE/DoczrJk31kCgUwPR+c0emaBEgMCjb+Leml1pzAOY8wJonp5a85CsohAYEBwG/GyLghvD1Qwm4oUQCQ7bo0NtwhGqCsBZAsxZAWAsgrIUJt12wmoxQtZD8mfadAo6+qI9JlMaCi4HzbwCCzfILxlhCmHQUNd5rxjEfwOqEcKZPji3jOwP42+JXr4TcgK8F6NsDb1jFqUErGgcsaBq0onHAiqZBJ5o8lWgZVPXfQh+AQyPtCDL9SW8oz8MPProGyyrzx/96iYiIiIiIaFJdf1YV/v25g7GxU7x6r4wb1lRP8Z6NTTCs4RtP78Xvd50esuz8BUX4wUfWoKrAltN9cFqMQ0Ke8nwr1tQUxO6HIhp2n+rD1iMd2HqkE/vOZAg0ABxqG8ChtuQKKs/tkeO81BXbccWycnzmkoWocE1guTBFlSXJ0pUwF5oMY0KDQMSrj2HslbfDPr0CR0hW40D/0McD8mJSg1XvRWMDVKucWkrkRaY0agxiaGrEem9M7GaFENjV1ItfbW/EC/vakq8cTyOsAa+f8uH1Uz58ZwtgNqqYX2RHXbEd/b4Q3mzsHdf+BCPAsR6BYz1Du1gW2k24uF4O9rVhSQnK8lI+jEVKABWblxI6DdvrKIvlmQKv6PPFAiJtjNvKZnnqc6Q8X+JjVL0c10iB1XhES7qFg3oX0GBK+BOIBzaxaUJvn5A/YVm0p0/C/RnXq0fI3iZBD4COrB4R7TM1HooWguLthOrtHM9WgPWfAZZeCLgPAKYCoOKKiQlhMj6lDGeaB03Ydgw41W2DEIv0LzoB9A0OorHbh6Y+De1eQ852w2Uz4c5N9bh5XW32gwkSERERERHRtFKaZ8FFi0uw7Uj8f+Ond5+ZkUFMryeIz/3mLbxxsmfIsg+eMw/3vn/VtPn/1WRQcf6CIpy/oAj/5+ql6BwI4JWjnXj5cCf+sr8NwXB253Yau7345asn8b+7mnHvB1bh+rOqcrznkOclouXS09HCyeFM0m2/PBcmIvEeNonX1xauZhAzRgxiaFbwBSN45p0z+NWOJhxszZxQjyQY1nCsYxDHOkbXi8CgKrErE7LV6w3hj++24I/vtgxZZjIoWFXtwsYlZbi0oRSrql0sJ5SJ0FICnTTT6O0hyxN7WWWYjrTN1OlI29QisgdH0BsfZyfoQ3L5toTQJjHcyRj6+GdFL56JFrAUofW821GysAFO3ynA4AQctfLqjcFG/cuFT05FKP47IiIyLFYMCc0ku+0mtpR5/rCK15sGsPVoD7Ye6cSJTs8we6cAyE0IY1QVfGJ9Hb5w+WIU2NmVmIiIiIiIaKa7cU1VUhCz7WgXugcDKHZOUAWSSXC8cxCfeuxNNHYnV7JQFOD/XrMUn92wcHzjrORYaZ4FHzh7Hj5w9jz0eoL43a5m/HpHE870+bJ6vNsfxh2P78bfDnbgnhtWIN86ispCE001AmoeYMpLvzzaoyZ63iTsi9/P9BgaEYMYGh8tnLteCVlo6vbg1zua8PtdzXD7M9dtTBT9TB/tbhtUBXXFdtQVO1Bb7EBdiV1Oi+2oKrChcyCAbUc6sfVIJ1471pX1/qQTigi8faoPb5/qw/f/egRFDjMuqS/BxiWluKS+FKV5M+cPbc4p6oT3rErkDYbxzqk+RITA6pqC3P2hjIU+WiwQGAwE8WZjH3o8QcSCoyFBEFBsN6CuUEW1LQz4e/Hmqy/j/DXLYIwEZGmykAcIeGTZsKBX793ilfODPiDogRb0IuDzQQR9MEZ8MGPsv7/D8QsTBmCHW9jhhxlGRGBGGCYlDAf8cMEDVRn7Z0pYqNiurcAftQvxZ/86eP4quzOXWCtR5wygtkhDXeFuVDiTx28qsADnVgGuLA8tIYAOjxwnal8nsPWUgjfOAIHIxP8yljgMsqxhXhi1Lg12I2R9WGuF7IIc8gCeRkBR4ShuwCVLqzCv0D7h+0FERERERERT46oVFbCa9sIfkucBIprAgy8dwzffu3xahxeArF7z7Lst+Nen9w05V2YzGfD9j6zBNSsrpmjvxqbQYcbnNi7CZy5ZiNeOdeFIe7wsmRDAwTY3th3pRNdgcMhjn9p9BjtP9uAfL1uE96+tThrrp6nbg4OtbuRZTagttqPSZYMhzYXZoYiG070+NHZ70NTlQWO3F03dHjR1exHSNMwvip+zlFMH5hfZYTNneUHoSD1qaEwYxNC4KD07UR7ZBaXNLMePMFjlCUI1OrUkzLMkjycxAl8wgqMdA3BYjJhXaIPFaIAQAo3dXmw93IG/HerAq8e6hg1UzEYVFywsxsYlpdi4pASLSp2xP1CeQBg7jndj29FObDnciVM96ceWKHFacNO6+bjp/PnD1nKsKrDho+fPx0fPnw8hBLoGg2jqjn8YRqcnuzwYGGVI0+MJ4pl3WvDMO7L3zMISx7BdNfP1D+y6EoecFstp3lSm7TPI8c5BvHSwA1uOdODNk70IRuQXHYOq4Jz5hdjYUIrlVflQE77sFNnNqC2xjz2oURT0+SI40eXBzpM92Hq4E7uaehCKZB9KGFQFVS4rwoGzkd+WB0VRoCgKKl3W2O/BvHk2GA366ERC4ESnB1uPdOL1090IJHSrNSEMB3xwKj444ddvy6lD8SMPPtjhhwFa0j54YIUbdgwIe2waDV4GYEdtsQ0bF1iwcYEJ51UbYTUKQESgRYI42O7Db08E8GajF40dATjhgUvxoACDKFAG4Uq471I80KAgBCNCMMIvzNgn6vCXyHnowdCxULr8FnT5LdjVNcz7pwBn1+RhY30hLqhzYWGxGYU2BYqIwBsIYsfJfmw77sYbp3xo6gtnNW5UtiqdQo4j5QJqXUJOC4D5+YDTnPAeG6yAcwHgXCi/GAFAx6tAEICzFihYPGH7RERERERERNOD02LElcsrkqqqPLa9EV2DAXz3Q6thNeWu7PV4vH2qF//2pwPYfapvyLLyfAt++YnzsLLaNfk7NkEMqoINS0qxYUnpkGWaJnCg1Y2fbzsxpBrOmT4f7npqH779/CF88Jx50DSBrUc6h/QWMhtUVBfaYEk4B+gJhtHS5x+2Mk9zjw+vHeseMr8iP35+qLbEjtoiB5zW+LlaBXKsnFGFNpQ1BjE0PppeDkkLAKGIHIR6OLGBnhJCGtWs3zcDqhm+sBG/2NGKn25rhDcox1ZRFcQG6jrdO3KXv9piO265oBYfOqcGLnv6E+MOixGblpdj0/JyAEDnQCApMPEGI1hdU4BrVlSMuj6loigozbOgNM+Cc+uKkpYJIXCmz4dXjnZh62HZe2YgMLpg5kTXcCWPpJ2NQ+ttFjvMCcFMcq+euV7CKBTRsPlAO361vTFtrVJAXnGys7En7XsbVZT0HstpTZEdVlP8d8gXjOBUjxeN3V40dnliv3f9vtC4XkNEE2ju9QFQ0OqNl9cbS7m+EIzoQx76REKXU/1vvM1kQG2xHbXFdjgt8eNLUYBKlxUNRTIErCm0Jx07ZqM6ZDC8KBXAigpgxWp5PxCOwBPQx1bS9LqkITcQHgBCbni8g9hxKoitpwReaTbCHRr/FUARAbx5agBvnopfyZJnNaLKZcPJLk8skBuNIrsR62odsJsQ6+lkMwG1LkUPXjTMz9dgVcOACCePHxQti2bKB6xlgLVU3k7k7wCCvTKUyWMIQ0RERERENFt94sJa/GlPS9IFyX/a04rTvT48fOs5Q8ceniJ93iBeOdqF5/a04oX9bWnXWVmdj1/cet7EDl4/zaiqgpXVLjz4sbXYtKwM33h635ALswf8YTz6WmPGbQQjGk5mcQ4wW21uP9rc/oznvRJV5FtRU2RLe070k+sXYGN9UZpH0XAYxNC4iNJL0Wnohyi9BFC1+IBOWkDe1gLyfsQvx11IHOgphSaAZ44A9+9Q0DqoDFmWTQBzWUMpbl1fh431paMeUyVTcDLRFEXBvEI7Pnb+fHzs/PkIRTQ093gRTkiyW/p82HakC1uPdOD4sONMjE63J4huTxBvp7kSwWUzoa7YjnmFdhgN8ffObFBRU2SPhQrl+dZYSScBGWA16t0fT/f6UGA34eLFJTi3rhAW4+Sk50IIuH1hBMKRpPkFdvOwIVpEE3j3dB9ePtSB/911Gm1u/7j3pccTRI8nmPZqj5mm0G7CBQuLsajUifn6z7+u2I7SPEvOuz5bjIaU3x8bgJLYvSIANcuADwsN4aAPR9v70dSnobFXD1S7vGjqHkRLfyB106My4A/jsH9g5BV1qgKcPb9Q9sJrKMXKqlGO76Tpv8NqlseO+5CcOhfIYJuIiIiIiIhmpXPrivCt963AN5/dj8TOEO809+HGH7+G739kDdYtLJ6SffMGw/jN6014fl8b3m3uw3DDKL9nZQW+9+HVSSW5Zrsb1lTjnNpCfPn372YVgkwH0dAmnfesrJzkvZkd5s5vPE24xi4PwpEwQjADJhdgGqEkkxZODma0AAa8Pmw/6cbWEx5sPRHAmYHRl/rJMwt8eBlwyyqBusJOQO0DOk2yh41iAgz6VDUnDKydclsxxgePmWQmg4qFpc6keUvK83BpQxmA5Wju8WLb0c5Y7xlPMJJ+Q+PU7wvh3dP9ePd0/7i39dMtx2EzGbB+UTFqix2xtzbaxTFaNm1+kT1j91khBPq8oVjI09idXNJNCKBjwI8mvQdTujF5VAWoLrTFeqXYEp6rze3Hq0e7suqFYlQVqIoyph4R42UyKFhU6kwKxxJFNKCt34de7/h60wDy/VobDRGWlGJltSttLdJpRVFhtDiwbL4Dy+anLOt6Hf5BH5r9hWjU6mP1Uhu7Pej1xuu0ahpwrHMQwfDof74Wo4raYjvW1BTg0oYyXLSoJGMvvKxkG8AAgK8NCPbLXjNO9oYhIiIiIiKa7W65sA7ziuz4wuO7MZhQXaWl34+P/tfr+NzGRfjnTUtGXdllrDRN4KndZ/Cffzk84sWtdcV2fO3aZbhqefm0H9cmF+YV2vHEP1yArUc68esdTXjpcEfa4RYK7SaEIiLp55tJod2UPBZMiR0mgxo7Vxat+tPuHt9FqjQxGMTQmH1v8xH88d0WqIoBPzzyKupKkg/82uKU0kSqEUIx4EBHGFuPeLH1cCfeaupN6gmSrVKHio11RmyoBTbVabAbwvGBzCN62DMaiiLDGNUUnybeTjdPNeoBT3Sam94fNUV23LyuFjevq0UwrOHd031o7c/8x00IgQ53ICnAONPnG3YsnVzwhSL426GOEderdMnak3XFDhQ6zDjT59N7NKQPV0ZDE7IuZnPPyL2pUpU4zbhyeQU2LinF+sXFMKoK3jjRg61HOrHjeHdSgBMRAt2DgWGv+MiWQVVQW2TH+sXF2LikDBcuKs5YzitRvzeEph4PGjsH8Nbbu7FmzRoYjEYEQhE098bf046BQNLvgs1swHl1hdi4pAwXLx5niDCdeE8D/k5YTSrq561F/QgDzPmCEbx+ohtbj3Ti1WNdMmhO+YEaVQXn1MoxgtbWFGJBiQNleZZR976bEEID+g/I286FMnAmIiIiIiKiWe+yhjL84fPr8alfvZlUPUYIeWHstiOd+OFH12BxWd4wWxkffyiCV4924Qd/O4J9Z4Yvh55vNeKfrqjHrRfWTVpANF0pioJLG8pwaUMZTnV78evXG/FOcx+MqoqL60uwcUkpllfmQ1FkVZumbg9a+/1J55uMqoJ5hTbUFjmyPofjDYZlifyu5ICmudeLUDi+8VBEQ7cnOMyWaDwYxNCYNXXLklmaUNDU40VTjxdbU9ZRFSDfZkL0NGUwrGXdo2P9omJ847rlmFdkwyk9UPAGIlhZ7cKyyryh6bkWAbQgIEJARJ9qITkvaRpKWS+ihzj6srFSlHgwEw1sFKMe1BgSbidM0843ZOyhYzaqOG8MpdMC4QhO6yfjT6Z86J7u9Q07wFeutfb70dqfXX3KyXD2/AJ8Yn0d3rOycsgXhMuWluGypWVpHxcMazjd642FX4nTM30+aAnvsSH6RzNhHJnotLrQBpNh9F9MXHYTzrIXYFm5A+KUwLVnVcI0Ui+12SoSBPr2y9v5DcAIIQwgA6nEn284oqGlz4/Gbg9a+30oclhwwcIi5FmnyXs6cFyWeDRYOTYMERERERHRHNNQkYenb78Idzz+Nl4/kXw+ZX+LG+/78Wv44UfX4kp9XOTx0DSBDr0s/b4z/dh2tAtvnOhGYJiqElaTigsXFmPjklLcuLZ6zo9LnM78Yjvuum55xuUlTgtKnJYJeS672YilFflYWpE/4rqegAxtmro9aEsJgaLOqS2ckP2aaxjE0JgIIbIaLEoTQN8oSybVlznxL+9ZisuXlsXClpXVLqysdg3/QNUAqDYANmA050qFlhDOhPXb4YQgJ3pbXybSTIXQW1BuZyJEB+pODW9iYY0hIcxJ0xLWsygGLCoyYVFxMdBQlhTyhCIazvT6YqFBx4A/qcfEgD8sg7YMoY2iANUFsvxXdYENh9oHsOd036T3wBmPJeVObKgvxQ1rqrFq3gi/ZxmYjbLEXGqZOZpkYR/Q86Y8Dk35srfIGBgNKuYX2zG/2D7BOzgBwj5g4Ki87Vouj3UiIiIiIiKaU0qcFvzPpy/Af71yAt978TBCkfiJGG8wgn/49S587T1L8ZlLFo6qFJg3GMaO493YdqQTb5zswckuz7ChS6KLF5fgHzYsxPkLijKWoqfpzWExYlllPpZVDh/ahELjL5E/1/DsDY3JYCCMiSrGYzaoOG+BHJfi0oYy1Jc5J7dWpKICBotsY6WFE0KcaEijzxNh2Vsndjs6P5KyTjge6gB6T53IxAU7iRRVD3UMMCkG1CkG1BUZgOJ04Y4RUAoBpRghTYU3FH28XG4zG2E2mZLm9XjCeOV4L95q6oc/HO8BFYqIWOjTMZBd+TijqqCmyI7aYjtKnZakjkL5VhNqoyXxihxw2eIJXFiL92ho0suzJYZIRoOKs6pd2LCkFFUFtnG/pTQNBHqAnl2yNKFqBorWyt/L2cZ9QH42WIoAe/VU7w0RERERERFNEYOq4HMbF+HixSW483fv4FjHYGyZEMC9fz6E4x0e/NuNKzOWBRNC4Ej7ILYe6cDWI51482TvqMfIXVTqwDeuW45LG0rn5PgvRNlgEENjkmc1Yc/dV6Oz34vf/nEzqpeuxem+gF7ySvasGK6m4PwiOy5tkAOCX7CwGI4sxsCY1lQjAKMsEzReQksT0ESGhjixICeSpiWukzA/8TlEEBjl2OQmAEP6i6TpGFUE4IZS2WRAoyYEOyqgmOEJWXGqX6CpD2js09DUp6HPL1DlMqKu0IzaIgvqiiyoKrDCaNAfi8RtJdyGCigAlIh+WwZIxU7LmHu4UI5FywcC0H94SQHhqAgN8JwC+vfJb5qmfKD4fMA4CwO2QDfgbZFd0QpWTfXeEBERERER0TSwstqFP33hYnz9qb148u0zSct+t6sZmw+2Y0N9CTY2lGJRqRPNPfIi2eOdg9h+rBtt7sxjEWdiUBWcPb8AN66txofPrRlTmXWiuWSGn/2mqVagdKHB0YnLGxSYzEWAUhYbH8UdBE71+DAYSB5wvcplm57lfqYLRdUH3p7g+plC6AFMSlCT2DIGO9GmpUwjAFLnabLFnjd6P/n3wAFgWb5smD/Mfg8/5tvwFAXx8CYhwEmdl806SfMy3B9223P0ipBIEAj2AsEeINQPRHyytFZiMJhKUVLGUkotzWeS723EC4QGgPBg/HfOXgUUrBl9mDMTCAH07ZW3HbUycCIiIiIiIiICYDUZ8L0PrcaiUif+8y+Hk5b1eIJ4+p0WPP1Oyzi2r6Ku2IHV8wqwsaEUFy0uSapMQkTDYxBD46IMHoNLOwmlZxdgSP51ygewUjEANlP85Gl0EPvehNtqyvKkAevHcHU8pacoejBgwISHPKmESA5noA0f5gwb8KRbV9OXa8mPhYakwWmEABAZ/qT/ZEkKhVKDm2GCnNR5ScvTLItEYBJuGX4IS+b1chUOhT2yRFhQb6HBzOtGxzYRAoCIhylCxMdoypZqBPLqxz9wfdgL+FoBLQD5Puk/N4MVMOUBxryp+UyKhjChAfk5mdcw+ftARERERERE05qiKLj9ssVYWOLAP//+HfhDoyyFojOqCs6pLcTGhlKcM78QC0ocKM2zsOwY0TgwiKFxEeZCBBUXYC4EVJEwoL1+4ltEgEgEGO958NiV8YYMt1PuJ4U5GQazn8u9FHIt2qNhKkR7/iT11ElzP9M6WjQEGsXjRMpjYvNS9isWCuVuQDMlEkZR5BCULueQcHToyqk9hjL16FEyh0JaUIYWkQAQ8acf08jkBMxF8nPCYJclwww2DBm/JRbgJZThi36eDBl7KSLDEWOeDEgMtrEfzxE/4D0D+FqAYN/I6xvt+vPmy+c25QFG59DXM1GEAPreBTzN8n7BWXqvOSIiIiIiIqKh3rOqEvMK7fjG03vx7un+rB5TXWDDRn0YgfWLipFnZW8XoonEIIbGx7USvYZTECUXAaaED+jYOCehhHAmOk03L3Gg+4QTsVFaGKmlrSZENJRRM4U1I7WUXgtqunFMWJ5qUiX1/JniLw1DwptMwU0kZZ0IAJEhFEq3vYT74SAiik0GHgY1zeMS9y8HPYYUFTAXyNDFXCRbtqFBLMAzyh/fZPCeAfr2xD9vFAUwF+tlvxJ66oS9QHhABk5hr2z+9uR9NzriwZDRqTdHvOfPWAgN6H1H7qeiAIVrZfk1IiIiIiIiomGsmufCM3dcjOYeL7Yd7cTWw53YfrwbnmAYVS4baovtqC12YEm5E5fUl2JRqYM9XohyiEEM5cZEjXOiRccz0a+Aj10ln2ZeugHt0455kjh+SXRslPHtZtYSexLEQps0A8+nC3SgDg1/0pW2yjTuCcOgyRf7GU0eEQqhyzAIUX55cjgaWyGbYCd6nCSUmMsU/KgmQLUABoucGp0zo5ygFgH69wGeU/K+2QXY5wO2SvlaMokE9HFpBpKnWkiWYQsNytJmiQxWPaRxyt5BBoc+tWc+HoUAQn3AwDHA1ybXKzpH7h8RERERERFRlmqK7Lh5XS1uXlcLIQQimoDRMLnnKoiIQQxNd2q0Z8MwJ0ZHK2nQ+pFaWA+Dhhm8Pl2ZqqReD4ljliT0Spis8CdVtmOVjHqA+nTjnKQJmZLKYNGk43svg5Oet+QUAPKXAHlLsgspDXrohJLk+RF/SkAzKMfLiZZsi/iBQHfyYxRVljkz2AHVrDeT3Ia/Mz5GjqICRecCtvJxv3QiIiIiIiKauxRFgdHAC3SJpgKDGJp7kkpXTQKR2qsg3eD0mZalDnY/wrgn6cYzmaKxSrKS2pMnUw+hkcKhMYdB0e3RnOFrB3rflr3lDBag8GzAWjLy40ZisMqG0uT5WigeyoQG47fDg/L4jPaiSUc1AZYSwLkQsBSNfx+JiIiIiIiIiGhKMIghyrWpHLg+aiIGqE8a1yTNmCZZDW4vUvZrgscnGasxhTdjCIeGKxs3E8p5zXQDx4H+A/K2pViW+hquDNlEUE36eDmFyfOFkL1kwoNyqgXjzWAFrGWAqYClBImIiIiIiIiIZgEGMURzwXQpRxUtC5e2J08WvX1SA6N04VC67aVdJ3G/0sybCopBNtUQvx1rxjTzousmLItoMIkBINQPwDp03blIaEDfHsDTLO875gMFq6b2mFAUwGiTjYiIiIiIiIiIZjUGMUQ0eZLKwqUZSH4yDRmYPsswaNieQsNsL+M6iWMI6T2ExpEJKZEwiiIHoXQ6AEOaj/ghYY8xPlWNCdOUecOtM517bfjaAPdBWf5LUQDXCsC5YKr3ioiIiIiIiIiI5hAGMUQ0N8V6CU112TgRD2BGalp45HVCfkQUfbwSVUkIfaLPN/6wZ4hYuJMuyDGlCXCM8WVJ940T10sl2CvLkAV65H3VDBStlSW/iIiIiIiIiIiIJhGDGCKiqRQbQ2hiPo5FKIQuwyBE+SbApPc6Gi7siYU7Ydk0fRpbFh5mHb03T2xbwfG/AEVNCW4yBDnRsAcJZfdCA0DIDYTdQNgX355zIZC3WG6LiIiIiIiIiIhokjGIISKa7SY47IkRWkIokxLYaKmhTeq80NCgJ7pNERx/qKMogL0GyG+QvYOIiIiIiIiIiIimCIMYIiIaG0UFDGYA5vFvS4iUsCak97IJpQlyovMSxt2BAIwOwJQPmFyAKY89YIiIiIiIiIiIaFpgEENERFNPUQDFxPCEiIiIiIiIiIhmnQkaFZmIiIiIiIiIiIiIiIhSMYghIiIiIiIiIiIiIiLKEQYxREREREREREREREREOcIghoiIiIiIiIiIiIiIKEcYxBAREREREREREREREeUIgxgiIiIiIiIiIiIiIqIcYRBDRERERERERERERESUIwxiiIiIiIiIiIiIiIiIcoRBDBERERERERERERERUY4wiCEiIiIiIiIiIiIiIsoRBjFEREREREREREREREQ5wiCGiIiIiIiIiIiIiIgoRxjEEBERERERERERERER5QiDGCIiIiIiIiIiIiIiohxhEENERERERERERERERJQjDGKIiIiIiIiIiIiIiIhyhEEMERERERERERERERFRjjCIISIiIiIiIiIiIiIiyhEGMURERERERERERERERDnCIIaIiIiIiIiIiIiIiChHGMQQERERERERERERERHlCIMYIiIiIiIiIiIiIiKiHGEQQ0RERERERERERERElCMMYoiIiIiIiIiIiIiIiHKEQQwREREREREREREREVGOGKd6B2YKIQQAwO12T/GeTC+hUAherxdutxsmk2mqd4dozuMxSTRz8Hglmjl4vBLNXDx+iWYOHq9EMweP17hoXhDNDzJhEJOlgYEBAEBNTc0U7wkREREREREREREREU0XAwMDcLlcGZcrYqSohgAAmqahpaUFeXl5UBRlqndn2nC73aipqUFzczPy8/OneneI5jwek0QzB49XopmDxyvRzMXjl2jm4PFKNHPweI0TQmBgYABVVVVQ1cwjwbBHTJZUVcW8efOmejemrfz8/Dl/0BFNJzwmiWYOHq9EMwePV6KZi8cv0czB45Vo5uDxKg3XEyYqc0RDRERERERERERERERE48IghoiIiIiIiIiIiIiIKEcYxNC4WCwWfPOb34TFYpnqXSEi8Jgkmkl4vBLNHDxeiWYuHr9EMwePV6KZg8fr6ClCCDHVO0FERERERERERERERDQbsUcMERERERERERERERFRjjCIISIiIiIiIiIiIiIiyhEGMURERERERERERERERDnCIIaIiIiIiIiIiIiIiChHGMTMQvfddx/OO+885OXloaysDDfeeCMOHz6ctI4QAnfffTeqqqpgs9lw6aWXYv/+/UnrPPzww7j00kuRn58PRVHQ19c35Ll6e3txyy23wOVyweVy4ZZbbkm7Xqq9e/di48aNsNlsqK6uxre+9S0IIWLLW1tbcdNNN6GhoQGqquLOO+8cy1tBNC3MhmPy1VdfxUUXXYTi4mLYbDYsXboU3//+98f0fhBNZ7PheN2yZQsURRnSDh06NKb3hGi6mg3H62233Zb2eF2xYsWY3hOimWI2HL8A8JOf/ATLli2DzWZDQ0MD/vu//3vU7wXRdDfdj1e/34/bbrsNq1atgtFoxI033jhkHZ5jorliMo/X//iP/8D69etht9tRUFCQ9T7O5XPCDGJmoa1bt+L222/H66+/js2bNyMcDuOqq66Cx+OJrXP//ffjgQcewI9//GO8+eabqKiowJVXXomBgYHYOl6vF9dccw2+/vWvZ3yum266Ce+88w5eeOEFvPDCC3jnnXdwyy23DLt/brcbV155JaqqqvDmm2/iwQcfxHe/+1088MADsXUCgQBKS0tx1113YfXq1eN4N4im3mw4Jh0OB+644w5s27YNBw8exDe+8Q184xvfwMMPPzyOd4Zo+pkNx2vU4cOH0draGmv19fVjeEeIpq/ZcLz+8Ic/TDpOm5ubUVRUhA996EPjeGeIpr/ZcPz+9Kc/xde+9jXcfffd2L9/P+655x7cfvvt+OMf/ziOd4Zo+pnux2skEoHNZsM//dM/YdOmTWnX4Tkmmism83gNBoP40Ic+hM9//vNZ79+cPycsaNbr6OgQAMTWrVuFEEJomiYqKirEt7/97dg6fr9fuFwu8bOf/WzI419++WUBQPT29ibNP3DggAAgXn/99di8HTt2CADi0KFDGffnoYceEi6XS/j9/ti8++67T1RVVQlN04asv3HjRvHFL34x25dLNO3N9GMy6v3vf7/4+Mc/PuLrJZrJZuLxmuk5iWa7mXi8pnrqqaeEoiiisbExq9dMNFvMxOP3wgsvFF/5yleSHvfFL35RXHTRRdm/cKIZaLodr4k+8YlPiBtuuGHYdXiOieaSXB2viR599FHhcrmy2p+5fk6YPWLmgP7+fgBAUVERAODkyZNoa2vDVVddFVvHYrFg48aN2L59e9bb3bFjB1wuF9atWxebd8EFF8Dlcg27nR07dmDjxo2wWCyxeVdffTVaWlrQ2NiY9fMTzVSz4ZjcvXs3tm/fjo0bN2a9f0Qz0Uw+XteuXYvKykpcccUVePnll7PeN6KZaiYfr1G//OUvsWnTJtTW1ma9f0SzwUw8fgOBAKxWa9LjbDYbdu7ciVAolPU+Es000+14JaLMcnW8jtVcPyfMIGaWE0LgS1/6Ei6++GKsXLkSANDW1gYAKC8vT1q3vLw8tiwbbW1tKCsrGzK/rKxs2O20tbWlfe7EfSOarWb6MTlv3jxYLBace+65uP322/HpT3866/0jmmlm6vFaWVmJhx9+GH/4wx/w5JNPoqGhAVdccQW2bduW9f4RzTQz9XhN1Nraiueff55/W2nOmanH79VXX41f/OIXeOuttyCEwK5du/DII48gFAqhq6sr630kmkmm4/FKROnl8ngdq7l+TphBzCx3xx13YM+ePfjtb387ZJmiKEn3hRBD5o0k3fqJ21mxYgWcTiecTife8573DPvcmbZHNJvM9GPylVdewa5du/Czn/0MP/jBD9K+DqLZYqYerw0NDfjMZz6Ds88+GxdeeCEeeughXHfddfjud787qv0jmklm6vGa6LHHHkNBQUHaQYaJZrOZevz+67/+K97znvfgggsugMlkwg033IDbbrsNAGAwGEa1j0QzxXQ9XoloqFwfryPhOeGhjFO9A5Q7X/jCF/Dss89i27ZtmDdvXmx+RUUFAJk0VlZWxuZ3dHQMSSWHU1FRgfb29iHzOzs7Y9v585//HOuWbbPZYo9LTTk7OjoADE1kiWaT2XBMLliwAACwatUqtLe34+6778bHPvaxrPeRaKaYDcdrogsuuAC/+c1vst4/oplkNhyvQgg88sgjuOWWW2A2m7PeN6KZbiYfvzabDY888gh+/vOfo729PdYjNS8vDyUlJVnvI9FMMV2PVyIaKtfHazZ4Tngo9oiZhYQQuOOOO/Dkk0/ipZdeip04jVqwYAEqKiqwefPm2LxgMIitW7di/fr1WT/PhRdeiP7+fuzcuTM274033kB/f39sO7W1tVi8eDEWL16M6urq2OO2bduGYDAYe9yLL76Iqqoq1NXVjeUlE01rs/WYFEIgEAhkvX9EM8FsPV53796d9EWbaDaYTcfr1q1bcezYMXzqU5/Ker+IZrLZdPyaTCbMmzcPBoMBTzzxBK6//nqoKk+10Owx3Y9XIoqbrOM1GzwnnIagWefzn/+8cLlcYsuWLaK1tTXWvF5vbJ1vf/vbwuVyiSeffFLs3btXfOxjHxOVlZXC7XbH1mltbRW7d+8W//Vf/yUAiG3btondu3eL7u7u2DrXXHONOOuss8SOHTvEjh07xKpVq8T1118/7P719fWJ8vJy8bGPfUzs3btXPPnkkyI/P19897vfTVpv9+7dYvfu3eKcc84RN910k9i9e7fYv3//BL1LRJNnNhyTP/7xj8Wzzz4rjhw5Io4cOSIeeeQRkZ+fL+66664JfKeIpt5sOF6///3vi6eeekocOXJE7Nu3T/zLv/yLACD+8Ic/TOA7RTT1ZsPxGvXxj39crFu3bgLeFaKZYTYcv4cPHxa//vWvxZEjR8Qbb7whPvKRj4iioiJx8uTJiXujiKaB6X68CiHE/v37xe7du8V73/tecemll8bOJyXiOSaaCybzeG1qahK7d+8W99xzj3A6nbFjbGBgIOP+zfVzwgxiZiEAadujjz4aW0fTNPHNb35TVFRUCIvFIjZs2CD27t2btJ1vfvObI26nu7tb3HzzzSIvL0/k5eWJm2++WfT29o64j3v27BGXXHKJsFgsoqKiQtx9991C07QRX0dtbe043hmiqTEbjskf/ehHYsWKFcJut4v8/Hyxdu1a8dBDD4lIJDLet4doWpkNx+t3vvMdsWjRImG1WkVhYaG4+OKLxXPPPTfet4Zo2pkNx6sQ8h9Sm80mHn744fG8HUQzymw4fg8cOCDWrFkjbDabyM/PFzfccIM4dOjQeN8aomlnJhyvtbW1abc90uvgOSaabSbzeP3EJz6Rdp2XX3552H2cy+eEFSH0EXGIiIiIiIiIiIiIiIhoQrFwKRERERERERERERERUY4wiCEiIiIiIiIiIiIiIsoRBjFEREREREREREREREQ5wiCGiIiIiIiIiIiIiIgoRxjEEBERERERERERERER5QiDGCIiIiIiIiIiIiIiohxhEENERERERERERERERJQjDGKIiIiIiIiIiIiIiIhyhEEMERERERERERERERFRjjCIISIiIiKiOee2226DoihQFAUmkwnl5eW48sor8cgjj0DTtKy389hjj6GgoCB3O0pERERERDMegxgiIiIiIpqTrrnmGrS2tqKxsRHPP/88LrvsMnzxi1/E9ddfj3A4PNW7R0REREREswSDGCIiIiIimpMsFgsqKipQXV2Ns88+G1//+tfxzDPP4Pnnn8djjz0GAHjggQewatUqOBwO1NTU4B//8R8xODgIANiyZQs++clPor+/P9a75u677wYABINBfPWrX0V1dTUcDgfWrVuHLVu2TM0LJSIiIiKiKcUghoiIiIiISHf55Zdj9erVePLJJwEAqqriRz/6Efbt24df/epXeOmll/DVr34VALB+/Xr84Ac/QH5+PlpbW9Ha2oqvfOUrAIBPfvKTeO211/DEE09gz549+NCHPoRrrrkGR48enbLXRkREREREU0MRQoip3gkiIiIiIqLJdNttt6Gvrw9PP/30kGUf/ehHsWfPHhw4cGDIsv/93//F5z//eXR1dQGQY8Tceeed6Ovri61z/Phx1NfX4/Tp06iqqorN37RpE84//3zce++9E/56iIiIiIho+jJO9Q4QERERERFNJ0IIKIoCAHj55Zdx77334sCBA3C73QiHw/D7/fB4PHA4HGkf//bbb0MIgSVLliTNDwQCKC4uzvn+ExERERHR9MIghoiIiIiIKMHBgwexYMECNDU14dprr8XnPvc5/Nu//RuKiorw6quv4lOf+hRCoVDGx2uaBoPBgLfeegsGgyFpmdPpzPXuExERERHRNMMghoiIiIiISPfSSy9h7969+Od//mfs2rUL4XAY3/ve96CqcnjN3//+90nrm81mRCKRpHlr165FJBJBR0cHLrnkkknbdyIiIiIimp4YxBARERER0ZwUCATQ1taGSCSC9vZ2vPDCC7jvvvtw/fXX49Zbb8XevXsRDofx4IMP4r3vfS9ee+01/OxnP0vaRl1dHQYHB/G3v/0Nq1evht1ux5IlS3DzzTfj1ltvxfe+9z2sXbsWXV1deOmll7Bq1Spce+21U/SKiYiIiIhoKqhTvQNERERERERT4YUXXkBlZSXq6upwzTXX4OWXX8aPfvQjPPPMMzAYDFizZg0eeOABfOc738HKlSvxP//zP7jvvvuStrF+/Xp87nOfw0c+8hGUlpbi/vvvBwA8+uijuPXWW/HlL38ZDQ0NeN/73oc33ngDNTU1U/FSiYiIiIhoCilCCDHVO0FERERERERERERERDQbsUcMERERERERERERERFRjjCIISIiIiIiIiIiIiIiyhEGMURERERERERERERERDnCIIaIiIiIiIiIiIiIiChHGMQQERERERERERERERHlCIMYIiIiIiIiIiIiIiKiHGEQQ0RERERERERERERElCMMYoiIiIiIiIiIiIiIiHKEQQwREREREREREREREVGOMIghIiIiIiIiIiIiIiLKEQYxREREREREREREREREOfL/AwZzoBez9dRHAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for selected year\n",
+    "\n",
+    "selected_year = 2010\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data_ERA5,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    ")\n",
+    "\n",
+    "plot_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "    plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    ")\n",
+    "\n",
+    "# plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_QDM,\n",
+    "#     plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "#     plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8a41ce5a-afa4-450b-a2aa-d553b34e5a64",
+   "metadata": {},
+   "source": [
+    "## TEST - QDM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "0f9385e5-b6f1-4f2c-9876-ee1b618214fb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Change observed and cmip to df\n",
+    "\n",
+    "# # Copy data \n",
+    "# cmip_mean = ensemble_data_CMIP[\"Mean\"].copy()\n",
+    "\n",
+    "# # Change into df\n",
+    "# cmip_mean_df = cmip_mean.to_frame(name=\"discharge\")\n",
+    "# observed_output_df = observed_output.to_frame(name=\"discharge\")\n",
+    "\n",
+    "# # Select open water season period to exclude winter months from quantiles \n",
+    "# def select_open_water_season(series_or_df):\n",
+    "\n",
+    "#     data = series_or_df.copy()\n",
+    "#     data.index = pd.to_datetime(data.index)\n",
+    "\n",
+    "#     mask = (((data.index.month > 5) & (data.index.month < 10)) | ((data.index.month == 5) & (data.index.day >= 18)) |((data.index.month == 10) & (data.index.day <= 17)))\n",
+    "\n",
+    "#     return data[mask]\n",
+    "\n",
+    "# observed_open = select_open_water_season(observed_output_df[\"discharge\"])\n",
+    "# cmip_open = select_open_water_season(cmip_mean_df[\"discharge\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "f20e8bd2-58ba-4139-85aa-0a3bb4c0d647",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# def quantile_mapping(observed, modelled, n):\n",
+    "#     # Define a common quantile grid (e.g., 1000 points between 0 and 1)\n",
+    "#     quantiles = np.linspace(0, 1, n)\n",
+    "\n",
+    "#     # Sort the data\n",
+    "#     observed_sorted = np.sort(observed)\n",
+    "#     modelled_sorted = np.sort(modelled)\n",
+    "\n",
+    "#     # Interpolate both series onto the common quantile grid\n",
+    "#     observed_interpolated = interp1d(np.linspace(0, 1, len(observed_sorted)), observed_sorted, bounds_error=False, fill_value=\"extrapolate\")\n",
+    "#     modelled_interpolated = interp1d(np.linspace(0, 1, len(modelled_sorted)), modelled_sorted, bounds_error=False, fill_value=\"extrapolate\")\n",
+    "\n",
+    "#     observed_on_quantiles = observed_interpolated(quantiles)\n",
+    "#     modelled_on_quantiles = modelled_interpolated(quantiles)\n",
+    "\n",
+    "#     mapping_function = interp1d(modelled_on_quantiles, observed_on_quantiles, bounds_error=False, fill_value=\"extrapolate\")\n",
+    "\n",
+    "#     return mapping_function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "7237db83-153e-4b5b-abf3-8efe0cb9cbe3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# qm_daily = quantile_mapping(observed_open, cmip_open, 1000)\n",
+    "# # qm_daily = quantile_mapping(observed_output_df[\"discharge\"], cmip_mean_df[\"discharge\"], 1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "22ffb8c5-c529-42e2-af1b-7a9d41d37737",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# cmip_corrected_values = qm_daily(cmip_mean_df[\"discharge\"])\n",
+    "\n",
+    "# cmip_mean_qm = pd.Series(cmip_corrected_values,index=cmip_mean_df.index,name=\"Mean\")\n",
+    "# cmip_mean_qm = cmip_mean_qm.fillna(0)\n",
+    "# cmip_mean_qm = cmip_mean_qm.clip(lower=0)\n",
+    "\n",
+    "# # cmip_mean_qm.head()\n",
+    "# # cmip_mean_qm.head(500)\n",
+    "\n",
+    "# ensemble_data_CMIP_QM = ensemble_data_CMIP.copy()\n",
+    "# ensemble_data_CMIP_QM[\"Mean\"] = cmip_mean_qm\n",
+    "\n",
+    "# ensemble_data_CMIP_QM.head(500)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "53515218-430b-4fd5-8a39-bcd90273f144",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# selected_year = 2013\n",
+    "\n",
+    "# plot_ensemble(\n",
+    "#     ensemble_data=ensemble_data_CMIP_QM,\n",
+    "#     plot_start=pd.to_datetime(f\"{selected_year}-01-01\"),\n",
+    "#     plot_end=pd.to_datetime(f\"{selected_year}-12-31\")\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "95c6b9fe-de4c-4f0f-ba81-27cac73ed1b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Qm_func = quantile_mapping(\n",
+    "#     observed=ensemble_data_ERA5, \n",
+    "#     modelled=ensemble_data_CMIP, \n",
+    "#     n=1000\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "bab56168-fcda-42d7-9d01-6341a90c4810",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Corrected = Qm_func(toekomstige data)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d017577d-79da-4a97-9522-81f4c307f3aa",
+   "metadata": {},
+   "source": [
+    "## 6. Lowflow calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "dcc14e37-5aea-4b00-ae71-32b68ee03d4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_counter_ensemble(ensemble_data, start_date, end_date):\n",
+    "    \n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "    \n",
+    "        year = years[i]\n",
+    "    \n",
+    "        # Define start and end month-day\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "    \n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)\n",
+    "        ]\n",
+    "\n",
+    "        # Set zeros to count from\n",
+    "        observed_lowflow_days = 0\n",
+    "        modelled_lowflow_days = []\n",
+    "        modelmean_lowflow_days = 0\n",
+    "\n",
+    "        # Count observed lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "            observed_q = year_data.iloc[j][\"Observed discharge\"]\n",
+    "\n",
+    "            if observed_q < q_critical:\n",
+    "                observed_lowflow_days += 1\n",
+    "\n",
+    "        # Count model mean lowflow days\n",
+    "        for j in range(len(year_data)):\n",
+    "            modelmean_q = year_data.iloc[j][\"Mean\"]\n",
+    "\n",
+    "            if modelmean_q < q_critical:\n",
+    "                modelmean_lowflow_days += 1\n",
+    "\n",
+    "        # Count modelled lowflow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "        \n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"observed\": observed_lowflow_days,\n",
+    "            \"modelmean\": modelmean_lowflow_days,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)\n",
+    "        })\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    days_sum = lowflow_days[[\"observed\", \"modelmean\", \"set_1\", \"set_2\", \"set_3\", \"set_4\", \"set_5\", \"set_avg\"]].sum()\n",
+    "\n",
+    "    print(days_sum)\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "7460b853-5619-44c9-ac89-3c6fc099bde6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">observed     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">670.0</span>\n",
+       "modelmean    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">735.0</span>\n",
+       "set_1        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">975.0</span>\n",
+       "set_2        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">689.0</span>\n",
+       "set_3        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">755.0</span>\n",
+       "set_4        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">763.0</span>\n",
+       "set_5        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">537.0</span>\n",
+       "set_avg      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">744.0</span>\n",
+       "dtype: float64\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "observed     \u001b[1;36m670.0\u001b[0m\n",
+       "modelmean    \u001b[1;36m735.0\u001b[0m\n",
+       "set_1        \u001b[1;36m975.0\u001b[0m\n",
+       "set_2        \u001b[1;36m689.0\u001b[0m\n",
+       "set_3        \u001b[1;36m755.0\u001b[0m\n",
+       "set_4        \u001b[1;36m763.0\u001b[0m\n",
+       "set_5        \u001b[1;36m537.0\u001b[0m\n",
+       "set_avg      \u001b[1;36m744.0\u001b[0m\n",
+       "dtype: float64\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">observed     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">670.0</span>\n",
+       "modelmean    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">635.0</span>\n",
+       "set_1        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">887.0</span>\n",
+       "set_2        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">555.0</span>\n",
+       "set_3        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">660.0</span>\n",
+       "set_4        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">678.0</span>\n",
+       "set_5        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">430.0</span>\n",
+       "set_avg      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">643.0</span>\n",
+       "dtype: float64\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "observed     \u001b[1;36m670.0\u001b[0m\n",
+       "modelmean    \u001b[1;36m635.0\u001b[0m\n",
+       "set_1        \u001b[1;36m887.0\u001b[0m\n",
+       "set_2        \u001b[1;36m555.0\u001b[0m\n",
+       "set_3        \u001b[1;36m660.0\u001b[0m\n",
+       "set_4        \u001b[1;36m678.0\u001b[0m\n",
+       "set_5        \u001b[1;36m430.0\u001b[0m\n",
+       "set_avg      \u001b[1;36m643.0\u001b[0m\n",
+       "dtype: float64\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>observed</th>\n",
+       "      <th>modelmean</th>\n",
+       "      <th>set_1</th>\n",
+       "      <th>set_2</th>\n",
+       "      <th>set_3</th>\n",
+       "      <th>set_4</th>\n",
+       "      <th>set_5</th>\n",
+       "      <th>set_avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1990</td>\n",
+       "      <td>11</td>\n",
+       "      <td>36</td>\n",
+       "      <td>60</td>\n",
+       "      <td>35</td>\n",
+       "      <td>34</td>\n",
+       "      <td>34</td>\n",
+       "      <td>40</td>\n",
+       "      <td>41.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1991</td>\n",
+       "      <td>16</td>\n",
+       "      <td>45</td>\n",
+       "      <td>51</td>\n",
+       "      <td>39</td>\n",
+       "      <td>44</td>\n",
+       "      <td>47</td>\n",
+       "      <td>40</td>\n",
+       "      <td>44.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1992</td>\n",
+       "      <td>32</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1993</td>\n",
+       "      <td>18</td>\n",
+       "      <td>0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1994</td>\n",
+       "      <td>36</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1995</td>\n",
+       "      <td>25</td>\n",
+       "      <td>32</td>\n",
+       "      <td>43</td>\n",
+       "      <td>20</td>\n",
+       "      <td>32</td>\n",
+       "      <td>37</td>\n",
+       "      <td>16</td>\n",
+       "      <td>30.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1996</td>\n",
+       "      <td>0</td>\n",
+       "      <td>97</td>\n",
+       "      <td>108</td>\n",
+       "      <td>97</td>\n",
+       "      <td>99</td>\n",
+       "      <td>101</td>\n",
+       "      <td>74</td>\n",
+       "      <td>96.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1997</td>\n",
+       "      <td>0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>50</td>\n",
+       "      <td>34</td>\n",
+       "      <td>36</td>\n",
+       "      <td>39</td>\n",
+       "      <td>32</td>\n",
+       "      <td>38.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1998</td>\n",
+       "      <td>44</td>\n",
+       "      <td>5</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1999</td>\n",
+       "      <td>35</td>\n",
+       "      <td>18</td>\n",
+       "      <td>39</td>\n",
+       "      <td>7</td>\n",
+       "      <td>21</td>\n",
+       "      <td>24</td>\n",
+       "      <td>2</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2000</td>\n",
+       "      <td>20</td>\n",
+       "      <td>29</td>\n",
+       "      <td>36</td>\n",
+       "      <td>26</td>\n",
+       "      <td>29</td>\n",
+       "      <td>29</td>\n",
+       "      <td>22</td>\n",
+       "      <td>28.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2001</td>\n",
+       "      <td>60</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2002</td>\n",
+       "      <td>52</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2003</td>\n",
+       "      <td>51</td>\n",
+       "      <td>6</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2004</td>\n",
+       "      <td>5</td>\n",
+       "      <td>23</td>\n",
+       "      <td>41</td>\n",
+       "      <td>17</td>\n",
+       "      <td>27</td>\n",
+       "      <td>31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2005</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2006</td>\n",
+       "      <td>42</td>\n",
+       "      <td>24</td>\n",
+       "      <td>40</td>\n",
+       "      <td>20</td>\n",
+       "      <td>31</td>\n",
+       "      <td>29</td>\n",
+       "      <td>0</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2007</td>\n",
+       "      <td>25</td>\n",
+       "      <td>26</td>\n",
+       "      <td>42</td>\n",
+       "      <td>15</td>\n",
+       "      <td>29</td>\n",
+       "      <td>31</td>\n",
+       "      <td>7</td>\n",
+       "      <td>25.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>37</td>\n",
+       "      <td>21</td>\n",
+       "      <td>38</td>\n",
+       "      <td>18</td>\n",
+       "      <td>23</td>\n",
+       "      <td>23</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2009</td>\n",
+       "      <td>42</td>\n",
+       "      <td>13</td>\n",
+       "      <td>23</td>\n",
+       "      <td>8</td>\n",
+       "      <td>14</td>\n",
+       "      <td>16</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2010</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2011</td>\n",
+       "      <td>36</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2012</td>\n",
+       "      <td>13</td>\n",
+       "      <td>91</td>\n",
+       "      <td>91</td>\n",
+       "      <td>88</td>\n",
+       "      <td>90</td>\n",
+       "      <td>91</td>\n",
+       "      <td>64</td>\n",
+       "      <td>85.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2013</td>\n",
+       "      <td>21</td>\n",
+       "      <td>131</td>\n",
+       "      <td>130</td>\n",
+       "      <td>131</td>\n",
+       "      <td>132</td>\n",
+       "      <td>133</td>\n",
+       "      <td>127</td>\n",
+       "      <td>131.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>43</td>\n",
+       "      <td>0</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    year  observed  modelmean  set_1  set_2  set_3  set_4  set_5  set_avg\n",
+       "0   1990        11         36     60     35     34     34     40     41.0\n",
+       "1   1991        16         45     51     39     44     47     40     44.0\n",
+       "2   1992        32          0      4      0      0      0      0      1.0\n",
+       "3   1993        18          0     16      0      4      2      0      4.0\n",
+       "4   1994        36          0      7      0      0      0      0      1.0\n",
+       "5   1995        25         32     43     20     32     37     16     30.0\n",
+       "6   1996         0         97    108     97     99    101     74     96.0\n",
+       "7   1997         0         38     50     34     36     39     32     38.0\n",
+       "8   1998        44          5     11      0      5      2      0      4.0\n",
+       "9   1999        35         18     39      7     21     24      2     19.0\n",
+       "10  2000        20         29     36     26     29     29     22     28.0\n",
+       "11  2001        60          0      0      0      0      0      0      0.0\n",
+       "12  2002        52          0      8      0      0      0      0      2.0\n",
+       "13  2003        51          6     21      0      7      9      0      7.0\n",
+       "14  2004         5         23     41     17     27     31      0     23.0\n",
+       "15  2005         0          0      0      0      0      0      0      0.0\n",
+       "16  2006        42         24     40     20     31     29      0     24.0\n",
+       "17  2007        25         26     42     15     29     31      7     25.0\n",
+       "18  2008        37         21     38     18     23     23      6     22.0\n",
+       "19  2009        42         13     23      8     14     16      0     12.0\n",
+       "20  2010         6          0      0      0      0      0      0      0.0\n",
+       "21  2011        36          0      7      0      3      0      0      2.0\n",
+       "22  2012        13         91     91     88     90     91     64     85.0\n",
+       "23  2013        21        131    130    131    132    133    127    131.0\n",
+       "24  2014        43          0     21      0      0      0      0      4.0"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lowflow_ERA5 = lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data_ERA5,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date\n",
+    ")\n",
+    "\n",
+    "lowflow_CMIP = lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date\n",
+    ")\n",
+    "\n",
+    "# lowflow_QDM = lowflow_counter_ensemble(\n",
+    "#     ensemble_data=ensemble_data_CMIP_corrected,\n",
+    "#     start_date=evaluation_start,\n",
+    "#     end_date=validation_end_date\n",
+    "# )\n",
+    "\n",
+    "lowflow_CMIP"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d98001e7-ada9-4415-ae0b-ed7cb8888319",
+   "metadata": {},
+   "source": [
+    "## 7. Cumsum"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "1e9e205d-08bf-4f19-9b12-a0141a4fad99",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# If including QDM, change function to -> def rank(lowflow_ERA5, lowflow_CMIP, lowflow_QDM):\n",
+    "\n",
+    "def rank(lowflow_ERA5, lowflow_CMIP):\n",
+    "\n",
+    "    # Combine tables\n",
+    "    rank_table = pd.DataFrame({\n",
+    "        \"Observed\": np.sort(lowflow_ERA5[\"observed\"]),\n",
+    "        \"ERA5\": np.sort(lowflow_ERA5[\"set_avg\"]),\n",
+    "        \"CMIP6\": np.sort(lowflow_CMIP[\"set_avg\"]),\n",
+    "        # \"QDM\": np.sort(lowflow_QDM[\"set_avg\"])\n",
+    "    })\n",
+    "    \n",
+    "    rank_table.insert(0, \"rank\", range(1, len(rank_table) + 1))\n",
+    "\n",
+    "    return rank_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "02d8a545-838c-4da5-9935-22f34d49f4ee",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>rank</th>\n",
+       "      <th>Observed</th>\n",
+       "      <th>ERA5</th>\n",
+       "      <th>CMIP6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>13</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>16</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>18</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>20</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>11</td>\n",
+       "      <td>21</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12</td>\n",
+       "      <td>25</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>12.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>13</td>\n",
+       "      <td>25</td>\n",
+       "      <td>29.0</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>14</td>\n",
+       "      <td>32</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>22.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>15</td>\n",
+       "      <td>35</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>16</td>\n",
+       "      <td>36</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>17</td>\n",
+       "      <td>36</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>25.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>18</td>\n",
+       "      <td>37</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>28.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>19</td>\n",
+       "      <td>42</td>\n",
+       "      <td>41.0</td>\n",
+       "      <td>30.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>20</td>\n",
+       "      <td>42</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>38.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>21</td>\n",
+       "      <td>43</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>41.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>22</td>\n",
+       "      <td>44</td>\n",
+       "      <td>58.0</td>\n",
+       "      <td>44.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>23</td>\n",
+       "      <td>51</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>85.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>24</td>\n",
+       "      <td>52</td>\n",
+       "      <td>67.0</td>\n",
+       "      <td>96.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>25</td>\n",
+       "      <td>60</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>131.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    rank  Observed   ERA5  CMIP6\n",
+       "0      1         0    0.0    0.0\n",
+       "1      2         0    0.0    0.0\n",
+       "2      3         0    0.0    0.0\n",
+       "3      4         5    1.0    1.0\n",
+       "4      5         6    2.0    1.0\n",
+       "5      6        11    5.0    2.0\n",
+       "6      7        13   10.0    2.0\n",
+       "7      8        16   17.0    4.0\n",
+       "8      9        18   19.0    4.0\n",
+       "9     10        20   19.0    4.0\n",
+       "10    11        21   22.0    7.0\n",
+       "11    12        25   24.0   12.0\n",
+       "12    13        25   29.0   19.0\n",
+       "13    14        32   30.0   22.0\n",
+       "14    15        35   32.0   23.0\n",
+       "15    16        36   34.0   24.0\n",
+       "16    17        36   36.0   25.0\n",
+       "17    18        37   39.0   28.0\n",
+       "18    19        42   41.0   30.0\n",
+       "19    20        42   45.0   38.0\n",
+       "20    21        43   54.0   41.0\n",
+       "21    22        44   58.0   44.0\n",
+       "22    23        51   59.0   85.0\n",
+       "23    24        52   67.0   96.0\n",
+       "24    25        60  101.0  131.0"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rank_table = rank(lowflow_ERA5, lowflow_CMIP)\n",
+    "# rank_table = rank(lowflow_ERA5, lowflow_CMIP)\n",
+    "\n",
+    "rank_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "f87182f3-7a63-4856-9594-f53b5dd421b8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Observed_cumsum</th>\n",
+       "      <th>ERA5_cumsum</th>\n",
+       "      <th>CMIP6_cumsum</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>5</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>11</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>22</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>35</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>6.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>51</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>10.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>69</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>14.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>89</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>18.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>110</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>25.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>135</td>\n",
+       "      <td>119.0</td>\n",
+       "      <td>37.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>160</td>\n",
+       "      <td>148.0</td>\n",
+       "      <td>56.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>192</td>\n",
+       "      <td>178.0</td>\n",
+       "      <td>78.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>227</td>\n",
+       "      <td>210.0</td>\n",
+       "      <td>101.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>263</td>\n",
+       "      <td>244.0</td>\n",
+       "      <td>125.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>299</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>150.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>336</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>178.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>378</td>\n",
+       "      <td>360.0</td>\n",
+       "      <td>208.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>420</td>\n",
+       "      <td>405.0</td>\n",
+       "      <td>246.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>463</td>\n",
+       "      <td>459.0</td>\n",
+       "      <td>287.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>507</td>\n",
+       "      <td>517.0</td>\n",
+       "      <td>331.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>558</td>\n",
+       "      <td>576.0</td>\n",
+       "      <td>416.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>610</td>\n",
+       "      <td>643.0</td>\n",
+       "      <td>512.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>670</td>\n",
+       "      <td>744.0</td>\n",
+       "      <td>643.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Observed_cumsum  ERA5_cumsum  CMIP6_cumsum\n",
+       "0                 0          0.0           0.0\n",
+       "1                 0          0.0           0.0\n",
+       "2                 0          0.0           0.0\n",
+       "3                 5          1.0           1.0\n",
+       "4                11          3.0           2.0\n",
+       "5                22          8.0           4.0\n",
+       "6                35         18.0           6.0\n",
+       "7                51         35.0          10.0\n",
+       "8                69         54.0          14.0\n",
+       "9                89         73.0          18.0\n",
+       "10              110         95.0          25.0\n",
+       "11              135        119.0          37.0\n",
+       "12              160        148.0          56.0\n",
+       "13              192        178.0          78.0\n",
+       "14              227        210.0         101.0\n",
+       "15              263        244.0         125.0\n",
+       "16              299        280.0         150.0\n",
+       "17              336        319.0         178.0\n",
+       "18              378        360.0         208.0\n",
+       "19              420        405.0         246.0\n",
+       "20              463        459.0         287.0\n",
+       "21              507        517.0         331.0\n",
+       "22              558        576.0         416.0\n",
+       "23              610        643.0         512.0\n",
+       "24              670        744.0         643.0"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cumsum_table = pd.DataFrame({\n",
+    "    \"Observed_cumsum\": rank_table[\"Observed\"].cumsum(),\n",
+    "     \"ERA5_cumsum\": rank_table[\"ERA5\"].cumsum(),\n",
+    "    \"CMIP6_cumsum\": rank_table[\"CMIP6\"].cumsum(),\n",
+    "    # \"QDM_cumsum\": rank_table[\"QDM\"].cumsum()\n",
+    "})\n",
+    "\n",
+    "cumsum_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "78105310-3388-48fa-9471-54003b019753",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_cumsum(rank_table):\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    # Plot cumsum for all columns, skipping rank column\n",
+    "    for i in range(1, len(rank_table.columns)):\n",
+    "        plt.plot(rank_table[\"rank\"], rank_table[rank_table.columns[i]].cumsum(), marker=\"o\", label=rank_table.columns[i])\n",
+    "\n",
+    "    # Plotting\n",
+    "    plt.xlabel(\"Ranked years\")\n",
+    "    plt.ylabel(\"Cumulative low flow days\")\n",
+    "    plt.xticks(rank_table[\"rank\"])\n",
+    "    plt.title(\"Cumulative annual low flow days\")\n",
+    "    # plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "b3fa8488-2d3f-4dbd-b82c-e3f8c5bb04d8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_cumsum(rank_table)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3abc8ad5-90fd-4ce8-bb44-4a5d8540b1d9",
+   "metadata": {},
+   "source": [
+    "## 8. Quantile Mapping"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "cee6e4aa-f4be-45c7-9d7a-d70782c60ad4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def quantile_mapping(observed, modelled, n):\n",
+    "    # Define a common quantile grid (e.g., 1000 points between 0 and 1)\n",
+    "    quantiles = np.linspace(0, 1, n)\n",
+    "\n",
+    "    # Sort the data\n",
+    "    observed_sorted = np.sort(observed)\n",
+    "    modelled_sorted = np.sort(modelled)\n",
+    "\n",
+    "    # Interpolate both series onto the common quantile grid\n",
+    "    observed_interpolated = interp1d(np.linspace(0, 1, len(observed_sorted)), observed_sorted, bounds_error=False, fill_value=\"extrapolate\")\n",
+    "    modelled_interpolated = interp1d(np.linspace(0, 1, len(modelled_sorted)), modelled_sorted, bounds_error=False, fill_value=\"extrapolate\")\n",
+    "\n",
+    "    observed_on_quantiles = observed_interpolated(quantiles)\n",
+    "    modelled_on_quantiles = modelled_interpolated(quantiles)\n",
+    "\n",
+    "    # Create mapping from modelled deficits to observed using interpolation\n",
+    "    mapping_function = interp1d(modelled_on_quantiles, observed_on_quantiles, bounds_error=False, fill_value=\"extrapolate\")\n",
+    "\n",
+    "    return mapping_function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "ccfd9d00-8165-4a95-a9bc-04d017c2d150",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def correct_discharge_ensemble(ensemble_data, reference_data, start_date, end_date, n=1000):\n",
+    "\n",
+    "    corrected_data = pd.DataFrame(index=ensemble_data.index)\n",
+    "\n",
+    "    # Prepare CMIP data\n",
+    "    target = ensemble_data.copy()\n",
+    "    target.index = pd.to_datetime(target.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Prepare ERA5 reference\n",
+    "    reference = reference_data.copy()\n",
+    "    reference.index = pd.to_datetime(reference.index).tz_localize(None).normalize()\n",
+    "\n",
+    "    # Select calibration period\n",
+    "    start_date = pd.to_datetime(start_date).tz_localize(None).normalize()\n",
+    "    end_date = pd.to_datetime(end_date).tz_localize(None).normalize()\n",
+    "\n",
+    "    target_period = target[(target.index >= start_date) &(target.index <= end_date)]\n",
+    "    reference_period = reference[(reference.index >= start_date) &(reference.index <= end_date)]\n",
+    "\n",
+    "    # Correct each parameter set separately\n",
+    "    for i in range(len(par_ensemble)):\n",
+    "\n",
+    "        set_name = f\"Set {i+1}\"\n",
+    "\n",
+    "        qm_function = quantile_mapping(\n",
+    "            observed=reference_period[set_name],\n",
+    "            modelled=target_period[set_name],\n",
+    "            n=n)\n",
+    "\n",
+    "        corrected_data[set_name] = qm_function(target[set_name])\n",
+    "\n",
+    "    # Remove negative discharge\n",
+    "    corrected_data[corrected_data < 0] = 0\n",
+    "\n",
+    "    # Recalculate ensemble mean from corrected sets\n",
+    "    corrected_data[\"Mean\"] = corrected_data.mean(axis=1)\n",
+    "    # set_columns = [f\"Set {i+1}\" for i in range(len(par_ensemble))]\n",
+    "    # corrected_data[\"Mean\"] = corrected_data[set_columns].mean(axis=1)\n",
+    "\n",
+    "    # Keep observed discharge if present\n",
+    "    if \"Observed discharge\" in target.columns:\n",
+    "        corrected_data[\"Observed discharge\"] = target[\"Observed discharge\"]\n",
+    "\n",
+    "    return corrected_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "2d4ef549-838f-44ce-884b-99c5a3447cbd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Set 1</th>\n",
+       "      <th>Set 2</th>\n",
+       "      <th>Set 3</th>\n",
+       "      <th>Set 4</th>\n",
+       "      <th>Set 5</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Observed discharge</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1989-01-02</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>12.40215</td>\n",
+       "      <td>92.004859</td>\n",
+       "      <td>20.881402</td>\n",
+       "      <td>141.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1989-01-03</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>12.40215</td>\n",
+       "      <td>92.004859</td>\n",
+       "      <td>20.881402</td>\n",
+       "      <td>141.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1989-01-04</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>12.40215</td>\n",
+       "      <td>92.004859</td>\n",
+       "      <td>20.881402</td>\n",
+       "      <td>139.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1989-01-05</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>12.40215</td>\n",
+       "      <td>92.004859</td>\n",
+       "      <td>20.881402</td>\n",
+       "      <td>135.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1989-01-06</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>12.40215</td>\n",
+       "      <td>92.004859</td>\n",
+       "      <td>20.881402</td>\n",
+       "      <td>135.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Set 1  Set 2  Set 3     Set 4      Set 5       Mean  \\\n",
+       "1989-01-02    0.0    0.0    0.0  12.40215  92.004859  20.881402   \n",
+       "1989-01-03    0.0    0.0    0.0  12.40215  92.004859  20.881402   \n",
+       "1989-01-04    0.0    0.0    0.0  12.40215  92.004859  20.881402   \n",
+       "1989-01-05    0.0    0.0    0.0  12.40215  92.004859  20.881402   \n",
+       "1989-01-06    0.0    0.0    0.0  12.40215  92.004859  20.881402   \n",
+       "\n",
+       "            Observed discharge  \n",
+       "1989-01-02               141.0  \n",
+       "1989-01-03               141.0  \n",
+       "1989-01-04               139.0  \n",
+       "1989-01-05               135.0  \n",
+       "1989-01-06               135.0  "
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ensemble_data_CMIP_corrected = correct_discharge_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP,\n",
+    "    reference_data=ensemble_data_ERA5,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date,\n",
+    "    n=1000)\n",
+    "\n",
+    "ensemble_data_CMIP_corrected.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "63008778-e23d-4fae-b8f9-f61c789934d7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">observed      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">670.0</span>\n",
+       "modelmean     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">858.0</span>\n",
+       "set_1        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1084.0</span>\n",
+       "set_2         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">804.0</span>\n",
+       "set_3         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">880.0</span>\n",
+       "set_4         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">892.0</span>\n",
+       "set_5         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">631.0</span>\n",
+       "set_avg       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">856.0</span>\n",
+       "dtype: float64\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "observed      \u001b[1;36m670.0\u001b[0m\n",
+       "modelmean     \u001b[1;36m858.0\u001b[0m\n",
+       "set_1        \u001b[1;36m1084.0\u001b[0m\n",
+       "set_2         \u001b[1;36m804.0\u001b[0m\n",
+       "set_3         \u001b[1;36m880.0\u001b[0m\n",
+       "set_4         \u001b[1;36m892.0\u001b[0m\n",
+       "set_5         \u001b[1;36m631.0\u001b[0m\n",
+       "set_avg       \u001b[1;36m856.0\u001b[0m\n",
+       "dtype: float64\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>year</th>\n",
+       "      <th>observed</th>\n",
+       "      <th>modelmean</th>\n",
+       "      <th>set_1</th>\n",
+       "      <th>set_2</th>\n",
+       "      <th>set_3</th>\n",
+       "      <th>set_4</th>\n",
+       "      <th>set_5</th>\n",
+       "      <th>set_avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1990</td>\n",
+       "      <td>11</td>\n",
+       "      <td>60</td>\n",
+       "      <td>68</td>\n",
+       "      <td>42</td>\n",
+       "      <td>44</td>\n",
+       "      <td>57</td>\n",
+       "      <td>63</td>\n",
+       "      <td>55.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1991</td>\n",
+       "      <td>16</td>\n",
+       "      <td>49</td>\n",
+       "      <td>53</td>\n",
+       "      <td>44</td>\n",
+       "      <td>47</td>\n",
+       "      <td>50</td>\n",
+       "      <td>45</td>\n",
+       "      <td>48.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1992</td>\n",
+       "      <td>32</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1993</td>\n",
+       "      <td>18</td>\n",
+       "      <td>15</td>\n",
+       "      <td>37</td>\n",
+       "      <td>14</td>\n",
+       "      <td>17</td>\n",
+       "      <td>20</td>\n",
+       "      <td>0</td>\n",
+       "      <td>18.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1994</td>\n",
+       "      <td>36</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1995</td>\n",
+       "      <td>25</td>\n",
+       "      <td>37</td>\n",
+       "      <td>46</td>\n",
+       "      <td>25</td>\n",
+       "      <td>36</td>\n",
+       "      <td>40</td>\n",
+       "      <td>23</td>\n",
+       "      <td>34.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1996</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113</td>\n",
+       "      <td>115</td>\n",
+       "      <td>111</td>\n",
+       "      <td>113</td>\n",
+       "      <td>118</td>\n",
+       "      <td>110</td>\n",
+       "      <td>113.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1997</td>\n",
+       "      <td>0</td>\n",
+       "      <td>42</td>\n",
+       "      <td>55</td>\n",
+       "      <td>39</td>\n",
+       "      <td>40</td>\n",
+       "      <td>44</td>\n",
+       "      <td>38</td>\n",
+       "      <td>43.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1998</td>\n",
+       "      <td>44</td>\n",
+       "      <td>9</td>\n",
+       "      <td>19</td>\n",
+       "      <td>8</td>\n",
+       "      <td>9</td>\n",
+       "      <td>8</td>\n",
+       "      <td>6</td>\n",
+       "      <td>10.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1999</td>\n",
+       "      <td>35</td>\n",
+       "      <td>42</td>\n",
+       "      <td>54</td>\n",
+       "      <td>35</td>\n",
+       "      <td>47</td>\n",
+       "      <td>45</td>\n",
+       "      <td>13</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2000</td>\n",
+       "      <td>20</td>\n",
+       "      <td>34</td>\n",
+       "      <td>38</td>\n",
+       "      <td>33</td>\n",
+       "      <td>35</td>\n",
+       "      <td>34</td>\n",
+       "      <td>28</td>\n",
+       "      <td>34.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2001</td>\n",
+       "      <td>60</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2002</td>\n",
+       "      <td>52</td>\n",
+       "      <td>1</td>\n",
+       "      <td>14</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2003</td>\n",
+       "      <td>51</td>\n",
+       "      <td>27</td>\n",
+       "      <td>44</td>\n",
+       "      <td>27</td>\n",
+       "      <td>39</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>26.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2004</td>\n",
+       "      <td>5</td>\n",
+       "      <td>50</td>\n",
+       "      <td>61</td>\n",
+       "      <td>51</td>\n",
+       "      <td>63</td>\n",
+       "      <td>49</td>\n",
+       "      <td>18</td>\n",
+       "      <td>48.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2005</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2006</td>\n",
+       "      <td>42</td>\n",
+       "      <td>45</td>\n",
+       "      <td>57</td>\n",
+       "      <td>45</td>\n",
+       "      <td>50</td>\n",
+       "      <td>47</td>\n",
+       "      <td>18</td>\n",
+       "      <td>43.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2007</td>\n",
+       "      <td>25</td>\n",
+       "      <td>34</td>\n",
+       "      <td>47</td>\n",
+       "      <td>29</td>\n",
+       "      <td>36</td>\n",
+       "      <td>44</td>\n",
+       "      <td>15</td>\n",
+       "      <td>34.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>37</td>\n",
+       "      <td>40</td>\n",
+       "      <td>43</td>\n",
+       "      <td>53</td>\n",
+       "      <td>42</td>\n",
+       "      <td>42</td>\n",
+       "      <td>22</td>\n",
+       "      <td>40.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2009</td>\n",
+       "      <td>42</td>\n",
+       "      <td>19</td>\n",
+       "      <td>36</td>\n",
+       "      <td>14</td>\n",
+       "      <td>19</td>\n",
+       "      <td>22</td>\n",
+       "      <td>10</td>\n",
+       "      <td>20.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2010</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2011</td>\n",
+       "      <td>36</td>\n",
+       "      <td>5</td>\n",
+       "      <td>17</td>\n",
+       "      <td>4</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2012</td>\n",
+       "      <td>13</td>\n",
+       "      <td>94</td>\n",
+       "      <td>99</td>\n",
+       "      <td>94</td>\n",
+       "      <td>94</td>\n",
+       "      <td>96</td>\n",
+       "      <td>89</td>\n",
+       "      <td>94.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2013</td>\n",
+       "      <td>21</td>\n",
+       "      <td>134</td>\n",
+       "      <td>132</td>\n",
+       "      <td>136</td>\n",
+       "      <td>135</td>\n",
+       "      <td>135</td>\n",
+       "      <td>133</td>\n",
+       "      <td>134.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2014</td>\n",
+       "      <td>43</td>\n",
+       "      <td>6</td>\n",
+       "      <td>24</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    year  observed  modelmean  set_1  set_2  set_3  set_4  set_5  set_avg\n",
+       "0   1990        11         60     68     42     44     57     63     55.0\n",
+       "1   1991        16         49     53     44     47     50     45     48.0\n",
+       "2   1992        32          2      6      0      2      1      0      2.0\n",
+       "3   1993        18         15     37     14     17     20      0     18.0\n",
+       "4   1994        36          0     13      0      0      2      0      3.0\n",
+       "5   1995        25         37     46     25     36     40     23     34.0\n",
+       "6   1996         0        113    115    111    113    118    110    113.0\n",
+       "7   1997         0         42     55     39     40     44     38     43.0\n",
+       "8   1998        44          9     19      8      9      8      6     10.0\n",
+       "9   1999        35         42     54     35     47     45     13     39.0\n",
+       "10  2000        20         34     38     33     35     34     28     34.0\n",
+       "11  2001        60          0      5      0      0      0      0      1.0\n",
+       "12  2002        52          1     14      0      1      1      0      3.0\n",
+       "13  2003        51         27     44     27     39     21      0     26.0\n",
+       "14  2004         5         50     61     51     63     49     18     48.0\n",
+       "15  2005         0          0      1      0      0      0      0      0.0\n",
+       "16  2006        42         45     57     45     50     47     18     43.0\n",
+       "17  2007        25         34     47     29     36     44     15     34.0\n",
+       "18  2008        37         40     43     53     42     42     22     40.0\n",
+       "19  2009        42         19     36     14     19     22     10     20.0\n",
+       "20  2010         6          0      0      0      0      0      0      0.0\n",
+       "21  2011        36          5     17      4      7      4      0      6.0\n",
+       "22  2012        13         94     99     94     94     96     89     94.0\n",
+       "23  2013        21        134    132    136    135    135    133    134.0\n",
+       "24  2014        43          6     24      0      4     12      0      8.0"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lowflow_CMIP_corrected = lowflow_counter_ensemble(\n",
+    "    ensemble_data=ensemble_data_CMIP_corrected,\n",
+    "    start_date=evaluation_start,\n",
+    "    end_date=validation_end_date)\n",
+    "\n",
+    "lowflow_CMIP_corrected"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step7_CMIP_Projections.ipynb b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step7_CMIP_Projections.ipynb
new file mode 100644
index 00000000..ea3c7ac0
--- /dev/null
+++ b/book/thesis_projects/BSc/2026_Q4_MaximedeBekker_CEG/Workyard/Step7_CMIP_Projections.ipynb
@@ -0,0 +1,3337 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6571f48a-467c-4dc9-8c4b-6029d09672e7",
+   "metadata": {},
+   "source": [
+    "# CMIP Projections\n",
+    "\n",
+    "The 5 parameter sets calculkated in Calibration_HBV.ipynb will be used for a validation period, in which the log NSE will be calculated, a mean will be calculated and total low flow days during the navigation season.\n",
+    "\n",
+    "The structure of this notebook is as follows:\n",
+    "\n",
+    "### 1. Startup & Imports\n",
+    "### 2. Model setup\n",
+    "### 3. Lowflow setup\n",
+    "### 4. Running model\n",
+    "### 5. Lowflow data visualisation\n",
+    "### 6. Forcing data comparison & visualisation\n",
+    "### 7. Algorithm checker (break up, freeze up dates)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14ec2576-8826-48ce-9b0d-3c28be7fec68",
+   "metadata": {},
+   "source": [
+    "## 1. Startup & Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "71668e92-f5c4-49b2-9eed-20f91997c193",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Imports\n",
+    "\n",
+    "# General python\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
+    "\n",
+    "import numpy as np\n",
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "from scipy.interpolate import interp1d\n",
+    "from scipy.stats import linregress\n",
+    "\n",
+    "# Niceties\n",
+    "from rich import print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f2135c0b-ba31-4f05-bf37-435a99b1788f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# General eWaterCycle\n",
+    "import ewatercycle\n",
+    "import ewatercycle.models\n",
+    "import ewatercycle.forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c5166bb7-f81f-4967-a65a-d1933464ce7f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining things\n",
+    "\n",
+    "basin_size = 132572\n",
+    "q_critical = 500\n",
+    "\n",
+    "start_year = 2025\n",
+    "end_year = 2050"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "6880e7f0-2609-4c3f-82bd-c2440981fa72",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define only future scenarios\n",
+    "scenarios = [\"ssp126\", \"ssp245\", \"ssp370\"]\n",
+    "\n",
+    "# Redefine scenarios to include historical\n",
+    "scenarios_new = [\"historical\", \"ssp126\", \"ssp245\", \"ssp370\"]\n",
+    "\n",
+    "# Attach colours to scenarios to make plotting easier \n",
+    "colours = {\"historical\": \"tab:blue\", \"ssp126\": \"green\", \"ssp245\": \"orange\", \"ssp370\": \"red\"}\n",
+    "\n",
+    "# Define periods\n",
+    "periods = [[2025, 2050, 2075],\n",
+    "           [2050, 2075, 2099]]\n",
+    "\n",
+    "hist_periods = ([1989], [2014]) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "c398fe4d-66fb-430a-8f82-ad85e924f592",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create pathways\n",
+    "\n",
+    "def forcing_path_cmip(scenario, start_year, end_year):\n",
+    "    \n",
+    "    forcing_path = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / scenario / f\"CMIP6-{start_year}-{end_year}\"\n",
+    "    \n",
+    "    return forcing_path\n",
+    "\n",
+    "shape_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"Shapefiles\" / \"07DA001_basin.shp\"\n",
+    "\n",
+    "discharge_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" /  \"Workyard\" / \"07DA001_discharge_daily_withoutmissing.csv\"\n",
+    "\n",
+    "hbv_config = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"hbv_config\"\n",
+    "hbv_config.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "a7bab7da-b7e7-442c-b4b0-e5c3b0ededcb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Adjust time period\n",
+    "\n",
+    "validation_start = f\"{start_year}-01-01T00:00:00Z\"\n",
+    "validation_end = f\"{end_year}-12-31T00:00:00Z\"\n",
+    "\n",
+    "# Define time period\n",
+    "validation_start_date = pd.to_datetime(validation_start.replace(\"Z\", \"\"))\n",
+    "validation_end_date = pd.to_datetime(validation_end.replace(\"Z\", \"\"))\n",
+    "\n",
+    "# Skip 1 year for filling storages\n",
+    "evaluation_start = pd.to_datetime(f\"{validation_start_date.year + 1}-01-01\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1bd0e989-16f3-4cd9-81b7-dcfaf582cc7d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load in observed discharge data\n",
+    "\n",
+    "q_obs = pd.read_csv(discharge_file, skiprows=1)\n",
+    "q_obs = q_obs[[\"Date\", \"Value\"]].copy()\n",
+    "q_obs[\"Date\"] = pd.to_datetime(q_obs[\"Date\"])\n",
+    "q_obs = q_obs.rename(columns={\"Value\": \"discharge_m3s\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f4a7211e-cb74-4a90-8229-de7000cf2dd5",
+   "metadata": {},
+   "source": [
+    "## 2. Model setup\n",
+    "\n",
+    "For running the model, the following steps are taken:\n",
+    "\n",
+    "##### 2.1 Load parameter sets & initial storages\n",
+    "##### 2.2 Model configuration\n",
+    "##### 2.3 Model setup run"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d31e5426-3e95-4902-913c-c40da613b8aa",
+   "metadata": {},
+   "source": [
+    "### 2.1 Load parameter sets & initial storages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d776ff36-b69a-4321-9468-d4fa85350ef3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define parameter ensemble\n",
+    "\n",
+    "par_ensemble = [\n",
+    "    [6.279135, 0.4808243, 174.127749, 1.9527195, 0.3305087, 6.19919, 0.0768362, 0.004366398, 0.4076606],\n",
+    "    [7.35776, 0.432509, 192.67085, 1.66088, 0.289296, 5.323766, 0.037268, 0.004399, 1.146504],\n",
+    "    [7.9355, 0.4593, 219.6962, 1.72624, 0.26391, 5.810765, 0.04804, 0.0155065, 0.76857],\n",
+    "    [5.5464, 0.46496, 187.8548, 1.82803, 0.440628, 6.29496, 0.062766, 0.033095, 0.80392],\n",
+    "   [7.23868, 0.47495, 181.82012, 1.8232, 0.4884032, 5.546412, 0.0449439, 0.00231717, 1.25052]]\n",
+    "\n",
+    "\n",
+    "par_names = [\"Imax\",         # Maximum interception storage\n",
+    "               \"Ce\",         # Evaporation correction factor\n",
+    "               \"Sumax\",      # Maximum soil moisture storage\n",
+    "               \"Beta\",       # Soil runoff parameter\n",
+    "               \"Pmax\",       # Maximum percolation rate\n",
+    "               \"Tlag\",       # Time lag\n",
+    "               \"Kf\",         # Fast reservoir recession coefficient\n",
+    "               \"Ks\",         # Slow reservoir recession coefficient\n",
+    "               \"FM\"]          # Snowmelt factor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c60f825e-520a-4b00-83ab-16bdcfe60471",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define initial storages\n",
+    "\n",
+    "#               Si,  Su, Sf, Ss, Sp\n",
+    "s_0 = np.array([0,  100,  0,  5,  0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "70ba5ea1-8a76-463a-a14c-415673632103",
+   "metadata": {},
+   "source": [
+    "### 2.2 Model configuration"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "70664027-bb24-47cc-814d-eb8eccbc1715",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model setup create function\n",
+    "\n",
+    "def run_hbv(parameters, initial_storages, forcing):\n",
+    "\n",
+    "    # Creating model object\n",
+    "    model = ewatercycle.models.HBV(forcing=forcing)\n",
+    "\n",
+    "    # Creating config file\n",
+    "    config_file, _ = model.setup(\n",
+    "        parameters=parameters,\n",
+    "        initial_storages=initial_storages,\n",
+    "        cfg_dir=hbv_config)\n",
+    "\n",
+    "    # Initialising model\n",
+    "    model.initialize(config_file)\n",
+    "\n",
+    "    # Define & update outputs\n",
+    "    Q_m = []\n",
+    "    time = []\n",
+    "\n",
+    "    while model.time < model.end_time:\n",
+    "        model.update()\n",
+    "        Q_m.append(model.get_value(\"Q\")[0])\n",
+    "        time.append(pd.Timestamp(model.time_as_datetime))\n",
+    "\n",
+    "    model.finalize()\n",
+    "\n",
+    "    # Convert mm/day to m3/s\n",
+    "    model_output_mmday = pd.Series(\n",
+    "        data=Q_m,\n",
+    "        index=time,\n",
+    "        name=\"Modelled discharge\")\n",
+    "\n",
+    "    model_output_m3s = model_output_mmday * basin_size * 1000 / 86400\n",
+    "\n",
+    "    return model_output_m3s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fc3a24e7-53d6-4b62-aab1-ea705cefa75a",
+   "metadata": {},
+   "source": [
+    "### 2.3 Model setup run"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "1dab11de-a9f9-4e58-bc05-29926875e2d0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model running create function\n",
+    "\n",
+    "def run_hbv_ensemble(par_ensemble, initial_storages, forcing):\n",
+    "\n",
+    "    # Define amount of parameter sets\n",
+    "    N = len(par_ensemble)\n",
+    "    \n",
+    "    # Create dataframe to append data to & add column for observed data\n",
+    "    ensemble_data = pd.DataFrame()\n",
+    "\n",
+    "    for i in range(N):\n",
+    "\n",
+    "        print(f\"Running parameter set {i+1}/{N}\")\n",
+    "\n",
+    "        # Run HBV model for the parameter sets \n",
+    "        simulated = run_hbv(\n",
+    "            parameters=par_ensemble[i],\n",
+    "            initial_storages=initial_storages,\n",
+    "            forcing=forcing)\n",
+    "\n",
+    "        # Filter data by day only, not by day & time to prevent alignment issues\n",
+    "        simulated_daily = simulated\n",
+    "\n",
+    "        simulated_daily.index = pd.to_datetime(simulated_daily.index).tz_localize(None).normalize()\n",
+    "        simulated_daily.name = f\"Set {i+1}\"\n",
+    "         \n",
+    "        # Append new column for every parameter set results\n",
+    "        ensemble_data[f\"Set {i+1}\"] = simulated\n",
+    "\n",
+    "    # Add mean of all sets\n",
+    "    ensemble_data[\"Mean\"] = ensemble_data.mean(axis=1)\n",
+    "\n",
+    "    return ensemble_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ae52fc14-876c-4464-8fb0-7f88c9356df3",
+   "metadata": {},
+   "source": [
+    "## 3. Lowflow setup\n",
+    "\n",
+    "Before running the model, the way lowflows are counted must be defined. this is so these functions can be called for every model run under every parameter set, scenario type and time period. The following steps are taken:\n",
+    "\n",
+    "##### 3.1 Lowflow counter for the future\n",
+    "##### 3.2 Lowflow counter for observed data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b585bec-2c55-4d07-90a6-b7122d931730",
+   "metadata": {},
+   "source": [
+    "### 3.1 Lowflow counter for the future "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "2a55954f-3927-4a02-b641-f4ba5fc3725a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_counter_future(ensemble_data, start_date, end_date):\n",
+    "\n",
+    "    lowflow_days = []\n",
+    "\n",
+    "    years = list(range(start_date.year, end_date.year + 1))\n",
+    "\n",
+    "    for i in range(len(years)):\n",
+    "\n",
+    "        year = years[i]\n",
+    "\n",
+    "        year_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        year_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "\n",
+    "        year_data = ensemble_data[\n",
+    "            (ensemble_data.index >= year_start) &\n",
+    "            (ensemble_data.index <= year_end)]\n",
+    "\n",
+    "        modelled_lowflow_days = []\n",
+    "\n",
+    "        # Count parameter set low-flow days\n",
+    "        for j in range(len(par_ensemble)):\n",
+    "\n",
+    "            set_lowflow_days = 0\n",
+    "\n",
+    "            for k in range(len(year_data)):\n",
+    "\n",
+    "                set_q = year_data.iloc[k][f\"Set {j+1}\"]\n",
+    "\n",
+    "                if set_q < q_critical:\n",
+    "                    set_lowflow_days += 1\n",
+    "\n",
+    "            modelled_lowflow_days.append(set_lowflow_days)\n",
+    "\n",
+    "        setavg_lowflow_days = np.mean(modelled_lowflow_days)\n",
+    "\n",
+    "        lowflow_days.append({\n",
+    "            \"year\": year,\n",
+    "            \"set_1\": modelled_lowflow_days[0],\n",
+    "            \"set_2\": modelled_lowflow_days[1],\n",
+    "            \"set_3\": modelled_lowflow_days[2],\n",
+    "            \"set_4\": modelled_lowflow_days[3],\n",
+    "            \"set_5\": modelled_lowflow_days[4],\n",
+    "            \"set_avg\": np.round(setavg_lowflow_days)})\n",
+    "\n",
+    "    lowflow_days = pd.DataFrame(lowflow_days)\n",
+    "\n",
+    "    return lowflow_days"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "960d2207-e472-44be-aa22-d6bcd155aff3",
+   "metadata": {},
+   "source": [
+    "### 3.2 Lowflow counter for observed data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "61884551-cc91-4478-bb2d-73eba100630b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def observed_lowflow_days(start_year=2000, end_year=2025):\n",
+    "\n",
+    "    observed_lowflows = []\n",
+    "\n",
+    "    for year in range(start_year, end_year + 1):\n",
+    "\n",
+    "        season_start = pd.to_datetime(f\"{year}-05-18\")\n",
+    "        season_end = pd.to_datetime(f\"{year}-10-17\")\n",
+    "\n",
+    "        year_data = q_obs[\n",
+    "            (q_obs[\"Date\"] >= season_start) &\n",
+    "            (q_obs[\"Date\"] <= season_end)]\n",
+    "\n",
+    "        lowflow_days = (year_data[\"discharge_m3s\"] < q_critical).sum()\n",
+    "\n",
+    "        observed_lowflows.append({\n",
+    "            \"year\": year,\n",
+    "            \"observed_lowflow_days\": lowflow_days})\n",
+    "\n",
+    "    observed_lowflows = pd.DataFrame(observed_lowflows)\n",
+    "\n",
+    "    observed_average = round(observed_lowflows[\"observed_lowflow_days\"].mean())\n",
+    "    observed_total = observed_lowflows[\"observed_lowflow_days\"].sum()\n",
+    "\n",
+    "    print(\"Observed average low-flow days/year:\", observed_average)\n",
+    "    print(\"Observed total low-flow days:\", observed_total)\n",
+    "\n",
+    "    return observed_lowflows, observed_average"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "18c80e0a-3c39-4ec4-91b7-49a5190ee3fd",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'pd' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m observed_lowflows, observed_avg \u001b[38;5;241m=\u001b[39m \u001b[43mobserved_lowflow_days\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstart_year\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m2000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mend_year\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m2025\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "Cell \u001b[0;32mIn[1], line 7\u001b[0m, in \u001b[0;36mobserved_lowflow_days\u001b[0;34m(start_year, end_year)\u001b[0m\n\u001b[1;32m      3\u001b[0m observed_lowflows \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m year \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(start_year, end_year \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m):\n\u001b[0;32m----> 7\u001b[0m     season_start \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241m.\u001b[39mto_datetime(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00myear\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m-05-18\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      8\u001b[0m     season_end \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mto_datetime(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00myear\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m-10-17\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     10\u001b[0m     year_data \u001b[38;5;241m=\u001b[39m q_obs[\n\u001b[1;32m     11\u001b[0m         (q_obs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDate\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m season_start) \u001b[38;5;241m&\u001b[39m\n\u001b[1;32m     12\u001b[0m         (q_obs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDate\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m season_end)]\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "observed_lowflows, observed_avg = observed_lowflow_days(start_year=2000, end_year=2025)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4f8cf70f-9c28-43fe-881e-afbb8fb5cc14",
+   "metadata": {},
+   "source": [
+    "## 4. Running model\n",
+    "\n",
+    "The previous functions in 2. and 3. will be used to run the model for every possible scenario and calculate the lowflows. The following steps are taken:\n",
+    "\n",
+    "##### 4.1 Function for running one projection\n",
+    "##### 4.2 Running for every projection and store the data "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a55dc672-29f6-40bc-89ba-f384078aaf4a",
+   "metadata": {},
+   "source": [
+    "### 4.1 Function for running one projection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "33bdfa38-cac6-4eda-8f0e-143e163eea2a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_one_projection(scenario, start_year, end_year):\n",
+    "\n",
+    "    print(f\"Running {scenario}, {start_year}-{end_year}\")\n",
+    "\n",
+    "    # Find forcing path for scenario and period\n",
+    "    forcing_path = forcing_path_cmip(\n",
+    "        scenario=scenario,\n",
+    "        start_year=start_year,\n",
+    "        end_year=end_year)\n",
+    "\n",
+    "    # Generate forcing\n",
+    "    CMIP_forcing = ewatercycle.forcing.sources[\"LumpedMakkinkForcing\"].load(directory=forcing_path)\n",
+    "\n",
+    "    # Run ensemble \n",
+    "    ensemble_data = run_hbv_ensemble(\n",
+    "        par_ensemble=par_ensemble,\n",
+    "        initial_storages=s_0,\n",
+    "        forcing=CMIP_forcing)\n",
+    "\n",
+    "    # Calculate lowflows\n",
+    "    lowflow_table = lowflow_counter_future(\n",
+    "        ensemble_data=ensemble_data,\n",
+    "        start_date=pd.to_datetime(f\"{start_year}-01-01\"),\n",
+    "        end_date=pd.to_datetime(f\"{end_year}-12-31\"))\n",
+    "\n",
+    "    return ensemble_data, lowflow_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d308b04e-e38b-4c76-af6f-4483d9920bdc",
+   "metadata": {},
+   "source": [
+    "### 4.2 Running for every projection and store the data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "a0bb6899-63e2-41b2-b83e-33a89203d9e1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp126, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp126, \u001b[1;36m2025\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp126, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp126, \u001b[1;36m2050\u001b[0m-\u001b[1;36m2075\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp126, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp126, \u001b[1;36m2075\u001b[0m-\u001b[1;36m2099\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp245, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp245, \u001b[1;36m2025\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp245, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp245, \u001b[1;36m2050\u001b[0m-\u001b[1;36m2075\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp245, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp245, \u001b[1;36m2075\u001b[0m-\u001b[1;36m2099\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp370, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2025</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp370, \u001b[1;36m2025\u001b[0m-\u001b[1;36m2050\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp370, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2050</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp370, \u001b[1;36m2050\u001b[0m-\u001b[1;36m2075\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running ssp370, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2075</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2099</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running ssp370, \u001b[1;36m2075\u001b[0m-\u001b[1;36m2099\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m1\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m2\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m3\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m4\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Running parameter set <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Running parameter set \u001b[1;36m5\u001b[0m/\u001b[1;36m5\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "projection_data = {}\n",
+    "use_periods = []\n",
+    "\n",
+    "for scenario in scenarios:\n",
+    "    \n",
+    "    for i in range(len(periods[0])):\n",
+    "\n",
+    "        # Define start year\n",
+    "        start_year = periods[0][i]\n",
+    "        end_year = periods[1][i]\n",
+    "\n",
+    "        # Define key where data will be saved\n",
+    "        key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "\n",
+    "        # Run HBV\n",
+    "        ensemble_data, lowflow_table = run_one_projection(scenario=scenario, start_year=start_year, end_year=end_year)\n",
+    "\n",
+    "        # Save data in projection_data\n",
+    "        projection_data[key] = {\n",
+    "            \"ensemble\": ensemble_data,\n",
+    "            \"lowflow\": lowflow_table}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7756d873-a5e7-4206-a232-11057afeb22f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "22e82719-70f4-45e6-a7eb-27f6e506553b",
+   "metadata": {},
+   "source": [
+    "## 5. Lowflow data visualisation\n",
+    "\n",
+    "All the results have been ran and calculated in previous chapters. Here results are presented. First a table will be created showing lowflow days for 25 year periods from 2000-2100 under various climate scenarios. Second, a CDF distribution will be shown:\n",
+    "\n",
+    "##### 5.1 Lowflow table\n",
+    "##### 5.2 Lowflow plot\n",
+    "##### 5.3 CDF\n",
+    "##### 5.4 Quantiles"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "71e398fe-05c1-4e64-a561-e0012210d52c",
+   "metadata": {},
+   "source": [
+    "### 5.1 Lowflow table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "f13aa66c-90fc-4de7-b2ca-42c2da16cd04",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_lowflow_summary_table(projection_data, scenarios, periods):\n",
+    "\n",
+    "    rows = []\n",
+    "\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        # Define table rows \n",
+    "        row = {\"scenario\": scenario}\n",
+    "\n",
+    "        # Put observed data in table\n",
+    "        row[\"Observed 2000-2025\"] = round(observed_avg)\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            # Define period\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            # Take data for relevant scenario and period \n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "            period_name = f\"{start_year}-{end_year}\"\n",
+    "\n",
+    "            # Extract data from projection_key\n",
+    "            lowflow_table = projection_data[key][\"lowflow\"]\n",
+    "\n",
+    "            # Put extracted data in new table\n",
+    "            row[period_name] = round(lowflow_table[\"set_avg\"].mean())\n",
+    "\n",
+    "        rows.append(row)\n",
+    "\n",
+    "    return pd.DataFrame(rows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "6c40d31a-ab6c-44b7-94f1-e7d538328252",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>Observed 2000-2025</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <th>2050-2075</th>\n",
+       "      <th>2075-2099</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ssp126</td>\n",
+       "      <td>27</td>\n",
+       "      <td>36</td>\n",
+       "      <td>38</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ssp245</td>\n",
+       "      <td>27</td>\n",
+       "      <td>40</td>\n",
+       "      <td>38</td>\n",
+       "      <td>31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>27</td>\n",
+       "      <td>34</td>\n",
+       "      <td>45</td>\n",
+       "      <td>49</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  scenario  Observed 2000-2025  2025-2050  2050-2075  2075-2099\n",
+       "0   ssp126                  27         36         38         35\n",
+       "1   ssp245                  27         40         38         31\n",
+       "2   ssp370                  27         34         45         49"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary_table = create_lowflow_summary_table(\n",
+    "    projection_data=projection_data,\n",
+    "    scenarios=scenarios,\n",
+    "    periods=periods)\n",
+    "\n",
+    "summary_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7fa21cd1-e2d2-4aa2-a20d-792d787a18c4",
+   "metadata": {},
+   "source": [
+    "### 5.2 Lowflow plot "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "2c509444-3614-42ec-b218-bfff12a5ea31",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_annual_lowflow_days(projection_data, scenarios, periods, observed_lowflows):\n",
+    "\n",
+    "    plt.figure(figsize=(9, 5))\n",
+    "\n",
+    "    # Plot observed historical low flow days\n",
+    "    observed_data = observed_lowflows.copy()\n",
+    "\n",
+    "    plt.scatter(observed_data[\"year\"], observed_data[\"observed_lowflow_days\"], color=colours[\"historical\"], alpha=0.5, label=\"historical\")\n",
+    "\n",
+    "    # Historical trendline for 2000-2025\n",
+    "    x = observed_data[\"year\"].values\n",
+    "    y = observed_data[\"observed_lowflow_days\"].values\n",
+    "\n",
+    "    slope, intercept = np.polyfit(x, y, 1)\n",
+    "    trend = slope * x + intercept\n",
+    "\n",
+    "    plt.plot(x, trend, linestyle=\"--\", color=colours[\"historical\"])\n",
+    "\n",
+    "    # Plot future scenarios\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_years = []\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "\n",
+    "            lowflow_table = projection_data[key][\"lowflow\"]\n",
+    "\n",
+    "            years = lowflow_table[\"year\"].values\n",
+    "            lowflows = lowflow_table[\"set_avg\"].values\n",
+    "\n",
+    "            all_years.extend(years)\n",
+    "            all_lowflows.extend(lowflows)\n",
+    "\n",
+    "        scenario_data = pd.DataFrame({\n",
+    "            \"year\": all_years,\n",
+    "            \"set_avg\": all_lowflows})\n",
+    "\n",
+    "        scenario_data = scenario_data.sort_values(\"year\")\n",
+    "\n",
+    "\n",
+    "        # Plot yearly low flow days\n",
+    "        plt.scatter(scenario_data[\"year\"], scenario_data[\"set_avg\"], color=colours[scenario], alpha=0.30, label=scenario)\n",
+    "\n",
+    "        # Plot trendline for 2025-2099\n",
+    "        x = scenario_data[\"year\"].values\n",
+    "        y = scenario_data[\"set_avg\"].values\n",
+    "\n",
+    "        slope, intercept = np.polyfit(x, y, 1)\n",
+    "        trend = slope * x + intercept\n",
+    "\n",
+    "        plt.plot(x, trend, linestyle=\"--\", color=colours[scenario])\n",
+    "\n",
+    "    plt.xlabel(\"Year\")\n",
+    "    plt.ylabel(\"Annual low flow days\")\n",
+    "    plt.title(\"Annual low flow days in LAR basin by climate scenario\")\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "61d5ad70-380e-4e98-9f78-6c366cfe45a6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_annual_lowflow_days(\n",
+    "    projection_data=projection_data,\n",
+    "    scenarios=scenarios,\n",
+    "    periods=periods,\n",
+    "    observed_lowflows=observed_lowflows)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "11c17a6b-3c13-442b-a8ed-2d2427ee4699",
+   "metadata": {},
+   "source": [
+    "### Slope significance"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "7216de94-1ea2-4993-aa46-3867453ce80d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate p values to determine statistical significance\n",
+    "\n",
+    "def slope_significance(projection_data, observed_lowflows):\n",
+    "    results = []\n",
+    "\n",
+    "    # Historical observed period\n",
+    "    x = observed_lowflows[\"year\"].values\n",
+    "    y = observed_lowflows[\"observed_lowflow_days\"].values\n",
+    "\n",
+    "    reg = linregress(x, y)\n",
+    "\n",
+    "    results.append({\n",
+    "        \"scenario\": \"historical\",\n",
+    "        \"p_value\": reg.pvalue})\n",
+    "\n",
+    "    # Future scenarios\n",
+    "    for scenario in scenarios:\n",
+    "        all_years = []\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "            lowflow_table = projection_data[key][\"lowflow\"]\n",
+    "\n",
+    "            all_years.extend(lowflow_table[\"year\"].values)\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        reg = linregress(all_years, all_lowflows)\n",
+    "\n",
+    "        results.append({\n",
+    "            \"scenario\": scenario,\n",
+    "            \"p_value\": reg.pvalue})\n",
+    "\n",
+    "    return pd.DataFrame(results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "7a196937-089c-40a9-818d-2444b60f1c33",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>p_value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>0.349174</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ssp126</td>\n",
+       "      <td>0.483318</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ssp245</td>\n",
+       "      <td>0.188232</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>0.053621</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     scenario   p_value\n",
+       "0  historical  0.349174\n",
+       "1      ssp126  0.483318\n",
+       "2      ssp245  0.188232\n",
+       "3      ssp370  0.053621"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "slope_results = slope_significance(projection_data=projection_data, observed_lowflows=observed_lowflows)\n",
+    "\n",
+    "slope_results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "15b68fb9-c134-40ec-b176-bd84f853b847",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "110cc380-2552-4be7-9846-5cc8b21d1b9d",
+   "metadata": {},
+   "source": [
+    "### 5.3 CDF "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "88c401d0-39ee-48d8-b048-c0f3d09f3efa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_cdf(projection_data, scenarios, periods):\n",
+    "\n",
+    "    plt.figure(figsize=(8, 5))\n",
+    "\n",
+    "    # Observed CDF\n",
+    "    observed_values = np.sort(observed_lowflows[\"observed_lowflow_days\"].values)\n",
+    "    observed_cdf = np.arange(1, len(observed_values) + 1) / len(observed_values)\n",
+    "\n",
+    "    # plt.plot(observed_values,observed_cdf,marker=\"o\",label=\"Observed 2000-2025\")\n",
+    "    plt.plot(observed_cdf, observed_values, marker=\"o\", label=\"Observed 2000-2025\", color=colours[\"historical\"])\n",
+    "\n",
+    "    # Scenario CDFs\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "\n",
+    "            lowflow_table = projection_data[key][\"lowflow\"]\n",
+    "\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        values = np.sort(all_lowflows)\n",
+    "        cdf = np.arange(1, len(values) + 1) / len(values)\n",
+    "\n",
+    "        plt.plot(cdf,values,marker=\"o\",label=scenario, color=colours[scenario])\n",
+    "\n",
+    "    plt.ylabel(\"Annual low flow days\")\n",
+    "    plt.xlabel(\"Cumulative probability\")\n",
+    "    plt.title(\"CDF of annual low flow days\")\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "4092c20d-19a6-4245-bfc9-a83ae151ba62",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_cdf(\n",
+    "    projection_data=projection_data,\n",
+    "    scenarios=scenarios,\n",
+    "    periods=periods)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8aee0214-a4cd-42fd-99fa-d892c7b859b8",
+   "metadata": {},
+   "source": [
+    "### 5.4 Quantiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "ad7d2cbb-351d-4481-bb8b-4fde80893fe7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lowflow_quantile_table(lowflow_results, scenarios, periods):\n",
+    "\n",
+    "    rows = []\n",
+    "\n",
+    "    for scenario in scenarios:\n",
+    "\n",
+    "        all_lowflows = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "            \n",
+    "            lowflow_table = lowflow_results[key][\"lowflow\"]\n",
+    "\n",
+    "            all_lowflows.extend(lowflow_table[\"set_avg\"].values)\n",
+    "\n",
+    "        values = pd.Series(all_lowflows)\n",
+    "\n",
+    "        # Append table and define quantiles \n",
+    "        rows.append({\n",
+    "            \"scenario\": scenario,\n",
+    "            \"mean\": round(values.mean(), 1),\n",
+    "            \"median\": values.median(),\n",
+    "            \"p50\": values.quantile(0.5),\n",
+    "            \"p75\": values.quantile(0.75),\n",
+    "            \"p90\": values.quantile(0.90),\n",
+    "            \"max\": values.max()})\n",
+    "\n",
+    "    return pd.DataFrame(rows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "09a29265-5d22-4916-874e-270a2107fd53",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>median</th>\n",
+       "      <th>p50</th>\n",
+       "      <th>p75</th>\n",
+       "      <th>p90</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ssp126</td>\n",
+       "      <td>36.1</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>52.0</td>\n",
+       "      <td>74.2</td>\n",
+       "      <td>143.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ssp245</td>\n",
+       "      <td>36.6</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>84.4</td>\n",
+       "      <td>141.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>42.8</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>93.2</td>\n",
+       "      <td>130.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  scenario  mean  median   p50   p75   p90    max\n",
+       "0   ssp126  36.1    31.0  31.0  52.0  74.2  143.0\n",
+       "1   ssp245  36.6    23.0  23.0  56.0  84.4  141.0\n",
+       "2   ssp370  42.8    43.0  43.0  63.0  93.2  130.0"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lowflow_quantile_table(projection_data, scenarios, periods)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0b8c0de8-91bf-4b76-9c46-4eb15bbe4d02",
+   "metadata": {},
+   "source": [
+    "# 6. Forcing data comparison & visualisation\n",
+    "\n",
+    "Here the forcing data will be analysed. First the forcing files will be loaded in and merged for each scenario. Then, units will be converted. Finally, yearly and period averages will be calculated and saved in lists. This will be used in 6.2 and 6.3 for visualisation.\n",
+    "\n",
+    "##### 6.1 Loading and preparing forcing data\n",
+    "##### 6.2 Period forcing avg table\n",
+    "##### 6.3 Yearly forcing avg graph"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9498e454-25ab-4b53-a01a-ccc11284d3e9",
+   "metadata": {},
+   "source": [
+    "### 6.3 Loading and preparing forcing data\n",
+    "\n",
+    "All forcing data will be stored in forcing_data[scenario][var_name]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "e09f5155-fc3a-4156-92e0-664a55cc8539",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "var_names = {\"evspsblpot\", \"pr\", \"rsds\", \"tas\"}\n",
+    "\n",
+    "forcing_data = {}\n",
+    "annual_avg = []\n",
+    "period_avg = []\n",
+    "\n",
+    "for scenario in scenarios:\n",
+    "\n",
+    "    forcing_data[scenario] = {}\n",
+    "\n",
+    "    for var_name in var_names:\n",
+    "\n",
+    "        merged_data_list = []\n",
+    "\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            # Define file path\n",
+    "            forcing_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / scenario / f\"CMIP6-{start_year}-{end_year}\" / f\"combined_CMIP6_{start_year}_{end_year}_{var_name}.nc\"\n",
+    "            \n",
+    "            # Load file as dataset\n",
+    "            ds = xr.open_dataset(forcing_file)\n",
+    "\n",
+    "            # Load file as array\n",
+    "            da = ds[var_name]\n",
+    "\n",
+    "            # Convert to series \n",
+    "            series = pd.Series(data=da.values.squeeze(),index=pd.to_datetime(da[\"time\"].values).normalize(),name=var_name)\n",
+    "\n",
+    "            # Convert pr and evap from km^2/s to mm^2/day\n",
+    "            if var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "                series = series * 86400\n",
+    "                annual = series.groupby(series.index.year).sum()\n",
+    "\n",
+    "            # Convert temp from Kelvin to Celcius\n",
+    "            elif var_name == \"tas\":\n",
+    "                series = series - 273.15\n",
+    "                annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "            elif var_name == \"rsds\":\n",
+    "                annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "            # Save for merged time series\n",
+    "            merged_data_list.append(series)\n",
+    "\n",
+    "            # Save annual values\n",
+    "            for year, annual_value in annual.items():\n",
+    "\n",
+    "                annual_avg.append({\n",
+    "                    \"scenario\": scenario,\n",
+    "                    \"period\": f\"{start_year}-{end_year}\",\n",
+    "                    \"year\": year,\n",
+    "                    \"variable\": var_name,\n",
+    "                    \"value\": annual_value})\n",
+    "\n",
+    "            # Save 25 year average\n",
+    "            period_avg.append({\n",
+    "                \"scenario\": scenario,\n",
+    "                \"period\": f\"{start_year}-{end_year}\",\n",
+    "                \"variable\": var_name,\n",
+    "                \"value\": annual.mean()})\n",
+    "\n",
+    "        # Merge periods into one 2025–2099 series\n",
+    "        merged_data = pd.concat(merged_data_list)\n",
+    "        merged_data = merged_data[~merged_data.index.duplicated(keep=\"first\")]\n",
+    "        merged_data = merged_data.sort_index()\n",
+    "\n",
+    "        forcing_data[scenario][var_name] = merged_data\n",
+    "\n",
+    "# Create summary table for annual avg values\n",
+    "annual_table = pd.DataFrame(annual_avg)\n",
+    "\n",
+    "# Create summary table for period avg values\n",
+    "period_table = pd.DataFrame(period_avg).pivot_table(index=[\"scenario\", \"period\"],columns=\"variable\",values=\"value\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "d1a5a1ba-05ce-400f-8ab9-a60bec0bfdc5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Prepare historical data\n",
+    "\n",
+    "def load_hist(start_year, end_year):\n",
+    "\n",
+    "    forcing_data_hist = {}\n",
+    "    scenario = \"historical\"\n",
+    "    forcing_data_hist[scenario] = {}\n",
+    "    annual_avg = []\n",
+    "\n",
+    "    for var_name in var_names:\n",
+    "\n",
+    "        merged_data_list = []\n",
+    "    \n",
+    "        forcing_file = Path.home() / \"BEP-maxime\" / \"book\" / \"thesis_projects\" / \"BSc\" / \"2026_Q4_MaximedeBekker_CEG\" / \"Workyard\" / \"forcings\" / \"CMIP6\" / scenario / f\"CMIP6-{start_year}-{end_year}\" / f\"combined_CMIP6_{start_year}_{end_year}_{var_name}.nc\"\n",
+    "\n",
+    "        # Load file as dataset\n",
+    "        ds = xr.open_dataset(forcing_file)\n",
+    "\n",
+    "        # Load file as array\n",
+    "        da = ds[var_name]\n",
+    "\n",
+    "        # Convert to series \n",
+    "        series = pd.Series(data=da.values.squeeze(),index=pd.to_datetime(da[\"time\"].values).normalize(),name=var_name)\n",
+    "\n",
+    "        # Convert pr and evap from km^2/s to mm^2/day\n",
+    "        if var_name in [\"pr\", \"evspsblpot\"]:\n",
+    "            series = series * 86400\n",
+    "            annual = series.groupby(series.index.year).sum()\n",
+    "\n",
+    "        # Convert temp from Kelvin to Celcius\n",
+    "        elif var_name == \"tas\":\n",
+    "            series = series - 273.15\n",
+    "            annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "        elif var_name == \"rsds\":\n",
+    "            annual = series.groupby(series.index.year).mean()\n",
+    "\n",
+    "        # Save for merged time series\n",
+    "        merged_data_list.append(series)\n",
+    "\n",
+    "        # Save annual values\n",
+    "        for year, annual_value in annual.items():\n",
+    "\n",
+    "            annual_avg.append({\n",
+    "                \"scenario\": scenario,\n",
+    "                \"period\": f\"{start_year}-{end_year}\",\n",
+    "                \"year\": year,\n",
+    "                \"variable\": var_name,\n",
+    "                \"value\": annual_value})\n",
+    "\n",
+    "        # Merge period into one series\n",
+    "        merged_data = pd.concat(merged_data_list)\n",
+    "        merged_data = merged_data[~merged_data.index.duplicated(keep=\"first\")]\n",
+    "        merged_data = merged_data.sort_index()\n",
+    "\n",
+    "        forcing_data_hist[scenario][var_name] = merged_data\n",
+    "            \n",
+    "    annual_hist_table = pd.DataFrame(annual_avg)\n",
+    "    \n",
+    "    return annual_hist_table, forcing_data_hist"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "f076a095-0bbd-4053-887e-df115ac18a1b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>period</th>\n",
+       "      <th>year</th>\n",
+       "      <th>variable</th>\n",
+       "      <th>value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1989</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>2.562430</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1990</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>1.319359</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1991</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>1.052132</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>0.776736</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989-2014</td>\n",
+       "      <td>1993</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>1.499663</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     scenario     period  year variable     value\n",
+       "0  historical  1989-2014  1989      tas  2.562430\n",
+       "1  historical  1989-2014  1990      tas  1.319359\n",
+       "2  historical  1989-2014  1991      tas  1.052132\n",
+       "3  historical  1989-2014  1992      tas  0.776736\n",
+       "4  historical  1989-2014  1993      tas  1.499663"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "annual_hist_table,forcing_data_hist = load_hist(start_year=1989,end_year=2014)\n",
+    "\n",
+    "annual_hist_table.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "7e9707fe-3fec-4f72-b9bb-bff4fe01ed6e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Merge forcing data (useful for freeze up calculation)\n",
+    "\n",
+    "forcing_data_all = forcing_data.copy()\n",
+    "\n",
+    "forcing_data_all[\"historical\"] = forcing_data_hist[\"historical\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c185c872-7215-4870-9c9c-3be7b202d139",
+   "metadata": {},
+   "source": [
+    "### 6.2 Period forcing avg table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "3f47b648-0f62-4c96-a290-4da99c2edb07",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_period_forcing_table(annual_table):\n",
+    "\n",
+    "    period_forcing_table = (annual_table.groupby([\"scenario\", \"period\", \"variable\"])[\"value\"].mean().reset_index())\n",
+    "\n",
+    "    period_forcing_table = period_forcing_table.pivot_table(index=[\"scenario\", \"period\"], columns=\"variable\", values=\"value\")\n",
+    "\n",
+    "    return period_forcing_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "4bdf8aaa-e8a3-4f5d-b062-91a50ee41317",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>evspsblpot</th>\n",
+       "      <th>pr</th>\n",
+       "      <th>rsds</th>\n",
+       "      <th>tas</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>scenario</th>\n",
+       "      <th>period</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">ssp126</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <td>621.1</td>\n",
+       "      <td>633.9</td>\n",
+       "      <td>138.5</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2050-2075</th>\n",
+       "      <td>625.8</td>\n",
+       "      <td>630.1</td>\n",
+       "      <td>138.7</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2075-2099</th>\n",
+       "      <td>621.5</td>\n",
+       "      <td>645.3</td>\n",
+       "      <td>138.2</td>\n",
+       "      <td>2.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">ssp245</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <td>628.0</td>\n",
+       "      <td>623.0</td>\n",
+       "      <td>139.5</td>\n",
+       "      <td>2.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2050-2075</th>\n",
+       "      <td>632.7</td>\n",
+       "      <td>637.3</td>\n",
+       "      <td>138.3</td>\n",
+       "      <td>3.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2075-2099</th>\n",
+       "      <td>635.6</td>\n",
+       "      <td>659.8</td>\n",
+       "      <td>137.8</td>\n",
+       "      <td>3.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"3\" valign=\"top\">ssp370</th>\n",
+       "      <th>2025-2050</th>\n",
+       "      <td>623.4</td>\n",
+       "      <td>640.5</td>\n",
+       "      <td>138.5</td>\n",
+       "      <td>2.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2050-2075</th>\n",
+       "      <td>636.3</td>\n",
+       "      <td>650.3</td>\n",
+       "      <td>136.7</td>\n",
+       "      <td>4.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2075-2099</th>\n",
+       "      <td>656.9</td>\n",
+       "      <td>645.7</td>\n",
+       "      <td>136.6</td>\n",
+       "      <td>5.4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "variable            evspsblpot     pr   rsds  tas\n",
+       "scenario period                                  \n",
+       "ssp126   2025-2050       621.1  633.9  138.5  2.5\n",
+       "         2050-2075       625.8  630.1  138.7  3.0\n",
+       "         2075-2099       621.5  645.3  138.2  2.7\n",
+       "ssp245   2025-2050       628.0  623.0  139.5  2.7\n",
+       "         2050-2075       632.7  637.3  138.3  3.6\n",
+       "         2075-2099       635.6  659.8  137.8  3.6\n",
+       "ssp370   2025-2050       623.4  640.5  138.5  2.7\n",
+       "         2050-2075       636.3  650.3  136.7  4.4\n",
+       "         2075-2099       656.9  645.7  136.6  5.4"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "period_forcing_table = round(create_period_forcing_table(annual_table), 1)\n",
+    "\n",
+    "period_forcing_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a458f6d2-2210-4a9a-bce0-7a41b1da5711",
+   "metadata": {},
+   "source": [
+    "### 6.3 Yearly forcing avg graph"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "f0f860cc-2ac2-4d44-b941-3a255012355b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_annual_forcing_variable(annual_forcing_table, var_name):\n",
+    "\n",
+    "    # Combine historical and scenarios\n",
+    "    annual_forcing_table_all = pd.concat([annual_hist_table, annual_forcing_table],ignore_index=True)\n",
+    "    data = annual_forcing_table_all[annual_forcing_table_all[\"variable\"] == var_name]\n",
+    "    \n",
+    "    plt.figure(figsize=(9, 5))\n",
+    "    \n",
+    "    # Loop through scenarios\n",
+    "    for scenario in scenarios_new:\n",
+    "\n",
+    "        # Extract one scenario and colour \n",
+    "        scenario_data = data[data[\"scenario\"] == scenario]\n",
+    "        colour = colours[scenario]\n",
+    "\n",
+    "        # Plot historical \n",
+    "        if scenario == \"historical\":\n",
+    "            \n",
+    "            # Plot yearly average \n",
+    "            plt.plot(scenario_data[\"year\"], scenario_data[\"value\"], color=colour, linewidth=0.3, label=scenario)\n",
+    "\n",
+    "            x = scenario_data[\"year\"].values\n",
+    "            y = scenario_data[\"value\"].values\n",
+    "\n",
+    "            # Polyfit method for making trendline function\n",
+    "            slope, intercept = np.polyfit(x, y, 1)\n",
+    "            trend = slope * x + intercept\n",
+    "\n",
+    "            # Plot trendline\n",
+    "            plt.plot(x,trend,linestyle=\"--\",color=colour)\n",
+    "\n",
+    "        # Plot other scenarios\n",
+    "        else:\n",
+    "\n",
+    "            # Plot yearly average\n",
+    "            plt.plot(scenario_data[\"year\"], scenario_data[\"value\"], alpha=0.3, color=colour, label=scenario)\n",
+    "\n",
+    "        # Look at each 25 year period\n",
+    "        for i in range(len(periods[0])):\n",
+    "\n",
+    "            # Define period range\n",
+    "            start_year = periods[0][i]\n",
+    "            end_year = periods[1][i]\n",
+    "\n",
+    "            # Adjust data to fit period range\n",
+    "            period_data = scenario_data[\n",
+    "            (scenario_data[\"year\"] >= start_year) & \n",
+    "            (scenario_data[\"year\"] <= end_year)]\n",
+    "\n",
+    "            # Plot trend line over each 25 year period\n",
+    "            if len(period_data) > 1:\n",
+    "\n",
+    "                x = period_data[\"year\"].values\n",
+    "                y = period_data[\"value\"].values\n",
+    "\n",
+    "                # Polyfit method for making trendline function\n",
+    "                slope, intercept = np.polyfit(x, y, 1)\n",
+    "                trend = slope * x + intercept\n",
+    "\n",
+    "                # Plot trendline\n",
+    "                plt.plot(x,trend,linestyle=\"--\",color=colour)\n",
+    "\n",
+    "    # Define titles and labels based on var_name\n",
+    "    if var_name == \"pr\":\n",
+    "        ylabel = \"Annual precipitation (mm/year)\"\n",
+    "        title = \"Annual precipitation in LAR basin by climate scenario\"\n",
+    "\n",
+    "    elif var_name == \"evspsblpot\":\n",
+    "        ylabel = \"Annual potential evaporation (mm/year)\"\n",
+    "        title = \"Annual potential evaporation in LAR basin by climate scenario\"\n",
+    "\n",
+    "    elif var_name == \"tas\":\n",
+    "        ylabel = \"Annual mean temperature increase (°C)\"\n",
+    "        title = \"Annual mean temperature in LAR basin by climate scenario\"\n",
+    "\n",
+    "    elif var_name == \"rsds\":\n",
+    "        ylabel = \"Annual mean shortwave radiation (W/m²)\"\n",
+    "        title = \"Annual mean shortwave radiation in LAR basin by climate scenario\"\n",
+    "\n",
+    "    plt.xlabel(\"Year\")\n",
+    "    plt.ylabel(ylabel)\n",
+    "    plt.title(title)\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "723362df-4c18-43a7-ae31-b584ff01198f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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fKCsr4wc/+EFGAZGNfK7RfO+PP/7xj/ziF7/gX//6F8ceeywVFRWccsopeY1nR49vPtex1+vl4osvZsGCBTQ2NrJt2zaefvppLrzwwnYTgbdt28Yee+yR11jyoaKiIu01j8eT9rrH4wFIerZde+213HTTTZxyyim8+OKLrFixglWrVrHffvvldbzsmP7rr78+7fly6aWXAuQMm/zxj3/MP/7xD9avX89pp51G//79Oeyww1i8eHF8mXyOV77POJt8rpFCj00+VaHseyHb88cwjA6FkAl2H1zdPQCBoLv5xz/+gWmaPPPMMxlroT/yyCPccsstSZ6BYmKLBmfyMaR/2TU1NfHSSy9x880388tf/jL+eiQSob6+fofGUFNTk/G1vfbaK+m1THXb+/bti9/vz5ps2bdvX8CqbqLrOjU1NR0qe5htjB6PJ2lWPl+efPJJ3G43L730UpJw+9e//lXwumz69OmDLMtUV1envWfHWtvHY1elI/dLv379OPjggwE44ogjGDt2LJMmTeKaa65JS8DMRrbzbxtghdwfJSUlzJ07l7lz57J169a41+Ckk07iq6++yms8HSXf6/iSSy7htttu4x//+AfhcBhN0/jZz37W7vr79evHpk2bijrmjvL444/zk5/8hFtvvTXp9e3bt9O7d+92P2/fK7Nnz2bmzJkZlxkzZkzOdZx33nmcd955tLW18fbbb3PzzTczY8YMvv7663jCe3vHK99nXCEUemzy6Zlh3wvZnj+yLNOnT5+CxyrYfRCeAsFuja7rPPLII4wcOZIlS5ak/Vx33XVUV1fHQ186A7uSzSeffJL0urMiD1hfCqZpps0U/v3vf+9w+IzNE088kfT/smXLWL9+fV5NxGbMmMG3335LZWUlBx98cNqPvX/HH388YFUD6QjPPfdc0ixkS0sLL774IkcffXROwZZtFleSJFwuV9JnQ6EQjz32WN7rSKWkpITDDjuM5557Lml5wzB4/PHH2WOPPQpKrt3ZKNb9cvTRR/OTn/yEl19+Oe+qKAsXLkxK6Fy/fj3Lli2LX6MdvT8GDBjArFmzOPvss1m9enWnh1fkex0PHDiQM844g/vvv58HHniAk046KSlsKRvHH388S5YsyRlW01VIkpR2Pl5++WU2b96c9Fo279iYMWMYNWoUH3/8ccZny8EHH5wUppOLkpISjj/+eG688Uai0Siff/45kN/xyvcZVwj5HptCGDNmDIMHD2bBggVJ90pbWxvPPvtsvCKRQJAN4SkQ7Na8+uqrbNmyhdtvvz2jATx+/Hjuu+8+HnzwQWbMmNEpY6iqqmLKlCnMmzePPn36MGzYMN544w2ee+65pOXKy8s55phjuOOOO+jbty/Dhw/nrbfe4sEHH8xr1i0X77//PhdeeCFnnHEGGzdu5MYbb2Tw4MFxF30urr76ap599lmOOeYYrrnmGvbdd18Mw2DDhg0sWrSI6667jsMOO4yjjz6aH//4x9xyyy1s3bqVGTNm4PV6+fDDDwkEAlxxxRU5t6MoClOnTuXaa6/FMAxuv/12mpubmTt3bs7PTZgwgeeee44///nPHHTQQciyzMEHH8yJJ57I73//e8455xx++tOfUldXx5133pkxPGPChAk8+eSTPPXUU+y55574fD4mTJiQcXvz5s1j6tSpHHvssVx//fV4PB7uv/9+PvvsMxYuXFj0LsTF5ttvv83oARg3bhzfffdd0e6X3/72tzz11FPcdNNNvP766+2Oq7a2llNPPZWLLrqIpqYmbr75Znw+H7NnzwYKuz8OO+wwZsyYwb777kufPn348ssveeyxx7rEaCrkOr7qqqs47LDDAOIVetrjN7/5Da+++irHHHMMv/rVr5gwYQKNjY289tprXHvttey9995F3Z9czJgxg4cffpi9996bfffdlw8++IA77rgjLVxn5MiR+P1+nnjiCcaOHUtpaSmDBg1i0KBB/OUvf+H4449n+vTpzJo1i8GDB1NfX8+XX37J//73v5wVry666CL8fj9HHnkkAwcOpKamhnnz5tGrV694Bad8jle+z7jOODaFIMsy8+fP54c//CEzZszg4osvJhKJcMcdd9DY2Mhtt93W4XULdg+EKBDs1jz44IN4PB7OO++8jO/37duXU089lWeeeaagmuqF8thjj3HFFVfwi1/8Al3XOemkk1i4cGE85MJmwYIFXHXVVdxwww1omsaRRx7J4sWLd7ij7oMPPshjjz3GD37wAyKRCMceeyx/+MMfMsYTp1JSUsI777zDbbfdxl//+lfWrl2L3+9n6NChTJkyJWkW7eGHH473Anj44Yfx+/2MGzcurW54Ji6//HLC4TBXXnkltbW17LPPPrz88ssceeSROT931VVX8fnnn/OrX/2KpqYmTNPENE2+973v8Y9//IPbb7+dk046icGDB3PRRRfRv39/LrjggqR1zJ07l+rqai666CJaWloYNmxY1jKqkyZN4s033+Tmm29m1qxZGIbBfvvtx7///e9OE5bF5LXXXkurNw9w88038/HHHxd0vwwYMCDrdoYMGcIVV1zBHXfcwdtvv80xxxyTc1y33norq1at4rzzzqO5uZlDDz2UJ598kpEjR8aXyff++N73vse///1v7r77boLBIIMHD+YnP/lJPJ+kMynkOj700EPjPReOO+64vNY/ePBgVq5cyc0338xtt91GXV0d/fr146ijjsrrfi4mf/jDH3C73cybN4/W1lYOPPBAnnvuOX79618nLRcIBPjHP/7B3LlzmTZtGqqqcvPNNzNnzhyOPfZYVq5cye9+9zuuvvpqGhoaqKysZNy4cZx55pk5t3/00Ufz8MMP8/TTT9PQ0EDfvn056qijePTRR+MNB/M5XoU844p9bArlnHPOoaSkhHnz5nHWWWehKAqHH344S5YsYeLEiTu0bkHPRzKdPiaBQLBb8fDDD3PeeeexatWqNAGys7Bu3TpGjBjBHXfcwfXXX9/dwxEIuoxPPvmE/fbbjz/96U95ee0EAoFgRxCeAoFAIBAIdiK+/fZb1q9fz69+9SsGDhzIrFmzuntIAoFgN0AkGgsEAoFAsBPx29/+lqlTp9La2so///lPkRwqEAi6BBE+JBAIBAKBQCAQ7OYIT4FAIBAIBAKBQLCbI0SBQCAQCAQCgUCwm9OtoqClpYWrr76aYcOG4ff7mThxIqtWrYq/b5omc+bMYdCgQfj9fiZPnhxvOGITiUS44oor6Nu3LyUlJZx88sk7TTdHgUAgEAgEAoFgV6BbcwrOOussPvvsM/785z8zaNAgHn/8ce6++26++OILBg8ezO23387vfvc7Hn74YUaPHs0tt9zC22+/zerVq+NdDC+55BJefPFFHn74YSorK7nuuuuor6/ngw8+yNnl1IlhGGzZsoWysrKdvrGQQCAQCAQCgUCQD6Zp0tLSwqBBg5DldnwBZjcRDAZNRVHMl156Ken1/fbbz7zxxhtNwzDMqqoq87bbbou/Fw6HzV69epkPPPCAaZqm2djYaLrdbvPJJ5+ML7N582ZTlmXztddey3ssGzduNAHxI37Ej/gRP+JH/Igf8SN+etzPxo0b27WHu61PgaZp6LqOz+dLet3v9/Puu++ydu1aampqmDZtWvw9r9fLpEmTWLZsGRdffDEffPABqqomLTNo0CDGjx/PsmXLmD59esZtRyIRIpFI/H8z5ixZu3Zt3AMh6BpUVWXJkiUce+yxuN3u7h6OYAcQ57JnIc5nz0Gcy56DOJc9h646ly0tLYwYMSIv+7bbREFZWRlHHHEEv/3tbxk7diwDBgxg4cKFrFixglGjRlFTUwPAgAEDkj43YMAA1q9fD0BNTQ0ej4c+ffqkLWN/PhPz5s1j7ty5aa8vX75c1IPuBgKBACtWrOjuYQiKgDiXPQtxPnsO4lz2HMS57Dl0xbkMBoMAeYXHd2tH48cee4zzzz+fwYMHoygKBx54IOeccw7/+9//4suk7oRpmu3uWHvLzJ49m2uvvTb+f3NzM0OGDGHatGmUl5d3cG8EHUFVVRYvXszUqVPFrMcujjiXPQtxPnsO4lz2HMS57Dl01blsbm7Oe9luFQUjR47krbfeoq2tjebmZgYOHMhZZ53FiBEjqKqqAixvwMCBA+Ofqa2tjXsPqqqqiEajNDQ0JHkLamtrmThxYtbter1evF5v2utut1vcZN2EOPY9B3EuexbifPYcxLnsOYhz2XPo7HNZyLp3ij4FJSUlDBw4kIaGBv7zn//w/e9/Py4MFi9eHF8uGo3y1ltvxQ3+gw46CLfbnbRMdXU1n332WU5RIBAIBAKBQCAQCBJ0q6fgP//5D6ZpMmbMGNasWcPPf/5zxowZw3nnnYckSVx99dXceuutjBo1ilGjRnHrrbcSCAQ455xzAOjVqxcXXHAB1113HZWVlVRUVHD99dczYcIEpkyZUtSxmqYZT44WFA9VVXG5XITD4U47tm63O+/ytAKBQCAQCAS7I90qCpqampg9ezabNm2ioqKC0047jd/97ndxV8cNN9xAKBTi0ksvpaGhgcMOO4xFixYlZVDffffduFwuzjzzTEKhEMcddxwPP/xwUY3AaDRKdXV1PFlDUDxM06SqqoqNGzd2Wo8ISZLYY489KC0t7ZT1CwQCgUAgEOzqdKsoOPPMMznzzDOzvi9JEnPmzGHOnDlZl/H5fNx7773ce++9nTBCq7HZ2rVrURSFQYMG4fF4RIOzImIYBq2trZSWlrbfVKMDmKbJtm3b2LRpE6NGjRIeA4FAIBAIBIIMdKso2BWIRqMYhsGQIUNEudJOwDAMotEoPp+vU0QBQL9+/Vi3bh2qqgpRIBAIBAKBQJCBnSLReFegswxWQecjPDsCgUAgEAgEuRGWrkAgEAgEAoFAsJsjRIFAIBAIBAKBQLCbI0RBD2by5MlcffXVWd+XJIl//etfXTYem6VLlyJJEo2NjUVZ37p165AkiY8++qgo6xMIBAKBQCDY3RCiYDemurqa448/Pq9liykgJk6cSHV1Nb169SrK+gQCgUAgEAgEO4aoPrQbU1VV1eXbVFUVj8cT37Zpml0+BoFAIBAIBAJBMsJT0MMxDIMbbriBiooKqqqqkno+OGf/o9Eol19+OQMHDsTn8zF8+HDmzZsHwPDhwwE49dRTkSQp/j/An//8Z0aOHInH42HMmDE89thjSduXJIkHHniA73//+5SUlHDLLbdkDB/673//y6RJkwgEAvTp04fp06fT0NAAwGuvvcZRRx1F7969qaysZMaMGXz77bdFP1YCgUAgEAi6GdOAuvehdV13j2S3Q3gKOkAwqvHN1tYu3eaoAaUEPIWfrkceeYRrr72WFStWsHz5cmbNmsWRRx7J1KlTk5b74x//yL///W+efvpphg4dysaNG9m4cSMAq1aton///jz00EP8v//3/+K1/p9//nmuuuoq7rnnHqZMmcJLL73Eeeedxx577MGxxx4bX/fNN9/MvHnzuPvuu1EUhbVr1yZt+9NPP2Xq1Kmcf/75/PGPf8TlcrFkyRJ0XQegra2Na6+9lgkTJtDW1sb//d//ceqpp/LRRx+JUrECgUAgEPQkoo0Qqga1CUqHd/dodiuEKOjh7Lvvvtx8880AjBo1ivvuu4833ngjTRRs2LCBUaNGcdRRRyFJEsOGDYu/169fPwB69+6dFHJ05513MmvWLC699FIArr32Wt577z3uvPPOJFFwzjnncP7558f/TxUFf/jDHzj44IO5//7746/ts88+8b9PO+20pOUffPBB+vfvzxdffMH48eMLOyACgUAgEAh2Xgw19lvr3nHshghR0AECHhf7Dend3cPIi3333Tfp/4EDB1JbW5u23KxZs5g6dSpjxozh//2//8eMGTOYNm1aznV/+eWX/PSnP0167cgjj+QPf/hD0msHH3xwzvV89tlnnHnmmVnf//bbb7npppt477332L59O4ZhAJaQEaJAIBAIBIIehBkTA6bevePYDRGxFz0ct9ud9L8kSXGj2smBBx7I2rVr+e1vf0soFOLMM8/k9NNPb3f9qd2CTdNMe62kpCTnOnw+X873TzrpJOrq6vjb3/7GihUrWLFiBWDlQQgEAoFAIOhBCFHQbQhRIIhTXl7OWWedxd/+9jeeeuopnn32Werr6wFLXNgx/jZjx47l3XffTXpt2bJljB07tqDt7rPPPrz55psZ36urq+PLL7/k17/+Nccddxxjx46NJyALBAKBQCDoYTjDhgwhDLoSET4kAODuu+9m4MCB7L///siyzD//+U+qqqro3bs3YFUgeuONNzjyyCPxer306dOHn//855x55pkceOCBHHfccbz44os899xzvP766wVt+5prruHII4/k0ksv5Wc/+xkej4clS5ZwxhlnUFFRQWVlJX/9618ZOHAgGzZs4Je//GUnHAGBQCAQCATdjukQBaYOKN02lN0N4SkQAFBaWsrtt9/OwQcfzCGHHMK6det45ZVX4tV97rrrLhYvXsyQIUM44IADADjllFP4wx/+wB133ME+++zDX/7yFx566CEmT55c0Lb32msvXnvtNT7++GMOPfRQjjjiCF544QVcLheyLPPkk0/ywQcfMH78eK655hruuOOOYu++QCAQCASCnQEjVRQIugrhKejBLF26NO01Z1diZ+Owiy66iIsuuijruk466SROOumktNcvueQSLrnkkqyfy9ScbPLkyfHX7fyGSZMm8d///jfjOqZMmcIXX3yRdb3Dhw8XTdAEAoFAIOgJmKrjb1GBqCsRngKBQCAQCAQCwc6B8BR0G0IUCAQCgUAgEAh2DtJyCgRdhRAFAoFAIBAIBIKdA+Ep6DaEKBAIBAKBQCAQ7Bw4PQWiq3GXIkSBQCAQCAQCgWDnQIQPdRtCFAgEAoFAIBAIdg5E+FC3IUSBQCAQCAQCgWDnQHgKug0hCgQCgUAgEAgE3Y+hg7PvkBAFXYoQBQKBQCAQCASC7ie1WZloXtalCFEgEAgEAoFAIOh+0kSB8BR0JUIUCArm888/57TTTmP48OFIksQ999yTtsy8efM45JBDKCsro3///pxyyimsXr06bbkvv/ySs88+mz59+lBWVsbhhx/Ohg0bumAvBAKBQCAQ7FSkliAVoqBLEaJAUDDBYJA999yT2267jaqqqozLvPXWW1x22WW89957LF68GE3TmDZtGm1tbfFlvv32W4455hhGjRrFm2++yccff8xNN92Ez+frql0RCAQCgUCws2Coyf8LUdClCFHQAXRD75afQnnmmWeYMGECfr+fyspKpkyZQltbG0uXLuXQQw+lpKSE3r17c+SRR7J+/XoA5syZw/77789f/vIXhgwZQiAQ4IwzzqCxsTG+3kMOOYQ77riDH/zgB3i93ozbfu2115g1axb77LMP++23Hw899BAbNmzggw8+iC9z4403cvzxx/Ob3/yGAw44gD333JMTTzyR/v37F7yvAoFAIBAIdnFSw4dE87IuxdXdA9jV0A2dV755pVu2fcKoE1BkJa9lq6urOfvss5k/fz6nnnoqLS0tvPPOO5imySmnnMJFF13EwoULiUajrFy5EkmS4p9ds2YNTz/9NC+++CLNzc1ccMEFXHbZZTzxxBMdHntTUxMAFRUVABiGwcsvv8zPf/5zTjvtND799FNGjBjB7NmzOeWUUzq8HYFAIBAIBLsoIqegWxGioIdSXV2NpmnMnDmTYcOGATBhwgTq6+tpampixowZjBw5EoCxY8cmfTYcDvPII4+wxx57AHDvvfdy4oknctddd2UNF8qFaZpce+21HHXUUYwfPx6A2tpaWltbuf3227nxxhu54447WLRoETNnzmTJkiVMmjRpR3ZfIBAIBALBrobtGZBkMA0hCroYIQoKRJEVThh1QrdtO1/2228/jjvuOCZMmMD06dOZNm0ap59+OhUVFcyaNYvp06czdepUpkyZwplnnsnAgQPjnx06dGhcEAAcccQRGIbB6tWrOyQKLr/8cj755BPefffd+GuGYQBw8sknc+mll1JeXs6BBx7IsmXLeOCBB4QoEAgEAoFgd8P2FChe0EJCFHQxIqegAyiy0i0/BY1RUVi8eDGvvvoq48aN495772XMmDGsXbuWhx56iOXLlzNx4kSeeuopRo8ezXvvvZd1XXZokTPEKF+uuOIK/v3vf7NkyZIkodG3b19cLhfjxo1LWn7s2LGi+pBAIBAIBLsjtqdAjhUcEaKgSxGioAcjSRJHHnkkc+fO5cMPP8Tj8fD8888DcMABBzB79myWLVvG+PHjWbBgQfxzGzZsYMuWLfH/ly9fjizLjB49Ou9tm6bJ5ZdfznPPPcebb77JiBEjkt73eDwccsghaWVKv/7663i4k0AgEAgEgt0Ip6cARKJxFyPCh3ooK1as4I033mDatGn079+fFStWsG3bNvx+P7Nnz+bkk09m0KBBrF69mq+//pqf/OQn8c/6fD7OPfdc7rzzTpqbm7nyyis588wz46FD0WiUL774Iv735s2b+eijjygtLWWvvfYC4LLLLmPBggW88MILlJWVUVNTA0CvXr3w+/0A/PznP+ess87ikEMO4fjjj2fRokW8+OKLLF26tAuPlEAgEAgEgp0CWxTIMVEgPAVdihAFPZTy8nLefvtt7rnnHpqbmxk2bBh33XUXM2fO5Gc/+xmPPPIIdXV1DBw4kMsvv5yLL744/tm99tqLmTNncsIJJ1BfX88JJ5zA/fffH39/y5YtHHDAAfH/77zzTu68804mTZoUN+j//Oc/AzB58uSkcT300EPMmjULgFNPPZX777+fefPm8ctf/pIxY8bw7LPPctRRR3XOQREIBAKBQLDzYvcpUET4UHcgREEPZezYsbz22msZ37NDiHJxySWXcMkll2R8b/jw4ZimmfPz7b1vc/7553P66adTXl6OLItoNoFAIBAIdluMlPAhAEOHAvMqBR1DWGECgUAgEAgEgu4nNXwIhLegCxGiQCAQCAQCgUDQ/cRFgdvqVQBCFHQhQhQIkpgzZw4fffRRdw9DIBAIBALB7ka8eZkLpFjIUGqXY0GnIUSBQCAQCAQCgaD7iXsKXNYPCE9BFyJEgUAgEAgEAoGgezHNLJ4CIQq6CiEKBAKBQCAQCATdi9P4F6KgWxCiQCAQCAQCgUDQvdihQ5JklSC1RYHoatxlCFEgEAgEAoFAIOhenKFDzt/CU9BlCFEgEAgEAoFAIOhenEnGIMKHugEhCgQCgUAgEAgE3YuhWr8lIQq6CyEKBAXzt7/9jaOPPpo+ffrQp08fpkyZwsqVK7MuP2/ePCRJ4uqrr056fdasWSiKQp8+fVAUBUmSOPzwwzt59AKBQCAQ5E9zpJm31r3F1tat3T2Uno1t/Mtu67cQBV2OEAWCglm6dClnn302S5YsYfny5QwdOpRp06axefPmtGVXrVrFX//6V/bdd9+M65o+fTpfffUVmzdvprq6mldeeaWzhy8QCAQCQd5sbd1Kc6SZzS3p33GCIpLqKYj3KRCJxl2FEAUdwdC756dAnnnmGSZMmIDf76eyspIpU6bQ1tbG0qVLOfTQQykpKaF3794ceeSRrF+/HrA6Gu+///785S9/YciQIQQCAc444wwaGxvj633iiSe49NJL2X///dl7773529/+hmEYvPHGG0nbb21t5Yc//CF/+9vf6NOnT8Yxer1eBgwYQFVVFVVVVVRUVBS8nwKBQCAQdBZ6bKZa78D3sKAARE5Bt+Pq7gHschg6bOmm2exBJ1hluvKgurqas88+m/nz53PqqafS0tLCO++8g2manHLKKVx00UUsXLiQaDTKypUrkSQp/tk1a9bw9NNP8+KLL9Lc3MwFF1zAZZddxhNPPJFxW8FgEFVV0wz6yy67jBNPPJEpU6Zwyy23ZPzsW2+9xahRo+jTpw+TJk3id7/7Hf3798/zgAgEAoFA0LnYYkAXxmnnklZ9SIiCrkaIgh5KdXU1mqYxc+ZMhg0bBsCECROor6+nqamJGTNmMHLkSADGjh2b9NlwOMwjjzzCHnvsAcC9997LiSeeyF133UVVVVXatn75y18yePBgpkyZEn/tySef5H//+x+rVq3KOsbjjz+e0047jcrKSrZt28bNN9/M9773PT744AO8Xu8OHwOBoFMwDKuOtkNICwSCnovwFHQRphAF3Y0QBYUiK9aMfXdtO0/2228/jjvuOCZMmMD06dOZNm0ap59+OhUVFcyaNYvp06czdepUpkyZwplnnsnAgQPjnx06dGhcEAAcccQRGIbB6tWr00TB/PnzWbhwIUuXLsXn8wGwceNGrrrqKhYtWhR/LRNnnXUWhmHQ3NxMeXk5hx56KMOGDePll19m5syZee+rQNBlGAYsXQoeDxx1VHePRiAQdAHCU9BFZAsfEs3LugyRU9ARZKV7fgpAURQWL17Mq6++yrhx47j33nsZM2YMa9eu5aGHHmL58uVMnDiRp556itGjR/Pee+9lXZcdWiSlzIzeeeed3HrrrSxatCgpkfiDDz6gtraWgw46CJfLhcvl4q233uKPf/wjLpcLXc/8YB04cCDDhg3jm2++KWhfBYIuIxKBtjZoaIAs17FAIOhZCE9BFyGal3U73SoKNE3j17/+NSNGjMDv97Pnnnvym9/8BsMw4suYpsmcOXMYNGgQfr+fyZMn8/nnnyetJxKJcMUVV9C3b19KSko4+eST2bRpU1fvzk6HJEkceeSRzJ07lw8//BCPx8Pzzz8PwAEHHMDs2bNZtmwZ48ePZ8GCBfHPbdiwgS1btsT/X758ObIsM3r06Phrd9xxB7/97W957bXXOPjgg5O2e9xxx/Hpp5/y0UcfxX8OPvhgfvjDH/LRRx+hKJkFTl1dHRs3bkzyWggEOxWOZxPRaPeNQyAQdBnCU9BFiETjbqdbRcHtt9/OAw88wH333ceXX37J/PnzueOOO7j33nvjy8yfP5/f//733HfffaxatYqqqiqmTp1KS0tLfJmrr76a559/nieffJJ3332X1tZWZsyYkXVGendgxYoV3Hrrrbz//vts2LCB5557jm3btuH3+5k9ezbLly9n/fr1LFq0iK+//jopr8Dn83Huuefy8ccf884773DllVdy5plnxkOH5s+fz69//Wv+8Y9/MHz4cGpqaqipqaG1tRWAsrIyxo8fn/RTUlJCZWUl48ePB6zKRNdffz3Lly9nw4YNLF26lJNOOom+ffty6qmndv0BEwjywflMUdXuG4dAIOgyhKegixCJxt1Ot+YULF++nO9///uceOKJAAwfPpyFCxfy/vvvA5aX4J577uHGG2+Mx5g/8sgjDBgwgAULFnDxxRfT1NTEgw8+yGOPPRZPdH388ccZMmQIr7/+OtOnT++enetmysvLefvtt7nnnntobm5m2LBh3HXXXcycOZOf/exnPPLII9TV1TFw4EAuv/xyLr744vhn99prL2bOnMkJJ5xAfX09J5xwAvfff3/8/fvvv59oNMrpp5+etM2bb76ZOXPm5DU+RVH49NNPefTRR2lsbGTgwIEce+yxPPXUU5SVlRXlGAgERcfpKYhEum8cAoGgyxCegi7CjE202M3L5B0TBZuaN9EWbWNM3zFFGNzuQbeKgqOOOooHHniAr7/+mtGjR/Pxxx/z7rvvcs899wCwdu1aampqmDZtWvwzXq+XSZMmsWzZMi6++GI++OADVFVNWmbQoEGMHz+eZcuWZRQFkUiEiOMLvbm5GQBVVVFTZv9UVcU0TQzDSApr2tkZM2ZM1kZgzz77bMbXDcPANE0ALr744iShYL8P8N1332XdbrZj9Oabbya97/V6efXVVzFNk5aWFsrKyuI5C8U+zvZ+qaqaNXRJsOPY907qPdSjCIeRNGs2ywwGe7S3YLc4n7sJ4lzuGOFoGE3X0HSt249hTz6XkhoGXcPUTevZqplIugZmGLPA/TVMgw82f4BhGgzwD6DEU9JJo+44XXUuC1l/t4qCX/ziFzQ1NbH33nujKAq6rvO73/2Os88+G4CamhoABgwYkPS5AQMGxJtt1dTU4PF40ppjDRgwIP75VObNm8fcuXPTXl+0aBGBQCDpNZfLRVVVFa2trUR3gxjiSCSCrutxodRVOMPBik00GiUUCvH222+jaaKKQWezePHi7h5Cp+FpaqLP6tUANG/bRijl2dRj0HX89fXIvXr16PO5uyHOZcf4uOVjIkZsIvFrkKXur9HSE89lP+1DZFTqlDCaFEAxI/TVP8ZEptZV2Hd3i9bCl21fAhD8Mkipq7QzhlwUOvtcBoPBvJftVlHw1FNP8fjjj7NgwQL22WcfPvroI66++moGDRrEueeeG18uteqNaZppr6WSa5nZs2dz7bXXxv9vbm5myJAhTJs2jfLy8qRlw+EwGzdupLS0NGd5zZ6C1+tFUZS049BZZPIUFJtwOIzf7+eYY47ZLc5hd6GqKosXL2bq1Km43e7uHk7nUFODFAtvM0ePBkfyfY9iwwaMDz/kv5s3c/hFF/Xc87mbsFvcm52I6zsXUd2aFJy+53TcSvcdw558LqVqCUwds//3wBUAPYK01dpHs8BS8N/Uf0NJneUdOHTQofQv2fmaonbVuSxkkrdbRcHPf/5zfvnLX/KDH/wAsJprrV+/nnnz5nHuuefGE1tramqSKtLU1tbGvQdVVVVEo1EaGhqSvAW1tbVMnDgx43a9Xm/G5lhutzvtxOi6jiRJyLKMLHf/7EBnM3fu3IxelM7CDhWyj3FnIMsykiRlPL+C4tOjj7OigMsuk2dCT91Pw0BTFBRV7dnnczdjlzuXtnfe4+nWYUiyhCtmLskuGber+4/hLncu28M0QZYAF3j8oLhBkUCJPW8VuaDS7C1qCy77szI79bHq7HNZyLq71coNBoNphqCiKHFDccSIEVRVVSW5VqLRKG+99Vbc4D/ooINwu91Jy1RXV/PZZ59lFQUCgUDQIZzVh3pyOKEt1nfjCm6CbsY0rUaBS5daf3cjzqpDogJRJ2E6woNSS5JCQcnGpmlSH6qP/6+J5md5062egpNOOonf/e53DB06lH322YcPP/yQ3//+95x//vmANXt89dVXc+uttzJq1ChGjRrFrbfeSiAQ4JxzzgGgV69eXHDBBVx33XVUVlZSUVHB9ddfz4QJE+LViAQCgaAo7C59CmJiQBY5OILuQlUTFb40rdu8cqkiQFQg6iTi5Uhl6wdAkqy/TaMgUdAcaU4SAqrR85KyO4tuFQX33nsvN910E5deeim1tbUMGjSIiy++mP/7v/+LL3PDDTcQCoW49NJLaWho4LDDDmPRokVJZSvvvvtuXC4XZ555JqFQiOOOO46HH35YVJoRCATFZTfzFMjCUyDoLpwCXNe7TxSkGKNi1rmTMFN6FNhILjCjyZ6EdnB6CUCcs0LoVlFQVlbGPffcEy9BmglJkpgzZ07O+vc+n4977703qemZQCAQFJ3dRRTE9lOEDwm6Dee1143XYZqnYGcNH2pqsnKeSnfeKjs5Se1mbCMrYFCQp6AuVAeAIivoho6qC09BvvT8zFmBQCAoFs7Zyx5YJzyOnVOgad0ez71bozbD1rcglLm8do9mZxEF5i4QPqSq8O67sGzZrnu/pnYztulAV2PbU9Av0A8Q4UOFIESBQCAQ5IvTONG0ZJHQk0gN3RB0D6GtljAIbuzukXQ9O8k1uEt4CiIR63hFIhAKdfdoOkY2T0GBoqAt2kZEiyBLMn0DfQERPlQIQhQIBAJBvqSKgJ4aQlSgR6Qh1MDm5s2dOKDdFNtQ0sPdO47uQHgK8sdZEKATG4F2KvZsvpSSO2KLgjwNezt0qLevN16XVXpehA/ljxAFgoJ57rnnOPjgg+nduzclJSXsv//+PPbYY0nLDB8+HEmS0n4uu+yy+DKmaTJ37lzGjh1LSUkJkydP5vPPP+/q3dnleemTLd09hN2HVOOkp4oC537mIQpWbVnF/6r/R1DNv3OmIA+yiYJt22DVqkR1np7IziIKdgVPQU8QBVk9BXZfmPyOux06VBmoxC1bAkN4CvJHiAJBwVRUVHDjjTeyfPlyPvnkE8477zzOO+88/vOf/8SXWbVqFdXV1fEfu4/EGWecEV9m/vz53H333cyfP58VK1ZQVVXF1KlTadlVH2rdRH1bDzVMd0Z2R09BO2VJQ2qIiGYZp0IUFBnbmDEiybHi330HNTWwYUP3jKsr2FnCh4SnoGsoUk5BXdDyFFT4K3DFBIbIKcgfIQo6gq53z0+BPPPMM0yYMAG/309lZSVTpkyhra2NpUuXcuihh1JSUkLv3r058sgjWb9+PQBz5sxh//335y9/+QtDhgwhEAhwxhln0NjYGF/v5MmTOfXUUxk7diwjR47kqquuYt999+Xdd9+NL9OvXz+qqqriPy+99BIjR45k0qRJgOUluOeee/jVr37FSSedxPjx43nkkUcIBoMsWLBgx86PQNBZ7C6eggLCh5oiTfG/o3oPPR7dhT17apqWMLCxPQSO53KPYyfxFKTOMhvmTphH1BNEQRFyCsJamKAaRJIkKvwVuBXhKSiUbi1Jukui6/DKK92z7RNOsEqO5UF1dTVnn3028+fP59RTT6WlpYV33nkH0zQ55ZRTuOiii1i4cCHRaJSVK1ciSVL8s2vWrOHpp5/mxRdfpLm5mQsuuIDLLruMJ554Im07pmny5ptvsnr1am6//faMY4lGozz++ONce+218e2sXbuWmpoapk6dGl/O6/UyadIkli1bxsUXX1zIkREIuoZUT0FPrUCUmlCdg+ZIc/xv22MgKBJOQ0gPgeKz/rbFqBAFnT+MXS18qLXVEpGO7/RdgiJ4CuzQoXJvOS7ZlfAU6CqmaSbZOYLMCFHQQ6murkbTNGbOnMmwYcMAmDBhAvX19TQ1NTFjxgxGjhwJwNixY5M+Gw6HeeSRR9hjjz0Aq8nciSeeyF133UVVVRUATU1NDB48mEgkgqIo3H///UkGvpN//etfNDY2MmvWrPhrNTVWib0BAwYkLTtgwIC410Ig2OmwjRNFsf4WngKawglPQUQXoqCoOGc4nXkFtqcgHLZ+fL6uHVdX4BQC3Vjla5cLH9J1qwJRINB94+kIWfsUuJLfz4EzdAiI5xSAdd5cqYJDkIY4QoWiKNaMfXdtO0/2228/jjvuOCZMmMD06dOZNm0ap59+OhUVFcyaNYvp06czdepUpkyZwplnnsnAgQPjnx06dGhcEAAcccQRGIbB6tWr46KgrKyMjz76iNbWVt544w2uvfZa9txzTyZPnpw2lgcffJDjjz+eQYMGpb2XqtyFmhfsMJoGK1ZAr14wfnxx120bJz4ftLX1XFFQQKKxM3xIeAqKjNMQ0mOlJlNL4TY0gOP53WPYWXIKdjVPAVghRLuaKCiip6DSXwlYzctkScYwDVRdjXsOBNkROQUdQVG656egISosXryYV199lXHjxnHvvfcyZswY1q5dy0MPPcTy5cuZOHEiTz31FKNHj+a9997Lui7bSHca67Iss9dee7H//vtz3XXXcfrppzNv3ry0z65fv57XX3+dCy+8MOl1W1zYHgOb2traNO+BQFAQa9dCfX3nJGHaxonfb/3uqaIgT0+BqquE1ERddJFT0EFME776CrZuTXk9g6cg9ZrrqSFEO0v40K7mKYBdM6/A3DFRoOpqPJTR9hQAItm4QIQo6MFIksSRRx7J3Llz+fDDD/F4PDz//PMAHHDAAcyePZtly5Yxfvz4pOTeDRs2sGVLoszl8uXLkWWZ0aNHZ92WaZpEMpTHe+ihh+jfvz8nnnhi0usjRoygqqqK119/Pf5aNBrlrbfeYuLEiR3eZ8Fujq5blVnsvztj/ZAI19gdREGOnAJnPgGI8KEO09QE33wDn32W/Hqm8KHU56wQBZ07jJhnwKN4kv7fqbDvUXcsXGZXFAW20S5n6VPQjiiwvQQlnpJ4fwJAJBsXSId8KRs3bmTdunUEg0H69evHPvvsg9frbf+Dgi5jxYoVvPHGG0ybNo3+/fuzYsUKtm3bht/vZ/bs2Zx88skMGjSI1atX8/XXX/OTn/wk/lmfz8e5557LnXfeSXNzM1deeSVnnnlmfHZ/3rx5HHzwwYwcOZJoNMorr7zCo48+yp///OekMRiGwUMPPcS5556Ly5V8qUmSxNVXX828efMYPHgw++67L7fddhuBQIBzzjmn8w9QD2JX7WrfKaxfn2yo63rBXrac2MZyT/cU5JlobIcOeV1eIlpEhA91FPs6Cqf0I8gUPmQv63JZ56axcddMLG2PnSR8yDYmPYqHqB7duT0FvXtbPSx2RVFgH1cp5XmdZ/Oy1NAhG2eysaB98hYF69ev54EHHmDhwoVs3LgR02GJeDwejj76aH76059y2mmnIcvCAdHdlJeX8/bbb3PPPffQ3NzMsGHDuOuuu5g5cyY/+9nPeOSRR6irq2PgwIFcfvnlSdV+9tprL2bOnMkJJ5xAfX09J5xwAvfff3/8/ba2Ni699FI2bdqE3+9n77335vHHH+ess85KGsPrr7/Ohg0bOP/88zOO8YYbbiAYDHL99dfT2NjIYYcdxqJFiygrK+ucgyLo2RgGfPtt8mudJQp2I0+BlCN8yE4y7hfox6bmTcJT0FHsY2wY1t9uN5hGsuJP9RT06WOFyWmaVXGmpz03dxZPgbkLeQr69LFEwa5YgSirpyC/5mV2J2Nn6BCmgQfrGAhPQX7kJQquuuoqHnroIaZNm8ZvfvMbDj30UAYPHozf76e+vp7PPvuMd955h5tuuom5c+fy0EMPccghh3T22AU5GDt2LK+99lrG9+wQolxccsklXHLJJRnfu+WWW7jlllvaXce0adOSxGMqkiRx8803c80111BeXi7EZAfZlZ77ncqmTYlKLNGoZWBpGng8xdvG7pBTkFrpJY/wof4l/dnUvAnd0NENHUUuohDbHXAKr0jEEgWpRowetgw9+5rz+ayZ4bo6y1sgREHnDCMlfGinNC7te7S8HGTZOl7BIJSUdO+4CmEHcgp0Q49PUCSJgm3LqGj6H9s9Q0VOQZ7kJQo8Hg/ffvst/fr1S3uvf//+fO973+N73/seN998M6+88grr168XokAgEHQdpglr1lh/jxxpxWdHo8U3JlJzCuxKMD1J0KYesyyeAsM0aIlaYQoV/op4lY+IHiEg72KVT7obp/CKRKC01GEkyTGvgQFGNOEp8Hisn7o6qwLRkCFdP+7OZGcRBamegp05fMjttq6d5mbLW7CriAL7+oYONS9rDDdimAY+l48Sj2Of1WZcMrj0sAgfypO8RMEdd9wR/3v9+vX0798fvz1TlsIJ3VWuUyAQ7L5s2WKVCPV4YNiwzks2tmfRnTlUqpr8/65Ong3aWiItmKaJW3Hjd/vxuryE1BARLULALURBQTiPsZ1XEK/bHgun0COWt8D2FHi9ibKTPTHZ2DAgGktk1ytzL9uJ7BKJxvb143JZHqPmZiuvYFep5Of0vqR6CuT2RUHm0CETTB1FciGb6s7p4dkJKWh6yzAMRo0axaZNmzprPIJuZs6cOXz00UfdPQyBIH9M0/IMAOy5p5VDYCe2t9ONtyCcxrLLlQhL6mkhRHmGD9lJxr28vQDwKpYwEmVJO0Bq+BAk121XYpNwejjZU9C7t/V3c3O3zqZ3CpoKLautH7X7rinbM2BXtCm6p8A0LW/Pjjyr7HNviwLommRjVS1OY7m4V0xJj4e1RUIOo74x3AikigLrmCiSjGyoInwoTwoSBbIsM2rUKOrq6jprPAKBoEB2++pDW7daX4AuFwwfbr1mJxcX01ByrkuWE+X/eroo0PWMX/x2PkG5txxIGE0i2bgDpIYPQXKHVyUWrqaHkj0Ffr/12zStsqY9CTUam+01QQ122zA63VOwdSssWwZffNHxddjXT1eKgpYWWLQIPv54x9eVrZsx5BU+1BptBaDM68iriS3vkl3IZlR4CvKk4EDY+fPn8/Of/5zPUusp93ByJcwKdm7Euevh2F6CESMShnpnigJJskSBHTLU00SBvZ/OBO0Ms5h2Yl8vX7KnQJQl7QAd9RSAVXEGel4IkdOIi3ajKEjJKTBMo7jfKcHYvoVCuZfLhq4nZoZSRUFnfvfV1FiTBdu37/i6snUzhnZFgWmaBGOiscTtyCewPQWyYnkKRE5BXhTcp+BHP/oRwWCQ/fbbD4/Hk5ZbUF9fX7TB7Qy4Y0ZGMBjMmkch2LmJxow2pZilKXciduvqQ9u2WcaQolihQzadGT5kJxX3dE+BomDa94yqJokE0zTjngI7fMg2mkT4UAfI5SmQHJ4CIyWnAKwQopqanicKNIcRtxN5CsASBkpqPf0Ob0BP/l0ozmvH5bKehbJs3cedWYHIFgPh8I6Xfs7HUwBg6IkcgxhBNYhpmsiSjM/lc6zTDh9SkE1NeArypGBRcM8993TCMHZeFEWhd+/e1NbWAhAIBJB2ayusuBiGQTQaJRwOd0pJUsMw2LZtG4FAIK2BmqAHYHsJhg1LntnuTE+Bve6emlPg2E/TvmdSko2DahDN0JAlOV7tQ4QP7QCZPAWZwodCLQnRZl9/dl5BQ0OnD7NLSRIFHZxFLwKpngL7NYUiiQLbqN9RUWDfq5KUqEDU0tI5osAwrB4ZNqGQtc0Ory8PTwHEDP10UQBWJ+Mk2yx2/7hkF4oRFTkFeVKwlXTuued2xjh2auxOvrYwEBQP0zQJhUL4/f5OE1uyLDN06NAeKeZ269CoSMQquyfLVhlSJ7bh3pmegp4qChz7adj7mnIcbS9BmbcMWbKW2WXDh3aGkrI5w4eURPhQOBYnbs8IQ0IUBIPWtVjMvhzdie645rpJFJimGfcUuGRXvOyubuiptmnHscVARxN2U0UBJFcgitkvRaWhIXm8weCOiYJsPQrAEjnxsrzpwsnOJ0gKHQLLq4D1/S+bInwoX3Zo6jQUCqGmzCCVl5fv0IB2RiRJYuDAgfTv3z9tfwU7hqqqvP322xxzzDHxUK1i4/F4emxjtKhu4FZ65r61i9cLU6ZYX1A+X/J79hdkV3gKetozwSEKsnkKUisPQWImdZfyFHzyCWzeDJMnJxrSdQep4UOmmTl8KNgCBJINf7s2fWurFULUv39XjbpzcRpxWrhbxJthJgxfRVJQZAVDN4pbgajYngJI5BW0tnZ8XLlIzSMI7mB4V67wIbDuATOaWM5Bm9oGkNyfABKJxqIkaUEULAra2tr4xS9+wdNPP52xCpHe08qiOVAUpcfGpXcXiqKgaRo+n6/TREFPJqoZeHZXUQCWkVCZoYZ5Z4QP7S6eAof4MZw5BQ7i+QS+hCiIhw/tSp6C7dsto6qpqftEgWkmiwLTjJV6dBhKckwURCNgeNL7YvTubRmADQ35iwJDg+bVENgDPL3aX76rcYYP6ZFuEQVO41+WZBRJQUUtbgWiHc0pcPYosOnsCkS2KHC7re3vqCiwQ3vkLDaArIBBRk9BWzQmClI9BY5EY8k00fUwpmn2yIiBYlLwHXbDDTfw5ptvcv/99+P1evn73//O3LlzGTRoEI8++mhnjFEgEGQhohl43buxKMhGZ4QPdVdOgWlaxluki0pBOz0FWY6jXXnILkcKyX0KdpmwNtugKuZ1UijObdsTI5FIsqdAViyDSdUsAyo1RKgjFYiCG6D1O2j5Or/low3QtiH/9e8IscZTif+1bulVYM8uK7KCJEkosSTXDnsKGj+FtvUpG9lBT4H9OeekWmdWINL1xHVmd9HeYVGQI3wIclYgyu4pSJw7ANkQ3oJ8KNiaePHFF7n//vs5/fTTcblcHH300fz617/m1ltv5YknnuiMMQoEgizs9p6CbHRG+FB3eQqi9dD8NTR2URloR/WhTJ6CqB4lrFldd52iwJmIuUtUILJn5KF7RYE9BkVJhMGFwwkDyA6pUPwQVcGIZvYUQGHJxpFYomi+4V4NH0HDx6A257+NjqLrVgw5JMqrRTspFCbXMIxEBRvn7w55CtQWaF0HTSn9CHZUFDivH5tAILkCUTGpr7fW6/NB377Wa21tO7bOXDkFkFUUOMuRlnpSchpiy8rIlqAzRQOzfCjYmqivr2fEiBGAlT9glyA96qijePvtt4s7OoFAkJOoZuBxCVGQRk+qPmR/keldlGwZ208zS06B7SUo8ZTgcsQAS5K0a+UVaFpiFnVnEAUuV8LYj0TSZ08VH0Q1SxSkegrKyy0jUFXzN9CiMQFh5HmutNj1p3VBeVBdB+za+7H7rTtEgSMExfm7Q54C+z42NHCKZmeicUdm9TPlFNgViKD4IUR22Hjfvpb4gI73WLDJJ6cA0roaO8uR2p7KxDoT58glu4SnIE8Ktib23HNP1q1bB8C4ceN4+umnAcuD0NuerRAIBF1CVBeiICOdmVOQKdG4M8Nl7BlTQ41X1OhUjMQMbabwodROxk52qbwCp5jbGcKH3O5kUZA6e6r4snsKZBl6xfIC8gkh0sPWD1jraw9DTxhZ+Sy/oxiGdd3LEtie0Mgu7ilwzlI7Bb7z2sunApHajM9whBI6rx8nnZVXYOcTOEWBqu5YwYUOhg85Q4fScgVS8kGKXoFICyW8bT2Igq2J8847j49jba1nz54dzy245ppr+PnPf170AQoEguxENQOvEAXpdEbzMltgpDYvg06uQOQwFIxwJ27H3oajJGmG8KFMlYdsnHkFOz07iyiwj202UeAMH1LVzJ4CSIQQ5SMKnMaMoSWEZzacQqArRIEdPiTLCVGg7mCISkeGUUxPgbNyjlMUOCcu8pjEkOpX0cv41gpHgsyeAugcUaBpieurb19rgsS+ZnckTKldT0EWUZAtyRiSvAqWp6CIvQoMFba9C9v+2zWesy6k4OpD11xzTfzvY489lq+++or333+fkSNHst9++xV1cAKBIDcRzcAjKmKl0xWeAklKVN/ozPrwToNND4OrkzqUxreRu3lZpspDNrtUAzOnkNsZRIHLlcgpyBY+FNHAkNI9BWAlG69dm19eQTRlGSOaKHuaCacQ6Ipza4sCRU7cb7t6TkExPAVqc+KzdthXV4qC+nrLKxoIJKp1BQLW9RoMJrxVhVIET0Ea9rKxUrJFDR9q/jrhadND4AoUZ707ATvUpyAcDjN06FCGDh1arPEIBIICiGg6ZT7RqTmNzswpcJZF9HgSoqCzcH4R6l3sKbD3NWa46oYebxaUKXwonlMgwofyp2BPAbk9BU1N7ZfvLFgURJKX7WycngJ3AGiDaA/yFDhnlwvxFIS2pq+vPVHQ2moZ8sUoxekMHbIJBCwh2iWeguT71PYUpCUZQ+K56SpBkSxRUJTwIbUZ2tYm/u9heQoFxx3ous5vf/tbBg8eTGlpKd999x0AN910Ew8++GDRBygQCLIjqg9loTPCh1I9BdA1ycapnoLOJpOnIHYcW6ItmKaJR/Hgc6UbkbtU+NDO4ilwGnX5JBrrkcyegpISS1gYRu6mVaYBqhUCFjfC2pv97+rwIcMAYp4Cexa4O0RBZ3sKUpOL2xMFkdrE37bRm00UdEYFIlsUOHvD2HkFO1KByD42UrY+BbF9y+YpyBQ+FBcFAVyyC8XUiuMpaPws+ZxlaKi2K1OwNfG73/2Ohx9+mPnz5+NxzFZMmDCBv//970UdnEAgyI2oPpSFrvQUQM8SBTlyCnKFDsEuFj60M3sKQg4jLl55RUnU73dlCRm0K87kMtDUJjANDNnF1kiYqBFt39BPEgVdFD5EzFPgjc14q+GuSbR3DsPuihszSoueU5B63eV6XhlqsofHaMdTUOwKRKoKzbFytKmeAthBT0FK+d1UMoQPGaYRL0eaOXzIPi4lyJJSnJyC4GarX4ykgLs8bUw9gYKtiUcffZS//vWv/PCHP0zq7rvvvvvy1VdfFXVwAoEgN6L6UBa6oiQpdFFZ0u5LNE6tPmSXI01LMjZN0HURPtQRMlUfCgcTIR+yfQ5MkOSYIMhyveUzaxszLLerOqsb1rGxaWP7okDvrvAhCdw+ywjTja4ry2sPw0gJHyq2p6AQURDZnnmGOpsogOLmFdTVWdsvKUnkvsCOiwLTcPSkyF8UhNQQpmmiyEp6OVLnskoAl6wgmxpqjudSW7SNpeuWsrl5c+YFDC3RY6JsFLhjx3Z39xRs3ryZvfbaK+11wzBQO7UCh0AgSEV4CrJgG7OmmV+Zv3xIbV4GiQpEPclT4BA/hvM4alr2mbkVK+D11/Ea1rHZJTwFO0v4kNNT4PHEYr8NiKgJYwiskCLFAx5X9uugJHZe8hAFYdmPIbusUK9CPAVdERpmh9UoMrjcoHit1/SurfQS72gsFSGnwBm6okes+zpVBOR6VoW3Jv/fHaIAkr0EkNyroCOlmZ1iScriAcsgCpyhQ2nlSJ3LKn6UmAdC17KLyprWGloiLWxq3pR5gZavE4UeykYmxtTF3qvOpmBrYp999uGdd95Je/2f//wnBxxwQFEGJRAI8kPkFGTB+QVZLIOvuzwF3ZhojKIkEhS1REyuW3bE/pqmFWscjeINW1/wwlNQAM7qQ5JkXVOGDqqWPHMajYLkscRDthlzWxTkmrWNlSONKAEMyWXNeheSU2DqnW8I6TqgW14SxQ2yp3s8BamJxjviKTBTJk31UGGegvA263dq2EouUWBfD+EiPDcyJRmDVYVIkqznRqQD970zyThbMnSG5mV2knHAnaXyjyMkSVasSkl6DlFpd2nPGGKktkCrlT9L7/GWx84eUw/zFBRctuTmm2/mxz/+MZs3b8YwDJ577jlWr17No48+yksvvdQZYxQIdnn+tGQNlx2b7mHbUaK66FOQEUlKJNkVK4Qok6fA2cCss+iunAJb/NjJq6oa/8J0Kw5REI3GZwi9se9HwzTQDC2p4/FOh1MUFDPMrFBSm095vdCqQ8RIjrGOewr0jnsK7KZlkkRY8mFILjRTK8xTAFZegdyJZRjjJUnd4PKA7LVEQRfXhE9LNC6WpwCsfdFTjOBs16HaHDtvCqa3f/L6comCYoVRRqOJfAJnkjFYz1q/3xKiwWByaFE+tFeOFHJ6CjJWHkpar4ISEw5GjusnLgoyVSiyk4v9VeCLHX+5Z4qCgq2Jk046iaeeeopXXnkFSZL4v//7P7788ktefPFFpk6d2hljFAh2eV79rLrT1p3RdSoofl7BzpBTYBqdH76RrUmbmijpl+QpcMxCKqoWN5y6xVsQDMLrr8OaNe0v6xRyhlG8MLNCcYYPgSUKDMPqXpzJU5BP+FAolHl/orGmZa4yVEwMyW0ZvoXkFEDn5xU4OxrHw4f0nc9TUEhlH9tTYN87hXgK7FKk3r6W1wQsA1nXEyE7nSkK7NChsrLMla92JK+gvXKkkFkU2I3LMiUZO5eVXLhclnDQ8xEFqZ6CULWVzyHJ0GufnGPqCXRoGmf69OlMnz692GMRCHokG+uDVJX7CKs6PrdoNNZlKIplcBUrNCSXp6CrcgrASjZWOqlRGqTvp8tlzVI7woeSPAAhh6EWjeJVvASNIBE9Qgmd3GgtlYYGazxbtkCG3LckUs+ZpnVeA7pcOMOHIDbTqsdyClI8BbIbPGQ3jj0eaz2aZhlopSmzqHb1Gm8FWlsIU7ZEgalHyDm1YIsASYmFD3WFMLU7Grti4UNtO5+n4PPPYd06OPxw6Ncv98rsmWt3uVXBRg+BnvJ9kM14t0uR+vrHn2eSqSc/2zI1sbTv4R0VvNlCh2x2pCzpDnoKMpYjdS4rKfHwITOHpzWrp6Bto/W7dGRyk7IMIU09gYI9BbNmzeLtt9/ujLEIBD2SlWvrmTauiuaQSMTvUmwja1f3FKTORHV2CFGqKIjNYJvRaCKnQMnsKSASiZcl7ZZeBbaR1F5ss2Gki8XuyivIFD5k6lZPAjnFUyB7wZ3DUwA5Q4gktdH6w9MHVVcxYoaNliuB1zQSyaB2xZXOTiS3Z8AVOZZT4AXD7PJE47SSpKmegtqYsZ5PIq/pEAWQ2VOQyXh3liL19U8OW3GGDmXyGBfLU5CpP4GTYngKcokCuwJXbNn2y5GajopGCq6YcMgnfMgwjeScEbunhx02FB+TCB8CoKWlhWnTpjFq1ChuvfVWNm/OUr5JIBAA0BRSGVoZoFGIgq6l2OFD7eUUdKTyRj6kego6WxSkip+YsapFErPTSZ6CVFEQKw/YLeFD9tjbE2nO0CH7HHaHKND1xHVli9i4KMjmKXDTEtrGxzUfZxZe2USBs2mZpw+qkRAFupqjckzcSyBZlVecr3UW8fChWPWheKJxpEurvaSVJHV6CiKRhBHc3vVmaInjawsrLZT+bMr0rApvsz7rLrVmqp0z1LnyCaA4z0BVTTTDy1MUFNQ5OK/wIXufrf1wliPN1EQxaSJFUlBiM/ymHsZIfZ5iTWA4X4+HEOnRxPPWFnOO9aZtqwdQsCh49tln2bx5M5dffjn//Oc/GT58OMcffzzPPPOMKEkqEKRgxr4IegfcNAbF/dGlpNTY32EyeQrs2V3T7LxkY/vLKt59tms9BXavAlsUKLKCLDm+OlJEQbxXQXeUJbXPdSwxOivOOH77HHaHKHBuM5MoSPMUWDkF1Y3r2NC4jprWmvR1ZhEFboIxQ9sDrpJkT4GpJpeGdBIXBbEZe+j8BmbxRGPZSjRW3GDGZsK7MK8grSSp01PQ4Ggk1p4oiM+GS+CyvS3B/HIK7NAhO8HYaYx2hSiwryOfL3t4nUMUbGnZwmtrXuPb+m/zW38HwofaDx1yHFdZweW2wuhkU83Y1dj2EtjERY0tol0l6aJFhA8lqKys5KqrruLDDz9k5cqV7LXXXvz4xz9m0KBBXHPNNXzzzTfFHqdAsEuyqSHEkIoAvf0eGoPdEE6xO1Ps8KHUqjwQm8mMbafTQojs7ca+eDvbKMrmKYhaX5xJScaQNXyoWz0FsbFkxT5Xdgw+dI8ocIoTO/zDTjSORDN4Clzg9aKbWlYDJ1t8t9uMzfZ6+gAxg1eSMSQld7Kx7Y1QvIkk167MKXDZ15sjQbeLSEs0dnoKChEFtuCSXBCLb0cPty8KTBPCjnwCex2QHj6UiWLkFNjXUUkWAxwS11w4TEOblZS8um51mrGdEfvYpD5XnDhFgWnmn2QcM+RlxY8sy8iGmtGLkSYKjBRR4MnQwV14CtKprq5m0aJFLFq0CEVROOGEE/j8888ZN24cd999d7HGKBDssqxYW8+hIyqEp6A76KzqQ3LKY7Oz8wrsLx07ya2bcgr0iLXdtDKjWcKHujWnIDaWrNjnyu3eOUSB06jzeklLNDbNWPUhCXyl6KaOYkQzi4IsvQqcosA0zfhnDcll/Z3N0Le9ArLHEgbQ+RWwtFi4jSxZXgIA0xYFXZdXkJZonM1T0J6XMB4i4wbFZ51H04BobF+yGe9qsxUyJSngjYXuZMspyIRzAqOjz0E7dCiXKPB649sygpbBrhs6q7evbn/9jipBWXE2NTONgpKMAVC8KJKCkqenIP7sUmNlWF0poUMgcgpsVFXl2WefZcaMGQwbNox//vOfXHPNNVRXV/PII4+waNEiHnvsMX7zm990xngFgl2K5pBKL78bn1shrPWsGYWdnmKHD2XyFEAXiAI75jz2BdjVoiBmcGhqzFOg5PAUqCqe2Jd7t4QP5espiBlxTUaIDW1brDC/LhIFqq4mvCipScaQCB/SdLBrAjlzVvyl6IaObEQzN9FyigKHkekhNuPr6ZNkGNkViLKLgtjrssfhKSjuuV3bsJb/bvhvYhbX/m2HD0HCaMzRlbbYZPMUGIaOWZCnwBEiI0mWMACIJcvGnyGphrvtJfD2tUpiQsfCh6xB5x5jNmxPQWolq1Ri3gKjNZF0vaFpA82R5tyfi5dqzVcU6AWUI419TrZEgWQaqBmun3bDhzJ6Cnpm+FDBJUkHDhyIYRicffbZrFy5kv333z9tmenTp9O7d+8iDE8g2HUxUxL3RDeBLqazqg9l8hToKmxdCeUHQWBwcbZnY6aGD3WiKDDNzM3LsD0FUrKnQNfTZkm9hnWld0v4UAGeAtM0+bJxDVE9SqnWh4ouEgXvbHiHiBZh2shpKJk8BW43EHt2qEZ8vPH33CUYpoFiqpmbaPl81rnTdas8a0kJ6GFkMwJI4OmN6pjpb7eBmdH54UPrm9bTEmlhW3Abg8oGgWYbio7woZ3IU+BqDWJovrhIyDt8yA6RUfyWuInYQs1jievUZ1UkJXQIHN4jA9TYdrOJAkmKeSVMa93uHCE62cjHUwCWKGhpwWhrBa8Ll2x5oL7Y9gWH73F49s/llVMgWaLINMDU2vcUOBqXASC7UBQvaOGMvQoyhg8ZGqixfXe3Ez5kmtm7Me9iFOwpuPvuu9myZQt/+tOfMgoCgD59+rB27dodHZtAsEuzsT7E0IpO7PopyE0xw4dMMzFTm8lToDVDSw20dsZzz/YUxK4lI5pekahom3KsNzV8KFNOge0lUJR4J1O7q/HO7iloijQRlg1MRaYl0tolngLDNGiLtqEZmmWIZPIUSBK4Y8c+Etsfe188HlB8GKaBnC18CNLzCuySlu4ykF1JcdWG5LKM32znS88QPlRkUWAb33aZyYSnwOUweO2E8K4RBaZpxivSpHoK3E2t1nu2oZx3onFsX+y8gkjM6LQbgjmv39RSpDbOWXM1dm6yiQLY8edgvp6C2LEwY8uPrhyNLMlsa9tGbVtt9s/lU30I4sfOMNTc5UghY0iS3atAU9NL9dqiwC6goOpqInRI8SWu+wzjSdpeDyBvUTBo0CAuueQS+vbti5w6UyYQFJkFKzbQtIvH4K9cV88hIyq6exi7L8UMH3J+oWbyFBgqqFrCFV5M7BARxZcIIegsb0EmURAzOPSoZYBk7FHgqEzijQ1X1dWM5f86lQI8BdvbtmO4XRiKQmu0pUtEgTPcRzO09G7GNrYoUFNKrHq9oPjQDSunIGP4EKTnFcQ6GZvu3tZqDacocLeTU5ApfEgrqjC1xY0dFhK/31yuxH1s2sZt14QPOb0wiqFBwyegNqPICu7mmCgYMMBawDByG91GSoiM7fVTY/uSKXwotRSpjSQTN92ieYgC+z7uiCiINS1EkhJCMxv+WIOwWE5BubecEX1GAPDFti/SPOdx8vEUQLxXQSjamrscKaSHDwFSbFlNa01bPBQ7D6UeS/iohkMUpJYiTRlP0vZ6AHlb9wsWLCAQCHDllVfSt29fzjjjDB577DHq6+s7c3yC3ZStzWFWrdu1ry07n0DQTeQbPhTcDNWLIJLjestkLNs4RUGnJGAmmvDEY5E7WxRIUmGeAp8vPtvpVg2kmCu9y5ON8/QUaKEgDeEGDLeC6VJoU4Nx0dOZOGf2k0RBqlHntStaxc6Hw1OgSdbxl80cnoKUsqSJpmUVaeMwZFeeOQVeK/wlLkyLd7zs8cQ9BZodsuR2eObcsTCYcOd5yhw4BZcSroa29dD6HYpkiQLdNKwuxpIj7yMbqeFDLttTkJJT4HzORLZZv70OL4G9OmLHpBBPQUdyCuzQIb8//bmXSkw02KLAJbsYVTEKt+KmJdLCxuaNmT+XT/MyiBv4QdXKWcgaOgQZRYHdqyBX+FC51xIAlqcglk+QKXTIpgcmG+ctCiZPnsxdd93FN998w/LlyznwwAP505/+xMCBA5k8eTJ33303336bZ11agaAdKks9bKjv2u6VxSTrrIiguDR9BY2fZjbGU9zmbdE2lq5bysamlC+n8FbLwGnN8fxy5hOkxo56PNaXQrSTPAVxA0jufFGQKW8iJgqMmNGcsXGZQxRI0Wi8V0FRREFws3WO8zEE8/QUbGuykosDJb3x+krANGlu6/xJCOfss2qomcOHANy2oZnuKdBjokAxoplzCiBZFKQ0LbNWmxw+ZOUUZDlezupDzt9FCiEyTCPuUbJjxeM5BS6HKFDcYHRdr4KkJGN7X/UoLs3AFYxgmDr06ZNfoYG44evIKYBE0nSm8KFIXey9vumrs4VZLPm/08KH8ilHapPinXIrbtyKm9GVowH4avtXmUVs3uFD1n60xRKXs4YOJa0zIQrkLKLAMI34c6rMa/WQsDwFOZKM42OyRcFu6Clwss8++zB79mzee+891q9fzw9/+EPefPNNJkyYwPjx43n55ZeLPU7BbsiunLezoT7I8L7J7lYhEzqBtvXQui6zQZNSarKmtYaWSAubW1K6sNsP9HBt9koS2SoPgWXQGWqiQkyxq1HYxrDkEAVGJ3sKnKLADh9So2AY2cOHbMMmGi1uV+PmL61zHNzc7qL5egq2NVrrGlgxjPISa/a8JdiQdflikdVTkC18KGonaGTwFBgqup6Hp0CzhIGJK17Byg4fcsmuRE5Bu30KChAFhgr1/4PQ1uzL2Kt3zMiH1JAlEOz9UlzJ16IUu8a6IK8gKcnYNjJNFW+ztW094E9ufpePKEgNH4qmeArs61ePWOcNwJsegmrGw4faSTSGHQsfyjefAOLhQ0Y0iqRq8cmD4b2HU+IpIaJFMjc0s++JXH0KIG6Ah2PJvzk9BfY15fA+KLFjbqRUH7KfUbIkx9epahGIeSRyegpsT0QPqkC0w8kBVVVVXHTRRbz44ots376d3/72t3i9GZIyBIICCXgUWiO75s22cm09Bw8X+QSdjj0TlGmmJtVTEJuFTJutsv83DctrkIlslYcgFj6kWeFDkL0zbEdwzo5LMshdFD6UoWuzbupImt5u+FBSA7MdDTGxw0UAghvaXz4PUdAWbaOttQEkiYEVQ+kVsO7TrvAU5CUKTNMhCtI9BRoKJhISJnq2GXNHh1lioRGGlNiG7SkIuAOYuXIKTDM5fAjyK0saqrFEXMvX2ZeJkertCKpBhyhwJ4ey2aKgyz0FsfNkqHhbYqKgdyzWPB9PQabqQ2B5RAwtXRQkJYanG8umHT5kC7ZcVYWKET6Uj6fA5UJ3KWCaKOFIXBTIkszYvmMB+Lbh2+RKP6ZZePhQJBY+lNNTkCF8yB0TBSnVq0IxkeBz+eITHnq0Kdb9252cz5FKDwwfKrgkqU1tbS21tbUYKRfaqaeeusODEggADhrWh/+tb+CY0f26eygF0xLWKPclP6hdskxUM/C4RKJ+0cjVVTJFFNjxymmiwPnZ0JbMJUVzeQo8HitsyDbgTBXw57kD7eAcW1fkFGQSP5IEitX1Vtb07OFDRiL+3Q4f2mFPgRFNVH2K1Fuzp64cxoAzfMgwLKM7xWDa2LwRWdPp5S3HFyinT1k/aoDWYCOmacbzITqDNFGQqc68qYHHnn2OGZNOT4GpY8guFEPFzHYd2DHghgFBK9zCcHzd2+MIuAO02X0KMoV6OQVu3KDNowKRbXhlSOpMJfV+DKpBSnVH+BBY951hgOQDmrvUU+CSXYmJA0PF0xIkAmjlVqhJ3KDPmVOQYvjKiiWutJiHxhbU9j0USwy3c0BSiYuCaATwZX4u2RQjfCgfTwGg+639UEKRePlWgIFlAyn3ltMcaaYuWMfg8tgzVg/HynnKCbGZDSmRaIxS3oGcAmv5VE+BLVJ8Ll98wsNUG8HfK3uSccqYelL4UMGi4IMPPuDcc8/lyy+/TK/DLknoxaoJLthtMU0TCRjZr5R3vtm+y4mCbPkEfQJumkIq/cqEJ61o5Hoop4QP2ZVN0trcO2d57BCi1PjWdj0FKhixsqV6NF49cYdJ9RR0VaJx6n663WimhqTr2cOH7GMUieBVLINphz0FqbPRbRuh197Zx27fe3Zt9mg0SRSYpsnGhvX00g369u4Lbjelgd4osoKmRmmJtsSTDTuDvKoPGRp4YzPktihwegoMDUPyoKBmN47tajGtrdDSBBIYjovSDh8KuAOxnALduocMPbmqSjyfwJFgbBtvufJF7HEZmnWt2tdtpkVTREFbuMXRm8MhClQVsD0FnS8K7HElhQ/FPAURQO0VM5TzyimInUfnbLjkOI6pngK76EGG0CFwhA9pUcCXn6egUNvMNAvLKQB0f6wscVRPE9elnlKaI83JeUb2eVT87ccLSwoGBhEtaImCfHIKHKLAZYsCPYcosK83tQnolTt0CHpkA7OCpyzPO+88Ro8ezbJly/juu+9Yu3Zt/Oe7774raF3Dhw9HkqS0n8suuwywHuBz5sxh0KBB+P1+Jk+ezOeff560jkgkwhVXXEHfvn0pKSnh5JNPZtOmTYXulmAnIhjVCXhcSJJEZ+TrbqgLoumdV71ifV2QEX3TH1i9Am6aQl1cjaWnk+uh7PgyNEwj7ibO6imQpOwhRLk8BS4l1lTHtGb+ipls7MwngG4VBbrejqfANmwc4UNm6zqrtGJHSd3P4EayPhScRk+sZ0JqCNH24HaioVYUWaGPvwLcbiS3mxJPCZJuUB8qYgiRLUocOK89q8JJhupDcU+BnBi/01NgaOgxw9zMFUZjG3KtVsKk4TBIbWHsd/sxJQWTWLhM6uy/sxypTT7hQ06jXc3tLUgtqxp0igL7uDgrEAHbWzYmypd2EhnDh1pakDWrt4VWEvMG5pNTkClu3nQcR2f1IV1LSwxPJdlTQOfkFIRC1nhkOZ4v0B6az9oPT4aw34zFB2zxmCtEx0ZSiGpRMLXc5Ugh8Ux3PKvs6kOGHkp6hmTyFChaq3X+cyUZO9ffg8KHChYFa9euZf78+Rx22GEMHz6cYcOGJf0UwqpVq6iuro7/LF68GIAzzjgDgPnz5/P73/+e++67j1WrVlFVVcXUqVNpaUm00b766qt5/vnnefLJJ3n33XdpbW1lxowZwmOxC1PXGqWiNFbz3C0TVot7Lhd/uZXtrZ1nnK9cV8/Bw9Mf5r39Hhp38d4LOx15hg8F1WDcg6MZWrI3x/7C9sVqjoe2pK8rl6cAzRIGYOUVFDOngC4WBfZ+pooftzs9pyAaTYiI1ERj2YNiRHA1f2ElnHZ4PLH99FZaBpUehsj2zMvaoThOIyZFFGxq3oSsalQEKpA9sfG6XJR5ypCLLQo++wwWLYKmpsTumCmegkzVh2xRICvW+86u0V4vuqknDHwjmr3SWVwUpIcP2Z4Cn8uHLMmWt8DIUIHI2c3YJp/wIacHo50QorTwoXALYMTC1hyeAgDJS3OkmW9qP+bjrR/nXO+OkjHRuKkNRTJRy0vR7XszQ/hQS6SF7UHHdZrap8D6oPVL0pLvt3C9JYoUb9ZQOUNyegronJKkTi9BniF1BYuCuKcgD1EguwhpYSTTyB06BBnDh9xuy7NjpCTVO0WBS3YhAW49ZN2ru2H4UMGi4LjjjuPjj4tzM/br14+qqqr4z0svvcTIkSOZNGkSpmlyzz33cOONNzJz5kzGjx/PI488QjAYZMGCBQA0NTXx4IMPctdddzFlyhQOOOAAHn/8cT799FNef/31ooxR0PVsb4vQt8T64jlgSB8+2thY1PVva4lQ39Z5oqA1rFHmS3fn9g64hSgoNnmGD6XOKiYlN9p/B4ZYvzNVIcpmLINlSNmiIJqjCVRHcJYjhUSisalnFR+bmjfx3w3/7Vg8fxZPgaHIVlifpiVc7LaXwOOxlreNI9PEY0jIRtQyPo1oohqITXNzfkaKHX7kCiRyPYJZ6p07z5HDa2GjGRrVrdVIqkY/f7/EMi4XZd4yJE2nPljX/pjypaHBmpFsSFQ1SsopcHoKUsOH3K6EAdnSkpjZdFtJwYZs9ypQs5cltZONbU8B6Z4Ct2yVjTQld+YKRM5uxjbtVR8y9GTRmqcosMNNgpFWa39lKXF/OzwFrWoriqESjLafr7AjZPQUNLUiY6L2Kk14ODKED63cvJLlG5cnkmpTS5JaH7R+yXry/RaKeday5BNYKMkN07KIgqAaZPmWlVS3VBfuKSgkyTiG6rX2zx1OfzYVw1MQ0cJIGLlDhyCzKFA8GLI7Tfw6RYEkSXjRkUwdzTDA1U4uRQ8MHyo4p+Dvf/875557Lp999hnjx4/HnRLLdvLJJ3doINFolMcff5xrr70WSZL47rvvqKmpYdq0afFlvF4vkyZNYtmyZVx88cV88MEHqKqatMygQYMYP348y5YtY/r06Rm3FYlEiDi+LJqbrZkUVVVRcyULCYqOfbydx722Mci4QeWoqsqelT6eWLmNg4YUL863LaKyrTmI2q9IyaAOTNNEN/SM11GJG+paQ0W7xgzDxNAzb6s7yHQuOx3dQNI1TDWcnuhnGEixmdimtgY0R/nGYDiI3+0H00SKGc+mVIokeUFrw2zdBH5HwnEkYq3LMDBTtxNpRVIkJEPHDIcxo8HcSYeFEA0j6Rrgjm9XMiUwVMxwi1WdJIU129fQEG5gU+MmhvYaWtj2wmFrP00z6Xyqho5u6BiRCIZmoEoqtLRYywYCibFJEqgqSljD0MJE1AiarmFGWhNf/LW1SCtXYg4bBhMmtLP/Ldb5NRTwVSHpa6B1I2bJ3ulVWUIhJE2j1YzgMsrxaRpma2v8XGxo2kBEjVChK/gUL5osW+M2TbyyF8MwaG1rojnYbF0bO4gUDIKmYTY3x8cQioTi12E41IYWuz5N00xcM6p1ziW3B1PTMOvqrOPsdmPqOqFICNWQ0A0dUwsTjoTj4VpJeDzW55qb0LUABu74OQ1Hw9Z50U0kQyJqSkTUCO5IGyiOazfaFjv+UmJ8umRdk9G29HsBQGuNXbMxwo2Zl7Pfjo2lzFNGS7SF1mAbqhZBxsTQrWRxyTStY6matESC6IZOONSQ/KwJheCrr2D06IIM2fbGZegGmhEGTKT6JtBdhEp8hKPh+PYlTYNgEFNVMU2T5rBlU7SF21A8ElJsRt/UzUR4oSojxwSUoWlIhmEZ+q21IGmYclnG54iqqhjI6KGolY+gaZh2Un0K1U3VtOlhtre10Tec4RmZi8ZGJE3D9Hjy/lzIZV2XcjCCGo0meRgkU0LTNYKRYOK4RZpB1zBNV/vb0A3aIm0YmoFH8uT8npHUiLVeLXFcTN0kasq4dY1IuBk5VgyiNdyKpmsopoLa2Ig72mZdX6YHt6YDOcSUbmb//smDrvrOLGT9BYuCZcuW8e677/Lqq6+mvbcjicb/+te/aGxsZNasWQDU1NQAMMBuIx5jwIABrF+/Pr6Mx+OhT58+acvYn8/EvHnzmDt3btrrixYtItBeK29Bp2CHjgEs3yrR2s+MV+X7rFrilfrPirat7Zsk3qxbS+Pq4ics1IZge1jilYbP094zTVi1VcJXXRxPW1SHr7ZLvFJXvGNTDJznsrMpN9bhN2pplatpk1cnv2kYDHj/fQDeb1tHtZFw50e+iuBX/EimTn/9AwC2KialZjUlxhYi0rc0KqPiy/u3bqV8/XoiFRU0bk8OX/EZ2xj87RpczUGCWgtNG5tpltcWZf/cZgsV+pfoko/tiiVeKvVPcZkhGpQWolJ6zOsnLZ8QNsJUe6sZ7MtQSSkH/tpaytetI9KnT3w/Fy9ejOfbr9i+cQ0Nbc2Ew9az379tG+Vr1xLp3ZvG2Kxi308/RQmFqGmu42vpI+qlbagbVeqVNlTJEjClmzdTsnkz6urV1G/MMusfo7e+Bq9ZT4u8jaA8gEr9c1xmiGa5lpCc3OnV3dyM/4sP+ZattPQuY8i2EPK3I2DNviiSwldtX9GsNTO2tYT3N7dZ425sBGDA/z5iQ2gDn3s16lc3U+mpLOi4ZaL/++8jGQbhtWtpWmtdD+tC66iN1gLQS/fgXhMFWWarY6bYZ2ynl/EdvjX1hIP1BDdtIlBTg+73s13X2RjeSGvkawZLNQRNP7UbXsaXIZFXCYfp+8knlLGRFnMIhjImfm/+r/l/aKZG5KsIa0NrKdfXoPlqMN0hgnJVfB1lxnoCxlba5C20ylZvB8UM0Vf/FBMXta70nAaP2Ugf/WtAAkwMycs2JbsHpiZSw4bwBircFTSoDXjbQlRtaMDvCVP9zn9plTfQ++uv8TY20lxXx1bfp2C2ssEMEl3jjle5Kd20iZItW6x7dK+9CjtZGdgc3szmyGY2utdheLYjaTq9Pv6ODZqf92jk2y2tfOf/DndzMxVffYXu87G9qQnVUPmw5UMAgl8GKVe89NOt/7cqUtxQDjRuYciaNWiBar595RX6/+9/SJqG1GZg+mXqlCCa9FXGsQVQ+PjD/+H/vJ5WdwO1WboNb4lsIfLdF9TVtrEtXEbL2vyfS32+/hpP7JiH1q3L6zO14Rq8366hVC5l7QsvYHgSHqYmrYnVbasJKAHqS60wvX76R8hmlHoliCrlnpUPGFtpCX1CtQbu70pZ682+L5X6Z7jMYNIz0jRNaprXUCIFqa9+GU2xrvP3m9/HMHR8i76lz7YGtpVtIDw4wraNfsxPcu9vibGFUmMTIWk9zcr6fA5RRjr7OzMYzD8xv2BRcOWVV/LjH/+Ym266Kc1g3xEefPBBjj/+eAYNGpT0emoGez4l49pbZvbs2Vx77bXx/5ubmxkyZAjTpk2jvLzzKk8I0lFVlcWLFzN16tS416lhxQa+f1hihrNhxQamHLRH0Up5blu+Hpcic8KhQ4qyPicvfFzNKaP60juQuRpEw4oNnHBYgbO3WWgOqUirt3HC/oPaX7gLyHQuO52mz5Ha1mKWjoTysWlvS7EqNMa4XmzVE7HdR+5xJH38fUAPI221nhXmoBmgNiNtexskGXPAtEQIx3ffIX3xBebgwXDAAckbaV2D5GlEqqnHHD0Ec8yB0OfA4uxfZDtSXQm4yjD7T7L2qa4SItswe++XCHlyIH8roxkaQ8qHsN+A/Qrb3tq1SH37Yg4ejDp+fPx8hgZV8vXKJvThwzhs2gnWsqtXI1VWYg4ZAvtZ25H69IG6OvT99yPQGKEsXM4BVQcgVx4K/oHW5z78EGngQCgpwTz22JzDkbb/F6INmH0Osj7fujdS8xfg6YPZ98jkhbdupVZqQzErCVX1pfzr9YT7Bmjd282AkgEYLVa40lRjBL5v1mLusQfsv7+1HUWh//Z++Pbpx5BBYxnff3xhxy0VXbdmfgEqKjAnTrR2vebDePO88ggc3BvweDAd3m7a1iE1VUBJA4T6QN++sH17fD2f1H5CTV05FW1fock+xu0zJXPFJMNA8nqRGtxoY0fz+tcwdepUXC4XxprYsRgxlY+3fkyozs/4QAmV/Q+Hckd1p4b/IYW2YJaPg9I9Y+uNItXEEskH/r9EvkvS+Mut8JdYaU1z4PSkUA4nX9d9zdf1XzOkfAj1oXqi22oY5d1Aid9g1KTJUDYGqqqQtmxBHzeW95rr8WiN9PMP54jRxxGI1Z/nk0+QNmwAl8s6nlkM5Xz5cvuXfNvwLXuWDWIfYwvUNSG1ypT4K2nbf0+G9hrKvv33tTxmpaXx89gabUVZb+3r4YMPp6/Hj1SrgOSyjpfN5g3I2kbMXqWMOf7/IXk80NYAYwzoVY5ZNT392GI9Z9/9zwL222c8LqMWs+94zClTMu7D59s+Z1upQZ/1tex36ETYd9+891/y+SzvxxFHUO21PB0DSwfm/Mya+jXUtdXQn1JGHHMMVCRCoJrCTZRtLMPn8jFlxBQwDaRq6zo0B0xNzlvJRHAjX3xdSwVuRo06kf4l/bMuKtX6LY9v34lJYVjLPl2HJ1LLPnsegr9iAqquYqzR6LV6HUeVDUceNpJ+W1uoHVnCHkMnUzXg8NxjaluL1PQ5pn9Qh575XfWdaUfD5EPBoqCuro5rrrmmqIJg/fr1vP766zz33HPx16qqLBVXU1PDwIGJC7G2tja+7aqqKqLRKA0NDUnegtraWibGHsKZ8Hq9GRusud3urjNmBEk4j72iKEnnYf9hlazeFuTAoZkrMRS8LZcLSaJTznVb1KBfr+zeJlfKvu0IRtgg4PPsdNdsl95Hbp/V9VSRM5fl8/lAVVHVEC6343GnxM6/FI11TXXFupNWgreXVQ9frwdvbKZdlq24Xa83fTuyCV4fuHyWp1kycpcILARdscbn9iTW6S0FrQEkPW07hmmABC7FhYZW+Hmw99OT2J7b7SbkdaPICm7Jcf3qurVseXliHCUl0NSEywS/4kKRFQzJwCs7xhqNWp+LhcTkRNKt/feWWsuWD4fgN6C3ABFwO2YXZRkdHdnlZmC/4VTWmlRLYVol2Brciktx0a+kH6XNHmv7gUBi+z4fvQK9cCPRrDbv+PWraYk4b0evBEmWcCnW65IRweXyWknRzu0pkrXPpaWguqywGJfLOrZuN5IsIbm8KLKCJJnIipx9vGVl0GhgqhoGPms5mfgYAr4Afq+fiMsHErjllGtXMpKPP4DpsvoHmCYoZiIZOP4Z1fqMvy+YYSv3QIpmTdqUFRmX4sLv8VNOOU1SLRoqisuH4o6V2/R6weUipIUwXT4UQ8Er6Ziymbzv9jFvabHE1A5gj8vnduHSXNAaBlnBVdELl+JClmPHPRCwtmualiDRzPjxlRUZt0LsGZVSOtTltV73uK28Aq8XWkOA3zp2nuxGsomMgoQikfmZFMOQDGS3G1MycctZnpEZPxgLu3G5UMtK+GTz+0hIDO412MqxyIKkWKVwvaoXd0qPkBJKcCkuDAzruGlt1v5LCvgyeAm+/RZ69UqcR7cPDQ2X7LHu1Vz7IsfuIXfyMXd7y1DUOpAiuN1uwmobfb9cR6C+Bc9gL0gSPi2KJ+hF95S2/xywv39kaYee+Z39nVnIuguW0jNnzmTJkiWFfiwnDz30EP379+fEE0+MvzZixAiqqqqS3CrRaJS33norbvAfdNBBuN3upGWqq6v57LPPcooCwc5NalDPPoPK+XxzU8ZlC0U3TOTO603UpUQ0HY+ymzdCiycaZ0n0UhRM0yQUscJb7FnFeMJnhoQ0/DHPi7MKUa6SpHoEPLEvfVXtpJKkju3aycZGegUiZxJfSO1A19csicZa7F+P4bh5nOVIbZIqEFnLaoaWSFgFq8suWKJCy3LebOyEVTs8RvEmqkSldjjWNKJaFNOlUF7ej8Hlgzm4cgITh0xkSK8hlHnLGF05OhH76whtcFYgaom2pJetLRRnecpwOJ4o7EwKNuxykqlf2Pa2vSkVlGLj1Q093p1YNjUrYTkbfq+17WAknmhs75ssyciSjFt2Y2TrapypJKkkJRJmMyUbO5NHbdGmtqQvZy8eG49LdlHitkrDRvWoJfRTEo1bQ03osc7KshFJTqZ3xk1vzdKZvADsRGK3fck3xRJve1thcPFz6UiwR9OS7kHDNDKXIwXr+pc9VpUpPWTdc2osqTxnkjGYkhIrf5w+MeAkokUwZQnTNDH0Aq7pYDAuclplq1qbYRrxqlXZ0AwN3W8JVlJCVuxEY8M0YpW3ciQZ19fDF19YFbxiRE0rr0kyjYR3KBuZnuuAHOskratW3pe27F282xtxu71wyCHQtw8KBu6GNiJSO54LSCQa96CSpAV7CkaPHs3s2bN59913mTBhQpoCufLKKwtan2EYPPTQQ5x77rm4HBn0kiRx9dVXc+uttzJq1ChGjRrFrbfeSiAQ4JxzzgGgV69eXHDBBVx33XVUVlZSUVHB9ddfz4QJE5iSxZ0m2PVwKzKaUZz4/4ZglIoSL3VtO9hUaSdAdEfGUSc6Sy6Tolhf0pqOLMmUecsIqsGE0ZfaaRQgMAhavkluZJarJKkRsarFKL5Y9aFiigJ7vxzbzVGW1GkkxSufFEIW8aMplmXkchYMyiUKIhG8Lslq8qSriWofmpZcJjQSyV5O0VAdTawc2wgMgVANBDdZIWN2qKiuEzWimLIHb6Ac2AyRCJWBSioDjhyB6LfW7xRR4FE8BCSDRtOkIdRAv5IdaJroFAWmae2nz5ckNkxVxTAN5NT9tw0MbwBwGFaxY6sZGqbkwkRCwkTP1avAH/t+DqlxA8k27OwqUm7FjSG70M1QBlGQofoQWOLMiFpiL9Um1WKVvpSAVb3F7kSdBacocCtuJMNA1UIg90kTBW2hZvTYcVCMSHIlm1RRsM8+WbeZD/HmZWasKWGjJQqk8hLATFQfsr1rmgbRaNKYdFNPzHKligJNi5UdlS0DWVGsSk16RdamZTYmMugqoOcsRxrRI/FmdFo0gifrkik4Kg+1RBOCTtXVnP0BNEPD8LiRJTmtHLAiKyiy1Rk9qkdx5SpHaoe7OO6jUCxZ26u4rPXnwr6HUppQKkrA6snR1gjLlqFtr8VwK0QOORAGDICmzSiSgtSoojobR2ajB/Yp6FD1odLSUt566y3eeuutpPckSSpYFLz++uts2LCB888/P+29G264gVAoxKWXXkpDQwOHHXYYixYtoqwsUXHj7rvvxuVyceaZZxIKhTjuuON4+OGHUXK1/RbscsiShG6YKDs4zb+tJULfUk+niYI8yzkXhaguREHcaEgteWmjKIS1MJJuEnAH4jX2412NM80oucut+uBam9XILDA4e1MvsIwjt8vqyqk2FFkUpPQpgJyiwGmQaIaGqqvJHYjbI4v4UWP/unSHOG9HFHjcWKLAUBNjTU14i0SyV4qxP+Pspgvg628ZqXrEEm7+mOcgNktruvz4Snol9scZygMJQyND2EkfVxmNqNSH6jOLgupqK1yqveo2qY2sQqE0USCpGoZhhXckYRsYPh9JoiAmYjRDA0nClF1Ihoqh5RIFMTMwnDBwnOVI7d/xPgWpHagzeQqc/2fyFNgixRVIlHTMUZbUWfrT5/KBYRDVIhk9BW3hZnTZiyRJuHKJgrY268c+T6ZZ8MPZHpdLMiEYtmbmZQm5zAfBUHIpWLc7IQpMhygwdKvTOSRPPEDMU+AFhdgx063jrxtZm5bZGMgxT4GRWxRoEeSYN1nTChAFjh4FrY7Sr/l4CgxFtpK/MxSd8SgeQkaIqB4lYF+3rgyVvuxeVA5PYjA24eFT2jFb7UaSkO4pcAWsaIGVH0GvQ4m6JBoOGMvAfrFnSG8PsiwjtZlooTySc3tgn4KCRcHaArLX82HatGlZm69IksScOXOYM2dO1s/7fD7uvfde7r333qKOS7BzMXZgOV9WNzN+cDsdBtthW0uEPfr4Wb01uzu7ozSHVUo8Bd9SHUZ4Cmj/oexyxUSB1bXW7sabCB/KPKOEP+YtCG2xREGuPgV6rE+BEnPpG2qHjJDMZBIFsS/RdkQBWN6CgkRBFvETla3X3Xb4kGEkDF+nKHD0B/DE5m5U3SEK2lJmjCM5xLltoKYmIEoyBPaA1u+sngUxUWBqGlFdxZRl/P4y63zoero3Ikv4EEBvdynQkLmJWUMDvP++lTx55JHp7+far1AI+vRJ6t4razq6qePKFj7kCwCOcTg8BQCy4gNDxcgQRpb4TGy/wxp2E9yMngLJld6nwL6OIf0cZBMFhpoQxYpDFBQYPqTqEesajDftc3gKlIGUekppibQQVZ2dkxMN3ohELG/BnntC82poXQv9j87aDCwT8eZlmInQofIS7IjNpE7MHo91jlWVqJTqKUjvrmvtuGYdR0W3RIER24Zcku5VSMFEscSDkd1TYJomUT2KV7ZFQQH9U2xPQWkprdFE6K6aK1SNmBdLka3woWyiQLVEQc7GZbYo0PX4szQU27Y39Tim4vwuSBEFiitg5Ya0qtDXTcM+49DU2oT3QwmjlJWiq2DWboX2+vH2wD4Fu7lFIdjZMAyTTKbUfkN6FaWJ2fbWCP3K8ogV7AAb6oIM75s71rGYRVCjmiFyCtoTBYpCWIsgGVYXTNsQyplTAFYIESRCiHI2L4taryu+xHLF8hZkGl+8o2wkYbTFiKTM9IZyzSJnIltOgR0+ZHsKbC+Bs2kZJHsKYqLIamAWG1cmT0HWsdjbyBCuUGI3mkvEjkejITBNTJeCV/EmjSUJW8x4PNS21cZjpwF6x4zYhnBD+mSVPfZ8yvtl8hSQ3LxM0i1RkGbUmU5R4MDpKSBm4AC6lmM8fuu6kcIpnZQhLpDdstW8zMopcAiBuJfAlV4Fx74GUz0L9lgUrxW2YucUaG1p16qNbVy7ZBcBdwDJMDANDQ0jyVMQ1aNoagRkN6U+K7xGVRsTK7JFweBYcYBaq/QroS3WfkUTTeTyIe7BwIRw7FiU+FFiQj3JU+BoYOY0nJNyCqQM4UOyx5pQ0EOgxwxxV/sVEE1iExBk9xTYEwRmzLuuqwWIgh3wFCArOT0F8bHlyilocYjI2DMp4SloZ5Ij/syU0q5bxRVADqsYehRKSwh5rff9trdCbYa+vS1vVO223NuB9sNXd0EKntY0TZNnnnmGJUuWUFtbi5HSldJZQUiwY7z48RZO2m/nKDfZVTSHVXoF0p2cXpeCqhfYpj0DrRGN0tjsWT7lbQthXV0bh++Zu765LEmouoG7CMZ8VDOylj7dbchDFET0CJLmpcRTEjeI4l9umXIKIBZC5ActBNHG7OFDdty7W7G+9O1hmCrk76zPTqbwIdmqkoFpWsa2I94+1VNQcLJxFvETlSyDLk0U+FIMdtsQD4fwxG6teAKraaZ7CsI5ZrnjScYZRLxih4UY8byPSNhat8fjt+5rr9cy4FMNdFXlm7pvmPviwzz13b/Z9sVJ9P5qLYweTcnxx+M9pIKIS6c50kwvn8MzaYuLSKR9T1DqNmP76UzylTTNMoizeQr8KcZS7NjGw1pcAXRoJ3wo9qzTQbIbJaWGD9meAvseMqLWMc/Uzdgmm6cgdfZXCVjXrhnrcpwhVCQuciQr5twnewCTqKThcoiCoBq0utm6S/DQB1iPHo3FntszygB77AHffQd1daBGE/kMBc7mxj0FpgGqbj0j3C7k2HFK8hQ4KmsleQoM3ZFonCV8SI4l3dqeAiW9IWEqVk5BbJ+zfJfYEwSm7SlQCwiZjd2nRkmA4LYg/kgNIBXFUwDk9hREIsn3j6ZZ598pCnLdf9kmegCXy48e1TEwwaskdTPGUEFrQ+5XgfZdM77t29u/z3MVughvh7a1UHlI9s/vhBQsCq666ir++te/cuyxxzJgwICiGlWCZD5Y37DbiYLtrVEqSzIbUxKWJ0HewbwCSZIo9bpojWiU+YpnVNflGLtN74Cb5pBKZemOeysimoFnd8+dySN8KKKFkYxSStwltKnWl127ngKwQh+0UMy1n6X6kG0UuWMzo/HwmmJ5Cmwh7PjilyTLmNDD1o9DFCRVY6EDycbthA+57BnA9kSBpuIybE+BlhAw9ix7IGD9nVf4UAZPgazEjE3DOgeyi0g0GBtCIHkszm1oGk989BhPfv4Ur4yyTpfr9TdgezN89BHS008zxeul7sC90Y+bAiedCYceGjsIsXNtdx/25LjX7WVLS61QjFAIwzSsmWMsI0RW2/EUuH2JEChI8xS4XCVEACNDGJljh8HnAcOFK3Yc0sKHZDdIEqppX7vRRCIxFCYKUmd/Jcn6W2218gpyiALbc+GXPEgYRE2NQIooQDHo5euFEvuMrsZEge0lkCSrjGVJiWXYbt1E3D9bYDJo3FMgxc634gWXYnkOyO4piLpSw4dyeAoUL7jC1jPGjIk7OR9RYHsKyBrvYT8LzJho0PMNH9K0+P3d6jbB0CgPWZW+1FxeKSzBacpWVaucokALJe7vVE9Ba2vy/7H1BLUIAbC8gKaR+ZkN2Sd6sK75aMTEMPWYKLC+D3wun+UlAOS+AzA81eiRMDQ2Qp8c+R3x6kOmFSK3bRmsewW2vQVtn1ihp9/f0LXJhjtIwaLg8ccf57nnnuOEE07ojPEIHGxqyL8LXU+hrjVCZWnmL9tRA8pYs62V0QPaf2i2R58SDw1talFFAaQ320vbbsBDYzFFwe6eU9BO9QdTlmM5BVYZO3smvd2cAnDE7oeyVx+yv9g8fiAKpmwZ1sUWBWnhG76EKHBg75/f7SekhgoPH8riKdBkUCQJWZYtAymbKFCUWCWWEG4NDMlF1I4a0SMJT0GfPu2LAjt8KJMogFiycTh+rKMR63np8ca8CDFDLRpsIRRusmb9VZUDBh7AU1/+k3P2P4frj7ie0lm9YOFC+M9/4PPPkbdvp9/yj2H5x/Dym/C//1nri0atROMBA6xx5yMKevWKiwLnzLLP5cPQNHQyeAqc16TPlzhmHg+6ocfDmtweKzTHzCUKjKhVljTkRglay2XyFACJ82Qb+nFRkOFZZb9mpJy/TLO/rtKEKCA9eTvuKYhVyQkoVhnVqKkl5RSE1BCSZFDmKcMVO5ZxT4EtCuxj2b8/rF0Lm9eB3dS7o54CYp4C2RPzFBhJ7wOJa0FVk0L4rPCh2Ngyegrc1ky/acTEvjtdPGRCkhIJzFk8BXGvoWyLgjyfSY7rrdWMIDmerbqaPWEcLBEkKTIuyZVTFGj2eZPd6fkTztAhiCcbt6lhSxS4vLHJnCyiIMdEj1t2gwq6YWB65fi58sluaLLKn7p8fYn26YWyrcEKQcspChSoXgS1S6FlNURV+AzLsh4PuHtbYWvtVJPamShYFPTq1Ys999yzM8YiSGFzYwdKCu7i1LVF2bNf5nbnBwztzb8/2lIUUVAR8FAfjDK0sp16x0Wml99NY7A4BqOoPkS7noIolhElG5YosONjc1YfsrENGz3YvqfAEwCi1syRpqfPoHaYHKIAsoqCXt5eligoNHwoi6dA1VVkV+zL3jGTmCYKIJZ0qeLWJQzZRcR2dmiheGw9FRWweXN+noJMRilYxoRDFERiosAX8xS0EGXxF89x/9uvMOG4c7j7/90N0Shj+47loTOeoPL7P0is6wc/gPHjoaqKRkVj4/MP03/VFwyYODWxTFMTXHaZ5eWYPBmOPx6OOw722it9JtApCjZvtkRB7FqTJAmP4iGqG+gZGtAlzXR6vZaR5vGAJKE5as27Y0mzOT0FehQCPgi7UGLHOlNOAYAmyRgYyPZxj3tqdsBTAO1WIIqHQzk8BWFMImY0KacgqAaRZYlevl54NOt4G3YCc6ooGDDAEgU1G2FwzCDrqKcg1n8AuRTcLhR0QE6vPgRpOQW6oVvhQZC5T4Ekx54dxBpglWU0pjMPMHbNZbGNU8OH8vYU2KKgtJTWaGs8XApAz5EwDta15ZLbDx/S1GbL+lTSPUdpokDXiWgRK+RHUiwRa2pkDc/MFT4kuyBiYpoGEZeGqVk5jJ7mz6zSubIbpdc4IpVf46utx9hagzxmTGy9JjR9AVvfgL1+aj2DJckqdhATFEiDoN9Y6LMffP86KNn1Ij0KFgVz5sxh7ty5/OMf/8Dvz3BCBUVB1Y2sVZl6MvVtUfpkiZMPeFyE1B1L6LEPaUWJh29qi1+BqD16B9x8XaTKR6L6EO2KgmCsPKBf8lhlDFOrD+VwNcdDHbQcngJ7plTxWoJBsquCdGKiMWStQGQbAr18vahprSlaorFqqHhcVofinJ4CsAxZQ8MT8xTokmwZC62N1g0oy5axDO2IgvY8BXaH3ZinIBY+1KwFuWHxDby2+M8M29RKYym8/M3L3DntTpRoFEmSqCyvSl6XHcKj65QddCjrS+tY96MZTBs5jbgk+eYb6xw3N8O//239gBXD/r3vwbnnWr+twVi/HftpV39xyS5csgtV1dDdmcKH7HPuSoRApYYOyS7k2PVp5AoRMyKWp0B24YpYxl5q+JB9TxiSG93QkdM8BRmMr3iicaoocPQosIlXIEoXBaZpJiUaA/hlL2HTJGJq8evekCCkhcHtodxbjhK7PiWtzer1kCoKKiutc9XaBM1eKC8pXBTExiWjW0JfcXgKTAkTyxMgS4lkezMSSe9TkO0ZY5fbtBtxKTK4yhL3YLsDjP3OJgpSwoe0fBONnT0KIi1IpobX5bUM8xyeAtuLZSrthw/paiu4PO0nGQNomhU6BrhcXmTk3Im9uTwFihspYoXtRRUVNKhUa5DCWAKt8hBcnj5EK3tbm67+Cs+XX0PD21DzOoRrrBX1Gg9VsXt9wHFWtbq9LoKWCvjkE+t1V+78wp2VgkXBGWecwcKFC+nfvz/Dhw9Pa172P9vVKtghglGdXn43EU3H69p94sYN08SVIwlXLlJsXkWJh/q24tWTD0V1/O72z1PvgKd4ngJRfcghCsyYCz75eIRsURAzbPKuPgQp4UP2rFzKcrYBoHgt4062PQWdmFMACUPZyO4pgA7kFGQLHzI0DFesqkg+osDUUDRQfH6ipjUuV2ustGFJSeJzOcOHcuQUQNps9fq673hn9Ss8uP42avwaA3U4qnwPLj7sR0z98ZyEoIH00B+HKFBkBb/LT1AN0qa2WeEKACNGwIIFljioqYEPP4Tly2HTJnj0UTjgAEsUmKZVDvOzz2D//S0RZBhobZaxY4sCSdfRXSmeAtNInHPZIQpSk4xlF0rs+jRTQ3iSjmHMUyDJKOHM4UOSJOFW3JixXgXuvMKHHMfeTsY0zeQeBTbu7J4C52x7wlPgohGTiJlouNaiWR123cR6GcgukCRkUyOqtuFLFQWyDP36Qf2nsL3REgUF3JPO/A8FE1QNPFZOgSzLSOiYWGVcZSUhCrRIsgi3PAV2+FCGnAIAXynQGmuCVlqApyA2w5UtpyA2QeCNeSJ0Pc9SyUmVh7YgmzqlnlIiWgQ9R7+JePEGRWnXU6CrLeCvzF2O1M6n0XWCMUHjta+rnKIge0ioSzMwTQXDNIgqUQLhLfQyGoEq6HMAeCuRgP7R1eyz/QE8326HWsC27xUf9Ds6ed29x0HpcOtna03i9Wg0cf/uQhQsCmbNmsUHH3zAj370I5Fo3ImEojp79AlQ3xZlYK/dxyPT3tWkyB2v3qPqBq5YacWARyEYLV5t4Q31QYZUtB+KVOJRaI0UZ7uaYeBWdvP7z2nMm3qaKAjGvhgDMVezbXjEv8By5hTY4UMh0GMP92yeAtljGZaSUtzwoVw5BZDkKTBMI27w2VVzdEMvrIFZBk+BaZpWAqGiWMfPKQoyeYtjngKiJt7yMsJqmIgeIRCMlYQMBBJfloZhrS9TCE28akuO8CGIG3sr1v2Xj2s/ITQUjhl2DL8aezFTt5Ygl5aBbdhnalwGCVEQM9RKPCWWKIi2UeGPhZ9EItbnxo2D738f9t7byotYtgzeeAPsPDtNg1Wr4N57Yf58q1b+hAko26tx7dsLpaIUt+K2+hS4jeSxOOPec3gKFFlBztGvIrE+WxQY8fChVE8BxBqYye7kXgXZuhmnvhZPTI4kYuOdYSG2p0APxytF2dj7I0lSvEutz75H0dFNayK8JRaWVGJf9zFRpGtBIuF6fGrsunUeywED4IsIbGuEPQcXlFOQ1E/CjHkKfAp4PMjIyKaKHqvY5MadOD/h5DzA5JKkGXIKANwlQCu43JaYylMUSPZ8QZbvANtTUOKzwm110zKwczU7A+KiwCwpobW1FY+pUeoppS5Yh6m235lacceujRyiwPI4VKZ7CpyVh8rLrd4guh73FHjd+YiCHJ6CiIaJguaW0UJbKA+updxshC3rrOsyVora8FQQ8G/HbJKQpH1gn5Ohagr0PSJ9ksLZq8CZJK0Wb9KxKylYFLz88sv85z//4aijjuqM8QhiBKMaQyr81LXuXqKgvYCpIRUBNtYHs+Yd5MKqDmR9yRZbzK6ra2PfPdpvrFbs7e72olySE7OUpg4kG3ttpvXFaHsKbFFgu7qlnJ6CWMyoaYBqh7JkySlQvJZBIsdi7s1ifSFkEQV27X49MTNpewkkScIre2Jx61FCWmiHRIE9m2u4Y+FDmpbIDcgRPkTEwOOuRNc0IloUWpsBv+UpkGXreKlqwthOGkfMIJUUtoUaaI40M7JiZPxtzdB4/bs32NMlMbpsLwzT4LCBh9DWvJ3ZP76biftMt76ga5ckeyPa8xTYosBdwja2JWq02xWHbOx1BgIwZYr1YxONWusbPhzWrbPKY373HWUvvMB0RaZ137E0/vF2mnUD3dSSjbR4pZrYdV1VZSU377FHfL/BDh+yjr1hRK0mVnLKtWkbpAGr7KWsqhCNpuUUgCUQVMmFZmoZEo0ziAI7KdZQE6Ig3qPAnzwbLbsTJU61VvD0jr+VGjoE4DZAlmVMWSKohSlT3DTHwpJKHD0rZHcZuhZEizaBGnvdeR317WONr1mFiAqeAkSBI/9DNjQrJFByxQoKaLixonfi4iG2XUsUBJLXky3ROO4p6AWRreCvsI5bvp4Ce3faySko8ZcTtseajyiIGbYhr4zRYqBgdYMHMPTWrB9L9M/wWIMzjDTPRFwU2B6HVE+BbVQ7Jw4c4UP5eQpyiIJQBJ+6jXLza3p9tYL+bd8mcib0IAw6HoBI2Rg+2PdaRg4eRe8+w2Hf6Wkels9rP2dbcBtH+WOGtKknl1zeRUVBwdOtQ4YMoby8/eYagh0jGNUZ0ifA9tb8agtvqAvSEt41L8JC2LNvCd9tyz5bkYttLZ3XuGxrc5gBZVnCHASdS468gmDMuPRLyaIA7Pr5OXIKJCkxK2TH5qeFDzmSYV2uWKJxZ1QfSs0pSPcUxEOH1tUg/ec/lEYsiV1QsnGG8CHb+yC53dZsbtCReJ3JPe71WqIoquJxl2LIHstAaYmFDwVSSoZm6lUQ269GNcyKzSv4YtsX1IfqaYu2cd/K+xh972iu+M/1LPx8ARhRwlqY3q4STh93OkeMODp5/Zqj+ZyjcVkStqEU+yIv8VhJvHYJ27S+A7nCnqJROPZY+PvfrTCi226D6dPRhgxG1g3KP/wc+va1dtPQ4amn4JZbLI9DNHau7OuxvBwmTbLEAcmiwOXyY0pSbDY6g2fKfs3lgkBsEqW1NS18yP473tXYvqadgjcT8SZ6seVydajNkmzs7FGQeFG1GqrZZUghLgoCDq+R7LZmwC1RkBI+BODSoCw2lrrGgnIK4pWHJAUisetTUsBj3XcuKaUsqe0pUCNJOQFWyI5tpDrDxMzENVk2FMrHWGEokH9OgdFO+FDMU1DqKcWUpZjga2fd0Wj8WLa4rGVLXd74c9PMUZI0zVMAaQLHFgWyHraWT/UU2KFDZWWJZ1CSpyBWWSyX18fIIgrUVrwvHcje1U8xIPIhvtavkU0dzTsARvwE9jglMU6Xjy1DJ6F6S6zj0ZDe+G5j80ZaIi202WWgDTVJFLS2NrA9uD37OHdSCvYU3HXXXdxwww088MADDB8+vBOGJAAIqXp8Vjwfln+3nb6lXo4bO6CTR9a9DO7tZ8nq2g59dntrhL36F+5hyAcrf3I3n7XvLiQF0LKKgjLAFzOyZMlKgjNMw4qfzuUpAGvWUwuBGrLqxqeFDzlmU+3wIb2Y4UP2+LLlFGjxkIx4uEBzCLwa5dvD1Ff5Cks2zuApsMNNZI/Xmp20v7jd7swdnj0eywCL6vg85RhSA1E9Am0RcFdZngKwjPbW1swGth4hqAb5smEjZskYmsJNzF06lyc+fYK6UB0A+5f2ZlTFKEw9SlgNIRkmHpcXyTbw3e54PD/hELiiCQMvW/hQzIgpjZX7bIt2QBTY73k8VmnMU06BcePYVuHh88gmhn1XR6CXVeZQl4EHH4S33oKbboLSEjh0LBx9EJwyAPbdN+lcOEWBIikYkismCiJAikfZeW2Wxoyv1tbM4UOKG0Nyoxlhh5GfI3zI+bq9nLPyUDQKH31keTgGDbJEQaQuLdk4k9cCXcUtezBkJS7KmrU2eoM1Y63rVty625qcVKONoMYq0jnPq9oK/XpDawS2N8GQwj0FiiRZDdDAEgSKB7SE4fT/2TvveDvu6tp/p596e9NV71azJfcqN2xTTS+mhQCGwAsEwiMJSXgBQiCUGEKSB7xAKCE0U0IzAffeJMuSrN67bi+nTn9//GbmzDn3nFtkGWys/fnoI+neOXOmz157rb12xBSoosfB8Rxk24FEQvQlxIsDVfsYdy7SIbEMCicm/q5ReB5+OFeiwaMrLBJk9Az9iowb6PMnjTCpTSTIByxkWtUroMC18F0LqY4jVXQuNQMoVvYlxkzIkoyGkGQ5noNa6z4UBwUh0HMcSpLYFkNLgW9OfNZ7nihWZDJignXf3ZDfJ9ycLv2OWEbLIEk9OHKZfMtcxnsvYG/LFSxb+DLmNM+tWl04u8Nqa4Ecwpq0rWIrart2BK4dzwcJ3Pw4+wZ28eSJTWzq28SP7t7Ja178YT79gk9PcsCffTFjUPDmN7+ZYrHI4sWLSaVSExqNh4eHT9vGPZ+jaLnMa0ux8+T4tJYv2x6HpwkgnsshyxKnaso0kDOnnDj8u4gz0OE0h6QC5oTqkemY2EFFLyFVJ0CmY2J7NslIrtEIFKSAYQEMtNY68qGY+1DEFFjPfKOxHDQ1e47YBlmNkgDdF8umx0vQk5hZs3EdUBBVAENQEFL8jdznop4CR4ACWce0TJGctVINCqBugl02R9k1tAtbznLr9lv5wbYfRPu3qHURf37xn/P2s24gOb4DfIdSSSQTuqJXyyMMQ0idBneCcgLGA3/zRkyB54EnpuaCYAp830eaKVMAle8IjpNXLFCa10VuxTqagsPsKBK85S2iKfbuu8UU3rs2iD8f/6roR9i7N5IuVIECWQkcg6z6IDSW1PvBMffyOfxEMOeglimQ1UpPgefEGp6nAAX1mILDhwVLYpoCFDRoNo6S77j0yXVE47MiU7AKlJ0yJg5IEkktGYEC1WgRi9vj9ZkCpwDtLXA0D0NjE52SJolI1gQQ9p7piYjBmcAUSBJoGrZnI9sORjZJwSrgh8dGUqqBfTw5D58pscr4VCG5MblYnUeX7dpRo3RaS+PLMk6cMWsU4b0d2JECpBUdJVbwcuwcmjLxPVoF8GJNwrWRCI6djRT1j0QRBwVjgln0HYcSAShQU2DXgAJrDO77Fmz5LXTvAmlv5XeyARf+e8VJbs0/sVl5jJEl8zB7Z+H5Hglt4nMsBMxme7NgOPv7RQ9REGGhxXZtfrX3Lk70P85vdmwmvbtyfUvtsGNwx4R1P9tjxqDgi1/84jOwGWeiNkqWQ0pXpp1AShJTC/Kf5WG7XtXD53RH2XFJ6s8fJ6fnTTSQDxXsAr4io6s6sle5OVRZxcQUL7HwM/UajUEwBa5bSSjiTIHvV1djNS02p+AZHl4Ggi3w8gKwqOkoadYCUJDIl5Ec97TJhxQ9IQqAsWpi3Qjch7AcEkYTrqRiF4tChO27FTDRwIHIdm02H38UybVJpFpY1r4My7U4q+MsPnHVJ3jVileJJLIcMIaeRTmoKGuqXn2OQlBQHIEsUBoHWhuDAgDHIaklkSQJ13MxXZNEuI3JpFjfqYCCUhFoRpEUtOAw2zLwjneIP54Hj94Bv/4BPLwDHtkKq1ZVaZlnvfj1aN1Z/KuvQnvp6wOmoFwBAPGIuwdlRFLujI9CQmjl44m4YApUMX06DjIkufG9EQ0wC5aNMwX9h8S/wwnWU8iHqpgCx0ZXBEgp2kXGzXGQJBJ6ssrqUtWDZvqGoCAPzWlItsLYOIyMwuxpuO8Qc3mSghkFoe1oAKTUcKqx58LAgJDE6TqO5yDZDklVgALPtQClcT9B/LqbASiQPQ+Qg8FnE5cP+wlUWSWhJoQtqe/j2ObkSV+V85BI0NOajoyLLMt4nodtj6Elng4oEM80u96QtjgoCACKWS7gpYX1q6GmwOyv3ueH3gQP/kpU9D2gV4LsEui6Gua/rvrYe1lUWcdNGlXTxWsjBMzlliwwJgBKuUxedtg3vI+ejJDzKbLCv2/6Bi3eGBQgpSU5p/sc1vasZfXFNzLv0hfVPczP5pgxKPijP/qjZ2I7zkRNFK2ZJ7CqIj+nvetHihbt6UmmhD5Lw3TcU3JDOhOnKRqAgqJdxJdlEkqi8hKG6lkF3hRMgZoS2l2vDijw7Mrgi1A+dNotSSeRN8kJIB+xFWEioAelQ0PW0UbHKTVNExT4fmx/YkyBH2MK4jEZKAgAV1LNgqTgFC1cX0XRlcq6a5gCz/f4xa5f8Hf3/B039Z7F9b0rWTHrAubMuQEZmfN7z+f6JdfH9j94Vvg25cCDX9drqn7RdxQhK4NVFqRLrXxIkiqJjOMg6zopLUXBKpC38iTCRD+bFaCgkWsSNAQFfgAKVFlFDewknfhjQ5bh7LNg7ivg/e+C5nMhzrwfPEjykQ3MBfjZ3fCBv+P8OR3kzpuL//I2pJfcJORKYUQ9AXoECtzcGHTJVSwBVHoKPN8VQDSaNzBJD1bEFITyoeAzvlbZbssS914ECgpVzaeN5UMaKCoFuyBAAZAKXHRqQYFjlyC0Aq0FBZIE7bNg7BCUrcChbOq0p4opcNygn6ACCpTAAMD1Xfjo38H/+38wezZtPe0sOXsR8mWXU5ybwe9tAtL1B5dBNfMY3hfTZQokRXy+DigICwSGaqDIClIAAO2pQEGMKchZxwFIKRp4Loqk4mHhWPXn7EwABQ32JYGHBVi158GyKvdOJhMBprKZo5m99Ba3Ix3cBsMb4erfQDYwHui5FozNkF0Dy66C8y8Q575lFWRqBu2WSiiSgmtU8oy6oCBgCsqqz07nJFt33c+tez7Ffxc20pHq4IE/fgAQcqgXL38ZCxSXdcvOYam/HEXVxPMh2TNhvc+FmBYoKBQKpEPK9xlY/kxMjKLlktKUGRX/18xu5qnjY5w7b5Kx3M/iGMpbtKWnbgTOGCrjZZumxDQdVRqELEk4rjfpXITpxNGREnPbnj8OUc+6aMQUWAV8VcHQjKqXU5gQ2Y5VPSiqXijJYBiZGTiuxEFBCBQ0UUmM9xSEyVW9Cv+MYgqmACIHoogp8ETCpSs6+sgI5d5pyofiTYiKEv2/iikgBnYagQJVEX6JPmhe4Mlv+Tieg5KokfYAVn6c72z6Dz7/0Ocjun2R28efrnkFCaOFrkQXa7rXYLpmtb1qzJLULAegwKhpXIyamQtAVoCCBBOZAhDnLwAFIGQXBatAwSrQESYriYRYznHquybBRFAQHCfPMpEcV4CC4FDbtVgvbpGracJWM4xZs9j/o3/HueN25m7cTeKJrSSPDpI8Ogg/2wTv3Q3/9m9iWceB4UEBgOQYKMiPg9eEpteAAkUDScEOr4Gwot9IOgSVSceeJa71sOl9pEiVxrNUEt8vycFypajBtD4oEPIhT1Up2SXGykJGkjQCYBFso6GmcGUNx7OhPA6olcq771dAit4UuPp4wfGdBiiImALEjAJZCZjAOkzB4cPi+44eJXP0KEs2bIb/+CmLACeVgE3fhpYWseIDB8S/w+NTjymYRqOx5LqCJVDkug3UYX+REYA6WdWBomiEniwCZsc0VOy8uNcTsiIeQ1oW3KGGU43DcykAXWNQYOAKUFB7HkKWIJUC8yQc/j5su40sW1g/r8ZcZPBR6L5K/Hv5n8FFawWgSaVBTQeAsGb9tg22jSIruElxXMKZIbVxz8F7+Pbmb7Olbwuzjo6xZBgONYPdI0DEkfEj0bKvXXUTS1QXdoxBWRHmAKOjz1n3oWmBgiVLlvC+972Pt73tbfT29tZdxvd97rjjDm655RbWr1/PRz7ykdO6oc+3mGqIV71Y1dvE9x8/8pwGBbNapnbwWdQpHIjWzm15Wt/XktIYK9m0Z56eI9GhoQJLOrPTXl7IEvxnVCr1vIrJ5EMhUxCzx6swBdbEddSGkgycQqzJZxRADBQEL3XPajx4a7oxlXwIItlGmAhoQf+BrugYI+OMTFc+FE9GwgZdKo3G0wYFngWaKrTYlktKSyGVfWzPwYiBgjG/zO3bf8R3D/2Sn3aLynJKS/GiJS/iM2teJHT9shFJIMpOmbyVpzUZPN9C+YHnUDZzqICuNwIFRfAzYJkCFNRL5lVVJPoBKMjoGfoL/aLZ1Yq5LRlGBRRk6hgXhKAg/G5VJPiu5yKXTdEPEAA4R5ZEz0IoafEmAamGwdil53F0dTdK50oWKR08+e2/puehjXRtGUK+9trKso88IlyL1iyGa65Cuu6VSK6L57ooJRM1Vf2OCIGyE/auhInfZKAglA+5VsUaV1JEU288ikXBsKgZsMdFwhaAgiqXnzBcRwBJWTRRDxQHgIAp8IjOj67ouHIiAAV5UFsqQMwtVUC5ngLkANw7DRtz41FhCnzBFBCAtIgpiPUU3Hab6J/46U85efcv8UaGaO/Po+7Yhd2UQk0lKgD25pvFTIveXvFn2TLx2TVrItvZaTMFasAU1HHiiVjDALgpmi4O3VSgIDi2hWDoY0pLRfsqac1QbgwKwuLBVEyBgUsOMOMnonQSBo+Jf2ezMPAgbPsoDILSBLacoth2Ic3dl0KiF7quiB0MucIEFwrgBNdA7TM9sFGWjUS0fQk1QcEqcO+he7l6wdWiZwXYeHwj9x++H4DupgwXJ1fxjqWXseY172Vx22I2HN8QMVh2CPDyeVCbobX1Dx8U3HPPPfzt3/4tH//4x1m7di3nn38+vb29JBIJRkZG2L59Ow8//DCapvGRj3yEd73rXc/0dp+JWPjBRakpMq47dZXh2RpDBZM1s6f2+l/UmeHOHX1PGxSIqcbW0wYFx0bLrF/aOe3lm5Ia4yWb1uegVOpZGXIDUGCJnoKIHg6cMCJQEB/6NBkoCCv/Ug1vF+q4Q4mFpgUVyeD3nn36QEE930E9SOxMYXtnuRZ4HmpwPDRFQ80X8U0Ty7WiBKFhhC9wSarSXUdMgZFACHeDmAwU6JrAD5Yl9Pmmh+PakKjsx/+6888Z2/xLTAVmL5nNq1a8isvmXsa5s85lsbmv6vhljSxlp0zOylVAQUySYZXGUQGjlikIk8RyMZB1OdU/j0edAWYQOBCZcuVzhiGSj0Z9BfVsT5NJXN9DMS0UWUELcaMqCxeskP2IGt/rv5rjlXWpuZnhqy/EurCNlvkvINFzZWXBDRsEqNu8BzbvQf3Cv3OBouAsW8yyS1YxdvNbYH5l8fD7rbCLLWIKpikfquon6K/sv2VV+gq0GCiga8L+iP33wXWQkNANcfzD6y+dyELRjK7TEBTYdgGsABRE5zDYfjUdyPoC5muatqQRUyA2oDJXo15PAQhGZ/16+tRBhme1svLK1/D4oYdpPr6bS30hvQGi5lmOHxd/NmwQU7IBZs2Cr361ch8+8YT4WU/PhD4I2XUDdrK+fChiCoKhfaqiYQG2Mz1QkA8mpWeNLHgCsEvBfAm3xkEq+ug05UM6DrJnog89CgO/hJN3wNg2SPwpaNcLUNB9DXReDNJiDrcvYMva81neuYpmXYax7RP3Of49+bwA/g1AAckk+4b3senkJp4aeIqtfVuxPZvfvPk3XL9YyBNfftbLGS2Pcum8S/mTs96Cdu/94hpoWShWFSu02L4wJ6BUFH1LISv0hwwKli9fzq233srRo0e59dZbue+++3jooYcolUp0dHSwbt06/v3f/50Xv/jFyLXVtDPxtKOqklQnRoo2rSl92ss/W2OsZNOUnPqSbE5q5MrTt5drFCEoeLrheTNjdVqSGqNnQMHpi0mYAhQlejEKbbMaJUBOmNRLSuPmQ1mhMhCt5iEfb+SEGP0fXAuno69gsp4Co0Nst1MAp4DlWkiOG1V95WwTmqKhj4xTsktTg4I6zkNQ6SlQ9RoQ0AgUuBYYGpR8ME2SRhLb9DmZ78P1RwlbFN95yf/iR49t4ZUrX80V7/k09x2+n5Jdoj3ZCqXg2IWgQM8yUBggZ8ZASTBAy/NMXGuSngLfE7MQ7KCxXAn6GkZGYN8+0cybTNYdYAYIFxYrUVnfJK5JQENQ4PkuimmLwWOuhyRJ+KpaHxQ0aO6NktXg91IASL1a29kPfACumg/33AcbjuHf+zDy0aPoO3azZMdudrzq5ZVld+wgMdIHLS5WiHunwxTE5xSEzkPF4FgriqiEHzxYAQVKICmOJZUT3Ic8LwLCul6RIGuKJs5tDShwZAPPtvGdsoAzIQMUgYKM2BZJDZiC6d2TUYIrBUPrJLViJEBNT0G0kRqOKyxJk1oSX1Wwu5pF0S4EsI8/LqrId90Ft98uWIK+Pti6teJu4/viOLzqVXDokJhpsWaNsKc9+2ykFStQSiVhM6uq9eVDbrV8KJwd4NpTvO+Caz/niespo6XB6gMCpgCmlA81BAV2DnZ8jq4D32V2YT9SlThaguHD0I0ABYkOuOZn8OijjJtH8CVF2NHKwfpq3bZiPWPkcuLZVPPM3H34SX7+0Oe5Lb+Juzuq92F+8/xIpgZw8ZyLsV2bhJpAa2qpDFrM5aC5OZqbAGB7PpRMwfKpqth++MMGBWHMmTOHD37wg3zwgx98prbnTNRENqGSM51J9fN942W6gqFc89vTHBoqsqDj99fT8XRAyTMFZsq2i16TuLeldA4OntogtKcTrSmd0aIFnOm7OS0RPvxjNHrcR9ow0qJZ2K1OqNw4KJh0/WG1tOblWysfChOSOFPwdMP3RIX70Q0wdyHMj5V3ZRX0NuH/Xh7AdE0kz0OVA3/+ri70/Tr66Dglp0QzU7Bw9ZofAccNXvZGTcI9FVMgefjlMpuGN7F3849Rxw/TuUDhPeteDcCVy67nyhf9C5Ik4dhOVH3LKMFrSZKjZCqcGxBNGI6OgYZl5VBsG1mW0eLb6PviJb59Gxx9Ah7dBssXVpL1666DjRtFonb++Q2ZgqJdxDclkXSGTAHMDBQEvvWhfAjbFnMGVCVKpsSxmx5TECbRcuDz7rqliQvPaoXXXAN/cgmO3MRjn/oUKw7twj6wF+uc1ZXlbrmFpq99jRuaM+TOWwRXXwKXnQ1L5kwhH4r1FIT6/eFgOzo6KtKqsEIbDBuLOxBNYApcl7CPJhHKhYBmoxmUIIkMwKuu6LhKEsnxcJwCWgj2oAI81IzIcqRAPjTZJNxYRLImfMEUSFr9RmPXiWSJfiARkxwXQzGQJAnJd/Hwqs9nSwuce654XsyaJa493xfN2Q89VDlmyaTYn8FBYVd7991il4DzFy2CT/9dpafgjjuEfe2CBSDLE5gCRRN/Tyofig1UC2cUZLQERDPsBEPnuaZ4ttU0T1edS1mC3D44MQZz3hysIAE7v4AenP9SYjbJOS8VjcLd18A9G8S9EybVwXMo7BcSU5WDjYmDAtet7mHJ5Si3wgMH7iabnc9Fcy4CQCqXuffQffS1QlJNsqZrDdcvvp63nvNWlrQtqco9or6z8Bne3CzOw9gYbjYT9W8BWL4LhbJ4VqfTlfdArY3xcyRm7D50Jn630Z42GMpbk4KC/pzJvDZBm587r5U7d/b9XkHBB3/wJLe8bu2Mh3k9k9xGvWnGLSmd4cLvHs23pDT2DtSnYM/EKUT4wo298MOhRwk1gaKJivVEUGCJi66R5WK0/uC6kWpBQc3E18jrXqr+/dMKD4bHYdAVmCQOCgASXWAO4Zf7sF0bxfXQwkpdR0fQbDw+PVvSBkxB+GKsYgpkub4EB8CzcDWZzSe38qn/+gb/7e/kzUOwRIO8VAHhkiyLBNuyKOSEREFXdPRQphVzvskaIlHI1TqfSGI+g+Raotr+k5/ALbcIb/+9e2E8NudFU+Erf1l5aS9ZIiQco6Pi/zWgIKkmo0F3ZnGcBNLUoCB0JYKJTIEXyIckJWp49JUaUDAFU1CbREsBk+LVAwVx9yEk8vPnM7awjWPXr6U1fi5VFT+bRR/L0X7XFrhri/h5VxtcvR7+84f1ezAi9ydfeMUDDBeApHBBCq1nJ7ElrQsKfA9kiYSehrK4JpuMJlDylWUQBSRZyyI5Lp5TmDijAIR8SCnHhgpO73kfMRh4wfWQCJgCBQoHae5/lHPzh+gq7IT1P4GuK7BVcd/Lto2u6CiSguQ7eJ438XzWAnBJgvaYzaeqwo4dAhxs3w5btgg2YcsW/M2bKcyaRUaSQQ0mjL/w5WKdmQysWcPcRV0kFvWQucyFi1pQtdjE5YY7XXl+jgfMT0YLrhNJRlVTeJJgtnBLE0CBWjzMvIH7aD/xNXj8Pugbhfx8uCAABbIGKz5MKX+EHX6GsVk3cvXCq8Xvap2HgmPg+R62LaRMKS0VgcSoIAPgOHi+x8HRg2w6sYlj5Ye4J3uAOwoOL115E9+dI+RZSxK9vOXsN5M853ycBfNQZZXVXatZ2LpwwqEIWVXXcwWYb2kRoGB0lFJPW9Wyjg8Uy0Bw/MPrMJh5MqEX7VkeZ0DBszw6MgZDeZOFkyT5/eNlzp8vUHxz0Dz7+4qC6dCRMbh39wBXn9U19QdiMROnJUkSsp3pAo/B/ERQoKsyznRHyjcIx/VmDH6aUxpjxecmtfisjDryoXASbUpLgWpWNZBGTZVOWSiDpmIKQvlQbZIfGw5lOiYbTzzG0sIAneH14D/NcxxahJoWkKmmyMNIdMHYDpzSSfBFA6IqBw457e3oqoGaG8HMjYrBYZNFI6YgdBXRjIptp2E0lFz9YOt/8sQDX6S4d5j9SejoTrK6ezkvmLWAtVe8v2b7EwIU5AUoyBrZiouNHE5t9sicHKb9kc2kD53Ay/0P8v4DsGcPHDuM9dA/oTgWhmzAE/eKqmkYkgTtbdCRgWXzwLRFIgXwX/9Vva/hv4PjLEkSaT1NzsxhFnMkjKapQUEICIJhVlEkk7i+i1K2RALsOCiSgq+pp8QUTJAPeW402RqYOEPDAyeRwDVHUQulqmnGfPnL+F/6Zx746Zfovf8BFm46gLxhB/QPw5NPVe/HF78o9PNXXy207uEAPXtUyLPGTdADUBBeTxEoCN5hsUrzhEbjUD4kyyS0NJQFCBSgIAA+seRV0bJIjicAfjz3CoGHlgHFrhgATLenIGw09l0xBVtuFsfh0A9g4/upSgv774OuK7Bk8QbT3QCwSDIynvDDr7UkrTenACb6+yeTcN554k/4Ucti97/+K92SIj4/OCTkRdu3Cz39ww/T8zAIQ8yvwpvfjPrO14jPlkvw/e8LKdKyZRPmcwC4vkc5eHZlw34sWUNTNFxZF4DJKUIwUZotH4MD3+aCwoHYuhDMQGphMEclAIiL34nf9wDF4QNV1fYq56HYMDfLscB1UeRABuoExyX4rOu5vPsnb8O8/deMBvKfVVmwl8KszGzmNM2JvkIql3ndqtdxZFEPT3JSHN46g8ug2g3Ldm2M5oBlHRuLpENhwcDyPAEKfFcwBcF0awGWrcaM6rM0zoCCZ3l0ZHSeODy5xKVouaSNZ8ep3Hx0lNecP4f7TgEUzCR6m5McHysxpzU19cIIpmD1NJqYZxonxsrMnoZjUjyyhpCEnYnTFHVAQfjgTutpUIJjXcsURAOaprh3wuRUatxT0F/oZ8TO0VfoozOVCZKypwsKAsBq2oH8oY70QWsCJYFdHkZ3HTR0QYMrImFQ2zogdxK7/wTMWzf59zViCgIZliZrIjFy3UlfdPuHdnLSHqZbz/C+c27iRS94D0dv/x662ofnlKpbpoMEuzg6SGroBD1DR+HEnfCacypMwRvegH7rrVza4Puc4wPIro2uJuFlL4MXvQiWLhVMwIIFcNsPYXwvzO+BQydBqyQdVVHDFIDoK8jnRyjZJZqNpql7CsJqZ9h0HkYyKdyHzIp8SJZlPFWpSBQg1mhcH6jWggJVMfAlRcwXCCZbAxNnaHgujmHgllxk20VzqkswsqaTW7eSAyvamNPUhGFL8MROUGNVVMuCv/mbSpK/ahVcvAwuXgGXrBa6ajkpqqWpVOU4BlaQaJpIFN2ySNr11gZMgQ+yTFLPEDa2C1AwWFkmCF1N4nkKjm+BHHyf51SApZoBZTwABU5dp56qcMsw9DgdB35A9+BDdOR3QP810PMKsf1dV4CcwEwv5EDmXOSeq1i2TFTCreCU6SG2lgOmoFY+BI1BgSw3HPoVRWiNLCmi0bi3DTZtEsd4zx7YsoV99/yUzM79dB7oQz777KinQD54CP7oz8R6DANWrBAAYc0aARJyOUoZHUhgqAZaeAnLGrpn0VTcT+vQHpj/4ooPf/kkFA7gSQoj6eWk595IYvYKGM3C8hUVQADgFtEUFU82sD27IjWODy0LQ1WFJNLxSKpJSnaJBw7di3XkV7xk6UvE7ARZYU//TprKY+iqwTldZ/PCljb+9IaXMXvF25Hi3x3I2NRME+QFKKg3o0AcYglN0YQM1YuBgvFxSsFMlKyRZaw8JuRDxbJ4fmYy4vyoauW6PwMKzsTpjNa0ztAUzbC1BbvmpMZo0aIl1YDefwZjT1+eN188n6PDJfb251nSVcey7zREaEs6XVAwmLdoz5z+43FwqMD89plJtSRJihyjzsRpiHpMQSAfSmvpCbKD6p4CfWr5kB82gdaCggpTUHKGRYLn2jNuamwcISiwqm33aiPRiVPsR7dH0fzgRR0kG1r3LDj0FG7fyWl83eSNxpqiVZKY4EW3a3AX//TwP/HHa/+YS+ZeAsAfrbmJHY7BFaXz0GetwpezHJU1vISG7RQxfA9+dRv85jfCYeXAARb397Mkngit/yYsDhLShQtB0yjN7WF8bjepFWeTXbkWFi+GLpeStg9luCgo/xdcCStXVu9XmNkUgkRRacDs1QMFehrZdjCdcuBiI08PFNRKqyKmwEXxHTALqLLaWD40TaZAkRVcScgscM1KNb52hgaiwdrSVTBBL018p4QDzBzPwUik4dKzoeeaygLFIrznPaJJ9sknYds28efrPxXH5SWXwjs+VBmgpqoVB6JSSSTVakYk3vYkoAAXFJmklokYjayRrdu8aqgGvqfieqUKKIjPWIg88xVxv9ZjCsxh2HkLDNwv/O89k1nx3+eOwqxgTkFiBVz6XcZKw+z12+jOzoma4UNQEDpLCfmQG8iHpjG8LPy/bU85q0AK3YeCScX4nti+lStxz1rO9nXiOnjhkhciyyrq43cB4OdzcMklQoqUz4vz+OSTlRXfdBOl170USNA6XoZ//Ti07Ia248wu72BOePyGHoOmZeLfS/8E5rycO8ZLmJLGNQuvgX2HBRCvBTdOUVyzsoHv+9iekFrVAwW+LLN3eC8PH3mI7/3212we2IrpmtyYUbhm4TUkPRPkFB+77G/oTO9h+fxz0VwPTjwESnv1c911o/tVTWchuEQagQIQ90PUm5ZujZqNyyPCIrfZaGasPIaHjFsoCqlZOJ9L1yug4DkWZ0DBszw0Rcb1Jk8ga/PL8+a3svHQCNeu6K7/gWcwfF/47199VhffePDAMwYK5raleHj/0LSXdzwPQ52GQfUM4/BwkQsXtk294Jl45mIS+VBaT1eSveAFFSYaginQp9FoHPpe1zzgY5akJbsEsoyNiy8rSI779HsKwv0x7VAvV1+janRhe09iOGNoUkCXB8mG1iXSG39ocOrvCxORmkTFdm0kOZjvEEhJNo3s4OPf/yQ/3/VzfHwGigP89PU/hWKR3sNj9B5pgw33wdCvkYaGOHvPTvZ86uWYjonhluGee+Bf/zX6DglwDR1/4ULUhT0CCIUMzf/5P/CpT7F3cDsHRw+ypG0JKzpXiN+N7cA+uBvJddDDqdK1oQXHqxA2vDYABZFzTSVxzOgZZMum7JQrif5koCD8WQ0o8A2RBEk+aCcfhIHNKBiNG43rAFXP96JiQgQKJAU7lOHEr7e4dCgWdlKHHGiliduuKRplqUbOFP98Swt8/vPi30ND4hz+6ntw3yOw7xikU8Ktq6sL9/gxyq9+OerS5RgrVsM554ihTmpaWOgGmv8J7kNhT4EiIcsa6+evF5shyXVBga7oFF0V13Mq92fYT6AF756wAdn1RFP+0Z+LhHr2Syv7uP0fK/dbopuh7GqOJ5Ywq3kJHeUR8YzQNLF/ioEsy8iOW+U+FIECKWCCJBm5XqMxTC4fCvbxyNgRdg/tZl7zPBa3LRbHIDwtngcElqQQzF8Q5yqU5ciSHD3r1KDROL94jmhm9jzhDBX0KbB1q2AbFi6khE3v8L2s/em/wudCMwaQesCZr2Mt6SBVeBJecQN0dkLrWvyWczBzvxT7r0wyvMwtIiMjBeA1skquAQVffOSLfOa+T3P+k8Le9gkFHAXmNM3hivmrKNklkp4FpLh67hVwwgAjWbGNLpSqj3nY7K6qkWGCJEmRO1O90BRhq1zbbGwND0BT8GyQZHDBM01hO5sKmInwWfJ8AQWjo6M89thj9Pf3CxQci7e+9a2nZcOe7/F0mm7ntaW4a2f/aduW6YYXAy+KLJHSpz95uGy7JGaQtGuKjOP+/qvttvPMgI0zMYOYkimo1opXMwWZ6YMC3xG2c7IiEpfwZSEblAJLSE+WsX0f3XFOiSk4OHoQCYn5LfMr8qGyDSEL7roTQUGiE9tzUN0Shu8AemU4T1cvvizhFPP4uRxSnJ6vjfAFHlu/54vJxCoqiqRwz9EHuOPur7NlfC+6C+klcM3ZN/KhSz4Ef/d38IlP1F21DihjprBK9Ey4/nrx4sxm8XyPx7ocBi5fx3VLb0Ad3Qzl/op8KKi+1XUgknUs10JxTHRNn1h5hQoICBNhTZ64DEwAjyCuH9l2KLt1QIHnRTa3UTRgChw8PF1DMUsoxXGwTDSPiT0FkzAF8eVCDb4qq3ghUzANUFBOqGLIW7E+U1CUNFwvkAcFlq91o70dXv1quGYJFA7DniOw/bg4/u3tjH3zy7Q9shEe2SiW//u/hyuugEvXwHm9cMncqn2KmIJYTwGSHDjOhDtdHxQUfFUk50oICmLOQ6WTcOJXcOiHYO+E0kcAH9ovrIACLQOr/gZSc6FrPWSXsvvoIwwWB+nxciCNifMRnmdZE4mt71TmFACW7+ArcsVdShZMQZUlaRiTMQVAqZxna+EpXM9l5+BOjuWOcXb32bQlRQFKMAUSqHErW3GuaweXQQUURJaksizcirpkWD0IJ3dA5mNwuImCdZyi3o2imLBahSPAmAMnQD1hoT5yHL7zT5BaB296k1jv9qeYf+ttjC9fgNp9+SSgQDwnFS0LPoyVx3j4yMMcvOervGLRi+kMnk+KpHCy1I+qaixsms8Fl76G1573Vs7qOAtp4H7R2B4WZeIAKxkcj4JZLaEIQUEqJYYpShIZPTOp22HkQBTIJwmaje3hAWhqJ6WlxP1XskQenFAr/Uq1oMAcgtGnwGiDljUNv/PZEDMGBb/4xS9405veRKFQIJvNVh1USZLOgILfQ9Re16di63l4qMj9ewdY3Jnh4kXtU3+gTuwfLLCos8IMvGTNLG7bcoI3XDhvys+KIWLPPd/+3+c8iDMKpCAiUCBeDo7nRJZ8KS014QUVJiBemLRP1VPgB/pdRQ5cNzKVhD9InMqOkKb4qoLteejOzOVDeSvP1r6tSJLEnKY5KCEosJxqUFDrBCNrWLJInlJOHmiLEpiEnsJuaUIfHsM6eQwje1bjDagjH8ru3U3vnU+SPdLH3u1vZfXRUa6KGd0c/PX3WPDCN4j/dAeuNU1pWDALsp0wey7Mns3xlEduZZKsa4mX+fXXiz/HjlF+9EEc6xCqqgs6P9SD1wx+q+tAJGuYronsOugJowFTUHOPNpIP1YBHiMuHLDw9mBWtKJWGUNOcFihwfRc3oaOXx5ELFvg+qmfiK0ol6YAKsK3DFMTtSMPnjiIreJJWkQ+F0QAUmAkNFVAbMAWerFaq35PZkYYRTfNWoLVdVI5lmeEL13DkE/+LOXdtoH3TTjG067e/FX8AvvL38O61OJ6DbNmoUvwe9cS9VgvW68mHFAPfVXA9L8YUBKDg0Zth+HEhFekHwqJw03JoOy+yEgXg7I9XfVXEYDihk1SssV7WBFPg1zAFroWnBcMRLasiH/JnzhTs6t+Om3TJGllMxyRn5njw8IPMa57H0palAhQAaGHBorIdtXakUAEFUnkYDt8KJ+8UQ8Py+yrf3SwDr6foW4yllzL8vjtp+6tZML4H8mnMA0X23/0DOrdtoeNQQbA/Qfj/8z+c/fGvBP/7K5g9W/xZtQpuuAFe8AJoa8O3CxwaPchPDj3FvUcfZ8fgDtxymRv2wbxkDzdk/giA16x8DWu619ByzyNYpQLzzvkjejqXBMc/ZoULletBVcXsBhCgIB5hH0wyiaEarJ+/fsq5LdFAv7AhOugrcEeGYUE7SS0pmq9LFi4epBPBedAm2pI6RTG4bxJm4tkSMwYFH/rQh3j729/Opz71KVKp6em5z8QzF4206aoiYzkeulq/Kub7PluPjfHEoRFcH+a2JnnVujncuvHIKYOCJ4+Mcv2qimSpOSWGjE3HJWioYNH2PBrm9dwbLfcsjshxRbwcwgFXhmrUpbLDCpDnWnh4yFMxBZ4nqHlZEqBAy1T6CSTRUBpafvqKguV7pN2Zy4eOjh8V6/B9oT8nmFEQZ8Qa9BUUA7vHhDkOtEX7LEkSUkcHDI9h9R3HWBobkDQwIIZ3hfadmzcLG8SPfhQuuojh0jDNO7az8j++P+H73I52lKXLWJCdW/nhm94Er389lB4BPNjigRs8f8aPU24bFVXM+CRpw6DslJAtO2IComNbAwrC3xftorAJlGRcZFzPRXUddFmrzxSo0uT/j34+sacgoSZQHdH8asp+hM0wDJFomGZFRwyVJMCofvk7noNr6Gi4kYxJ8038uHzIcytIfxKmIO6MokgKnqzh+l61TWMkbathCpIqaUArlqkNTdbwUbAjCdM0EpgwQRscBTkb9ROMtCY5+bobGFt/IevHWsSx6u+H238F9z0Il60V17nnsvjbPyf5n++Fa66BdetAGYIl7VODAt8nVTpC5/ATNA8+CdvuhEveVJlRkOwBJGhbDd1dkGmH9W+FOS+ZcreiYx2CAiNuxxsyBW41U+Ba+KqKKoWgQIYQFEyXKZBlRsujDIy7SKkOzp11Lgk1wY6BHRweO8zhscMcGzuGbI2K5YNkP94rUTW4LAA+mmqgunnWbftkZPUPiGPcfpGYFeCdj3fYo4SNLykkOy+Bwn4Bhnp7kZctYd8il9zYQlp7z0OZXSkwOL09DF95Pk27D5E8MQDHjok/jz0G3/gGPPIIG3sdvvSzt9K7bQR5P7R3Q1M3dDb1cO3CVfR2L4mOx6zsLGZlZ7FBfkScSil2/MLrMny+xgFWI1AQYwogaFyfIurNKvB8D29sFDyPlJYSyxTLeL4PqUQg42IiU9DgmfZsjBmDgmPHjvH+97//DCD4HcZkCeR4yaE5OZHiXd3bxFPHxzh33kQfwuGCxX88cID1yzp5yyULUGZoqdkocnWkQlct7+Se3f1cc9bk/Q1DBYuzZrXM6PuSmkLRckjpp94aY6iykC5pUySGdcKbotfjmY7n4NDqZyZq5EMj5REAWhPBtV+T7EV2jnjCEWaqRmPXDZoWlYj+jvcT2K4dJRGeKosJl447I6bA932OjB2pfKXniv0Jm4zDaAAKSrKoohtWTsgvVFWAmRMnaD7cj5UrYPefFEnCd78rGkZzubrrGtn1JH/368f4+qav89Ge6+l65TVYC+cz/7xrsBfNJ73ibJTQjSMezc0isS0FjEMiAwVRodP1BG4iieWY1cmrYVC2y8iWRcrIBgOUwgbu6qQ0oSYiR5C8lafJaKIUWke6LqqiNmAKgr9lTZyTRrd6+NkaHXDa1/CBgmTXBwXxaMQUeC5uwkD1HciJY6JIwiEoAgXxJtg6QLUeKKjIh0oN5EOVY+j5HlZSbJdSMif0p2iKALiOH3z3dJgCxRBWpGMFSHdEoCCUeJV1WTyoZs2CN7wBbn4d9D8CyZaoyt62YTtSXx9873viD0BXK7xwE1z/EiFTSiREwlg8CvvvhcKnYeA+usv9dB8HikAZGN1a6SlY+xm45NtgqfCbn0JxH+iTyOdi4QYATbGDc6LFkjlJRZZlJN+syxRoiIZUGR8PAhZjekyBJ0scGjsEnb0sbFkYJa/n9JzDnKY5bOnbwmhplLHiUcpOmYzWAsRclTwHafARlp74OXOKO2H/PFj/ExRNx1EylNQOks09SD3XQve10H1lxVp0/35MZwOeLKPIirDrDM0VZC0YSiauN9d3UdwiyOKz5Ve8lMfObSGlpbgsu5Jdt36V0q/+m54CLDCTsGoVi91+RsujvGaLzMseqsjO/XYbac4gHHgMrG+K853N4noulu+iAqn4syBiCurIhzLBeSoLK9MIdMWYgulGyBRETF46jSX5SJ6PURK9EJqi4ZXKom6TSlTu4VpQ0OCZ9myMGWdTN9xwAxs2bGDRokXPxPacCcD1pj8RuC9XnuC/D7Cqt5kfbDgyARS4ns+3HjrI+69d2pBFONWot8VLu7PcvWsaoOAU3IEWdKQ5MFhgVe/kVqO+7zeU2rSlDYYLFr0t039YhNGXK9Pd9PtB/o7rIZ9BBSIij3Pxgh4uCc/71mRw7ddUGCVJivS+gtqfBlMgG4IpcIKXSyzpCqVDEDAFTlDhn8GcgqHSUNV6hJbfqzQZh9EAFHjHhun4xZNk94zC0Z/CyDgcOQKlEquBPTe/GmvuCiHjaGkRgECSYO5c4eKzdCknVZNHTjzGlw/dwm9VccP8rPMky9/0F7SmWlm64CqmvEMjm1cZkqkIFGjZFjy5hOmMT2AKSk4J2XbJqKkYAyPVTUqzepbh0jA5M0eT0UQ5OKdGeH/XZQrC3yUEKGj01qvTUwCQQqMAFOPD6xo1GzfqKfAcvIQufO/zgc+5JqN6pYmgQFbrIv4Jnv7E5UOFKeVDru+CoeOriqhiF4uVQVHEKqPRyqcpHxoaE2CuuR2SSXzfjyyBHV00QSthpTZkc3w72p+NX/orXjLcLlyNbrsNNj0B/SPw7e/BrT+BV7wYCEDBxh+BdBcEyhVfNhjTe3GzWdpX3wBqSoBpSRIyISmQ/ElK0Kg/zTkFvouEi+yEADdWBJU1ZBRk38WJMQW2awv5kCuYAlXzsQjm78g112UDpuBI/jimbZKQNJZ3LK/6XXuqnSsXXMl9B+4j53rkrBwZtQuKB2DvZuEI1H8vc+3YwL78TnAttGBY3eZ57+f8F/5V9ZyK2DaVnTK+IcdYuwookCRhNuDKujh3Tgm0Jnzf56n+p/jZrp+xtX8rW/u2kh0tcWEzzF2zmv/7jw8D0FIc43PXfY5F+iDjbRuRt24jffgE0tCQaFzfvFmAwpe9DICSU6Lj0S2kjw2gZZbB+vUwb15FglOPKdAUMaTQV4S7Uli8CK+/mYCCWqYAKAVqhkyxwjq7xTgoCM5reP9HTEEoifwDBAUveclL+PCHP8z27dtZs2YNWo2+9cYbbzxtG/d8jZLtkoxVrmVZwnY9NGViEt8/btLTPDEx1VUZ151oa/bthw/yxovmnXZAMFayyTZoKF7cmZnSnrRkuzOu+C/qTPPwvqEpQUFhkjkObWntlEHBoaEiCzpOkTGTpBkNX6sNy20sDXveRQ1TEIKCsCmvnlZckzUkXzAFU/YUuK5IkBS/whR4FXlG2GQM4KsqVskNQIFfPVBqkgilQ2FUQIElRmYePw4nT8JTTwkZxt698Kd/KvS6gLZtB4v+8ZcTVyzLWHN7cZOG0MYODoqX6/btwuozkeA3e3/DZx/6LEcfv4tlCTiegesWXccHL/ogJzafiI7XtCJuhRmT0BhNrXjykJBYuOVKAUHTKAbHL4MeG1xWfzhaRs8wXBquVKKDpEwPH3X1mAI1nJCcADs3daNxDfBK+2oACmJg4RRAgWvogikoWyBJyKqG5uRj8qGZ2ZFCIB+SVPGsr2IKKna50ed9BwUF0mlRdMrnq0FBWBn1Q+38NOVDQ8E04x7hfBXKuwDcpIHjOSihPWN4HXkVdk1OJOHKK+GyC+FFy+CO/wfH9sGxPnF8xx+H9PXiPv6vrXACWNELV63HvuHV7GzdQlPpKG3tZyOFCbGarjBsihKAgunPDnE9F8l3kd2g70CPV6o1FDloNI5r+V0TWVNQ/QAU6EKp49Yr3tRhCgpWgcP5YxjAspbFVec5+mpJpguHIyHw0g146iswtrWyarWJ/sxqtN4X0rnoDQLEKILdcHwxF6MuKHAcSnYJL6XQEjIqUe+UWF6TNVzZCKYaF/F9n9VfXs32ge1Vq1qU7ebahas4e8llsfUXWda+DN5yLf1vfgc7BnYwX+vg7Lu3C1vUYlEULYLJzkW7SOcDm2jdugd+frdYR1MTrFoGSzrh7DXwZ6uqj6XvQiYJeV8UPkJQEDIFM1C4hD0H8Z6fUkZcB5lS5V5USmVcED0F3vOQKbj55psB+EQdlwlJknAnG7pxJqYVQhJTAQXtaZ2RgkVXnap0f67MOXMbJ8XRcBDgzh19rJ7d/IxUtzcdHmHdvJa6v7tq+TNjT9qe1hmeYoYDwGBu4jTjMFpTOsdGS3V/N1UcGipw9pzeU/psU0IlV3ZoTk0z2aoJy/EwzoACETFQULQKmI6JJEk0G8F9UacCrMoqku+Kl9t0mQLJjMmHKkxB2E8AQj5keaZIQCCY3Dr5Y9b1XE4OHSJz+Dh2No3Z2SqSqocfhbf8JZwYqu9bfumlESgYWzSbgfVn09qcQW1ph6teIdxe5s/naOEoxzbeyfyjeQEKliwRQ4uC+NxDn+OuA3exCpmr5l/BS174Ps668tXYts23Nn8rOl7TiniFugoUtOFJGr7vY9m5qOfTB0qK2Lesp1XJsupFbbNxMXhh68iCKaplCjy7MqwsfCErDWjDOCiINaGmXPH5QtyS9lSYAkNHIUga9FZkbQTNzVcqkTMcXBb+25M1PMetlmU1YgoAKRMkfPmYixNxpkCa8NmGIRswOBZIhIShRJU7lKJga55gcopFCPvGPDvanvbCHrj9H2DocThmwSgwH7gC0NuEExWIY60kxEWz/Ths/z76//0+FyoypXmdeP0uyp92BAcmU7UN0TG1p35fgDhWsu8iuR6gVDf3SxqyJFeKCkFYroWhaSiOcB9SBUeA69cBBXWYgqf6n8KToCnRRHeyo7KsNQJ9d0fNwStHdvMULxOgQDOg/QLQm4WbUve1PF4oM1ga4dxZ50LT7EAypwiGyfdEklvvteM4lJwSvmJMYApMz+PBA3fxH5v+A3dkC1++6i/AKSJJEmd1nMW+4X2s7FzJFfOu4ObzbmaV2ov04IPVSbgbJOZKCt0X10HZUGDOHCE7W7++ksQjQIF98dkomSaaRouiEDI+Dg9vgIeB5vvhQ/9YAQVf+xrIJqjj0NwBIyNi3Z4H5aDYcCryoRiQLAbv61RRfKfm+pi2K1qnkkZj+dAfck9BrQXpmTj9UbJcknFQkDEYzNcHBXnTIdOgCj6/PR1Us9Ps7c8zlLeesdkFBwcLXLmss+7vFFkibUxuT3oq9fLpSqwG8iYdDaRJ7WmDrcfGTuHbxXk61X6G5qTGaMl6WqBAV2Q8z6fsnPp2/EFELIkaKQ0BYrBM5H1ex7VElVXRU+B7U1fyXVckP4pdebHFB5dZAhSktJQYRuU64AXXpmdRsQ4CRkeFv/vuHbBnFxw4ir9nFzccOYbk++z5i5vZ+faXiYQpm4ZjYlAOug49PSKZX7NGJPaXXw4I4D86p4PHvvJ33LB3Lwzm4MrLYdFSAJJmErO1CevwMMW+o3zlwc/zxnPeTE9GDDr7yOUfYU3XGj7c/GJ6B8vQvbSy60HiVreyWC/iyWgsMZbSaTRb6I9NaywCBSWnhK3K6JJEylMqNLtc/+VZa0tacm18SUL1ZPFCrmUKPAv0YICXrAmXnHoDrKD6s65bcXDyBfjOUd0LIXamBhQ0mFPg+i6+HrQzSBLo7chqAc3JUaxlChpcj3WZAlmptiQNwUx4HmISIJfg+s9koMBEUBCc44LaClq2MrF2sii7oHVDMgHtIpGtAgUICREmMHoMxnbCgW9D8yqc1gsB8NUUDDwoFtY7obkLFqyCF3wI2s+vVPyzWfi3fxPH2LKE3OjOO5EPHiR9oA9n18FYZTsBn/ucYCDOPRfCOdqOXe06VCfCeRCyH8iH5BpQIKvBDAJxPlzPRZZkbNdG01Q0UzAFcjB80KsFeb5f7ZgDnMidoL/QT5OisKB5AYzuhCe/IRyChjcSiJDEx12JNmmUglvGlxSkOa+A5pWQXQyAmbtHHEpFF443/feB0yaeea5TPUE7HqF8SEmS1tJsH9jOjm3fZ+uJx/h/R3ZwwhTPuQUqnMgdp7VVFBb+5UX/wj9c/Q/sGd5Db7aX1V2rRfIerDOKUHqpptA9sd+WXa4A6ZqEvWgXGbzhMvQrrqbp8heLBH/XLtj4EDz2W0AR5zEEBT/8IRw6VFnBR/9FuB+tXCmu+Ze9bIIBwGQxwZIUKCTFdqdKYsCcUbLJA46hBrK40BXqecQUnIlnPoo1yWZ7evJqdqPk+Nx5rdy5s4+OrMGvt57gT69Zctq3dTrbAfDiNbP49dYTvP6C+vakz2TL7kDO5PwFExuuAbIJlfHS737ASEtKZ7RoM7+B0ZPn+QwXLfrGy/TnTPrHy/SNm/TnyvztS1ZiOh6GJvMXP95CwXT48pvP+93uwLMp4qCgOAjEpENQXz6kCBtHz3enyRQEHvhuOZAFhUmXQdkJGpuTreTKFsqBQ3DkMPy6ACe/Dy+6UbjyABw+DK98ZdXqwzvdS6dQLXEter4Hi+fBp98rpmnOu0A0ha5aJfzFYxFa5nmyhiyngRx4FaCbUBP0KyW27P0VT967kV/MKTJsjvLJaz4JwLWLruXaRdeKIUaDh6qaTyNQMGP5UDVTQDpNoiRAgW3lo8Qsb+XxDJ1kGSTLmpopCGQNeSuP53uBdEtBQzi9TGQKLNBVULRgAJXaGBQoQZLh+1XzB5KeWGcRJ3I9qgsKXLfC6NRhCiTVRVYUcWy0LLKqoXp53FB+NsNpxlCRDwm5WSCPUfQqJivavJApyGbrg4LgHBfVJui+qv4xqo3RUUj2QltbdN2EoMCwhmjPb0M/sgMObRVTbruCz9mjOIveDYCZWQIXfwM6L4eDJdE30NMDLaurm+zD67KlRVhcvvGN4Hns+MyHST21lc6XXFhJaLYdgr/4C/HvpiY46yxY1AydLTDfArVxchZW/6UQFEi1oEDo66XgeLoxa9K4JWnEFNSWvOKJsqriOCZHDvwYQ8owt20BiSEPhrfC8D9WlmtaAT0vgJ5rseXV9G39G5KKRNG1SEO1+1DcktQcFteFPSj6qDyr2gI3Ho4j5H2Kwucf/jxfeOQL3JASjr5jFvRkejhv1nmc2zpbWD0HBZLebG80LDK6NuvNKQhZViWJHuQKthXrL6oB9EW7iK8qGKou7kdNg9Wr4ayFcO2synM7ZPZuvhn2bIEnNsLuI+LefOIJ8WfJEnjd6yorf9e7xHWxZg2cfbYotiSqCxETLEmBgg6ypmBIGuRy6GVxLO1k8Nl6TIEXM534Q+wpALj33nv5/Oc/z44dO5AkiRUrVvDhD3+YK6644nRv3/MyBCioZgq2HK1fzZ7Mq745pTFWsvmPBw7wzisWPmOe+u40tPHNSY28efqlZeIdPnlj9nDBoj1d/2aUZemUAcmpHM8w2R/MmWw/Mc7Ok+P0j5vcvH5R5ID097/czrceOojTwN3o3esXYzoeuqLQlTV4ZCBfd7nnTUiSSB58j9GAKYiajKGhfMiK5EPTYQqCaaa+DwPHof8EtEggG7gHD3DZe/+a5qMDKANDEz+fyFZAweLFcP75MDsN87uxVlzA480e+Xk9XHHBqzlyYiOUx0SSp2uwbB6UVFFFM826jcbhS0tTNGSlBTgJtgAq2we285kHPsN3n/ouVx11SDiwsnkJKztXTtzOOnMKwmTn6cqHSKdJOM3YgOmWxXKKQc7M4ekaCVUW+9dgRkEYSS2JKouBX0W7SNkpo/vBwCjfmQgKXKHfF9NOVQEKaiql/7HpPzg2foyEmmD5vgMkfIWRzn7UphZSssGLEG4snq6xe3A3CS1B0i6RsQroRQ01fP6EFU9ZnpDguJ6L6ltg6CIxkFWUZAuQR7KDZ3tYZZwJKJAVkORKc7BnimSpzqwBJ0hY5GwTnMw3ZAoaJo31YizY9qYmUZXWmshbeVS3yHVb346ED8MId6A0oqKdXgit63CDc60qOix4W7D9m4PhZVI1IID6iaZt43d3MdC0jqYLlhKJVbS0AN933y2Ay2OPwWPA92+Hzs+IadrxJDEW0YwCPGQ7AAVxkCcJS1I1YAJcrwIKFCMRXQvhlehSsx+2DYWjMLoZHvgP5JN3caEzzu5572J+xwdgaC+0XgDNbxUOQT3XQmp25ev7+jAkA09RyNklAQqCa8P3/eh5YChGRTbjC5AiuV7EFFiuxUNHHuK3+37Lb/f9lv/X+XYc18ZXFS7rvYwvb/i/XDhrBet61vHpVf+LVT3nsqVvC8eHd6JLo5XKP3WuzUlBQQI9mDxsWyVAFvdMzVDGol3El2WxH/H1hEDXd0XC7TjiHr/5ZkiMwuBT8PBhyCdFf8JDD4lG45CJsCxhkxp/lioKLF8uQMJ118E73lG30bhoF0lk0mKbxsbQS+JYW6ECIpSTxecUROYJcuNhgM+imDEo+M53vsMf//Ef86pXvYr3v//9+L7PQw89xLXXXss3v/lN3vjGNz4T2/m8ipLl0hKTlQj9+alVs0u2y43n9D6j8pLdfTmWdk1t9TarOcHx0dIpNfU2is6MwUDOrCutCsPz/dNmuxqGcDSqJO1hst8/btKXK9M/XuYV62ZH046/dOcevv/YYfpzZt1k/xXrZjO3TbzSDFXG8XwkSbBEXdkEXU0G3cHfCU0hV3bQVZn3XbOUD1637LTu23MyJAXXs8mZoyAn6jMFNaDAxhMv83pMgWXBhg1Cx3r33bB/Pwwdg6N9MJaHt90If/9OkHXyKZW2TTujj9qZFMrcHuSV8+GsdXBNzBc9nYaH74GTdwFwXGphOD9KW7KNlJ4WVWgCpgAPyiagic+Z5sQJoVRAga7ooIhqvO8M87ofvoYf7fhxtNzs1vncvOwNXPLaDyJ31ZER1gEFYSJ5SvKhEBRIEiSTJEspTFkTlUzPBMUQFX9dI6Fp0wIFICREo+VRcmaOkl1C92RUWWvQUxDODUiJmQl1QME3nvwGDxx+AIBr90HSgftPwlgSOqQ0A+u+h6Gn8FWF9972Xu4+eDcpC645AK4E//OwRFJL0mnrHFj3LaQggfyrO/6KB488SEJN4Hous7xRrjtSxnBayWvtvOWGNwJH0Zwcv9n7G0YGNtLtDuIY3ZjD/STUBEk1SUJNcE7POVHiaXs2ZaeMoRhREuaEKahnVUCFJFdJkaLENdsE5EVyaprReYoaK6fTjOv7ML4DnvomHHwMTu6Ck0vhuvvJWTkcJUUhvRTXc/AXrqWlfTksvRKuuEFc+04BL6hox92UcEMJ1STDy+ISZtsWIFFPYMf0/VxwGfzkanG/PPkkfPWr8PBdsO+omM/RHbv+77gD/uu/xJyEa67B7WwRX0fAGEnaBKZA/N6Ljmt4D6qhS5FtIweyMydkCkp98ORfwMHbYeMJoWhqEn/ZSpqMoqCEw8j0Dlj3rfrH3nEwZANflcnZJXpUogp1vKqtK3olEZdlNM9kqDDAr574Gk+ceIJ7Dt4TTX4HeLi4jAuMxUiqxsuWvYzh/91PcuBe8cuedWLegRJrNPbsyEghvGYmgALfF+fLdyoT2pUkeuDk5ZhlfD+JVMcgoGSX0BVZMB5VoECNikB41sRGY10TblFNs0Rf1Zo1sHt3pb/BdeHLX4atWwU7unmz6D/Yvl38kSQBChQNPI8L/vij+Gt/CWefTaI1j6cq6KoOo6NoZXG8zWQ4RK6GKfA8sMNeimc/SwCnAAr+4R/+gc9+9rN88IMfjH72Z3/2Z9xyyy38/d///RlQcBqittF4sor0VMXq9171zEqGALYcHeVl50zdcHvV8k7+e9Nx3nhRtYTo6UzmXdSZYd9AYVJQ8HTC83xGihb9OZO+8TKXLG7HUBVOjpfZcWKcl//bgwwEEp/aZP+SRR3MaxcPIsvxOD5WoUrb0zqaKnNWT5bubKKKaXn75Qt5yyXz6cgYdR2nAI6NltBVuar35HkdkiIobE8maYhEKop68iEUvL5R1O0jcP93Yf9hWLoU3v52sUChAJfFnDNqY3g0WLdBPiHz+L98hNUXvIRNuT2oe/axsreLzHkLoHkFZGvuQbsyH+Bk7hhIaeY2zwWoAQWumGasy0ITOzxclykIhxVpsia01JKCJPnMSWaRkHjlildy5fwrOXd/iXO0echOA8auTvNjqEOfsXxI0SGZFdW5piaQZVJaimFJE4mLWwatiZyVw9VVkpomqppRr0bjF2gICkbKIzieg+8FTIHsTXwghtuTSAnGRZ0oH3rlWa9kZcdKym6Zhf4hlHwRfV6S/qRHW1mcDyMpehkkSSKpJjGDZEvxQfKEE4xbcsSzOgAF2wa2RWAD4DwDOscgPwR9LvzxKz8A5W1oTp4vb/o6T+65leU6HLJha00/7MhfjkTV2E/f/2l+uP2HYrfUBIqkcEVSZnYixR4/y6033SZUOrLO1574Gr/Z9xt0Wefg8YO02C10Z7pZv9cm48hce+5KWmcLLfrOwZ08euxRdFkno2dIa2mSmriXEmqC7nQ32sFvw7FfwcD9UB6EzYAHdAAjeSwrHzENhy76AfvHjrDEaaJl/zh4wT0ZXEtOcAyrWKhwWNg0Jxpj22LomqZhhWBI1iq9FIoC550npEaXz4NVc2G8Cy6+uLKOn/0MvvlN8QdILFvKmvOWULpwETS1QKKjLiiI5EFeLSgoQ2GE9NAOWvM7KbcGrJzeDId/CIWyAG4dq+Gc13E4sZQttsq81kX0FuWJ+1gbIShQFMatAqgVK8zwWaArOpIk4bnFYAq3zHDuCF/e8HV+NSaGtAN0pbu4fvH1XL/oei4/4DJwYh+GkRKAIt74HjyXNFnDlxScsHk6mFUQXptR8SAOzl1XHBMQxQJJjp4nsuvheA6aGhsAiGAeLNdCUxRRla997smBU5lnVoOCsC8nmxV9LLncRDvSZBLe+c7KuvzA3W3LFvEnMGHQZI3UkZN0PrwZHt4MwOXhR3p6YMkSEpdfBPOSWLXyIVWtSBHLASPXoE/q2RYzBgX79+/nZYGPbDxuvPFG/vqv//q0bNTzPUq2S0qb+tRM5r//dGIqOU5tTLfhNqWrlOyJD7uyC9kGzdJTxfz2FJsOj3DJ4gbi/AYRT/bdWDL/35uO8eunTtA3bjKQExp+OzZR9t4PX8X89jSP7B8ik9DYfGS0ar0dGZ3ObILuJgM3dnJef8FcXrCym+4mI0r2//Phg7zlkgUTtq0jM3VFwXK8hg3mz7soHgfPJmflkMhWWALXFS+FsApVKglJwd69rNi3F7lUM9X1hS+sgILWVli7VtDPqZT4+4KFsLQVVl8O7lEALF8k8Cevu4Tzll2C8uQI7NmHHSbe9aquASgo2AUK5hhyMsuszCygBhSUS+KlIiuVqbl1QMFYeYzb9tzGL/f8kjt7/pJlWhYUmb+44F2899K/Zmn7Uh48/CDukUcxPZOM3aASfDrkQ3Etu6LAtddGiXpSTeKGTEGQvOStPLKmkVST02YKQgeigYJowlZQhe9+PfwcgoJkGkohU1DtLvTnl/x5ZfmOB0TV8IILhK69vx8efRQjKb7zlutv4Zyec/B9H+cXP8O0S+SvuIiSJuEdOQyHxqPK+99e8be87Zy3UXbK7BraRdPoJha3lJEGm8ihoGa6USwFzS2wtvscupxB2twRWh2FhC1TdsqUnBIlu0RSTUaJlxWzHg1nWwzIoLo5Dpl9qGFDsayz8fhGfrT9R5X9C9Q+245CVwEuevG7IlDwX1v+i88//HkAtHvh/ARckIAvjYrPPPj2B1l38FaSfb8BoFiCA6bKHl/nZ3YbO0facL91DWWnzAcu/gCrulYBcP/gRu7dcCeqnuCwdyeL3H5aJYd9NHHIcrlxecXGfHD8BGbuGG5BxRzeFwGSpJYkISkiYQmrz7IcMQWerGCFU2/jzkNhhA5EsgSXnF8tbbvpJnF/3XUXbNyIsnsPC3bvge8hrpEvfbwCCnw/xhSE7kIuljVOe24LC3K74IlHIbeHtrU+iUQnu+a8KtiGBJz3JbDbocODpjZYdQ35ge34w/vEPVaPDamNKlBQxE8ZSMG1kTNzPNX/FNsHtvPRuz/K69s7+dCFfwKyxOxkM016lktnreDla17DdYuv4+zus6NnzsCh7zMAGEbwrInmZlQAUaSzDwFYMKtggnxIlitJseuCHyTmqkjMpYB1kFwX23PQ6vQTAKiagWIpE0GSYgSgIMYUKLHlmppgwBPP/6nsSCUJZs8Wf170otiPJbz2Np747AdZfdKHrVtxN28i2T+MdPIknDyJNqsL5q3ENDQ4OQTv+itYd7HoUyiVxBwYs1DZ5udAzDirmDt3LnfeeSdLllRXv+68807mzp172jbs+RzFGvchqN+ImzMdsonTmxgmNIWy7c2oAj0TXNLbnODYaInZMQlR3oZFMxxcFkZCU7Bi8xh832ekaNOc1CLJ0K6TOT7630/RnwuadcfLDOTNKNn/wAsqbiv7BvL8ZlvfhO9pT+t0NSUo2+K7Rgo2rzt/LhcubKO7KVGV7NeLuW2pSB4Ubesp7bEIy/HQ02csSfF9+M4VsG8/s/pVuvp15AEN+jw4UYBLV8Btj4llFQXuvQdGRpEBX5GwZ7ejrzhPNKJdeGH1ujdtEn/fdZdgDtZ0gdoPmgUuIMmUArmDoRrIkoxhpLEAO7Kiq5OAO8KZY7A4hIRMT6YnetmGUooIFIBIYMKkJAYKBgoD/Nvj/8aXHv1SNMX5V8M/Y9mqV4AiMyuRhRZxbSfUBHlVwS7ZEyb2RjEJKJi5fChYPlZcSGkpPEnDcnPgljEdE9u10Q1dMDtxpmAyUBA0G4+b4jjqUhIYB7nOHRVuT3MrjOYhG9yDvhN5r1dF7ayCoE8gkRFWiaHcQpIktFQGraSQ0VoFiBzxgW0RU3DRnIu4iIsA2HB8A+5RiUVNSTq7F4nkKNmKLOtITon3rns7LWteBoVDYuhW00RJYJh43XL9LXzrFd+iZJfIW3l+u++3NJUOsS7bSi4xi6Zw+q5icNOam1jdtZq8meeezfeQ7kzTkmxhQWeB7LEBmp2QRStysVbkX+a0c65SYJ1mkgx033dZaXaVLfYM7UHNnMfqjov45vH9fHbjd1gz4DCScHiwrwgcrRxGWY3kSJtGd3J0z20A/Kb8E9akoVeFp0w46MB5vRWThHv238H2J7/Bnn74zoMfq9p/yYMNvR/j3N5zwXX5wfZb+df//girj1gMZ2T8cpaVyQTjSjMntR7+/JI/5/ze8wHYN3aQAwfuxtbaOFk6ip/sqcizOhOs/Zs/Y9Y//iOMjtL3qx8y+MsfMv/xbaTGSnjtLSiqKkRAr389HD0CF8yjeWWWYxcvIbXhvbQc+xnzvLJ4qAdEoKv3kkv04sYvyyU3C6CpPBpda1VD6eqxIRMuBAdd1jE1Fcf3OTBygCeG7+Hbxz/JXQfuqpIEnWW14/NuJFlGx+F9F/wpxg0vY93CSyas1jJF8pxIVtuRxiVoYYXfClPHoNm4Xr8LiiLuozgoUCrvfV3RcRwXx7Mn9OCMlkcBSCaDpvh6TAGAU652cgr7FrNNMDAq+mZOYXBZGFJrK8duvJqF8y6nYBfYdGITPWWVC/5nC+zbB0sX48sFygkVNh+ETdvFn3h0dcBZc+FP3gY3XTDjbfhdx4wzyg996EO8//3v58knn+TSSy9FkiQeeOABvvnNb/LP//zPz8Q2Pu/CmeZgqv5xk67s6aWksoZKzrSnDQoG8yZt6ekn9Fct7+Knm45VSYjyDrSlJl9HqN8PGYwNB4d5ZP8Q/TmTxw8M89NNx+gPqvuW63H3/76KhR2i4nF0pMS9uwfqrrc9rVOOsRfXruimqylBV9agO/i7I2NUnQ8v0Psv78myvGfqXopnIizXPTOnIIwPHoAiyDjI1Lw8Du6rftG+MwnyGO7cVsrtKqTa0DtnQbIJsjUvYrcsktPwpaNnwOsHa1T8X64MLgvlSkYyI0BB2HTq1ehAAOxxPDyGS0NIajtzmuZEvwqrdq7nxkBBomof9g7v5ZaHb+GbT34z+v7udDc3n3sz7xk9G9xc8EKuNJImtSTjqorpWBNBQf4AaE115UNhT8EpNRrXRFJL4sk6nudh2/lo1oCRaUbu96BUgGhwVuPnQeShHoQRJhqTgYIlS2BJB4zeGzQo2tRt+quVmgXuQslUMzAeuayILzZEwhE6EDWYUQDgOgUk30NOJaEQVAw1DV9vBqeEZw5Vtn8KS9KklqTJaKLJaKLL72JO0xzSOixt7UbLLgFCcKezfv7FrJ+/Htu2kY/ILFmzhPNnn8/cUU9IJWwZdn4BnvxLXu3ZVe65GB3QtZ6tL/l7Ro1e7j90P33Ji2npWM5Nyzp5SdNNePv3kutpZ2TpHMpOmd1Duzk8dpilbUujBHJFz2ouWnsTXrnM8hXtpNVBss4w7SWb9rJFZ6piZZ2SNFqMJlJJaFYkSk4pkub4MmhqcGxdl8HiIEcGD9CSgxM+7D4BhzTYZcOYB29cU5Ey7xzZw137bmfYgjv2/YCjNY+J7736e7xh9RugpYVfrlR45947WbcGXrsD9t/2fr69888wtCSHf1mipeTDw4+wEJirf4uRd8yn8/IyZbWVcsdltFjLILOKsTWtHBp7Aq+Wwqq5z6oS6mmAgnI5j4REKtHEiCTzuQc/x1Ojx3ggINmajWYunXspb1z5Gl6UkZEQTduKIqO6Lq5Tf1aDFVgrJ/SAKagZXAZxpiDcztLEfQijChRMZAANxcB1XRyPCaAgmkqf6YDB8YnHI3w+xGbECPlQDBQwKqxRw2brGQwui/ZX1ihRwvbsiL3Qu3thfQusXInsubij2/AkBffsRSj/8Sk4WBb9Co89BseOQf+g+PPG18/4+38fMWNQ8J73vIeenh7+6Z/+iR/+UOgaV6xYwQ9+8ANe/vKXn/YNPBONoz9Xpqvp9FJSaUMlX3aYRt8wAJsOj3LuvPp2n/UiqSsTJEQ5W6I9o7O7L8fmI6ORfr9ixylkPL/94JVRon/f7gG+dNfeht8zmDdZ2JHG930WdaZZM7uZ7iaDzqBZt6cpESX73374YCSZWju3hbVzWybdhx0nx1kxq2na+/xMhGmfGV4GiEr0eZfjDRwh1ylRmtdF98o1SLN06AbmLax+4ZxXAtdHYZi0B+T7IR80Cbeug8V/XFn2tnOgdAy2N4HcAuoCSMqgtwobxt4XR/KNZEANG0aaHGDbofd8TQLue+AUGCuPiyq5LtOZriRF1fKhcOBOItoHz7a47j+v4+DoQbE7s87j1StezYqOFZzduYrEwzsBS2iynUoCm1ST+KqC5RYrySuIwUijTwlqO9J8xwBw0Bx4SpakNSFLMmqgHTatMfKKeG6kMq3AkHjBuwZoyYnOM7FIaSlkSY5tW/AMnAwUyLqQEI2rQZLSwJa0lpEJmYJUEzBO2SnjeI5IfmptSScBBYQMQ6q5sm+ahq+1ACcFKDCCZ8oM3IckSRLHQtIqswrcOufAHGCxv5k1R++l58D/gYWfBGRRSZ21QFynydn0p1dwMrWMWYtfR2fP+ojp6RvcFa1qqDjEsvZltEot0LIQzlorZBII168FLQvozfZGTMGqzlVce+m5QpZ1/vmQGoXcXnaWLfa4OkvaKqqDFy+8DtQsXHAOX139GkBcg2WnTMku0XTXg6Ia77q8euWrufAVrZjbNvOkPszg0tksbFlIySlRdsqs6lwVrXdO63wunHMxuV6fVEcrhxwlkmeVnXIVMHFcB13RSboWtgauDZbkY7lF1r4Lvtt2M5c+uQf7/o1ogzm2zz+fros+w15bY0XXSlo4DIUCapCwurXXcs0046lAge3aPHL0EeEStP+3uE89xRdTf0prqplhyWJV1ypSqS5etugNLG4Vk5CXtC1hVetc6Ls3sMDNICsKilfGrDfAzfcroGACUxADBcG/Tb/CME3YhzDi+9KAKSi5Lo7rNwQFzel2YLwOUxDce1YgDZKkYE5AsFxTMAQtZAlkeUYzCuLbCOIchEMqk1oSWnQYFDavXjqJL8m4rWmUl66HzqAX7ZFHhAW1dRiOH4T1lzf4lmdXnJL25JWvfCWvrPHaPhPPfNRq/fvHTVbNajzN+FQik1ApzMA69OhIkRes6Gr4++OjJfb05+mP+e1vOTrGTzcdZaRg8823nUveFkzBVx84xJfu3NNwXX3j5QgUrJ3XwmvPm0NXk8Hh4RLXr+xidmuK7qYEnbHK/njJYe3cFl6+dnbD9TYlNMbLDs3J6SU+TxwaaThv4XcV1jTZpOdF3Hcf/Yd+weGTj6G0raNn6auqfx9vvLnxGDDO8MAGBvb+F2nZY07bGug/CD0Lqz9XPikS62IBvBNwcgfR1K3MYpj7yuhFsWbDTfBYkTlKG20nTCQ1C/u2QroXrGGYHTgQOXnwfYYD69SeVEcEBKAGFJRKeHg8MbydtdIVqIDs+bz/wvdz+/7b+fClH+aqBVfx8NGHGSoOYYSPczkZgIKiqJzJiqjSa4pwCYkzBXY4ZMgEqzFTMC35kOdWHEYaVPp1ownyULbGyMmCKcimWkEZFUm1pUzwC68NSZLI6JlIPpSQggpgPVAQDQ0KtkfWxM8aOew0kA9pqQy6pGO5FkW7SJPRNCNQ4Dt5JEDKxnqfNE0ATMArD4Ee7McUoECpacBVZRVPUnE9T8ivPA3sPJz4Dez+V+i/D218B6+SgMHgQ8XHgYuE3rrrWrhxP6QXsP/YowwUBmhNLaqSfvUX+qN/j5RH8DwXObQjjU2hDWcUZPRMlFBZrgWpVgEKikXIiGvJc01Ar2k0DhvVKz+TJdGkntJSoCciF66eph56utaSH5KwE8M4c5dx3eLr6h67c2afyzmrb4I5BpxzdV15VhgvWvoifpT9EUvGDrJk6zHMpoV88oUvo2QLANGb7YXRDRzo28yuvePMOudacokkOH1in3UdCgXk4HqYAD9rmIKqvp0AkPeNHedHj/0bv93/W+46cFfVQLizTTipnGRuqgVfGuIFi17AWV1rYdZ1PHnySY6MHRHbEc6/UJOgtQRzMcYpODUD9wAcJ2oQTyQCUODXAQXBc8AM2Y+p5EPh/kZMQTUokB0Px/OqQEHZKUeMXEu6HTjQmCmwwn0MPh9a8RpJcX+G92YiMbUrS52ITzUOmYKUloLm2Ls3ncFHwXFddC92tjVNSJYWzIOrlkP74hl//+8jznQqPgujntY8pasULZd0rLl0vGzTlDy9pzBrqAzk6zw0YpEr2xwfFZX8zUdG+b/37IuS/r7xMl94/Vrmt4vk/QePH+GfJ030TVwf9MCJZ/2yTrqzhrDgbEpU7DgDKU8Y15zVzTVnCVu5B/cO0pU1WNo9kd4YyJenbNxtTeuMFKxpgwLb9U9LQv50TFJN5wwoiMdY8NJsMepQXGEVyXXFzZXqQWpexVh6CUW9iTnqS6C0D5rXVn/uFccEMPB+LBL787pg7BFRXTc6hXwomPKpm/3gFtD9PvTQvvvgZtCAwYcqoMAeh41/xhxrjC4lhTG2EEbvg+QsSPSQtXyQuyg5Je7e+Wt2bvgRPzKGeE/PbF5DDzgOH1j/AT54ScX9LbIkDS1F9IQABZ4NbgHkJhJqAl8LmnyrQEHFCQlzHEhFiYnrufjB02ha8qGwKl9jhRkPQ2vCAiw7R16uJJAYBhRsKCvQOnVFL2tkI1BghFVDqU4xo5a5CKUQU4GCMAmJJfppKY1Vsshb+VMCBQByqhXSllg2kUDS24LNycXsI+sfu1B7XnsuFElGt4fwS8OQ6hT7XO6DTf+7ark+v4tC57n0LHodqdkvhoEnBPixJMgKQFzPm910zEjjHc6IGBs+QavjiGslK+45z/eixCmjZyKA63gOXjIh0siicKsB8DwT5Gz1/oRJldLgequtpIfuQ6paZccZD8/3cCUfTVIq9piTRHScHRdN1tCyHWSyNe564yqyrKCtWE57xzyO5Y4BVEABINsmSOD6NU/6OkxB3soL5yBFvDfv3X83f7rp36OPdKQ6uG7RdcIpaKSDw3c8TCbZgs8IRatYcR+KDy6LTwfXW5FVFcU1caw673fXxXRNfEkiWSsfqscUoODjIzlTyIeCdVeYggrg1xU9aDSuZgpClqDJaEIzktXHLFp3yBQ0AAWSEjgQBft6CtIhqJ5qHEo1k2oSmiv7IWez+JKP6zuV74fYrIICkPzDajRua2tj9+7ddHR00NraOvmgqOHh07ZxZ6ISHRmdobxVBQqEgcbp8d/3fZ+xks3J8TIbDo5ESX+Y7P/1i1dEjbJff+AAX7yjcaJ/bLQUgYIFHSnO6snGdPoGXdkEW4+NcdOF81jUnuC/g8+9eM0sXrxm1oy3fVFnms1HxuqCgv6cSWd28puxLaUzVLBY0JGedDkQTkvhkLHfZ1iOh96gqfn5GGNmCArqOI9ABRQELxctnKjp+6KCCcKpIh5aBpRFYuASwIoXwuDZFYcc2aBkjwLQd/X9zNIkyuMHOHbimyStMXq7UqDmoOPSyjrtHH75BIZbxrCHoXwUBu+Pft2VWcEnvAu5bc9tvOjAAP+gw/VzJLTDn4ejcyHdjjT7KUj2QHoBdFxUGVYUVpgVBdSU6H1wCqA1kVSTeKqC7dp4lllROcdBgTUmPhe8zMPEUEKaGSiYpB/AMAJQYI2Tl8Q5yxpZkWB7tmAKJmkyDiPeV6DLQeIg1ZRTwgm/UJEbhPvRCBQ06ClA10mTZqQ0UukrmAEokAKZhaxl4YqVIjlVFBQ1SVk2xGTtcBjUVPIhSRaSr/77oP8+rjhxB4Y9hNVxBbSsFMc/swDaL4bOS6FrPXbLRfzrT/+Nc+ecS8/8G0BLCZvb0VEhIQoS+3oDzEKWoDnRTFJNcjJ/krGTh2gFwRIE91LBKuD7PpqiYahGxGz7vo+tq4JkK5VAEmyJ71kg11qShglzg2uoDihQZRVPVfB8ryLtisXWvq2MHH+ECx2LlKtXgEeDiCr3oT2qVud6lDRkWUYOphlXzQoJkkHFssGIzSmI7aPruWwZ2Mp/3/1TfrTjR+wc3Mm/vOhfeO9ZbwHggp5zuar1Kq5fdD03LLmBtT1rKyDrwQc5DKSTzeAKkGY5RXQqlqTCxjN4rqlJ0FtQFBXFN3GcGtc1wLHKogigCVYRmLSnwJV1MZAPC9+16wPWaciHJMfFqZkvEoKC9lR74x6LiCkI7plaUCAHoGAwoMZOock4vr+Wa0WscEpLCYmjpoFtI2Wy+FIBx7OqAWf4HAgauP+gLEm/8IUvkA0eGl/4wheescm4Z6JxdGQMBgtm5Hs/3QiT/YpOX/w9kDN51/pF0SCxf71rL/90++6G63nLJfMjUNDdlKA1pdGU0GhJ6yztykTJfneTwfJYcv7KdXN45bo5E9b3P0+doLvJOC22mj1NCX49erLu7wbzFit6Jtf/t2V0dhwfn9Z3PXpgiIsWtU294DRjpvavYXi+j3oGFADigV1wLNJAk94A2KmqSNrc0OlD/Njx/cpk1/LEl2WVNaCiiJdaZJtpRD0FRnY+JNtQm1fT37YVpVyie95qlOYmmP3S2MaOUVrzafYM7SZrD7KoqRe0NF7xGLuO3sddx/fwrb4dAHQrTcxS8ygpD8zd0Ldb2G4+IXq5aDsf/4bHooQkff/rYeswNHUI2ZKswehWaF2LnpoLwWAkq1wgej05NUyBOitiCsLE8HQ0GYeRNFrJASUrjykXQFIqTIFbEqBgGi/P0IEIwJDCXogaUBBv8g6rneHfjarFDeRD6DoZBBCJ3F1qQUEMQEyIoL9D0ZuqPO9VWcVWM1EiKrZx4vH2fA/fszl//2dIbP1jsIai3xmAK6nBMClbXJ+SAlf9Eoz24FCYE/tD4qAgiHoDzPoKwo2tO92NpmiczJ9kfOAIkK4rHUpr4h6UJAlNFnMpbEMToKBYjM6B55qgBlOZw4iGl02fKVBkJRoYZ7lW1fXqei5Hx4+SlCTGrQIpV502U6CE14BR53qUxVRjyXeq5hRoshadf8m2qkDBaHmU7239Hjvu/RF9Wx9mS7bEzkorAzsGdsAqsX8Lm+Zx94vvrr+BwXYpukHaC1yxrAK671UKBKoBdowpUFPIWhLJ95HMcTzfq5ItlgMvfVmNybnquA/Jkix6WFBxJBcVcGKFhbqgwCqBGg4uqxzL0JLU8Zy6TEFbsm3i/RitO7j37DJQ6bmKAJ+kRkAXeNpMQd7K4/kekiRVZuCcfTaMjiJlx/DzZQHsa+VDnlNhZv+QmII/+qM/iv79tre97ZnaljMxSbRndJ46Vklcfd+nZLns7ssFFX0xSfc1586JBnl948EDfPrXO7Gc+p7H163sjkBBWE1vSWromszy7myU5HdljajyD/CGC+Zy04Xz+O6jh3n1eZWpvTOJK5d18ZNNR3nduVMPPZsqhOexRP94ecIQs9Hi1LKgtpTOcLE+9Vwb+wcKXLmsc+oFpxGZhErOdGhKTL59Z2LyGC4NgyST1JJojRpUa5KJ8MHn2x6eWRYvyKlAgSyLqpslKnC+pFUajQP/bVVWkTUdTAvLKpOkSbxcw2FKbp6i1sxQ0xp0PwezLoTuq5CBd39jPff3HWBe8zzeue6dfOR4EmV0N1x2PqgSFO4HcwTmJsHsg6aV2J4tnLl8H3nwCRgvgQUcrt4Nqe0CknM+BkC5lCdxz0tF0uy7Qteut8LACNgWFBdBZlVlINFpaDIOI6ll8CWFnJVH1m00Iy0SCXcQzCGwjEhnP1lkYzKxRMQUeFXzB6rsUcOfSTUJT200AgWGQdoXz8BI3x0HBb5fefnXgALf95Hc0He9ugdMlVVsJYPjFSs/9BzofwAG7hPszbrPiCqupJAuH0eyhkBJQccl0HUlT9HGIaWLi/Ui7VBhHGLnwYklK1HilgnYlhgoCH8XAkLP96J5EF3prqiAURw4jp9YgtSgnyAMTRGgwDQUAamqQEG5enugAgrUBtdc2AQfAwVAJDMxHVNUcoPoL/QLKaJyzAAAl6NJREFUQKXIFJ0yeNlpMwURKKjHFMgBU+CIpDY8XpF8yHMxSzmGlWG8ZtEUbzom773tvZx9EubZkEk18/pVL6Q328vqztW8dtVrK1PFprAkFdul0UQrNlC0C7R6TkU+pBjVPQWAkhD3lW7lsF1bAIcgymUBWnUjVlGvM6cAxDk1HRNH0gEXJ+hLCgFDFOEz1y6KB65iVBkICPmQVwUKHM+JZIFtyTbwguW9mns7vLbNElWgoFY+FMbTZArGTNE/k1ATlSJeby/09qIe34CPLPbDdyvbqWniOWO7wTPouVHEm3GZVlEUTpw4QVdXdXPp0NAQXV1duJNdzGdiyqiX7F+5vJO2tM5Q3uSHG47wL3ftoW/cxHI8/vF/dlZ9/pw5LVFinNSUCBC0pDS6A31+XKcfxivWzeYV62aT0BS+/fBB3lpnqFYY4U3heN4pAQIQLkSh5//piJsunMe/3b2P91+7pKry7vtUTQtuvC3Tv25PF1PWktQZK9pnQMHTjJHSCD6ySEb8BuexRhaiBudQLolKn6w0AAXh8yxMRpRKwmHCxOoRoBkpnHwB27aFw6NvA7p4QQTDqJ4cPswdR37FX7YuIUyrPn3tp9kxuIOuVBfzsrNRj9wFiW6YfwNk5sLeHrHgJS+KXoJWkIhpioZ0yfdBeQiMMixzYWynaGz2TGhZRTLVhA+YpRyU76xojsM4BBz6MbT8FF72eFQtXrf/U9D375DoEbKlRI/ogUj2QHIOJEVvT2XGwGSgIIkrqaieiexbIrkvHgXrkFhA7a2sb5LI6BnmNs8VzYongmRclavnD9QDKWGCMx1Q4HlViX7GF8luXVDgOJWG9hpQENqR+kgoWrXEUVM0PEnDyO2A0YdgbBvk9lTPazj774XEAtgx92YuWngdtJ0b7Uvh6KN4hX5carTisf2Osz7R8ytMlGLXfS1TMFISk5R1Racl0SI2SZKRxsYpqSVSLS3RZ+uBAl3RKVDADhlh1wVHHCffq2GiPK9iKalNUz4UygGNFOBN6Cs4kT8hvisEBe40ewp8FzWcf2PUSSglNWIKwsKA67lsPL6Rxzb+kP6H/gdL2o21Zj7XzXohnu/RnenmHevewSX9BuvVxSy6/GUoS5byq92/wvO94DjE3qfhgLbaiA3ratZbGJBkClYR2ylFbJCu6NU9BYCUbEGWZTS7gO3ZGMRAQSC/1PVYRb2OfAhEkcDExJE08F3cgCmYwChGTEFRWN3WyALDnoI4KBgpjeD7PiktJZ6p8aKM61buz2hOgSWumfC74qAgU7kOny5TEIKtOOCML+NJcsQw4bui+KBp4tnvOM8ZlgBOART4vl/356ZpotejTc/ElPHrrSf4+gMH6AuGa1mOx6d/XUn2v/OOi7h8aQeW62FIMkeGK968LSkt8tTvzBpVVfEXrZnFZUs66MwaU+rgfx86+dktCY6OlKZecBqhKjKvWNfLj584xmvOq8iVTqfS7eRYuQpIPd1oTmmMFm3mnj410vMyhkvD+NIUoKCmgVTCRZEV/KLQw2qKNjlTEL50YppYM5iEbShGFVDUjCQOYFuhLakFpHHMER46fB/f3PoDftR/hCuT8Mud/82b5gu3pMvmXcas7Cy29W8LtsUDVREJUnxCqFN5iYYvK101IHU2dErQ0QHnrArsCDXofSEAqZNbKQBlpwTrfwTFHTCyVSSg5UFI7RHSkybhkiESQ5/2kUdguAGT1n4R3PBIcGwt4XmvZUQfRqIWQMwSA8xkHTwTxbNp8Usw8iTomgBA+vSZw7U9a8U/jj0ZTKuVxbGWa0BB/IUcJjjTkQ+FLEFQ9UsHNoy2a2M6JkYIChynYn2oqhMSOccSlU9PMVAUTVT/dQEFVVnlnEP/Svf4hurtSHRB53roWg++LRxagNHWC6DjoupNDpIxt/Z1XocpqErcwu2PWdTGGyuhIh2KswQdpMBxGbfzpGKJVwgK4ixO5EDkO8IBplyGkli379ngexU3Jc+DcBrzVI3G4X0ZbLtqJIFCFSjwfK/imiQrWJ6H7ZhoU4ACx3OQfQ/ZCUFeY6ZA8h1+suMn3H3wbrb0baFgF5g1DpcNwcIWGLOKotHZc1Flla/d+DXhX9/XB7rouwgTeUUOpi6H4br1QUGMvWrWVfqRKToFrIAZUGVVrKuGKUBvRpZkNKdQ1TMCYAZMgRYHQHUajSHWdyJp4Jcj+dAEh7IIFARyO6UaXBmKgVzDFAwFrmzRVPoGz72o8u4E9sLxGQUgjqOuCmBQLFazBjMIvabAETLC8dAUDSSlwsb5LqBWmALPqfQ0PQdi2qDgS1/6EiCqpF/72tfIxB4Gruty3333cdZZZ53+LXweRK7ssOHQSNXPmpMi2e9pTmBolQfD1Wd18aM/uYRsQmXjoRHeeNH8huttTmrTdtT5fcRVy7v4/qMHn5YLTzzmt6d58sgoe/tzLJnuoIUZxIN7B7l2EvvVmUZLUuPY6OkBRc/X8HyP0fIoxnSZgrDC6LmC7i6ZuKFrTdiIHPfMnsAUVF4KxeB3UWNeEJqRogRYQUWvUB7l65v+kx8+9jlazaP0OyDLGtctvJJrFlxZvZlBUuAXi+JFaGgQtgWrqqhcx/S1kYZYMaqtDpWYg4hrgmKQSTSRV2RM14KOq8CeD9nlkF0MrgRHvgtGG1z+fkAkRxKwd9n/YXmmWTgxlU9C6QSUgn+nYv1CrgkDD4jq2LFfTDwH7Rej3vAwspoCJ8fqI1+l+WQSUr1gdkE5DQNboNgrkuLpypYcRzQWqko1A1CXKZiBfChMvjQhP1IkhZSWomgXyVt5jFR7AES8SpN6HS90L7+f1vwOMlYf3HYrjG6BVxyG1BxUWWUou4rW0n701rOheRUsfx9kl1VVNBxbvB/q9XeEmnw3nlDGJVNUKv9VUrCwiBcDBZF8KFi+Lx/0E2Qq7E2HpTEIjOk+PbGktRFTAKEtaUqAgrJYt+u5SL5b2SfXrbAtjSxwJ2MKrELUaAtinkIok0knm/AlmVK5gDYN+ZDku8iOFySXdYqdQU+B7Dvcvv92Hj/+OCCS2RfPvYI3ze5iXWcLO1c0MyDJ1T0jsft0gqxLiiXBrlvVfwKIay28/3Wd5oSOLylYjkneHAVC5yE71nQbgBqjBUVSUO0SjlMCKjI9M2iG1Y1YJbyOJSnEphoHUjzPzle2Px6RfGhikzFUGo1dz8VTZGRqmozj6wmHoMVD1gXzE05E9mtAAcCll4rPnmLBuhboNGIKICLAgoKDUS0fmoZ5wrMlpg0KvvCFLwCCKfjKV76CEusW13WdBQsW8JWvfOX0b+HzIC5Z3M7/fdO5UcX/t9tP8o7LF9VdtisrbDoPDBaY3XpqlNizJRKaQn/OIn0aXVVvPKeXf7lrL39yZRpdlWlAbJ1SjJVsWqaYvDyTaEnpbJtmg/OZqB/jQdOcohqiijNN+RC+gyIpeEUbNxX7TLlcTTvXTvlVK/dcKajw1VaPdF3837ZdLM/iiq9fzKbxflbrMD+TZcWCK/nAklfzqtaMSOZjWtlIk1suAz4YekWLqigCFMRejlWuJ2bM6lBWRIXQKYkmV8UgrafxVEVY69l2xXlIzVZeok6+qtHYR2K8+3qYc0H94xq/wXwTlr43GIRmBsAhBiCSQv6kaRn80km6xx5HDs9XAdgF7AFGEXr56x+qrHvjnwtZUsQ+9EQ2rjiOoOtDG9bo3E0iH5oJUxBL9DN6JgIF7al2kWyUyxVQECYfg4/Bvq/BwH2kxnextPZ7hh6PQMH+7leQ77yGC5taxfY1LZ+wWXUr/UGEQNKu0nNXg5PpgoL4sKZwPyVJqhru1WbKDAJDeuUYhkPdJEmqSpyiBNK1KnKlUgk3EVzvvltpNHaDOReKXF0xr9rZ2LIxyZaWSIFFFVNwMi/MJ7rT3ahFlTIyZbNIUyNAGIQAKw6y64nz0QAUKLKC5Ltcu/BalrcvZ/389bx93dtR8gW4/edQ3o8U9k/4MRlMzJI0BAvhEDqxblnsn1dHXhs2s8syaBqqrGJoaRzTZLAg9lcUCELpkCaeBSAYDzmB5Pm45jDEbFZNU1TzjXryoUZMQZA+ek4e0CYBBUUgMSExVmUVOdhHS/LQfY+RkgC/EVMQHKdJQUHIFIT3dAisQNy7pzC0LNrXmn2vLQBB5XhUQEEogQtAgfMHyhQcOHAAgKuvvpqf/OQntLZOf4rtmZg85ralImcfAG0arjL94+Uq3/7naqzubWLHwOnL3CVJ4k0XzeO/Hj3EH1+2cOoPTDM8zz+tUiQQTM5YafIX1JmYPMLKUkuyHXAag4Ja//mgQumVbNzEJKAgfDGHFVE1LZJtWacUDFqK9xMAjAVNo5Zto8s6L1hwJbmjm/jE2ldwTe85PFa0sY12dMWPtiVsgK0CBb4r9MxhglTHiSOsjOqKXgfAZAJQkAejjbSWFrMKCiV8y0Jyg0RWy1YacH1bJPRKYnqNxvGbwnOh51qhd0/VGRYYrM/Qmyjjc7j9OuZmukVSOHocju0BewSkMZHsh+H7sOffqt2E4tG/DjpuEvvtWbD5b0R11PfEMXTLwoUn0T39OQWOU9dNKGtk6S/0k7NiIGB4H2x/BKw50B1U1AsHYJ/wmfeRKOmdjDWdw6yzbobOKyKApMoqvqRgysHzv4HrzmSgoK58qKbZO5SLVFU+w/0Kq8+qWsUUhNKbtmRb1eeaTOGYVkzpFKwCaT0dsQThtOnoK2IgI9J1l0q4SbGMFIDzaDt8T1xT0wEFYb+HLGMEFe4QFPi+H4GCWdlZmAWPoiRTNsen7inwXWTfFfIhSZlYrQdhSSoJpuDSucJyuDu8ljWhtcdxkILz4HqTMwUTXHtct36zcQDgvBibmTKaGDeHGSr0g5QMngV1qvOKAloavDKuOVi1WrNcQAaMRMAw+n61k08sIp19cC959jj4bZP3FJCYwBRIkoTmSbgIUFAqj+H5HrqiV7FNEwo60c+NynTyOFPQwNL3VGJmTEHwPA+Pm66L55Hn81waCTbjLb377gY2WWfiGY94TtqXM+v68j/X4gUrOrEOnN51tmcMFnVmeHT/0JRNxtON7SfGWdV7eqdHK7LUsEfnTEwvwspSc6IN3P7GziK1sgPfQfZBMh1RrWtqgvHxiX0FtYm2JEP3NQCUT2wCKtWjh488zGcf+iw77/9vPjP/nWQtMfX6o5f/JZ9uX4ty8nZGiv04SoqM0YxEMBE21KAyBVNQBxRUWRDWAwUMCFBAAF40DfwipfwgKd2sLGebAQtiivkGyZ6ounzaLEmD9WiJLsqSzMnO61lwzvtFJdN1wb5NLHfD9SDHzqPvwJqPi4FcpRPVMiZ7HJSA6VBkwQ7s+FyDpF8SoGXZ+yu/f+qTMO+1lep8ZG3oVa6FGCjIaCmyxQOkR++B3Ufg4TthcFj4gva+Bc66RCzYdSWs+N/QeQVj5TF2D+3GbTuPWfNeUbVFYUJRVNKQ6o4sRGsjmmYsT0yWw585caag5hw0TD5D+ZNlgapGSbzruVFS3ZWulkzK4znSeprBbIqh0lAVKIhbxUKtfCgoJBaLeO1imzUpZtzgusAMmIIQFGha9D1hj81oeZSyU0aVVTpSHeRSJU5IgikQYNFr6Abjei4SLrI7CSiQQ1BQSdwj/bmui3va85G8QNoVL1bEmYKp/P1rIwCqXmyb0kYT44BpF0BPBs+CiROEkWUkLYvklfCs6nlSllUkQRwUxO6/BkyBhdD1e66N4lszlg8BVaBgLG5FWm899ZgCx50oH6pzj5xqTGAK6vQUREA6fJf7lfMbzbN2nxvOQ3CK8OXo0aP8/Oc/5/Dhw1hWdfXmlltuOS0b9nwNz/OnpbEfK1q0pp69/QLTDUmSTnsFHuDKZZ388x17WNw19UCy6cQTh0e46cJ5p2VdZ+L0RRVTkO+ffk+B76KVHMpIOKrcGBTUNhpDlEyUArePew/ey1t/+lYePPIgAIsUODh6kPmOoOezWiKowNuUnDKO3Bz0PxQEiAk1qNQyBUFPQVw+FN8HYo3Gil6xogwTWzWotgUe+ZIkYSQzuCNjlPInSbURsB4qeCXBgriWsFxN9jwjlqQARrqX/U1raUl1V17gilKRCVh2NVsja7Dqr+qvzCnCHb+BkSNBhbUIK/5CAIix7VDuF6DIHBTHOXSP8h2RGD71CVG5rwUFIBoUoQIKxncz5/aLmBcMrBP7jKhMGsvA6Kgsm+yBdZ8DwN37nwBIWmyfgggTCsf3BMPSIKKBWpPJh5CDDWIiU9AI4IXyJ0to/uO/HyyKanJ3OuYGVSiAbZNNNOOkkwyXhpnXPK8yo6BmTsiEngKAYhE36JPR4s/+KvnQNKyF64CCECRH0qFMN7Ikk001I6HgucItKOG7jUFBvKdAbQQKVGRJRqoHChQlGqSnuGIHGzMFYnuVqn6QSWxJQ1AQu04zegtAtC1CPjRxgjCKgqxmwD2Jb1Z6GG3XxguOZSQfipyHlAnHKWpG9x0IZmwobnHitRVuo11nW4L9U4P735I8hoo1Tca166llCuSgEOLVMgWnDxRIkhRN8Yap5EMx5jfaxpA9+ANmCu68805uvPFGFi5cyK5du1i9ejUHDx7E933OPbfxQ+1MTC/KjovRwAlIkiRcz0eRJbzTOM34VGK64OX3Ge++chFmgxkNtaHIErbrNZRu2a4/LVnXTOMMT3Dq4XouHakORsojginIM7V8KHyxeA5aWSQGdiohnFGgIhmJvqSm0TgIy7X48fYfc+v2WzmWOwaIpODNa97MB3tfRXHDIxX3Ib+i3y/6EsiyqKhag9RKnqpBgQcJY1L5UHWjcSBpiZiCIEFzKj70RjJLEbDG+6AtI/oJwv1UM8BYNIdhMslK3ZgmKOhOd3M01cmC1hp5n2FUZDuZiQl03VBToGQqTAHAOZ8Uf/cHPv/tF0KiU8xBsHPC9jMc9LX0f0F2SWwfTMjtgOEtcHgP2LNg2WfE7zILkTwLR04ynDmL9vmvQpm3AAaTFRvWWv25a+J5ojdDVhuDAs/3JgyUisd05ENOFSio6SkI5UO1AC8OCqhOgnzfJ6klq9yEGBPsVrZjNshEiVy9JmOonggb9RQUizgBCK4LCuSZMwVG0EMR3g+hFWlPRsi0ZFUjbWTAFMPnEp7dsJHd9UL5kAeaOql8SIpV1KucahIq5EApudDUuKfACedX1GMK6vUUhPKh2DZlAqvYCBSoBrgBC1kjH5K0DLg+rlMQbIKSoOSUkFwhp1T04Lpp0E8ANVOvDQEKVLdUnylw7UrlvBYUOA5q2HOCW7/JOH48GjEFfsAUNJA7Pd3QFA3Hc0ioibr3ZwUk1ciHAEKJqPdsz5YqMeOj95GPfIQPfehDfOITnyCbzfLjH/+Yrq4u3vSmN/HCF77wmdjG51UULZeUXv+B2JrSGSladGR+/70EBcshfRqmET+TkdCUaVuthse2KzvRJaBoOSR/D5atZ2LyUGSFdbPWif8EDhgzYQqUoo2PjJ2MNaNNhykAPM/jW5u/JQCJ0cx7zn8P77/o/czKzsI7eoQNPILv+tiejebZQuYC5DwJ5CB5slXArHqJRPKQUgnwhFVn3H0I6oICwRSEL9+4fAjBFARyiWQICgoDQEb0E4T7qWbEy8saBd+vr0NvFF5QeYcpQUFaT7N+/vqJv0gkRCV6eHiil3AqVQFuteE4gu1QlYpjCsQsSQMJVqIT9BYBCvygifTcW+Dk7bDnywJEDD0KWyzB+huAMruS6Msa0oue4O7+/ZRdhyvmX0HL8WEY2Vb5zlpQ4BSEu4qso9dJsOKJVDgPoO4uTtZoHMqHUIjkCkp9pmDCuaxnSxokQVDDEkAECjJds5Gk4xTtIiW71BAUVM09CEGB5+EGTfFqPFn2PODUQEGcKciZOQpWAVmSK9InRSGtpSl5EnmrQPskfQUiybVFkVeSp5YPBUYBVeeuOQMDoBXsaJ1AoNUP9llVcewGsq5wH2ujjnxIUxNiTkkACA3FCIZ6UZ2IyzKKrON5hmAuAplgyS4huULLX5HPTQIKQg2954DaKuxWPac+KPCsgP0xJjIzjoMmq/iKzHB5BNsV06mbjKbq5Sabaux4MaYgxm6cxtBkjRKluv0EEANJtfIh3wc5ONfOcwcUzLj0uWPHjmjCsaqqlEolMpkMn/jEJ/jMZz4z4w04duwYb37zm2lvbyeVSrF27Vo2btwY/d73fT72sY/R29tLMpnkqquuYtu2bVXrME2T973vfXR0dJBOp7nxxhs5evTojLfl2RClSUBBe0ZnKB9WdH6XWzUxxkp/WEO32tI6I4X6zYeP7h/m4kXPzDCB586j4lke4Ytg2qDAQS3Z+JKElTIqCWeDnoIThT4+ds/HIhmAj88b17yRd6x7B4c/cJhPv+DTzMrOAkDWdNFA6gbVNM8CR1Txx4PZBhk9U3ebZUkG30eyLPFSSdS4D8X3gQaNxuFLVEmI7/D9SE6QTIkXrl0IGg3VGChQEsIK0nfBydV3rGkUYQIuKaeu6Q0T1J074cEHq//ccUdlFkBtuEGjtjwN96F4FdGzxYN0w5/Ctn+AgfvFfiRbofNymPduWPGX1Yl+03LShugtylv5ic4mdUCB53s4slE3oZckKUrqa73jq1YzDfchJ/46rwFm4XVblymAurMKYGI/AaOjYjvaOmgOjsNAcYBSIBFpBAos1xLnJwAGXmCwoJ5m+ZDjORFz15HqqBwvRSGtp/GRKJTHG/ceIY6VYllISCIpVusUvwJQAGLmSXxfAWgOJpznzWidYgPjVWSlMj05fs9MBxTEt0lSSWsZpPjgsqinoFo+pMoKLgaO70SMYNkpI7mumHUSTQZ2ov2sjSr2R8uKwWuNmALPEol7nX4CXDEfxleUyPq2NdE6sRo/GVPwDMuHoLK/9aRDULlfPCRxPsPt8EzQFPGMcZ87b/oZl3rT6TRmcGH29vayb98+Vq1aBcDg4OBkH50QIyMjXHbZZVx99dX8+te/pquri3379tESm5L42c9+lltuuYVvfvObLFu2jE9+8pNcd9117Nq1i2wwkOIDH/gAv/jFL/j+979Pe3s7H/rQh3jpS1/Kxo0bq6xTnwtRtFySWv3T0pHR6R83gexptdqsDQkhD5qsSXesZNP8B9DTEIaYGF3f3WT/YIGrlnfW/d3TjTPyodMU4QvJ96osPqOorTb5LlrZwZdkrJReFxSU7BKbDz/EAw99lR+MPMCGWR5rutbw6pWvpuSUuGHxDaS0FE2JmspWkKS4nonlWaQCpsDyLExJDDpL6+nYNlcSBVmSkW0H33VExhTvKajZB9/3J280liQhIbLHBZOipkkmxbY6xUBTHDIFriuWDxI9rJGZNRrHq/KnGvPmCWvPWtlEqSR+NjZWqTZH3xue70A+FG6HF3s5V4ECKeihcAQoUAyY9zooHhGDwjrXw6bjor8kjJpEP6tnGSoOBaCgo3p76jEFvourJBoeR03WcD23yrO+NqYjH7LiJYaZ9BTABKYAxLXYkarZv4ApoLmZNrON0fIoh0bFNGpd0ScwHeH//YB50pJJ4T5UFDmEFn8CRvIhZcZMgaaIJN3zPY6MHQGIQHr4ubSWph+ZklXA9+yGBRnHc1BsC1mWxeDAehU4SUYOjqXku/iSWr3vTaKqrOZMiA0oi+5RScgIGzaAx5eNR3Ce3BpQkNKSyGbQF6DGewqq5UOKpOJKMaYA0Rslux66kohJl+xo3bVRzRRkcTwH1Suh1S4bMQVufZ9+J7CFVivHYUI/AUzSUxDKh3hmQUGwv/WajEEAOkmS8CUB8pTwPnZNsV2SOnHbn8UxY1Bw8cUX8+CDD7Jy5Upe8pKX8KEPfYitW7fyk5/8hIsvvnhG6/rMZz7D3Llz+cY3vhH9bMGCBdG/fd/ni1/8In/zN3/Dq14lpn5+61vforu7m+9+97u8+93vZmxsjK9//ev853/+Jy94wQsA+M53vsPcuXO54447uOGGGyZ8r2maEbABGA9eALZtY9uNqzW/ixgvltFlqe52NBkyW8eK2LaN67rP2LYmVInRQplsovHlMZIv05bSn/Y2hJ//fR/3rC6xc7yIbVcneGMlcaydZ+imPtXz+Eye/1ON3+u59D0kN0iWrfJEa0fPQwr06r5tI1klKJi4roatydiKIn6fz+NZFnccuIOP3vNRxrc9wVmDYDXDtQuupSvZhW3bjJfGcVwHVVMn7q/vIyPj2i4ls0RGL4Jvky/nKfs6CUnHdVw81wfXEdurBjIDx8UrFnFcG1dV8T0X33EFUvd9JMfBL5fBtrFdG9sRn5M8CadcBkdowaOESUogucP45RFQ29D0NJ5n4RTHxWd9QyxrmmL/jZTYpmI/ZSsASO40zqlZEMdflvFP9fy3tMBll038+RNPIB0/jj82Bu01emPLEtvtIZo7rZL4frcktkeSRa4Qq8JLnhQc9xJgwMq/q1qlJJ2oeon7slw5noAhGziuw0hhBDvbJb6/wbKYY1i2hekbeK5X/zh64LgOJbNESqkvUShbZRzXqbsOz/VwXAfTcXEU4azje9XbUbJK0XdVfV6SxDUVNBCHx8dxHbpSXXiuh+cGCW2xiFQqiXOcSNDkNeG4DoMB69SkNdXdP9/zcX2XolkkpWlIjoNVKOLqLrixd65pIrsOPjK+61Ufx2hnY/dxsSi2HcC2kZGxXIu8K6RMbXpb1faosg7IOKbJSGGArDoxAfV8cSx9s4Tv+Tiq2vB69n3hHuQ5Jo6iIHmV97ZkKEiSj29J+Lk85bay+F2pJLZf0/Btu+55lQKL2PA+j4dUKOC6Lp6mVfbN9TBkA9ct4LgOsuPh2OXg2CuVdXge+GB6Gqpj4ZQG8S2L8dI4nmWhKFkhgbFtsIpIroPvSRPPQ3i9eiVsX8NyHDzXBqdcff49D8kuIvk2nq9OXE+phORLOJJYH0BWzU68hoJzPuF4eDKybYEv4/k+OKVgm/36184pRlbLctQ9SrPW3PA5KPkStudjWiaSHWynmRcjE3wZr1isu02/q3fmTNY/Y1Bwyy23kM+Lm+5jH/sY+XyeH/zgByxZsiQacDbd+PnPf84NN9zAa1/7Wu69915mz57Ne9/7Xm6++WZAzEY4efIk119/ffQZwzC48soreeihh3j3u9/Nxo0bsW27apne3l5Wr17NQw89VBcUfPrTn+bjH//4hJ//9re/JZWq/1D+XcXuMYkmzedonc3wfHioT8I5tIndgxK3DT/1jGzDzmGJ4gGflklaFzYPSczP+Ow5Te0Nt99+++lZ0SmG68EjAxL+4UrlquzCXcdlrpvtcdtt2yb59KnHtpMSvxp8asZysG0nJW4bembO/9ON39e57HY2ADCgOHhSTcVybIzWXbtwUimGxsboyT2CcfAgexydoxsepS81SveGDZS8Eu/a9mfstUX18ywPFicX8dqFr6a55TKGtwxz25bbOGGe4Ej5CO1aO6NbR6u+SzFN3F17yHujDDeP06aJdY3Y4zxqZWnV2ihtL9Hi7sXwhxmXByjJQrtteib7jjxO7sBxUm0JckmHPkUCSSJ94gSZI0coHTzI+OHDlNwSW/NbUSQFeY9M+9atqKUSI/k8VpMAtxnvGGnvGCXpEOPKQvTRUXL7dtOcHGXg8Y2MB1LFxNAQzfv24TfJSCUPh6fYUBCJxb133zulhCjhDdLs7ceSmhlRck/jLE6M7JEjpE6coHj0KLl51Q5gsmnSuXkzimThKjqepDOgFFD9Au3utuD/1etrd59C9YuMKDksaaLNcMvu3RiBTAZgwHHwYgzAmDPGrsIuknKSgcQxujZtin7X73n4sSpuu/sUQ+UDbHPSHNgjsd/YP+H7tuW3UXALjG8fp0VrqXsMdhV2MeaMMZQcYoe+o+p3BbfAtvw2dFlHSzWhUWBI9qsqpptzm/n/7b13mBzVme//PRW6Ok1PlGYUUUAEWcJEC0QSJhpjrhffix/MggN3lzW2yRevr70GhytY79pgg2ENxjjusg6wP+56rw02mDUrjDFCRiIqCyVGYfJ0qqrz++PUqa7qrk4znWbm/TzPPDPTXV11uk5VnfM9bwKA5559DnFPwHPknXeQ2LkT6W3bMOi43O5N78Xu1G4sjSzFwT/nrP/hw4fRvmULzFgMhyCsDy+P5L77rNCsgntBHjttpzH++jh63xlCfM8eHGwfwcCc/dDUMWzbIibn0f37MW/H6zC7wthtP40sK0y5HRoeRucbb8CMRGDGYggfPIiRd97B+LZt2DS6CeNO4G6b2gZls98NZfbLLyM5dgDvtA1jW/8vETW2Fuzf5CbWD6/HUUNbMGsPx9A7HPv5fwT2Sae5ATvHt2AnTyKJKKw3Lfc+6bJeReeet7F7wMQb4wPYs30IbxhvQBsbQ/err8IOhXDAsvB26m3sS+/D7tBu7IkIt6f2bdty32vOHN8xZ23YACWTgb18ufucjdgHELU2483xfuxnIwi9lUa3tREcGvo1T82IwUFE39iIt9h+RBlHelcaB9UxvDq+E7Nefx0p9OAV5WmY8bj73BhXdmFE2Rd4jgDAetPC6NhmwB7B23uehKEvcLdTk0kcsekVaOoo9sRewJiyy7ef8OHD0N58FVv0AexCEgwMPMH9mZgAxPbsQXzPHiR37cLwjh3u68zK4Ki3NgMA3nry14ipBzxt3hvYZxOFc44XN79Y9P1XRl5BzN4LLRwBtH4MqzsRtg+g9+03oO3LoH/4aYxsLbzeJPUeM8dlJrUKqFoULFmSq7QbjUZx//33V7sLl23btuGBBx7AzTffjP/9v/83/vjHP+L666+HYRi4+uqrsX+/k1ZMFoRx6O3txc6dYqDdv38/QqFQQTG13t5e9/P5fO5zn8PNN9/s/j88PIwFCxbgggsuQCKRCPxMozDe6McxfW2Y1xFsqhp6YRdOXNaDjoNjWHNUfVxaOrcdQk/cwLLZxTOAjK/fg/ev6EOkSPxDpWSzWTz11FM4//zzoQcFdDWQoRd24eJVYtKRzFj4zu+34x8+vnjS37EUmQ17cdYxs0taZYI47Glrq9DsvmT7FICb4LPPyWXekQwMgLW1AdEo+HvfC/bnAYyPJDEaacesU07EOYvPAdN18EwG8/f8J/aOHMA5i87BVcechMWHbbz7tMugvGuFu7tN/ZvQO9SLpZ1LcWzPsf5jZTLYm+rHvpG30XNMr5tlZ+voYaRYV+4zAy+DJfeAJ44F4ksBiBSj//XcANoVA0cv7AGOPxp8zsVivzt2gG3aBMyZA37SSTicPAxjt4GYHsM5i84BMwwgmQQ//XRAPg+Te8AGXgZC3eA9pwEDA9g8uhHc3otZJ5+KzvlOcohdu8A6O4FZXcCCw7BsC+8Mm1j/54246IKLYITKqP/RbWDDXeCReUDnCRPqv6LI793XB37yyf73RkbAdF0E9B0vAlT5nPcB6QNghyKAngCf5Q9qZgc7gMxh8M4TgchcFDBnDtiePe6//OKLfdmnUmYKv9n+GzAwXLj0Iqia5rqs8Ysv9rmbsH0KthwKgWnzcGzfKVjUsajgcF27u3AweRAn9J2AeW3zAk9Bx9sdOJw6jJPmnIQ5cf9EcSwzhsjOCDRFwxlLg5N92G/a+NP6P+GCcy9AR6wj98bevWDr1wPd3eCniRoLNreRzCYL0ovi9dfBOjrAFy4EjjtOtGtnh1vIbXnPcizpXIJ84jvjGM4M4z1z34PZg1mwl1/Gbns39s2NozuxBIuPcq7vzZuhhPaB9yVw7NkXAXpAXZiBAbB4XASet7UB77wDftxxwMKF6N7TjQPjB4q2hYVCeGfHOOKLLEQWH4Njjri4YPfJbBLKDgVzt1lYFlXAF60CP6twOwDAgQT0nWl0R49EWu/E+498v5sRkPVHgEQcsR3D0LtjmH3qGTim5xjg0CGwSASIx8HXrMHG/o3YObQTy7qW4ehuJy3uK6+A7doFftRRwFFH+b8DACubxZO2nXvOJveCDXTjaFsB7z4NnYoJdsgAtDbw2WfnPnzoELKxCJSRN8CP1nFy7zHgHccj1N+F2OgYlrcvQ/z894nzOrQJbGwHePxIIHGMrw2ccyhbxP1w/uLzsfGNPUBqL45a9B4kejz3fjIJJb0dsEdx5LkXAZG8a3vXLoxFNah8H2YftwwdRgfOWHhG4XneuhXs9dfB580DTvDsP5uFMrgB4BxLLz4fSO4EG90GHl8CJJYH91mdSOxKIDP8JlZGDLR3LQc6TwRGNoNtygJdSRx91Kn+trtfoTFj5rDXHbIMExIFL774IrrzzLiDg4M48cQTsW1b4UpIMWzbxsknn4y1a9cCAE444QS8+uqreOCBB3D11Ve72+Wn3uScl03HWWobwzBgBJS+1nW96RPTjM2QiIaLtkNVVRxOWpjTEatbWztiYaQtXnL/WRtoixo1S4vaCudeVVXouo60aeG767bjb9YcibY6B1N3t4UxluXoaqvuOLKtrUjT+lI3AAuAFpAxJBx2/DuZyFKTTCNtp/Hv+3+P7/1/D+DNT7+JzngcGBnBd877JpKdcewa2oW2t3YCh9/BgDWMPs8+TZjQVA2JSKLwu6oqInoEihKCbVnQVPGYTSmiYmxntFN8JhQBMhqgslx7FSBk2tAYgxIxoGih3HuRSM6/VtfB0xyaqiFqRMX+GBPvRyK5z/AOQNUApMRr0ShiKkMqC6TVUK7tsk5AOAYYFqz0YYRZCgpTYISM8v2pcHGcUDQ4W8tkSCRE27LZwn0rinjP0AHVMZGrSq49ekB79Ahg5Z13L4bhO8/5wcS6riOsi4rPGWTRFouJWBTD8McUWGmRykNhYHoM4VDwcz0cCkPLaICC4udZATRVQyQUKdgmzMLQVE1UiA34POfcTSkSMfI+H4s56Rxt37kIFIHj42Lbnh5329lts5EcFK5JnbHOwONHjahYwVcAvaMD0DQoIyZURYWhKrnPKIqY9Wq6uJeDzoX3Pubcd71HjSi0tOi3BZ0LCttiGIhFElD5EFLmaGBb0zwNTdVgcC6Cf6Px4tdzKApN1aArgBKKIOTte8aBznboe7KIjKagas7z2r1exfdjCivsV/kdlbznWDYrXlNV2IqSe86aYUDVMCvSASRmA2O7xLVvtPk/bxgiCQIYUqEEmMKg8jFkeRYaB6KhiIj50HVxvZS4nyOhiAiMVwFTi8BQVISVrP+ccg4wC4ACNdRWuB/GENbDUBCCpmqY3TY7+PqXzz2Wd7+apogJgglVY+K+VzVAD9f+GVSGiBGBpYXAVAZdcdqp2M6zxPE+KNGmeo+Z1ey76uxDO3bsgBUQAJNOp7HHs7pSCXPmzMHy5X5Fd+yxx2LXLmFm6usTOYbzV/z7+/td60FfXx8ymQwGBgaKbjOVSGbMotmHABFT0z+cRm+iSHq+GhA3NIymy/vQN7NOQr3IWjbuf2Yrrjl9cd0FAQB0REMYHG+t2IApS6kMRJ7gvdf7N+Ff/vA9PLT+QTy29xkcGD+An2z8iRtsfFR8oXtt684jct/YO77dJU0xEQprAfehokDXnbzp2VxbRpxc1W6GliLZh5R0BgAHNzzpSPO+A5BXuMzzui99qnQVsdIieFDXEWYczLQw5s2dLYN7FQUIiTSDIXMMKiq0klVYo2BCeIpeFSD9+XUjt0LPs6UDn2W8SWDVY/izzeQHDjvIPvRlIAoIMgYAk4lg8aKBxrL40QQDjaW7BfcGtAZ81nssl4BA46KMOG5hHmt6dyS3OBjTY/mfEIfwZiCKiW3sdBYwbWjeQGOZkrTSisZu3+u+4ySMRHD6SFVFRI+D2TbG00OB58qtMCz3HSoxznrSkvqCjDOD4vrraAeUMNSxJKysc349NQoAVJd9SPaRpvnv8fyEBUGZh5z9qooKxjksNQKLW8imD8O2TDCbi2ujgpSkgCc3v5VF2nHV1GRws/d7yPsQAfsxRRpT23FxCgwylvsBCs+HaYr2qarI9FOnOgWVoCkabDgB07If7LRYgFL0msY41JuKz94TTzzh/v3rX/8a7e05055lWfjtb3/rCxKuhNNPPx1vvvmm77W33noLRxxxBABg8eLF6Ovrw1NPPYUTHNNLJpPBs88+66Y/Pemkk6DrOp566ilcfvnlAIB9+/Zh06ZN+NrXvlZVe1qBtGnD0EprtcNjaXTH6jD4OsQNDaOpqRMtXyssm+OB323FVacd0bDMSh0RHXsGi6RaJKpDTiTsQlHAVRWv9b+Kx15/DGtffBHX7weiNtDXdyQuP/XDuO6U64A/vyI2TqUwzIW5dWF8HvZhHw5nhpDMJt20dClTDLzFMlKEDDEpkRXfTdvEGBf3dU4UyAE4L/tQOgMGDjukQfWm58vLwuErXMZ5YUpSQEwYVEOIAnMM0BMwnInYqEew+ARFKAHTNqFbo9AqHWDrKQpkxqFsVnx37/fzfmemAzzjFCYr0R450ZmkKBhMDVYkCjJMHK+YKHCLj00y+xDgFN7KK7IoMw8pTClM91ipKOA8V9jPkwGqO9oNxRE8xfK4+0SBrgOhECwwqKkMVMZz2cIsJ+d/paJAttkRBT3RHmwf2I7F+UXxPJ81tCg0rgC2ieH0MDqcwl+S3cMirsKwHLESCr6/AQAsV9XYJwrGncXRzoVg0UGwUS5Suc5FgSioKvuQPP+Om6C3HQByz5GgzEOe/epcgamEYVoW7NQhMAtu9ib32G7O/9LXbNpKI+PcY6qdN47xLHJpEouIAlWD5hQFKyoK5P0YKAo0QLVyWY6AmmcfqgRd0UX2ITvtEWdpUfxO4ZWJ7hahYlHwwQ9+EIBYHZZ1CiS6rmPRokX4+te/XtXBb7rpJqxevRpr167F5Zdfjj/+8Y948MEH8eCDD7rHuvHGG7F27VosW7YMy5Ytw9q1axGNRvGRj3wEANDe3o5rrrkGt9xyC7q7u9HV1YVbb70VK1eudLMRTTXKrcDbHCXThU6WeLgyS8F0Q1MYPnzKgoYWh+uIhvDq3sr9/YgSlLAUvJM6iM8//XlY3EYoDpyQOBqnHbMap5x+Iax4VLhYOJYCnkxiGKJPuowOjBkJDDOGt4ffxlHdR8HmtrtKXzR3dVhMkEzTAgdHykrBVKMIO4WG/O3N3WuMMWgZE8JSoPkHuLzJgm9C4R0w89Mwa3FHFIi0pCFNvD+S8gxU+ZYCbkG3RqGyChMv1FMUaJqY+DnZW9DmCUD1FmxTdNGOcqKASdeqIs+4CkSBrPI7khkpKwqyzkqqWqR+w2RFAWPMTcdp2maBNUBeqzoLmJjJNsusM8XcDGTdDMDnThXWwli9YLWbljEIX157AIjFYAFQklkherkp+sSUq9MViALOC0RBX7wPFy+7uOh5FsJRQUyNYJBbGEwN+kTBcHoY2we3A5yjL9QJIFORpcAnCjgHko4oiM4H79wF9APKoJPKNc+a51omvP0q41eKWQpCIb8ocC0FzvYlLAUAoHEGU43A4kmY2RQU0xDtV5TcseW1WMRSIL9vMpuEpYTBwaBCZACCXCix00LgcVVMWvJx7t3jF5wMa+FSkUo1CNnn+RkATee6UU3xfGumKFB1cKaI+g/eftCFW+C0tBTYzqCxePFivPjii+jp6SnzifKccsopePzxx/G5z30OX/7yl7F48WLcc889uPLKK91tbrvtNiSTSVx33XUYGBjAqlWr8OSTT7o1CgDg7rvvhqZpuPzyy5FMJnHuuefi+9///pSrUQC0RjGriK4imS2cWE13rjptUcOP2R7RMZSs7oHB61mkYirjEQXJbBJPb38a7z/q/QCAvvZ5OHfxuVCYgnuu/Fssfe63gBrCK1ExcJq2CdURBanRQViGBYUpiCoGemI9eFvleHtIiAJZqElhStEKtHooAjAG22bI2lkkLQu2ovuLO+UP5g5qJgsm3YdKWAp8rgflREH6kKhVoEYRCkdgKxpSqXHY3BYrhN7Jip6AxTkUbiHMKnwO1FMUAMKFaGhIuBB5RYHXUuBaADJlLAVVuA8FxJ4B+e5DTsKHfFFgVWcpKFa8zOsWVGzCqyoqbMvOVc71IF3dQizoXDg+7qYpJp3FRIF3lTpv8t8Z6Qz4QA5fVWNAiALOwVJZce3ZWdF3lpyIlihe5gn4doWsp81FBQEgrm2mIqoYYBCiwMvGdzaCc4658dloY1EAGSBcQhQrusj8xT2VqNMHnFiSEGD0gHWK1W824ByriKVADRL/+fU6vH3gJX9xwRUFeQsWzrnTmAoOFSY0pM1x6Bmn/d7nBi/tPiSv2aSZFGl/tago9maO5ESBJdLXgocKBQ7gnot4tAMIBwSVS0q5DzEd0NItZCmwcoJKug+xgLSuLUzVzlfbt2+vaQMuueQSXHLJJUXfZ4zhjjvuwB133FF0m3A4jHvvvRf33ntvTdvWioQ1FQPj9TVFTcdYgVZFVZjIsVwFWYtDU4oMmjMZpmI4PYzvPf+PWLv+xzgwfgCvXvcqls9aDjCGT596PRjnAJxJTCwGXTeQtbIwbROGIwrGRg8D3SrajDYwztEZ7oSqjmAsO47DycOuKCtmJQAApuvQFQ1pWxQYG+NioPKJgiDLhmVBNUVBLkvXSosCZ5VRYUrBZMOH7hzTHAXMCLRQGFyJQDEtjGXGxKq311LAFKSdCUUU6cL95cNtj8tCnURBJCJEQX5VY5+lwDm2nRUTM6C0+9AkLAVeUcDnnwA2NgY4bq+5tom2pp1+LlW8DChuKfC+XmwfKlORRTZwH1LEhooJtlAoJwpiwXEBblG/IiKpFD73IQCIx2FxC0raFpN42Q+m9JlXy1c09lJpEKUrCiJg3PSJgt3Du3E4eRiqomJ59zLAfFa0oVTWrSBLwbhwP0J0nvi8kwWMDQVbCibiPsQLAnbl4gLPuxeDLQWqooJZNrKqgYydhpblCKmG/7ovF1PgWH/kteXGLmVHgLBTBdtKOQUFS4uCwGeWl2LFy6T7kCaLpElR2fiYAl3VweGIAm4JF1bbdN2HxtOjeHXXH9AVn4WlXUsb3r5qqOjsfetb38Jf//VfIxwO41vf+lbJba+//vqaNIwIpqcthK0HRpvdDKKJZCwboTJxJzONbQPb8LN1X8eLW/4/vJTM4IAJHNF+BPaO7BWiAGKijkwGGDgsPhSPQVM0UQTMzroTnuTIAIAetBvtgDUCVVHR2z4X2zCOt4feRndUBFcWiycAAGiiwmnKyiBrZTHKxaTBLwoKYwqQEhl/uMLANYaigcbe1WOmFkw2fKjORM8cA7JhQFehhdrAsibGsgGiAMBhUwifDqUCN8LxPeI7qOHc5KDWFAs29lkKAgKNS7kPTSKmIKbHoDAFlm0hFdYQyU+VCgB2GhwcphNLkp9/3T1cGfch+XpgTEDePqyAeJrxrDhnhlJkghsKifNayu9ZioJw9QkuCkRBLAab22BJEwoUwMoIl3PpPpQfDJ2Pqvr7vdJFLEcURFQDCs9gNDMK0xbF/l478BoA4KjuoxDRdFEpl6mlBQfToCgKFNNZabdNIOkkRYnOBwAoHZ3gjIGnkuIc5sX9BAYal3MfKmYpAMREXF7XRS0FGphtI8OiyJgZ6JkMDK0rd91z7gnaLR1oLK1QbmV00zM3sZJCFKCMKCjn0VEy0NgJum62+5DidR8yhZUAENePyjGWHED/4B6YjE8PUXD33XfjyiuvRDgcLlmgjDFGoqDOdMeMuubNJ1qfjEmiQLJ/dD9u+NUN+PlrP8dK3cYCHThu1nLcufrv8N+X//fgFbihQfE73uafkIXF5Dk5OgDwbiSMBGCLFb65HQuwLfkm9o7sdX1fS1kKoGnQ1RBSShRJvQsHswywbNcXHUCwpSCZhMIUZEOqsEgEWQoAwLL8E4pSA6zXUqCEAE2Dpre5lgK5P/l5y7aw3wLiAPpUy/GNLTE5GnXSUMcXF1/hnSwyuDXfUuAVQ+5kyuM+pAZMhKsJNC6yMs4YQywUw0h6BCOZkeBrwc7A5jbsSQYauy4mJVxj5Hsl3YdKWQqA0qJAuq5MQBTICaQvpsC2EMpIS4GsuCuv4TLTEq8oqCaNoyMKQlyFoYj7ayg1hL0je5E204iH4qK2QWYAyIpq2CX3r+jQFR0KT4oFgtR+cS9rMSDUITbRdJjxCHiaAwMDBfdpSUtBxe5DTDxLuJWblCta4Yo5Y4CiiHNu28goBjJWBlp2DLra6xEFnuuwTMasnKXAea5lPYULpftQOVEwGUsB0z2WguaJAk3Rcu5DnAOms3ihhgHdRMpMgWVj/kWhFqUiUeB1Gaq1+xBRHd3xEGa31S8dKdH6ZEwbIZVEAQC0G+14ZvszsLmNUxesxiePfR+OO/K/g7UfU7ixHGyHB8Xvtja/60ZUDLbjmTEoWVOIAmcw64x1I2pGMZ4dx64hkTI5MB2pRNcRUnVwW8NQdClGB0Q1y+CYAr+lgDEGO6wJS0C+r7HMz25ZfvehoMxD7ueiYoLDbSBzGNBVhEIJKI6lAIDPUnBg/ABSShRtoW4YymFgdCsQPj74e6YOAtlh0c7YEcHb1IJilgLvxEIuGJezFASddy8VWAoA0Zcj6RGMZkYxOzbb/6bjPmBxC7ZzvHKBxtkiIqVUkLFEWiFKug8FxRQAlYmCGrgPuTETjqUAJodq8pw4k5aCcpNEr/CdgCiAZSOui3t359BO7B0R1W9X9q50YhxMIQqUMjU3FB3zE/MRNzOY1TYHOPRH8bpjJQBEn2cTMdj9o35RoGngnAcHGpdLSRp0TcpkA1IU5LsOefYt3YcyCCFjZ6BnU8KKlJ+OlBV345LPTZmFjekJAEkRUyCR7kOTFQXe/rYsf+CxtBTY6VzWuWYFGsuUpADgVNaGYgA6Q9JMQjEt/6JQizIp5yvpW0s+6I1jbnsE7z9uTvkN60gqa9GktIlkTBuGTucfEKv13730u1jUsQjHhTVgZCuAwvzjAApT27W1+YM8FQWmpiJjZqBkso6lwNmXqmJB+wK8efDNXOahcu5DSgjMMnEoeQicc2iK5hcSQZaCVAoKFHBdBwcvHJRVxypgmpW7DzEGaFERaMxtQNNghGJgZjpnKfB8z/2jwgUi1n0Cxnb8Fmx8F2AdG7zqPirEDmILi/of1wQpCkpZCtzJwnguU06d3IeAnMAbSY8UvumIEpsDnGklJ/Tl6hTI1f9S+5i0+xBQd/ch0xbXrKJpyOoKjKQCJZUtFAWVuA9JqhYFQkBLUbBnWGQKmpeYh56okzzFSouO08q5D+kwVAO9elz0d/qgeN0rCpiKbCIO+51hIQo8xQK9Vp2qU5IWtMX5TFaKgiLPJlV13YdSTEfGyiKUTSIkJ9dA2XgCoLDehaK3ASwlBJXMQCTdh4oFGpdayMhrs+8zPlGgA5riWAqcZ1gT6hToig4wBlM+d5zMY1ANQOdCFGTNKWEpmNDM4uGHH8aKFSsQDocRDoexYsUKfPe7361124gAFIWhPdLYan35DCezTW/DTCZtWjBIlLlcevSlOK73uNLFywBPOkPn/Xi8wHVjzPGhj1qKGPjkwKUoWJBY4NtdefchHYqVy3JSMCAUiylQFFiG6lgK8vrZY0oPzD5UbID1+vpHYgjrMSimJbLnAO7nOWOuKJjVuRxZFhPnS7oIecmOAql+8Xe8SG74WiHdh9Jp/wTD644hJ/tyQFa04JXOGlkK2kJi1c89h14cn2ILpYOMve+Vcx8qaSko4j4kg+iB5rkPaYrmLhxmLOFSZUYMcKZA9YqCatyHJNWIAk3zWAqi7iRSUzQ37ggAkHKEJ9NKT1i9Aevje4QQNbqEAJdNVRxRwG0RKJ/NWUNkv8iUsgXfr5goCLom5bPELCMKHPchZtkYMdOwmSYKl8EstBSUEgV572lqSLhNyTZwLiwFipMAYDKWAsaC05KapvjeqiquHVcUNMdSAKBQFCgGbE1F2syAmdNUFPzd3/0dbrjhBnzgAx/Az372M/zsZz/DBz7wAdx00034whe+UI82Ei3GcIpEQTNJU0xBMBWLAhswdEAPB4gC8dkOOJMfzwp6RI/kVhNRWaAxMy3XolooCjztlYNJKgUGBh5y3IfyH9GeCUNg9qFiQXteURBuh6EZYFnh6yrS6InvOZAZQtbKIqSG0BXpwpgyT3xmdLvw1fcihUKkLzchqBe6p9qq11oQlJLUNd0XmQS7dQq4X5B5jyUtDyXcZXxpSfNxLAVWGdchwL/KH5RueDLuQ248gRoqGuhcb/chxpivAq5pm7CiEXCmQklmcjEFrvtQPS0FQhTE9BiY85w4uudovwUv7Vw/eqh0ELPiuY7Gdoq/I/P8mzAFVjQMS3Nc/GQWIid2Bwjo16BAY29dhqA+UPJFQXH3IU3RwDjHSGYEphJGiKtgdsrzfKzeUqApWi6uwBzJrdyripNuNu+ZzHnlosBpN4DCBQFFExl+vDQppgAAbChCmLuWgjDGIYq4hWxW2uW0RajazvLAAw/goYcewhVXXOG+dumll+K4447DZz7zGXz1q1+taQOJ1mMomUWCREHNYBCueJW64VH2oSKUEwVuIJ0NxCMAU6E7Fhfpzz2iiN9tXE4wc5YCAFjQvgAHx4WbQMkHvGMpYNncJK3An9Rr5uaW+N+JKeAhLdh9yGMpqNh9CPBP2iMd0NVRhLLiehvLjiHhiIIDyUOADvTGe8EYQ5p1iEBle1yIABmrYWWA8bfF3/Elxc9DLYlGgeFhIQriMng6ICVpKdchQKxeyhgLO1sYTKkowKmnOtV1i08wpCjIWBlkrIy/ZoWTEtWEAsCqyFIAILD4WCWioJj7kHQdimgRjCDAzQmou6UAEJNIeZ5URYUZMQCmgY2lG+w+xABbnK+juxYgCQWLO/KsXFkpgEqIfkBcQ/I6MsfE35G5/kMyccx0XObuz4nYwBoF3u/nDTT29k2gpUBOmp1+KuE+JC2Llm3BVCPQoTouP/kxBVVYChRNiKjkPhFsHHLOoR4GTKVQFHj/r0QUaJo4B15LgRtsnp9lqTmigDEmgo25BdXjPjTOnHoMrHFFUSdD1TMLy7JwckD6tZNOOglmfnQ4MS0ZTppkKagh8bCGkSoqSFP2oSIEueN4cScTFhCNAB5fbzlADzMx+LbZurOSbPs+Oyc+B21GG3qiPQWTNx+6k5nEyg3sBZYC7+AlhYxMSWrI7EN5A1wx96Fyq255lgIAiHCx7VhmzB1g9ycPABDVYd2mxZeJP8a25yYMYzvFZCjUDhjdwcesNdKFyBtsHGQpkJQqpObmdi9yrXR1Ad2lv5eqqK4LWUFcgWMpMJ3jlJrQe1ONBrkQFZ085rUFKHQfkkHGUb1EEa5yoiCTyd0HE7AUAP60pJZtwYqEoSg6MO5JoekWL6tjoDEAcCGGl3UtwXG9xxUuxqSdCW2pGgUS7zUXnl1Qp0P2S7ot6rcCqWpxsRe0Ku4NMg5aPMr3oy9mKVAUEVPgPJdMJQIDmnD1yc8+VEEcjMRnKciO5Gol6HliSCKfV17XoFIUsxQAgO7ppyZYCSRuWlLLyj3PFQNjEH0XKxbo32JUPbP4y7/8SzzwwAMFrz/44IO+SsTE1KZUPS2yFNSWjkgIQ+OVVzyk7ENFqMZ9KBYGFNUnCjjnGGGiH+Jc96/UOZYCVVGxZtEanLbgtNJtcWMKSogCwO/fzrnrPmSHisQUFHMfKmsp8Bw7KgoqRSHu4bHsGGDbGMuMIWmloSoqZkVn5bYP94k85LYJjO4Q52/MyUIXb2DO7aBgY5+loApRUC4taYUUjStwYwpK1yiQlMpAVAv3oZJWrXKiQLoOhUL+isJV4K1qLNyHwmAFoqDCNKPea7ySVeb8z9nOpLpY32fk963AKuK95jwBxu7bzv2bbY+7lj0AgKYF1yjwthPInZNSQcZA4QS+XPYhZ4C31Ah0rgiXu8nEFCiaJ/WxRxSEov7vIanGdci7XX5MAeC3FDShcJlEV3XHfcjTRtXAGHdEAZ8ac6YJncGHH34YTz75JE499VQAwB/+8Ae8/fbbuPrqq3HzzTe7233jG9+oTStnCEH+pM1CUxmylu26V3gZSWXRZjTv5ptudER1DIxnsKCrxGqeB5F9iGpVFFCx+5AFxISlQHcKXmWtLEYzo8iGxKAZNuEXBZWsZgUcy3ACTRWmBK/WMhWAKdqUFb6nClPAdcV5HlToPlQupkANAaFOwE4BkS4AQAR+S8FAagBc7cCs6CyoigpbChrGgLZlwOH1ItuQogk3BTUMRBqYCa2spSBPBJQUBXkToErJDgvXDGdSFA/F0T/WHyAKHEtBBYHGQM69JshSUNT33EMx9yFpKSgZ/+IVBZwXrkSXm5BWgNdSYNomzIghRIFpCR9+ywIg+7KO7kOAaykoalHMyIDeCkSBdLFRNCDcW3hI55mUbYvB7rehOtcDNA1mtojY8wov2xbtLhVkDARYCkpkH1L8lgKNq+J+VvLEUgn3IVVRoTDFfQYJS0Hccc8ygcyg2FCPArCLi4JKn6ulLAVGFMCw0+bmjYturQLv+KOEMWqnoQCIYmpYCqqe2W3atAknnngiAGDrVpGObtasWZg1axY2bdrkbkdpSqunlQJI44aGsbSJjmjhhcwhsiARtaEjGsLbh8fLb+iQJktBMFVZCkRMgabk3DaG08OwjRAiegTMm+WGscqrpkqkKODimFE9GlyNlmkA0s5AKgZ+FjLAWLawToFnv1VnHwKAWacD4EBGDPoRrgGciwmtbWMwOQgoXZjTFjDRj8wFtDeF7/TQq+K1ehYrC6KcpYApuSJOQBn3IU/mmErJDAH9/yncRHpWAcjFiYxk8tyHfDEF5UVBqQxEk8k+JGMKSroPeSfW2WzhxHMS6UjdQ3gKmFlcpJVkkZhYoR4dEZNfuZJeLqbAO2meiCiQp6hY38uCXBVZCpw+icwNvBdkZiE7pIPHdCAl4yZUmOkSosBTjwSyEjtQXJh5nxMswGomkZYCZ8HDVnSnfoUJwBEeFVgKACFkZXpmXdXF99diIitZ+oCzUQTAWAMsBc0XBbqiI+NUOZdwJYRRnkYCQHRyFQAaRtWtfOaZZ+rRDgJAMmMhEmqNCyduaBhJBYsCorZ0RHRsTFbhPmRZLSMeWwqlQlGgMZF9iGmFoiCkiwmUVxRUayUACkRB0aI1XiGTdiZFoRCAdEn3IW6a4IqwLFbkPgQ4woa5EylDM8BMC2PZMaQy42ICqSjojRWueLrWgoENzmqyWt9iZUGUsxQA/kwnao3dh2T61eyw+1LRDERuTIHoj1LZh4AaiIIy7kMlLQWKU7k3mxWTzzqIgnxLAQDY8TZgaBwYHRV9xm2n6m4dU5ICOUtBMVHgWkbKBBoDwmXISpV0o5Mr6laiDUgdFi+Wiilw3odpVu4+5LUUlOlrhSlQ7JxXgqbEAQwC3OnnSkWBoiPtCAn3O2htQhTIgOdQDDURBaUsBaEoID3fmikKVB1plutXKDqSVhqWpoAxhjCfGtZ9mlm0EONZC9EWcQuJGxpGqwh+JSZOIqJjqBpRYNowSBQUUqn7kFO5WGQfclIl2lkMpYccURATE185+ZyIH7UzWQlrBmBZaDfag7fzxhS4GV4MMM5LZh+ysmn3JZ/7UCWDrKIAqoqwGoaSNZE20zg0Iia8XfFZxQOoo/NyOdjrXaws8PjOsVMpZ2W5MBDc16Zauw9lBpzPpN2gKykKktmkf0LuxBRkG2QpCHIfsrmdK7RXqqYGUDquoIbuQ966CYg798TYOJB1XJdUpfzEbrLuQ9IrsKj7UBUxBdH5QO+anD990GEdQWi2OwsDigIouRXlwHiT/ElwOfchr+hUSrTb2a/uOWZIcdrOHQtJBSlJAX+wcU4U5J0HvUhMQaWFy/La7T7nLE8aZ694a0LhMomuiKrG7j2oGhhJj8DWNUS0CNgUScRT0Rm87LLL8P3vfx+JRAKXXXZZyW0fe+yxmjRsJpLMmIiGWkQUhIX7EFF/VIVVFU9CgcZFKCcKenqAtjagzckqo2jQkJuMDaeHAcYQiXcIHzkpCiZiKXDSH/bF+nBiz0r0dhZZVfdZCsSEjBlhABw2L1LRGICdzQLOHK1iS4EXXYdmWTC4jXEA7wzvAwDMbusr/hmmAJ0niFSkbUdVdpxaEgqJ72dZwoXIO0HyWgokxSr4AhN0H3JEAefCEqAaCKkhhNQQMlYGY5kxtDuZneRKaRZiVbriQGNrgoHGAe5DMp5AVVR/utQgQiFgbCxYFNTYUuBOmuIJYRkYTwFmCoBjKai3KOCOa06xvndjCiqwFFRyWGnF6XCuDd1fwTqwX/NrFZR1H6rQUiBFARf7V5gCTZWuZY4okGKpzATbG2zsfgc9zyJa60BjuR/vBNsreJtsKeBMhelmbwpjNDMKW1NFoH92ckkNGkVFPdLe3u7GCLS3F1nxIibNeMZCpFVEgaGhfyRdfkOi4VBMRxHkgFBsBTAWA9asAfb+WkzqmAqNFU7Gom1dwPDI5CwFAKBp0DjHvGhvcZcIbxpVz8DPuAWbWygWaGybYluFCdN01YF7oRCQSiHGQhi3bXeC0peYW/pzRpf4aRaRiHA3SSZz35WxXB95rQO1zD5kjrkuQQCEy4gqJmhtRhsOjR/CSGZEiAJPddVKLQVyglUyJWkFBdC8n68onkBSiaVgMjEFai6mQLZRaUsAUBxRkPYUu6qzKHAKmBV9TkgrnFGbQlMylshOxIHly8VzCCiefcjbVmkJq8Z9qJSlwLlPpKUgokcALu8TR/xNxlLgFQWM1U4U5FtOvJ/3ZlpqQo0CiUhJqsKSzwnVwGhmFFzTENbDoi8ta2KLTA2koh555JFHAv8mast4xkJni/jwxw0NoymyFBBTCF8xsAB/fPe93EpYfmq9WCgGNRIVomBMFqCZ4ENc08TqUCmzsc9SIAZ+JRwBg3QfCg40trNi4HEnFNWa453JVAwGDtrO5DEURSRc3A2iJYhGhSgYH8/FGHj7p1r3oUotBenD/v+tFACxQBYPxXFo/FAurkBOCpgKyzEATsZ9SE4eK4kp8LoPVRRPIJGiIB2wEDSJasbu7gNiCpR4m+iHZFpMxLkNaFW4DzFWXUpSKRylKAjqe9sEZMHBUAViqgJ8VpyludiDsjEFQKGloKj70MQsBREtAshUmTyVK+gHVBRT4B7S6z4kg6QVI5dJqtaBxsWyjjU7+5DXfUgxMJoZBNdURKQwz2ZbXhRUvQS2fft2bN68ueD1zZs3Y8eOHbVo04wlmbHIfYggJop3QCi2Csh5LssJczJxeDILJYxEbkW0BpYCAKVFQUBMATMMIQqC3IekKHAmCa5bygTchwAgzkJuJpKucNfEv2ujkEIgmQyeWHjTKJaa1LAqLQXSdUhip9w/O8IdAIBD44ec92RV2VBFrj/e92uZfchNR1oungAobSmoofuQrFMAOKKAqSIt6dgIAMu53stcg/Iar8ZKAOQKZTFVrNoG9T13RAFjNbMUBAk2oEpRUNZSUF1MgeYEW4eVkLhPmCpSkpqjHvehyi0F7nOIKYB0R1IjwQHCQO0sBarqWuzE8Ztbp8DnPqQablaycNSxoJSqGt4iVD0CfOxjH8O6desKXn/hhRfwsY99rBZtmrG0kvuQoanIeAovEUTLw1huEl0srsC7OugMxt5Bud1oLxQFk7EUAFVbCpgRBrhdMvuQ7bg7uWlOqx1knQlVlGuui0JHrIluQZUig43Hx4OFkFw1VIpUfnW3m6AokK4KVk4U9ER7AAADqQEx0bOcgV8xKnL9ASZfvCwo0Fi6D1VlKciftGSzk65mDOREAeccKVOcO1XTgahwpcHwQPWBxtWKAvlZGYMTaCnIOpYCZWL7Dzqk0/e+4mUoU6naOwm2LE+mnQrqFFRgKTCc7WMy7kaNAJrqt4hV6PKmKZo/Bb10IVLDtRMF+c9S7+eZlrvXW6CisbwH05y5bqnhsKz23PpxBVWLgpdffhmnn356weunnnoqNmzYUIs2zVjGWyjQuBiWzakGBdG6lAs2lq97BITXDO6zFMgH+GQtBaUGgqCYgnA4ZykoElPAnX0WuA9VaSloU8JQuPA7j8qBq5UpZymQfVkusJZ5LDTlsLO5NKQRJxDbIwqiehSxUAycc2EtkJYCxajI9QfIrbrmWwo45xUVL5MTS1uKSeTchyYVUyCtBLo+KbcHhSnutSrbpSmaCDYGgKHBXExBuYmdFIbxCbi6qaro+2IxBdkkYHMxIa6RKJDCPb+GRMl+lc8c2871iVJCqHj3UUFMwbzYHBw761gsijtVmENR8UyU4pepZWuQyGu2oP16h/itxetvKdAcQSAXA1oh0Ni5rsYs8TuqR6EaeWNKC1O1rYUxhpGRkYLXh4aGYOV3PFEVKdNGWGttUTCSyiIRbo1aCgRRAFMBZCsQBbn7zDuoCVGQ93yb6GRIDuBVWgpUIwLGbdgIsBS4gcZZAJqYcHhTc1Y6yDqTwCh0nDHvNIR3KK3vOgSUtxRIV4JSmYeA6iwFsjqrFgV0mV0o5dukJ9qDscwYDowfQG9Yrr5O3n3I+38l7kOAmGwqqlIb96EapCN1D6GGkLSTrgVDZSoQd4To0CAA23FlKXMdJhLA2WfnBGI1eN2HggThqFOLQotVF69Q6pCTdR8ql44UENc7U8T5KyWIPZaCI7uOBORczkmti4xjKagg3bDXUuAjvkTcK+HZQMbKfQ8vtbQUAOL7W+mmWwpsT0zBiJMMos1oA3Tn+TwFREHVo8CZZ56JO++80ycALMvCnXfeiTPOOKOmjZtxcN7yWWWGklkkIg3OTz4DYABsu/K0pEQRylkKAtLtyUFNV3Uxgcr3nW5ETEE25Q6czDAA2LDtgIrGsniZtBR4axR43i+LFCzZLNr0mFj1mwqiQE4EU6ncAOudWBizxaQkcUzp/VRTp0CunoY6A92HAGBWdBYA4MDYgVygsWKUzkXvQV6DGcs/KZery7IybjHcLFTOZzjntbUUTCKeQCInkb4VcikKUklhKVAqSEkKCGEwGfchs4j70LhTiTfSUX0V82KHLFJtuqLsQ5ZVPh0pIK7nWWc4VctLNabIiru0Epoyjqr8uU0YCTDGcml43baooqaJ4rEueRcuvMethaUA8LgNNjumQHH7ddRxHYqH4rn7awqIgqrP4Ne+9jWcddZZOProo3HmmWcCAH7/+99jeHgYTz/9dM0bOJOYClPCoWQW7SQKak5bWMdI2qRzO1kqdh/KDcTSDJ4wHFeG/MG3ETEFcvKlqlD0UNniZTIlqaqouYHSm5qzHB5R4A7WU0EUGIZop22LLERAXkyBCnS8q/x+3DoFspJuie8uV09DXTlRYPuz9PREe8AYw2hmFOlsGAYAzvSKLQXxUByMMYxlxvD6gddx7KxjAVQWTyDRFM0tDsa5cD9jjMFQDZjlCifJa76YpaAGoiC/VoLPfQhm5e5Dk0HTnOxD6UL3Ic6BsYPi72h3zQ7ppiQtElNQsaWgnLUmVEG6eK9bEpB7NhkJAJ5rugJREAvFcMHSCwoyuPnw3puWlTt+rS0F0bmANQ6Eatdv1aIpGjjThMsfOEac1LbxUBzQnWf0FBAFVY8Cy5cvxyuvvILLL78c/f39GBkZwdVXX4033ngDK1asqEcbiRZiOEkT13rQHtUxNN76D4yWx83mUybQWCm0FLhVh0N5Qar1tBRIi0U6l/ZRYUrx7EMy0NjJea0ytfp4AsAvCiby+WbBWM5aIF0fJuLm4Z2IFctUBYiJonQfCnXm/LWtdC6LFYSwlFmIBseEC4oVcI0VI6yFcVzvcQCALYe3YNvANgDViQKvm4o3HWlFMWByJdM0/Su6NUhH6h4iTxSoipoTBbbVGFFQyn3IHAXSSXHPRTtqd8iJuA95i5dV4j5UcWPyVtzl71DUf0+UyTwkCamh0teXouSepV4XomrrqpSzFMSOAPrOLVlZut5oigauGhgJz0c2cSxGnBTFQhR4nrctzoRsLXPnzsXatWtr3RZiCjCUzOLovikQkDjF6IyGMDCewcLu2uTGnrFMwFLQG+vFofFDmNM2x3mPiZXRpFPhc7IxBSUDjZ19p5MAdFcUADL7ULD7kA0bimWLbatddctv21SyFAAirmBsLCcKJtI/zJl8culGUmTCZY4KFyOmAnoi91luC2HgyfTSE+3BQHIAQ+P96E30wUKuXaVcfyQL2xcibabxxsE38Gr/qwipIVEJFRWKAo+bSlXxBEAuYJNzYS2QloEaug8FWgpiTlVjbkLEFKiNEQWW7bi0WLmCV5kBIJMVAbLh2lQzBoLdh7wB5CWzD3kDjWsgzEpOrrV4TgDX0g1HdVwcg0TBZCsa1yjuo1boio7x8Fwk9R6kzDcAAG2hNkB3XBCnY0pSQLgL/eVf/iVWr16NPXv2AAB+9KMf4bnnnqtp44jmwgP8mYZT5D5UDzoiOgaTrb+K0PK4oqDI6m9ATMG8xDycv/R8dEU8KTm9k6B6ug/JwVdOvkIhKGBgnItA4/xHtJNr3eY2mGX73YdmgqUA8GcgAibe7kqCjb3xBIw559+ZnNnBcQXDyYPg4DCda7EgZWMJlnUvw5LOJQCADfs3YN/IPgDlYxK825i2WV06UkB8L3lNeCcuNXQf8ua1BxxRoBlAOCTuV86dmII6ilM3JakjhL3PifShnCioxaq8PGSApcArEGrmPlRRY0qIAm814grchyZ8zPzjVrMP2xY/rSoKnGt8ICWeG4ZmiNemkKWg6rvvF7/4BS688EJEIhGsX78eaeeCHRkZIevBDCBr2QhpU2RFcQrREdUxON76qwgtzwQsBYF4B+C6ug/JVcrcwK86yQYC3Yec/QpRYPkDjauZHHsD3+RgPZUsBV4mOjGoJNjYjSfo9HzO40LkoTPSCVVRYVlJJLNJWE7flqtRkM/yWcsxLzEPnHPsGNwBoPKYAsDvPlRRkLEkKNi4nu5DTBWTz6gBOEGZjXEfYoBTvMsnCjIDQMYULii1mIA7BMUUeLNKlQ00rqX7ULGYAlUVYkhSoftQReSLgolkS8uPTWhRUSDvwcHUIADHdQiY3qLgq1/9Kv7pn/4JDz30EHRP9P/q1auxfv36mjaOaC5UjqBxJMI6hslSMHnkhMIuJgoKYwoCaZSlQFosUs6qt2G4D+XA4mXOfjnnYKYlJhxysK1mgPRuKycdU0UU5KeinGj/uMHGJfrHaylwjydFQdK3qcIUzAp3gHGOofQQTOQsBVU1izEc33c8ZsVmua/V3X0IKC0K6uU+pOhANJLrA1Zh9qGJ4mbDkZNj57hWGjDH6mMpCHAfKlt7otrsQxU3pkhMgaYBWoMsBd7nYaXPLMWTMtk0W1YUyKDrw0mxmNAWcs7p7NnAhRcCATW+Wo2qR4E333wTZ511VsHriUQCg4ODtWgT0SJw7qxWEnVHUdiUyD7V8tTKUuCdBDXCUpBOixsuFHIfyoHZh4Cc+5A9CfchRcm1T4qCqeI+VDNLQRn3ISsDZJ0MR4GiIF3wkZ6wiDsYyozBdFaGK3H9KWgaU3Dy3JPd4GVDKz8hnJT7EFAoCrx+4DW2FLgpVJljKZDI2IZ64bqhOP9LMSItQtwQCwY1tBQEuQ+VDSAPCjSupSgACt1wGuU+JI/pnehXu59WFQWO+5AU5a6lQFULE1i0KFWPdnPmzMGWLVsKXn/uueewZMmSmjSKaA3CuoK0aZffkCBahQnUKQiklpaCSioaZ7IieNVnKSi+X5vbYGae+1C1A6S09MrV4JlmKXAzVRXpH2kl0OP+glBuWtJUwUd6nHzvg5mkW3OgWkuBRFM0nDr/VCyftRzLupZVtD1QQ/chORnVtJpMvrypK91zouhA1HOv1XuSJ/dvO5MzKQjTjiiwnYl3nd2HStYoAIItBbV0H5L79j471Eju+dkIUVBtX8v9TAFLgcQVBVOIqkeBa6+9FjfccANeeOEFMMawd+9e/OQnP8Gtt96K6667rh5tJJpE3NAxmi6T35ogWgk5yS7mEtJIS0FFFY2dfftEgVADNliwpc4TU+BzH6p2cjxVRUE47F9xm+jEQLoPFUtJGuQ6BBQtYAYAbU5gocVU9DupSScqCgCx8ri0a2lFbkBygpk0k+6qdFXuQ/m1CmoYTwD4LQXuOWEMiHsmTmoNJ6NBuJaCvJgC2dfc6ds6uw+VtRSoHgui9L+vRT/kpwj1PjsYy9U6UGuXfalmosCbgWgiLpMNIL8/24ypl6mx6jN62223YWhoCOeccw5SqRTOOussGIaBW2+9FZ/+9Kfr0UaiScQMFaMpEz3x2q2aEERdUcq5DzUhpkBmzAiadEsf6nQWCFki0JhJa4YCm9uF7if52YfMCbr/SFEw1dyHZK2Ccaf6ar2yD7mioMv/uuI8DwNEAew0EkYCI1m7JqKgGuR1MpIWqVoNzagoFapLvqWghvEEgF8U+FbIY/FcOlS1zufKjSmQlgJTxB9lBx1/2bAoL99s9yHZTplhS9NqJ9q9KULzJ+idJwLmCBDqqM2x5PGA+lgKWuyZ5c2wpSmam1J4KlFVr1iWheeeew633HILPv/5z+O1116DbdtYvnw54vGpZyYhStMW1shSQEwtWjGmABCDWNHVRwUwrZylwBEuHEyIAuS1NT/70ERXzfJFwVSxFAB+UTBhS0EJqxLnE7IUwMqgPdyO3eYIsk5GnWqzD00UOcEcdYomVRVPABR3H6qRKJCpWTnn/smwEhJxBWMpQKvdCn0gQZYCKQhsTaREBRoWaFw03iQ/S1ANRYpv3/kTdC3iq71RE2ptKZgi7kNT0XUIqNJ9SFVVXHjhhRgaGkI0GsXJJ5+M97znPSQIpinkPkRMOSoWBWUGE13PDZ4Tzm7D/KtbxXAXqm1A18HAAcbAwXwTCRdHFLjFyybrPuQN/JsqeION62EpyA6La0XR/akaAU9MQbYwy5WdRrvRDjvIf77OyMlnyhRipap4AqC4paBGE1LGmDtp8osCHThyATB/FtDdUZNjFSVfFNhmLp4ATj/XOCC0VErSspYCSS1FQVDAbj1X3IuJgmqP6XWpkrSaKFBnmCgAgJUrV2Lbtm31aMuMJmPa0FpsUJbuQxLKRES0PBUHGlcwIMmJpz4JP+dKMhDJYH5d5lC3oDhuRd6JhIuqisxErvvQJAONPfudMniDjeuRfci1EnQUThAV3ZP6Ni8DkZ2GruiIGh255jVIFOQfp6p4AqDu7kNAzoXIt0Ku6MDsTuDYxQ2MKXD+52Yu8xBiTiNra62YlPuQpJZt8mY2aoRvfq0tBVIUeBddWgSvpWAqxhMAExAF/+f//B/ceuut+Pd//3fs27cPw8PDvh9iYiQzFqKh1rrA2/IsBeMZCxG9tdo4nWCMwS6ackbAOUfrJzVrImUtBVWIgne/G1ixAmhvn3h7KhEFWWeGEpLuLDYYmOs+FLRP27ah5LsPVTtA5k80WmxRoiS1sBS47kNBokAWLesqfA8o7kLkZBzqiPbmNq1n3n1vk/KO02ruQ0BOFBRYCiT1Plf5osDOeoKMnWuqlqvyKOI+VGn2IUk9LAWNqgxc65gCb1asFmM6WAqqPqsXXXQRAODSSy/1lW7nnIMxBssqMhgTJRnPmoi0mCiIGapPFAwls2iP1HklZwaTCGsYSZlojxY/x2nThq5Ooclbo6nUfaiS1duuLvEzGSqpZJkvCiDcgjgrIgpUFRYsMOk+NFFzPFkKxO+g7EPF4gkkqiGKXeWLAsdy0BXvA5JbRfMa7D4kmbD7kFxBrrH7EJCbNPnOCWugKHCD/53/s4NCGDAVsJ3vX2NLgXQfahlLQaPz/ZcqmFYNcnt5XbagKPD2p1u4bIpR9Vl95pln6tGOGc94xkIs1FoXuaYqsD0uQ8MpEgX1pD2iY2A8U1IUZCwbIY1EQVFct44iK/PVuA/VgkosBRk5SDr9ym1nwUXxTSS8++Sci0Bjb/GyyboPTUVLAWMTb7ccwPPdh4ZeB8xxkS62qCgoUqvAFqvsXbE5UA5uh83tqeM+JDPc2LawFtTRUuATME2xFDgLmt7idKPOPVprS4HnO9lcCPmKi5dJ6hVTMFEr40SPB0xrS4Ghin5SFbV6Ud4iVH1Wzz777Hq0Y8aTzFgtZynIZ2g8iwSJgrrRGQ1hMFliRRki9oREQQlcl5BJBhrXiopEgbQU5KwcChRwJyVp0D5t21O8bLKBxpKpJgqWLBGTpYkGhcoVam/2oZEt4gcAOlYWtygpAe5DnLuiQNUi6In2oH+sv2FpCSftPgSIFelUSqTClNatGk5IuyJd2D28G51hj9jyiYI6X4P57kOSUGduslnrmAKPALJsC4qqlM8+VE/3IXmfZ7PimgWmhvtQfkxBK4oCzcAJc05ASA35PGmmEhM6qwMDA3j44Yfx+uuvgzGGY489Fh//+MfRNVlT+wxmPGOhLdx6F7mX4ZSJBV1TU/1OBTqiOrYfHCu5Tca0ESL3oeKUch/ivPKUpLWiokBjp00yXsdZTSwZUwBP8bKZGGgMAO961+Q+Lyej3BZZhJJ7hJUAANqXA7GFxT8bFFNgeyZZSgjH9x2P4fQweqI9k2tnhXgnn7qq+/ybK0aKgpERZ6fq5ALt81jYvhDz2uY131IAxV87xOgGMjudv2trKfDWirC4BR16eUuBtIDJlKT1cB/yZvEhS0HNmJ+Y3+wmTIqqZxfPPvssFi1ahG9961sYGBjA4cOH8a1vfQuLFy/Gs88+W482zgjGM2bLBRrnQzEF9aUjEsLgOFkKJgXLTayRny3LKxQaZSmQEyoZvBlENs9SAMd9qJilQFVhc54rXjYTA41rAVNzVobxXcDgK+LvtiOBtqWlPxsoCmS9Bx1gCgzNwKzYrIatGHonmBOyEgC5a0ImDamh65CkILi2kTEF8h5hCmB57q1QR26yWWNRAOS+s7yfy4oCwH8/18N9SD6TVHXi1rZqjlcrS0H+fomaUvXI+KlPfQof/vCH8cADD0B1OsWyLFx33XX41Kc+hU2bNtW8kTOBqeA+NBWEy1SmLaxhJFVGFFg2DI36oCjeSQW3/JN/ryhoUEEp1/d9rIQFKCimoET2IVtVABlTUIviZZIZJwqYuD54Fhh0xq3YQqD92PKfDRQFcpLVnArwXleUquMJJPmioA4T5AIaaSlQFGcVXhOiQAegJ0Qb5CS5xu5DgOgbC5brNiRFQcnCdt77sR7uQ41aca+1pUDSopaCqU7Vo8DWrVtxyy23uIIAEEXNbr75ZmzdurWmjZtJjGcsRFss0DiIqeonNxVQFIZylSDSWbIUlMTrk5zvQiR9xxsU+AkAaHMyUEh3jCAyTru8MQVKcfch23EfY3ZenYJqV85o5c1/LUTnAh3HVfY5N9DY44JhSUtBnavyFsE7wZy0pUBer3WwFBTgFQXVT0mqR1UBqJ5qwY7bcx0tBW4GIueZJH9XZClgrKYuXAWWAhIFhIeq78ATTzwRr7/+esHrr7/+Oo4//vhatGlGksxSDQCiPBnLgkGioDhO0S8AAaKgwfEEQE4UjI3lJiH5uMXLHMHNbSfQWA2saGw5mzHThsKRc5OqdlKvKP6BdaZZCgBAcSaA4VlA5wmVu1HIz9lmLqOVtBQozbEUeCeYE858IkWBDDJutChohAVP0/zuQ6EucW/K71wPS8Fk3Id0vbbuPUHuQ/WkXu5DJArqQtVn9frrr8cNN9yALVu24NRTTwUA/OEPf8C3v/1t3HXXXXjllVfcbY87rsJVFwKcc6hK663CUxHj1iJt2mgLU1xHSZgqBED+hNpNR9rAwSQcFoOXaQphIEWCJJuFax5yLQVOTAEPthRYqnhOKIA/VmEig7uu5wbpmSgK2pcD6YNAfGl1mW8UTfzYpnAhUuKemILmWAoUpoAxBs755N2HJI1wH2pkTAEg7hNFzaUlDXXl7qNar8rLQ+ZVNS6bfQjwBEHXuA8aHbBLloIpRdVn9YorrgAA3HbbbYHvyYcSFTIjiOopJ8Io+1AFKKpIOdgKlgJACIGBAWB0tFAUpNMAVEBTASY7v3TxMttZPFCYkhvYFWVik3pdF+kngZnpPmR0i5+JoIYBe1SIAj3e9JgCQEwyTW5O3n1I0hBLgSoEGbcbJwoAILES6O4AtAgw7sRQhEJ1Cbr1VjXmnFdnKai1KJDPianmPkSWgoZQ9Vndvn17PdpBtCgUQtBaUPahCijnPtTImAIAiMeFKBgZAebM8b+XTjtFsrScJcNTvCzQUsBtcFWBAo8omOiE3rsqOhMtBZNBCQMYzVkImhxTAAAL2hdgKDWE9nD7xHbQDEsBIFyIrHRjRYHeCUT6xN91jCcA/FWNvfd0RaKg1u5M+c+Kei8GyMm7LJY2UXdHshQ0hKrP6hFHHFGPdhAtjG1zKC3o2jQdKSfCRPYhmryVpFhVYxlo3AxLARAcbJzJOKJAz7WPWyL7EAuuaGxxC1ypgyiYiZaCyZCfgajJMQUAsGL2isntoBmWAiAnChoWaIzcyjVQ18xDQM5NyOa2ayUA/DUMCj9UJ0tBoyfX3uN53R3JUtCS0OyCKEk0pGE8S25grQJlH6qAYlWN0wfFb7XBBfikKBgdLXwv7ayOhvRce7kNhalFsw9ZtgWuqX5RMNEB0jsJIktBdRSIguZbCiZNs0RBZL5wwQp1lt92sgSJgjpbCrzuQ17XoZLZ/KaLKPA+V7yLGNW6IZCloCHQWSVKEjc0jKVNxA26VBoBYwyWXTzoPGORKChLkPuQbQLje8Xf0QZXnIzHxe/RUWE69w6Grijwuw8pJYqX2dwGV1UoFiP3oWYiYwdsRxRYzY8pmDT5IrEOQbeBJJaJn0Yg7xVvlfE6Wwq87kMyo1jJGgUAMHeusC729ta4MXn3eb0n197qzJNZxJBCQrofkSioC3RWiZLEDQ0jKROdURsaTRrqTsIpYNYRDR6cshYFGpclSBQk94r/9XguL3mjiETEgGZZwPg4EIvl3ks7LhPSUsA5gNLFyyxuwdYUKFk2eUsBiYKJo3gsBZy3hPvQpFHV3LXaKCtBo/H6uEvqbSkIcB8qGU8AAH194qfmjWlwTIE8xmRFgdzPRAOViYqgUYAoSTysYTRtYjiVRXuEUmHWm45oCAPjpasaUwG5MgSJgvG3xe/ogia0h+WsBflxBW6gsXNvcVsUL2MKeClLgSLST9bMUkDxBNXjdR+yPb7SyhR/TsrV8kYFGTeaZsQUBLgPlUxHWk+a4YZTqzSo3raTKKgLJAqIkkj3oaFkFokI3YT1pjOqY3A8U35Dojj5osAcA9KHxeS80a5DkmLBxt5AY0AEGzvZhzhYcPEy2xLuQ0ytnSggK0H1+ESBJ55gqot2OTGerpaCZsQUeOoUyOQBZS0F9aLR7kNA7USB93MkCupCRWe1s7Oz4tXJw4cPT6pBRGsRNzRsSZmIhMhS0Ag6IiFsPRgQkEpUTr4oGHOsBMas3ESu0RQTBem0mEQaTru45cQUKCiektQCVxWoDLVzHyJRUD3yWuI2kHXu2akcTyCZyaKggZaCpomCZrkPAbW1FJB1sy5U1DP33HNPnZtBtCrSfSicVLC4J1b+A8SkaCdLweRxRYEpfL2b6TokKeU+BOQmYNxEueJl0lLAmJ1ze5joABlxilzVaTI0rWGKsAzYGSDrFL+aypmHJHK1fCaJAnkf1blOQVUxBfWiGe5D8hi1shRMtFgjUZaKeuajH/1oXQ5+xx134Etf+pLvtd7eXuzfvx8AwDnHl770JTz44IMYGBjAqlWr8O1vfxvvete73O3T6TRuvfVW/Mu//AuSySTOPfdc3H///Zg/v0luAtOMqK4imTExlGRIhMlSUG8SYQ2jKbP8hkRx5GDLLZGG1EoJP+9IHYL2KsWbllRmILLtXNCcEQaQERmIuFWyeJnNbZGS1Gu8negg29YGHH98YaVlojLUsF8UTAdLwZIl4vqcrmNoviiwrNx9WOc6BVVlH6oXrRBTMNFFDPk5ch2qG5OSWslkEsPDw76fannXu96Fffv2uT8bN2503/va176Gb3zjG7jvvvvw4osvoq+vD+effz5GPKttN954Ix5//HE8+uijeO655zA6OopLLrkEllXoi0tUj6Iw2BwYSZlIkPtQ3WFMnG9iEnjdh1wrwTyxstssotFcWr7xcfGaHCAVBQj53Ydk8bKi7kOK4i98NBlT+oIFQEfHxD8/k5EiIDskfk/lzEOS9nYhFKe7pUAKAWklqGMK1pZyH5oOMQUkCupG1Wd2bGwMn/3sZ/HTn/4Uhw4dKni/2sm4pmnoC0i7xTnHPffcg89//vO47LLLAAA/+MEP0Nvbi3/+53/Gtddei6GhITz88MP40Y9+hPPOOw8A8OMf/xgLFizAb37zG1x44YWBx0yn00jLixNwxUw2m0U2WzrzSz2wbA7btpty7EqwLAu2DdiWiYACq5NCfudW/e7NwLKsouej1HvNpmX60rLBLBNIjwLZQYDb4KE5QJPbxcJhYHgYfGBArEiOjoKZpph82QAsEzybAjMzsC0bWctCJpspOJ+pTApZxmFbNkxnYsM5r/n3a5n+bGW4Kq41S8QUcJs1/ToLgvrSA+fivkunwbNZ333I63R+bMuGaZnIZDNIIgnTMsEtPqH+mHRf2rb4vg7ctut/zcpzPtnnlaft9eqrRtKo+7Ka/VctCm677TY888wzuP/++3H11Vfj29/+Nvbs2YPvfOc7uOuuu6rdHTZv3oy5c+fCMAysWrUKa9euxZIlS7B9+3bs378fF1xwgbutYRg4++yzsW7dOlx77bV46aWXkM1mfdvMnTsXK1aswLp164qKgjvvvLPAbQkAnnzySUSjDa52CiBlApsHGP7j4MbyGzeB1/YLP4X/OLSpbsd46qmn6rbvqcZr+xn+43DwuX51P6trP9SCZvdl2D6Ednur+7/JojjUArUd2rduRfjQIYy+8w7G5syBMTiIjrfeghmLwU5qCPEhDCmHkbB3IGmNYn1Kh65ux9DGId9+tie3I7NvC6z9FvZrwtVy+OBBJN94oy7tbnZ/tjJxezdi9l73/2HlIJLKlia2qDTUl0BocBCdzn13aHDQ/3+mPvFch7OHsWV8C9rUNoTVMA5kDmB/eD+2GdsmvM8J9yXn6P3Tn9x/D1gW7DoXqUts347IgQPu/yPvvIPxrVtLfCKYth07EO3vR7atDYeDKsRPUep9X45L63QFVC0K/u///b/44Q9/iDVr1uATn/gEzjzzTBx55JE44ogj8JOf/ARXXnllxftatWoVfvjDH+Koo47CO++8g69+9atYvXo1Xn31VTeuoDevml9vby927twJANi/fz9CoRA6OzsLtpGfD+Jzn/scbr75Zvf/4eFhLFiwABdccAESiUTF7a8V/SNpxHYN4sJ31bhyYY04/MIuAMDFqxbWfN/ZbBZPPfUUzj//fOiNqp7Z4hz6wy5cfGrwuT78wq669EMtaJm+TO0HO5x7JvDEciC+pHntkWzeDPbmm+Dz5gEnnAC8/TZYIgHMng0cqQCp/eDtK8CGujGSHsZIxkDU6MKaRWt8u3l5/8s4tCWOlbuz6IsLKys//via+4C3TH+2MmM7wIZyIp13ngRE5jSxQcFQX3o4dEjcd/E4+Jo1uftw1izwVavqcsj+sX507O1Au9GOmB7D3tG9eNesd2Fxx+Kq91WLvmQypgkAf9/76p/JZ9MmsB073H/5ypXAEUdUv5/XXgPbtg2YPRv8Pe+pXfuaRKPuy2pc+6sWBYcPH8bixeJCTiQSbgrSM844A5/85Cer2tf73vc+9++VK1fitNNOw9KlS/GDH/wAp556KoDCQk2c87LpUcttYxgGjIAsA7quN+WBmbUzaIsaLfuwVhQVjKGu7WvWuW9FVFUtei5KvdcqNL0vrTCgOo82xoDEIkBtgXPW1SV8YdNp4bts2+L/WAzQOZDVAJUBqgpd06HaISiqUnAumcKghELQNeF+CUBkEarTOW96f7YyRlvuWgMAI163fqgF1JcQ7nqaBmdQE4H/7n1Yn3MTDoWhqRqYwgAF0FQN4VB4Un0xqb40jJz7TiNiR+Q5l0z0eRWJiP2Ewy19n1VLve/LavZdtU19yZIl2OEovuXLl+OnP/0pAGFB6JhksFosFsPKlSuxefNmN84gf8W/v7/ftR709fUhk8lgYGCg6DZTgfGMhWiIcu4Sgqle+6jpeCuFhntbJyOMNy0p5/6CSbLNTmVcWbysWPYhqGrtAo2JiZNf92I6pCSd7uRnH6pz4TLAn5JUZh9qWqAx0PgsPrXKeCTdu5vg5j1TqFoUfPzjH8ef//xnAMIN5/7774dhGLjpppvwv/7X/5pUY9LpNF5//XXMmTMHixcvRl9fn8/XKpPJ4Nlnn8Xq1asBACeddBJ0Xfdts2/fPmzatMndZiqQzJqI6K07qNMklZhSeAfbZtYmyCcWE5k/LAtIJv0Fk2SbpSiAKF4WWNGYW7BVBYpCoqDp5IuCVhGgRHHyRYGMI6hjrY6Wyj4E5DIQTTVRMG8ecPrpwFFHTb5NRCBV98xNN93k/n3OOefgjTfewJ/+9CcsXboU7373u6va16233ooPfOADWLhwIfr7+/HVr34Vw8PD+OhHPwrGGG688UasXbsWy5Ytw7Jly7B27VpEo1F85CMfAQC0t7fjmmuuwS233ILu7m50dXXh1ltvxcqVK91sRFOB8YyFzmjrrjDJtOpEY2CMwbI5VIVO+oRQwmLlXTWA8OxmtyYHY0IYjIyIegXegknMyQZiC5O+whSgTPEyxbumQyn6moPXMsCYqIdBtDZeUZBvsavXIT11ClpCFMhz0KjFhFqJAsaEGyZRNyZ9VS5cuBALF04s8HH37t244oorcPDgQcyaNQunnnoq/vCHP+AIJwDltttuQzKZxHXXXecWL3vyySfR5im0c/fdd0PTNFx++eVu8bLvf//7UKfQyplwH6JBnRC0R3QMJ7PojLWuUGxp1BAw+yyx+t7M2gRBtLUJUTAykuc+5PztWAoUx0+9dPEyshQ0HaYI8Wmlp0eNgpmAd0Jq236LXZ2QlgKb27CcvN4qa+I9O1Xdh4i6U3XPfPnLXy75/he/+MWK9/Xoo4+WfJ8xhjvuuAN33HFH0W3C4TDuvfde3HvvvRUft9VIZixEWjimgHMOhUwFDaMjomNgPEOiYDLo8Wa3IBi5oJEvCvLdh5wJA+e8IHFCzYuXEZNDDTuigO7XKYHX7c40/Ra7eh3SE1OQdayB5D5EtCJV98zjjz/u+z+bzWL79u3QNA1Lly6tShQQglYPNFZVBXGjdds33eiMhjCYnPqFWYgAvMHGXl9mW7o0OJYCRQcgrgGb275VReE+lCcKaJBtHkoYwBDFE0wVmMjwBcsSP42wFOTdv0DOetAUpqr7EFF3qu6Zl19+ueC14eFhfOxjH8Nf/MVf1KRRMw3TtqG3QHGlYrQZGhIRuokbRUdUx+b+kWY3g6gH0lIwNCT8mQExGUk79xcXQkBYCjyiALlB1eY2oChg3oGWLAXNQwYbk6Vg6iBFQTrt5utvhKXAS0vEFDTDUiBFGdGS1GQmmkgk8OUvfxl/93d/V4vdES1G3NDQHqEAukbRHtUxMEaWgmlJLCYGRa8gUJRcSlLndcUzYciPK5AZiRTdmYQqCmUCaCa6I/S0FnVZIwqRk1JZ6VVV6zpRZYwVCIMZG1NAgqClqdkVMTg4iKGhoVrtjmghjpwdR5TchxpGm6HhnZFUs5tB1ANFEcJgdFT8L10WCiYIwj3I5nahKHDcDxRNBzIWmeKbTewIQGsDDMqKMmWQE9NkUvyuo5XAPaSiwrZs9+9yRVjrSjNjCuh51dJU3Tvf+ta3fP9zzrFv3z786Ec/wkUXXVSzhhGtw6KeWLObMKNgjGHF3HZs3D2ElfPbm90cota0teVEgZyM5LsSMNWdRHhrFXgFgqKFgEySVt6aDVOAcE+zW0FUQ76loI7xBO4hmYosWiDIGMhVA25UVWASBVOGqnvn7rvv9v2vKApmzZqFj370o/jc5z5Xs4bNJE5c2NnsJhAtxpnLevDAs1t9osCyeXNXl4jaEPe4mUhRkG8pYIovY4lEWgkAQAmFgPEkDbIEUS35oqABlgKv+1DTRcGiRcJVcUGDijuSKJgyVN0727dvr0c7ZjQr5tFqMOGHMYZ3z+/AhrcHcfyCDgBAxrRhtHBAOlEhnjorOVGQbykoIgo8VgNFc1b5yFJAENWR7z7UCEuBJ9tQU+MJAOHCuGJF445HomDKQDMMgmhRVi/txvNbD7n/Z0wbIY1u2SlPRaJADRQF8m9VUXODK4kCgqgOee800FLgFQJNtxQ0GhIFU4aqe2dsbAx33XUXfvvb36K/vx+27Q+C27ZtW80aRxAzGcYYjl/QgZd2DuCkIzqRtiwSBdOBeDyXgcgVBXn96rEUeF2GfNVQ5eBKgyxBVIecpDYgHanE6z7U1BoFzUBmSOOcnlctTtW98z//5//Es88+i6uuugpz5swhH2eCqCOnLe3G/b/bgpOO6BSWAnIfmvooChCNAmNjnuxDTMQVuO5BiruyGGQpUJjS+AJEBDFdyL9nGuw+NOMsBYA456ZJoqDFqbp3/t//+3/45S9/idNPP70e7SEIIo9TFnXhxR2H0R0LkaVgunDMMcD+/cCsWbnXFE0UVALKxhT43IdokCWI6sgXBeQ+VH9IFEwJqp5hdHZ2oquL8jETRKM4ZVEX/rRjABnLhkGiYHowdy5w4ol5lT69f5fOPqQyVQQLArnfBEFURpMtBU0PNG4GjS6YRkyIqmcYX/nKV/DFL34R4zJAhyCIuvOexV34z7cOkKVgOuMNNi4SaOxWM2YKsHAhcNZZwNKlDW0mQUx5mmApaKmUpM2A3B2nBFVfmV//+texdetW9Pb2YtGiRdDzil+sX7++Zo0jCEJw0hGd+NHzO3D6kVQkadriWz0MthT4sg8xBrRTOmOCqJpmWArIfUj8JktBS1N173zwgx+sQzMIgijHdecciZ54/Ve0iCbhnSgwxXU38NYm8LkPEQQxMbwTU10Xwf91xuc+NNOyDwE54RUON7cdREmqFgW33357PdpBEEQZjuptK78RMXWpIKbAl32IIIiJ4bUUNMBKAJD7EN71LqC3159cgWg5JnxlZjKZwDoFCxcunHSjCIIgZhzMbykom32IIIiJ4RUFDYgnAMh9CPG4+CFamqqvzLfeegvXXHMN1q1b53udcw7GGCzLKvJJgiAIoijMn4mobPYhgiAmRhMsBTM++xAxJahaFHz84x+Hpmn493//dypeRhAEUSt8q4dFKhp7sw8RBDExyFJAEIFUfWVu2LABL730Eo455ph6tIcgCGJmUkVMAbkPEcQk8AYaU0wBQbhUvdy0fPlyHDx4sB5tIQiCmLnk1SmQK4vkPkQQNaYZloKZnn2ImBJULQr+/u//Hrfddht+97vf4dChQxgeHvb9EARBEBOgkorG5D5EEJOnGTEF5D5ETAGqvjLPO+88AMC5557re50CjQmCICZBkZgCch8iiBrTBEsBuQ8RU4Gqr8xnnnmmHu0gCIKY2eRZCuTEn9yHCKLGUPYhggikalFw9tlnF31vw4YNk2kLQRDEzKVInQJfRWOqU0AQk0dRhBgwTSASacghpRBQFZWyNhIty6RtWENDQ/jJT36C7373u/jzn/9M7kMEQRAToYI6BVTRmCBqxGmnCVGg6w05XFgLgzGGiNYYEUIQE2HCouDpp5/G9773PTz22GM44ogj8KEPfQgPP/xwLdtGEAQxc1AqqGhM7kMEURsSiYYeztAMnLHwDITUxrgrEcREqEoU7N69G9///vfxve99D2NjY7j88suRzWbxi1/8AsuXL69XGwmCIKY/vok+ZR8iiOlGR7ij2U0giJJUPLJcfPHFWL58OV577TXce++92Lt3L+699956to0gCGLmUCSmgLIPEQRBEI2gYkvBk08+ieuvvx6f/OQnsWzZsnq2iSAIYuaRV7zMDTS2PYHG5D5EEARB1ImKLQW///3vMTIygpNPPhmrVq3CfffdhwMHDtSzbQRBEDMHRQUSRwOJowBFC65oTNmHCIIgiDpRsSg47bTT8NBDD2Hfvn249tpr8eijj2LevHmwbRtPPfUURkZG6tlOgiCI6U/iKCEMAMo+RBAEQTSUqkeWaDSKT3ziE3juueewceNG3HLLLbjrrrswe/ZsXHrppfVoI0EQxIyDsg8RBEEQjWRSy01HH300vva1r2H37t34l3/5l1q1iSAIYsaTLwq84oAsBQRBEEStqcnIoqoqPvjBD+KJJ56oxe4IgiBmPDJuwOY2OOe+gGOKKSAIgiBqDS03EQRBtCBeawAHd4OMGWNkKSAIgiBqDo0sBEEQLYh34m/ZlmspIEFAEARB1AMaXQiCIFoQ7+Tf5naucBkFGRMEQRB1gEQBQRBEi+INNqYaBQRBEEQ9IVFAEATRonhFAdUoIAiCIOoJjS4EQRAtihQAFreoRgFBEARRV0gUEARBtCjkPkQQBEE0ChIFBEEQLYq3VgFlHyIIgiDqCY0uBEEQLUpQTAG5DxEEQRD1gEQBQRBEi0LuQwRBEESjIFFAEATRokirAGUfIgiCIOoNjS4EQRAtipt9yKbsQwRBEER9IVFAEATRopD7EEEQBNEoSBQQBEG0KD5RQJYCgiAIoo6QKCAIgmhRqKIxQRAE0ShodCEIgmhRyH2IIAiCaBQkCgiCIFqUIPchshQQBEEQ9YBGF4IgiBZFWgUsblHxMoIgCKKutIwouPPOO8EYw4033ui+xjnHHXfcgblz5yISiWDNmjV49dVXfZ9Lp9P4zGc+g56eHsRiMVx66aXYvXt3g1tPEARRe8h9iCAIgmgULSEKXnzxRTz44IM47rjjfK9/7Wtfwze+8Q3cd999ePHFF9HX14fzzz8fIyMj7jY33ngjHn/8cTz66KN47rnnMDo6iksuuQSWZTX6axAEQdQUyj5EEARBNIqmi4LR0VFceeWVeOihh9DZ2em+zjnHPffcg89//vO47LLLsGLFCvzgBz/A+Pg4/vmf/xkAMDQ0hIcffhhf//rXcd555+GEE07Aj3/8Y2zcuBG/+c1vmvWVCIIgaoK3eBllHyIIgiDqidbsBnzqU5/C+9//fpx33nn46le/6r6+fft27N+/HxdccIH7mmEYOPvss7Fu3Tpce+21eOmll5DNZn3bzJ07FytWrMC6detw4YUXBh4znU4jnU67/w8PDwMAstksstlsrb8iUQJ5vum8T32oL2uPbdkwLRPpbBrpbBqmZcK27IacY+rP6QP15fSB+nL60Ki+rGb/TRUFjz76KNavX48XX3yx4L39+/cDAHp7e32v9/b2YufOne42oVDIZ2GQ28jPB3HnnXfiS1/6UsHrTz75JKLRaNXfg5g8Tz31VLObQNQI6sva8U76HexM7cQ2fRvGrDGk7TTGXh9Dm9bWsDZQf04fqC+nD9SX04d69+X4+HjF2zZNFLz99tu44YYb8OSTTyIcDhfdjjHm+59zXvBaPuW2+dznPoebb77Z/X94eBgLFizABRdcgEQiUeE3IGpBNpvFU089hfPPPx+6rje7OcQkoL6sPTuHdmJj/0b0xfowmB5EykzhzAVnoj3cXvdjU39OH6gvpw/Ul9OHRvWl9IaphKaJgpdeegn9/f046aST3Ncsy8J//ud/4r777sObb74JQFgD5syZ427T39/vWg/6+vqQyWQwMDDgsxb09/dj9erVRY9tGAYMwyh4Xdd1usmaBJ376QP1Ze0wdAOaqkFRFTCFQVM1hI1wQ88v9ef0gfpy+kB9OX2od19Ws++mRayde+652LhxIzZs2OD+nHzyybjyyiuxYcMGLFmyBH19fT6zSiaTwbPPPutO+E866STouu7bZt++fdi0aVNJUUAQBDEVoOxDBEEQRKNomqWgra0NK1as8L0Wi8XQ3d3tvn7jjTdi7dq1WLZsGZYtW4a1a9ciGo3iIx/5CACgvb0d11xzDW655RZ0d3ejq6sLt956K1auXInzzjuv4d+JIAiilgQVL6PsQwRBEEQ9aHr2oVLcdtttSCaTuO666zAwMIBVq1bhySefRFtbLsju7rvvhqZpuPzyy5FMJnHuuefi+9//PlSVVtMIgpjaSAFg2qb7GhUvIwiCIOpBS4mC3/3ud77/GWO44447cMcddxT9TDgcxr333ot77723vo0jCIJoMFIUZK1cSjlyHyIIgiDqAdmhCYIgWhRXFNhCFDDGymZfIwiCIIiJQKKAIAiiRfFWNAbISkAQBEHUDxIFBEEQLUp+UDEFGRMEQRD1gkYYgiCIFiXfMkBBxgRBEES9IFFAEATRouRbBsh9iCAIgqgXJAoIgiBaFHIfIgiCIBoFjTAEQRAtSoGlgNyHCIIgiDpBooAgCKJFyRcB5D5EEARB1AsSBQRBEC0Kg78mAVkKCIIgiHpBooAgCKJFYYz5XIgopoAgCIKoFzTCEARBtDBeIUDuQwRBEES9IFFAEATRwpClgCAIgmgENMIQBEG0MD5LAcUUEARBEHWCRAFBEEQLQ+5DBEEQRCMgUUAQBNHCeK0DZCkgCIIg6gWJAoIgiBaGYgoIgiCIRkAjDEEQRAtD7kMEQRBEIyBRQBAE0cJQoDFBEATRCEgUEARBtDDkPkQQBEE0AhphCIIgWhivyxC5DxEEQRD1gkQBQRBEC0PuQwRBEEQjIFFAEATRwpD7EEEQBNEIaIQhCIJoYSj7EEEQBNEISBQQBEG0MOQ+RBAEQTQCEgUEQRAtDLkPEQRBEI2ARhiCIIgWxmsdIPchgiAIol6QKCAIgmhhyH2IIAiCaAQkCgiCIFoYch8iCIIgGgGNMARBEC0MZR8iCIIgGgGJAoIgiBZGCgGFKWCMNbk1BEEQxHSFRAFBEEQLIy0F5DpEEARB1BMaZQiCIFoYKQYoyJggCIKoJyQKCIIgWhiyFBAEQRCNgEYZgiCIFsa1FFCQMUEQBFFHSBQQBEG0MLFQDAAQD8Wb3BKCIAhiOqM1uwEEQRBEceKhON67+L0Ia+FmN4UgCIKYxpAoIAiCaHGktYAgCIIg6gW5DxEEQRAEQRDEDIdEAUEQBEEQBEHMcEgUEARBEARBEMQMh0QBQRAEQRAEQcxwSBQQBEEQBEEQxAyHRAFBEARBEARBzHBIFBAEQRAEQRDEDIdEAUEQBEEQBEHMcEgUEARBEARBEMQMh0QBQRAEQRAEQcxwSBQQBEEQBEEQxAyHRAFBEARBEARBzHBIFBAEQRAEQRDEDIdEAUEQBEEQBEHMcLRmN6AV4JwDAIaHh5vckplHNpvF+Pg4hoeHoet6s5tDTALqy+kF9ef0gfpy+kB9OX1oVF/Kua2c65aCRAGAkZERAMCCBQua3BKCIAiCIAiCqC0jIyNob28vuQ3jlUiHaY5t29i7dy/a2trAGGt2c2YUw8PDWLBgAd5++20kEolmN4eYBNSX0wvqz+kD9eX0gfpy+tCovuScY2RkBHPnzoWilI4aIEsBAEVRMH/+/GY3Y0aTSCToATdNoL6cXlB/Th+oL6cP1JfTh0b0ZTkLgYQCjQmCIAiCIAhihkOigCAIgiAIgiBmOCQKiKZiGAZuv/12GIbR7KYQk4T6cnpB/Tl9oL6cPlBfTh9asS8p0JggCIIgCIIgZjhkKSAIgiAIgiCIGQ6JAoIgCIIgCIKY4ZAoIAiCIAiCIIgZDokCgiAIgiAIgpjhkCggJsWdd96JU045BW1tbZg9ezY++MEP4s033/RtwznHHXfcgblz5yISiWDNmjV49dVXfduk02l85jOfQU9PD2KxGC699FLs3r3bt83AwACuuuoqtLe3o729HVdddRUGBwfr/RVnFLXoz8OHD+Mzn/kMjj76aESjUSxcuBDXX389hoaGfPuh/qwvtbo3vdu+733vA2MM//Zv/+Z7j/qyvtSyL59//nm8973vRSwWQ0dHB9asWYNkMum+T31ZX2rVl/v378dVV12Fvr4+xGIxnHjiifj5z3/u24b6sv5U0p+PPfYYLrzwQvT09IAxhg0bNhTsp2XmQJwgJsGFF17IH3nkEb5p0ya+YcMG/v73v58vXLiQj46OutvcddddvK2tjf/iF7/gGzdu5B/+8If5nDlz+PDwsLvN3/zN3/B58+bxp556iq9fv56fc845/N3vfjc3TdPd5qKLLuIrVqzg69at4+vWreMrVqzgl1xySUO/73SnFv25ceNGftlll/EnnniCb9myhf/2t7/ly5Yt4x/60Id8x6L+rC+1ujcl3/jGN/j73vc+DoA//vjjvveoL+tLrfpy3bp1PJFI8DvvvJNv2rSJv/XWW/xnP/sZT6VS7jbUl/WlVn153nnn8VNOOYW/8MILfOvWrfwrX/kKVxSFr1+/3t2G+rL+VNKfP/zhD/mXvvQl/tBDD3EA/OWXXy7YT6vMgUgUEDWlv7+fA+DPPvss55xz27Z5X18fv+uuu9xtUqkUb29v5//0T//EOed8cHCQ67rOH330UXebPXv2cEVR+K9+9SvOOeevvfYaB8D/8Ic/uNs8//zzHAB/4403GvHVZiQT6c8gfvrTn/JQKMSz2SznnPqzGUymLzds2MDnz5/P9+3bVyAKqC8bz0T7ctWqVfwLX/hC0f1SXzaeifZlLBbjP/zhD3376urq4t/97nc559SXzSK/P71s3749UBS00hyI3IeImiJdRLq6ugAA27dvx/79+3HBBRe42xiGgbPPPhvr1q0DALz00kvIZrO+bebOnYsVK1a42zz//PNob2/HqlWr3G1OPfVUtLe3u9sQtWci/VlsP4lEApqmAaD+bAYT7cvx8XFcccUVuO+++9DX11ewX+rLxjORvuzv78cLL7yA2bNnY/Xq1ejt7cXZZ5+N5557zv0M9WXjmeh9ecYZZ+Bf//VfcfjwYdi2jUcffRTpdBpr1qwBQH3ZLPL7sxJaaQ5EooCoGZxz3HzzzTjjjDOwYsUKAMLvEQB6e3t92/b29rrv7d+/H6FQCJ2dnSW3mT17dsExZ8+e7W5D1JaJ9mc+hw4dwle+8hVce+217mvUn41lMn150003YfXq1fhv/+2/Be6b+rKxTLQvt23bBgC444478Fd/9Vf41a9+hRNPPBHnnnsuNm/e7O6H+rJxTOa+/Nd//VeYponu7m4YhoFrr70Wjz/+OJYuXeruh/qysQT1ZyW00hxIq9meiBnPpz/9abzyyiu+lScJY8z3P+e84LV88rcJ2r6S/RAToxb9OTw8jPe///1Yvnw5br/99pL7KLUfYnJMtC+feOIJPP3003j55ZdL7p/6snFMtC9t2wYAXHvttfj4xz8OADjhhBPw29/+Ft/73vdw5513Bu4jfz9E7ZjMM/YLX/gCBgYG8Jvf/AY9PT34t3/7N/yP//E/8Pvf/x4rV64M3EfQfojaUao/J0Iz5kBkKSBqwmc+8xk88cQTeOaZZzB//nz3delukK9k+/v73ZWQvr4+ZDIZDAwMlNzmnXfeKTjugQMHClZUiMkzmf6UjIyM4KKLLkI8Hsfjjz8OXdd9+6H+bAyT6cunn34aW7duRUdHBzRNc92/PvShD7luCtSXjWMyfTlnzhwAwPLly33bHHvssdi1a5e7H+rLxjCZvty6dSvuu+8+fO9738O5556Ld7/73bj99ttx8skn49vf/ra7H+rLxlGsPyuhleZAJAqIScE5x6c//Wk89thjePrpp7F48WLf+4sXL0ZfXx+eeuop97VMJoNnn30Wq1evBgCcdNJJ0HXdt82+ffuwadMmd5vTTjsNQ0ND+OMf/+hu88ILL2BoaMjdhpg8tehPQFgILrjgAoRCITzxxBMIh8O+/VB/1p9a9OXf/u3f4pVXXsGGDRvcHwC4++678cgjjwCgvmwEtejLRYsWYe7cuQXpEt966y0cccQRAKgvG0Et+nJ8fBwAoCj+KZyqqq5FiPqyMZTrz0poqTlQzUKWiRnJJz/5Sd7e3s5/97vf8X379rk/4+Pj7jZ33XUXb29v54899hjfuHEjv+KKKwJTks6fP5//5je/4evXr+fvfe97A9NxHXfccfz555/nzz//PF+5ciWlV6sxtejP4eFhvmrVKr5y5Uq+ZcsW336oPxtHre7NfFAkJSn1Zf2oVV/efffdPJFI8J/97Gd88+bN/Atf+AIPh8N8y5Yt7jbUl/WlFn2ZyWT4kUceyc8880z+wgsv8C1btvB//Md/5Iwx/stf/tLdD/Vl/amkPw8dOsRffvll/stf/pID4I8++ih/+eWX+b59+9xtWmUORKKAmBQAAn8eeeQRdxvbtvntt9/O+/r6uGEY/KyzzuIbN2707SeZTPJPf/rTvKuri0ciEX7JJZfwXbt2+bY5dOgQv/LKK3lbWxtva2vjV155JR8YGGjAt5w51KI/n3nmmaL72b59u7sd9Wd9qdW9GbTffFFAfVlfatmXd955J58/fz6PRqP8tNNO47///e9971Nf1pda9eVbb73FL7vsMj579mwejUb5cccdV5CilPqy/lTSn4888kjgNrfffru7TavMgZjzpQiCIAiCIAiCmKFQTAFBEARBEARBzHBIFBAEQRAEQRDEDIdEAUEQBEEQBEHMcEgUEARBEARBEMQMh0QBQRAEQRAEQcxwSBQQBEEQBEEQxAyHRAFBEARBEARBzHBIFBAEQRAEQRDEDIdEAUEQBEEQBEHMcEgUEARBEBOCc47zzjsPF154YcF7999/P9rb27Fr164mtIwgCIKoFhIFBEEQxIRgjOGRRx7BCy+8gO985zvu69u3b8dnP/tZfPOb38TChQtresxsNlvT/REEQRACEgUEQRDEhFmwYAG++c1v4tZbb8X27dvBOcc111yDc889F+95z3tw8cUXIx6Po7e3F1dddRUOHjzofvZXv/oVzjjjDHR0dKC7uxuXXHIJtm7d6r6/Y8cOMMbw05/+FGvWrEE4HMaPf/zjZnxNgiCIaQ/jnPNmN4IgCIKY2nzwgx/E4OAgPvShD+ErX/kKXnzxRZx88sn4q7/6K1x99dVIJpP47Gc/C9M08fTTTwMAfvGLX4AxhpUrV2JsbAxf/OIXsWPHDmzYsAGKomDHjh1YvHgxFi1ahK9//es44YQTYBgG5s6d2+RvSxAEMf0gUUAQBEFMmv7+fqxYsQKHDh3Cz3/+c7z88st44YUX8Otf/9rdZvfu3ViwYAHefPNNHHXUUQX7OHDgAGbPno2NGzdixYoVrii45557cMMNNzTy6xAEQcw4yH2IIAiCmDSzZ8/GX//1X+PYY4/FX/zFX+Cll17CM888g3g87v4cc8wxAOC6CG3duhUf+chHsGTJEiQSCSxevBgACoKTTz755MZ+GYIgiBmI1uwGEARBENMDTdOgaWJYsW0bH/jAB/D3f//3BdvNmTMHAPCBD3wACxYswEMPPYS5c+fCtm2sWLECmUzGt30sFqt/4wmCIGY4JAoIgiCImnPiiSfiF7/4BRYtWuQKBS+HDh3C66+/ju985zs488wzAQDPPfdco5tJEARBOJD7EEEQBFFzPvWpT+Hw4cO44oor8Mc//hHbtm3Dk08+iU984hOwLAudnZ3o7u7Ggw8+iC1btuDpp5/GzTff3OxmEwRBzFhIFBAEQRA1Z+7cufiv//ovWJaFCy+8ECtWrMANN9yA9vZ2KIoCRVHw6KOP4qWXXsKKFStw00034R/+4R+a3WyCIIgZC2UfIgiCIAiCIIgZDlkKCIIgCIIgCGKGQ6KAIAiCIAiCIGY4JAoIgiAIgiAIYoZDooAgCIIgCIIgZjgkCgiCIAiCIAhihkOigCAIgiAIgiBmOCQKCIIgCIIgCGKGQ6KAIAiCIAiCIGY4JAoIgiAIgiAIYoZDooAgCIIgCIIgZjgkCgiCIAiCIAhihvP/A+WfHIFgy8XpAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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F8uGHH6IoChdffDFut9v3k52dTZ8+fcLcp7KzsznppJOCttWm70AzkU+dOpXs7GyMRiNms5khQ4YAxN1/v//+O7/++quv7wI/09ixY8nPz/et7l900UVYrdYgt5FXX30Vh8PBpZde6tvmdru57777OO6447BYLJhMJiwWC7/99lvE9k2dOjXIfSAvL49Bgwb5rtvWrVvZt28ff/3rXzEY/I/V1NRUzjvvPL799tswF7nzzjsv7Dx1Me5WrlwJEDamJk+eTEpKStiY6tu3Lx06dPD9b7PZ6NatW63Gw9lnnx30f7T7uKZ88cUX/P7770ybNs33vNBd3aK5PmVnZ2M2m2nZsiVTpkzhxBNPZPHixTGfMy0tLexzTZ06FVVVg6wqK1euZMSIEbRo0cJ3L9x1110UFhZy4MABQOtzi8XC3/72NxYvXhzRpbAqatu/oc+lqVOnAvjGt8Fg4Nprr+XDDz9k165dgLaqvHTpUmbOnFllBrFly5bh8XiqtSbEw/jx44P+79mzJ0CYtaxnz54UFRUFuRD98MMPnH322WRlZfmuxyWXXILH42Hbtm3VnvvDDz8kIyODs846K+hZ1LdvX7Kzs6vMRJeZmUnnzp156KGHePTRR/nhhx98bpo6sfTX6tWrKSoqYtq0aUFtUFWVv/zlL6xfvz7MVTPSGLHb7b4xGG/ftGzZkjPPPLO67mLlypWkpKT4LNs6+vMolu80Sf0hRYGk3vj999/58ssvGTduHEIIiouLKS4u9j0sIn15Z2VlBf1vtVoBwky0ycnJ2Gy2sH3tdnuN2jp16lT+85//cPnll/Ppp5+ybt061q9fT+vWras1D1dFdnZ2xG2FhYUAvt+6G1Ag7dq1871eFfv370cIQdu2bTGbzUE/3377bZj7U2gfg9Z3Nf2cZWVlnH766axdu5Z7772XVatWsX79et555x0g/NrF8nkAbr755rDPo5us9c+UmZnJ2WefzYsvvujz7V60aBEnnXQSxx9/vO+Ys2bN4s477+Tcc8/lgw8+YO3ataxfv54+ffpEbF9tr5uqqhw+fDhoe6R962LcFRYWYjKZaN26ddB2RVGCPoNOosdDpGNGu49riu5rPWHCBN9zpUWLFpx22mm8/fbbYbEToPljr1+/nk8//ZTzzjuPL7/8kuuuuy7mc7Zt2zZsmz5O9D5dt24do0aNAuC5557jm2++Yf369dx+++2A//N37tyZ5cuX06ZNG6655ho6d+5M586deeKJJ2JqS23612Qyhb0/9HMAXHbZZSQlJflc3f773/+SlJTk8yWPhu5nn8hkBJmZmUH/WyyWKrfr3wO7du3i9NNPZ+/evTzxxBN89dVXrF+/3hefFUt/7d+/n+LiYiwWS9jzqKCgoEr3UkVRWLFiBaNHj2bevHn079+f1q1bc/3111NaWgrE1l/6M3HSpElhbXjwwQcRQlBUVBT0nurGSLx9E+n5FYnCwkJfmuBA2rRpg8lkiuk7TVJ/yOxDknpD9+996623IuYQX7x4Mffee2+QZSCR6KIh1Ic69CF+5MgRPvzwQ+bMmcM///lP33aHwxH2oI2XSHnQCwoK6NKlC+B/cOfn54ftt2/fPl+2lKpo1aoViqLw1Vdf+R78gUTalkhWrlzJvn37WLVqlc86AEScmMWC/plnz54d1Qe1e/fuvr8vvfRS3nzzTZYtW0aHDh1Yv349Tz31VND+L7/8MpdcconPN1/n0KFDZGRkhB0/2nXTr1d1181gMNCyZcug7aFfknU17rKysnC73Rw8eDBIGAghKCgo8AWRN1WOHDnC22+/DRD1syxZsiTM57lPnz6+sTVy5EhGjx7Ns88+y4wZM2Lqk0gByfo40cfDa6+9htls5sMPPwxatPjf//4X9t7TTz+d008/HY/Hw3fffceTTz7JDTfcQNu2bX2W1brA7XZTWFgYNGkM/RwALVq0YNq0aTz//PPcfPPNLFy4kKlTp0a8XwLRx9yePXvIzc1N/AeIg//973+Ul5fzzjvvkJeX59seKdVyNPRg7qVLl0Z8PS0trcr35+Xl+UTstm3beOONN5g7dy5Op5Onn346pv7Sx+2TTz4ZNSNVJNFaFfH2Taz1ZbKysli7di1CiKD3HDhwALfbHdN3mqT+kJYCSb3g8XhYvHgxnTt35vPPPw/7uemmm8jPz+eTTz6pszboGVk2bdoUtF3PSKOjKApCiLDJ8/PPPx+WWSReXnnllaD/V69ezc6dO33ZGk499VSSkpJ8Qb46e/bsYeXKlQwfPty3Ldpq4Pjx4xFCsHfvXgYMGBD207t377jbHc/Ko/7gD+2/Z555Ju7zgjbh79q1Kxs3boz4eQYMGBD0RTxq1Cjat2/PwoULWbhwITabjQsvvDCsjaHt++ijj9i7d2/ENrz66qtBAas7d+5k9erVvuvWvXt32rdvz5IlS4L2Ky8v5+233/ZlJKqKeMZdPNdDHzOhY+rtt9+mvLw8aEw1RZYsWUJlZSX/93//F/HZ0qpVq2qzJymKwn//+1+MRiN33HFHTOctLS0Ne3YsWbIEg8HAGWec4TuuyWQKWuiorKzkpZdeinpco9HIySef7Fuh3bBhQ0ztqQ2hz6UlS5YAhGWRuf766zl06BCTJk2iuLiYa6+9ttpjjxo1CqPRGCbMG4JIzyYhBM8991zYvtGsY+PHj6ewsBCPxxPxWRS4QFEd3bp144477qB3796+6xxLfw0ePJiMjAy2bNkS9ZmoW0liJZ6+iYfhw4dTVlYWJoRffPFF3+uSxoO0FEjqhU8++YR9+/bx4IMPRqx22KtXL/7zn/+wYMGCMH/RRJGdnc2IESO4//77admyJXl5eaxYscLn1qKTnp7OGWecwUMPPUSrVq3o2LEjX3zxBQsWLKh2Vaw6vvvuOy6//HImT57M7t27uf3222nfvr1vFTMjI4M777yT2267jUsuuYQLL7yQwsJC7r77bmw2G3PmzPEdS5/cP/jgg4wZMwaj0cgJJ5zA4MGD+dvf/sall17Kd999xxlnnEFKSgr5+fl8/fXX9O7dm6uvvjqudnfu3JmkpCReeeUVevbsSWpqKu3ataNdu3Zh+w4aNIiWLVty1VVXMWfOHMxmM6+88gobN26scb8988wzjBkzhtGjRzN9+nTat29PUVERv/zyCxs2bAjKXmU0Grnkkkt49NFHSU9PZ+LEibRo0SLoeOPHj2fRokX06NGDE044ge+//56HHnooqsn+wIEDTJgwgSuuuIIjR44wZ84cbDYbs2fPBjSf63nz5nHRRRcxfvx4rrzyShwOBw899BDFxcU88MAD1X7GeMadXk332WefJS0tDZvNRqdOnSK6/uir4LfeeislJSUMHjyYTZs2MWfOHPr168df//rXatvW0HzwwQcRV2AnTZrEggULaNmyJTfffHOYCyHgGwsbN26kT58+Uc/RtWtX/va3vzF//ny+/vprTjvttCrblJWVxdVXX82uXbvo1q0bH3/8Mc899xxXX321LyZj3LhxPProo0ydOpW//e1vFBYW8vDDD4cJv6effpqVK1cybtw4OnTogN1u9wmZESNGVNs/tcFisfDII49QVlbGwIEDWb16Nffeey9jxowJ64Nu3brxl7/8hU8++YTTTjutyv7U6dixI7fddhv/93//R2VlpS8t5pYtWzh06FC9FWAE7V6wWCxceOGF/OMf/8But/PUU0+FufaB9nx95513eOqppzjxxBMxGAwMGDCACy64gFdeeYWxY8fy97//nZNOOgmz2cyePXv4/PPPOeecc5gwYULE82/atIlrr72WyZMn07VrVywWCytXrmTTpk0+62As/ZWamsqTTz7JtGnTKCoqYtKkSbRp04aDBw+yceNGDh48GLcIi6dv4uGSSy7hv//9L9OmTWPHjh307t2br7/+mvvuu4+xY8fW+fiWxEmDhDdLmh3nnnuusFgs4sCBA1H3ueCCC4TJZBIFBQW+jEAPPfRQ2H6EZOCYNm2aSElJCdsvUmab/Px8MWnSJJGZmSlatGghLr74YvHdd9+FZdbZs2ePOO+880TLli1FWlqa+Mtf/iJ+/vnnqNkwYs0+9Nlnn4m//vWvIiMjw5dl6Lfffgvb//nnnxcnnHCCsFgsokWLFuKcc84RmzdvDtrH4XCIyy+/XLRu3VooiiIAsX37dt/rL7zwgjj55JNFSkqKSEpKEp07dxaXXHKJ+O6773z7DBkyRBx//PFh54+UCeTVV18VPXr0EGazOegaROrn1atXi1NPPVUkJyeL1q1bi8svv1xs2LAhrJ9jzT4khBAbN24UU6ZMEW3atBFms1lkZ2eLM88805fJKpBt27YJQABi2bJlYa8fPnxYzJgxQ7Rp00YkJyeL0047TXz11VdhmTP06/vSSy+J66+/XrRu3VpYrVZx+umnB/Wjzv/+9z9x8sknC5vNJlJSUsTw4cPFN998E7RPVRl1Yh13Qgjx+OOPi06dOgmj0RjUr5GuXWVlpbj11ltFXl6eMJvNIicnR1x99dXi8OHDQfvl5eWJcePGhbUrtF+iEXpv6uN+/fr1QfvFet/ofRXtZ+PGjQIQN9xwQ9Rj/PrrrwIQ1113XdAxI/X//v37RWpqqhg2bFiV7dLvm1WrVokBAwYIq9UqcnJyxG233RaWIeuFF14Q3bt3F1arVRx77LHi/vvvFwsWLAi6X9esWSMmTJgg8vLyhNVqFVlZWWLIkCHi/fffDzpWovtXf3Zu2rRJDB06VCQlJYnMzExx9dVXi7KysojvWbRokQDEa6+9VuWxQ3nxxRfFwIEDhc1mE6mpqaJfv35Bz4J4sg+9+eabQftF64dI1/qDDz4Qffr0ETabTbRv317ccsst4pNPPgnrr6KiIjFp0iSRkZHhe77quFwu8fDDD/uOk5qaKnr06CGuvPLKiM9znf3794vp06eLHj16iJSUFJGamipOOOEE8dhjjwVl2Yulv4QQ4osvvhDjxo0TmZmZwmw2i/bt24tx48YF9U+08a73WeB3Rqx9E+17Q38t9FlRWFgorrrqKpGTkyNMJpPIy8sTs2fPFna7PWpfSRoGRYgYkzhLJJIas2jRIi699FLWr1/vK5IkafysWrWKYcOG8eabb4Zlz5BImiN6Nq0dO3ZgNpsbujkSiSSBSPchiUQikUgkUXE4HGzYsIF169bx7rvv8uijj0pBIJEchUhRIJFIJBKJJCr5+fkMGjSI9PR0rrzyyrhSt0okkqaDdB+SSCQSiUQikUiaOTIlqUQikUgkEolE0syRokAikUgkEolEImnmSFEgkUgkEolEIpE0c2SgMaCqKvv27SMtLS3m0t0SiUQikUgkEkljRghBaWkp7dq1w2Co2hYgRQGwb98+cnNzG7oZEolEIpFIJBJJwtm9ezfHHHNMlftIUQCkpaUBWoelp6c3cGuaFy6Xi88++4xRo0bJvNdNHHktjy7k9Tx6kNfy6EFey6OH+rqWJSUl5Obm+ua6VSFFAfhchtLT06UoqGdcLhfJycmkp6fLB1wTR17Lowt5PY8e5LU8epDX8uihvq9lLO7xMtBYIpFIJBKJRCJp5khRIJFIJBKJRCKRNHOkKJBIJBKJRCKRSJo5MqYgRoQQuN1uPB5PQzflqMLlcmEymbDb7XXWt2azGaPRWCfHlkgkEolEIjkaaFBR0LFjR3bu3Bm2febMmTz++OPccccdfPzxx/z555+0aNGCESNG8MADD9CuXTvfvkOHDuWLL74Iev/555/Pa6+9lrB2Op1O8vPzqaioSNgxJRpCCLKzs9m9e3ed1YhQFIVjjjmG1NTUOjm+RCKRSCQSSVOnQUXB+vXrg1aHf/75Z0aOHMnkyZOpqKhgw4YN3HnnnfTp04fDhw9zww03cPbZZ/Pdd98FHeeKK67gnnvu8f2flJSUsDaqqsr27dsxGo20a9cOi8UiC5wlEFVVKSsrIzU1tdqiGjVBCMHBgwfZs2cPXbt2lRYDiUQikUgkkgg0qCho3bp10P8PPPAAnTt3ZsiQISiKwrJly4Jef/LJJznppJPYtWsXHTp08G1PTk4mOzu7TtrodDpRVZXc3FySk5Pr5BzNGVVVcTqd2Gy2OhEFoI2zHTt24HK5pCiQSCQSiUQiiUCjiSlwOp28/PLLzJo1K+pK/JEjR1AUhYyMjKDtr7zyCi+//DJt27ZlzJgxzJkzp8oiDQ6HA4fD4fu/pKQE0PzbXS5X0L4ulwshBKBNYCWJRe9bIUSd9a8QAiGEFAV1jH7vhN5DkqaJvJ5HD/JaHj3Ia3n0UF/XMp7jK0KflTUwb7zxBlOnTmXXrl1BMQM6drud0047jR49evDyyy/7tj/33HN06tSJ7Oxsfv75Z2bPnk2XLl3CrAyBzJ07l7vvvjts+5IlS8KsASaTiezsbHJzc7FYLLX4hJKGwul0snv3bgoKCnC73Q3dHIlEIpFIJJJ6oaKigqlTp3LkyJFqC/Q2GlEwevRoLBYLH3zwQdhrLpeLyZMns2vXLlatWlXlh/r+++8ZMGAA33//Pf3794+4TyRLQW5uLocOHQo7tt1uZ/fu3XTs2BGbzVbDTyeJhhCC0tJS0tLS6ixWw263s2PHDnJzc+U1rENcLhfLli1j5MiRstLmUYC8nkcP8loePchrefRQX9eypKSEVq1axSQKGoX70M6dO1m+fDnvvPNO2Gsul4spU6awfft2Vq5cWe0H6t+/P2azmd9++y2qKLBarVit1rDtZrM57MJ4PB4URcFgMNSZz3tdMXToUPr27cvjjz8e8XVFUXj33Xc599xz67Vdq1atYtiwYRw+fNh3PfU+rgk7duygU6dO/PDDD/Tt2zfsdYPBgKIoEa+vJPHIfj66kNfz6EFey6MHeS2PHur6WsZz7EYxy124cCFt2rRh3LhxQdt1QfDbb7+xfPlysrKyqj3W5s2bcblc5OTk1FVzjxry8/MZM2ZMTPsqisL//ve/hJx30KBB5Ofn06JFi4QcTyKRSCQSiURSOxrcUqCqKgsXLmTatGmYTP7muN1uJk2axIYNG/jwww/xeDwUFBQAkJmZicVi4Y8//uCVV15h7NixtGrVii1btnDTTTfRr18/Bg8e3FAfqclQVxmbqsLlcmGxWHznbiTeaxKJRCKRSCTNmga3FCxfvpxdu3Zx2WWXBW3fs2cP77//Pnv27KFv377k5OT4flavXg2AxWJhxYoVjB49mu7du3P99dczatQoli9fLrPMeFFVlX/84x9kZmaSnZ3N3Llzfa8Frv47nU6uvfZacnJysNlsdOzYkfvvvx/QiswBTJgwAUVRfP8DPPXUU3Tu3BmLxUL37t156aWXgs6vKApPP/0055xzDikpKdx7772sWrUKRVEoLi727ffNN98wZMgQkpOTadmyJaNHj+bw4cMALF26lNNOO42MjAyysrIYP348f/zxR8L7SiJpjHhUD+v3rmf3kd0N3RSJRCKRHMU0uKVg1KhREVeLO3bsWO0qcm5ublg14/qgwunmt/1l9XrOrm1TSbbEf7kWL17MrFmzWLt2LWvWrGH69OkMHjyYkSNHBu3373//m/fff5833niDDh06sHv3bnbv1iYh69evp02bNixcuJC//OUvPsH17rvv8ve//53HH3+cESNG8OGHH3LppZdyzDHHMGzYMN+x58yZw/33389jjz2G0Whk+/btQef+6aefGDlyJJdddhn//ve/MZlMfP75577CduXl5cyaNYvevXtTXl7OXXfdxYQJE/jxxx+bXJyHRBIvRZVFFJQVUOGqILdFbkM3RyKRSCRHKQ0uCiR1ywknnMCcOXMA6Nq1K//5z39YsWJFmCjYtWsXXbt25bTTTkNRFPLy8nyv6UXmMjIyglyOHn74YaZPn87MmTMBmDVrFt9++y0PP/xwkCiYOnVqkCUoVBQ88cQTDBgwgPnz5/u2HX/88b6/zzvvvKD9FyxYQJs2bdiyZQu9evWKr0MkkiaGR3iCfkskEolEUhdIUVADki0m+uRmNHQzYuKEE04I+j8nJ4cDBw6E7Td9+nRGjhxJ9+7d+ctf/sL48eMZNWpUlcf+5Zdf+Nvf/ha0bfDgwTzxxBNB2wYMGFDlcX7++WemTJkS9fU//viDO++8k2+//ZZDhw75ipzt2rVLigLJUY+veKKQxRMlEolEUndI34ujnNBUVIqiRKwc3L9/f7Zv387//d//UVlZyZQpU5g0aVK1xw+tLSCECNuWkpJS5TGqqx1w1llnUVhYyHPPPcfatWtZu3YtoMVBSCRHO7oY8KjSUiCRSCSSukOKAomP9PR0zj//fJ577jlef/113n77bYqKigBNXOg+/jo9e/bk66+/Dtq2evVqevbsGdd5jz/+eFauXBnxtcLCQn755RfuuOMOhg8fTs+ePX0ByBJJc0AXBdJSIJFIJJK6RLoPSQB47LHHyMnJoW/fvhgMBt58802ys7PJyMgAtMDvFStWMHjwYKxWKy1btuSWW25hypQp9O/fn+HDh/PBBx/wzjvvsHz58rjOfeONNzJ48GBmzpzJVVddhcVi4fPPP2fy5MlkZmaSlZXFs88+S05ODrt27eKf//xnHfSARNI4kaJAIpFIJPWBtBRIAEhNTeXBBx9kwIABDBw4kB07dvDxxx/7svs88sgjLFu2jNzcXPr16wfAueeeyxNPPMFDDz3E8ccfzzPPPMPChQsZOnRoXOfu0qULS5cuZePGjZx00kmceuqpvPfee5hMJgwGA6+99hrff/89vXr14sYbb+Shhx5K9MeXSBotgaJA1vWQSCQSSV0hLQVHMatWrQrbFliVOHCCccUVV3DFFVdEPdZZZ53FWWedFbb96quv5uqrr476vkiTmKFDh/qDJ73xDUOGDOGbb76JeIwRI0awZcuWqMeNJX2tRNJUEfjHtipUjIqswSKRSCSSxCMtBRKJRNKICQwwli5EEolEIqkrpCiQSCSSRkygpUDWKpBIJBJJXSFFgUQikTRiAq0D0lIgkUgkkrpCigKJRCJpxAQKAVmrQCKRSCR1hRQFEolE0oiRlgKJRCKR1AdSFEgkEkkjJshSIGMKJBKJRFJHSFEgkUgkjZjAdLvSUiCRSCSSukKKAolEImnEyJgCiUQikdQHUhRIJBJJI0bGFEgkEomkPpCiQCKRSBoxUhRIJBKJpD6QokASN5s3b+a8886jY8eOKIrC448/HrbP/fffz8CBA0lLS6NNmzace+65bN26NWy/X375hQsvvJCWLVuSlpbGKaecwq5du+rhU0gkTQMZaCyRSCSS+kCKAkncVFRUcOyxx/LAAw+QnZ0dcZ8vvviCa665hm+//ZZly5bhdrsZNWoU5eXlvn3++OMPzjjjDLp27crKlSvZuHEjd955Jzabrb4+ikTS6JGWAolEIpHUB1IU1ACP6mmQn3h566236N27N0lJSWRlZTFixAjKy8tZtWoVJ510EikpKWRkZDB48GB27twJwNy5c+nbty/PPPMMubm5JCcnM3nyZIqLi33HHThwIA899BAXXHABVqs14rmXLl3K9OnTOf744+nTpw8LFy5k165dfP/99759br/9dsaMGcM999xDv379OPbYYxk3bhxt2rSJ+7NKJEcrMtBYIpFIJPWBqaEb0NTwqB4+/u3jBjn32K5jMRqMMe2bn5/PhRdeyLx585gwYQKlpaV89dVXCCE499xzueKKK3j11VdxOp2sW7cORVF87/3999954403+OCDDygpKWHGjBlcc801vPLKKzVu+5EjRwDIzMwEQFVVPvroI2655RbOO+88fvrpJzp16sTs2bM599xza3weieRoQyBTkkokEomk7pGi4CglPz8ft9vNxIkTycvLA6B3794UFRVx5MgRxo8fT+fOnQHo2bNn0HvtdjuLFy/mmGOOAeDJJ59k3LhxPPLII1HdhapCCMGsWbM47bTT6NWrFwAHDhygrKyMBx98kNtvv52HHnqIzz77jIkTJ/L5558zZMiQ2nx8ieSoQcYUSCQSiaQ+kKIgTowGI2O7jm2wc8dKnz59GD58OL1792b06NGMGjWKSZMmkZmZyfTp0xk9ejQjR45kxIgRTJkyhZycHN97O3To4BMEAKeeeiqqqrJ169YaiYJrr72WTZs28fXXX/u2qao20Tn77LOZOXMm6enp9O/fn9WrV/P0009LUSCReJExBRKJRCKpD2RMQQ0wGowN8hNXG41Gli1bxieffMJxxx3Hk08+Sffu3dm+fTsLFy5kzZo1DBo0iNdff51u3brx7bffRj2W7loU6GIUK9dddx3vv/8+n3/+eZDQaNWqFSaTieOOOy5o/549e8rsQxJJAFIUSCQSiaQ+kKLgKEZRFAYPHszdd9/NDz/8gMVi4d133wWgX79+zJ49m9WrV9OrVy+WLFnie9+uXbvYt2+f7/81a9ZgMBjo1q1bzOcWQnDttdfyzjvvsHLlSjp16hT0usViYeDAgWFpSrdt2+Zzd5JIJDLQWCKRSCT1g3QfOkpZu3YtK1asYNSoUbRp04a1a9dy8OBBkpKSmD17NmeffTbt2rVj69atbNu2jUsuucT3XpvNxrRp03j44YcpKSnh+uuvZ8qUKT7XIafTyZYtW3x/7927lx9//JHU1FS6dOkCwDXXXMOSJUt47733SEtLo6CgAIAWLVqQlJQEwC233ML555/PwIEDGTNmDJ999hkffPABq1atqseekkgaN9JSIJFIJJL6QIqCo5T09HS+/PJLHn/8cUpKSsjLy+ORRx5h4sSJXHXVVSxevJjCwkJycnK49tprufLKK33v7dKlCxMnTmTs2LEUFRUxduxY5s+f73t937599OvXz/f/ww8/zMMPP8yQIUN8E/qnnnoKgKFDhwa1a+HChUyfPh2ACRMmMH/+fO6//37++c9/0r17d95++21OO+20uukUiaQJIgONJRKJRFIfSFFwlNKzZ0+WLl0a8TXdhagqrr76aq6++uqIr3Xs2BEhRMTXdKp7Xeeyyy5j0qRJpKenYzBIbzaJJJTAe0laCiQSiURSV8hZmEQikTRipPuQRCKRSOoDKQokEomkESMDjSUSiURSH0hRIAli7ty5/Pjjjw3dDIlEQrhlQFoKJBKJRFJXSFEgkUgkjZRQESADjSWSpovD7ZDWPkmjRooCiUQiaaSEBuxLS4FE0jRxeVys2L6CNXvWNHRTJJKoSFEgkUgkjZQwS4FcZZRImiQVrgo8qodSR2lDN0UiiYoUBRKJRNJIkTEFEsnRge76J10AJY0ZKQokEomkkSJFgURydKBb+YQQ8j6WNFriLl62Y8cOvvrqK3bs2EFFRQWtW7emX79+nHrqqdhstrpoo0QikTRLZKCxRHJ0EHjvelQPBqNck5U0PmIWBUuWLOHf//4369ato02bNrRv356kpCSKior4448/sNlsXHTRRdx6663k5eXVZZslEomkWaCLAoNiQBUqQgiEECiK0sAtk0gk8RAYD+QRHsyYG7A1EklkYpKq/fv359FHH+Xiiy9mx44dFBQU8P333/P111+zZcsWSkpKeO+991BVlQEDBvDmm2/WdbslDchzzz3H6aefTsuWLWnZsiUjRoxg3bp1Ufe///77URSFG264IWj79OnTMRqNtGzZEqPRiKIonHLKKXXceomk6aCLApPBFLZNIpE0HUItBRJJYyQmUfB///d/fPfdd1x77bV06NAh7HWr1crQoUN5+umn+eWXX+jYsWNMJ+/YsSOKooT9XHPNNYDmezd37lzatWtHUlISQ4cOZfPmzUHHcDgcXHfddbRq1YqUlBTOPvts9uzZE9P5JTVj1apVXHjhhXz++eesWbOGDh06MGrUKPbu3Ru27/r163n22Wc54YQTIh5r9OjR/Prrr+zdu5f8/Hw+/vjjum6+RNJkEGgpSc1G/6qidCGSSJoeoZYCiaQxEpMoGDduHABut5vFixdTUFAQdd9WrVoxcODAmE6+fv168vPzfT/Lli0DYPLkyQDMmzePRx99lP/85z+sX7+e7OxsRo4cSWmpP6XXDTfcwLvvvstrr73G119/TVlZGePHj8fjqcObTvU0zE+cvPXWW/Tu3ZukpCSysrIYMWIE5eXlrFq1ipNOOomUlBQyMjIYPHgwO3fuBLSKxn379uWZZ54hNzeX5ORkJk+eTHFxse+4r7zyCjNnzqRv37706NGD5557DlVVWbFiRdD5y8rKuOiii3juuedo2bJlxDZarVbatm1LdnY22dnZZGZmxv05JZKjFd0qYFSMGBRD0DaJRNJ0kJYCSVMgrkBjk8nE1VdfzS+//JKQk7du3Tro/wceeIDOnTszZMgQhBA8/vjj3H777UycOBGAxYsX07ZtW5YsWcKVV17JkSNHWLBgAS+99BIjRowA4OWXXyY3N5fly5czevTohLQzCNUD+xpoNbvdWDAYY9o1Pz+fCy+8kHnz5jFhwgRKS0v56quvEEJw7rnncsUVV/Dqq6/idDpZt25dkI/y77//zhtvvMEHH3xASUkJM2bM4JprruGVV16JeK6KigpcLlfYhP6aa65h3LhxjBgxgnvvvTfie7/44gu6du1Ky5YtGTJkCP/6179o06ZNjB0ikRzd6AJAURRfXIGcUEgkTQ9pKZA0BeLOPnTyySfz448/JjyY2Ol08vLLLzNr1iwUReHPP/+koKCAUaNG+faxWq0MGTKE1atXc+WVV/L999/jcrmC9mnXrh29evVi9erVUUWBw+HA4XD4/i8pKQHA5XLhcrmC9nW5XFoKMVVFVVVQVWiolTpVBWILMNy7dy9ut5tzzz3X5/J1/PHHU1RUxJEjRxg7diydOnUCoHv37t7Da4GMdrudhQsXcswxxwDwxBNPcNZZZ/HQQw+RnZ0ddq5bb72V9u3bc+aZZ2p9BLz22mts2LCBtWvX+rbp/agzevRoJk6cSKtWrThw4ABz587lzDPPZP369Vit1pr1UQT0z+VyuTAaYxNVkvjR753Qe0hScxxOB26PG9WjPX/cHjcOpwOLYqnzc8vrefQgr2XDY3facXvc2t8OOy5zza6FvJZHD/V1LeM5ftyiYObMmcyaNYvdu3dz4oknkpKSEvR6NN/x6vjf//5HcXEx06dPB/C5KLVt2zZov7Zt2/pcXQoKCrBYLGGuKW3btq3Sxen+++/n7rvvDtv+2WefkZycHLTNZDKRnZ1NWVkZTqdT25h6WlyfLWGUlce8a6dOnRgyZAh9+vThzDPPZNiwYZxzzjlkZGQwdepUxowZw9ChQxk6dCjnnnuub7LvcDg45phjSE9P94ml448/HlVV+eGHHxg8eHDQeZ544gleffVVPvjgA5xOJ06nkz179nDDDTfw9ttv+7a53W6cTqfvmABjxozx/X3cccfx2muvccIJJ/DWW29x1lln1aangnA6nVRWVvLll1/idrsTdlxJZHQ3QEntKXIV8XvF76Sb0nGoDhyqg4pfKkg1pdZbG+T1PHqQ17Lh2FG5gwPOAwAUJxeTaa6dq6y8lkcPdX0tKyoqYt43blFw/vnnA3D99df7timK4kuTV1Nf/gULFjBmzBjatWsXtD009V4s6fiq22f27NnMmjXL939JSQm5ubmMGjWK9PT0oH3tdju7d+8mNTW1ydVhWLFiBatXr2bZsmUsWLCAf/3rX6xZs4aXXnqJWbNm8emnn/L+++/zr3/9i08//ZRTTjkFq9WKwWAI6weAlJSUoO2PPPIIjz32GJ999hkDBgzwbd+2bRsHDx5k2LBhvm0ej4fVq1fz3HPPUVlZ6VuxF0JQWlpKWloa6enp5OXlsXfv3ojnryl2u52kpCTOOOOMJncNmxIul4tly5YxcuRIzGaZbi8R7C3dS0ZBBq2TW1PhqqDcVc6gYwaRmVT3sTfyeh49yGvZ8Py4/0f2lGhJUPq07UNuem6NjtNkr6XHAxUVkJbW0C1pNNTXtQxcjK2OuEXB9u3b431LtezcuZPly5fzzjvv+LbpK9cFBQXk5OT4th84cMBnPcjOzsbpdHL48OEga8GBAwcYNGhQ1PNZrdaI7ilmsznswng8Hs2f12DAYGh6xUZOP/10Tj/9dObMmUNeXh7vvfces2bN4sQTT+TEE0/ktttu49RTT+W1115j0KBBKIrCrl27KCgo8Am0tWvXYjAY6NGjh68PHnroIe69914+/fRTTjrppKBzjhw5kp9++ilo26WXXkqPHj249dZbg/pYdydSFIXDhw+ze/du2rVrl9C+NhgMKIoS8fpKEo/s58RhMBowGU1YzBY8eHCoDgxGQ732r7yeRw/yWjYcBoN2LwMJuYeb3LX86SfYuxdOOw2iJB5prtT1tYzn2HGLgrooTLZw4ULatGnjy3IEmvtLdnY2y5Yto1+/foDmBvLFF1/w4IMPAnDiiSdiNptZtmwZU6ZMAbQA259//pl58+YlvJ1NibVr17JixQpGjRpFmzZtWLt2LQcPHiQpKYnZs2dz9tln065dO7Zu3cq2bdu45JJLfO+12WxMmzaNhx9+mJKSEq6//nqmTJniE2rz5s3jzjvvZMmSJXTs2NHnqpWamkpqaippaWn06tUrqD0pKSlkZWX5tpeVlTF37lwmTJhAWloahw4d4o477qBVq1ZMmDChnnpJImncCKGlJFVQZPYhiaQJ41b9rqvNMllAebn/txQFjZa4RYHOli1b2LVrl9/P3svZZ58d13FUVWXhwoVMmzYNk8nfHL3Y1X333UfXrl3p2rUr9913H8nJyUydOhWAFi1aMGPGDG666SaysrLIzMzk5ptvpnfv3r5sRM2V9PR0vvzySx5//HFKSkrIy8vjkUceYeLEiVx11VUsXryYwsJCcnJyuPbaa7nyyit97+3SpQsTJ05k7NixFBUVMXbsWObPn+97ff78+TidTiZNmhR0zjlz5jB37tyY2mc0Gvnpp5948cUXKS4uJicnh2HDhvH666+TJs2LEgkQkJLUIFOSSiRNmaCUpM0x+5AezycDpBs1cYuCP//8kwkTJvDTTz/5YgnA7/sfb0zB8uXL2bVrF5dddlnYa//4xz+orKxk5syZHD58mJNPPpnPPvssaNL42GOPYTKZmDJlCpWVlQwfPpxFixY1+ywzPXv2ZOnSpRFfe/fdd6t9/9VXX83VV18d8bUdO3bE3Z5Vq1YF/Z+UlMSnn36KqqqUlJSQnp7eJN2zJJK6xJeSFAWjNx1xs5xQSCRNnEDrQLMU9vrcUCb7aNTEPQv7+9//TqdOndi/fz/Jycls3ryZL7/8kgEDBoRN/GJh1KhRCCHo1q1b2GuKojB37lzy8/Ox2+188cUXYW4pNpuNJ598ksLCQioqKvjggw/Iza1ZAI9EIpE0JvTJg0ExSEuBRNKEafbFy3QxUJeFZSW1Jm5LwZo1a1i5ciWtW7f2Bd+edtpp3H///Vx//fX88MMPddFOiUQiaXYEigKj4rUUNMcJhUTSxAm8bwPjC5oN0lLQJIjbUuDxeEhN1XJkt2rVin379gFaAPLWrVsT2zpJvTN37lx+/PHHhm6GRCIBBJp7prQUSCRNm2YdU6AXfgUpCho5cVsKevXqxaZNmzj22GM5+eSTmTdvHhaLhWeffZZjjz22LtookUgkzRJ9dVGKAomkaRNoKWh21r5AlyEpCho1cYuCO+64g3Jvaql7772X8ePHc/rpp5OVlcXrr7+e8AZKJBJJc0W3FCiKDDSWSJoyzdpSkEhR4HBAhDpTksQQtygYPXq07+9jjz2WLVu2UFRURMuWLautNCyRSCSS2JGBxhJJ00cVqi9TIzRDS0GgEKiNKCgogPXroUcP6Nq19u2ShFHjHJC///47n376KZWVlWRmZiayTRKJRCJBBhpLJEcDofdssxP2ibIUFBZqv4uLa9UcSXTiFgWFhYUMHz6cbt26MXbsWPLz8wG4/PLLuemmmxLeQIlEImmuSEuBpNFQVAQ1qFEjCXcXanbuQ4myFFRUaL9DiuZKEkfcouDGG2/EbDaza9cukpOTfdvPP//8qMWyJBKJRBI/QZYCGVMgaUh+/BF++gmOHGnoljQ5Qi0Fzc7alyhRUFmp/W5qosDjAbsdAlzIGitxxxR89tlnfPrppxxzzDFB27t27crOnTsT1jCJRCJp7uh+yLqVAKSlQNIACOGfkFVWQosWDdueJkaztxQkyn1ItxQ4HLVrT31z6BCsWwcZGXD66Q3dmiqJ21JQXl4eZCHQOXToEFYZEd4seOeddxgwYAAZGRmkpKTQt29fXnrppaB9OnbsiKIoYT/XXHONbx8hBHfffTc9e/YkJSWFoUOHsnnz5vr+OBJJo0W6D0kaBU6nP898U1ulbQRIS4EbXOVQsQ9UT82qGrtc2o/+dxNYdfehixmbrWHbEQNxi4IzzjiDF1980fe/oiioqspDDz3EsGHDEto4SeMkMzOT22+/nTVr1rBp0yYuvfRSLr30Uj799FPfPuvXryc/P9/3s2zZMgAmT57s22fevHk89thjzJs3j7Vr15Kdnc3IkSMpLS2t988kkTRGdAGgoMhAY0nDYbf7/5aiIG50y4DZaA76v9ng8UDFbqjYA84jNbMW6JYqnaY0DvW2R1hQb2zELQoeeughnnnmGcaMGYPT6eQf//gHvXr14ssvv+TBBx+sizY2PjyehvmJk7feeovevXuTlJREVlYWI0aMoLy8nFWrVnHSSSeRkpJCRkYGgwcP9rl+zZ07l759+/LMM8+Qm5tLcnIykydPpjgg2n/o0KFMmDCBnj170rlzZ/7+979zwgkn8PXXX/v2ad26NdnZ2b6fDz/8kM6dOzNkyBBAsxI8/vjj3HbbbZx11ln06tWLxYsXU1FRwZIlS2p3fSSSowRpKZA0CgJFQVNz3WgE6ELeYrQA2vdfs7qP3W4Q3lV+4a6ZKNBX23Wa0jjU294EREHcMQXHHXccmzZt4qmnnsJoNFJeXs7EiRO55ppryMnJqYs2Ni48Hvj444Y599ixYDTGtGt+fj4XXngh8+bNY8KECZSWlvLVV18hhODcc8/liiuu4NVXX8XpdLJu3bqgGhO///47b7zxBh988AElJSXMmDGDa665hldeeSXsPEIIVq5cydatW6OKQqfTycsvv8ysWbN859m+fTsFBQWMHDnSt5/VamXIkCGsXr2aK6+8Mp6ekUiOSgJFgX7vNLtVRknDIy0FtUK/Z61GK+VoxV89qgeDscZZ4ZsWHg+oXiEgPIkRBU1pHB7NogAgOzubu+++O9FtkSSQ/Px83G43EydOJC8vD4DevXtTVFTEkSNHGD9+PJ07dwagZ8+eQe+12+0sXrzYF0z+5JNPMm7cOB555BGys7MBOHLkCO3bt8fhcGA0Gpk/f37QBD+Q//3vfxQXFzN9+nTftoKCAgDatm0btG/btm1lwLpE4iWSKGhWK4ySxoEUBbVCtxSYDCYURUEIgUd4MGNu4JbVE263ZiGAxFkKmtI41NuelNSw7YiBuEVBx44dueyyy7j00kvJzc2tizY1boxGbcW+oc4dI3369GH48OH07t2b0aNHM2rUKCZNmkRmZibTp09n9OjRjBw5khEjRjBlypQgK0+HDh2CskudeuqpqKrK1q1bfaIgLS2NH3/8kbKyMlasWMGsWbM49thjGTp0aFhbFixYwJgxY2jXrl3Ya6FVsIUQsjK2ROJFigJJo0C6D9UK3VJgNBgxKkbcwt28YoNcTn9gsKo2L/cht9sfIN0ELAVx265uuukm3nvvPTp16sTIkSN57bXXcDSVi5MojMaG+YmriUaWLVvGJ598wnHHHceTTz5J9+7d2b59OwsXLmTNmjUMGjSI119/nW7duvHtt99GPZY+GQmcrBsMBrp06ULfvn256aabmDRpEvfff3/Ye3fu3Mny5cu5/PLLg7br4kK3GOgcOHAgzHogkTRXBP6UpDLQWNJgBAZ5NqUV2kaCfs8aFWPzrDfiChCV1NB9KDRYt6mMQ13MWCxgqpFzTr0Styi47rrr+P777/n+++857rjjuP7668nJyeHaa69lw4YNddFGSQ1RFIXBgwdz991388MPP2CxWHj33XcB6NevH7Nnz2b16tX06tUrKLh3165d7Nu3z/f/mjVrMBgMdOvWLeq5hBARxeHChQtp06YN48aNC9reqVMnsrOzWb58uW+b0+nkiy++YNCgQTX+zBLJ0YQMNJY0CqT7UK0ItRRAMxP37oC5gVpL96GMDO13UxmHTSieAGogCnT69OnDE088wd69e5kzZw7PP/88AwcOpE+fPrzwwgu+ojuShmHt2rXcd999fPfdd+zatYt33nmHgwcPkpSUxOzZs1mzZg07d+7ks88+Y9u2bUFxBTabjWnTprFx40a++uorrr/+eqZMmeJb3b///vtZtmwZf/75J7/++iuPPvooL774IhdffHFQG1RVZeHChUybNg1TiEJWFIUbbriB+++/nw8//JCff/6Z6dOnk5yczNSpU+u+gySSJoAvJamiNM8VRknjIFAU1DAbXnOm2VsKnF5RYFCokaXA6fS/Ry+c11Q8VJpQPAHUMNAYwOVy8e6777Jw4UKWLVvGKaecwowZM9i3bx+33347y5cvl6klG5D09HS+/PJLHn/8cUpKSsjLy+ORRx5h4sSJXHXVVSxevJjCwkKflScw20+XLl2YOHEiY8eOpaioiLFjxzJ//nzf6+Xl5cycOZM9e/aQlJREjx49ePnllzn//POD2rB8+XJ27drFZZddFrGN//jHP6ioqODmm2+muLiYk08+mc8++4y0tLS66RSJpIkhLQWSBsfj8ftE6zidTWaS0xhwezPvNFtLgcvr+mMxg7sGoiCw+Jc+7pqKpaAJ1SiAGoiCDRs2sHDhQl599VWMRiN//etfeeyxx+jRo4dvn1GjRnHGGWcktKGS+OjZsydLly6N+JruQlQVV199NVdffXXE1+69917uvffeao8xatSoKi1GiqIwZ84cbrzxRtLT0zEYmkl6NokkRgJFgT6Z0HOc6yJBIqlTdCuB0Qhms/a/wyFFQRzoVgGTwdQ8LQUu7wTeatEEQU1FQXKy5psPTUcUNDH3obhFwcCBAxk5ciRPPfUU5557LmZzeEqt4447jgsuuCAhDZRIJJLmSiRLgb5digJJvaCLAptNEwZ2e9OZkDUSgtyHmqOlQI8psJih1BG/KNBX25OSwGrV/m5q7kNHmyjYtm0b3bp1488///TlvY9GSkoKCxcurHXjJBKJpLkihPBZ2iKJAomkXggUBbo1V4qCuAgKNG6WlgLvBN5qrlnxskiWApdLS3Pa2FOYNzFREPNSU79+/ejZsyfz589nzZo1ddkmSQMyd+5cfvzxx4ZuhkTS7NHTkYK/ToEuDJrVKqOkYQkUBfqErKms0jYSpKXAKyJtFhBqeIxKdUQSBULEf5z6xuXyC6Am4m4XsygoLCxk3rx5FBYWMmHCBNq2bcuMGTN4//33sQdmJpBIJBJJrQm0BuhiQAYbS+qdQFGgu25IS0FcNGtLgaqCxzt5t3jdzV1xispAUWAwaLEt0DjHoVD9hdr0dlutcdeaaihiFgU2m42zzjqL559/nvz8fN59911at27NP//5T7KysjjnnHN44YUXOHDgQF22t8GQKVabLvLaSZoigRN/Bc1E3uwmFJKGJ5KloDFOxhoxzdpS4PGA8K6WW7we67URBdB4LVZChYIVcPAb7f8m5joENaxToCgKgwYN4oEHHmDLli38+OOPnHHGGSxatIjc3Fz++9//JrqdDYYeSF0RWmJb0mRwer/AjE1EqUskEFyjQK8mLi0FknpHFwVJSY13MtbIadaWArdbK1hmUPwVfV1xeJc4HJq1QVE0YQqN12LlqQSPHZyHNWtBE6tRALWoUxBI165duemmm7jpppsoLCykqKgoEYdtFBiNRjIyMnwWkOTkZN8XtKT2qKqK0+nEbrfXSUpSVVU5ePAgycnJYQXUJJLGTGDmIR0pCiT1jp75xWbzB3U2tslYI0daCtya24/JuzDnimP8BNYo0OcIjdViFSj0hLvJ1SiAGoqCvXv38s0333DgwAFUNcDErShcd911ZGVlJayBjQG9ku/R6hrVkAghqKysJCkpqc7ElsFgoEOHDlLMSZoUgZmHdJrdhELSsAjhtwrYbH5f6cY2GWvkJNRSoKoo8WbvaUjcblA9YDX6YwHicR+K5ILTWC1Wqjv47yboPhS3KFi4cCFXXXUVFouFrKysoImWLgqONhRFIScnhzZt2uBq7NHuTQyXy8WXX37JGWecEbHmRSKwWCyyMJqkyVEvlgKPB1avhtatIaAApUQCaJN/feHPatXGi769qVNYqE1Y27at81MlzFIgBMqaNbT58UcYPdo/yW7MuFyAB0xmsKVp2zxxpBONNLFurO5DoZaC5iAK7rrrLu666y5mz57d7CZaRqNR+qUnGKPRiNvtxmaz1ZkokEiaIr6YAvxfnAn3Rz5yBIqLNb9xKQokoejxBFar5rqhT8ZcLk0sNOU5wPr1migYOdL/ueoAvQI5JMBSsGsXHD6s9X1ZGaSmJrKpdYPboQkAgwEs3vbqtQpi+c6P5JffaN2H3MF/N0FREPcdXVFRwQUXXNDsBIFEIpHUJ/ViKdBXgT3SHUkSgcDMQ6AFih4NcQWq6i9+VV5ep6cKnPzXylLgdsPWrcH/NwWc3jFkNoE5SQs4Fu7Y2x/JL7+xug8FCj17hf+52oQCjeOe2c+YMYM333yzLtoikUgkEi+RRIE+oUio+xA0nQmGpH4JFQWK0nhXaeMhUATXcWbBwMl/rSwFv/0WPAmu7T1bXxkV9UxDJisoJi1fv6rG3v6m5D4UGFNQXqr9DgyQbgLE7T50//33M378eJYuXUrv3r3DXD4effTRhDVOIpFImitVWQoSFmisWwqEaPruIJLEEyoKQBMFDkfjW6WNh/oUBQFBxlBDYV9RAX/+qf2ti7LaiII//4TNm6FvX8jNrflxYkEXBWavKDAZ/e5D1SFE1ZaCxiYKRARR0IRch6AGouC+++7j008/pXv37gBhgcYSiUQiqT316j4E2pe0/mUrkUBwjQKdxjohi4fACWk9WQp0MeCzFMQj7H/5RbtXW7VC6HGNtREFR45ov4uL614UuL3i0WQBg1mzFLhidB+KVKMAGu8YDLT+lJdpv5uQ6xDUQBQ8+uijvPDCC0yfPr0OmiORSCTNAIdD82XOzIy6iyBCStJEBxoHrpjKuAJJKIE1CnQaq+tGPASO9dCYAvshMCVrP4k4VRRLQcz3cFER7Nun/X388fD779rftREFehZFexxFxGqKL6bABgYTmAzgjNF9KDDIOHDRWR+DemxIY0lSEug+VOEdV03MUhC3rdhqtTJ48OC6aItEIpE0D374Ab75Rlupi0KDWAokkkCiuQ/B0ek+5CqDQ2ug6PvEnSrEUhCXC6AQmpsPQIcOkJ7urwqcCFFQH9dQtxTUxH0oWvYeg8HfD41JnAYKvQqvpeBoFwV///vfefLJJ+uiLRKJRNI80L/sSkuj7uJLSRqwQpbw4mWBkyMpCiShVCUKGtNkLF4Cx73d7hfHrhLv65WJO1WopSAea9++fdrCgdHoTxmcSFFQ75YCr/tQrNmHqkrp2RjFqWj6loK43YfWrVvHypUr+fDDDzn++OPDAo3feeedhDVOIpFIjkr0CVUVX8r1bimQ7kNNHyFAqGBIQD0dj8c/eTya3YdAm3ympvrFgJo4gRwWU+D9rdcvCLy/w9r4yy/a3127+vtdjymozf0aaCmItYhYTQmMKUiUpQA0UVBR0bjGYWhMQUqboz+mICMjg4kTJ9ZFWyQSieToR4iYVurqraKxjrQUNH0K14LzCGQP1/y3a4M+No3GYJ/tulihdbu189VXMa7qRIHwJGyyHM1SAJpgMBijiIIdO7SYjqQkOPZY/3avpUBJhKVA98mvywQDLu84sXhjCoxGTbjWVhQ0RnGqi0mHSxtjinL0i4KFCxcmtAF79+7l1ltv5ZNPPqGyspJu3bqxYMECTjzxRCB6RqN58+Zxyy23ADB06FC++OKLoNfPP/98XnvttYS2VSKRSGpN4JdhnKIg4YHG0lJwdOE8rE1MPBVgSK/dsSK5DkHduA9t2AD798PQoZCWlrjjRiN0QqpPPgPdhoQblNoHsEaKKVAUBSEEHuHBTJRz6BmCOnb0Wweg9u5DqhruPlWXosCpxxTYtP40GWJ3H9ID3SNNrBul+5C3Xysd2mdsYjUKoAaiIJEcPnyYwYMHM2zYMD755BPatGnDH3/8QUZGhm+f/Pz8oPd88sknzJgxg/POOy9o+xVXXME999zj+z+piakziUTSTNBX6UBaCiSJRZ+UJML9JZooqIsVWj22pqysfkRBJEsBhIgCD0SbsMeB23stAi0ERsWIW7irjg3S2xg6Ya+tKAh8/oB2ndNrKSCrwh0gCnyWAgGuasZPtBoFOo0xtkWPKah0aOOnicUTQA1EQWFhIXfddReff/45Bw4cQFWDv5yKiopiPtaDDz5Ibm5ukPWhY8eOQftkZ2cH/f/ee+8xbNgwjg00pwHJyclh+zYV1m0v4qRO0VMTSiSSo4gYRYEQWkpShToMNJaWgqMHoWoTKQj2ba4psVgKEuWPrk/sQiesdUXoWNfTkroDRIHqhkSEZnivhSnAnctoMOJW3VVb/PQ2GkMaoYuCmt6vkURBXaKLAkuSP6YA/BaEaFRWauPLYPAL0UD0bY3KUuAVBXavKGiCi9Nxi4KLL76YP/74gxkzZtC2bdtaFSx7//33GT16NJMnT+aLL76gffv2zJw5kyuuuCLi/vv37+ejjz5i8eLFYa+98sorvPzyy7Rt25YxY8YwZ84c0qKsODgcDhwBA6mkRMs44HK5cNXXQymAzXsP0++YelgdaYTo/d0Q/S5JLPJaxkhFhd8fuLwc4XRGnFg5XA7cHjcej8fXpx6PB7fHjdPlTEw/Oxy+tojKyqAJg7yeTQzVheLxXkuXHYy1vJalpShut1YsK/B9iuIfMxUVtXc9UVUU78RUlJfXjzCw27XPkJKiCYKSEoTTjuLypycVzkogwmQ03lM57bg9blSP6ut/4RG4PW7sDjtJhsgTR8XhALcbofv9e3F5hZ/bbkfUpK8Cnz+AKCur0z43OCpB9aBiBLcbxWBEUT0Ie1nV7T9yxHeNRCSriD4OKypq1g91gOJyaGKyrBzF7UI1m6vs2/p6xsZzfEXoy1ExkpaWxtdff02fPn3iblgoNu8KxKxZs5g8eTLr1q3jhhtu4JlnnuGSSy4J23/evHk88MAD7Nu3z/degOeee45OnTqRnZ3Nzz//zOzZs+nSpQvLli2LeN65c+dy9913h21fsmQJyQ1g7vmqQOH07Lgug0QiaaJYi4rI0AsQAQf79kX1Tqxs6kEUoNLQmt323eQ78sm2ZNMhqQMAh12H+a3iN9KMafRM7VnrtmT8/jtWr3W3IieH0rqubiqpMwzCSWvPjwAcMXTGbsiq1fFa/P47tqIiSjt0oCLECt9mwwYUt5vC3r1x13I11OBy0fqHHwAoz8mhrB7GYNquXSQXFOBo2RLr4cMIo5HC/sfRyvOTb5/Dxh44ldq71eys3Ml+537aWdtxjO0YAH4q/YlKtZIeKT1IN0U+R9bPP2OqqOBw9+44W7TwbTc6HLTauBFhMHBgwIC422MpLqbltm2+/yvatKE0xEMjYQhBt+9eQ/Go/NHnbNxJabQr/Jq033ZSlNaDg8efGPWtSQcPkr59O84WLTjcvXvY69biYjK2bcOdkkLh8cfXTfvjpK37O0AlddteTCWV7Ow8Envr1g3dLCoqKpg6dSpHjhwhvRpXsbgtBT169KCyMjE5fFVVZcCAAdx3330A9OvXj82bN/PUU09FFAUvvPACF110UZAgAIIsC7169aJr164MGDCADRs20L9//7DjzJ49m1mzZvn+LykpITc3l1GjRlXbYXVB4be7GHtKh3o/b2PA5XKxbNkyRo4cGZbeVtK0kNcyRnbuRAmImxKnnQYZGSBUlPxPtG05o9l86Fe2F2+nc8vO9GylCYAD5Qdosa8FLawtOL3D6bVuirJuHRw4oJ0zLw969/a9Jq9nE8NdjnJA+0oXGSdAsv87pSbXUlm9GoqKECeeCDk5wa8lJWlWrlNPhazaiQ/KylC8LjIiNxcSsOBYLRs3ouzejejSBcUr0MUZ/VBK/ZYBkTkAbLV3Sd64fyO7S3bTPas7XTO7ApC+K51iRzEDcwbSNrVtxPf5+njQoKDK567ycjZt3Ej/Pn0wjBkTv/vW3r0ogfOc7GxEDcRFTKhODEXrQQg6jz0bkpJQtrpRhBmR0wcxcmz0927dipKVhejQAU44Ifz14mLtc9hsiBEj6qb98SAESr63tozTChV2Oo8dB61aRX1LfT1jdW+YWIhbFMyfP59//vOf3HXXXfTq1Svsg8Qzqc7JyeG4444L2tazZ0/efvvtsH2/+uortm7dyuuvv17tcfv374/ZbOa3336LKAqsVivWCD5qZrO5Qb78jEZjs//Sbai+lyQeeS1jwBTw6PV4tJSPHofff9ioPRdMRhNWs9XXnzaLDZPRhMFoSEwfB1YGVZTg1JNe5PVsIggFjN5raTTU/lq6XNrYSEsLP1ZKij/HfW3HhhDB90N9jDV93KekaKlI7XaoLPX3H0Ttw7hPZTRgMpqwWWy+vrdarJjcJgymKu5jRdHaaLMFt8NrmTEajZii3LPVYjJpfaBnIqqrPnfaQTGAwYgxOdn7eVK0Ohqqu+rz6uOvRYvI+6WkaK+rav2MmepQXdr4EQKcbu0zp6fE1La6fsbGc+wa1Sk4cuQIZ555ZtB2IQSKouCJI/hl8ODBbN26NWjbtm3byMvLC9tXT1Mai9vS5s2bcblc5ISsbjRWFMXffxKJ5CgnWqBfYNCh6q4y+5AMNJaEETJ+ancs4Q/gDA00hsSmgwzMHlPfgcZGo5Yhxm6H0sMQWCZBJCYbV2hK0sC/Y8o+FBpobDD401y6q5lYR0Lv49RUKCmp20BjpzdGw2D0fw6zd0G2uuxDVdUoAP8YVL01D0wNmkzTf/853SDQJnaWBm5TDYi7xRdddBEWi4UlS5bUOtD4xhtvZNCgQdx3331MmTKFdevW8eyzz/Lss88G7VdSUsKbb77JI488EnaMP/74g1deeYWxY8fSqlUrtmzZwk033US/fv0YPHhwjdtWn1hNBhxuFZs5AakOJBJJ4yaqKAiYhIjIokBPayhTkkrCCBQFtc0+5HT6BWOkzC+JTAcZeD/UV3rJUFFQVARlhyE1IKd8gqoahxYvC/y7RtmHABEoCuJF7+NAUVBXVY1d3mebwew/vk8UVCMoqxMFgdYOp7PhRYE+XuwewAg2I9D0Flri7sWff/6ZH374ge4RAj/iZeDAgbz77rvMnj2be+65h06dOvH4449z0UUXBe332muvIYTgwgsvDDuGxWJhxYoVPPHEE5SVlZGbm8u4ceOYM2cOxgg3U2PEZjZid3mkKJBImgP6JMhq1VZadVEQOAlR3Qi8KUkDvqx9loJEFS8LFAXN0VLgrgR3KdjaNHRLak8iRYE+Jq3WyMWXElmroDFYCgBKiyE7U5vAqq6GtRQI4RdlkUSBvq0mokDvYz07o15hvS4KmDm948gcICwtXsuT8ERf4VdV/xisKpDdatVSlzocdVcTwOmEQ4cgO7vqQmT6PWd3aZaRJGvCxlB9ErcoGDBgALt3706IKAAYP34848ePr3Kfv/3tb/ztb3+L+Fpubm5YNeOmhs1spNLlIaOhGyKRSOoefRKUlhYsCoImdVW7DyXMUhDoPtQcLQWHfwBHIbQeBNZaBsw2NHUhCiK5DkFi3YcChUB9iQJ9rAeKgooSIBPMaeAoalhLQeB9GUEUqLWxFOh9bLFoP05n3VU1dnqT0lgCRIHJ6vWZrkIU6MlsjMbIliodi0Xbty4tTNu2wfbtWgB8hyoSwugCwOEGxQg2S8LGUH0Styi47rrr+Pvf/84tt9xC7969wwIYTogUJS6pkiSzEbsrQV/yEomkcaN/KaenaytQEd2HPJHdh+qyeFlzFAXOYu23o0iKgkCqEwV1ZSlwu7UxWdWKbCLQLQUmk/YjBJR5M7SYvKKgIS0FgVa7CH3hsxTUxLqnP3/MZu366qKgLjIvur3jyBQgOAwmLYhbeKK3XxcF1aW7rYvq2qHobkx61e1o6Pecw6MFVzcXS8H5558PwGWXXebbpihKjQKNJRo2s5FKp+w3iaRZEGq+r4GlADRrQeD/NaI5uw957P4+dxU3aFMSQkNYChItCkATBnWxah1IoPuQ1aq5C1V6rR6mFO13glz0amQp0NtnMET09U+I+5DFol3fugw21qsWmwPGkcHsFwXR2l/d+NNJpMUqGnp/VddHulWg0qVZCpKszcNSsH379rpoR7MmyWzE7m5mX8gSSXMlVBS4XNokICSmoKpAY6gDUdDcLAWugJU/3WLQlAkcP7VdoazOn7uu3If0/+tbFOD2ppJUtEkrJM59qDaWgihxkQkRBbqlAOpuUu3WhVaAC5BiApMRXAkUBfGI04oK+PVXrTbMscdWv7/eX9XV59LvObtXFNisoDrhm29gwQI4/ni46abY29lAxC0KIqULldQOm9lAaWnjKNMtkUjqED2oDzRfZqNRmwA4HGGWAr3YfDRLgUf1YDLUMuNGaErSuspC0hhxl/v/9ti9dSKq8F9u7CTSUqBPgOrbfUj/PyWl9setisBJt6KA1XtfORVt0gqJcx+qjaUgiihISEyB2ey/jnVlKdCzD1lCRIHRCE5P9BiSqtLhBhLPOBQCdu6ELVu0/j1wIMGiwPv8dLgAA7y8FN65A373LqR36gQ33lj3rnG1JKbWrVmzJuYDlpeXs3nz5ho3qDlik5YCiaR5EPglHrhSZ7cHT0JUt2/CEGoNSFiwsRrh/c3JhchdFvy/60jDtCNRNIT7UKDIrSn6+3UxWtfBxpEy+1i953Yqms87JEQUCCEal6VACP97Qp8/dYEuCgItBQazZimoKqYgMPtVVcRqsaqogDVr4Kef/Od0ubT+qA59POrF+qLhdoLdCRjAaIavN2qCICUFLr0UXnyxSSy4xCQKLrnkEkaOHMkbb7xBWVlZxH22bNnCbbfdRpcuXdiwYUNCG3m0o8UUyEBjieSoR1/RMhq1FaPAL+UQ9w/dUqAQ/EWSsFoFkb6Qm6Mo0EVXU3chqk9REFgJu7bWAv39uqtSXYuCwDEeKgoc+C0FCXAfCrxHE2kpqLEoCOxbvVoy1KEoiBRT4LUUeGMKftr/E9/v+973vAtqT23dh4TQMgetWgWFhdp5jz/e/3p1/adXfNaPFUl8/PIL3HILHD8E9uwHjJCcAtecB0/Mgfx8eOEFOO20JiEKYrI9b9myhWeeeYa77rqLiy66iG7dutGuXTtsNhuHDx/m119/pby8nIkTJ7Js2TJ69epV1+0+qkiyaHUKJBLJUU6g6R6Cv5STgid1kWIKAv+vda2CQEuByaR9Qbrd1a/OHS3ooiApGyr2SVGg4wlw66hqUmaxaOPF4ai5u0/gpCslRVvRresCZpFEgUW3FIiEWgoC79EaWQqiFOSqtSjQC3/VeUyB91qaQ2MKDKB6EC4XO+w7AOjeqjupFm9J6VhFQXXuQz/8AHv3an9nZUHfvprb5q+/an3sdFZdETpUoFZW+oOz33hDixX49lv/6+9/DSefoYmCfv0gub0/dqyJEJMoMJvNXHvttVx77bVs2LCBr776ih07dlBZWUmfPn248cYbGTZsGJmZmXXd3qMSm8lApRQFEsnRT1WiQFQfaBz4f8IsBUaj9uN2Nx9LgerRCpcBJLXXRMHR5D5Um5S1+oTMaKx6wmSx1H4Sr79XUerPUhBYo0BHn3tWerQgUYhNWDkPQ/luaNHTH6AcgD7pNyiGoCKEDRZTEPr8CYwpqIt4Il/xstDsQ1q1X9Xl9PmrlDnL/KIg1piCqtyHKiv9gqB3b8jLC6iqbA4Wv9EIff3PP+E//9EEgZ6q1GiEceNgyjDIMcNBA6SkAq7mkX2of//+9O/fvy7a0mwxGQ2osfi2SSSSpk1gOkAIEQXVpySFBNYq0C0FuiuIw9F8MhDpVgKDBayttcmCx679GKuZiDRWQsZPjUnUKm0s6O81m/33RH25DwWuwlu8378OT7D7UHUT5dLfobIAzOmQ2jH8VBGCjKEBYwqiiYK6qGqsesCjxy9EyD4kBKqjErxasNxZ7m+j/vljjSnweOMTAvsrP1/7nZUFHTuGv89uj00UBBZYMxjg1Ve1Z2X37nDZZXDJJVq146Lv4btvQLFCUgpQ3DzqFEgkEomkhlRlKVADJh9ViIKEBxrrlgJoPpYCXRSYU8FgBFOqlqLUeQSSjgZRoNZ85bc+c8QHimT9nqgv9yF9zKtusOqTbAUCbwERIBIioXrb6qmIfKoIQcYQg6UgkjUjsFmJEgUGgzbx1iurJ1IUCBe4PdoYtASktlWMmigAVJdfFJQ5vfekPp7M5qif34fZrH0GVdXGTWAKXV0U5OREfh8EiwKPE0p+hZRcIAU+/BCeegr27IF587R9LBZ48kktLuHUU4PvL9Wt1bpQUiElDSkKJBKJpLFQtgNMyWBr09AtCSZwZRRCLAUBX8iqG0F4SlIImFCobigu1iqR1iTNXWCBJH0lrLlZCkxedwVLhiYKXMWQ1LahWlU7QieY1U1oo1GXOeJD0d9rsdS/pcAnhCu1SarVpglEu0Ob7AnhndRVJQpc/mNEOlU1loKowr6+LAUQLAoSWdVY1Vf8jcGfQ1F8lgPV6e+3cpfXUhDr+NPRV/0DRYHDAUVF2t/Z2eHviSQK7AWw4St4ezW8tQwOHvS/lp+viYvKSrjiisjtEB5t7BgNkJwKKs3DfUgikUgaNe4KKP5JCxjMGe3PLtMYqDKmIKCdMVgKlF274c/90KMHdO0af1sCLQXNXRSYWwC7NUtBUyWSKKjJV3x1hct0EuE+FHg/RJqo1QWRRAFAindCXFGhiSnhqj6uQBcF7iiioDpLQQ3dh2ocUxC6KAF1V9VYdYFH9VriQsahWROAqqMCPajA5z4UazpSHV0UBFqsCgq03xkZkcdxqFXq00/h9lvh+43+fbKz4dxzoU8faNdOE4lV9ZHq0lKSphohNQ1KaJKWgkb0bSmRSCQJQP+iVt2NL3g0mk+vx+MPyoOgQGMlxAVEFwWizFuRtyKy60K1BFoKmpv7kCuCpQA0S0FTJaIoqAGJzhFfFYGWgoYWBakttN8VFf5g4+pWevVJXxT3Ibf3/aFFBqvNIFafloK6ykCkOsGtemMIQkWBNraEy39Ou9uu9Ve8loJI4rQq1yHQ2uN0+vujvFwTBCYj/GUwvP8+7N4Ns2ZB+4AMQlUVMLPbQRWaCEryPleaoKVAigKJRHJ0EfhF6yhquHZEIvRLOTDDS8AXjhBuhFp1oLHq8H551nQi39QtBU5nzdorhL+asdn75W1K9wYbO7Rg46ZIokVBdZaCRLoPBQYa13VMQai/vr7Kn5qh/a6oiC0tqRD+SZ/HocVx6GzbBt99h8ej3e/R3IeEEJFdiOrbfQjqxlKgevx1CQKJ4D4EXmtBrJmHdELHjcsFhw5pf4eKgr174b77YPx4eOcdf3+MHw/33QrrXoAFd8BZZ2nPRP11XRRUVcCs3LvQYEvxZ6LSqxw3IWrkPrRixQpWrFjBgQMHUEOqYr7wwgsJaZhEIpHUiMAvWUchpHVuuLaEEpp9CLQvP5cL7JWQrH35qEJFAQTGqO5DwukCjDUXBU3ZUuB2w8qVWj+eeWZ87/V4Mz0pBjAma9sMRjClgatEq1eQFMEPubETuipZ15aCRLoPNYSlQBfC+ip/Wks4UKytGreJoYCZGtJOTyWYvPUafvsNVBWRpX2maO5DoLkQGYwh67PViQLdfUivzhxrTFFVloJEiwLhdR+q0lIQfM4yZxktauI+BH4xsX+/1i9paVrtC6cTPvhAKyC2dGlwfZbA8XfVVCjfqV1XPUhffz011R9nYrdHFsz6ok5Kql9UgiYslSpS+zYy4hYFd999N/fccw8DBgwgJycnzLQtkUgkDUrgZMhZVDf5t2tKtC/lkiPeL2VNFAghUISKUMJFgT6h0EzvycFfcvEQmpIUmo6loLRU60uXK/7r64snSA5+n6WFJgpcR5qmKNDHvcHsndjUUhTUR/ahSO5DekGzaJlnVFWrItuqFbStQVB4VPehlkCx133I+9mrtBSEiAK3VxQ4nb57SxQfhuRwS4Fet0AIgUd4MBMyaYzFUqCvQLvdsWcNirYoAYkXBR6nJgpMxqiWAuEMHjvlrvLauw8Fug7ddZeWQUi3HACcfjpMnKi5BQUK0KA6H04wWoP7y2bTJv7RRIHuxpmcoi04KAZtgUp1R6xh0ViJWxQ8/fTTLFq0iL/+9a910R6JRCKpJQGTZNWlTQLNjaSqZLRAP6GCw/sFpBgRuFCEv/BRIH5LgRMMybW3FDRF96HSUv/fqlp96sJAQoOMdcwZaMHGxbVsXAMQaB0zWLyuGzW4li6XXyzGKgpUNTiXezwE3g8mk3811uWKfk0PHdKKSG3fDiefDK1bx3fOaKIgvSWw3SsKvCv+VYmC0P7VLQ6Bk+viI5BsCLMUgGY9cAt35GDjakQBiuK3DtREFNRHTIGektRchaXAGSxEyp01EAWB7kOHD2uWAtBEwd692njJyYHp07Wfbt3gwAFYuzbYyhVUPNIrCvTnodmsCYHKSu2nZcuQz6r6253ifa4oJhDOJhdsHHdMgdPpZNCgQXXRFolEIqk9oSukjsKGaUckon0pC1XLXKEYwGhBIFCEJ0wQQIA/skvPkV7LmIJ43YdqWzQtEZSV+f+O9/NHEwUWb6BpkxQFAX1gtIZvixXdBcJiqd4lxWTy71NTF6LQletYahXobRQCvvsuWCDGQuCEWwh/DElKS22yrarg9O5TVR9Gch+CYFFQoiU6CLUUBG6LGGxcnSiAmgn56tyHEun/rrsGRYopsGjnFB5nkKWzzFkWvygwmeCnn+COO7QsQb/9prkNpafDjTdqrkO7dmmxBN26ec8fIf1tqKUAgkWrbh2IFGys1ygAnwuoz4UodJw0cuIWBZdffjlLliypi7ZIJBJJ7Qn9knU2kmBjIYJXnnRsNq3NDpeW9UQxIoTAgBrRPdNnKdBX9urTUlCyDfI/afgA7kBREK/7VGjmIR092Fh1Rk0x2WjRV60Vg782QU1EQW2DPOMl1HIWS1xB4KTb7dZWfONZ5Q4c9x7vRFgxgCnJP/Gze/uzKmtLqPtQBFEgSkvB44lqKYAoaUnrUxTo11CIxAZ565mFlEjuQ15RINwobg8pFs0yU1FxxH8/VxdTsHs33HsvnHYa3H47fPaZ1vfr1vkDjHv10oKIwywVEcaZGmIpCHzdZKrazUp4vIs6iiZIoHb3YQMSt73Pbrfz7LPPsnz5ck444QTM5mBfqUcffTRhjZNIJJK40R/CRquWFaSxWAoCv4Aiug85vaLApAUaR7EUGBStgqfQJxOJiCmI1VKgx2i4isGaWbPzJoLA1eGaWgrMIaIgMNjYdUSbJDYV9DHvFZVB2+KhJv7coTni4yHUUmCxaIG+sYiCTp00N5Dycm0iOGhQbG5kgdmH9Im80aZN6JKTNfchuwssVOM+FCGmILB9gCo8mMsqMbatI0uBwxG7KNDdsiD4+RNY1djhiD3Atzr0zEIma3jMj9ECRgPC6cLgUUm3plPuLMdTUY7LY8ZsS47+2ffv19yAPv3Ub9lISoIzzoDRo6Fz58gFywLRP7/b7Y9JimQpCByfVVkKhG4pMPr3a6KWgrhFwaZNm+jbty8AP//8c9BrMuhYIqk7Dpc7sZoNJFtkzcEq0f2rrVlQma+tBrortMDShiRw1SnQNcNmAzyaKDCYQDH5Ao0jug8ZjBhc/joG9Wop0L8sPXWcNrIqPJ7g2gzxfH7V7XcXCbUUgLeycRPMQNRQoqA2lgK32y9M43Ef0gVIeromDL76Sqvs/cMPcOKJ1QedB2Yf8okC70Qu2fuMsLsgnWosBd7XTEmaIIgQU6CqKqbS8sZhKQjcL2Qxt06qGuvuQ+YIY0nRXIqE6kDxeDAbzCSZk/A4j2B3ezDbQhYcDh3SAssBsrJg0yZtMj9kCFxyiZZpSB+zNptWtKwqAj+/y6WNv0AB6HEGW3ZNpgArUgRLgb1cq1FgDBAFesahJhZTEPfs4vPPP6+LdjR7mlgqW0kDsOyX/fRq14Lj2iWwFP3RiC8Li0ULHnUe1la4G4soCP1Cttm8fsxuwAgGEyqapUCJYilQXG6E/tCoz5gCXRSoDSgKysuD/4/HUqLXJzBaI2cEsWRA+a6oRcyK7cUkm5OxGGMM7KwvEi0K4k0HWRNRoN8PgeMvHvchq1Vz1Rg4EL79Vss68+uv0LNn1ecNnHC7vRP5SKIAYrMUmNK9osAeXPXWakUVKuayisYRU6D3qdEYHi9SF1WNdfchc4R7xWACk8HnPmQ0GEm1pFLqdGF3C9JsNk3ovfqqlkp0714tLsDkDVpetEgThF26aH3+0Uf+SVROTvXCUFG047jdAaIgxFLgCagxoGcfgsiWAt2d0Wbz920stS4aIbUqXrZnzx727t2bqLZIJJIq+CW/BIe7afknNgiBEyTdxaUxuBBFEwVWKyiq16fX47cUED3Q2OD24GkIS4FuIQj1p65PQgNL4/n80YKMdcx6sHF4JewSRwlf7fyKDfkbYj9ffRE45mszGYm1cJlObWoVBKYj1YkUABpKaNxDVhb06aP9/fvvUFBQ9XmDYgp0FxevGND9wSu854ilToE5zet+ooLq8Pdh27aaKCipG0uBqKkoCH3+QOIzEAkBbl0URLIUmMFgRFVdKB7tOZdiTsFQaUds2gT33KNN7mfO1ILJDx2CH3/0v3/kSE0QgNb3gWMoWhXjUEKtUqExBYGi1WAIthSELkRUeJ8ryQELT3pMQROrahy3KFBVlXvuuYcWLVqQl5dHhw4dyMjI4P/+7//CCplJYseggKpKc4EkOnaXit0l77Fq8aVnNIDFKwoaQ7BxpHSk4P1S836BOFUw6O5D0WMKFLcboX9OVa2ZqTHeOgVC9U8+G9J9KDDIGOK0FOiiICXy6+Z0LehUdfpXkb1UuLT/iyobwVgKpaEtBTWZTEa6H6qzFAjhP1dgG485BvLytL8PHKj6vJFEgW4p0Cd+Du99EIulwGDRYhJAGzMhosBYXomR8JXrWlsKAlOSxkK05w8kvlaBcGvpSAFM0S0FCI9mKVCMtPryOwZNv5M29z8Bn3yiteX44+HRRzVLwYAB0c8XGJOSGWOsU+BYEyLcUhAqogIzcoWOd10UJAWIgiZqKYjbfej2229nwYIFPPDAAwwePBghBN988w1z587Fbrfzr3/9qy7aedRjNRlxuFWSLHHk25Y0G4QQJJmN0lIQC4ETJF0UuMq0oGNjgoLoakJVK3U+UeC1FKDFFChRJhMGt8cfUwDx5+qH4IlHLO5DgS5DDek+FCoKamIpiFa3QjForzmPeION/V/yen97VA+VrkqSzI0oELkhA42hdu5Dgau81cUUOBz+wNBQ4ZKaGnzcaFQlCnxVjr0iu6o+1Cd7BrP2fncluMr9E8aWLXGbjCgOgam0AloEvz2qpSBQ5NeF+1Ck54/el4kSBapL62dFAUuEZ67BDAKUklIMHhWjwYi1XS5J+wvxJFkxnjtRSyc6YEBshQn1MZSdHXshw0CrVOh1jiQKFEW7LyoqNBeiQGtahdctMSVgsaGJWgriFgWLFy/m+eef5+yzz/Zt69OnD+3bt2fmzJlSFNQQm8WI3eWRokASkT2HK+ncJkVaCmLBF1Ng1LJcmNPAVapZC5JiNC3XBZEmQTo+UeD2Zh8SGKqzFBBgHaiqAmw0IlkKVFX7iZSjvrGIgtq4D+npSI1RLAWguRA5j3iDjf3jJXDyVuosPfpEQeAqfH0EGkdaua7OfSjQShA6+QvMKFMVgdmHnFFEgW61j8VSoJjAmAwUQYXX7cxgAIsFV1oSlBdjKisPe3tUS0HgeK6LQOP6sBSoLq2asRKhRsHGjfD8s7B4EWnHtUcZcBoGxYB1wClsufGvVHZsT/9J16G0axf7+bKztedCx46xvyfIUhBBFKgRRJQuCkL7SRcFyc3QUlBUVESPHj3Ctvfo0YOiokZoVm0i2EwGKl0eWla/q6QZsiW/hH65LfntQJyFepojvge8d2JrzdJEgaORiIKIK3XeR7HDAwYjQqgoRMk+pBgxON3B7po1cd3U3xNoKQBtUhJRFLgi/12fCOEPNE5N1awGsX52IaKnIw3EF2wcHFcQaJkpdZTSJqVNHA2vY3yr1gGiIN4ic05n9FX4aNTGfagqS0E0UVCVe1MsQcrgn3QbhH8VN0wUeCsrxxJToFsKwC8KvKLFkWLDCJhKIoiCaJYCvX2BVYsjEa8oqE/3IdVbzdjgDQw+fFgLGl6wADb4Y3LMOw5gcNgxKkaSLSmU9OmOocKO3SiIS3Ife6z2Ew9BoiCkD1UneCI8r6OlJdVFQVLTtxTEHVPQp08f/vOf/4Rt/89//kMfPdhHEjdJXkuBRBKJ/OJKOrZKxuGWloJq0Sdv+uTIF1fQwMHGMYkCd4D7UHRLgcHtQSVgLNQk2Ng3OTL4f6o6VqB1QHgCYjfqkYoKvyVDdxeJ9bN7KrU2Kwbvym4UzBna75DKxoEruqXORibO1QRYCgIn3LG6YCQ60DhWURDJkqFPkmMVBXjPb7BoYgr84thg1Ca1Va3yigBRoNe0KCvWfnsnj44UrZ3G0hCXN2KwFFRn+fO5OsV4nauyVAYGGiciFaJwafepYoR//1sL/r3mGk0QmM0weTLcP5P9/zwHg6plH1IUhWS39gwqM9TDRDrQVc1nafM+A1U3OB3B+0F08eSzFEQQBUe7pWDevHmMGzeO5cuXc+qpp6IoCqtXr2b37t18/PHHddHGZoHNbKRSigJJFVhNRhxyjFRPoCsFaJYC0PLPq26/Wbe+qWqlTncb9LkPVV28TAs0DnEfipfQyYfRqH2RR1t5DHUZUp3+AMv6QncdSk31tztWS0FgkHFVk15zmjfY2KX5iXsnfIGWgjJn+CSvQfGNeVPNJyPxxhOAf4Kp1xyoamU7lKrch6KJjKraGKv7kD7uhfccgUXqdHHsMWruL1UJKzUwpsArMitKgFSfWHKk2kgGjGUVYf1TZUyB3paqqGlMQWh1XwivalybAmY7d0K6UxNVilm7Vx0O6N0bLrsMLr5Yqznw5fOIH77G4HZpzzmXC5vRip0Kyo0eWte8BbERKEB9FiObd/FAgKMieD+IbClwOsHt7duUAAtkE3UfittSMGTIELZt28aECRMoLi6mqKiIiRMnsnXrVk4//fS6aGOzIMlsbLT+4j/vPcLuoorqd5TUKUaDgkxQFQM+S4H38Wa0aQGjQmg1CxqKWCwFTr9oiSYKIgYa10QUhE4+qptkhLoMNURcgR5knJYWe20FnerSkeooBv8+rhLf5qCYAkcjsxQkIqagJqIgcIJZ3Qp9KNW5D0Vasa6tpSBorHjHrzHEUcVo1MaAnqc+khuWECExBfpk0TtevJNHp82MajZiFIQFyCfMUpCIQGO9qjHUzBXMbofXXoNRo7T6AR8u1USVwQjnn6+lFd24EW64wV+EzGJFFQKj26UJJLsdm8mKajZS7q6s8nQJIVKgsWLSLEcQuyiorNTebzFrMWw6TdR9qEZLZu3atZMBxQnGZjZwpLJxlsPec7gCj5pEbmYDF39qphypdJFm0x5Msmh4DIRaCkBzIXJXaPUKbHW+BhWZKrMP6anugi0FkarE65aChIuC6ibZYZaCBnhe6RMrffUR4nCfiFEUgJaa1FWi/SS1BYItBW7VnfAMREKIiNc7tjcH1ilIgPtQrCiKNp5drvhXmKtyHwJtsht6r1QVCK3vq0/mI/VlRFEQ8r1mMoHL6E+pKbxFBQMJXP01mP0TwIpKbRJos/nGizs1RRP3xcVB1YKrjSmoK1Hg7W+Xx4XZGNC/Nalq/MMPWnGxV17R4gZ0fvwJRh4HmDXXoc6dw99rtgICxePW+qfSTpIpCdViqR9LXKRAY4MJEFqmukiiIJL7UEWFthCVZA3+zmmiloKYRMGmTZvo1asXBoOBTZs2VbnvCSeckJCGNTds5sYbU1Bqd5OR3Djb1hz4Jb9EVjGOh0iiwJoFFXsatl5BldmHvG11qyAUhBAYqgo0dkVISRovoZOPai0FEdyH6ptA9yG9nfG6D1UVZKxj9t5v7gBLQcgku8xZljBR4PQ4+Xz757RJaUO/nH7xH6ChLAWgjWeXK35LQST3Ib26scejHS9UFFQlXEKtFpHus8A4GlUvXBbBUgAgvPeecAMh59NXfxWvVUFBW2F2ODW3JJvNN9l3pSWjeBQ4Ehy4Xq2lQDjgyC+Q2jl4BTr089bAUrCzeCeb9m/ixHYn0i7Nm+UnnqrGpaVwxhnBBcVyc+HSS2H6dMgogW9WeDPARRE3ZguqUDG4HFpfOCqwmqx4FDN2V3hgdtXt+QNKf4PWg/z3bnVECjRWjFrRKPBnpopkKdALmBkMXquBB2yWYNdUxfu+hkrKUENiEgV9+/aloKCANm3a0LdvXxRFCfZn9aIoCp6aVtds5jTmmIJSu7vRtq058PuBMqYMyG3oZjQdolkKQHMf0oNN65uqLAUmBYwGrV1ONyoxxhToE6hExRQEbg+lHtyHPN6gw6gEug+VeCfsMbsPeScasVoKIKr7EGjBxq1TEmN1KrYX4/Q4OVhxsGYHaGhRUF4ef7BxNJFsNmvX1OkMTvEIVVsKAgWF2121KDAatXgRCHcfCsxABJHdP3xBxgFTKFOSJgqMDk0UePvfk56KodgQLgqqsxQ4CqDUpbk/pnYKb0MtREGxXav6XGwvDhYFENl9SFVh82YtLgC0+89q1fr43HNhxgwYPtz/DCn8TnO7UkyRYxgATLr7kDvAfciGajRT4arQBEOsz+nyHdrzyVEUvyhwOkNEnp70oRKwhse8GAxafzgcmkio1lKgNtx3Tg2ISRRs376d1q1b+/6WJJ7GHFNQ5nDLANcGxO1RsZiaxgOlURAaUwDa6rDBok1kncVgjbHqZaIIDOCNJApUN1jN2peKw+2taKxiiFC8zKAYMLi0Y6lWC4aKynqKKdCztZi09ia4qvGfh/9k84HNnHLMKZEn23a71jZF0YoExRNorLrB4530RqtmHIhe3Mxdrk1uDEafZcZkMOFW3QmNK6h0aRNUZ037tCFFQXUFxyIhRHSRbLFobQm1PESrZhyIyeS3MkQisEZBaOGywGNAQAGzCPdDYDpSHWMyOFxgC7YUiPR0KEYTsQFuTdVaChTv72jiuxaiwGXX/nYHCp5IrjE7dsCiRbBwIezfD/v2+SsGP/+85hqUlRV+Lr1OgaEKUWDR3IcMbq/7kN2OxWhBMSUhhKDCVUGqJQYB767wVx+Px1UnWkyBfv84I4iCSAXMKr1ZzWwWv6CAYIEgPE1GFMTUyry8PJ+v486dO2nfvj15eXlBP+3bt2fnzp112tijmcZsKTAalEbbNokkjEiWAvBnIWoIF6LAL+5IokB4wGoJEgUABsItskYUFG/Euap/sdWnKNAn1SKxZvEdxTsAKKqMcn1016HkZP+qMMT22XXXIaM1eCIXDaNNE5EBtQ30yVu6VVuJTGRaUrtbm4gJIYInarESJAr0FUoRX9rYeAuX6VRXcCwSbrc/kDiSpSDS8aqqZhz63mhj2GcpMPhFYjRR4HMfijC+fEHGAWNJNWkTYTXYUkBKil+sBAQbV2spMHj7J9p4CJxsxyIMAkSBPsYiioLiYliyBEaM0IKG774bdu3SJsA//eTfv1evyIIAtGeF25uSNKr7kE2ziHpcmkDyihFbWgYQR4YvR4B1LZ57JzAGxROw4KEHGkdyHwJ/P+nBxhUV2hgJtRQohuAUp02EuKXLsGHDIhYpO3LkCMOGDUtIo5ojRkNkl6zGgNVkoNLZOK0YRztOt4rJ2DRWGBoNUUVBgAtRfROYDjBSAKRwe0WBAZwuVK8YMEYQBbqVQCgKqiXgiy0eVNU/KYvVfUj/4tTdbxLoPlTuLKfcqbn3RF0tD3QdAr+YicVSEGvmoUBCXIh0S0GGLQNIbAaiyoBsKzWyFkSyFARurw7dHQLqx1Kg72s0hqferEoUQNV1FKqrc+BbhfeOfUXxTwJ1fPeB9/9IE7pIlgJvjn0MHjAafRNuo9HkD9wNcCGq3lLgHdfRVr+NRn8/xFLFWb/fo4kCq1WLERg7Fi66CFas0LYPH64FEu/bB0OGVH0eHeHyuw9FFQVWhKpZCoyK0Xd9bakZAL7nQbU4DgWfN1YCRZVek0Ax+uM3nF7RGCoKAuMKINhSEJruWh8fCV5AqUvinm1Ey5BQWFhISkoMZllJk8NsNOCuSSCjpNb8cbCMzq3jmMg0dwJXRkPNtQbv6mJDrNpUVaMAvJYCM6CZ0YU324mBCPedy6XFdZkMqHpQXCyiwFWi+dxC8EQ61kBj/YtNtxQkMIBuf/l+39/VigK9aFk8loJ4Mg/phIgCfUU33ZqOoii4Vbdvhb+26O5DkAhRoPjHfqyiQJ9wGwyRffGroiaWgiqD7qPUKoglO1J1aUl9E27v60ZbuMAIjSmINCn3VZAOuJ9d3j7Xdbp3vBgVI2RkaBsDRUG1FY11UVDFNYz1HtD7w2thc+nVegsL4ddftb9tNsjL01a+O3SAOXNg+3ZYvhymTvVPhmNBdWmWgirch1Szdp2NbrfmJum9vkkpGUCMlgIhwF5DS4GeOQvA4R1bekpSVQV3hOJlEJyWVA+wjxRToB8v3nY1MDGnJJ04cSKgBRNPnz4da8CN6fF42LRpE4MGDUp8CyUNjkyD2XD8kl/C8B5tG7oZTYfAL9CwB3QNfa1ri+qqOshY9aZQ1N2H7HZUm3bTGSK5f7i0Yj8uswnVqAdDxiDaD67RJvbZI8ATcFPHkpJUDcgb7xMFibMU7C/ziwJXNLERmHkI4rMU6P7jpjjSKkexFJgMJlLMKZQ5yyh1lGIz1b6AW6ClwDdhiwffJNV7DRWjNlFR3WHZNCNSk3SkOrWxFPjeW6y59aV0ir7aH0vMQ6zuQ7q/viHCsXyxKlWIgsAaBTou7/5m7T7RLQBGgxFatNBeKy72n8Z7rdTQe9zn4qSfq4oJpcmkfdbqLAWBzx+PhxarvqXbmx+Ts2ItDD4NVq7U+rVlS3j0Ua36cLRYgOoQwhvD49E+RJTjeEz6s9Cj1XHwXt/ktEw4coDyWDIQuUqCFyfiTf/pS6dr1xJMKUZNFLg8/n4PbX9g7EWlt9CZSfFabkItBU0vLWnMV72Fd1ALIUhLSyMpQDVaLBZOOeUUrrjiisS3UCJpxpRUumiRHIMPtEQjSBSEWAoaQhSU74LDG8Geo/0faWVUb4/VrLXZbseTpLU9mqXAoBgQJlPslgLV45/E2w+CwVtAKNB1oypLgf5exeifSCVIFLhVN4WVhb7/Y3YfisdSEC2otCpCLQUBk7xUS6omChKUgSjQ4lAjS4EaYCnw/XbFPtZrGmQMibEUFP+kCQMMtRMFsVoK8NYeiFSR22cp8P4fq/uQfkozoHqCLQW6KAgINvZZCiK5Dwnhd3GqakIZa7Cx0wkFBfDVV3D55fTfvdv/2pEj2uRW79djj9XaUFNRoC8g6IHGUdyHVKMZFEVLqGB3+MR9SnoWHInRfUiPJ1AMfhEcDz5R6hUFekyB2631u9kcvioaaCkIzDwE4aLgaLYULFy4EICOHTty8803J8xVaO/evdx666188sknVFZW0q1bNxYsWMCJJ54IwPTp01m8eHHQe04++WS+/fZb3/8Oh4Obb76ZV199lcrKSoYPH878+fM55phjEtJGiUTSRPBlHorwRdQQosDldReo8E56IwYZe78wbEnaF5DdjurNOhQppkAXBarJ6F/wr1YUBEw0HYf88RWBX9jVWQpA87fVfW4T5D50sPygzy1VCBF5Uuxy+V1cauI+5Asqjadab6p2PVQneOy+FV2DYiDNmkZBWUFC4gqcHmeQC0nt3Ie8X+nxjvVEiIKaWAp8gfLe85f9DqZjIx8vlpiH6iwFvu3eVeyqREFV2YdEJFHgTTtptYBqD7YUpKZ606C6tfStqak+S4EQIjj9ptutXTdjDC5gsYqCO++Ep5/2/etskcre8UMomDKWU8+e6d9PL2DmcNTMagTeeALV78oWzVKgKAijQTOI6ILfbCbFqol+u9uOW3VjCvXTD0R3HbK2AvuB+H33fYLWCSjhloJIz+vAmAJdFNi8xwlbiGp6loK4YwrmzJmTMEFw+PBhBg8ejNls5pNPPmHLli088sgjZOj+d17+8pe/kJ+f7/v5+OOPg16/4YYbePfdd3nttdf4+uuvKSsrY/z48bJmgqRJ01gDzxs10YKMIcCUW4/PBf1cjiiZLMD/hRHwZaOiWwoijAGn0xtTYPJ5OFTrQhP4Zek4FFzESScmS4HZH5iZIEuBHk/QJqUNEMV9Rncdstn87YzLfagGosBg9LtKuUqDVn7TLNrEJRGVV0PjEqK6T1VF6LiPVxTUNMgYEuM+pI8ldyV4vAK6Nu5D1VkKDHpq0gRaCux2LbuV1QzuimBLgaKEBRsH5uAPiivweLTrpo/veC0FQsB332nxAjrdu2ttOPlk3EteZtmXi/j5zis53LNj8PH0uhD791Nj9MxDuitbaCC5vhtGhFHRrKG6KLDZMBvNWLwLD1VaC1SPP5NcktcSW1NLQWhMgdutTfYjJfkIdB8qLwe8mYcMEZJIHM3uQ4G89dZbvPHGG+zatQtnyINgw4YNMR/nwQcfJDc312eFAM0SEYrVaiU7OzviMY4cOcKCBQt46aWXGDFiBAAvv/wyubm5LF++nNGjR8fcHomkMVFQYie7RWIqpjYbItUo0GkIS4HeHkclkBo9HSl4RYEdPB5Ub82SqO5DGFDNxtjdhwJXnz12cHiLcgVaCqoUBfokyOJPwyiEtj2WFJ9REEJwoPwAALnpuewv249bdYcXLgp1HQpse7VWkgA3mkg+5FVhTteClF1HfJYCo8FImnc1MxFpSQODjKEGloLACaU+xuMVwHp6xYZwH1JdwQkC7LtBmKKLgkQEGlOFKAjNPhQxJanXZ/7/HoNb7tRSc9rt2v1htYCnMthSAJoL0eHDmiho314rQui1jnmEB7MvQtm7Sq1PSKuLKQDtnj10SMsStGCBljr0oYfg5pu110eOhOeeg379cPXuifrncu1Uqic4eUynTlobf/9dCzqON+gcvDUKPP7CZVGCEj1olgKDB+/kGt/4S7WkUlRZRLmrnBa2FpHP4yzyTtxtYMnQttUkpgC8loIkr6XApIkaAGOEtgcWMDt8OKBGQSTr9FHsPqTz73//m9tvv51p06bx3nvvcemll/LHH3+wfv16rrnmmriO9f777zN69GgmT57MF198Qfv27Zk5c2ZYbMKqVato06YNGRkZDBkyhH/961+0aaOtKn3//fe4XC5GjRrl279du3b06tWL1atXRxQFDocDR0DVvhJvZUyXy4Ur3lLtCcTj8TTo+SPh8mjV+DyqqJO26cdsbJ+7MbBp92G6tUkJ6pvGOEZ0GsW1dNlRPG5QBCK0HR5Ve83jCX+tjlBcDvC4oaIM3DZt3T/03M5KrV0Gg/YF6nLhrnTgUT2obmd4f1ZUaPnsFQWH6sbtdoPDUfVncpZr5/AiSveiuN2gqv73qaq2zXusoOvpfb8QBq0fVQHCg3BUxBe8G0KxvZhyRzkmg4lMayYejweBoNxeHhzAe/iwVsXZavX3n8ejtdfprPqzu0q9/WtGeFTN1zlmkrTPXVmEw+XArbrxuD0km5PxeDy4PW5KK2sXbFxSWYI74NpUOCriu4dUp+/aCrcKigvFI8DjRrjsYHJVe28q5eXgdiOMxvgm9/r7vcGuwm6PnoIykIoK7XoqCji8Y1MxamJerYBKO5jNQdc11jYqbreWwSvSPna7d9zbwZOMUCMcSwhtH5dHu3ddAcfyxgMorkpAYFj1DSLrBdQbbkApKwNhBJMBYT+C3aXg9rhRParW78nJ2nELC33HE6pWl8LusGMUWr8pDoc3842qnV8E39tB19LtxrBuHcr8+SgrV6J4F2mF1Yp66BBq4L2dmYlQFCocFUHjrdJRidnonRynulDUfVCZhdiyBY4/vrorGY6zAsXpRBGa4Il2b9pdbjwGsKgq7uLioGtrMVhwe9wcLj9Ma1uUmJ3yfO3etGaAW2hjSI1+vmgobjdUloMnBeHRiuopLoGiehCKO+LxFJNJcx0qKgK3EywmUAnfV9XaJVyVEcdsfX1nxnP8uEXB/PnzefbZZ7nwwgtZvHgx//jHPzj22GO56667ItYvqIo///yTp556ilmzZnHbbbexbt06rr/+eqxWK5dccgkAY8aMYfLkyeTl5bF9+3buvPNOzjzzTL7//nusVisFBQVYLBZatmwZdOy2bdtSUFAQ8bz3338/d999d9j2zz77jOTQsur1yOYChY8Lf26w80ei3AW/H1GocFOnbVu2bFmdHbup8mW+QmW24KeAxYrGOEZCachraRFHaOnZiltJptAYvAKrCDdtPJolc79R1EuFyZaerVjEEZL+KKTySBYlhw5R+dtvQftY1cNkqL/hUlJRtngwVVbyZ+4hPCmH2bs7FbO1JGj/Fn/+yaG9W9lZnEzhPid5u4pwtmjB4QMHorYjST1AurrD979aYsbwuwt3cjKFFVo1UHNpKZm//ILHZuNQqX8FfNmyZaSqe0lR91JpaEOJoYDWnh8xCCeFxgrcSs1T5u6172WvYy+Z5kzUrSo/lvyIS7hw/OogKSAouOW2bViKiyk5eJDKXbsAMNrttNq0CWE0cqCKL73gMRGflcgqisnwbMOtbGFtmR0VFddWF1aDlZ9Kf8Ku2in9pZQWpiirmTGwx76HfY59GBUjHuHhN9Nv5Kfkx/x+g3DQ2rMRMLDfW/k8w/MbVnGYEsMhKg1tfPtGuzezfvoJU2Ulh8vKcOpuLnHQ9vvvQQgOut3+gnpV0HLrVixHjnCksBBPKxuZnl/wKFYqlVakV2wn9ecCjpg6ckD3RBCCtt99V+05rIcPk/Hbb7hSUigKdJ/xkr59O0kHD2LNKcZxKINDRgceJdgaazlyhJZbt2JIcqOWm3Aq6ZSXbiNvxQpyP/+cr++7j/SU7RiFA2XsCDzl5Rz86CPafvcdNrUQh7GAyt8P8rPLTL4jn73Wvey27cZUXk7W5s2oZjMHvXOlH0p+wCVc2H+1k2zU5h6Zv/xCckkBlAhce1MBhf2m8HG7fOlSRlx5JcmH/Hn6i489ll0jRrDnjDNwpaaC19U6bccOkg8coHzfPvL/3Mwv5b/43qOPZ4BWnp+wFh/C+lsp5T+049C2bXjijC1IVveTceRXkrYWcyTZxaEo92aZq4jM/H2klno4ULwSxeOhfO9eyvbtI9+Rz277bnaYd/B78u8R35/l2YxJlHPEUIRD2RXwbI+9enBKfj6pu3eTlHGIyuJWFBrtuJVk2u/eSOrevRwqSaawMNyFqeWvv2LxLiabqUC1G3Hs2hf2nZOi7iVV3UulYRclhh1R21HX35kV3md8LMQtCnbt2uVLPZqUlESp98vjr3/9K6eccgr/+c9/Yj6WqqoMGDCA++67D4B+/fqxefNmnnrqKZ8oOP/883379+rViwEDBpCXl8dHH33kS5MaiWj1FABmz57NrFmzfP+XlJSQm5vLqFGjSK/BAzFRFK3dxdiTOzTY+SOxq6iC1ofK2XO4sk7a5nK5WLZsGSNHjsQcLYd7M+XQt7sYd0pwnzfGMaLTKK6lvQClKA0sLRGtBge/JlSUfO3LQmSPrpXbS6woh1qCsxAMvwNdEP37Q7t2wTtV7EEpbgHW1tAGOHiQpLQdVKQcJK/dQFq3Gxp8zPXr2bbFSWrHlvTMOYH22/IhMxNRVUro0t9QSluBKQ3cpXCoDFqkaO8b7O2nI0dQUlLAZkOMGBF8PSt+RSnfiUjtAuk9UA6mgqsEkXWy1u4a8tWur8hx5NCnbR9y03NJ2pFEuaucU9ufSlayv1qqYrNpFpJTT/VXUbXbUbymfDF2bPSTVOxCKU4DaxtE1knxNdBTibJ/BaBwsEybbIzsNBKryUqbfW0oKC/g+NbH0ymjU/wf3ssPBT+wt3QvmbZMiuxFZFgzOK3DabEfwF2GcsCsWUKyvZbxwz+gVO5FpB8HqcdWe28q3hVaMXSoP5A7DhSTSbPYnHGG33e+qv3T06G4GDFwILQQKEUp2j2beRLKnk9R7OsRaZ0Qf/mLZkGz21G8q/Ri7NjoebILC1FatIDUVO2zhPLDDyh7dkHrg9AhG5H9l/CCU4cPo6SlgdEO9j8wLPkU5eOvUbyT21H79yPO7w+qCzF2qBaQrrfPVQQntQRrK9LVVHYe2UnXzK50z+qu7ZOU5P8MgG27jQp3BYOPGUzLJG1hU0lLgwN/QFcTtMoAQOSMhkoHyuef4xw1imXLljHiL3/BduKJiG++QT3rLNQbbySlb196Aj0jfe69exHHHceBtqmk7PPHhQ7pMMTnDqfkK5q7VMut4GyN6NgR+vWr9noGUboNZYcFTEWQ00cbExHYX5pPUcmXpBW7ye14AihGxPHHQ6dO5Jfl833+99HvBdWJUqBZ/ETbkWAw1+zZvmsXyqZNYPwD+nRGtDkTTMkoq0tQkpLo3Ptk6Dc0/H05OSh792p/Ow/DiWmQ0gbRKuQZXPYnSskWRFJ7aBnej/X1nal7w8RC3KIgOzubwsJC8vLyyMvL49tvv6VPnz5s37497sDInJwcjjvuuKBtPXv25O23367yPXl5efzmXW3Lzs7G6XRy+PDhIGvBgQMHotZNsFqtQXUWdMxmc4NOTI1GY6ObGFe6oWWKjfwSZ522raH7vjFiNBjC+qQxjpFQGvRauoxgNIHJEtl/32T25pU2gLEe2mhUtPa43WA1aoF8oe0yGbR9zFZINcPhwxg8AqPBiMUUPgYQApPJjMFqxWA2YdL9dqvqc4PQzpGSAxUuEEcAh+Yfq78vKcnvoxxwLLPZjNmA9n5rivaaOVlz8zCIqs9bBXa3nXJ3OSajifYt2mM2mUm2JuNQHQiD8H9uj0cLTDWZtDzq+nYh/O2twncZxeNte5SYjqowm8GchKo6sClu3MZkbFYbJoOJliktOWQ/hF2112q8u3FjMprISs2ixFWCqqjxHU94x4/R6v98Zis4TZpfeui1DD22ngLTZNIEQU0+S3KyP+A7lverqna+5GQwlHnHfzJYkyGrOxg2gOOA/3gVFdr+NlvVfu7Jydp+oopxqahgsYLZBtYIMVseDyxdCp98DLv3+LefdBJcfTXG88+HohWav7glSXuOlJdr57VkaM8YxYXBaMBkNGGz2LQ+NxiCg+SNRqwWK07hxBB4nyuKlgLGYtGCdTf+DvddB6+9ASUliB9/9HaLGcNdd0F+PsYuXTD26RO9X/Trm5wMBjAZ/VM/xaho51ZdYFAAE3TvCOu2wr6WWpByizgsYYoHhALmJO16RbkOBrMJxWLGZBSY9OdLWhqYzaQnpWMymvAonsj3QsVB75hJA5tXxJqs3qxNaNcgFpKTNXc3j/cZYbFp11MxgcGI0WKM3P60NP+1VMzez2kN39eSpB3XQJX3RV1/Z8Zz7Ljt52eeeSYffPABADNmzODGG29k5MiRnH/++UyYMCGuYw0ePJitW7cGbdu2bRt5eXlR31NYWMju3bvJydGizU888UTMZnOQ+SU/P5+ff/5ZFlNLAKV2N2m2xj0JPRopc7hJtkbW7DIrURVUlX0ocHt9BRvrAZQuV/QUd3oQmmLyB3o6tfZFzD7kcmFUDAizCY/+BI81+5DRqqXvU1Vwl8SRktTrxqFnHtJX4mqRgUgPMM6wZWA1aYs0etaRoAw8ehCi2RwcZBrY9qo+f00yDwViTkNVVUwezQSvB0DrGYhqm5ZUDzROt2or7HFnH4o05n2pEGMY53oArzHKBCgW4k1LGhho7PHG9xm91zats9YOdzmU7gtuY3WuLLEEGqsu76Q8ynhwOuGFFzRBkGSFi8bA99/D2rUwfbqWXUh/ButB93r7UryTZ08lHq/fvl6PQCtupQS1L2JVY48HjhyGVz6FUdfDWTfBs89rNQ46dkTZt8+/b3a21odxFC9zhwS9+v7Xa3kYzJCVA9ktoHwHbNlS9bFD8VRo96PBWmV8iSpUVJNZ8+jw1WrRrq+ehjS0rT70+gSBVsqaZPoxm7VntDskpa+e69kY5bs2sLqzPj8KrVEA/udkvKlSG5C4LQXPPvssqvcBfNVVV5GZmcnXX3/NWWedxVVXXRXXsW688UYGDRrEfffdx5QpU1i3bh3PPvsszz77LABlZWXMnTuX8847j5ycHHbs2MFtt91Gq1atfAKkRYsWzJgxg5tuuomsrCwyMzO5+eab6d27ty8bkaTmlNpd5GU1XJxFc+XX/BJ6Zoeb4a0mAw63is0cS5nSZkhMosBdj6LAex63B/BUnZLU4BcFwqF9iUTMPuRNSaqaapB9yGD2igKhFeWKlJJUiPDjBaYkhYC0pDX/stOrGLdN9Vfs1kVBUAYePb4hMPMQBLfd44k+AalJ4bJAzOmolQXhoiABGYiEEL6UpC2s2oTS5XFV6f4afpBIosAvfj2qh3V717HHvif8vVC7GgU61aUCDUSIYFFQESI4jVZIbw+FO6BoK7TqFHsbfSlOVe/ENGTd0+MB4dTGikFzSeP117VJv+76nJMDEyZAi1S4YaRmnWrXP6D9uog3+NNu6u1LTgfFDkKgqtp48WUf0tvndGqf32bzvRZUwOynn+CW2/z3oNUCE8+Fy6+EoUMRHo8vViCu4mXe87vVYB95vyjQxWESZPaDLodg/0bY8wsc6Axt2hAT7grteWcMsDxGwKN6UI0mFAz+Mey9vrooCBJLgTi8cRTWVv5tiglwxJfpRxcFroBrCv7MU9FEQeA4tOmFy5ph9iG3282//vUvLrvsMnJzcwGYMmUKU6ZMqdHJBw4cyLvvvsvs2bO555576NSpE48//jgXXXQRoLlK/PTTT7z44osUFxeTk5PDsGHDeP3110kL+IJ47LHHMJlMTJkyxVe8bNGiRRhjyYIgqZIyh5s0Ww0rG0pqzLb9ZUzs3z5su9VklKKgSqpISQoNYCnwaJMTj7faZlUVjRVjgKVA+xIxiAiiwOXy1ymIVRT4ii1ZNB9ojwquUq+7gJfA56XHE+yOo4sCvXBZLWsVqELlUIX2xd42xS8KzN6VtSBRoKcjDfV1VxR/asA6tRSkI4TA5KkImuClmFNQFAWXx4XD7fBZO+LB6XH6Up3qIkPfHvPxqhQFbg6UH+BAxQEKnJETbyREFMRjKQgUDmYzqF5LgSHg3kjPg6KdUH4AHEWxtzFwEuqOcL95PNqY3XUEnl0Kr38CxcXaa9dcAz17asf46181IZ1iDF951oVw4Mqw3r6kJG0y7K7Qai4QYCnQP68uCryvJe/ch+m3ShjvnUcdeywk2aBjNlw4Es45A7qM9hccDLzXYxUFAZYClzNYuIVZCoxJWiretn3gmALYvQt+/hGGjYzuoqcjhHYcT/WWAo/woJrMGAItBd7rq/eZKtTw9MTucq1/FQWs/rijGlsK8GiiQK8nAeCOw1KQZAZEeGxKTdvUwMQ12zOZTDz00ENMmzYtYQ0YP34848ePj/haUlISn376abXHsNlsPPnkkzz55JMJa5dEo9zhJsUiRUF943R7Ik78rSYDDpfH+yCShKFGmCAFom+PtgKVaISqpTYE7Ysh0spZoPuQ13yuWwoUQtrp0USGASOqyYhbdy+qzn0ocKXfnKadSwgt6FhHUfz+te4QV6fAOgVQa/ehwv9n77zj7KrL/P8+9dbpJZNJLySkAiEQIICAFEUWG7IuWFasuKvo6uradn+WVdd1LetacNe1Iq6rKyJFRaT3JARCep9JMplebzv198f3nHPP7TMhgSjzvF55ZWbuued+72nf5/P9fJ7Pkx7EciwiaiSQzUBIPhRuYOYzBeUKYH1QUA0UHQdQ4LgOqpMpSE4UWSGuxUkZKcaN8WMCBT5LEFWjyJKMpmiYtonpmER4HqBAzoNfX6bluE556eHzaVzmx1QamIUbl/kdoyEvHwKhE4+0ihXn8d2Qi01ujH4HXcsSiXAYFBgG3Hsv/PJnsC3kALZgAbz73TDDA6e+NbCkiM9XFfG88I9ppcZl/vg8UOBYKUArZAr8+390FO64g+Xf/hp1jz+NOX8uXHmN+GxZhn/5e7hilZAqQeVFjMmCAv91TcPKVpAPWT4o8I5xchEsXQ5HHoAjz8ChZeAtBlcMOyueeY7jLUBUzh1K5EN+3QUUdDG2HCt4LgB5lkBvKkzEj2VV3mcKHFfUQQTfw/tfrvBcDYOCiAqY5eVDf4JMwZRrCi699FLuv//+EzCU6ZAAxzm59OIuIMuTpLGn47hFpasgqgmmYDoqxElXU2DnJ2SF8ittZeRDkiGKP0uYAm/FT1Zk3KnIh/xExp9cFV/7XCR98Vf2CjqkOvlJTS5mCo5NPuQnqjMSMwpkMmXlQ+UalxWPt9L3d51Q0nmM8iG1Dsd1UBwTteh8BJ2N0/15nfkUIuMlYn6fg7Lfv1YEjdnCCVIpKIAKGu3jyRRMQj6USYmOviXdjMNMgaaJLrWGBdk+0edjsmOslCj/3//BZz8rAIEswZWXChnOnj3w0Y9Cc3PhPiQ5f12FV3qrgQKfKQChrSeU4Lou7NoF3/wmrF4Nb30rdY8/jStJmIvmi0ZYPrivjxV206200ux/16qg2C4oAq9YU+CE5EMgnlUdZ8OC2UJquPmB2te4951x9fwiQ6VNHRtb1ZDwQEHo3EqSFADwEglRtkw9AYT0+1NlCrxjE35bIB+qMNf6DcxANC6D6vKhP1emAETfgI997GM899xznHnmmSQSiYLXr7766uM2uJdaRDSFrGUTPwlX5n3AMg0QTnzYjiso1TIhagpeoIT2TzImKx96oR7SIaYgdFvvHtxNX6qPs2edjRYGMh5T4DgukuUgFYMXL+mSVLHKakshpsCzbCw/jKLEy/fVt0YLt/OsJQuSjEAuIeUnuecpH+pNldYTAEETpSApdpx8oXElpsDfrlz4LIEkH7sFraxie6unETdX8FJST5LIHsE9sldoi5MLp7Rrv8g4polErKx8qlYEGvdS+dBEbjRgI6BCEfPxrCmowRTsG97H7j0PM6vvMJ2zl9MM+ULjMCjQdbFibXvXd8YDBZPxzNc8N6C77hJJ+mteI/7+2tfC/PmweiF88BpY91qIdZTfh18U7Hj3U/g+DEB8BabAb+ZnZUBvyMuHPv5x+OIX8+9ZuJCj117JlivOYN6q81nS0pIHVa4tgIskeZ3Da4CCakyBGbp/VTVg4RRZwXbsUqZADYFnNQGrLoK9P4LBPZBOQaKKZa3lgwKtcHxlQjAFKpIkl4ACEGDKsI1CEOO6eaaguKlZsCo/xYUKtaiOwHXB8q67SkwBCOvdkRFIRIBUDfmQaAL7QvTGeb4x5ezzxhtvBOArX/lKyWuSJGHXWrGajooR0xSypkP8GDqLn+iIeCvUMX1ay36iYyxj0hgvn8BENJmsOc0UVIyaTMEUXFme91i8RD1gCkSC0T3azY6BHQAMZgbpCMuHZBkiEVwkJMOqyBRIukiO7PAcY9uV5UnFbilqozfGCfG6P3mVSzLC0iMfdDwP+dCEMUHKSCFLMq3x1oLXSlbK056TiaIUUvZ+1GIK7KLVz2MMRxGLX5pT2JyoXrLJHtiGenAM3IVw2hRBgZeIxbxErKx8qubgKrsPDacHgPzC3YvNFAykB5BNi7SRZuvILqSuh1ll9tMQqRMadD8CFsG73jIpQK09xr4+uPVWuO028fOiRXD11cF9xb//OwxvhtnthXKl4vDvgwAUlGEKytUURKMgxcCyabz/KVKnrEGZ752XK6+Er30NzjkH3v52uO46Bge2kx3el18N969jyck7JFmZ2kxBNVAQlmuRvwaiapSUkSplCuSiY1y/SFh3TqRgtL86KPCZArzzV6OmwFU0ZCRxDU8GFJijnnuUClpj4Q6PVb+v+s8Q73cr9DysxBSAsKjNZsHaBRmqMwUgnrPKSZjcFcWUQYFTS7s6HcccUU0hY56coMof2zQoOPExmjFpqFAzIAqNT85r5KSIWqBAfgHlQ4EdqfdZCoxmR3m299lgE9M2S8ccieAgIecsJIoYgAAUiMnFDgvNKj2bg6Q+5JYiaSIpkiTIDULMW7Evl2QHLEPomnwe8qGhjOjm2hxrLtAOQxlL0rDzUDkWpCZTUKSTPsawPFCg2/lVdxybhsHtTOzrw3Al6DtS4d2VI1xTAM9TPlSGKRjO9IOeBwVlwcYLyBSM58aRLZumWBO9EZWR9AA7R7eT1JPMaFpHi79K7e/P8lbKMxOiB0A5psB14aGH4Nvfhl/+Mg9MGhoEIMhkIJHIs2mOKaQ51YBiAAq8350yoMC/H2w7/5ldXfD9m+FHP2Fp3xD6dVeiXPJm8dr558N990F/PyxeDLJc6j4UgAJ/pToKZGrXFPi9JorvEdeFkX0CHGviOqgICsoxBSD2Wd/sgYI+6KzSqG8KTIHt2DiaXpUpCI8XAEM8O9BbSr/rser3Vb+42DvmplcfIEueRMIqzwJEIuJff2hRpzj82hTX9sDKnyEomI4TF4IpODkTvpN5bH9uMZIxaaxAF0U1mbHMn47n8Qse7mTlQy8EKPA+w0sYLMniqSNPBW4z4CW/btGkEo1iA7phCV2ta+df80GBJq4PB7d2sW1xkTCIbbV68d7cQB4UlFt5dMu8PwwKqsmWyoSf8PqSmXCUJMWV7Ej9mDRT8PxAgV2OKRjbRmz7XlxXxnYsrOwYqm1MaTWwWD50PEGB6ZhMZEdBz4OOqvKhyUhzKsUkmALLsUibaZKmxYLGBcybP489DTapsU2Mm2n2HnqCC+ddSEO0IQ8KbAlyprjOJKn8GD/yEfjyl/O/r1gBl14K73oXhJuj2naeNVMVMraDbU+Q1MusfAf2vN5zxC13P3hjHBwUBcx/+ANs3RpsZjbGMZob8oXGkiTqFvr7K/cp8JN72UtQ1ZjomFtLPgSl5gAA2V4YeBZSvdAipFL+NeBfE5ZjefexX5tS5l6pawa6YXSg/Dj88JkCaXLyIVtVvUeHXXJuA1vS8LPavy98iVY4jlW/78uH/Fo9yxKLJ1pIIlkOFPhRcyFK9c7rn0ZdwTGBggceeIAvf/nLbN++HUmSWLZsGX//93/PBRdccLzH95KKqCaTMU7OxDt2ErMYf24xkjaY35Io+1pEFXUn01EhTqZCYz/5t2xcXA6M7ydjtpDQEzRGGzk8driQKfCSBzcSAWQkw/aK8CyCR7W3EivrEcAWE6ai1AAFZQo5HccDBWa+ERDUYArCoKDImWgKibCf8GplNP7+31zXxXIs1FqgYLI1Bc+bKfA0/042r2ve+RTKcAorNhc1000uk0I1x0BprbG3fBTLh0pqKiYTFUDBaG4UCYf6SD0K4rUS+ZBp5s/1CbYk9Zu8RR3R6ZdYguUt7RjmaWwfOgjAaG5UgAJ/fzZgeMA54jFbmzZBSwv4TU6vvhq+9S24/np4z3tEInrwYGlC6tuRShKoMR7ufgTTMbls4WXBcQ8iuA+838sxBZLXxOy882DvXvE3WYYrLsd5zWo2L1fobVnLwmJLUsiDgmKmwLLEc8Ov3fMT9EoJpe9W5DjlQYGdFn+3MiXyIf+asxwr1LhMz7OJ4WjwrumxwfLj8KOAKbAmYUkaEX0KysiH/GNTWFNQpsjbj0DSeIw1BT5T4F/DEW88jgFU6dVUvKhTHMfSP+FFjClXPfzkJz/h0ksvJR6P8/73v5+//du/JRaL8fKXv5yf/vSnJ2KML5kQzjInZ8J3MgOWP7eoKh/SZHLTNQWV46QCBT5TYDOQHmTMHkORFc7qPIu4JiYZ0zELLUkBJyISIslwhDNPgaa2UD7kuE7t1fJy8h/HAbVevNcczxd7VqspCL9fko65rsCXsOhlgIQiK0EyYNjGcWAKnmfjMn83cgRXksWEaQxDz5Owqwui7Uhzl2LJEXKZlOgSPckINy4rZgqm1NW4EijIjiK5DjOSM4JV15L9+nakmhYcy8Njh/nDvj8wkh2Z/BjCTcMqnAu/yVtS8laEdR1sA13WqYsJv/mUEepeDaJoJmdAJi1W488+G848s5AZOP986OmBm2+GlQvzGvFi1sLvZqzIGEhkrSy2Y5M205REIMvxfi9gCvJuYS5gX36p6Cz87ncLMHLX3ThXXoirKSiuWdq8LDS28kyBt1ItyXkgXu15Vc4xLPjOWSFfdMzguITlQ8HvtcBzg1fUOzZUeRyuk9+P62vyq7sPOYqa71MwGflQOecnP465pqBIPuQfRz0MCqpEcD1UYQqOZVwvUkyZKfjnf/5nvvSlL/HBD34w+NtNN93EV77yFT772c9y3XXXHdcBvpQiqimMpE9OacjJDFj+3GIsa1FfpaZgmimoEicTKPAEyaMTgwxnhpCUTk7vOJ26SB1aSpxfwRRUAAWm7Xl4lwMFESAzSVBQQT6kaOBZapIbgPis8glGOaYAxMTsmFMGBf4qeDlQAIItsB0bw8wS952HikCB67o8dugxmgb3sIymE84U2K6DpcSFnGtoIzy3QyQ+s1ajzY6T2fsE46lhmowxJiukytm5oHNxxCt6PTb3odJr3kVmJDuChEN7op2JrHDvKWEKytQTHJ04SsbM0J/qpzHaOLkxqGp+xdowyhaF+0xBwteb63rQuCyi14EBKbMIFOw/Aj+5H+54BNKZ/PvC16ckCSeYiQMwsgVy3ncpBwpcA2SZbMiTPmNlaKChcFv/PvC3q2BJunNwJ0evXMmai8+nfvEKmD1bbOKdCxm7sPGWDzYqMQW2Lc6n4rllTSahVFWxv0qgwP+7bAnJjgdAfCBqOmZt8NzodTOeGKFsp2jI70NS8rKrWvIhTUOSp1BTUK7I249jrinw3YeKmALdOxa1nm9BoX81puAYxvUixZSZgn379vEXf/EXJX+/+uqr2b9//3EZ1Es1YvrJq9uP6QoZY3qF+oUIx3FRKli/iuZl0+ehYgR6/ZOjpiBjZTgy0g1Ae30bnXWdQF4mYtpGqA7C6+IZYgpk5LJMgey7Dzl2bQlNuZV+H0DEvBVA3+avnO95OVAR/n2KdL2/Wl0i2fAiWC0fH807DxUlDCkzxWB6kP7skGjIVREQHR9Q4LgOphwTIO3QYRgchfpT4Iw1zG5bBEqcXCZFz/COSe/TryeIKJGgV8MxuQ+VAQXDxhi2Y6NKMk2RxjxTULzfMqDAPz9lnYqqRdEqeHGM5QSLkvSLLTUtuDZjkUYgxBToOnzpS3DTJ+HnfxCAYNYsYenZ3S2KiovDb8TnevalxUmyZQlNuiKTDdXn++ehIIqZAqfM/SBpomjehYHMYMExtL1zoRZ3nAkKqMXYyjMFHiiQ1MkllNUciHymAEC2Cs6pzxTYjl0bPMebBdPg2jA2XH4bXzqkxvNjqVZo7Nq4soa7sBPmtpcAyZJjA+XtYP2YQk1Bf6o/AKm+K1xwnI6VKagFCv5EmIIpg4I5c+Zw7733lvz93nvvZU6tbnfTUTWiqnxS6fZtxw0mq5PZGemlFBFVxrCnQUHFOJmYAtehL9WPbTjEtBidjTMDAOCvCFshD3l/VTDPFPj7qQwKjpkp8AFEzNMK5zytcJkEQypufBaM99h6FVSrKYB8YmyNeslHGechX3bjKrKX1JT57q5b3ZLUzoExMqkx264tmALTgZ0HRWOtFWugro54vIHOxsXguhzu3caEn2zUiGLpEBy/QuPelDifjdFGJJz89VacmJQDBfYxgoIadQW+fCguhZgCT7YW1euJ9vST8o+dpkF7uzjv56yED79NFPJ+9KPi7+XCl8DhJfllmQITFIVMqElouI9DENXkQyGmwLRN5JzBaHa04Bg6tUBBNabAB/pTYQr89xZHmCmQzOCcKrKSvybCNQWVmAJZgTqPTRntK7+NX2SsxPNjqSEfciUFFnTCktmlX6sqU3DsNQUZM8Pjhx7nycNPeh9UJB8qZgqq3YuuW7KoUzquPy1QMGX50Ic+9CHe//73s3nzZs477zwkSeLhhx/mBz/4AV//+tdPxBhfMnGyMQUTOYtkRFzo0+5DL1xUM3KRJOlYGqe+dKKoaLck/Af3C0HlujY5KweOTJ0eR9I8uY0SCTEFWfEUlqTAMckHBbKFN+mE7rswKDC8ZML3W59qoTFApFF08rTTYnKrVmhcPBGfgJoCyDMIBaCgKAJQIEkCGJVjSRwj74zke+DbOTh6D3T9Lxz6NSx+F5zxpZpjdlwHQ60jumM3uM0w41ThgQ+gKLQ1ziU3WMeYafDM4Uc5b8HlBZ2ay0VxkTEcP1DQlx4ghgAFuHY+wbInAQqeL1NQBhQYtiHuBSDmKPnt0xn44wZitz7Epb9/gCdu/keyiy4Vq9ivfS1c/jJoTkHGFl751cKTIiFZYJsVagpyoMgFoMA/DwURuA9Vlw8ZtkHcMDFtk3HJxL9SbW+9tSYoKMcUYOXlQ8+XKXByIaYgDwpUWS1Iul0rI2RvxXak4ahrhuEh0auAZaWv+0yBEss/P2rIh1xJQcIqm8ifqJoC/9mRNtPCzMAHBb58yL9uIjHAyl9X5SL8WZUciv7E5EPH1Lyso6ODf/u3f+PnP/85AMuWLeN//ud/ePWrX33cB/hSiqiqkLVOnlXg8axJXUTcfNPuQy9cTCf9zyNqyoem2Lyskn52kmMxHQMsF1WPgKYGoCBYDbdzgFRAPbu6hitJwpUjZxZOPGH3IWOqTEEZ+ZAeB0cVE5aVqlFofHzkQ7VqCvy/O2OjgFYWFPiSD1eRsa0KTEHQU0CCI3fmgYAZ6uLc/8ikxmw7NlLaxc7OhKaFcMaawutC15nRMJ8Be4KhVA97hvZwSsspVfdZbEcKeUDka7+VSuA2HEUdjTNmhrHcGFFZoT5SD66VB6HF56qMHenzZgrKyId86VBciaK4WdEJ9qtfhf/8FnT1BHUYzU9vJ319WoCC9nZI6TD2nNCo17JMDRfL+647Ba/7hcYaqdD1UlY+VM19KCQXMWyDZE5czwPORAko0IpBQdD/QADZikxBAAomwWxWAgWO5d3X/niN4NyGQYHYNCX8qcrZkfrR0ALsgbEKtqSBHWnoPNVyH5IUZFmmXMffkmMD1UFBOPmuYpMc3l/KSNFQbEnqX796HBirvugRAHKJijbYx+qK9CLFMVmSvva1r+W1r33t8R7LSz5kWRL62JMkxrMWdVFxiQgt+zQoOBliCpbwL704nvKhjRuFp/gll+QTnimOxbANdMtBjUU9UFAonRHyoVjBeB1cHF0FQxHOK1VqChw3BFpq1hSUYQoUBdSkkNFYExWYAlM08TkO8iHbsYM+DbVqCpyxUVBbqzIFyLKY5Mt9dzsjkoMNN0K6O//32EyYcw3MvRbazpvcuF0bbTyNpEShrV00xioYtI6m1zMnUcewk2HX4C5mJGeIpLxCFDcuA5GsyZIsmAnbICZPwjUpYMfEs7ovJeQdSb1BXGeuXSgVKRjEC8MU+PrtprQL//qv8Nhj+WS1IQFvvp7N11xCd0ecmJGiOdYs9iep4LgIH/sa96C/oqsqYKfKMwW2AXKEdKhXSFWmwGcUfCDg2MHCg42M49jIOfE5ffYYflsvHxQoFF2X4ZVz06xcUyB7NQVTkQ+VgALveJh5UOCfU03WUGTFY55dbGtCjKUaU1AvHKIqOhAFdqTeeZKkqqDAcR1cFGR/Aaeo428JU+A6oWu9CigACnq7FA8zdF2nzBQNgXyoCBREpgIKqqTSf2I1BcfcvGzDhg0FfQrOPPPM4zmu6TgJQoACcfPJslS85jEd03HyxTGAgv5UP7sGd7GyfaXwSAcxMfT0iKRyfFz4ok8xHMfENA10F1Q1KpKVoiJb1zWxXR0lvGrnOkJClFZKmQIfFERCRYLHYknqbyvLeVBgToDqJeDFTIGilHcfCu9/EuGzBLIkl3Qz9kNXdHAc7IkxaKwOClxZJNAi4fOkQT2/gzO/LpgCSYKWs8T5nvP6PBCotKpXIRzXQcnmRPfVcjIWXQclTousMkOHva7D0z1Pc8G8CwrdZ0JRTj4E4trIWTlMxyTGJECBU3jN96Z6AWiINYu/h+RDtQqNLccKFqaOG1Ngmnk70rpmYdtpWcJe9LoL4cp1MO9SlOFuGDmQdyDSdZEUS15XY73KOXNscmaKI+NH6FCbiZVjCoxcUMSbCjm4Za1s4AIVRHFHY/954fvkSxImLrJpIXnHa8AeD9idoNBYKpo1JUmAHVPIm5RIOfeh4yQf8pky/6tKpsdM5hNuVVaxrAy2bQpAUJUp8Go5aoECnymoAgjAe3ZJEnJgu2oS7vhbAgrCx6BcEi4r+Wsl3NuleJhhUGCk8qRyuHkZTM59KLCTrvJd/9xrCg4dOsRf/dVf8cgjj9DY2AjAyMgI5513Hrfeeut0sfGfUYxnTWY2PD/XjumYjhc0anU0lktBwaGxQwxlhtjUs4mXzX+ZSOL6+/M6rkrJdo0wrCySZSMhoyoRDxSICUaVVSRJQnIdbNcOVgzBk45EdDHRGKE+BnZ+Rfy4FRr7oAA8pqCxYF+Sa4Mv7iipKZi6fKiW8xB4q5iZHJZliISnjL1lwBRINvLgRhj/Kex6JC8NmvdG0D0gd+qHoXXdlIFAOGzHRsnkkKVkeVCgacJ1xUyxuH4W3RmFsdwYuwZ3cWrrqWX3WU4+BAIU5azc5OsKQkDYcR0G0kLe0RRvBRxw7MqFxn6fAg8UhEHDlHolQClTsHGjcAm66y5S9/4QZKiToqLTcEuLaDR2+C5vZVwnoYuGjQW9CiQJUECyq2crTo6+VB/9qX7QbRZY2UCiEzBpXj8CUwb/m/kr5Tk7V8DY5O8p7xlQnJh60iE5Z4hrORLBkWAgPcCM5Iw8U+CWYbDCoCAqrqVS9yFN3G/hRYxKkphaoMCNCNcCTcUyhYwrDApcx8B2Ha+wuUpy64OC7IQAWHpIJuRYoeQ5UjiuCuEzhrIaEd+v6HorZQr855hamS6XVLGdY0GFr1LMFASFxi7i+PvXbzQhAFXVQmPfDWkSTMGfSE3BlJ+SN9xwA6Zpsn37doaGhhgaGmL79u24rsvb3/72EzHG6XiRYjxrUR+tPHlPx4mJaXnQMUbYum4KTIE/SUwYE+wZ2iP+2Bdy2DhGUJA1U0iWg6pGxKqTJOUnNjxg4NpYdiHV7bgOjq4hSZ58yJ94zPwqpRKakB3fvraSA0+5LqBhdxAtBAqKEgyZ0EpYccJwDPKhWs5DIJJiNZURiVIyWXYbdWw7p+//Khfs/BDJ3V8VyaU5CrFOWPJ+iLTnHVWibc8LEIA4J3Iuh1KVKYiBZaO7NqvbRCHmnqE9gZ4+HH4iCoXyITiGYuMQKBhMD2I7NlE1SkKvD14vyxQYRqjgXFxPYSBQYAU5mdB1ATJ++UvBAqxdC9/7HvT0EPvtHwCoIwKrV8PKlZ4Ux2esdBKaBwqKexUoKuhqdfDp5MhZOVxJIovhScecQtbCA2Gm4ktiI0F/iJK6grD7kGuLrt8jW2HAq0HxiowXdP+ahNFHvZcw96dFd3BbqlBoHN63ZRXUjASMl2Pl3YeKJTHlohoocBxAFWYEqoJjCsbGB+WqrCI7Bo7j1G7wF0kK8Oi6pXUFfj2BrOfZlSpMgeu6ASiQKjxHSpmCKvUEfvivuZWvlRKmQPHAlqQU9nuIxPP7qiTrrsVMgwAMYSe0kzymzBQ89NBDPProoyxdujT429KlS/nGN77B+vXrj+vgpuPFjfGcRTJ6zAqz6TiGyJo2EfX5JTAv3Qityk0BFIQLz3YP7mZWspPEcQAFOSuDZNqospb3vA4lerqi4+Bgu1YpKIjoHigw82P1ExxNK5Ck2JK3ulMWFFj5CS2g6d383xQFCIGCWGGCIWECWgW3j6nLh2o5D4FIWNRURkzevnTIzonOy9FWwaQYI8wZuk+8pDWizL4cLn1foTSo/zHvOz5/ttN2BVMgJaTKoEBWwXPWmRlN0JHs4OjEUbpHu1nRvqJgc1+yIktykJgG338qDcyKgLAvHWpPtIPkJdeuHSSBtmvnpTLhImNvNf2YmYIjR+Bzn4Nbb4VUKKm/5hpy77yB7plpJEkqtCMN3IJkkNVSpsCXI0makA5Vu85swaxYcoyM48lv7Jy4Z/wCZUMkrjkcIsYgbTao1giZTD/ZzrX5fW3+GBx8ADZ2gTsGwxPgJ/dKHNb/LLAjbRnZimEsJ9rYAVhBPYfluRYplLknQw5EBfexYyPbNuAXGquTk8RUqykwLO8+dT1QIHo4FMiHHAPb1WqDAkmCukbIHoXhPmidlX+tXI+CGkXGfshKVIC4ouutpN6imh1pMMYKq/KO5zwlqcH+VDuNPNIFagaMLhi2YJ8F3c+AlYOc6CkjQNAO2PcDsQ87m/9njkK2D+a8DtovFNsPbYSHrinczslB23q47KHKYz9JYsoZ39y5czHLuAtYlsWsWbPKvGM6/lTDdSs30ZqOExMjaZOG2DEUtU5HkRNEJXq5DCjwJglNERP91j2PcbYvq4BjBwVmGsmyhXSoTCMcTdbIuTaWYxeswvtMAZJaWGhcARS4/netZMsJ4nv77wlvJ8sgJ8TxciwCYYX3nWXyK7klcQzyoVrOQ/5raiqDbWVh4kl49N/g8O0w76/g7O+Qs3IMJ5ayu+MNjDQtZnbzPGYuXA3t5xZ9d78Y+TiAAtNAy5lIyQqgwE/0bC8BNceY0zCHoxNHOTJ+hOVtyws06349QVSNlliXTqmBmVsICvykdEZyBmS7vG2sgvoNy/HciMo5DxUxBSVa+0qRywlWwHVh5ky46SZ429ugvZ3RVB8ceoKknkT2i15Djct8S924Fg/Gl7NyRPxjKqkQUSqDAjsLqQPIqf3UOw66NYY9mkKJzc8nqE+8Cx6/Aw4P0TSU4/L+/NstOULXkpDKYWQLDD0GaQq1FHoz6E1e4b1gCgbi51CfTdLQOANJOkLKSAmrS6lCobH/3SEABUGxr2ujBe5DSj75lRQP3B8DU2B5oEDTQZJwcmOAXgAKZNfAduXJgeeGFug/CuMVmAI1DrkiO1LXFedOUoPnnJMbpC69H8U1keU6ATSyvaA3iHHPuBhVbQIgPr4Tnrlf9FJJdwMy7P3PfMK9/KPQfoH4rKGnYPtXhOLRMfPb+GzrOT/ESor615bx5zh77+fE3w8COcAAPLKYocXQtFg8F1MHYHsV6+LW0LPHdcX2xTFF6+YXK6YMCr70pS/xvve9j29+85uceeaZSJLEhg0buOmmm/jyl798IsY4HdPxkonRjElDbFqydUwxGSo3AAVuYIHnr1qd2noq2/q3MXFoH/0pjbaE1+33mGsKMki2g6ZECqloLzRFw3RLmQLXdbEjmkjis6FCY1/r6iUViqxgOza2n7iUG2e5xmPh7WTZcwmJC0tSN5vfxnWRA81sOVDgU/VeIjMJ+8yaNQV2jsjR37Ns7w9p6t8OGOAb/Qw+Ca4r6gkkmR2z3kykf5iZQ6nqlqTVHFUmGxmRxMuqXt6JKvhbHhS0N85DlVWyVpbh7LBw1PF3Z+ZBQcmupiIfCq55cR79/dZH6oV7lbeNLMkBkDQdsxAUlGlc5kcAIMLR1QXf/a6Q2H33u+JvCxbAxz8uEsFzzoFXvCLY3JdP1el1kPHtHvONy/xrS5ZkYmoUIzdMZmQbkfGDMLgJxveCMwE7D8GZX82P46FrRFG5JVa/w5Ubbp8CLa/IA+lMD6R6BJkog4uMrTdhaY1MSHGyYYnXqR+EWdeBuh/kOKxrhkgTzL4aUgdh+FmQRU3BUHQliYSLGk/SHGtmMD1IX6pPJNlUqSmAgl4Flmvlm/C5IfkQeM8Gq7ImvRooMD1pomdM4FgTaLZKPH0AhtI0jG8lNv4cSk4FJw2jW6HzFQL8APQ9BEf/kE+uj+yBw4fA+ANMfBNO+yI0nCqYgt4/wqHbod+AvRNQZ8EhK38fXnIvdFwifj74My7a/oHy3wfgwl+jdlwBQDy9Dw58tfK286/L/+w6kO2pvK2TDeRDlhIno7UQkVXkhCtklIlGaPSAVP1cTw5lQbQDTv07AZzkiPhfiQr2MjdQCAoalsHlTwiwq0TF+4c25k0cTvKYMij467/+a9LpNOvWrUP1LkbLslBVlRtuuIEbbrgh2HZoqEKV+nRMx3SUjZG0QWN8GhQcU0wFFPjbS3IwSdTpdSxpWcLRDVvoHsvSGG9Gk5TnJx+ybDRZzzfCsQuZAgnHqykoYgoiOpKslq8p8JIKWZKxsavXFJRrPBYuMvZXgdWkAAWEdK+2na8pqCQfCqQNJhUr+0JRs6bg9+egDW6mrR9wwW2aiXTKtTD3DWLilaSCDrSuLGE7Tul3d0JJ1HFgCqS0SLaleKL8Bn6i5/gOPGPIkkxHsoNDY4c4Mn6kABSU62Yc7EqZgnyoqMg4sXM/6kQKbeHlJayY4p2fQFNdxY7UD9u10dDE8f3d7+A734E778wX8H7ykzB3rtj4k5+Ee+4pSU5TqR7i2SO0qxk4cBh69oEagYkxsUK84uPBtmft+AcaRjeJX4aAA94LBqBFYM1X8tesYwSAwJVUTDlGTmvAUOqoa5DQrYn8WFb/PxhaDX1D7Fq8mJ2zF7Oq4zQc12Fr31ZmhhPujpdDuwM77vQKViVAEglnuJuxJboZq3IMolHa4m0MpgfpT/UTU3XvmEuikZoPrLL9kDsEE/uhPwP1R2gf24xtpZC6h8CcR9CnoO9+UccwvlPcm4d+DRIoZpqzsgcgtw60DsEqdP8KnrsPhlTBkNlZ8Z7hHOxx4MLvAHW41gSL+h5g7jP/C5RtQQav2AjNHijofxie+0z+tVFgBLGqXodIlPFAgZWG1D5IIQhHBwrUUyFNvaPWkVUbcWWdmJYAXNDqBRhRoqA3B/UW49E5OEveh2znwByDSAvULcon6C3r8p/RvBZO+xcBVJLeNkpESKNk8b91dDMAg3Ur+ePK73KuOk6z3g/uEjjlFGjcI+7nOa8QoIi0sDFe82+lx2pst5AWJebm/6YmoPXs/O9WBib2Pe+6phcqpgwKvva1r52AYUzHdEwHCKZgbkuNzp3TUT5qOQ/5r0l+sxwb0AL5kCIrLEzOIZN2yDgW+9RxltqNz4spUCwHTfXlQxOF8iFFQ3JtbLeweZnjOti6Fip8895TBAoUScHErAEKyjgPhe1Ig8EkBX3vZPKJvmWFQEEFuY/srfg6xqTkB/5KdERCrCoevh3WfivPZHRcDsNH6W2Yx0D9cua99mski7z+w77yrizjkHdlyn9HXzpUw1FlspER8ggpUQEU+EyBqwOOWEF0XTrrOjk0doie8R5WtK0IpDiV7EghJB+ajCwrBAos2yR2uA/JdVEn0iWgQJWKio0nwxT0HIFbfg433wwHDuRfeNm58OZXgvU47L5bFOKmemHbs4ArmAJv0XD+5vdy2vhz4n3bgQyii/YwAqyu/H/5/WqCFnLkCHKyBZJRAepm1sOchYX+82u+Cmf8G0TbGO3fwK5DDzAem4upJDgj8wwzcrn8PdN8JsQ2QERmXEuCJBNTY0GxaxhoAnnALClgmZ5zmFWgazdsA9m0aOr5DTz4LRbWm8wyRpFdE9W1kO2MYNoW/SUonhPW0x+GR34ERxGSlf0QmLnvBdp+RVBTcOR3sPe7xWccGegETHMU6BDH2RiF8QMwUbSx/7Vi4hy7VhpTjmFrTShqnBwytp1DVaLo8Q6xmh2uLWg+E055bz4BT5sw8TRoUTj7akguFtvZaWg9BzqvhB4T2g/DnHlwxhni/ClRkSx7Ycy5hgfsNiJqhMvbF8LodkjMgabTg20Ur+5pNLEYc9F7iaT2w/huSC6AxpUlxwWASKtYqa9fCvVLym7ig2JJkpBwyNpZIa8ypcJ6GKhtpjDZQmOgXIO2kzGmDAre+ta3nohxTMd0TAcwMi0fOvaYzAPafz3UCMeXD6myijw4xIKG+Tyb2scRxpmZk6kvTrb9It0aWuuclaEulUPTdIgkgIlC+ZCsIbmOqCkoYgpcXfNWF03IeklwGaYARKGxeGOVmoKwfCjcuMyPAltSRayw2jZSTVCgCVBgG1DrsrWzxHv/wBk9d9D5zEawhBMKs18Hs64UP6/6R5jxfo6mv89ETC1cwfXCT+AkScJVZOGcUnyOfOeh41BkDEBKgAI5Ud4NKQAFtiz0zK4Ndpq2RBuaopVIiI6/fEjBHB9Fcl3RlCqXg1ghKAjLh4ASO1IGnyLW8yDzRvYQsUbQrTGidx2Crz0rXm9shL/+a2El2vV26P9HeLxoPAMAqti3quK6LhklSUKOIkdnIOs6xOph6VJIRMS9FKp3GFr9JR4Z2seMhoWcGV8EDz8stOSLZJh9SqH1Y92i4EfDK6B1JA1LiWNIXgKfTeW3N8V1k/bu27gWD+79sl2NVVXcc65vWWkVMgV2Gsmy0MwRSG9DkaHsco49AXigQK2DaB1oilgoqG9gwrIwUUjGWtFMz+lGlj2dvCt6iLg2JOZBtA0bjee272a53pwf58zLoH0tXPYycc1LCgw8AVsOwezFMP8ckPdiuxZd7a+i9ax/pT3Rzv6BHYzuu5WORBvzlr6tIHEHYObl4p8flgG7PifG2PlXEPckMVZaJOQdl8BEFyQj0DBfjLncIfEXYqRQ/5Oi612SJK8Q2sJyLCLlXNSKYxI9AfxzntSTZNIp4QIWiQp2I+3VRkwaFOQtaitG+LWiBm0nYzwva5lMJlNSdFxfX7mD43RMx3RUj4xhE9OOw8rmSzGmAgrI+/8XTFB9fSQjSVrblnMo08v+kf2sslbk6w0dW9D6cgTaz688FNfFnhhFG0yhztJh9hxI9xbKhwKmoDAxCqz6IjHIpYNV6gAU6HkNNoDjg4JqTEFYPlSOKQiDAlUVoMCy8jUFlSaygsZDFWJ0O2z9PBz6Naf4QAAgNgvmXgPJhaFxJGDiMJqsYSWiZRNjHxTEtTg5OVW+o7HPFBwnUCBlJikfsixQG4QriTmGrAoXou7Rbg6PHQ5AQTX50LGCAnt8DHCQJa9eIK7A0AYYeATZlblS+iNt+39DU5cD1hhszcHyr+dBwUPvY+5tTzC3CTjL2/8KYDlwoQL/djhfZD24EDK9wu5ViYuEMLkAMkPgJoSPfSJB2kyzYeFHkRWdV865BJR7BJi++EoYfRZS3aI41YtYcjb2aA8pKx1yH1IholYt1DS85miqliArKWQU79rOjeY3MrPYrk3OY45iWiy493N2rrSoWvGYOicECkK+9IZtoJgWuZlXEr3gY1DfxM7hg/Skh3FkjYb0XubVz6I13JX6rP+Ajo/C5s3Q3g7r1vH0wYcYyY5w9qyzmfHwBrGdqsCC62DBm2DgScHiNZ0Gibk4psmBPXexXG/0tlUhPgvkOfkO3VZKMAfpo9DQBO0zINsj+m042XyhMa63MGFNTman6pBIwsQ4jPQJUGDn8tehEsvbOXt9rMpF0KNACtVOlHmGKLKC5VjePT4JUDCJngA+U9AQaSCb6hH3oublrVMGBZORrHqMk+vVi/BnBgpSqRQf/ehH+fnPf87g4GDJ6/YxUu3TMR3TIWJSbh/TURpBUV8NejYkqwj7ZSuyEkxoC5au4+jW35Ezc4ylhmn035sb8Oz30pWbCSGSjFiXsDjRZnSKzrxpvIlBUMiipsDGst0S+RCAG4sJ7W42Kz6rWD7kJTfVC439bsYVGpf54a8QWmmQfPvUUE1BJRvAcpOmnRWrm7EO8btrwYGfiOOit3K48Vyal76bxtmvLE+lj4+L4stErCooqNPryMqD+QLNcBxnUBAUGlfom1BYfBwHBCggNpPOuk66R7vpmehhZftKJEmqKh8qsCS1s0IaEpuR32D/jwXQyvULN5bUQbAmSB4e5bQul52n/IO4ZiQNun4BY9tQgNMRwwpiVBHX1Y4doh7gJxshC+bCOEdecT45rZEZLStpuHOxSP5joWN53o/E/3YWerxEv/NKGH0IxsbA6xg8lhvDlRTq9DokX5oRi4lrzy69Nv1eBWkznU/MJBUiIQvTMmF4/vtNiQ4m0iNM+CA7M+yN0wBbrDhbii5sb2UVRVKQJdEVO2tlC0Fa0Ksg1MAsLB8ysyRMm3sG93Pbhue47sy/ZsWMCxnvFcyKbo0h6U1QbEsaBpCE7mPXzksF1dD1VGv1O+i+HGrWZmdhNAWOLK7N+nqwEtiOjerkAlCgeWOzkCcvs6tvFqBgrB86F+Wdh5QopDPi/EsSdHRU3IW/Wq/IIZelMom3KqvkyIlEPjj2VdLWSTAFASiINtDn2uJ54vd9KXrGTpopqNa8zH/dLyI/yWPKoOAjH/kI9913H9/61rd4y1vewje/+U0OHz7MzTffzBe/+MUTMcbpmI7pmI7aMSWmQGwf9stWxlMimVIUtPYOkvsasICc528OiBW74POsislyZnyYSO8wqqwgnbJYTGS+Vt/T3wumoLx8CMCNJbyiPkN8twryoUkVGldqXBZ8+YjYxjFB9iYuy5qcfAjAGIfh26Hrf0VB5KyrYP1PxWsNK2HVZ6Dj5Tw4Ok7WNriw7fzK2trxcSEbSMTK2nL6oCCpJ+mTJXG8SpgCXz50HJyHANkrNK4oH5KkfKda10ueve6xrfFWNEUjZ2YZGu+iSbLQx3eSi83PJ6HbvwKjWyDbTyLbxyUTXUSsMXgyI5xPXhdyVNnzn9Bf6ncuT4Bmy6iS4oGCKDSuglgndnIxT+3dT3TWXGa0rmBm7BR48Kfw4Q/D7t3BPlJLFrDvLy/nwJxXgKIQ6zidhoY5lQ9M0DXXFSvGRV2Nx70V/LpIXV6v7QMrP8kPgwKvV4Fpmxiyi97YCHYM9HSVxMzBsMS+m5MzOZQZJadFMd0sWtZzFXKyYDuYrourqiQ8+1NJkoiqUdJmmoyVKQ8KHO86LVqttnLimrjvwP3ckunilp3/y4zEDNbNWsfF8y9mjS4AR4llr7/fkPsQeIxlAApCvSv8Z0OlZnLhzsGW5Tk7ZWF4TBzblhZxfaoJ0W/DyQbAU3d9UDCFVLCuGTgII56va7hHQY93nba25q+FMhEsxEhKnoUsU0NT0MAsSMCrMQU+wKjdvKw+Uo+Eg2mb2JpaaJMQNM7zzkMl1s6Z7JyjArmqDMbJElMGBb/5zW/40Y9+xEUXXcQNN9zABRdcwOLFi5k3bx633HIL119//YkY53RMx0sipkmC5xG1QIFhwLPPQnQEGmVw7YLulsqAx3y2tIAsE4nEPVAQ0hsXgAJRqFwurN07kRwHqakhPylLGriGmLCUqFdTUCofcr1GSW7U64Kc82xJyxQaQ6imYLKFxuWYAhASImNYjBG5sNC4nHzIzkLfw9D9CyFTsUL67eGn80V1kgSrPgWAMXwnUKVPgeNAKoUqaxWZAl//ndSTuLKclw+FmZvjyBQ4Rg7J89dXEiFbQdcViX+uX7jKTGyFyJI8KNjxNTCGkLN9XJI+gmIMoWwS3+cctZF7T/9J/jgc/jX0PQgInqtApGSOFX63Oa8TBZmRNq8YfRyS8xlImnQl9xMPQIEC86+HaDtOwxqe2v8dZrfNRm9bysz3fAr+7//E/rwmY9x4I0/Nthg3JtAVXTQDq5XE2KHVezuTZ0y8a7XAjnTIq4L1i7WL+hSAZ0uqxciYGVJmGv388wEXDt/pAWqzNCl0DAzLwEUirjcQ1+KYkSSmNYaW8agROwuWjeGI4vQwQxPTYgIUmBkIY0gfNIdrCkK6diubxsXlvee+H7Wti58+91N6U73cvut2bt91O69onsHbllzGtTPWF4632JLUZwqckDuZFgYFNVa/JUmM1bYLQcGQBwrahLWyo8RE7yE7Lx9SvO9j1kpqw9HoWTWPe+6SPihQ4nD0qPh55syqu/BlW7IkV03k/WecVcTSVIzJ1BR4nx1TY2jegkquuB7keNYUTHJcJ0tMGRQMDQ2xYMECQNQP+Laj559/PjfeeOPxHd10vGjhVmrrPR0nNKYP+/OIWu5D3d1iJWt8N6zqhGa7wHko0MK2twMQicRJAYbPFJhjBbZ6FZsJGQbWgb1Iros7f2YepMhewyYn38BLcm0sxynLFEixGCDnG5gV9SkoqSmoVmhciykA4UBkDINkAFEhH6rWp+CPl0L/I/nf/RqBudcKJ5Ki82A7dvDdKvYpSKXAcVB0HScaKQEFhm0E+0joCZDlUMdTJ/+djqVxmesI2ZOf5Of6wTFx6l8udqlrKE+/X/RLyPULKVk4WdjXBKf9EFwvoRt5FkaF60746LlyBFuOEAsXGS98G8y8QiT60XYe69tDRkmybtFVJBKdhasFp34g//PEPmFbGZ+F4WzFkuMi4ctk8teUkUP6xS+oHxYJuuVYcO21ooj3qqvgC18Irnlz7z2ASJQnBQrCkh47W8oU5ARTUB+pzzd08pkCu5QpACEhEqAgRVOsCZBEUuVY4ngXgwI7h+EYOLJKTIuT1JOMa0kM2yCe9QCVnQXHwQBQlKBRGuSLvUsciAL5kP9d8za3FhKSYSIhcWrnar5+6Yf48uVf5nd7f8c3n/om9+67l+6JXnYP7S5IdtNmmniZPgUAtmXmnylhpmAyCaWq5kEBgJGC0QmIzBCr9ogmbUChfMjbpzEJO+Eg6sX+GPNAgS8fshQY9uRaVaRDUCQfCmoKnJJ+J/44bef41BS4rhtc06qskvAWDTKK+zxBwWSYAqoyGCdLTBkULFy4kAMHDjBv3jyWL1/Oz3/+c84++2x+85vf0FilsGQ6JheSJGE7L34n4ZRhE9efVx36dJygOFmukZMuajEF/oTlSvDsHpi5FrtOrPxqjgR+XxUfFOhimjB8piDTW7C7iqBg3z5MI4ud0FHamkOgQAdSwcSgKaJPgR22WSQPCohGRWJtFDEFxYXGU7UkrcYUiG8MRME0kLDFhHjkbjj8G1j7TQEeAGa+Esb3QctZMOtqWPS2qnZ7foIvS3JBh92CmBCryUqdsKYstuX0Ezdd0dEVXbgP+cfLtvOgYCqNyx58HQw8KpL84nMaacM++0mxy1gEeXw3jDxTuI2aEMl8XdJLQAE1Ko7J4ndBcgGO3sLDvTuZkGN0Ni2he+wQLWGpysK/Lthl2riXtJnGUOIkqtGHPiByJVyvSFKRFeH+c6gH/uMn8D9/QO0bYuXrrqTrouVCknXhhcJmtKUluN4hf7xjaoxRRqfGFDjZAqbAcR1SpmCP6iJ1wbklkRDj9o91MSjQEwykB0gZIebJbyLlGBTxKBjmOI7j4ChRYlqMhJZgWI9hON49Y6WEV7zjknNdHEUukAn5rEHY6hYIyYe830PuQ4bjIJsWsiyjRMX7NUXjqiVXcd6c8/jdnt+x58CdXNmxJEgot/Vv46z/PItrFr+am4aXclrHaSiOk2cKLCMECkLHZBLFs6ie45MPCgb7wXEhUR8wM6Yk9qlhIeECEmrAFExhrm/0rpeJEXHP+VK9fs9EoLm5oEt2uShgCmQ1bxPtGBAqzC6QD00GFNQAUGG5qCqrxDWdNJCWHN8fSsRUC41r1hSEGj2e5DHlrO9tb3sbzzzzDC972cv42Mc+xqte9Sq+8Y1vYFkWX/nKV07EGF9SEVVlsqZNIvLiJuTjWZO6aOEYVFnGtB00pfLE/+cYm7tHOH1O44s9jCAiqkzOmgZtJTFZUBCJwPgIbNiEff6lAERHJoTsI5EIJtFoRPwfgILsJECBacKBA5i2SXZuM62Knk+U/YnByTfwkl1HNCuT5KA8OmAKojGxapbznJKOV6FxJaYgAAVZsKNIh3/LIvPXKE9+NT/xz3wlzH+j+HnZh0QyO7QJIs01/bdrdjPO9sGB+8BSUZobgVwJU+CDgqgaFQmDJGH7WZsPdlwntAo9CabAGC48t1qDt2LfBtEOXC+ZdWJRWP1pIZeItoltIm154LFpExw+LM5TrF6wJY2rIDkfGWiw44yOdnF4/AhQvsg4GIKigTkJByL/GsyYWLaFi0vi2R3w0C2wYUNwTNyODkxvhd50TCFTUZSCHgWO6+SlFV7SXJspCI3PyuRlL4bBhDGB67poikZUieSdXZLJ/PvC7jNe+MXGPqAAvOs3XQhCvMh6DkOqlkCWZCErU1UyyKLg2RwTK+eA4bi4ilzAFPjftcSWNGCdQs3SvON9f9cj/PzpH1K3fR/RznmsJO9E1hhtpCnWxHnzXsbyhqZAcvSbnb8hbab50bZbGdoFTdFGOpS3sm7hBWiyhmN64F+RC+V6QQ1UlXPhj9UHBX2ejKc1X6BuSSquJKNIsrif1QSqzxS4U5jTE815udLEUF4+1O/Vb9SQDkFRTQHkrY1dk7CGKwAFdggwPQ+mINyjQJEV4kqENJCRKhSDB6DALG8s4X9OLVD158wUfPCDHwx+vvjii9mxYwcbNmxg0aJFnHbaacd1cC/FiOnKSQIKrBJQENNlMqb9kgIFO4+O890H9/Kt68+svfELFFFNIWc6xE9uZ7MXPgL5UBlQkMl4OmsJ1p0JD/weRkfhmWegFaJDY0C0YNU0EgkxBXZOJI/grVoa5Qv/DhwA0yQTUbCa4yK5K2AKCCYGVVaDMZuOg7+2VsAU4OnDLSOf9BbVFFiSpzlz3bz7SPB7mdW1akxB5gjs/S/YsxW1LUNbp/dafDbMuQaaVue39xsaQVW7SD9qdjOeOADDvWDEUOrnA70VQUFMiwUJg+tJiBQf7PgsgSSXr4UojjO/Djhekt9aoHEHcDY9IX6Ix6H9wsr78VfJDUNYHGb7gmJjgFn1s+ga7QrObzk70mBXk21gFoCCHI5tsvIL3yPRfTT/+vrV8NevxrruH9hx189pwEuM/MZloRXdcFG3L6mZmnwoA7pXc2GagXSoTq8T959/bUaj+eNSRpbmFxuXMAVQ9jrLGWJfmgdqk3oSR1XIuVIIFIjENeeKMZSTD4WZAsuxODh2kMMHH+LA0QMcTBzkunP+gUW6uHY39z7HI3vu49RR2Da2h3ArLVmSWTdrHbnxViJGT3APfmT9R7h4wcX8+Jkf09f1Q4azI/zysa/zrxu/zryGedx80b9xqmN7jdNC90iw+l1lldlnNXxQ0O8VAbfnE3TLsbDlKIrkCPZETaC44ngaU6kpkCSoa4SRQRjpBTUt2MxRQ5ynSYCCAvkQ5EFB0fWelw+FrrOq7kP+inwFpiBsPw3EPUYmFdBBXgSgIPzcNEqeDZM2t/hzrik4cOAA8+fPD36fO3cuc/0259PxvCOqKmTME08xPbp3gPMWtVZ8fTxrUh8tnLyjqgAsxX//c46Hdvdz+fIO+sdztNVVp0SfbziOy2QUQYIpKKMff6lH8IAuA1p9lqC+Hurq4LRTYPsYHD5MYjxNdCgD9e0FoCAWEUmGY5rY6R6hutUbAEkkfsUPeNuGffsAGJnThiYNElEiIaagMLGRcFG9hNZ03RJQIEW9JkSmDRkvQZKkIAEokQ9BISgIT7CVagrsrJDNxGcL9xBZhdENYIOrtnFUmU/bqutQl72//HH1k+5JeOr7SWfFImNrAlIZcHS0hmbI9Ja4D4WbfvkTuysJByLFBztTLTIOA50y4XquOW68hhQprKfXPDFCqC9DS6wlKOCF6kzBpHoVuC489TScWg9pAwuH0VMXEBsaQ375pfD374f5aXHdaVpwvEzbLN/NOMTk+MBtaoXG2QJg5BcZ10fqC6VDklTWeciPykwBZUFB1hBMQUQXXvMJPYGrqWRcCccykc0xMNPYrkPOK3wvKDT2ft58dDP/uek/2dK7he0D25nfa7BkEGgD5sDa3mdYNGctyCpnzTqbo/NezroZrZy/6JKSMYlaiDkwmAcFkiRx9qyzOXvW2ZjKlWza9wjNsS3c2n03g5lB2iLN4B4GRWbn0F5mxeeR1JOTlw+BAAWmCaMj4vcZncEmpmNiyRFUyQxMARTveNqShuVYlWV9xVHf7IGCw9DiwsAoSC3Q0CAsZ2tEQZ8CqHh+AzY06FCuVnfjCIqyy3cPDtcTAMS8JD/tmuK5WbTwgiTlXdnKgoJSS9Ldg7uJqBHmNoTy4smcw5Mkprzku3DhQs4//3xuvvnmoMh4Oo5fCKbgxCd8v376SNXXx8owBVFdIWu8dJLRrGkTUWXOP6WVR/cOnPDPE+xMbcAV8SRm01EU1VZtfFDQ1CReb6qDZYtxXIfk/sOoOW9SaMkrSzU9KrrDOg65VJf4Y3RGaOIpOgddXWAYuLEYo61JcJ0ipqDIjzs0CZuhIuFgwtQjoHrvGR/xBpW/PkoKjaFQQhQ4paiFk6OZgf7H4ZmP4/6yjcEHruXZ3mdxkSCxAOa9Dlb+E9ZZP+SgeplwuqkkDZpM8zIv/AS3LChwbDAnIJ0F10RrbC54jx9h+ZAvAXAVubBXwXHuUeCkvIQ2WiPZCTvv+M2QfOcgRFI4sy6/ilqum7EfBb0KimNkBL7xDVi5Ei5/M2zaCWnRmGvfDa9l4H++D+94B8zxusm6haujBUxBGBR4AEyTtUItd7UoZgpCwKjAjtQHBYEdaanzkB/+Kr5pm/nvr1RmpPzGZbrHUkTVKIoWwZIjmJYJuWEw06TMFF2Zfn6/9/d88Hcf5GU/eBl37rozYGwG04P85Nmf8EzvMxi2QTQS59SWpVwx/zLeteadrG5dIj5Q1ljcvJjXL/oLzp51Np2t88sfm+B+L703tEiMdbPX8cNX/RdPvOMJPnH+J1BcwHVwFYl33/W3zPjyDN78qzdz38EHxcp6rUJjEKCg76g458kYxBuCTXymQJZlAQocUyx0SBK2rNc+1+Gob8F0Lbbt+D2Hxg7BQFok0JNgCaB0xb6SA5F/HTqWDyJrzI/hZ3+Z414MCuLe8zXrWNhhBUTYTrUSIHWdvDOI97kZM8OOgR082/ts4fGs5SB1EsWUmYINGzZw66238rnPfY6bbrqJK664gje96U1cffXVRGoUl0xH7YhqL0zCt61nrOrr5RLUmPbCsBgnS/xu61EuW95BazLC4MQkuos+zxjJGDTEa4OCqKZMMwXlohooGBkR/zc1geRpYGe3C6nx0F6xItXSUuTdr6ApGpaZwUwfAT0hQIG3MlkAChwH9uwBwFgwF8fcIazrq8iHcC2R1EoyZmiy8J2/JCSRiGaAUe9+DU1W/iqa5Vh5jW8YFITrCewsHPmt6CPw5G1wOA3tIM2GaHo/XcN7USSFFVoddL4CDkt5z/RqFoD+a5XsIkMRyIfK1RTYKY8lcEF20ZIiqXa8bqv+JB4GBSAmd1eWcAj1KvCdh45TjwI3PUmmICwfUpMCSDmWp98WiW5nXScHRw4Ck5QPhZmSjRvh29+GW2/N6/PjUdhzCJKLcFyHTEcbstoIwznIGqIm1wcFnsOM6VRnClRZDYHVGmCvoNA41KfANAvtSFPeIpRvR1rBeQjEdR1Vo2StLCkjhR7TqzIFfuMynykAiMfrseUIRye6ueWeT9AzeJC2rQM8ZsNvJ/LvvWjeRbxqyauQJZnFzYv51IWf4syZZ7Jqxirmj4D83FZocGFhyAFJ0jAdE9m0UBWtqHFdKIoXAcIRamDWHGtmRfsK7JxgH8esFLYkkzbT/OTZn3DHcz/h1c3NnDvv5Zx7VjPLmpeV7i9wSrKh15MOtTQVrGBbjoWtRFHcrAAFHniWZPGMsiv1QSgXDW1kzQyMjdA7GmfWSANSHZMHBeXkQ1BZPmRnRbZa7VkE3sq+d55cCyjMSYtBgeYvLCCTk0MORGFQoEQ8EFV0HguSfg8UeBI013UZzgzTlvDsW/+c5UNr1qxhzZo1fOlLX+L+++/npz/9Ke9+97t5xzvewetf/3r++7//+0SM8yUTUU0hY5zYxNu0HWzHrepgM5G1SBbVNUQ15SW1Qt03lqOjQUyakuTJe06g489oxqQhNjmmIGe9dM5DrXBd1+sCXcGS1HEKQYG/uunaZJcsJHfwaeSMDJ2dhe9TFHRFx8oOYhgTEGsWRaj+RBYGBQMDItGKRMjObEPq2oYmq4jy4fKFxrg2qqTiIhckfwXUeiwOw8D4KKAVTFZ13spoX6oPV5aRSkBBqJ7gwddAz+/E7yZCO7/wSrrXXMVmQxRD7xveR31MZ46qgJ1GMkXS4FZ1+1DEhOg3dqqyrZ9glmUKzHFIeYlqXEeV1aDTrGmbJaDAl3yosgqyUsgU+Nrw48EUZLM4toUrSUjxePVtw/IhSQKtTgBIcywABS2xFuoj9Ri2EchkykWBfOjIEXjNa+Cpp/IbrFgB73kPXLlMNPbaPC6SvlgUVasToMAw80Y9rl3QJMvNZpGgLFOgK/rkmAK/EV/4d0Vcu3YuS8aQQJI8O1KvQVoxUyCXX0hM6AmyVpa0mRZSHB8UhECI67ocHj/MM0ee5Ojwbp49sJlNw9289bS38rL5L8PQNIycxNOHN6Jb0OqCHk1yzuyVnD/nfFbPWM15c84DBEBrdBu5ad1NtMQ9tjB1yPsgv9A43zzLsA1k00KT41VAQZUi1RB4iniyVCOXAcemIdnIg695jCeGDvKjZ37Endt+xmBmiP/b/r+8Z+P/8vH1H+dszi78rAKmwANgbe0Fm5i2iS1HUF3VAwXiPpEUj5mZShFsYzuWYyPnTOSBMXJ2PdG6uvz5rRGTlg9516xjGyJbnYy8SVIBi3JSnWJQgGsTVaO4kkJGsojjnaNJMQUhuar3PXJW/vocygzlQcGfkHzomKtZJUni4osv5uKLL+bGG2/k7W9/Oz/84Q+nQcHzjKimMJQ6savSw2mDUzvq6B3L0tlYfrXKchx0tTC5imkKw+kTv2J+MsSevnEWt+cfcMtm1rOtZ4yVsxqqvOv5xUjaZHZT7dXNiKowkTv5Hy4vVFzxkyvIWBn+smMBZzfP45ToXJrCc9PYmAAGmiZWKidCHY0lh5HVS2iUmmBOUedWRSGiRDDsNIaR86RDEuGOyEH4PQTq68k4OXCdfPJbMvEVMwVKwYRcMGFGvUR0fAxoKZisOpIdqLJK2kwzZuZoICJcVrrvFQ3Flv19/nM7r4LRbaJYeNYaGK2DU5cxGE+D2U1STzJhTLBz9DBJc4wmxwSz8mpuQciaSMgdg6IWQAURlqeUhF9PAOCxZbqik7WyGLaRd4ix8jUFIJIGV/EamPmgwDmO8qF0Gtd1cSIaSiXXJD+KGneJZnCj4rt5IUkS5889H0mS8glRmYiMi+9p2AZ0zhA9NHRdNBl7z3vg/PPFtdj/CKTHIWtiOzZWPIrsF9Fmwwl7HhTgONiZNKqiVq4pUCZRU+CBaweXnAuGMcZY6iDS2CHSZgbJWkAklhT7CtcUQHlXrFAktASDDDJheM5PkiqgtWPQM97DG3/5Rrb0bmE4O8zlcdAleCAD4w5s6NnAladcSU5ViUWaecfCtzI31kmiaYBLmxfQcPlfsLJ9ZcHnxdQYKSNVaEsa2NsK+84gZA3DMJBME0VTajMFQEn38xAoiKqC4RAuZxYoOpKscc7sczhn9jkYl36BTU9/iXsP3Md9uzdwyfxLmNgqjsu2/m1s6tnE66QV4s4bH4eJUXFttLQVDMdyLCw5iuwI0O+7BknKJJ2mwtHQjuPayIaF3jdGSrGI1uhNEI4S+dBkmAL02kwBCOBgU3ZVvoShCECBTAYL0ISMNGzC4IEmcoOQmJf/e5nGZeFeF4OZwcIxhd9zEscxg4Lu7m5uvfVWfvrTn7JlyxbOPfdc/uM//uN4ju0lGTHtxNcUDKdMVsxq4PBIpiIoKBcxTeHIS4QpeGDXAH993vzg9zVzm/ifp7pOKCgYzZiT2n9UkxlMvTTOQ63IWTkePPggOTuH1fcwv1Ng0z2fo77pVNbPWc8Vi67gDfG1YuOmJvF/KKm3XEtMAI1NpQVssoym6uj2BKaZFaAg/P7wJOq7fqgqWSuLhAcK/I6+ULri5MliXKkKU+AnbRPjEG8pSEAUWWFW/Sy6h3aROnovDUPboH8jRL0Czfpl0LhaTLiL3wVL3ivGs3kzjHWDLAcOMae2nspAeoDDA+McGH+OSDaKbjUWjrtS+PKkGiuNVWsKzHFRTwAQ86h9RQtAAYhEwj9OBfIhScp3NYZ8TcFUGpdVikxGWHVGI8LKsVqE5UOQt3gNgQIIJSTFYRhw223wne8wY9tWpHu+jRk1RXJ6662waFFBITwggGkmB5KMqYCra6gx73Nzubz/u2sjS7IAI4aB7YLqFSD7EQZtBfUHlcIxcHB4tn8nE46Lbk0wkrZoSB1Fsh1kcw5NzU0CrGW8ZLu4cVnRtWDaJruHdnPfgft4tPtReid66Rrr4ur55/P1M68Fx6A51swjXY9guzaKJDMr3kxboo11817PqplrWTNzDbIkM6go5FC4Yu7LwbI5pE7gKkrZAu+ytqSBJKcIFEgqpscUqBG1MiiQ5MosWgEoENepYWZwbRsp3NAL0LV4ABBuvPpcEmodv936WwC+s+E7fOPJb/AvYzHeFlnHxYsuZXWiBaUuDtHCVXvLsXAkDUVWBXNhiJpQyQORUwIFkTimd3y04TQTTSYtxUxrlQgsSUvkQ4WLjkFNgZMD9No1BVCxPgHKMAWORUSJ4DoKackEysjB4rNEk8BMj3jmF7tBhe7nXIjJGsmO4LiOeI5H2mHm5bWtS0+CmPIIv/vd73LLLbfwyCOPsHTpUq6//npuu+22Akei6Tj2iL4Auv3BVI7Vsxs4MpKpvXEooppM7iUACrKmjSpLBdIqXZUx7RPbbng0Y1IfrX1LRjxL0ukQCebGd23kicNP0Lv//+jq38yG7GF2DOxgx8AO+tP9vGHJIgDcxka++eR/cE7zXE7TLTTXDlaOKrluRBSJtGNimIaQ3ED5QuOQo0/GzCC5rgcKQglgGflQTaYgFi/cf5jWnjjAqTs/w/Ijd6F2ZUTtQQPQPEcwAo2eq46sFyZfvne9LBcUg3YkO8gaY7jKRnpGDzAz2eRR9jUm4loNfryoWlNgjYPpJSUa4B8/8ivY/iqcIivBPlRZxVBkHMc5MYXG6bQABbEIeqVk3g//3NgeQPFBgTlR+T0ABw/Cf/4n/Nd/Qa/olyDLMk3P7iJzrqeTP/fc8u91bUjncJAxo+J4qXHvc7NZLyl1gmtVlVXkXArblYUdaQgIl2MKbMcOyfOKws5hWAZp28aRReMwPVpPfdNsoqbDnNaVtHWcAhOp/PHxEi7XyZExM8Q9+ZBpm6z7r3Vs7d9atrh6c78n6XEMImqEX1z7C+Y3zmdOoo29276DLCusXftPwfcZzY7iqAoZF2FL6jgYbmmPAj/K2ZKWNC/zQ9YwrHEipi2eG1qV+yNg0YoS1JDcx7/OJcvGdnKoSn3hPRd6hjRHGwhPwQubFrKwaSFjI/u478D93HfgflYl61l7xtmsGlnGKc1rgm1NxwRJQlY929icWMmW1QQ4UwQFQC4RB6/UaVSVhLPbJMN/7pbKhwqPkw8aHDsH1E0OFFRZlS8rH9KiuIZMmvzCTkHojaJhozkhgEHCY5TL9CgIMwW2YzOaHfXkbwpMpWv0ixhTBgWf/exneeMb38jXv/51Tj/99BMwpJd2xF4A3f5wyuTsBc1sr1FsXBxR/aVRaHzPtl4uWz6j5O+JiJDtFNdaHK9wXBd1Ej0gIqpMdrqmANuxebT7UcZyY7x59ZvRZi0GY5TPJRbzSN9uHul6hNM7Tof+EQAOKSned/f7aFdgfVyls3kZ6aa1zKqbRXuivexnRCSx8pN29fxkU04+VI0p8CNw6nHwO7qqkioSuoo1BYn8Z9k5MHqBVd5nJdEP3wauTU5vwKo7m8QFN8HyV4rPHdkivP+LKXcvec46BrYjVpATWgJJklgz6xx2HPgjtnOIQwPbsGfMmJx8CGqCgoo1Ba7nm26EJmXHLLHlLC4yBjG552QZ2/YKjV03BAqOQ6GxDwqikapyH0Akh5LkrcIa+c7PVgVQ8Oyz8IlPwF135VmOjg54xzvIvPV6huzdKJNpXpbKYLtx7JjHnsTDTIEOmEECo8karmFiOYWNy6C8+xCIRKoskHNyoo5BUtH0elY1LobkQmgfEJK9SAvIKuNDRznUv51ddh/33HUHW/q20DiyieVN8/jCGx8Un6lojGRHMGyDpJ5kWesymqJNLGxeyF+u+EtWty2D4Se9AlKH15z6GgAGR/eL76zGCwBOQk/gaCpZV8EycqiSQs5xcWW5bIG3zx6Ek7pC+VAoZA0rlyGCl1xWYgq8bQWLVnQeQ0yBLMlE1AiSZWE7ppgDCkCBHOr4axFO2z5wzge4ad1NbHjq1zx5x3d4+ODDpHNj/LLvD/zrb57l4fddVWhIAMiaBwqCQuMYOO6UQUE2FijwGWoWdTIV7YaLoqJ8yC0vH3KDZneTrSlgkjUFHlMgKaQlDxCWO5+x2WDugPShPCgI5EP5ZN+/fiRJwnVdhjJDnj3tn05MObvp6uoqv2owHcclIuqJX40fThs0TcLlpjiiqkLmJWBJWqnW4tyFrTy2d7AsYHghIzrNFABiFcl0TBzXYSgzxAwvSW+Jt3P10mVcvfRqkZwdEAW2E3GVVy99NdsOP4TpDLG1bwv3H9wCwOce+hyfvfizfPLCTwIiMZeQ0FzxkE+5oQSqHCgIMwXWOJJfU1DAFKj5pNE1C2oKwqujBaBAk2FsB4zvgfEdMLoCztwgNoy2wtpvcFhpZ7+0h6a0y4rG0/NAxF91K56ovbGmPO19Qk8Ez3RFVjil80wOKTvIGWmGzKHJyYegNiioVFNgpb1k3hXHS1OFLWmRLWclUIAs4/iFxo6Rb2JXxu5yyhFiCpRyrlbFoWnimjMMSPr6eb+DsF5acHrHHeL/Sy6BG2+EV78aNA3NNmHPbmzHzksQyoUj5EMOcaxYBEVWkH3rVMcB0xF17iGmwM4Z2I5eCgpCTIEsyUGhd0VQYOewXAtX1lC0BJZj0T92gJl6s7dDk3P+6xwGn32CUwfgUD1s9mpgXxFHWFmGrq2fXfMz2uJtzGuch+u63LX7LgDWz1kvPn9Eyhc3eyyQ381Y0wqlMqqsousxHFkjZ2SR1UjAFBybfCgUsoaVFXp8NRKr7ptfyZY0BAoAIkoExzYxHYuILJcmvwWMT+FrkiRx1rxzOesshXeteRfb99/GHe07Wd22rgAQfPKPn2T1jNWcduqlCLcBf4hxsFJTBgWZeII44Eoy2RntDGWG6EhOrq6gtNC4hnwocKs6AUyBGsXFJo2YS+RyzE98tngO5waEkYEaCxUa58+HX2jcGm+lP9XPUGaIRSyqPeaTKKYMCiRJ4qGHHuLmm29m7969/OIXv2DWrFn8+Mc/ZsGCBZx//vm1dxKKw4cP89GPfpS7776bTCbDkiVL+N73vseZZ56JaZp88pOf5K677mLfvn00NDRw6aWX8sUvfpHOkH7toosu4oEHHijY71/+5V/ys5/9bKpf70UPWZY4sSKV/Iq0O8UP0hQJy/nzTkb39U8wv6W8K8jcljh/2N77Ao+oNKaZgny0xltJGSkG0gPMCDoahxIovz9BMsmyztXc9sbbcHPDHNn3P2wZ3EN99242Hd3EobFDLG1ZGrztwYMPct3/voEvjrbSYOkcHlzI6UZKdFudBFNAOaYAPP19Tkx+4ZqCUNIg2Vk6hh+jrvcHcOC30J3Ov9/sFUm052bDKTfSZhsc2PgfpIxhxjOj1DFLvFapmNO7hyfMNKh5FyM/9HgrrfE2Do8fIefkpgAKjrGmwG/w5WggW6Ap4Bgltpy+tCOc1KmyWlhoHLAEkdJjfyzhFRpPiikAscpoGCLZkxWRPJhpuO/38L1bhKb+P/9TbLt6NXz1q/DKV8LSpQW70RQtWG00bKNyTwPXhnQWy3GwE7EAJBGJCKbAdIQro3etaooGhontVmcKQABEx3ZKkkXf9Wf/gT9w4NC9/LH/ALvGB5hhdONqjfzq3LvFhoZBfaSerAEtsWbaFy3n0tPOYVX7Cs5XR5lTP6cAuJ09K+SoI5G3JTVTNCqNhfeODwqKGpeFIxqvw0Aia0moTg5H0pBVjYhaChb9a6qifCgE5lwU7KzYTqnVu6JSH48iUBBVo+RsC9ux8oxTwX5Uz8XIAqkM2PX1/YrG6lPOYvXpb4C284KX7913L/fsu4d79t3DXZu/zbsWncvF8y9i1YxVKGoSmDooSHmgQKtrwaxPMJwZnjQoKLUkLf8MyTMFJi6usE+tFUFNQWVQoEiKBzAtUUOjqBgtTWTlGPFiwwkQ93GkRUiu0oeg/pRQTUGpfKizrjMABRXldydpTBkU/PKXv+TNb34z119/PU8//TS5nEBG4+PjfP7zn+euu+6a9L6Gh4dZv349F198MXfffTft7e3s3buXxsZGANLpNJs2beJTn/oUp512GsPDw3zgAx/g6quvZsOGDQX7euc738lnPvOZ4PfYJLrqTcfU4k/pwj7WuG9nP289d17tDV/EUGUJ6wTXN/ypRGu8lda/fi+x8Qw0J6EhDrMfhPZOaG4WiWJbW77I2HWRZJVZdbOY1bCAxvnX0J/qZ27DXE5pOSXY76PdjyLlBtg6NICchv9+8Fn+7pmvsrZzLVd2ruKG+WvoiIbcPXxQ4NUUqK6DrsRKeybImkhsbCNfU1AkHzp19z/TPvSQ+EVCNMJqWAlzXgsXX5cHBF7oik5TspWJgWF6Rg5Rx3LxQkC5F02kPiiwPVAQKQQFROrRFQ3JdclZ2dqrc0ptpsBf8YYyNQXmuMeeaCCZIikKSREqMgXGCNHsYeK5I6gpE3oTohgbjk89geOIQmM8pqBWTQEUFhuPjsL374Yf/C/s6hZ/j0TgX/8VvDmOD3yg4q40z/pyMqDAVl2sWISof66iUQEKslYBKPCZAsvRxFhCEWYK/M8fzY6y8chGLlpwUbDdq376Ku7eczenR2C2CtsNGLShOQZYE6QwhROqafKdq75D66yd1KcsOPNMYftrZ6Hnnny32AoR1+JBr4LGaGMeFNg5UXcC5AwhgdWLmAKAWLQOAxiXmlEUG1NNoOvl8wL/+Jq2cHFSZCUvH5JksB1QvT4PgOzVv6jReLnd5aMSUxC2EPU+37RMLMeGMqClQBJT7jIM6+A9G+3wPbCsbRlvWvUm7tl3D32ZXu7dfy/37r+X1lgL+pzXsG72eSxoWlD9u4TCdV2G2ztRFi6lY8n5IOUYyky+ma0vHwqAdjiRD3Ui9kGB5Fqia/mUmILSRQr/c1VZzTOKiO71o6QYW7yaeCVgE58tQEHGBwWF8iHHdYJnVXuiHUUWDHDKTInO1H8iMWVQ8LnPfY7vfOc7vOUtbylYiT/vvPMKkvLJxL/8y78wZ84cvv/97wd/CxcsNzQ0cM899xS85xvf+AZnn302XV1dzJ2bbyMdj8fpmIIl1nT4SobyKHaqLMKfQ+QsG0Wiqq5/bnOcg4Mp5lVgE16IkCSpKmP9UoqWWAvuxu1E+8MT0m/zP86fD//+73lQcPrp0N0N9RFoqmdpQxOz66M0dS4ivnQlfPCDAHzo3A/x+jGJkdzv2eAeoEkdoM+e4JHuR9h75BGu7fxKkGg93PUwQ9t+xxqpkzaWetIj10uuyjAFICYsa4LI8NMsO/oguyMfCDbpbzqH5MQO5Hl/SXTOa8F9AFwF6peWJHJ+dDTMYg+76Rk9xGJfblJDPjRhZSBSyhQQaUCT/YJQG8MNcrDyEUzolUGBP1nKklxa1G1NiGJQJSr2oSlCPqRUkQ85JvQ/Qix9iIgzgmTaYEyA2ywSiniZ1b6pRjYLrosjgaNrk2MKNA3274ef/hRuvz3UZCwG179JSIR8QFAjdEXHsI3CBmbhcGxx3HImtuKKHgX+sY1GBSgxPA16CBSYOQPHiRYwBZZjsWdwD9sHtnP/gfvZPbSbp448xdGJo0hIjH9sXLBkwPzG+SiSwtLGOSyra2FhdC5LOtfz+qYG2pPtyOONwAAYBgubloDp9SiYROOycCT1JEOZIVKmV6gsR4DxguusuJtxOGLxekaBtC0Ric0E9hCNlk/ONEXUUViORcbKiCROUbwVexlsK8iWTFeAAkVWkCM1wGclJ5xi+ZAaIWWbWI6Z72JesJ8alpYBq2GLxREo6AExt2Eub1r9Jt6w/A3EZYmdW7/JQ10P0ZMe5HdPf49T21YEq+iTWdk2HRNXkuhfcRYr5p8LB+4vdNupEYH7UHFNAXjAR1wbgWOWZwqhTMaSdLI1BaFjmdDqGc2lSJvpkvcEEesUdVrmBBgjoUJj8R186ZAsyUTVKI3RRgbTgwymB/+8QcHOnTu58MILS/5eX1/PiN8gaJJx++23c8UVV/CGN7yBBx54gFmzZvHe976Xd77znRXfMzo6iiRJAZvgxy233MJPfvITZsyYwStf+Ur+6Z/+ibq60gcFQC6XCxgOgLExsdpgmiamWeEB/AKGbdsndBz+/pO6TP9YmqZ46cO50hiO99j8fZ0Mx/13zx3loiUtVceydm49d245Sufa2cf986dybC3rxF4jxxIvxrmUkXnuXz6C3dfD0rE+EhM2rtGINDwKg4NCb25ZuMkkmCbqwADS8LBoCHbwKE2AgAsP4C5bhvW3fxvsd8mHvou08wDrgBtlGauxkXRdlOGYzdzNv8b699NwTZPvbfoerT/8AdsysPvOBNnF81k6az6zVpzF/HnnoYeOh2QaSH0PI+2+GanvPmJ2mhgw0P9HTPMvAehquIBdyXO4cN7LUBQFWXsYMgauZQlpYZnjWxdpRJEUjFyG7uFuOus6kcwMOBauLRW8RzIMsCyGc2msaJyoHC08Z3IMWQIZBckxGU6PoZfRYQfhSEi2BUYGt8K5T+fSWLYo6iu+PqTssNdh17McdB3cXAqJOJZtkTEymKbJRHYCy7ZQUTGz40iWgevIjGutJDQXM7kCWs8UyZAklT1OU4rRUSTLIqvKWI6NYzu1r21JQn7qKRRvwcw99RSc6y7CfeM1uPMvFtvs3StW8U85pcqOQHZlLNsilUtRr5VxdnEMpPEJJMcmJ0mYMkiuJMaoKEiWBekc2GB5PSdc22V0pJenx/fSyCvQvO/zrjvfxQ+e+UHZcbQn2jkwdIAlLUsA+KcL/ol/ueRfiA0/xcH+Z9lBA3PbzqTV3Idj29iugWRZuOk0pNNIHjBydV2cEyMlrhc5XvF6AdAkDcu2GEmPYNab4MpItoVrpEDzJGXZEXBsFClecm40LY7t2KTGR9DliGAAFL3iOdQkjaydZSw9RsST6EiuK1bzLQdUkQSmDRMnmxXHutZ15pAfc/F1b1mQEfeM4iq4Zk6wBZJSclwkxwXbwjWzmG6Z56wsi7EqDiQi4IhzTQhQZowMLi7r5r6ci6IObzvtBh7rfY6WI3uZVz+PrJHFNE1uvOtGjowf4bqV13H1kqvLFmZP5MS9qMkaUTmKjIxhGQyMD0yqsDZniiL18D0luRI4pjhWagiUOKKmwDANJIfa97XtiuvLzJYcx6yRxbItXNvFNLJiO0lB1yL5ay1ZZf9aG1LmMO7YfpAUcW5tF0yT8cw4lm0RU2OYpkmdWkev3UvveC+difJ2rS/UnDmV/U8ZFMycOZM9e/aUWJA+/PDDLFy4cEr72rdvH9/+9rf5u7/7Oz7+8Y/z5JNP8v73v59IJMJb3vKWku2z2Sz/8A//wHXXXUd9yP7q+uuvZ8GCBXR0dPDcc8/xsY99jGeeeaaEZfDjC1/4Ap/+9KdL/v773/+eeK2ulS9AbD0qcdfgcyd8/13j8PMdMKcIxLoubOuVuGuodAwnamyVztULGQ/2SLhdLs/U2G5Dj0Sy79nj/vlTObZbe8qfn5MhXuhz2RWLc3RmnHVzE7Tr7fQpZ+BKGmomQ8uWLbibNtEnie6q+uc/T2RslPaxDWjjGXYNWSjj48zJxZHrm9kTkj++3DKIayqyaSE7DvrQCPoQNALpia08/fijDCjjKAMKN23SmD1kwiMpYKv3704MBSbmzuPJf/tHVhg/oMN+AuU3BkwASTCTUQ4mOtge7+Po5m9hNjTwuLIfy7XI7TRIyCoL9u9FHc8wIrv0myZOGbagrquLTPdRdo308PRIiqXxJcywnwKgT7FxQytsbc88g51NsWGOhZGIwy4KV/dchyX79jOc6cduaOa3f/wtbXpb8UcGobnjNNvbsaUIA0p5R7Mxa4wdqR3E5BjmjtAE5brMsDeiTKRwd2lo2jg5vZ+UfIQep4Htqe1E5SijdaNsHt+M4RikE2maFYcmeweDlsHOgxPM68vQldnMWM9o7QtmkhHr76d+/34OxNJsyXZxNHqUvZG9BdskDx1i/m9/y8CqVRxdt466ri7qW1qYvXYtu1/7WiaWzabJ2Ym95QkGtmXAcZixcSO4Lv2nn45TxblmV2oXI9YIg7HBssdfdnN09j9JYl8vO2MWG7IazVozg/FBEocPo3fvZ6j+ED0do2zIZngi1c/+Z/dzwc40mgNdLQvpbPZqVTYV5QAAtSVJREFUGfpBl3Ta9DaWJZaxILYAGZm4Emd5cjl7ntjDHvYUfH6bvZm+bBfPWo0cihqMq73Ibo70cDfx/b0Ye/YwsXs3zdu24eg6/V5DqKgzSIOzF0OqZ1ipbNc6ZA6xJ72HHcoOepI91DkHiDt9pOQjTMizcV2X3rGniEspBo48jaP2Fe6g/whje/aQ6T1CItKMM3AIyY2xd7D8KvjO1E5GrdGC4922eTOyYcCEC3Hxvr1OP/17NtM5kGHEfJzxI0cqfoe400udc5CctI8R5XDwd8k0aX/6aQB6bZthawRl53aciUEObd5Cb09hIt5o7ybiDjMmD5CRhVNa8XNWyeXQGKdh4z5sKcaAkpfH2K7NxrGNALi7XGY421DcDJrUyCXOJWzcuJE96h66Y9389LmfknEy3L33buJynHMbz+WipotYkVwRPCfC97O902Z3ejfD5jC9z/UyMzKz4vHwY8PoBhwczJ0mEY/RaLWfQXFzDClpTCmflGwe38x8dwd2V4pxTcaWqrMzhddX4TWxZXwLGSfDRGKCZkWlxX4OB41tTh/7M/vZre6mO9Fdcd+6O0KTvQuHZ8hJjcTcflJyDxPyQYbNYXand5NUkuS25xi1RtmZ2skWeQs9dT1Vx3yi58x0ugoDUhRTBgXvfve7uemmm/jv//5vJEniyJEjPPbYY3z4wx/mH//xH6e0L8dxWLt2LZ///OcBOOOMM9i6dSvf/va3S0CBaZq88Y1vxHEcvvWtbxW8FmYWVq5cySmnnMLatWvZtGkTa9asoTg+9rGP8Xd/93fB72NjY8yZM4fLL7+8AGy8WDH0RBdXrptbe8Pnuf+e0SzPHR7jsuWFdowZwya95ShXnjnrhI/NNE3uueceLrvsMrRqfs8vQEz2uw0/0cWlZ84u6fj8Qn3+VLd9oeLFOpdHJ46y8cgTzElvY1X7KtyZrxSUblcXUiQCLS24YZ9310XquROA/RmFjGPTMed8GqONLAlvc/p/4Dy3j0NHHPbHLVrbF7BUboPeLiKZ3aw7ey3ujJdzJVei/PIwzoEDTGTHcEaGSY5nUW0X3QYtluCSV7wW9dd/g4SB9RCoXn6gkWUxB1jMAeBO3JkzMe79DrZrc8n8S6j72w/ApseEI0/zCK5lQVsbblMTzJiBe8UVYkfbt2PsbCUS6WN88Vwunns+8UGhAXRnvqqgcFHSNEZH+xhZpBFrnsHL5r2s5JjK2V0cPbqT3fYEa85Zw6qOVZVPgDWB1JcAWcPtuKLsJj0TPSR7kjRHmzlvznmh96aQ+lwYHIO6OtDHYFUDbnwuE/GFJA4m0GSNyxdejrvHxcXl0gWXEjUHkYaTDNigNRyls3uEpaedB2ecUXmcU40dO5BaWkgkM0RmxVjeupyFTQvBMJB+/Wvk734X2TO4WDA2hv3pT8Pu3UizZ+Nefz0tp58Odhap9w+AhDvzFTCRCmwc3QsugIbKzQo7ezs5NHaIU1tOZXHz4tINrAmkJ/pxpDqONreRjXezetFqLpp/EXR18YuffYo7un/GmAY7DdhtguRAxJVoi7ex4rwzOXehYP0vzF3IVQevQpZkrlx8JbIks6lnE0cmjrCibQULGov05q6L1OOyazCKpM9n1cyzmGt0gTGMa8xBaumGxkbc+fOR4nFobcU95xzx3ol9SGNNuLFOaCqdn/0YzY7yUPdD6IrO5Qsvh/GdSOO7ceNzoXE1OSvHpi3Podlp1qz4C+RYoXzY6evl6dwhjGQMPVGP2xhl9gWX0LHs7LKfN6t3Ft1j3SxpXhKwIlI8LroxLwG8PHVGfDn75Qk62kxOOe/l1RmfzGGk4ach0orbck5ocA6SV7PgXn45I3aKfRPP0TKoMe+c82DZ5YX7GX5arFDXL8OMzK38nM0cRhpuLvm8nJVD2i+uvFctfhXycAdke3Hjc1mgtrOhZwNN0SbWz1nPk+c+yS1bbuHWrbdycPQg9w7dy71D9zK3fi4fXPdB/uasv+HI+BGSR/P3897hvWwf2E5HooO1nWsrHw//6+8WgOWyBZcFhd9Sfx2Yo7jNZ+UbRQLx/VGSgzlObTmV5LyrahsfZPuQhp4ErQG37YKClyL7I2SsDOfPOZ9G2UUaiIISZ1H96Tx66FHiapxLFlxSed+uK+5nJycYSWcebv2pkFzMgZEDNPQ3BMfAcix+t/d3uLhcsuCSsnVBL9Sc6athJhNTBgUf+chHGB0d5eKLLyabzXLhhRcSiUT48Ic/zN961PtkY+bMmSxfvrzgb8uWLeOXv/xlwd9M0+Taa69l//79/PGPf6yZuK9ZswZN09i9e3dZUBCJRIiUWW3TNO1FT0wBFEU5YeNwXTfY/6xmlQf2DJV81nDGpikRKTuGEzW2k+HYT/a7nbWwlS09E5yzsOW4fXbWtInpkz8GsnzirpHnGy/0ueyo70Dr9exJJQdd8+QjExNCa9vWVtpgSNXBdZBlB1VSierRwjE7Jigq6BqxZAK7yWR82XzU2eeIwtje+0W5gP+eD38YxocZb98Do3dRP/IkrjSDsYVfoKFxLVqsCeesb/Hm39zIhWfmiM2H5gy0Z0BNyzRnddqzMrG2NhRFQXIlInoE+YknYZunyWY7/D60ojRzJvirlNEo2v/7HBd1HSDXVI/S0oLaoENzA8y+T/jff/zjYltJwu45RDLZSFPdLDRVLXU7iTUQ1aLgpMg5uernU06IY4Urjne5GiXJRVVU4pF44b6snHivFBfHMl4nflcgHomjKiouLrZki+MiSSSjSSS7HxSViBpD1gZBAk2WqzeSmmqYJqgqbjyGqqgkjg6g/fuPC5qMIctw1VXIN94orAwTiby+W9O8f1GhP5ZMUYDsv+66VcebiCTE95fd4JgNZYZ44tATbOnbwp7ejSza/BCZQ73cknTY0wLzmuZx2SmXQV0dC5sX0tbbwCkzF3F+4yp6+hq5/PTzaXx0I83JVk5d+vLgs6JE0VVdeObrYm6M6lFURUWSpdLzbxugKLiSi6xGxVilOrDHISKL7+i6QialqgL8+PuQXe/eSlT9/o1KI6qi4uBgYRHTvetMFsctZafQJYeIFiUSrS/dVzxBLBLDdVwsK4cuKyTjDRWv5fpYPWpKxcLKbxOJeE3gJFA8kK0oaI5LRIugJap/B+x4wZgLIhIJ6nuS0SSa6+LgokbiSMXbalEwVFCkYD9ln7NZu+yxNVwDVVE9q1YdYm1gDkKshZgsrm9ksc+VHSv5QscX+OdL/5mHux7mx8/8mJ9v+zldY12MGqNomoYrC4BuuAaaptFe187u4d2MW+M1n/2O64jPA6KRUB2MHgcnJQqpQ/uIaZoo/JYlND1e9vlS+AEx75hTesxlUBWVWCSG5mTEdlqUxri41kxMFFWpXhdRN090OMY71loMNA1bslEVVZxLTUNDoznRzGh2lDFzjLpYeTk7nPg5cyr7PqYuTP/8z//MJz7xCbZt24bjOCxfvpxkcuqFFOvXr2fnzp0Ff9u1axfz5uXdX3xAsHv3bu677z5aWmonYlu3bsU0TWbOrE1jvdQibdjENLFCocjC8q44xrIWddGTM+E8GWJZRz0/euzAcQUFYxmThtj0MT+W0BSNRq/QcCw3Qas/afg1Tk1lNK6e77djmyBHSotf/WJGRSOiRZG8DqzivaGOxlYGeu6GZ/8djj7OrFNy4CsQ9QwN8+dAu1h1lBe9jf948xp2n/dLnhzq4onezfQMbuORtEmvneXShZdyz5t+j7NLeNd/8eEvculH3siZu3YT298LNEJLu6iVGBws/F6KAuPjqBNp1Ik0dB8NfZn7BYDwQYHjUHfz97l41778e5uaoKVF/OvshBuuRpN1HEsmcs8foa4r/3pLi3B2SiRKHWRyA8ItqahHQMVuxr4dqettH4kBdoH7EBB0Xo4oEVEE6RcuqzGQQ5akxzM8yt2K6oBD640fgkefEK91dMA73wnveAeEDC+CJMQIFV2rCTBGRUH1REguE96mKMZyY2zp3cKDBx/kkoWXsLxNLJ7ds/ce3vjLNwLQJMM7BkFzwIlHObVlfn41Mhrl7Flns27Gl+HsGZjR2dz1SBenNSzksPwMplZoYVPsPAR555eyVpXe/WG6gCSL98m+642d/34pr0g4nB84kys0VmWVlngLg+lBeiZ6WOgX9XqfnTHSSI5FRE+U70mhacTUmOgb4l0bsQqFxlDLltSbJyUFw7GQLAtF1qs3LoPK7kPe+LBtME0isTpk2wLXxVRkSvYa8tWvGhW6eZec37pFEG0HrR7V6/VQfJ5lSebCeRdy4bwL+fdX/ju/2fUbzpkt2IecleOpI0/x5ce+zCsWv4LrV11PRImABSnfurnSEJ38dyhIviscK817nNtQGxDA5PsU+M8LSSGiCncx27FJm+nqhcHx2R4oIHg/5AuNw4xAc0yAgqHMELPqS5UXJ2Mcc2vWeDzO2rW1aaJq8cEPfpDzzjuPz3/+81x77bU8+eSTfPe73+W73/0uAJZlcc0117Bp0ybuuOMObNvm6FEx2TU3N6PrOnv37uWWW27hyiuvpLW1lW3btvGhD32IM844g/Xr1z+v8f05xlDKoCWZf+SUcxkaz5rURU9M194/h5BlKZgjjleMZkwaptBQbtp9qDBaYo2MAaPGBK0gigN9yrQCKHAxcF0LKGM36U9Mqo4ma0i2Q9pPFoI+BQ48dSPs/yH0AA7k4jM4NONcGmddTktiFuiFn90Ya+OszrM4a8EV4FiYuUF+cngPD/ftZP3c9Thel5LBzCCffuDTfBq4VoYLG5swO04nedVlrJ+znlNbTy10CFEU+PznsXWNpziM3tfNsnSaWFaDXEPetch1wXGwZQkrFkXNZMXkODAg/oEABe97J7qWIJ2LMe/bt8Cm7aXHUNdh9mxROCvrIln710/CkX5oaoDWVmhuhZmLkGMaEYbRm4rqzswwKDAgEsd3mJEkKXCEGcuJcxlMuF5iqShx0afAsfNdgY9H9PXB978Pl1yCubANyJG54c1Eo4mCJmNljwkUgYJkeVDgmV0MZYb4/d7fs6V3C1v6xL8DIwfyb5dVXr/s9QCsnrGaZa3LWDVjFetaFnLlswdoj87m9RdeyWF5ghXtK8SbolFxfZjecfHdh7yu0SWgoExjueqgQIzd8MRQuqILL3cQvSZAMC3+902EksRK/TPKxMzkTAEKxntYGFta8P6MOYaEK+Qn5falqkTVKFJ2FMl2kCSJSKRysupfWwVdjYMGZhLggqxh2iayYaKqNboZQ2X3ofC+va7GmjcZ5ySpFBRUcdQpCB9wFYGCkqZdkgx6Q8HfqvUpiGkxrl1xbfC7YRvsGNiB5VjcsesO7th1B0k9yXmzzyNn5Xjd8tdVXG33exRIklS4TQUXM1VysQGn2MmtUlQ4Vo7rBIugBe5D3vdPaAnGcmOkjBoWonoDaHX5Z5f3fv+6CffBaI41s394/5TsWl/seFEzv7POOotf/epXfOxjH+Mzn/kMCxYs4Gtf+xrXX389AIcOHeL2228H4PTTTy9473333cdFF12Eruvce++9fP3rX2diYoI5c+bwqle9in/6p39CUZTij3zJh+hmXP1BNp61mN003eehWrQkdfrHc7TVHYeuqcBIxqQxNrkW8dNRGq2xZgEKct6D2mcJYrHyNp6SIqxDi63x/PAncS2KrugoVpb2wYdwjv4AecUn8tvN+gvovQ86z4S29Tx2xgrGZZPzG5rBGirfvMzfv2ujyRrLZ6ymtXkZZ3aeGVj12Y7NO9e8k0e7H2V4eCu95jD39t/Ho7+5D4APnvNBvnLFVwAxmVuOQbShAWXGDGJzT6WvfyN9cpp5M9ZCa6GWGWDnB95Ez/mn87LZ66lLmYJ5GBoS/zsOxJpQms8kM34/w8sX0phoRvEdnQYH8117fRe3xhWQ6oLfPAJPbS053IuA+VGdfYdCxfEf+ABsfAgaY6A1iaRybid0Aq0t8OYL0RVdgIKsWM0MQIFna6locdzjxRS4Ljz0EHz72/DLX4qk1nGwznkrWDly174O3v431ffhJ4lhtw81iYtL38he9u3YwpGDz7GoeRGne1r0/cP7+atf/lXJrmYmZzKzbiYtsTwjuaxtGdv+Zpv4ZawbDnwXtCS7YzrkQkm9rgtpkyRDzoSo1yPCEMfI0AuvS38lOczO+MmiWS6htXOefESAAk0OMQVyKBkb9+7HAqbAZ+FqPztn1s3kub7nGMoMkXUdoqH35zygqKmJ8o3qPKZAcl1kw0RXdSS1cspTtquxn0O4eVBg2AayaaPqkwAF4dXv4m7WPqj0ehXoDriAUW7Bp8rqd0H4TIFceGxLQEEoJgMKiiNn57jhjBt471nv5f4D9/PjZ39M91g3v9/3e36/7/fMb5zP0+9+WvSXKB5icY8CPyo0MNMQLIHFJFfC/GPu2gU9D8LfTzQvyzMFIDq7j+XG8ha41SI+G0a9hRKpEBQUMwUgmD/TNst3Bj/J4kVfDr7qqqu46qqryr42f/78svKWcMyZM6ekm/F0VI7BlMHC1vxqSbkV5/Fp+VDNOHdhC0/uH+JVq4+PRG0kbdLZOA3EjjWaovVIkkTOtgR97XcyLscSQAgUFHXW9MMxReI5sgllx5Oc6zyJmvGSmfql0OIVK858JVz1arhbdHFNS57vuKKCRWnzsnCjL3/VSomCaWLaZvC8a0+0c/NVNyNJEuPdd7Gz53GiI6NoR57hycNPFhTzPX7ocd707Yt5Q3YRcxetIaldRqM1zLCcZl6ZbsY5KycmZlUhUd8CDbJgB8KxaROSJBFDY8vH3k7d3POYkfSK/1xXSGsGB0M+/LPFv3e8H9Zvh4E+GBqAvkMwPIo1NI4RixR2M37qKXh0U/nzE9HhLZ9CV3TSZpq5b3k/q558BrepEdpnQp0M9VH0jgUsNEYZOnMFrm2LtGHfPgFsWlqEll2uscI4Ogo/+hF85zuwbVv+70uWwJw5WIoEFihlEqqS8BK9dGqEH2+4mS19WzjSt4HI6HN0Z1MkngPdhlcsvoLTjVcDsLxtOefNOY+VbStZNWMVq9pXsWrGKhzX4bHuxyqvWk54CXc0himL66Yg6YhGIa1A1kCq95gC0wMFWuEx8eVd4aTR/zks9wjC8SwlvYSogClwvToCy8onwuFmopPsUwAiwWqKNTGcGaY3Pcw8CO4dv5txuR4FACgKEa9ZmWxaRCLxfJJfJnz5kOVY+QQuYAq8jWQNI5dDMUU38kmDAvDqlELbF/Uq0F3IIf6VRFiyWC0qyYfKMEF+BF2DXTffuK1G+NfLivYVXLboMj57yWe5bcdtfOupb/HYocdoi7cVAILf7vktazvX0hpvLe1R4EcF+ZDvTjppUBDer2uXgAJFFrVJ+T4DeaYAYNxfWKoWBaDAkw/ZpfKhqBoloSdIGSmGs8O0J9pLdnWyxYsOCqbjhY3hlEHzvHyiFFUVMoZNTM/fSBO5aflQrWirizCYKvv4PqYYzZg0TtcUHHMoiGZHw5bFQHqgNiiQVa/JmFM6CWb74Ml3wdF7oTcL/aA2QFpvx517DYm510D6sDfhEKxQW7aFjQJIRILJtyghLSMnUFXRlMl0zGDCFA3qxCRYF21ibedZrF25ho/HZ2HYRsFiyYYjG8i6FjsGd/JYaiePjN7KUg3W1TfRse9xrr/wC6yesVpsbNtkrAyuJJGM1FUuqPOSp5grxjthTDADDxRIkpCDJMpIMd71rsLfx3bD2A62jRzhoDqTM8NJ6z9/BrbcDSMTcMAUkh1FhtFD4n/XCZJceWgYbTwF4ynoyls7KjzIgojO0FkrsU1DTGg33QR33OEdfjlfL9HcLP6/7bZ8snf33fBXfyWAAUA8DtdfD9deC5kM1NcH56T4WJm2ya7BXULy07uFRc2LuGH1WwFwbJu/uf092IrALy+LQTMSsxOzmN84n2WtywKJUUyL8cgNj5QcSl8yVXalHiDlJS+JRPmV4GjUYwqMYIVZ80CBqSkFTar895erKajEFNiOjSOLpl+SJIHiJf52VhTG+l2+4/FCYBbIhybHsnbWdTKcGeZwqp95Mp4EziRnjCEDula5gDMazb8WUSNVQYEiK2iKkAdlrWwhKHC8hFRSsXITKHjHp1YBpySLVX7H8jrsVgYFmg8KyuW+fqJbazW/AiioxhSEk3PLsSYFCnz9vB5qMvaqU16FJmu858z3sLw9byAzkh3hNT97DbZrc+UpV/K6U19HUk+W9j8IQEGRfMiTVE4eFMhezZgtnrPefkuOQRFT4IOYrtEuGqINzG+cX/kzlCgkF4IxDFoDjusExyRSxIA1x5pJGSmGMkPToGA6Tr6YyFkkI/nT3tkY4/BIhsXt+dWonOUQOc52mycyLNvh3h19XLHi2Dta246LPAWhfq2Oj1ONtGER12s/jKejUjjUR+oZsoYZSA8wr1qRMYAkisok10FzTBh5DhpXite0Ruh/GJwsxNth9nr2dSxn68qzWd1xGonGeZA56tHTdrCKaEg2SCqaoqH4l0fxBBt0NM7r3zUvmTLtECgIT4BF0gG9qEPxTetu4jUt69l/961sSu1htHE/0shzDGWHeXz3Xbz23E8F2z64/372bP8/ErEGZpdZNQzCS4ai5EHBMUV8NoztQDIGkZXWwrGfswoWp4U+d5ciJF9nnQX2Bi/xyxcbP/mtT6APj7FSnUl7VoG998HQKFitHDwizCps2xQTmqoKwJJKCcbAlzyBSFDDEpJvfhPWrBGA5MYb4U1vEuzC/v3w3HMQj2O7AjC4uHzpkS8FIGD7wPZgxRTg5Qtezg1n3ACyTDKS5K3L30hLyxxWt63gPHWEOW4T2t4k+Il3lUJjyJ/n8GcUREivX3YlOBoFZCHx8hkxQ2znRIQsq7hr9FRqCgRToOXPqd80znUFSvcjLB1ynTwgngRTAEJGtbVvK0PZEYwY6BLgGBjGOFGqMAWAHo0HBaS6olcFBSDYAtM2yVgZ6iJ1+e3921XWsLJpIoCiR2uzUN57cKzSuoJQTQGOE3QNT1NGHVGrozF4wMN7GMmTBwXh2h3LsYhQG6z510s4AY6okaDAuDXeGvz90NghVrSvYFPPJm7feTu377ydhJbgovkXEVWjrJ+zXsynFeRDPiiwJ1tTAOKZadsFx6sUFBTWFHQkO5jfOJ8DIwfY0rsFwzYCa9qy0bgi+NHwpEOSJJU8n5tjzXSPdjOYHpz8+F/EmBQo8HX9k4mrr776mAczHS9MhBPazsYoh4YLQUHxNid73Lezn01dw88LFJwMSfmf0jE/6cK1qY/U46ZHGRo6LJbbZLmyD7xjIg08zqreh2mbeA5iHXD1Ps96UIeVfs+VM2DPBA5DIEl5ZxJZEYmCa4ElJi1DEplDTI2VrEIFIStiJSsEClSvMM2wjfKr0jWKDCVJYn7LIuYvuJiLE1fxoUsuYffu/+HJPb9iYzrHmpl5W+b/2/K/7N1xG4YC92V/ypqZa1g/Zz3r565n/Zz1eYmQDwpc8f+kdLblQo1BpBnLsYiag4VJq+UltX4hLoj6j4wGrlEACsymesymepQ550G0Afx+UZ1XsveZ22h4fDOO5SUTv/qV+D+Xy9dJPP00bN8u5B6Ok0/mVq2CN74RVq8GSWIsN8Zz3Y9y6MnfMbRtA9l5s1j+smsAkTD/66P/ykB6IPgKST3JyvaVrGpfle+/oOuQzfK9V34nf/0d/QN0dwugqUXEGGqAAv9Yua5bXo88PhWmwNNx5wxkWcbRNUwnv89yTEHxawVh57BcHxR475EkAQzsLKihxLZckXGxa1WViGkxGqONjGRHGM5NMCOaxLYy2JaQrkX0KhblXrFxykjVZAr8zxrLjeXrCvzEXWmCqAyJeVhZYRGsRiYp95Q0IFMKCsI1BbaN6t3zWakMKJhMTUFQT6CWLEaUc5cKRxgU1ArXdQNQUC4BLl4VX9m+ko3v2sjWvq38+Nkf8+Nnf8yR8SPcuftO7tx9J99+1bd5z9r31GYK3CnMj5IK5Aqemb4MLmBGip7RkiSxasYqdEVn1+Audg7sJGflWNm+subcHBQZ++5oRccEBGPiuE51u9OTICYFCl7zmtdMameSJGEfb1u46Tih0dkY48n9fzqV8eXiwECKWc9Tj582bOL6NHH2JxuuTUJPIMsadmqCtKkSb2wtXMmz0nDkbuj6ORy+nZidJX/VuJDpgbinre94uSiczcWACSLeOl7gTBIk6nmmIIeYgKJqNJT0l5kAZD0/gUsSmkf1h+VDhVZ9k0gI/O/pFRLPq+tguPkU2mcvCvYJsH72ucTbn2TnxEFMZ5wnDj/BE4ef4CuPi6Ll3g/3islcURg3JojYMgbPgykAiM/GcixixmBhEuG7d2h1YHqJtqaB4TkZOWZJ0hFVo6HEUgFZQdHENrZdlHRFIsKKdeZMsRrb2Cj+vmULnHaa+PkLX+DzD32ex3/2qQLXn7WHoWMCht1ZfOKC1wIicXrf2e9DkZRA+z+vcV7pJO+BghIHolQWbBca5sLwcE1QoMhKsModTuCDSIlz4sYTWI4AbSU1BX6hsZ8AZbMokoKtawUJ4NSZAkMwBbJWeI6UmLi25ZATVLkiY0mbkoXazLqZjGRHGMiNMSOaJGuOIbumkPyolR2F0DRm1c9iMD1IU7RpUkwBhGxJfVAg6dAqjABcr7hei1b53HBUSHYL5EOWheZ1Xc/iUBKTkQ9VkA5BdaYg/PfJgIIwc1VpVbyc286K9hV88dIv8r6z38f3N3+fR7sf5bFDj/HqpaK2BllnY89GelKDnNdwepBM5+VDU4gyz8ySY1BUU+DH0tal6IrOc33PcWDkAIZtcMbMM6om8+WKjP1I6kl0RcewDUayI8H3OlljUlmQczyt3qajZsiShGU7qMqJR5RRTcGwJ39+JcBxXGT55FjVPjScprMx9rz1/amcRSIyLd/5kw3XQUamLtrIxITJWC5NPFLkC/30R2D3N4Nfbb2VQ3VnMDTrGs5Y8c7CJCWwJPUaOXkTR75XQWi1yWcKvMk8psXAnSjcLhyyFgIFSpDIheVDhUzBJBICP9nxFmV0WRI1FpJCX6qPuQ3CS/8Np76OhcsOkYuo/L9Xvppnep/hka5HeKT7ETJWJq95TSb56uNf4cmxnfQ3LGNF+wpUSeXcOeeWaoFrhB2ZgQOodhrNyYIPxXymQEnk3Xp0HTL5YuziwsioGgXLs5r1pAuq6oECq0qSHXYD6uoS3ZMXCnvU3+z6DY8fejx4eVbdLC5un8Wy2bNIXvDy/AqjrPCPL/tHakbZXgVJSGfBdoSkbRKgAESSbjs2hm0Q1+KFL3o9AKx4FLLi51KmQAmYAskW9qSKrOBE9EByBNVrCirKh2wLR4oWniM/IVVDc0qYKfATykk4D4VjZnIm2/u3M5xLYTom2ZwABUISVGVfqkpjtFHoxWW5ptynxJbUv6+8+gjhPGSBJKFEJ3kfVOpVUAAKciiygitLZOwyx3syhcZB/4cTCwr8glpd0UtWxZuiQq5ZbVVckiROm3Ealyy4hLWda0PyM41f7fgVm3uf5XUP3cyrlryKt6x+C2dFxTmYdE0BhBZtSq/xSjUF4VjQtABd0dl8dDNHxo9gOiZndZ5Vsd6iXI+CcDTHmjk6cZShzNCfByiYjhc2oppC1nJIvgCgAMr3KqgUEU0hZzkFhckvZvxhWy9/tW4ud23pEV7/x1ism8rZJCJTvx3CxXrT8SKG94BvjDYzkDuC0/cEpP4HlnwG2s4V28x5HRy5E+a+AZrWMGJk2JfJEmlYWbpqGViSioQj4j0qMyW9Cmyx+gvk3BBTYHuJa7nVpbCWWlKDpKoiUzAZPXERKMAxaIw2ctBROTpxNAAFmVxK1FIoEVa0r2DVjFW8afWbxPitPLB2Gxo4OHoQNZvhmcOb2HR0Ez9+9sdossaamWu4YtEVfPriT+c//+hRkaQuWlQyNMN1yamNxKwR1OxRiHh1Hj5TQGgi1bQCv/LwSqSmeJ1NA/cacW4UDxQ4Ybeb4vBBQWur6MewbZtYwW5v52/O+huuX3V94PrTLCfgj38Ey8JdexF3HLlffNxkaf9KvQpSHihobhYOSa4rxlWlWFVXdLJWtiCBD/ZtiuMgQIEYX8EYi+RDsmmCriOrOq6qFBQQ+/svZ0lqO3bpc87OVWYKAORQ8noMjcuKI6EnqI/UY6cVRrIjmOoYsmMS0SLVC5bDx3YSFuUltqQ+U+CBAtM2kSwLVVKQylkdl4sKWvkCUGBmUWUVV5HJeS5kBcd7KvKhMiCpmvsQHBtTEPbj9yOpJ4Ni7bHcWFVLUkVSCq4dF5WzO89mPDeOk9rPbTtu47Ydt3FJfZIL2peweGGMM06pOTwRYVtSL2rVFBTHrPpZ6IrOU0eeoj/VT/dYd8Xi43I9CsLREm8JQMHJHscEClKpFA888ABdXV0YRasd73//+4/LwF7KEdMUsqZdUBB8skRUU8iY9kkBCizbwXEhoirMbU7QNZhm1ewKGvIakTKsmv0biiMZUZnITdu3nhRhTkD/I3QMPsnMZx5G7TGhFTi4PA8KZlyUrxsY3YHT+yi4Tqk1HuSpfk0krLpXOVmeKRCJfE7yuqaqMbAqr0IVaKmLmALXo8rLJwRVVglLQIFJY7QJNyPRn+oPrAZTGQFWInq8JMkNT2hSLMbNr/8hd933K1Ysk3k4s509Q3voS/XxxOEnRBGmH47D9/7rb5gV72Du1W/i1EXrCvZtOiZZrZk6ZwIyh6H+1EAehCSB4913mpav6fC+g67kV8fzjcsKm18pqjh+jusI+VS55M+fp045RRQbd3XBxo1wwQUBKMK2RbK+5wmRBMoyTjR/TMpeJ+WiyFVGvDkBmSxgQ329GKNti3HVAAVQptg4lRIStaiO5a1+l8iLgkJjExwL2TAEKIjlrTeDw1PFktTfNti/V9BqORaOqhZ+rs8UKA4gie8ZTp6n0LisODrrOjk0spWhzBCa3uYxBcnqTMFUQUEl+VARU6AoSm07Uj+CBLVKobHHFDiKhuM6mMXSueB547JncBc7Uzu5wrkCjdD3e4HkQ8XOQ+GQJImmaBN9qT6GMkNlQUElNy9JUbn61Ndw9dKreac8gx9t/QW3bLmFrHGEjT2beDRl8KZzP15zfGJnz48p8KMt0caipkXsGtzFSHak4nbV5EMgmIKoGi1xJjoZY8pZ59NPP82VV15JOp0mlUrR3NzMwMAA8Xic9vb2aVBwHCKqyWSMF642YyoL3T5gORnivp39XLS0DYB5LXEe3zd4zKAgbVhTrkuYUR+ldyz3ooGCaZYCYQn35Lvh8B1gZ8QUaUBObYAlryay6Ib8tkWSHNtxkF27/ETpFjIFuqQALo7rYNiG9ztitcn2CgS994iJwSn9TD/CCZGs5otpQ0xBQQI6mW6mYVmEbYFjEddiRG2dlG3Qn+6nI9lByvPgjkerdOz0Qm1upTMykzfNPZvzW1/N4ubFRNUoj3Q/UjDZ9/fs5bZt/7+9946Xq67z/1+nzZl257bktuSmQiAhISSAdAGpAqLiiiIiurbVtVEe7PpdV0BcRP1Zce2KorKoK+yyikpHJBAFAoSQkEJCEnLTbps79bTP749T5kw/0++9834+HnnAnTlz5jPnc8r79Xm3ewAAz+/9LmL9XTh1+FQzgXn4NCzpXoK01AVBOwBoSUAZy7gnhSCgWr/LNuBcngLJZdTlNi6zjUFB9IEBma7GhYw/d3jSqlVm5Z6xMeBvfwNOP930dLzyipkLAJgJwitX2lNrHuJaPAW6aHoJeAUI+K0wqaS5TaHSrha51YEcbFEQ8tvRa/nnse0p0A1AVSEoaQBhcFbYi6qlgOgrQGDIMZjchp7teTCYkSMKLA8FGFjOaq/jKRB0AFYVqBwPg/l+5cbRYMcgdvMioqkoAqlx8EyDT/SV9hS4K015EAW22I0rcWiGBjFHbKuGCl7VzBV3r6KgWFdjd6KxmgYPHrx1v0lpqRxRkPkdr45txaQ2idHkKOa5QySN5uYUFDNwu/xdOBg/WDQPSS/WGwZw8q1WzjkKXznvK/jSOV/CU89+CX/c/BsEBt/kbLY/th+X//ZyXLnqSlx+zOXoDuRUmSvgWbG/t1xOQS72OVGqf0GhHgVuuvxdOG/peSW/Z7pQsSi45ppr8Ja3vAXf+9730NXVhaeffhqSJOG9730vPv3pTzdijG1HQBKQ1upveOtGYSMyN4ehVDhRwPIUTAd2HY7jvBVmtZTekA+jsfIxusWoJnyoPyLjYDSVV7mpGYg8D81gkIQ2FwVSJ3BoHaAnAbkPmHcJXhXn4/Cojr4jzsei7tWFP8cLMKAX7lMAuMKHrOZHBnOSxVJaCj73apPlKUhZqXBmTkEFngI+4ymwXetZ12kl4UMAoKac/+3vmIdXJ3biQOyAKQosT0FALn/OMisxtyOuAnNkxNU4ls9djsXdi7N/ztg43rXicmw+vBn7jG3Ym5rA/dvux/3b7gcAXLnqSrzrmHfBkPuhMx1jh5/H3E4znt9MMnYZ7IAr3CI7fMhexc2EoFg5BYIEheMyXY0Lrbzb3yFJpoA68USze3E8Djz0UMbDEggAy5ebzdw4Doa1AshzvHcBXkgUJDXTQA/4zHPVLQpK7aqYpyAWA6ADQRmadcPOCw0RBMBnGW5pWxQAQsASIfHXAC4BJPY6JRVzjUaRF6HoSraxaBlAdjfjbFFgGUWdfqArDCxcmD0mzTKsCsS9lyPsCyMod4El9yAaH4HImGmY1tFT4BN88It+pLQUoukoegp4CjivjctsvCQaW6FgvNVsLaWlEJFdVZU4DuAEpLUEdGsu8oxup/pQ/rH1Un0IqDynoBC2x9Edjpg1zNwqQG7sfCtrvAIvYG3/KviMNKY61zib/dfG/8ITu5/AE7ufwKf+9ClcsuwSXHXsVbjoyIvMcRVYSHE3LwPgyVMAwJmHKWWq6EKcu/rQTKdiUfD888/jBz/4AQRBgCAISKfTWLJkCb7yla/g6quvxmWXXdaIcbYVsiQgqdQ/ubtYzH1/xI8DU2lPK+V+iZ8WngI7wdim1hXzahKN+yJ+bHx9sqbvBczE7UpHL4s80poBqUl5J9MWjgdO/K65Ai0EgMgyBEZfAEZfwqgew6KinxPMAgqFwocYyzxMXCs/AUGGoitIqklEsnIKOLNCjFWSNKv6kJecAteD2jb+ClYf0pPFY+Z5PlMj3g5x4iX0dwzg1Ymd2B/bj2PZsRlPgQdRYFfrCcVVADLiSuGypL0pDu9dbYbg3NzTjecX+53k5Sf3PIk1A+bDnAXnYcfYi/jUA9eDDwzh3IFlGBp8I9YEz8CRzABvG0lZ4UOZY5UJH8pebRZ5EYrAZ0RBLlaCLYCMIebzmcLgySdNg0+SzNCixYuzvC62AVNRGcFC4UPxuGkwB2UzwdoOqcnyJqTMVWWXSHV7kbIYGzPPsYAfqnWuFVwFDgTN8yKtQLANz4AVkpU6CATCMLQYAqn9iPuH8oRFQVFgGbeqVVkrO9HYuidLhumByUre18zvBIBAf/5YPTA3PA9jExsh6OY57pNCha8x5weIhf+/BJ3+TqRiKUymJtEjW+O0ziszfEiFwMlViIISngJblFmLEAUNal5EUkuCY+bvnVJyVq5LeGEa4ikoEj9vG8bF+msUCx8yX8wXUILldVVdq5XvXvlu6EzHL178BV488CLu2XwP7tl8D3oDvXjXMe/CjWvfgz6goj4FxQhKZqilbpiNH/MS/lE+0XgmUbFFIUmSY4D19/dj9+7dAIDOzk7n/4naCEgCUg3wFIzFFfSG8m9kQ11+7JtIOn+Xsq/90yR86KGXD+DcFfXrDqjoBnwVGtgdsoipVEWF0goSUzSEK+wgLU8TcTYtmH8p0Hm0s5oWsZrvjCNZ/DOcAJ0Z4Jie7ylwP7zFzPUS5Mz9JrVkTk6BZnYZFgSIvGg+dEp6CrLDh9wJovYqXNYD09dtPri0BJDch6LYK6G2p4D3oSfQA0mQoOgKxlPjjqcg6Or0WhRLFAQ0gFdUxJRYVidlh7FM8pyYSOKEoRPw6ZM/jd+88zfYe81eXHzkxQAATp6DXVP7zeZTyX14dNdjuP6xL+DNPzsPV/7uSnzyoeuwbs+6LE+B0y0XBcKHrO1EXgTjOOiGkTH+3djGOcdlG4aRCHDKKcAxxwDnnGMmSedUpykZ6lCMQp6CeNw0mG1RkLuNMml20B79W/auLFGQZSTu3Wv2XuAA9HVnPAWFVoFdeQWCan6XEAyZ56diNlPSDR2h9D7wRrqgpwDIMRYtUZa2ToXsnAK7gZmRvzKeOmC+LoUBqURvgRL0R4YBAJw1Lz6pjLit0FMAZFaGo+lodvUhq18Er2gQKwkfKpdozBiQMnsuiD7T4HSqH7nhBCTUhPPb80T6NMgpcL9u38tyKRs+BGTCN5nh9MHTwDmCYrBjENefej1e+KcX8MI/vYDrT7keg+FBjCZH8eMNP4ZsnxeG6hzLanIKAPNeHPaZ+ysUQsQYc35rMaE0k6jYU7BmzRo888wzWLZsGc4++2x8/vOfx+HDh/GLX/wCq1atasQY2w6/xONwrP4G33hCKZhMO78riEdfOYgTFwFpTS+5+hzwCZhIFGh730Q03YBuJRjXk0q9DfWK559MVF41yS+aVaAICycJl4PPCrJOCyXyLjgBBrPCh/I8BXbHVREQRNNQNAz4rdjgpJoEZLenwFwVYzyfKdfpeArKhw8BmSoz9gM321MgAeEjgOgW819gsIgHwnpNyxjNPMejL9SH16Ov47WJ18xa/hyHgOyhxrooQgsEIAsyfFMJpHxS/kpZLGYattYxQiqVVVGH4zgY1kqfT5Rx/qoP4LR5x+OVw69g8+HN4A7tw97DzyCmxrFx3zq809CcGOxn9z6FXz773wj7wk4+AwBXsqqVU8ALYAIPo5inwB06lEtXV6Z/QQFKrmoWwzYW3Z6CWMw01kK+wqJgcpN5ztj5FjlCyDGw0mmz0zIALJ0HBP1QjRKeAlcFItHlKfBpI9ANFRD8UPkAOGagWxnJu1YKGovWWFQUCB/i+EwDMz2ZvWptC9rAUPFjV4aOwBwnvAccB59URtxWmFMAAJ2ymZc2mZ7M/ryuO4nGUkAsmSCeRbFEY7tEqmE4okAoKQpEJNUkOGvRI8tTYLh6URToZsyKhZhZ1DOnQBZLewpKet9yvSqGBt66rzFOhG7o4HPsk2P7j8VXz/8qbjv3Njy882FsObwFncFeILUbYBrO/vnZEHkRpw+fjmP7j604pwAw8wqi6SimlCn0I9vLldbTznOmLcOHbr31VkxZnRRvueUWXH311fjYxz6GI444AnfccUfdB9iOBHyNWY0fiysY7s53fUUCIqIp8yKcSmnoKLFqPR08BY++cghvOjrfS+ATzdVzv9T6ykiVYIZ1VVaNQ5Z4pMlTkME2wjUDgvWwMSQxO0HSDSfAYAY4ZuQbU/YDyX5ACQJgGAhYq1gpLQXYK+1Wn4Kx1BhYl99cUWKsfPMyZxzmd0uCZIqCQp4CAAgvBuI7TW9BfDcQXpS/X8dTkAkfAoD+UD9ej76O16deR9Bg8IsyeNGbQaOGQuA4DpGEjlSvuTqZJQpsL0F3N5BImHHyU1Nm2U2LrMZYwX6EpnZg7eBarB1ciyuH3gzt2Bex6/nHsS54GCcOnQjAPP7r9/wV39zwv85+FnUtwukLTse7erqxsvdILOh7I3hYngKey1QfysU2vL0acS5Kxj8Xo5CnwBYFQcmslOXrz2yT3A+kzVV7MMM0pkXzGOfVzd+40RQbnZ3AQj+gp4rnFABZDcwExQpRCYbhm5iExmmAfy7SQjcY/oKQNgmkDgP+Oc7Hi3kKGFjhnALA/J16KrNyDeSEDlUvCmzv176pffAJErgCq+JZVOEp6PSbomAqPQWD58DbYXm6DkVLg9Ms72Kt4UP2+NJpIGmKAskS6wVFAW+JAsG896iGirSWNo1w3XXN56zA23PHcVxRj1c9cwqckDer70ruvaxgMQUbl5cQAMBU8ODNBRqOK34/h7k4cP7S83H+0vPNawrAwdg+/O31v8FgBv66+6+QeAkXLL0AH177j7goaP1uD9d2h694srG9kFOom/FMpGJRcMIJJzj/P3fuXNx///11HRDRuGTesbiC7lD+BcVxnJNcbIqC4g/P6ZBo7E4wdjPcHcTe8QSO6PMQGlEnKunxUIyJhIrBrspiEWVRQEolT4GDvUqW1sBzPJjPTCgt2AkWyIiCQonG9sObc4kCVUWAMx9YZviQVe3C0KCkFRyOHwbjF2Bx12KXIIAHT4ElCvjsKjNcbpYJLwIdRwITLwFTW4HgcN7DPyMK0uad3XrA9oX6rGucgTMMM2G3TBMnG9WqMd+R0HEQZnLj3NDczAa2KOjpMb+/gCjIqoEvRazk4ilADAC8CFFnOKL3CByx8m1mYrdu/vaTB9fi48I8PLnnSafb8K6JXZiwnBzfm38x5vs6IfIiJpQpM8+jlKfAqxHnoipPgTungDHzX9LKeQlKlqfADINBOg1EN2d/Xos7osBeeUxpKWBkxPzHccBxxwGxp8yvKZlTEHAamNnhQ2IgBPlwFIbAA/JcqExCUp6LEIsBky8B8pmOp6KYp0AzNOg5566DEAAwkTFUASC13xU6VMP9mRcxJ9SHA/EDVofiMiuzVYiCoBR0au3HlBgigmDF/WvQlBQExiAKFSQaO9WHNPMYuM8lUbREgdV8zvIUFAq9McAhqSXB8xlDe0qZMkWBZoUSifnhVOVCh9zv1SOnQOIl536j6EpenH3J8KHcSk3Wf3nrXuZlfOZ+zN/TF+jBa595DXdtvAvff+b72DmxE7/f9ns8sP33+IfuDlx97NU4f94lZXfnVCDKzeNA+R4FM43pVwifgF8SkC5i8O2bSGLj65O44JiBiver6kbZkJuplFrSU9BqUZCbYOxmYW8QWw9MNVUU1IPJpIqjBysbs1/iG1KhasZiG+KK+dDg/fm12LNwPAV6/oqVE57iEgWA4ylIqtk5BfsmdoMxhki4B73B3kzXVsBDorG5H1u4FAwfsgktBGKvWt6CnUDHEdnvO/HPqSxRIAkSegO9OJw4DOiGGeLk0UBSrXKZ4aQZU51X8cQtCgwDOHjQFAUuHE+BLc4C8wB1CyBaceX2irptZFmGwdrBNVh7/IUALyGajuLpvU/j6dceh/L67zGWHMf8TrMKksiLuGfb/+Lw69uQmvg1jl55llkOdcFpGOoYKh0+VIaqcgrc36OqptHHGOALATIzDR17d9E9gOoz50qKAOnDVqdnU3jZBpWRSkHbvsF8YB95pJkPMWWVybTO/VI5BVw8ZXY0BiDIAkQ9AY3zm6Igfggx/3z0KbtMsRbfZXqmUNxToBs6DE6CJEj5q6N2srHbU5CoPXTI+Um+CNYOrjWFc6lypEBV4UOAmVcwmhjFZGoSEVE0RYGuQ03FIQAQJb9nYZ21CGCo2ULGPldsT4GvuKcgpZthQCLHISKY105MiWFOcI7pfQIAMT8s0Bbl9RAFBjMKNrpzw3EcfIIPaS1dWBR4Ch+y7gmWKOAqFQUu78z8yHzccNoNWDuwFpsObcLW0a3445bfIZo+gIAv7AjgQ/FDSKgJLOxamLc7t6cgNyS1XDnSmYYnUbB27Vo8/PDD6O7uxpo1a0q6SJ577rm6Da5dMSvLFDb4Xt4Xran0ZjHsKZ1KaeiPFL/RymJrw1Ye3nwQ737DcMH3Bjv9eGzroSaPqPZ+ARNJpeKcAlkUMJ6o/3kwY7E9BbYosCqs5HWCtbHiUzlWwlOQIwpka/UppaXAwIMDoBlp7J98HTyARb12N19X5aGC+QyuueazV1uLhg/Z+4scBYxtAKa2myKBL7ASquWIGgAD4QEcThy2PAUhzwaNFjC9CgEmQkimEQu5REE6bSbQAmb4kG3cR6NZ+7Ar5zhGRMdS87j4rYWNXKOdF0yxxHRzLngJETlihgYsOBk4cDIY73OOrcAJGFcmoTMDL468gD/HX8C31n8LgBlydEXwJNw6cGVVoqAqTwHPm8aoppnHxD5GkU5ATJuVsngVMHRgfAeA5UBkmWlEpw9nVn1hihFJkBDYvgMKG4LY02eKAsacc95TTkEiBQ4GIEnwGeb+07wfEHxQDRWME6GFLZEZfcUUboKvpKfA4KXCIUt2SI/tKTBUIG3dl+sgCsD7wJXo3ptFFZ4CwMwrGE2M5iUb6ynzNwn+/DDconCceS0aanFRYO1X8ocBKAWrD8UsodAhBRAQzP93wll021OQLwrsuSuWTwB4FwWOJ5PjSu7PFgVpLQ3kTJG38CE70dgKfbLuHTrzaHsU6VOwpHsJ/nHNP+Jb596CF178NlYNZiJfvv/M9/H5xz6PNy58I6469iq8c8U7nVAyuwKRwQwk1ARCvsxxnk3lSAGPouCtb30rZKuE2lvf+tZZETc1neE4DsWiUvaOJ8DzjTn+jDFMpdSSdfd5vvjYmgHHFU8wFgUehtHc0XUFJUwkVHQXqOrkFd1gFZcWlUWqPpSF/bBQsz0FeaUcbTgBBozCicaOKLDm1DIK7ERjgxlQmA4ZwMGpERiKgoAkY25kMHssxQxJt9Gb4ykoWJLUTWAeIG03V3SntgOdy137tRON7fjizDnZH+7HSwdfAsdYRZ4C8DzQ1QW/GocUjSEWcYkC20sQiZjGTYfl7SriKXBEAcdnezlyPQWAVa9ct1YMXQaYJZrcseQiL+Izp14H48B+jB+9EA8qW7Bu7zq8eOBF7JrYhb2JucAAHAPsI//3EQxHhnHagtNw0ryTsh7wuVSVU2D/Fk0zBU/MOmahECBKlihQgOQIoCZMQy60EEjsNbfTsr0xHeMJSPtHoc6dC6xebSWnZq59x1NQKqcAAAcG+P2Q1AkAQEIw7/O2cGaBYUCImpWQopuB7tWOsZh1HRkKVEODwcmFvROOKLAM96yqQ3Xw4gqynXZS3lPgTub1WJIUyOQVZCUbaxo0KyFYqkQUABlRkJtsbIsCK9/DJ3cAGM00SXStxsetRPGQKMNvJRM7njutvCioh6fAfS2XsgNlQcYUpgomG5euPlQkfMgyuCsNHzJDtpiTjwCYv1VkGo4fPN4MYbR4bfI1cODwl9f+gr+89hd88o+fxKVHXYqrjr0KFyy9AB1yByZTk5hSpgqKgrbyFNx4443O/990002NGgvhkUZIgq6gD+MJFdEyicZENmaPh1RNoqAa/BJVH8rClVMAZFbyinsKzD4FHGMQi1YfsleuTaOKNxhkUTZXwHQNEgzsi+4BDB1D4SFwtvHgpdSdbfTmxGXbVUKKigKOAyLLzdKVsZ1mmIdthLE0EN0GxLuArrlZK5JBKYilPUvB+6cQSHvPKQAA1tkJ//gopOgYprQUdMNKtHSHDgGAlX8ARTG9CNZCkj0HRVcWC4X3WJ1N85Izc3oUAHaiMY+IHMGZyy7F2xZ+EoBZUnL93vXo2LoL0Mz9jyXH8KPnfuR8VuAE/Nc7/gvvPOadBYdWlafA/VvcnoJwGBAVAIcAFs3E2UeWm4a7HQ/u8hRAVdGzbS+mACSHB9DZbeWyuFZMS3oKfD5X7okByDJEbRwAkBLCYIxlGluJPiCyEjj0pJnMHlqUbywyAzBU6EyDwYcLh5A44UOWOK1j6BCA7PA7L6uzdjJvheFDADCZmgQTIuAA6EraEbCCv3xPnyyKJRvn3DN40Z/dJNF1fG1PQUj0I8Cb3+/EuJfIKbDntx6ioFw5UptSZUkr6lNQqygAAKaDQch4KHgh00Xdtd2PL/0xbjzzRvxq46/wixd/gZcPvYzfbPoNfrPpN1javRS//odfm6IgPYWBcCZ8ezb1KACq6FOwZMkSjI6O5r0+MTGBJUuW1GVQRGkasRY+z+pVkFJ1BGZY9Z5W0h/x40C0cD3mRmI3LyNs7JwC6yEStERBGU8BAOQ1hS6UaAwAuu501U3qCkYTo1C1JGSIZi6B84Av0bjMxjZmrIdg7oprSSM00A/IPaYhEd1qGs/jLwCTzwPKuLkqGlpodnh2sWLuChzdu8xc4avAQEJXlxnCEjPPc2d1MlcUCIK5Gg443gLN0JyHccFVZcNwusVmewpyqpA42yvZ78MyaHjTte9ONI7IEZy39Dyc3H+8s3+BE3D7m2/Hu1e+G8ORYehMx/K5y1GMqnIK3L9FUXI8BbbhfzCzei72Wj/EOnZaInMO7d0LWWPQgjJiS+Zn9u/yRmnW/xdOqOcA2TRWOBhgggaBaWAcD0UIQzO0bNEm9wBBy3hP7HH26RhjdjlSwwDjxDKiIFX/0CEgp8+HB1FgX5cVnPNhXxg8x0MzNKSsRQJVSYFXNXAcB1GuUBTkJtDa2OLR9vxIcqYMbU4IUcyqKhaW/AgImSZnqprM9O4oFT5UpGoPkBEFBjOc67UQ5cqR2pQqS1q6o3FO+JCTaCxnfbYsvJAJ3WRalpgo1UdmuHMY/3r6v+Klj72EZz78DD590qfRF+rD6QtOd7xH0XQU3/v797B70uzL1faJxrt27YJeoMJDOp3G3r176zIoojApVYdPFKAVKrtXI/O6gnh+zwSA+tXfbwU8Z4bjCBWGWFX7i/s6ZPx911j5DesMNS/LwX5Y2KLAHwCQKuEp4M2OxsjkfGb2VTjRGLqOgC+AidQEkrqKqdh+cMzAYGCuacTb23nxFESWmyUaZdMgzF1FL7syHTkaOLQOSOwGEntMI5LnzEZnXScC3ccW/px9767AUwBrdbojZeCgYSCmxNAphoBJq5u3q9IQOjrMlfFoFJgzxzn+PMcXXqks1lisQGdTc/x2D4bMA1jgBTDe7CpdsnmZJKHT34lPvOET+MQbPgEA2DO5B/Mi84r+9JrCh+zvtkWB4ymA9XsFILjAFA4+nykU7TATLW6G2sTjZnx2d49jnALIOsfKemICQWDcCh/iE+DBQ5M6Ac6szuV4CtyJ4Il9QOoghKA5945RZXlqNOuOWTinwJobZpgeB2aYv6UeoUNA5aJAyrmOvXwFxzvhIjEjjQAARUmAVzXzPJYrNACLnc+OdywjCmRBBtLZyca6oSOupREBEBb9ELg4fKIPGtMQSx5AN2CdP/nXWCXhQ/b2xTwB5cqR2tiioVBuhKfwIaab5w1zVR/SK/AUAKYXgKmAoUFDxgPLc3zZbsYcx+H4oeNx/NDx+Op5X0U0HXW++7mR5/Dx+z8O7n4OZy46E8cPHo8Th06cNZ4Cz6Lgvvvuc/7/z3/+Mzo7O52/dV3Hww8/jMWLF9d3dEQW2w/GcERfGK/sj5bfuEL6OmQcmipQG3mG0R/xY380hXlFKhQVo1rvS0gWkVSab5zL1LwsGyd8yCq76A8BSJWoPsQ59d2LegoKiQLLU7A7+jr8ahIiL6HPMuwzoqBEjwIb/1zzn0XuKl5ZYS73Av4+q/Y7M/+e0216CoQS575tNFciCoJBwOeDX/BBjCUQV+PAxIQZqxsImP9sOjqA/fsdT0GewZmLu4eA+zcX9RQUDx8CAF1V8kVeiepDw52FixY4X1dr+FA8nvmNoRDAuYzJjgFACGf3MxBDgDKREQXJJCRegi7nVKSxzncGHpp1TIoafc78GOD4OIAADJ95zuZ5CgBAnmN6ubQ4JKY42wFwRJnCOIArYhxyvDk/etqskgXUz0sAZM4NXswvy1uI7m5TwEYq66LcKXdaoiCJuRCgWZ4Cka+gcZkz5hKeAkPP1LYW/fALOb0pYIYJMc5MOpes66TD14Hx9DgSyYOmKCjgJQC8VR+yexjohl5SFJQrR2pjf76Qp6DkNcWJVkdslknMBiAIfkDXKxMFrjwO517PV7BwYyEJEnqDvUioZj5JNB3FWQvPwmOvPYbHdpn/fIIPbz3qrXj/ce/H+UvPL3mspzueR/62t70NgHnyXH311VnvSZKERYsW4Wtf+1pdB0dk88r+KZy7or8qUZBSdfhKJLO2OoHYC7pRvsrPwt4QXhuNVywKZhoCzzU9qXp6Yxm7aQ0AByEYApKjRcOHGGMwwJnNr3LPqSKJxtB1ZzVoSknAD6Df3wPRfrhVklOQQ+5D2JMR2r3aTDaW55ohRQc3ARgvXKvfxn6vkvAhwEw2HvWbycZKDIha557bSwBkDC9LFOQlGedSzGDPDSNwxp/Ofh/mKr4jCjQ1XxTU0rys1vChcTN+H36/dX6IZg8CQwG6jgCmkma8u40jCizvQiIBn+CD7i8sCtwzXdQQseLfeWYAnCkKmDzXLLGpF/AU8CLg6wHSh+FTzfHnegpUS/AWFXtCwJwrO+k9MFh4u2pwQu88rtavXAkcfXRFicaAlWw8CUzpSQBhaGoanC0KKu15Uex8liTX/YIDJJ+TRJwlCtJTYODNRQlrlTvsC5uiIHEIkFBUFHipPgSY548tCorhNafAFg2FcgpKet84zrXCrzhdh82cgkTlngIAMDToyO67kelm7P26DogBCLyAZb3L8H/v+T+MJkbx8xd+jh899yPsje7Fb1/+LX778m/xpyv/hAuOuMD7OKcZnq8S29W+ePFi/P3vf8ecOXPKfIKoN1MpFZ0BqSrjvdYKOdOBWEpDpEwS9IKeIJ7fMw4sLblZFppumF0riZkJM6yVJQPQDLMhViAEJIsnGutMB+N4gBUIH8pNNHZ7CiQzJpxxPDiOQ39gjtWQSKgsfCiHXIPOkygQ/EDXStffmXEWxfYUVCEKAmIAUnTMFAVj1sM+VxTkVCDK6mZciEKVh4Di4RZOaFfGIOQ4DoLVoVnT0si7y9XQp6BqT4H9e+zyrCGXwTb3DPMc2bvRFAVZnoKcZGPbU+Dni4gCzhlfUeFiiQIRcUAWAcEPTvID+oQZPlQo/CjQD6QPQ1JyRYE5VgVFuhnbuDsN1zN0CACkTvPasj10XqhQEACZZOMpPQEgDDWdBK+qEHipClFgh8UUSDR2ksbNe4jtKXAb1NF0FIwTEJCCzvZhn3mupNKjgNQNCKVFQbnVa5EXkUa6pOHtNaeglKfAFtpFrynel/ESWMdLEP2oWBS4ypJqLEcUOPdo7+cFx3Ho8HVgIjWBqfQUFnYtxGdO/gyO6z8Ou6O7sW10Gx577TGcs+Qc5zO3r78dCTWBK4+9EvMj80vsffpQ8ZWyc+fORoyDaDCj8TR6Z7goiJZprAYAAV/lYTVxRUdYnnnuPtIxFk7okGom9PG8UzKwmKdANyxRAIDPldklwodsTwEDjznBOfAx0RQFQqZuvqdE4xyq8hTk4kUUVJNTAADd3fCLfkjROCZSUWDc+nxvjmEWsnogaBqQTJZtdFR0Fb+C8CEA4K3PG1qB+a6ho3HVOQX277HDQuzKTIB5rrjHkxs+BJieAqukqSRIMPwi0lo60xPFWi22wyJKGnxWzw4OOiBLgL8PklUZSDO0wiFech+ATRC0SYDxeeFDaQaAKyH23CFs9QwdAkxPy+AF3kKHasAWBSmYIVaaysArGiQ+UL0oKOgpsOPbLVEgFg8fCkoZT4HdUCuVGgPC3WbSegG8VB9yv+9FFNSSU5BVBagQ7gWBnOpDnvsUAFmegnxRUDqnoBgdsiUKlCkMYhApLQWO47CqbxU+8YZPZPUs0g0dX37yy3h96nV89uHP4sIjLsTv3/P76u7tTaQqS+jhhx/Gww8/jIMHDzoeBJuf/vSndRkYUV/G4yoGu2Z2Ikw0pSLir3y1rxwJRUPQ15qKS4pmQKzUQLNgFD1kYhvhadWM2ZZlx1gp6SkAD57nzaZO7n05ruV8URCUrPrkHIeBjiEgWSAcpwpPQcWJxoWoxFNQ6TnX1QVZlCEm0xDGJqAoAfj8oWxj195vKGR6CqJRKGJON+NcihnsZcOHskWBYO1fzxUFmpa5UFrhKbDJPU7ubYp5CpJ2Q6sgmKiDMQOqoZoGmXWO2QmUpSrLIOBaQfZJgDwXYtIsE6rqRTwFUhgQAxAUFT4tCoXrNg0eO3yIVeApqLcoABouCADTgAz7wtAFHgk1AU3xgdd0iHIV4UNcEc+XnVMAON5G26B2iwLHUyAGnPuT7SnQlQnoTIdQLnyo1DkCb6LA9l54zSmwq4/Z14/BDKfsclGh7b723TkFZcaWv5+Md0YzinkKKjuP3J2NgfweBe7wZp3puOmsm3DnC3fiid1PICAFpr0gAKoQBTfffDO+8IUv4IQTTsDg4OCMrlQzkxiNpZ3wn2qO+FhCwTFDpROt/JKAsfj07ZIbTWroaYC3I57WEarBU8BxgGGwqprKTSZVdAXrL3TaCqdxmfVfWS77gLM9BTzjs2q+w719EU/B6oHVEDgBgdhGYGocYDmVc1C5p0DgBadjJlClKLAN/VLVyarNKfD5wIfCkEUfgnv2I8UPwtczXNhdFYmYomBqCmqnR0+Bl/AhQ80IQD7HsyLaoiDn/mWLDp6v/DejDjkFNqECBptdwaaQp0BPA3Ez9IgPhiCLZndYp3a9HT5k56eWWvG0BInhM0u3Qp4DiTfLhCbtmH8UMBr9/RC0OGRtEorUDc3QINmeAvtnFptX+3dIHUVXsGcCETmCMUFAXI1DUwxwqgYhINTXUwBXKIsgwG/dS+xVdkU3OxwL4BGQZDBr7n2CD36eB890JLUkwnUIH3JvXwivngJJkMwmrIwhraXNholAVrnT4uFDrlAr28tRjShw5xQY5vXrCBFn4adyTwFgijSgdI8Cn+DDh9Z+CB9a+yHsHN9ZML9iOlKxJfT9738fP/vZz3DVVVc1YjxEEV7ZP4Xlg5VVT3AzmTTzEUoxryuA10bjJbdpJVMpFYvmlO8kyRiy3HjlSChaTaKgNyRjNK5gbkfldYonkwq6ysxLMUiPW9gPGlsU+P2OgVMsfEgzNMdTkCUEnHwCMXOAbYPfMqgXdC4w/05sNg1whmyD06huFUoSJOch03BPQRUGMrq74d/tR3p0Eununvx8AhtXXoESLlG6EvCQaOwWBXY+QX7VGUGUYKCAp6CGfAKgDtWHbLx6Cngz5h96Coha/YCCQfhFzhEFETmS8RRYq64lk0iDYbA1yxCTFTMeX/A5BqBdUcUWpVnIfeBju+DXopiCec1IRhoMDIrBAUKJ1Wf/gNlt299X+P0ZQqe/E6OCgIQyCSPJwDFmHut6JRqLYiZ/hJdMT4ElcO2uxvaqtN8XhsBZNfctT03Euo6TBkO4iHD1Un3I/X4xw9tghrOvcjkF9jYpLQVFVxxR4O4zUDZ8SE9nmrrZ4UNe+xQA2TkFliiol6cgrsZhMMNzj4LF3TOnMmfFTx5FUXDqqac2YixECXYcjmPxHHMloJqoEcbKr2QPdQUQlqfvqnU0pXkKH+oKSphIFKlPX4BYWkOohvCh/oiMA9HqyrlOJlVEqhQFFD5kYd/gFcvgzQkfYgUOlJloLIBHrqcgp0cBUNzY5gRA0wEYNXsKgGzDjqvGH9jInAIA6OpyHqo608uLgmjUe05B0fAhLSP6ioQOAYAgmtvneQpqqDwE1KFPAWCKS3fZ1txtlJwx26vsMav/SSCQH2duZIuCkgYfJwC9nTACsll1CBljPmk1xCooKqzSpD6mQdCTprGom4moht10r5gY4Tig4whAqn4hazrQKXeCiQLiWhxG3KwIJUhy5ddPMU+BIACKJf58PYBgijP7eklpKWdVusPf7XzMDnm0RUG8hHOwkupD7u1zsb0EHMd5KrlZqKuxJ5FtX/t6IjM2K0elWk9BnrekypyCgBQwSyAzhrgSzwsfmg1U/GT40Ic+hLvuuqsRY2lbNo9E8b3HduDOp3bht8/swR9eHMHWA1N4+tVRvLh3ApNJFbpuQBJ4swwlYw0pRznU5S8bYtRKkh5j/xf2hvDaWKLsdjaJtI5gDZ6C/ogfB6vs8TCRoPChmnFEgXWjl+WsFcxCDxI7fEjghRxRkNPNGCgtCnTDSjSuLacAyF51nXY5BQDQ1WV6VgDoYEBXV+HtbFEQi0GxPB9lcwryPAWuv53upoWTjAF3+FART0EVScaAh6TIYoguT5OdfJ1LBaIgL84811NQKl7cfR5aoiDXU1Dw87xZ4UfgBcjaJDTdLBOpGRoMTnJCRGYzETkCxvNIq2koafNYVdzNGMhvymWTOgjwzDRgfZ3ONezuapwRBV3Ox2xR0GGdV7Ei9gBjrG7hQ+5ypF7mvVBXY0/hePax0qxnOC9CzO2s7YUsT0GuKKjuHg1khxDZgmc2iYKKLaFUKoUf/vCHeOihh3DsscdCyrmZf/3rX6/b4NqF5/dM4Mt/2pL3+i+fNttof+/Ktc5rv984ghvvexlf/vMrCPpEBH0CApKAoE9A0CfiY2ctxWlHmOVitx2Ywv8+vw8Bn4BNr09CFnkEfCKC1vZH9IfR12GezKpuwDCAM46cvqVmGbx1W17YE8Rfth3CccNdnvYbV2rzFMztkPHX7Yer+qyXsK5izPLnsXdyPQV+v9O50mCGGfaQY/Q4icZcrqcgp0cBUFoUGEZ+ToGX5mUFcK/kNSSnwP16NeFDnZ0QrIeq0hEsLiyCQXP/ug49PgUIVXgKOC7TfMhQTSHgeHHy9yWKPqQBGFqO0VBj+FDZ8onF4DjzOxWlcD4BUEIUWKFG8QkAc4FAAAHJHEcxUVDS4LOOF4NgdrxG5lwrWzLW3weBE+BTJ6BZRpopCvzwl1l5ng3IogyfbFUys8Nw/OVDWPNwx64bSiYRO7kXkARA6AaEjJCUxUxX4ynFDB/q8HUAigjomllJCkDIuoyniogCd7Uer4nGxYozeC1HauN4ClwViDx53rgcUcCJ2R5Kr3AZ70xe+FCVOQWA1TQuOY4pZSoTPuTxmMwEKj4iL774Io477jgAwEsvvZT13mxfNWgUC3uDeMfa+UiqGuJpHUlFx57xBAI+AUnFTIK1Q3+SillvIp7WEU/nXyDvfkOmQ+crB6bwnUe3O3/f/9L+rG2//I5VeNeJZnz0k9sP4/13/N30dFuiIeATEJRE+H0C/umNS/DmVWYDmtFYGjfdt8kSIoIpNOz/lwQcPRDBgl7zxqloBiaSCoI+EQFJgFBFMm6ldAUlTCa9hw/F0zqCvuo9BX5JgFJld+FYWpuR5VCnFU5OQcZTAGRi9FVDRQDZq3ump0AoIQpcD1Db+C0WPpSbUzBdPQXu16vxFAgC0BEBoiNQO0vUnec401swMQFjcgLoCVdekhRw1Su3tvEQPmQUSzRudviQ/Z2KUjifAMiIAk0zBZs9J46nYNzseh0IwM+b53auKFC95BSIQbDOlZgQok5IW66BWNRglPvMcBZtCrpqGqcaeIDjyiabzhYioW53fTII/io8BXki12/+N7nfvK6k3qx7iDtczM4piMgRIG4+K2xREOTM+Y8ZLKvKj429Qm4vkpSinOFtr4p7nXfbUHZ7CioKH3KFctqehWo9BXkeijp4CqbSUyUTjWcqFVsjjz76aCPG0dacunQOTl2avUL/q/Wv4fIThiEJPF49FINh3fzfetw8yJKAuWEfuoI+JBUdCetfStWxZkEm7nBhTwhXn7IQCUXH5pEo+iJ+JBTN+UxvKPNwTSrmRcIYnP25mXAZ2dGkhp+t21X09/zbRcvx4TcuAQBsfH0S7/jeOuc9WeQdr0bAJ+DqkxfADljaN5HE1x/cmiVI7P8PyUJW3L6iGXh9Ium8H5AESFbH5krFqWYY8ImtKxVGYrpGnD4FGiAjIwp4CWmkC658aYYGcKU8BV7Ch8SMp6CQKKgw5KRmT0E5UWB7CjiuOlEAgC1aCG18F5KDZTyKlihAdAroCZdPNC4U3pNbgahE+JDdvEzPnetWJRoD5nkYjxf3FNghRoyZ4sFvGRZi2Jyr+BTgBxAMQlbNY5ARBaZxpDIDgIcY79AiKNzLma/O2b7o/EhhcGIInBIDkq8DADSr3V+5lefZQkewG5Ouv6VAkfksh7spFwAk95kLGoFOwAgVFAXjqXFohgae4xHyhRwj1g4fkpkKgRegcj7ElJjTW8HGa5Kxe5tyOQXlkmptCuUUVBQ+5PrbHhtjDLqhewvna0BOAZBJNh5Ljjn3B6/HZCZQ9RLl9u3bsWPHDrzxjW9EIBCoqNoLUR6/KCCl6pAEHq/sn8Lahaax75cEzOsKIOQTsaJM/P+q+Z1YNb8TAHDnU7vwvlMWFd32gmMGsOnmC5BQTE9FQtUy/6/oOHogszI40CnjQ2cshm6wLFGStD4z1JVZSUlruvPcM/82kNYMjFuJwFNp1REFB6Ip/Peze4uO8cxlc53/3z0Wx7lf/0vW+5LAWV4OEcfMizi/dzSWxuf+5yVHPNiixPZu7HblH6i6gS0jU6Yo8WU8Jj6Bp/N7uuLOKZDhGFelKhDZ4UP5OQXVJBrXKXyoWZ6CKgUBAGDBAozKqyEFyqwWdnRAN3TwMbOySsHVRV3PjKmYpwAo4CnI35edU2CoOXNda6JxtSVJAWDRIvNYDwwUfp/jTDGUTueIgiCgqFb8uQb4fPCz3ERj83ea4UNcxQZ6rggo9XlDngskDoAl9gDBOeW7Gc8yIqEeRxTwPA9ernJVODfZOL7H/G/HEDCJgqJgNGEmIYd9YfOewLs8BXoaMDQExAB03l9QFHjNJ3BvUyx8yJ1T4IWCOQWGh3C83Oubk7I8dTrTIeT3oS+wn8bmFLjLs86E/gNeqVgUjI6O4vLLL8ejjz4KjuOwbds2LFmyBB/60IfQ1dWFr33ta40YZ9sR8AlIqQY6/Kax3Ocqdxn0CUgo3t1ojLGytUx4nkNIFj2V5lzQE8Lb18538hFKcerSOXj11ouQUg0kFEtoqLaQ0DDY4cOLT20GAAx0+nHDhUdlCw3XZ+aEMzcLRWPokEUkVB26FU+p6gyqriGa0rBsIOOyn0iq+GNO6JSbk5dkqqiMxRW85Tt/zdtG4DkEJQHvPGEYn3/LCgBmKdOP/uJZBCQB+ydT2LJ/KktILB+M4OyjzJJ8jDE8/epYlmcj6DPDjkhQ14phhg5ZZfpsT0Gph5zTpyC3+pBdkrQVicbN8hTUIAps47hsbG8kAs3QIMYS4O2E7lxsA96Ov88l14hyBFv+qpxohw/lrnK20lMwb575rxRuUWDD8YBiHS8fAI7LSjxlugYubRqLKU4GoHoy+tx49hQATllRZhlBtigoV81mttAZ6oFlvpvHrcqk9az6+2oMUMbNcz88D5jcn3UPsUNvbGPWNkTt1W+eGYBuCm5Z7gI43gwzyonqq0YUlPUU1JBT4CTul7o3FvAUcBwHgRegGzo0Q/MmTEp5CmrIKfCLZslr+7kym0KHgCpEwTXXXANJkrB7924sX77cef1d73oXrrnmGhIFdcIv8UipmQev22gM+USMxrw3GZtKawj76xe37vcJSCneY+g5jjMNYZ+A3pz3VFXFi9b/D3YG8PGzjii6nzuf2uX8/4qhCDbefAEYY1B0I0dI6Fi34xBSqg6/JKA35MMtbz3G5dHQHYGSSOsI+DIPfFU3MGCHWak6VKs7kG4wTKU1aK5kzVhawxPbMgnGL77udjIDl62d54iClGrgih89XfB3/cf9m/GWY4fw7SvWADAFxDu//xRkiUdAErOERtAnYFl/B956XMbY2LB7PCtsrO1gurmyyvGm8WcZvU5Z0mKeAk4wq+kUCh9yP3TcxjZjmQxvTrBe4wt7CiotSepara1KJJZLNK62cZkLLw2OAJieAqZDSKYhFTMAyq3i53oKSoUPSXZOQX2rD9WUU+CFYsnGmnU+WW/bFV8YY0jHX4Of6YAYQloTAKgVG+iecwoAQO4F4zhoTsgS74ypHQhKQfA+HwxFgcjVQRQYCpCwPOJyH2AlMhfyFNjYISu2EctBd/obyP5eQAViSizvK8eSZgUrL3NVtvpQHXIKqg0fssdniwJPOCIsRxS4ex1UeV13+DqcYzubQoeAKkTBAw88gD//+c+YP39+1utHHnkkXnvttboNrN3xS0KWKHATlCvzFIzHFXQH63cDD0gCkkXGVilJRUeBfGnPcBwHWRQgiwK6XEUhptIqdo8lsKy/A11BH64qETrlFhvzu4N4+v+d4/yt6oYrjCq7yVlYFvH1y1cjoej467bDOGogjJSWESgnLMwY6opu4Ii+sLOfhKIjbSUnM4asBGxFN/DMa+NFx3veiv4sUXD7I9vx0/efWPI4zWoMHUhbokDO3KClEmXsdMOqPoSc5mWlSpICpsFt/+14CvTp5SkATAGQa/zXw1Ng/aayTYT8fugCD44xyMWS/ssZ7EXDh0p4CnQtW7i10lPghWKiQLG+z2cuSnCWtyCpJqHGXoMfAAJDUC3jspGeAlGQoYgRZ84VKxS0XXIKACDg70BcGa3NU+CqhoOE5XsIDQOSmUhcShQ4YUG8nVOQEQWBwBxAnXKqFNmMJ8exbWwbAGC4cxjlaEZOgafriePNe6dzHxWd8aWR9i4KbC8AM5xcI5EXsxeBqhUFckYUtL2nIB6PIxjML8l1+PBhyPLsUkytxDa842ktrzJO0CcWrDxUjNG4kpVUXCulBEulPLljFLum6h86s7A3hJf3RbGsv0SVFA9IAo/OAF+wbGjQJ+KytaY4nhOWcdxwFwY6C98gOgMSHrr2zKzXdIPhp399FW9dMw+Ca2VY4Dj84KrjXd4PKzlcNcXJUa78Dt1gOLKvSHWTdoFZogBctihwNTDLRTM0M3yomKegUE4BkG1s86K1+p7rKWhx9aHccbpfy92uQjx7CgBoITO3yJdIF96gWDlSG3cXWGa4vDglmpcZerZwq0EUeOq+WivFRIFq3Q+kjNfHL/qRUqagJfcBcicQHIJ2aJe5WYUGuh3SZf/GUp+XBAlpsRMGM43QdsspAICQP4J41BIFVQpM53xOjpgdq3kJ8PcDkpUn4g4fyjG8c8OHOBjgLFEQ9M8FolOIK3EnFFUzNDw38hwYYxjqGML8SPYibiEq6VPgBfs36IbuJAd79rwJPkAzG+vZ92LPCxI2ru/wJXdDMHSIU1sziyKcUHVdb3fuRtuLgje+8Y248847ccsttwAwVzAMw8BXv/pVnH322XUfYLvilwRMpTRsPTCFZQPZhm1AEpCowCgfjytZhmStBCQB4wnv4Uul2HEojrgH4V+oK20pBiJ+PLLloKdt6yFJBjr9OBBNFRUFhRB4Dn5JyMvNEAUeFxxTJDmxwD4+e9Hy8hvOaoxM+JA/cyw9JRq7V6SAwonGdrUew8iO1y+WU1BlR2P3w7YqUeAeZ6EQojp4CioRBWrInAu52L2inMHuDrew54XjCsYBi5JpgBjMyBYFNSQaG64mU833FNiiIHO+yYIMWZ2AwulmHLoUqShmPBc7HAMo4yngRShiF3TVbKKVtm7F7SQKejv7MTH2OrqD3VkLDxVhH2OrtCuC88x7xJw5ZsdrV0K63dVY0RWIvIigZC3EusOHrJwCv9wLgX8NuqEjrsYR9oWx8cBGJNQEAlIAx/Yf62l49jlgMKNgedNKcwpEXnR6xaT1NIJ80HviPicByBYFldx7zH2YZWCZoSCQMHs+SYm+zDwI1RvzTjgXZlePAqAKUfDVr34VZ511Fp555hkoioIbbrgBmzZtwtjYGJ588slGjLEtCUgCDk6lsetwCpesHsx6T+C5iozksbiCnlB9w4f21clTIEs8Eh6u8ZRqwC95X62r5BjVozd0f0TGxr2T5Tes83dTkjKycwo8egqcRGMvJUkB08gsJAo0HWBCfTwFtYYPAYXFi40tCmrwFHhONAag2p6CeJFu35V4CtyhQwXOd1GQwDjONHJ13RQBjDnCY396FM8feBI9gR4s6lqEucG5Za8b+zdyHNd4UZDO8abYGkHK5LH4RT/86ihUIQQE5pneLi99Copgl+wFSnsKRF6ELvihGAGA45CCBMBom0RjAOgIdOG4gePMP6r2FOR8LmiF9HR0AOeem7e5X/RD0ZWMlwBwlSS1wod4DpyvA2FfGJOpScSUGCZTk9gb3QuO47B2cK1nL5LbUNcNHbzAZ/1tG+OViEFZlJFUk1B0BUEp6D0cL6tPTJWiAAA6j4Ge2IuUrxcGePAdR5qeRl408zmqxD0ns81TUPGdbsWKFXjxxRfxhje8Aeeddx7i8Tguu+wybNiwAUuXLq14AK+//jre+973ore3F8FgEMcddxyeffZZ533GGG666SYMDQ0hEAjgrLPOwqZNm7L2kU6n8clPfhJz5sxBKBTCpZdeir17i5e2nAnYIToJJT98CKhsdTup1tacK39sPNJ1EgUCx3kyjKMpFZEKk6UrdC7UxJywjEOxImESRajU+5GLT+CdvIS2hhlAWgGQLQqc6kNFE41zRAEzXD0Gch58hSr7OInGudWHak80rtoILVWBqA4lSZ0GR4Ze9vz1HD7kJdHYKF6O1BmXwJuGvP07Xd2NX08dgqqrOBA7gPV71+PRXY/i1fFXi5ZfBJqQTwAU9xSkdVP8+H2AbpZM9vM8fGoUiqEAgSHHOLIrs1SK27tQzlMAAOOhZUDfG5FCeyUaA8gW/bUmGgOAFAZ8XSU3t8Nv3KvSdplNkaXNexXHAULA2eZg/CA2HtwIADiy50j0BHrgFXeDs1zD2/YS8BxfUahabgUiz+FD7uucq0EUhIahda/BZHApYqElELpXAZFlQHiJOQdV4hN8zvzMNlFQsaW4e/duDA8P4+abby743oIFCzzva3x8HKeddhrOPvts/PGPf0RfXx927NiBrq4uZ5uvfOUr+PrXv46f/exnWLZsGb74xS/ivPPOwyuvvIKODvNC+MxnPoP/+7//w913343e3l5cd911uOSSS/Dss89CqGFVrJUE6hi3X2/8vvokGh+aSqPXowdjKqUi4p++K1OSwDulUb1SqfcjF78kIK3Vto9ZgeMpCBUOHyrmKQAP3h0+5BYPuSEqRUWBFT5UB0+ByIs4svdIMMaqCgcpOk6bOuYUAKawEkuU9FOs8CEprZor4blhF2UTjV3hQ3rxykP2uJhVncfQNdNstfcvCIhppmE9NzQXE6kJxJU4Nh3chC2Ht2A4Moxj+o7JM/4bXnkIyBwTtyhIp63qA35AlswVYTGEkD6FcTAkIQFSGKrV6bbac8Vt3JXzFACACh6GGHaMsnZKNHaub0Go/vpxFy+wvQQl6PB14FD8ULZhbyfdMqu3jhAEOB5hn2ngvjZhFnvpDnRjWe+yioco8iIUXcnrAu+uyV8JuRWInJKk5URsAU9BJV5KN426jlf3r8ZEagJd/q667rfVVHw3Wbx4MUZGRtDXl+16GR0dxeLFi6EXq5FdgC9/+csYHh7GHXfc4by2aNEi5/8ZY/jmN7+Jf/u3f8Nll10GAPj5z3+O/v5+3HXXXfjoRz+KyclJ/OQnP8EvfvELnGu54H75y19ieHgYDz30EC644IJKf+K0QJZ4p8twIZq4CJ5HQBKQrKAkaTE27ZvEMUMRPOFh28mkho4KRQHPc9B0A6LQwJW+GoilNYQ99IUohizySGs6gDZ6OBeC6WY34yLhQ4VWluxEY8HtKXCHDuWGlhQUBaIpCpBbfai65mUAcPScoyv+TBalREEdcgp4jndKY2qGVtIg1QQOWihgCq/x8fwmXl7Dh5gB6HZ8cWFRIPACmMADKqCrSpYoYKLolGtc1bcKftGPvdG92DWxC9F0FLsmdqE/3I++UPYzrWWegqT1W4Od5lxpMQB9CKhmRbKYYCY5OsZ5lWE89txxXOmOyO4VWrfAbqfwIUcUVOslALLLHAfLJ/4ePedoDIQHskWBNRc8rHkQze7K7nAWkRexdnBtVWGltijIvWdWWo7UJrcCkW3QVxY+lKk+BFToKUBlvRoqoT/cj/5wf133OR2o+CgVi2GOxWLw+ytzo9x333244IIL8M53vhOPP/445s2bh49//OP48Ic/DADYuXMn9u/fj/PPP9/5jCzLOPPMM7Fu3Tp89KMfxbPPPgtVVbO2GRoawsqVK7Fu3bqCoiCdTiPtiuGMRs0EKlVVoeZ2xGwRPGN47XAMK4YiBcek67rnsVayrVfSdThWrx6cwgnzzZtauX1NxFNY2Bus6Dv7whJ2j05huDu/Wpabeh0fTatsPxPxJPxi+d9eDIFjiCXT6PZPD0+B/TuafQ1xahpcMgnmY2A8n1khNgBN15BkybwxpdU0VIOBGQyapoApaUBNgNM1AD6wnO05xgBNA0ulMvvXDfCqCnAcDDt+nTFwmmngMd3INENrEpxhmONMpzPjtEmnwWkamGHkv1eAovNpmA/aVDoFgRU/95JKEsmOAFjUgHrgANCb3aWESybNsZpfUvz3MAMsNQ5O18AYX3RbAwAMHclkHFC7gHgcnKYhJXFQNNUMfYAEQzcwFBrCUGgI619fj0OJQ4gmo+j2Zff6SCkpaLoGxrPGndMcB07TgEQic85Fo+Zr/hCga2CpCUCMQUxPQDd0jDM/VFVFIp2ApmuAUP6aKziX1vXhE3wlP890Zh4HgznfKfESNK0y42xGYxjmnPB83r3BM8wPyIOmIW8I2Z7JIkSkSPZx1hkMzTSsdU0Hgw9QVfg5v3kuAFg1dxUkSFWdswIEaLqG3eO70SFmhEY8FYemaxAgVLRfnvHQdA3xVByqqjrXlKEbpfdjcNa92FqzYapzHibT+ffzUiTTSfPY8M1/NpWjWc/MSvbvWRRce+21AMxVhX//93/PKkuq6zrWr1+P4447zvsoAbz66qv43ve+h2uvvRb/7//9P/ztb3/Dpz71KciyjPe9733Yv9/sQtvfn63G+vv7nZ4I+/fvh8/nQ3d3d9429udz+dKXvlQw/OmBBx4oWG61VfxlC4+eqIH7C7R/2LSfw/2jL3naTyXbeqUe+9w0wuHhsZcAcHjwwQdLbvvcYQ5HdTJsqmBxan8CeEE1P1cMzQC2HKrP8dk0wuH+Me/72RMDNAZMba3u+7ZOctgpMQxMn1MWAMrOZb3pVl9G3+YtSHCTeF3sgiFlqg5tmNoAANC2aFmLGRuiG6AxBT0BFT7eh4OCAQkxdOtboXEhjArZybHdW7bAF41icnwcKcu4FfUYlm7bBgYB2x54AEw0a2D362ZO1EGBgTUy9KQAPZs3Q5qawsTEBNI92fHEoX37EN67F8nXXkN0ZMTzPnPn8/mp56EYCpJbkggJoaKfezXxKtT9r0LZr2PPSBxju3Zlvd+7cSPEZBLjsRiUSKTgPuZqG8BDhcYFIbIEYvwBxPldBbcd274DYiKB/Q8+AL6nH/6xMXRu346xAIdnDjIE+ACQc63tSu7CQeUgRuQRzPNndx+e1CbxSvwVBIUgki8ni/7OmtB19Fs5dAd1HUwQENy/Hx27d4N18+BSBhRuG1LcMwjrO/FSYi9eA4f0VgET2gS2J7YjIkYQ25TfuKoQ7rncndyN/cp++Hk/tC3FDXz3dTT58iS2xLfAz/uhvzI9w1sbQXjvXoT27YPS2YnxqanyHyhLdTd9H5tEt/4KAGDD8xsQ5ceQ5M3KOiOpEfAcjxe2vYAX8EJV+59QJ7A1sRXP4BlsDG1ERDSvy5H0CPak9qBX6sVocNTz/uzP7ZJ2YVdwF7YntmNMHcMh/yG8Ir9S9HMB4yAixi4AwAGBAzgO+9L7sDe1F6/5XsPuwO6Kf1NICCHxcsLz55pJo5+ZiYT33+1ZFGzYYN4UGGPYuHEjfC43ms/nw+rVq3H99ddXMEzAMAyccMIJuPXWWwEAa9aswaZNm/C9730P73vf+5ztcj0TXiqulNrms5/9rCNyANNTMDw8jPPPPx+RIg+nVvCfO9bhqrefktXYymZ8/W5cdJK3/I2xCrb1Sj32Ofr0bpx3/CCe+MVDOO+88yCVqOow+fc9eNvaeZAqCAWaTKp4fOthXJRTvSl3G27bYVx0bPFtvDL69G5cdLL3Y7J+5xi6g1LVvRQGdk9AFnkcMzQ9zllVVfHggw+Wnct6w+3xg5ucAutYhlWXXuqE/hjMgLDdNMrPX3J+dsfg7Rx0puN4OQ1ZlMH6zwXSh8FNRAB5DljvydnfMXcucOAA2LHHAnbeVHIC/PgmgBNwxCWXWJV/FHD7ze9ngxdXXQe7WrjeXuDQIbDjjgNyGkxiyxZw27eDLVoErFxZdl/F5jO4K4iYGsMp805BbzC3R3mGZ/Y9g0OHBrB6SxR9HQNgF16YFbrE+XxAKgV2xhlAZ2fh33MwBGhTZmgYM8C6VheNx34uvg3G+BiOOONUdC08CnjtNXBdXXg9qCM9LGAwPIjjB4/P+szW0a3YOrYVw5FhrO5fnfXegdgBdIx0oEvuwukLTi97vKqFsypbsTe9CQgGgZdeAtfXB7ZgDrg5hwEhYMaOK3ORGF+Eub4+vGnRm3AocQhdB7swEBrACUMnlPyOQnNp//Zyv899HR3XfxzCB8INPybTju3bwW3ZAjZvHrBmTevGoYzD2B/Ehuc3YM1xa8D3nwrIc+v6FS8efBG7J3fDL/px5oIzIQkSNh/ejB3jO7C4azGOmXuM533tie7BCwdeQF+wD2+Y9wb8fd/fcSB+AMf2HYsFnSWelckRcOPPApwINnghAGDnxE5sOrQJQ+EhrB1c63kM+6b2IbI/gt5AL06Zf4rnzzWDZj0z7WgYL3gWBY8++igA4AMf+AC+9a1v1cV4HhwcxIoVK7JeW758OX73u98BAAasGNT9+/djcDBjtB08eNDxHgwMDEBRFIyPj2d5Cw4ePIhTTz214PfKslyw0ZokSU01ZsqxtC8Mv1w4hk8QBM9jrWRbr9S6z8mEiq6Q7Oyj7LHneAT9ldUD7hVFxFWj5H7TcQ2RgFyX4+P3STA4HrLobXU4pQFd4UDV3x3y+5DW9Gl1zgItuI501ez0GQrlxfz6RB8MZoATOGdMjDFwPAcRInw+ASLHASIPaAAEEZAC+RVxZNmMK+b5zHtp0fxegYdg30903dwHx9UWf1wthcZpI1ilU2W5orKKufPp9/mRMlLgRb7kPHMCB64jDCmoQ+R5IJEA3B5dw0rQDoWKj8cXAJi9Ss8DcrjotpLsh8YL4MEy4xJFpEUVoiCjK9iVN96OQAdEQYSO/OuIF3mIggjZV5/7Q1GCQSCVMpOLJcmsmiSKQFc/IEzATJSYBAQRYngBRF2DzunmOSyI8Pv8nsfnnsuAHIAoiAjI5e9B9nWkQvX8mVnFggXAxASwZEn1JUnrQgCa9XwRRAGivwsQ6zue4waPw6QyibgSx+axzTh+6HgYnAFREBGSQxXNe0gOmdcXZ15fns9ZPWjeRwW/c7wDPvN8BY+8z06mJrEnugdHzzk6L3eAEyq/TppNo5+Zley74gyqO+64wxEEe/fuxeuvv17pLhxOO+00vPJKtgtp69atWLhwIQAzqXlgYCDLtaIoCh5//HHH4D/++OMhSVLWNiMjI3jppZeKioKZwjnLiyexeE00VnWjoKeh1WwamcTKeebqoMSjZFJ1tXhJtEqkNQTl+oR49EdkHIx6L0saVzSEaygVa5aGpZKkSFmhPnIg761CDcyymlLZCW1ML96jACicwGtY5xfHZZKLq6w8VDe8JBrXWJHNrgJSLuHPKZnZO8d8YWws86auZ8ZT6oGVW4K0SKIxAAjWXOt2MqwVRxtnZo6HXaHFjV1OMKXl91JoSqIxkJ9sbCcahzuzz0W5B5LPfPamtJRzTldbBajb3w2e4z2VrbQNraRqjq2typECpnA95RSz0Vgrcd9XON70ItUZgRecROV9U/uwN7o307hMrGxhzt7eLknq+ZrydQFSh9ngzaJUovGLB17EzvGd2DO5J++9RiUaz1YqvtsZhoEvfOEL6OzsxMKFC7FgwQJ0dXXhlltugVGoi2YJrrnmGjz99NO49dZbsX37dtx111344Q9/iH/+538GYBp1n/nMZ3Drrbfi3nvvxUsvvYT3v//9CAaDeM973gMA6OzsxAc/+EFcd911ePjhh7Fhwwa8973vxapVq5xqRDOVfzi+fIWCckwkVHQHp98NfMehOJbMMeORQyIwkWxNAlBc0RGqUw+H/ogfB6eKNGoqQCytIVSDIJFFgfoUAEDKEmL+AqKgQAMz90OlsCgocL0UMrZ1S5qLrrKmNVQeqgt2eE6he3Ed+hQA3quA2O/zdoKxWxTYBjDPZ5dzzSWvX0Rxo4S3Vkx1Vcn6jjiqEwVNKUkK5JclteN/AwGnuoz591DWeGs1droD3bjwiAs9la60vyOhmmNrO1EwXXCXABaCDQtP7PJ34ajeowAAGw9sRDRthp9UW33IFhWeOxrzItB/FtCZiSQpdt9JqklMpCYAAJPp/AaiJAoqo+Kj9G//9m/4yU9+gttuuw2nnXYaGGN48skncdNNNyGVSuE//uM/PO/rxBNPxL333ovPfvaz+MIXvoDFixfjm9/8Jq688kpnmxtuuAHJZBIf//jHMT4+jpNOOgkPPPCA06MAAL7xjW9AFEVcfvnlSCaTOOecc/Czn/1sxvYo8ILXW8F4QpmWokC3SoWqho6wxDAWV7CgBYsw8bSG/kh9mo/0RWQ8s2vc8/a6wWoqlyqL/LTtZdFU0pZB58/PuC7kKXA/mDheBHQAhp6pFOTZU2BYzYN4wNDMzznNz2avp6BSUSD0zAF27jfLktrY1TDKubXzPAXF72WOKLCqP0FVoekaUpx5LEqJAkVXYDAjawWzJZ4CTcscm2AQ0MKAMmGeZ4Eh+C3BkNJSjtCtpTSo16ZnuaKgrcqRTifchq1YffMtLxzRcwQOxg9iLDnmXMtyCVFeCHt7gxnQDK0moV2sT8FILFM0YTJVXBQ0XNzPEioWBT//+c/x4x//GJdeeqnz2urVq51yopWIAgC45JJLcMkllxR9n+M43HTTTbjpppuKbuP3+3H77bfj9ttvr+i724HRmILe8PQTBW5CIjCeaJGnoMbVeje9IRmjFXQ1rnWNR5bIUwDAbPYEZDUusylkwGY9mOwHRTXhQ5oGgDffmy6eggZ3NAYyD1f7OBYjIwp6ze9Mp4F43AzFKNejwCa3iVEJA90JH9Iy4UMpLQUmSfCL/oIrhT7BB57jYTADaS2NgJTxNnle1awVtyiwQ4ckyfSg2IafrxcQ5CxPgX38m7ECan+H7VEhT0GL4HjYTw4mNrbsHMdxWDO4Bo/vety5liudd4EXIPACdENHWkvXJLSLLUbsj2WqTMaUWJ64b+Z1MhuoeGbGxsZw9NH5DXaOPvpojLndw0RDsRtzlWM6egoSioagK2QnJAITCaXEJxo5Fj1rLLUg8BwqaWpcawO6TPOyNsfOKfAYPpRl7GWJAusc5DyKAl234npdDdBmQk5Bk8OHRNGXqS5kewtsUVCJp6CElwAAeCnfU5DUkjBEoaCXwMaOe84NIWqJp8AWBQHrXA4vMv91mdWi3KKg1pyCSrDn3D4mbdXNeLphG7clygHXi6AUxMo+89zjOK7inAIgu6txLUK70H0nraUxmjBLpNri3m5UaEPhQ5VR8d1u9erV+M53vpP3+ne+8x2sXr26wCeIRhD0CUh4CB0ZTyjoCk6vG/jmkShWuMpoBkRgMtWaRjhxRUPINzPdiqYoaHNPATMAxTL4A/kPyYLhQ/X0FHC5noIWiwIvOQV1SjTOdeO7MZgBxkzZK3ACYPdMsBeO7BCZsp4C1/tlQheKegpEsaQoCIimAZ4rCpqWU1BKFPAS0LXKTLpEjiiwhG4zPQXOkMlT0DrsRQux8aIAAIY7h3FM3zFY1beqqnPN3dXYFpVVhQ+5PJT2veVA/AAAMweiO2BWNssNISJRUBkVH6WvfOUruPjii/HQQw/hlFNOAcdxWLduHfbs2YP777+/EWMkChD0iUikdUT8pQ1+3WAV1fZvBq/sj+Edx2eqCvAcnIu83gg8B1U3ih6DWuP6a6HW8KFq2tjPOpieEQUVJhpnewq0KhKNdfPzWZ4Cyxhv9OpyMaZJToH7PZEXTVGwY0dGFFQVPlRGFEjmvgxbFCgKklqqZk9BS8KHijTRtEVBWks7xlYrRAHlFLQO1nEkktxmM6SsSSzpXlL1Z+3rS9EVR2jXEj4EmAsSIidiZMrMJxgID0DRFYwmRjGZnsQwMr1MSBRURsUzc+aZZ2Lr1q14+9vfjomJCYyNjeGyyy7DK6+8gjPOOKMRYyQKEPKJSCitazNfizmqaLrnWv610hP0YTzemtAkogkwHUirZiJmAVFgPwgKJRqLvFgfT4EomKLC3g8wPcOHmlh9yC28OI7L9CeYmjK9BNWED5XxFGRVH2IM0DSktCSYVKWngFVvwFSEWxS4Kw8VwBYFmqE5422GgU6egmlEcBhRYXHTGyNWi+MpcOUUVCO0nXsJzPNf1VUcThwGAAx2DKLTb4Yo2pWSbLIWgYiyVCWdhoaGKk4oJupLUBaQaEBtf680Zl2/MJpugK/yBtgT8mE0rqCvThWG6kkzj+GsRU0DumEa4YUaEgoFcgrcYSG2sWOorspBFeYU8C5PAWaAp6AJicZ5q3OybCYYx+NmXkE14UNlcgpE0fIUGGYFH4MZSGnpqj0F0yJ8KAeBFyAJElRdbWp8f+53kCggvGLnFCS1pPNatUJb4ARozKxiNJoahcEMhH1hhH1h53qYTE2aDSotmyFrEYgoS1VHaXx8HD/5yU+wefNmcByH5cuX4wMf+AB67LhRouEEfQImW1SxpxbSmg5fhV6CWFpDh7+6C7o3LONAtHjvgHqvtQQkIS+RmmggKetBY3frzcFeRc2qPlQo0Vh3nSNcgbkrWn1IyOlTMAM8BU0MH8p6EHd3Z0RBI8KHLFGgqwqgqkhraTCBhyBKzgp7IYr1KmhJorG9+FFEFACmkeUWua0IHyIDi/CKLSDtcrZA9UJb5EVohgbN0JxSpIMdgwDMksM8x0MzNCS1JIKSGYJH4UOVUfHd7vHHH8fixYvx7W9/G+Pj4xgbG8O3v/1tLF68GI8//ngjxkgUwAwfap2noFpjeuv+GI4a6Ci/oYtoUkMkUN1qWG/Ih8MlyoTWe7W+N+zDaMxbuFI9BEmDUjFmDrYoCBQ2+golGmfVrXZEgbUfXirslvdafchosSgolWjcxOpDBWuDu5ONvfYp4HhXtZVyosDcl6FrTpKx7SUolX9TTBQ0vSQpY5lKWiVEgVvgcBzXdFEgCRLlMxGesT1xdjdsjuOqPn/s81DRFRyMHwQADIZNUcBzPDpk07ZwJxuTKKiMip8O//zP/4zLL78cO3fuxD333IN77rkHr776Kt797nc7nYiJxhP0CYi3MKcAAIxK6m9abB6JYvlghaIgpZZNqC5GZ0BCtIndkjsDEiY9fl+72/N1IRk3/+srbDAWLElqlPAUFIvPLll9iM+IgekcPtTE6kNFPQWA6Smwe0uU8xQAGQ+BV0+BpjjlSMtVHgKmgacgt6szzxcMhbNxi4JmGTru76HQIaIS7PPFDh+qJRzPvveMxEagGzoCUsDJJQCATtn8f3dnYxIFlVHx3W7Hjh247rrrsroFC4KAa6+9Fjt27Kjr4IjihOTWegqqbZyVVCvvC2CKguouaJ7nShrf9V7vigQkRFPNEyFtv2BndzMuYkSV6miclWjsiIIiBk8xTwEEqyTpDEg0boGnIOtB3NFhGr+6boYRAeU9BQDQuQLoOALwdZcel51ToOuAomR5CkrhTt4t2uSu0bjFUSBQ8sJutSigykNEJdg5BVmLMVVin4f7pvYByHgJbCKyWercTjbOK41MlKXip8PatWuxefPmvNc3b96M4447rh5jIjwgizzSHvoUNIqAJCBVxfcXKz3qlwQki4icWsKHyo6nzvvz6plIazp8dSiFSuFDVthPgcpDQLYBa597RfsUANV7CqZ7R+PRUfO1MqvQnr6imkRjwDR0u3MMey+egsAA0Lm8rAK2qw8ZlqcgpaVglKk8ZI8xt2Mv0ERPAZAvCkrgFgXNMtDJU0BUS+75Usv15FSTszy/dj6Bje01sMOH8kojE2Wp+Ch96lOfwqc//Wls374dJ598MgDg6aefxn/+53/itttuw4svvuhse+yxx9ZvpEQWHFd6BRwAUqoOWWzMA80vCUiqOkqv3WWj6QaEIoZwd1DCWELBPF/+A3EqpVadaNxsIn4J0WT5sK54WkdInhm/aVrjdDMuklNgGU2MMae2dcFEY5tyosAwTCXGcdO7o3FuToHtxR0ermuisbvKhxtbMOQ9iHt6gEOHMn978RR4HZftKVBVMEVBUk2CSYGyogAwDe2YEkNKSznbNy2nAKhaFLTEU0DdjIkKyO2CXMuKvfs8lEUZ3f5sC8T2FKS0FBRdyS+NTJSl4jvKFVdcAQC44YYbCr7HcZzzoNALubCJphFNquhs0Ap7wBIFlbDjUBxHzC38gO62+gnM68p/ICZVHQFpZrj+/BLv6bjEUhrCdRA6bX+fS1kVLYqsfgu8AJ7jYTADqq461SuAHE+BDVdGFACmGBDFnD4F06R5mR0a5L73Tk0BB8zOn1i6tOavcD+YDWYUfMgXjeN1V6gThJoFSta4JPMc4BhDKjkF3dA9hQ8B2aLApmWegiKNy2yyPAVNMtDJU0BUC8/xWffdWq4n972mP9SfZ+iLvIiQL4S4EsdkatIRJOQl8E7FR2rnzp2NGAfRACaSasPCbgI+vuLwoU37JnHO8v6C73UHJRwoUbWnUSq/3nv1Os5YWkO4Dp4CCh+yPQXFV1clQUJaS0M1VAQQyF7F9uopcMfh26LA7mjMT1NPge3RsL0Eg4Nmr4AacT/UNUMruJJeVBR0dZljYqyuXgIg09GY0w1Mxc3OybI/7MkIKZRs3NKcghK03FNAOQVEhciiDE2pvYmY+zzMDR2yicgRxJU4oukounnTk0D5BN6p+I6ycOHCRoyDqIJy5udkAz0Fslh5TsFUSis6nu6gD5sPxOsxNM8wxlpWASiuaAhRL4PaSZcOHwLMB0kaaScONSssJNeoKmbwcJxpcOt6ZhXe7SmwY1db7SnI9WhoGvD66+bfdfASAJkymHZirox8L01RUSCKQCQCTE56yyeoBJ6HwAswmIFYzBQFgWDE00cLioJpGj7kDsegnAJiJuATfIjDfL7XI3xI5EXMCc4puE2n3ImRqRFMpiedcCLyFHinRU8uohlMJhoYPuQTkFQqrz5UjIhfbFjpUJ7joOn5Y1V0oy7JvtUQS1XfkM1N24cPhYNAyA/IxUVBbgOzgonGNqW65ubG6+s6AH56eQrcHg3DAHbuNP/b05Of5FsD5cqSumN587DHUWdPAQQzVIzTDcTjEwCAYLCz9GcsComCpoYPucPfyogCnuMdw7xZ4UM8xzvHgUQBUSmyq8dILdeT3ZBssGOw6H7cFYioHGnl0JGawZRb5W6kp6DS6kPFqg7ZlCsdWgvdQR/GEyrmdmSvaCZamOwbS2uUaFwPTlgFTPmBQPE47NyypFUlGgPZlX0Mw/yXm1Pg9ClokSjgOFMYGIbZC+C118zX6+QlsLG9L8XKkpZ8GA8MALt2mR6DesLz4HkenMqQSEyCAxAKexNCpcKHplv1IcAcr6IrTTV2RF6EoiuUaExUjFtI1uJ5mxeZB5EXMTc0t+g2dgWimBJDWjf7oZAo8A55CmYxcaU+ceuF8FeYaBxNaugKtuZh0hv2YSyen69gGuatMd7iLfzuWYWHlfncBmZVJRoD2aLADiEqWn2ohbdWe5w7d5qdg8NhoL9wLk/VX1GmLGlWL4hc5s4FzjkHOOaYuo4JguCMiyXNUrXBQHWeAoNlPItNzSnw+z31kQhIpnBo5qq9/Z32ai1BeMUd8laLyOY5HoMdgyWNfL/oh0/wgTGG8eQ4ABIFlUBHagbjJXKkUQm6lVYf2jeZxGBn+RWwRtAb8uHQVBpAdiflhFJ5IzUveDnkim5AFkkU1IwHIzzPU1BNojFQWBTw4vQKHwLMcaoqsGeP+ffSpXWPMyvXwKys275MhZ2q4HnHgOdV8/tDoS5PH7VFQVozVxbdYqcpOQXd3cDChUBvr6fNj+g5ArIgYyA80OCBZTh+8HjElJinak4E4SbLU9CEe2OnvxOH4ocwljRzi5pyDc8SSBTMYhoZbi6LfEUdjUcmkziyr6P8hg2gJ+TDlv1Tea83KtnXS0Wgdk8FqB/lw3VyPQV1CR/SLGPYqngzbUqSAtm5D7IMzJ9f96+oWRQ0Ap6HIGS+T+AFyAFvBqy9kmkwA4quZIU7NiV8iOOACvr69AR60BPoKb9hHQn5Qgj5aq9eRbQf7pyCZhjoETmCQ/FDSKhmyWryFHjH05Hq7u72vOI8NjZW04AI75SzPRtZWYfnubJ5Am72T6ZxxpHF4wAbSVfQh4kCScyJtI6hrtaENNVrbjiOg24wCHybygwPK/O5zbayE435TIlMwFuisdtTIEgADIDZ1YemgafAHX6yeLGncJRK8Zpo3OyHMe8SBQEp4DmZ2U7eVXQFKS3ljLspgoAgZjluT0EzrqlOOTtskESBdzwdqW9+85sNHgYx29EMA1IVlX4qER7FEIoImEYl+0oCD0Uz4GtQN2k3smh+V8DXpu5Rw0NOgSt8KCtW3F6x4gTTqOe4/BKlbgp5CkQJQNoUFcxweQpaHD5k/7dBJaSnpacAAO9KgpX94YrCpuzk3ZSWcuLmKeyAIGrHnVPQrPAhNyQKvOPpSF199dWNHgcxA2nE2rTdDdumkd2ME4qGYAOM6UhARDSlYk64cJddoH7HThbNJnJtKwpQPlzHHT7kXtl2Hk6cAEArnWQMZIxtTct4CiQfADMOHUx3VSFq4QqzaN3WFyyofy8A+ytKiAKDGY4Ib3bTIF7MPNL8gcrCFf2iH9F0FCkt5YQ7UNMjgqidelUf8kpICkHghez8McITNR2pZDIJVc0Oy4jUu8wcURRfE1ekC1Hv8CS7opE7+Tea1BrWlTneoETjiF9CNFlaFNQLvyRUlNsx6/BSfcjlKbCNWJ7jM+KTEwGkS+cTAMU9BXb4EdOnh6dg8WIzbObIIxv2FaWqD7mFQrMfxoKYMT6qEQWAWYGow2d+lsKHCKJ2mh0+xHEcInLEqT5E4t47Fc9OPB7HJz7xCfT19SEcDqO7uzvrH9E8grKIhFLYfT8T6bH6CbiZSqmI+BsjChhrTCx+Z0BCNNWceTETvivrLD2rqCCnQNXVTD6Be7XK/mwlosD2FIiuCkaGq+xtK43JgQHghBOyG2LVmVKeAnfjskZVPysGL2bm0GvjMhu3KGhqN2OCmOXwHO8szjTLQLebmAHkKaiEip9cN9xwAx555BF897vfhSzL+PGPf4ybb74ZQ0NDuPPOOxsxRqIIQUlAXGmdQej1ce81L6A75MN4Tj+BaEqtS+ffZhIJSJhsUHfmXGRRQEptZ0+B/ds9hA8ZauH6+dWIAttTIAiWpwGA7hYFs9uYLJVo3MouooJleHAc57nykI1dhz+lpZrbzZgg2gDbW9Asoe1ONiZR4J2K73j/93//h+9+97v4h3/4B4iiiDPOOAOf+9zncOutt+JXv/pVI8ZIFCEoC0ikC69Ip1Qd/gbXwfcaPjQaV9ATKh/b3BPKbzIWTWoN68rcKCJ+EdEmiQK/RJ4CAECJB429QqUZWnblIRtHFJQ5R8t5Cpg15xxX974A0w0vnoKWiAKrRKwsyuB9lXlK7DyClJYqfJ4QBFE1dvK+VG7xpU6Qp6A6KhYFY2NjWLx4MQAzf8AuQXr66afjL3/5S31HR5Qk5BOLegomk2rDYvErZWQi5alxWXdQwniiMZ4Cu3Rn1ms177UwkYCEaKq0KKhXPoYsUk4BAE99ChhjTtv7msOHsjwFOeFDbWBIegofasFx6Ah0QhIk9AZ6K06ydocPkaeAIOrLirkrcEzfMZgbak5p8ogcccIXKQzQOxXf8ZYsWYJdu3YBAFasWIHf/OY3AEwPQldXVz3HRpQhJAtFcwomEmrDV9i9GtX7JpMY6vKX3c5O0HUzldIQrkPZ0K6AhIkcwdGoPg6SwEPTG9klIoMsmdWH2haOt/4Vv+kLvOAYdyktZb7m3t4pTepRFBhGYU+BEz40+w1JL4nGrVid88shrBlcg3mReZ57FDifdXU1dudFEARROxE5giXdS5omtAVewMLOhegJ9FAX7gqo+K79gQ98AC+88ALOPPNMfPazn8XFF1+M22+/HZqm4etf/3ojxkgUIegTkUgnCr43mWy8KPBq9h6cSqOvo7wo4Hkub58GYxCr6G+QS2/YDE3qbUJFoHJoulG3BGe/JCDdzjkFA+d62kzkRacGvf23gxC0NirTrbVg9aECicZtYEhO1/AhZ46AikWBT/CB53gYzHA6oZKngCBmLqv6V7V6CDOOiu/a11xzjfP/Z599NrZs2YJnnnkGS5cuxerVq+s6OKI0QZ+AeBFPwWRSxbzu8iE7zaBRVX4qoTck43BMwZH9zfm+UiHl8bReF+8HYFcfamNR4BFJkLJEQdYKcMcyQJ4LyL2ld1Kwo7GQaXhmtI+nYNqKAnf35gpFAcdxkEUZSTWJuBoHQDkFBEG0FzXftRcsWIAFCxbUYyxEhQR9IhIlcgqmS/jQdKAn5MP2g7Gs1xo5/lIFl6bSal1FQVuHD3nEzitIqkkABcKH/HPK76RsSVI70Xj2G5Klqg+1tGGQ21NQReM2v+hHUk2Sp4AgiLak4rv2F77whZLvf/7zn696MERl+EQeql54lTihaAg1uMttc6Lm60OhJOZWjT+e1hGqkyho++ZlHrErEBVMNPaK50Tj2W9IzkZPAZDJK4grlqegDULBCIIgbCq+a997771Zf6uqip07d0IURSxdupREQZMptdrd6MZBPMdB1Q1IdYj5L0a9foEo8DA89ktoNLF0fZKnAUDkOWgGiYJy2J6CgonGXikWPtTG1YcYYzCYkbWiPlNzCoCMKGhlBSWCIIhWUfFde8OGDXmvRaNRvP/978fb3/72ugyK8E4rzdzFc0LYdTiOI/s7im6jG6wmcdLI39eq8KdYWkNvKFiXfTW7Y+xMxTZQawpt8Zpo3AaeArexrBma05jI/huY2Z4CZ3dtMJcEQRA2dbnjRSIRfOELX8C///u/12N3xAzhyP4wth6Ildzm0FQacyus+OO1A3ItMMZaGD6k1S18iPCGHT5kU3P4UJanwE40bp+cAo7jnGOYG0I0LTwFHGcKtgrJFQUUPkQQRDtRt2WQiYkJTE5O1mt3xAxgbljG4Vi65DZeexTYBCQBySYkzqY1o/Edn4uIm3qGDxHeyO2iWXP4kNtTkGs4toEoAIr3KpgWngJRrKqrNHkKCIJoZyq+a3/729/O+psxhpGREfziF7/AhRdeWLeBEd5oZfCIl9CVkYkU3rC4x/M+e0JmP4Ggr7EGRTytISg3zngL+ExxU+h3pFQdfomMjWZSV0+BYWQnGrNcUdAec2v3fijmKWjJKrs9R1VUHgIKeAraROARBEEAVYiCb3zjG1l/8zyPuXPn4uqrr8ZnP/vZug2MmB2MxdPoDXl/QHcFfRiPq5jfDai6AZFvjIGVUOpXAagQZndmraAo4EC5AM2mrp4CwBQGgLkirbWnp6BYBSK7TGlLw4eqyCcAyFNAEER7U/Fde+fOnY0YB1Elra6nIwocFM2ATyz88GQwOxV7pSfkw54xs0b4VEpDh79+hgUHwDAYeJ5DLK0h1EBvRGdAwmRSxUBnfuhUvedsmhRVmtbkegqqMlgLCVRBAPRcEdAehmSxXgUtDR/q7DTnZI6HvhMFEHkRIi+21ttBEATRIlr69LrpppvAcVzWv4GBAef93Pfsf1/96ledbc4666y899/97ne34udMG5qRqGuzeE4IOw/H67a/nqDP6ScwlVIRqWMDts6gD5NJMxk0oWgINrCPQyQgIppSG7Z/ojJyDdSqjT1ByP871zPQ5p6CloqCcBi48EJg+fKqdyGLmcII5CkgCKKdqPiuHY/Hcdttt+Hhhx/GwYMHYeTUSH/11Vcr2t8xxxyDhx56yPlbcD10R0ZGsrb94x//iA9+8IN4xzvekfX6hz/84aymaoFAoKIxzDZSauOTaG2W9XfgqR2jOGqgeFnSSujwi4hahns0WV9PQW/Ih9F4Gt0hH+JpHb2hyqoiVUJnQML+yVTB9+odOESRSOWpS/gQYHkGXN2MgUz1IZs2EQXTMtEYKOzRqQC/6M80L2uTuSQIggCqEAUf+tCH8Pjjj+Oqq67C4OBgzbHRoihmeQfc5L7+v//7vzj77LOxZMmSrNeDwWDRfcx2Ch39yaSKzmD9VthLMScsYyyulN/QIzzPOeE1UykVfRHvlYvK0RPyYTSm4Ii+xicaR6zwoWZA4UPlqUuiMZDtKXDKX7ZvojGQ7SnQDd3xVLZMFNSIO6+AwocIgmgnKr5r//GPf8Qf/vAHnHbaaXUZwLZt2zA0NARZlnHSSSfh1ltvzTP6AeDAgQP4wx/+gJ///Od57/3qV7/CL3/5S/T39+PNb34zbrzxRnR0FF+5TqfTSKczpTSj0SgAszuzqs6skA9d1/PGfDiaQEjimvZbCo0BABTNAJhRchz2e+5t7P2NxVJY2OOv2++IyDy2H0hCVVVEk2n4ONawYyRzDJOJdMH9Fzte1VLv/VVLobmcNhiApmeMV0MzoPKVj5NjLFN5SJbBVBXQDXCufTPdAKbjMaiQcvPJDAZN15BUks42aS3tHGdDM6ByM+84CExwfoOuTY9rq1am9bVJVATN5eyhWXNZyf45VmEA+uLFi3H//fdjeQ0xmzZ//OMfkUgksGzZMhw4cABf/OIXsWXLFmzatAm9vb1Z237lK1/Bbbfdhn379sHvz6zk/OhHP8LixYsxMDCAl156CZ/97GdxxBFH4MEHHyz6vTfddBNuvvnmvNfvuusuBIP16TTbLJ7Yz+H0fpYVQrI9CgQEYF6oOWP4ywiHNw7mn0ajKWAkyWFld2VL2U/s53DGAMPTBzms7WWoV+i/bgBPH+JwWj/DE/vN/1aQA10x9u/w+nq9v4fI5pnJZ2DADHdc07EmL6TIC72bNkGMm6ElWjCI0ZUrwbM05uovONtE+cVI8nPrM+hpzJ7UHoykRzAoD2LYPwwASBtpvDD1AniOxwmRE1o8wurYn96P3andAIBV4VUICO0djkoQxMwmkUjgPe95DyYnJxGJREpuW7Eo+OUvf4n//d//xc9//vO6G9DxeBxLly7FDTfcgGuvvTbrvaOPPhrnnXcebr/99pL7ePbZZ3HCCSfg2Wefxdq1awtuU8hTMDw8jMOHD5c9YNON/37udVy8cgABl+X80OaDOGYogsEClW8awd1/34u3rxmCnFOB6O+7xhGWRSwfLO61UVUVDz74IM477zxIVhnBX67fjfeetAC/XL8bV75huK7lO+19/2r9blx50oK67bcQv3h6N646Of876v3dxb6n2RSay+nEA68+AEU3Q90uXHphVeEt3Lp1wNiY+UdPD9ippwKGAm7/A842rHsNEJhXlzG3knLzuXV0K7aObcWCzgU4tu9YAEA0HcVfdv8FsiDjvCXnNXvIdWHf1D48t/85AMDZC89GyNek1ZUGMt2vTcI7NJezh2bNZTQaxZw5czyJgoqfil/72tewY8cO9Pf3Y9GiRXk/5Lnnnqt0lw6hUAirVq3Ctm3bsl5/4okn8Morr+DXv/512X2sXbsWkiRh27ZtRUWBLMuQ5fwkU0mSZtxFFgnIUBiHiGvcMcVAb0cAktScmN4jByLYM5HG8sHsk+1QXMWKeV2ejqn72AuCAEmSIAgCfFU2ISqGvW/e+m8jEYp8R7HX6/09rWK6XkcBXwCGYnoK/D5/dWJTljMJxrJs1sNnAiC4rjVJrrpO/nSk2HwG5ABEQQTHc877nMZBFET4ff5peQ54oSPQAdGaT7/shyTOzN9RiOl6bRKVQ3M5e2j0XFay74qtxre97W2VfsQz6XQamzdvxhlnnJH1+k9+8hMcf/zxWL16ddl9bNq0CaqqYnBwsFHDnFYEZQFJJbv6h9lJt3kJcsv6O/DEtkN5omAyqaKzjiVFZxrNqgpE1Ye8YYcL8RxfvffJnWjsVB/KSSxuk4o1haoPtbzyUB1wJxpTSVKCINqJiu/cN954Y92+/Prrr8db3vIWLFiwAAcPHsQXv/hFRKNRXH311c420WgUv/3tb/G1r30t7/M7duzAr371K1x00UWYM2cOXn75ZVx33XVYs2ZN3RKhpztBSUBc0fJeb2bH3J6QDxOJwoks1Y6jmb0WGkWhn2AYrO5WfCObsM0m7ApENVWUKVR9CAB4EXCq8LSHIVmo+pDT9GsGCyO/6IdP8IGBzWhxQxAEUSlV3/EURSnYp2DBAu+xzXv37sUVV1yBw4cPY+7cuTj55JPx9NNPY+HChc42d999NxhjuOKKK/I+7/P58PDDD+Nb3/oWYrEYhoeHcfHFF+PGG2/M6ncwmwnJIuLpbE9BK+zpehrxAUlAQtHrXs/fTasW1+OKhlCdvTjvOH5+Xfc3W7ENvJoM1kKeAsDyDljGcZuUsSzU0Xg2eAp4jscZC89w/p8gCKJdqPjOvXXrVnzwgx/EunXrsl5njIHjOOi6XuST+dx9991lt/nIRz6Cj3zkIwXfGx4exuOPP+75+2YjQZ/gdACeLfSEfHXtfVCIZuimQg6BWFpDWJ65BtNMxg4fqslgLeYp4Ir8/yymlKdgJosCAAhKM6sKHUEQRD2o+M79gQ98AKIo4ve//31dmpcRtVHIU9CKKfGJAlKqDr9Uu0HUXSIcqVY4WCE8TaCQ8yROoqBl1D18KM9TYNMeq8vFmpe53yMIgiBmDhXfuZ9//nk8++yzOProoxsxHqJCgj4BSTU/p6DZLJ0bwo5DMRwz1AkASKl6XolSr/QEfXhtLNGQ1fxIQEI0pTYlfIjnTAHCu5ohxNI6QiQKWoLtKahb+FCbewpma6IxQRBEu1Kx1bZixQocPny4EWMhqiDoy/cUtIJl/R3YdiDm/D0ymcJAZ3VNf7qDPow3KHyoJ+TDaFxpSvhQh1/CVDpbsMVSGsJ+MphaQWM9Be7/b19PAYkCgiCImUvFT68vf/nLuOGGG/DYY49hdHQU0Wg06x/RXASegzENKvWYIT8ZQ35kIomhKpundfjFhq3mNyNfwSYSEBFNZodBUU5B6+gN9MIv+jEQHqh+J+QpcLANf4MZMJhZcIJEAUEQxMyl4jv3ueeeCwA455xzsl6vJtGYqD/TpZTnvskUjh3uquqzPM8hltbQ31H/jsy9IRl7xibqvt9CRPwSJpMqhl2vxdMahQ+1iA65A+ctrbHLbjFPgdv70CaeArfHRTd08AJPooAgCGIGU/Gd+9FHH23EOIg6kaxTsm+tJJTaVsSnUhqO7Kt/47PukISxuNKUnILOgIRDsXTWawlFQ3AazA9RJeU8BRzXNqKA53jwHA+DGdCZDgkSiQKCIIgZTMV37jPPPLPoe88//3wtYyGqxG3gTiRa10XYL5ndlQM+oeZeCdGkio4GxN7LooBoSkVvyFf3fecSCUjYcSiW97o78ZiYYZQNH2oPQWAj8AIM3XDEgNO8rE16NRAEQcwman6CTU5O4rvf/S7Wrl2L448/vh5jIirEbX9PJlV0tUgULO0LFzSCqyGW1hDxN+Z3JJoUwhPxS4gmsxONp0dwF1E15RKN2ySfwCY32Zg8BQRBEDOXqkXBI488gve+970YHBzE7bffjosuugjPPPNMPcdGVMFkUkVnsDWiYFlfB7YemKrLvoI+oSGeAgCIK80pC+qXeKQ0yrGZVZQNH2ozT0FOWVISBQRBEDOXiu7ce/fuxc9+9jP89Kc/RTwex+WXXw5VVfG73/0OK1asaNQYiQqYTKpY2NuabpydQSmv2k61dAd9iDTI4xFPawj5Gr+iy3FcXhgVBQ7NcMo1L2tzT4HOqHkZQRDETMXzstZFF12EFStW4OWXX8btt9+Offv24fbbb2/k2AiPuA3NyWTrcgpsYmkNwRqN7oW9wYaV7mTM7O9AEBVT1lPQ3qKAPAUEQRAzF8937gceeACf+tSn8LGPfQxHHnlkI8dEVIh7MTql6gi0uLrN/skkhrqqa1xm864TF9RpNPn0hH0Iyc05Rhy5BmYXtneA4yh8CJmEYp3p0A3dKYlMooAgCGLm4fkJ9sQTT2BqagonnHACTjrpJHznO9/BoUOHGjk2okq4FlqiAZ+AHYfiGKyycVkz6A35qFcAUR2yDBx9NLByZbbiE2Tzv3zjq1pNJ9yeAndnY6HNPCYEQRCzAc+i4JRTTsGPfvQjjIyM4KMf/SjuvvtuzJs3D4Zh4MEHH8TUVH0STInaaHXvsiP6wnhi2yEMdtbmKWgkpy6d07DKRkQbcOSRwKJF2a/Jc4CulUBne+VWuRON3eVIW7kwQRAEQVRHxb7uYDCIf/zHf8Rf//pXbNy4Eddddx1uu+029PX14dJLL23EGIkZxBF9Hdi4dxKBJiTyVsuKoQh8YnuFeRANhuOB8GJA6mj1SJqK21NAScYEQRAzm5oso6OOOgpf+cpXsHfvXvzXf/1XvcZEVAjPcdCN6VEBvzMgYW6H3OphEATRBAqFD5EoIAiCmJnUZblUEAS87W1vw3333VeP3REVEpAEJFVzlW46eO3fe/LCVg9hWsJaHdtFEHXGnWhMooAgCGJmQzEUs4CQLCCR1spv2CTOOqqv1UOYNog8D0UzAABJVUeASqESswjyFBAEQcweSBTMAoI+EXGFOudORyIBEdGU2dAtltIQblIpVIJoBiQKCIIgZg8kCmYBIVlAPK1ReMo0pDOQ6fIcS2tUCpWYVRSsPkTlSAmCIGYkJApmAUGfiKSqI6G0vnEZkU3EL2HSEgXxtE6igJhVZFUfMqj6EEEQxEyGRMEsIOgzPQUTSRWdAaq/P52IBCREU+YK6lRaRQeJAmIWQeFDBEEQswcSBbOAoE9EQtExmSBRMN1whw+Rp4CYbVD1IYIgiNkDiYJZgJ1TMJlU0RX0tXo4hIsOfybROE45BcQsgzwFBEEQswcSBbMAvyggpeqYpPChaYck8NB0MwE8ltYQJlFAzCJsAaAbOlRDzXqNIAiCmFmQKJgF8DwHBiBKomBaYjeUY4xB4KdBdzmCqBPuSkNpLQ2ARAFBEMRMhUTBLCKl6fBLNKXTDbtSLBWMJWYbAi+As1RvWk87rxEEQRAzD7IgZxn2A5ogCKIZ2N4C8hQQBEHMbEgUzCKod9n0xNZpJNeI2YgtAgxmZP1NEARBzCxIFMwSyOCcvpBYI2YzueFCJAoIgiBmJiQKZglkdxIE0QpyRQCJAoIgiJkJiQKCaDCU5kHMZkgUEARBzA5IFMwiyPicvjCKISJmKe6ypIX+JgiCIGYGJAoIosEEJAFJVW/1MAiiIbg9A+4SpQRBEMTMgkQBQTSYSEBCNKm1ehgE0RDcooBChwiCIGYuJApmCfG0jqCPHsjTkYhfwmRSbfUwCKIhuKsPkSggCIKYuZAomCVIAofOgNTqYRAF6AxIODSVhixSrDUx+yBPAUEQxOyARMEsIegTSRRMUyIBEfsmkgjJZDARsw93YjGJAoIgiJkLiYJZQkgWSBRMUyIBCfsmkwjJ5CkgZh/kKSAIgpgdtFQU3HTTTeA4LuvfwMCA8/773//+vPdPPvnkrH2k02l88pOfxJw5cxAKhXDppZdi7969zf4pLWf5YASDXf5WD4MoQNgn4kA0hQ4/GUzE7INEAUEQxOyg5Z6CY445BiMjI86/jRs3Zr1/4YUXZr1///33Z73/mc98Bvfeey/uvvtu/PWvf0UsFsMll1wCXW+vEpDL+jsQ8ZOnYDrC8xyiKY3Ch4hZiTvRmHoUEARBzFxabqWIopjlHchFluWi709OTuInP/kJfvGLX+Dcc88FAPzyl7/E8PAwHnroIVxwwQUNGTNBVEo8rSFE1aGIWQh5CgiCIGYHLb+Db9u2DUNDQ5BlGSeddBJuvfVWLFmyxHn/scceQ19fH7q6unDmmWfiP/7jP9DX1wcAePbZZ6GqKs4//3xn+6GhIaxcuRLr1q0rKgrS6TTS6bTzdzQaBQCoqgpVpdKRzcQ+3rP9uMdSKmSBzerf2S5z2S54nU+mM2i62YeDGbP7HJ+p0LU5e6C5nD00ay4r2T/HGGMNHEtJ/vjHPyKRSGDZsmU4cOAAvvjFL2LLli3YtGkTent78etf/xrhcBgLFy7Ezp078e///u/QNA3PPvssZFnGXXfdhQ984ANZBj4AnH/++Vi8eDF+8IMfFPzem266CTfffHPe63fddReCwWBDfivR3nxnE49/Wm5AbHnAHkHUl7gex6bYJgDAsH8Yg/Jgi0dEEARB2CQSCbznPe/B5OQkIpFIyW1bKgpyicfjWLp0KW644QZce+21ee+PjIxg4cKFuPvuu3HZZZcVFQXnnXceli5diu9///sFv6eQp2B4eBiHDx8ue8CI+qKqKh588EGcd955kKTZmxNx3W834mvvXNXqYTSUdpnLdsHrfMaVOB597VEAwKq+VVjYubBZQyQ8Qtfm7IHmcvbQrLmMRqOYM2eOJ1HQ8vAhN6FQCKtWrcK2bdsKvj84OIiFCxc67w8MDEBRFIyPj6O7u9vZ7uDBgzj11FOLfo8sy5BlOe91SZLoImsRs/3Yz+sJzurf52a2z2W7UW4+/ZwfomA+SgK+AM39NIauzdkDzeXsodFzWcm+p1UwQzqdxubNmzE4WNj9PDo6ij179jjvH3/88ZAkCQ8++KCzzcjICF566aWSooAgms1Zy+a2eggE0RAo0ZggCGJ20FJRcP311+Pxxx/Hzp07sX79evzDP/wDotEorr76asRiMVx//fV46qmnsGvXLjz22GN4y1vegjlz5uDtb387AKCzsxMf/OAHcd111+Hhhx/Ghg0b8N73vherVq1yqhERxHTgpCW9rR4CQTQEdxlSd3lSgiAIYmbR0mWdvXv34oorrsDhw4cxd+5cnHzyyXj66aexcOFCJJNJbNy4EXfeeScmJiYwODiIs88+G7/+9a/R0dHh7OMb3/gGRFHE5ZdfjmQyiXPOOQc/+9nPIAj0cCIIgmg0HMdB4AXohk6eAoIgiBlMS+/gd999d9H3AoEA/vznP5fdh9/vx+23347bb7+9nkMjCIIgPBL2hTGVnkJQouptBEEQMxVa1iEIgiBq4pT5p0AzNPgEX6uHQhAEQVQJiQKCIAiiJiRBgiRQJRSCIIiZzLSqPkQQBEEQBEEQRPMhUUAQBEEQBEEQbQ6JAoIgCIIgCIJoc0gUEARBEARBEESbQ6KAIAiCIAiCINocEgUEQRAEQRAE0eaQKCAIgiAIgiCINodEAUEQBEEQBEG0OSQKCIIgCIIgCKLNIVFAEARBEARBEG0OiQKCIAiCIAiCaHNIFBAEQRAEQRBEm0OigCAIgiAIgiDaHBIFBEEQBEEQBNHmiK0ewHSAMQYAiEajLR5J+6GqKhKJBKLRKCRJavVwiBqguZxd0HzOHmguZw80l7OHZs2lbdvatm4pSBQAmJqaAgAMDw+3eCQEQRAEQRAEUV+mpqbQ2dlZchuOeZEOsxzDMLBv3z50dHSA47hWD6etiEajGB4exp49exCJRFo9HKIGaC5nFzSfsweay9kDzeXsoVlzyRjD1NQUhoaGwPOlswbIUwCA53nMnz+/1cNoayKRCN3gZgk0l7MLms/ZA83l7IHmcvbQjLks5yGwoURjgiAIgiAIgmhzSBQQBEEQBEEQRJtDooBoKbIs48Ybb4Qsy60eClEjNJezC5rP2QPN5eyB5nL2MB3nkhKNCYIgCIIgCKLNIU8BQRAEQRAEQbQ5JAoIgiAIgiAIos0hUUAQBEEQBEEQbQ6JAoIgCIIgCIJoc0gUEDXxpS99CSeeeCI6OjrQ19eHt73tbXjllVeytmGM4aabbsLQ0BACgQDOOussbNq0KWubdDqNT37yk5gzZw5CoRAuvfRS7N27N2ub8fFxXHXVVejs7ERnZyeuuuoqTExMNPonthX1mM+xsTF88pOfxFFHHYVgMIgFCxbgU5/6FCYnJ7P2Q/PZWOp1bbq3ffOb3wyO4/A///M/We/RXDaWes7lU089hTe96U0IhULo6urCWWedhWQy6bxPc9lY6jWX+/fvx1VXXYWBgQGEQiGsXbsW//3f/521Dc1l4/Eyn/fccw8uuOACzJkzBxzH4fnnn8/bz7SxgRhB1MAFF1zA7rjjDvbSSy+x559/nl188cVswYIFLBaLOdvcdtttrKOjg/3ud79jGzduZO9617vY4OAgi0ajzjb/9E//xObNm8cefPBB9txzz7Gzzz6brV69mmma5mxz4YUXspUrV7J169axdevWsZUrV7JLLrmkqb93tlOP+dy4cSO77LLL2H333ce2b9/OHn74YXbkkUeyd7zjHVnfRfPZWOp1bdp8/etfZ29+85sZAHbvvfdmvUdz2VjqNZfr1q1jkUiEfelLX2IvvfQS27p1K/vtb3/LUqmUsw3NZWOp11yee+657MQTT2Tr169nO3bsYLfccgvjeZ4999xzzjY0l43Hy3zeeeed7Oabb2Y/+tGPGAC2YcOGvP1MFxuIRAFRVw4ePMgAsMcff5wxxphhGGxgYIDddtttzjapVIp1dnay73//+4wxxiYmJpgkSezuu+92tnn99dcZz/PsT3/6E2OMsZdffpkBYE8//bSzzVNPPcUAsC1btjTjp7Ul1cxnIX7zm98wn8/HVFVljNF8toJa5vL5559n8+fPZyMjI3migOay+VQ7lyeddBL73Oc+V3S/NJfNp9q5DIVC7M4778zaV09PD/vxj3/MGKO5bBW58+lm586dBUXBdLKBKHyIqCt2iEhPTw8AYOfOndi/fz/OP/98ZxtZlnHmmWdi3bp1AIBnn30WqqpmbTM0NISVK1c62zz11FPo7OzESSed5Gxz8skno7Oz09mGqD/VzGex/UQiEYiiCIDmsxVUO5eJRAJXXHEFvvOd72BgYCBvvzSXzaeauTx48CDWr1+Pvr4+nHrqqejv78eZZ56Jv/71r85naC6bT7XX5emnn45f//rXGBsbg2EYuPvuu5FOp3HWWWcBoLlsFbnz6YXpZAORKCDqBmMM1157LU4//XSsXLkSgBn3CAD9/f1Z2/b39zvv7d+/Hz6fD93d3SW36evry/vOvr4+ZxuivlQ7n7mMjo7illtuwUc/+lHnNZrP5lLLXF5zzTU49dRT8da3vrXgvmkum0u1c/nqq68CAG666SZ8+MMfxp/+9CesXbsW55xzDrZt2+bsh+ayedRyXf7617+Gpmno7e2FLMv46Ec/invvvRdLly519kNz2VwKzacXppMNJNZtT0Tb84lPfAIvvvhi1sqTDcdxWX8zxvJeyyV3m0Lbe9kPUR31mM9oNIqLL74YK1aswI033lhyH6X2Q9RGtXN533334ZFHHsGGDRtK7p/msnlUO5eGYQAAPvrRj+IDH/gAAGDNmjV4+OGH8dOf/hRf+tKXCu4jdz9E/ajlHvu5z30O4+PjeOihhzBnzhz8z//8D975znfiiSeewKpVqwruo9B+iPpRaj6roRU2EHkKiLrwyU9+Evfddx8effRRzJ8/33ndDjfIVbIHDx50VkIGBgagKArGx8dLbnPgwIG87z106FDeigpRO7XMp83U1BQuvPBChMNh3HvvvZAkKWs/NJ/NoZa5fOSRR7Bjxw50dXVBFEUn/Osd73iHE6ZAc9k8apnLwcFBAMCKFSuytlm+fDl2797t7IfmsjnUMpc7duzAd77zHfz0pz/FOeecg9WrV+PGG2/ECSecgP/8z/909kNz2TyKzacXppMNRKKAqAnGGD7xiU/gnnvuwSOPPILFixdnvb948WIMDAzgwQcfdF5TFAWPP/44Tj31VADA8ccfD0mSsrYZGRnBSy+95GxzyimnYHJyEn/729+cbdavX4/JyUlnG6J26jGfgOkhOP/88+Hz+XDffffB7/dn7Yfms/HUYy7/9V//FS+++CKef/555x8AfOMb38Add9wBgOayGdRjLhctWoShoaG8colbt27FwoULAdBcNoN6zGUikQAA8Hy2CScIguMRorlsDuXm0wvTygaqW8oy0ZZ87GMfY52dneyxxx5jIyMjzr9EIuFsc9ttt7HOzk52zz33sI0bN7IrrriiYEnS+fPns4ceeog999xz7E1velPBclzHHnsse+qpp9hTTz3FVq1aReXV6kw95jMajbKTTjqJrVq1im3fvj1rPzSfzaNe12YuKFKSlOaycdRrLr/xjW+wSCTCfvvb37Jt27axz33uc8zv97Pt27c729BcNpZ6zKWiKOyII45gZ5xxBlu/fj3bvn07+//+v/+PcRzH/vCHPzj7oblsPF7mc3R0lG3YsIH94Q9/YADY3XffzTZs2MBGRkacbaaLDUSigKgJAAX/3XHHHc42hmGwG2+8kQ0MDDBZltkb3/hGtnHjxqz9JJNJ9olPfIL19PSwQCDALrnkErZ79+6sbUZHR9mVV17JOjo6WEdHB7vyyivZ+Ph4E35l+1CP+Xz00UeL7mfnzp3OdjSfjaVe12ah/eaKAprLxlLPufzSl77E5s+fz4LBIDvllFPYE088kfU+zWVjqddcbt26lV122WWsr6+PBYNBduyxx+aVKKW5bDxe5vOOO+4ouM2NN97obDNdbCDO+lEEQRAEQRAEQbQplFNAEARBEARBEG0OiQKCIAiCIAiCaHNIFBAEQRAEQRBEm0OigCAIgiAIgiDaHBIFBEEQBEEQBNHmkCggCIIgCIIgiDaHRAFBEARBEARBtDkkCgiCIAiCIAiizSFRQBAEQRAEQRBtDokCgiAIoioYYzj33HNxwQUX5L333e9+F52dndi9e3cLRkYQBEFUCokCgiAIoio4jsMdd9yB9evX4wc/+IHz+s6dO/Ev//Iv+Na3voUFCxbU9TtVVa3r/giCIAgTEgUEQRBE1QwPD+Nb3/oWrr/+euzcuROMMXzwgx/EOeecgze84Q246KKLEA6H0d/fj6uuugqHDx92PvunP/0Jp59+Orq6utDb24tLLrkEO3bscN7ftWsXOI7Db37zG5x11lnw+/345S9/2YqfSRAEMevhGGOs1YMgCIIgZjZve9vbMDExgXe84x245ZZb8Pe//x0nnHACPvzhD+N973sfkskk/uVf/gWapuGRRx4BAPzud78Dx3FYtWoV4vE4Pv/5z2PXrl14/vnnwfM8du3ahcWLF2PRokX42te+hjVr1kCWZQwNDbX41xIEQcw+SBQQBEEQNXPw4EGsXLkSo6Oj+O///m9s2LAB69evx5///Gdnm71792J4eBivvPIKli1blrePQ4cOoa+vDxs3bsTKlSsdUfDNb34Tn/70p5v5cwiCINoOCh8iCIIgaqavrw8f+chHsHz5crz97W/Hs88+i0cffRThcNj5d/TRRwOAEyK0Y8cOvOc978GSJUsQiUSwePFiAMhLTj7hhBOa+2MIgiDaELHVAyAIgiBmB6IoQhTNx4phGHjLW96CL3/5y3nbDQ4OAgDe8pa3YHh4GD/60Y8wNDQEwzCwcuVKKIqStX0oFGr84AmCINocEgUEQRBE3Vm7di1+97vfYdGiRY5QcDM6OorNmzfjBz/4Ac444wwAwF//+tdmD5MgCIKwoPAhgiAIou788z//M8bGxnDFFVfgb3/7G1599VU88MAD+Md//Efouo7u7m709vbihz/8IbZv345HHnkE1157bauHTRAE0baQKCAIgiDqztDQEJ588knouo4LLrgAK1euxKc//Wl0dnaC53nwPI+7774bzz77LFauXIlrrrkGX/3qV1s9bIIgiLaFqg8RBEEQBEEQRJtDngKCIAiCIAiCaHNIFBAEQRAEQRBEm0OigCAIgiAIgiDaHBIFBEEQBEEQBNHmkCggCIIgCIIgiDaHRAFBEARBEARBtDkkCgiCIAiCIAiizSFRQBAEQRAEQRBtDokCgiAIgiAIgmhzSBQQBEEQBEEQRJtDooAgCIIgCIIg2pz/H5TwW+7RXX6NAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Run function to display plots for each var_name\n",
+    "for var_name in [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]:\n",
+    "    plot_annual_forcing_variable(annual_table, var_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "e1accf91-c0cc-42ca-9b93-d01fafd0a457",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_annual_forcing_variable_fulltrend(annual_forcing_table, var_name):\n",
+    "\n",
+    "    # Combine historical and scenarios\n",
+    "    annual_forcing_table_all = pd.concat([annual_hist_table, annual_forcing_table],ignore_index=True)\n",
+    "    data = annual_forcing_table_all[annual_forcing_table_all[\"variable\"] == var_name]\n",
+    "    \n",
+    "    plt.figure(figsize=(9, 5))\n",
+    "    \n",
+    "    # Loop through scenarios\n",
+    "    for scenario in scenarios_new:\n",
+    "\n",
+    "        # Extract one scenario and colour \n",
+    "        scenario_data = data[data[\"scenario\"] == scenario]\n",
+    "        colour = colours[scenario]\n",
+    "\n",
+    "        # # Plot historical \n",
+    "        # if scenario == \"historical\":\n",
+    "            \n",
+    "        # Plot yearly average \n",
+    "        plt.plot(scenario_data[\"year\"],scenario_data[\"value\"],color=colour,linewidth=0.3,label=scenario)\n",
+    "\n",
+    "        x = scenario_data[\"year\"].values\n",
+    "        y = scenario_data[\"value\"].values\n",
+    "\n",
+    "        # Polyfit method for making trendline function\n",
+    "        slope, intercept = np.polyfit(x, y, 1)\n",
+    "        trend = slope * x + intercept\n",
+    "\n",
+    "        # Plot trendline\n",
+    "        plt.plot(x,trend,linestyle=\"--\",color=colour)\n",
+    "\n",
+    "        # # Plot other scenarios\n",
+    "        # else:\n",
+    "\n",
+    "        #     # Plot yearly average\n",
+    "        #     plt.plot(scenario_data[\"year\"],scenario_data[\"value\"],alpha=0.3,color=colour,label=scenario)\n",
+    "\n",
+    "        # # Look at each 25 year period\n",
+    "        # for i in range(len(periods[0])):\n",
+    "\n",
+    "        #     # Define period range\n",
+    "        #     start_year = periods[0][i]\n",
+    "        #     end_year = periods[1][i]\n",
+    "\n",
+    "        #     # Adjust data to fit period range\n",
+    "        #     period_data = scenario_data[\n",
+    "        #     (scenario_data[\"year\"] >= start_year) & \n",
+    "        #     (scenario_data[\"year\"] <= end_year)]\n",
+    "\n",
+    "        #     # Plot trend line over each 25 year period\n",
+    "        #     if len(period_data) > 1:\n",
+    "\n",
+    "        #         x = period_data[\"year\"].values\n",
+    "        #         y = period_data[\"value\"].values\n",
+    "\n",
+    "        #         # Polyfit method for making trendline function\n",
+    "        #         slope, intercept = np.polyfit(x, y, 1)\n",
+    "        #         trend = slope * x + intercept\n",
+    "\n",
+    "        #         # Plot trendline\n",
+    "        #         plt.plot(x,trend,linestyle=\"--\",color=colour)\n",
+    "\n",
+    "    # Define titles and labels based on var_name\n",
+    "    if var_name == \"pr\":\n",
+    "        ylabel = \"Annual precipitation (mm/year)\"\n",
+    "        title = \"Annual precipitation in LAR basin by climate scenario\"\n",
+    "\n",
+    "    elif var_name == \"evspsblpot\":\n",
+    "        ylabel = \"Annual potential evaporation (mm/year)\"\n",
+    "        title = \"Annual potential evaporation in LAR basin by climate scenario\"\n",
+    "\n",
+    "    elif var_name == \"tas\":\n",
+    "        ylabel = \"Annual mean temperature increase (°C)\"\n",
+    "        title = \"Annual mean temperature in LAR basin by climate scenario\"\n",
+    "\n",
+    "    elif var_name == \"rsds\":\n",
+    "        ylabel = \"Annual mean shortwave radiation (W/m²)\"\n",
+    "        title = \"Annual mean shortwave radiation in LAR basin by climate scenario\"\n",
+    "\n",
+    "    plt.xlabel(\"Year\")\n",
+    "    plt.ylabel(ylabel)\n",
+    "    plt.title(title)\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "ca7627a2-2243-4402-9575-079e1f767d5f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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PW44dO8aFCxe49dZbUaurwr+goCCuvfZadu7c6ZbxOlLDk8G85HbJycls3bqVSZMmoSgK+fn55OfnM336dACb+aORkZFWj02DrKr/EQ0ICLD6Q2dat6yszKW23nzzzbz55pvceeed/PLLL+zevZs9e/YQHR1dr8GQERERVo99fHzsLrdse0ZGBvn5+fj4+ODt7W31Lz093fzHpri4mGHDhrFr1y4WLlzI5s2b2bNnD6tWrQI8f9xMbf3rr79qtDM4OBhFUWr8YXTmmAA12taqVasabYiNjQUgJyfH3CZHjp+JrcocqampDBs2jPPnz/Paa6+xbds29uzZYw6cPDFINiAgoMYgNWffi6Oqf9dAfBbc9b5c+f5ff/317Nmzh+3bt/Puu+8SHBzMjTfeaDPwt8f0Wai+zPTZAMe/76+//jqPPvooq1evZtSoUURERDB16lSH2lPf42vvfeh0OoqLi83bu/vuu1m+fDn5+flkZWWxcuVK7rzzzjoHqGZlZdG6dWuH2uKI6t9fEN9hR77Xc+bM4amnnmLq1Kn88MMP7Nq1iz179nDJJZc4dLxMOetz586t8R257777AGr9ntx666189NFHnDlzhmuvvZaYmBguu+wy1q9fb17HkePl7O9CRz4jzh4bR6oMmb4LttaNj4/HaDSSl5dX53akpsersRsgtTwfffQRiqLw9ddf26z9/Mknn7Bw4UKrnnh3MgWt1Qd3Vv+FWlBQwJo1a5g3bx6PPfaYeXl5eTm5ubkeaVtdoqKiiIyMrDFQzMTUm7Nx40YuXLjA5s2bzb3xAPn5+Q3RTEC01d/f3+7gvqioKLfuz9bgvPT0dKDqj6Ojx8/EVp3w1atXo9VqWbVqFYmJieblzpTFc/QzWFs7nH0vTYUr3//o6GgGDBgAwODBg+nWrRsjRozgoYceqjEw0B7TZ6H6MtNnw5nve2BgIAsWLGDBggVkZGSYe+mnTJnC0aNHHWqPq+y9Dx8fH4KCgszL7r33Xp577jk++ugjysrKqKio4J577qlz+9HR0Zw7d86tbXbVZ599xm233cazzz5rtTw7O5uwsLA6X2/6HfP4449zzTXX2FynS5cutW5j5syZzJw5E61Wy9atW5k3bx6TJ0/m+PHj5oHYdR0vT/wudPbYODLngem7kJaWVuO5CxcuoFarCQ8Pd7qtUuOTwbzkVgaDgU8++YQOHTrwwQcf1Hh+zZo1vPTSS/z88881UlHcxVRt5a+//mL8+PHm5d9//73VeiqVCkVRavRkffDBBzUqpDSUyZMn88UXX2AwGLjsssvsrmf6xV297Z4o5WevV3Hy5Mk8++yzREZG0q5dO7fvt7qioiK+//57q1Sb5cuXo1arGT58uLlNjhy/2tg6toqi8P7779dY196xcfQzWBt3vJeG5q7v/7Bhw7jtttv45JNP2LFjB4MHD65z3ytWrGDOnDnm83fmzBm2b9/ObbfdBrj+fW/VqhUzZszgwIEDvPrqq5SUlBAQEFBne1y1atUqXnzxRfMFYVFRET/88APDhg2zugCKi4vjuuuuY8mSJeh0OqZMmWKV3mPPhAkTWLZsGceOHasz0PU0lUpV43z8+OOPnD9/no4dO5qX2btT26VLFzp16sSBAwdqBL3OCgwMZMKECeh0OqZOncqhQ4dITEx06Hh54neho8fGGV26dCEhIYHly5czd+5c83dFq9XyzTffmCvcSM2PDOYlt/r555+5cOECzz//PCNHjqzxfM+ePXnzzTf58MMPPRbMx8bGMmbMGBYtWkR4eDiJiYn8+uuv5hQUk5CQEIYPH86LL75IVFQUSUlJbNmyhQ8//NChXiFPuPHGG/n888+ZOHEis2fPZuDAgXh7e3Pu3Dk2bdrE1VdfzbRp0xgyZAjh4eHcc889zJs3D29vbz7//HMOHDjg9jb16tWLL774gi+//JL27dvj5+dHr169ePDBB/nmm28YPnw4Dz30EL1798ZoNJKamsq6det4+OGH3RqERkZGcu+995Kamkrnzp356aefeP/997n33nvNQYyjx682Y8eOxcfHh5tuuolHHnmEsrIy3n77bZu3n3v16sWqVat4++236d+/P2q1mgEDBjj8GayNO96LJ5w8edJmj3v37t05deqU277/Tz/9NF9++SVPPfUUGzZsqLNdmZmZTJs2jbvuuouCggLmzZuHn58fjz/+OODc9/2yyy5j8uTJ9O7dm/DwcI4cOcKyZcsaJNjRaDSMHTuWOXPmYDQaef755yksLDSXTbU0e/Zs83fMVA6yLv/73//4+eefGT58OE888QS9evUiPz+ftWvXMmfOHLp27erW91ObyZMn8/HHH9O1a1d69+7NH3/8wYsvvlgjraVDhw74+/vz+eef061bN4KCgoiPjyc+Pp53332XCRMmMH78eGbMmEFCQgK5ubkcOXKEffv28dVXX9nd/1133YW/vz9Dhw4lLi6O9PR0Fi1aRGhoqLkcpiPHyxO/Cx09Ns5Qq9W88MIL3HLLLUyePJm7776b8vJyXnzxRfLz83nuuedc3rbUuGQwL7nVhx9+iI+PDzNnzrT5fFRUFNOmTePrr792qoa0s5YtW8a//vUvHn30UQwGA1OmTGHFihXmW/kmy5cvZ/bs2TzyyCNUVFQwdOhQ1q9fX2OgakPRaDR8//33vPbaayxbtoxFixbh5eVF69atGTFiBL169QJEYPvjjz/y8MMP83//938EBgZy9dVX8+WXX7p9tr8FCxaQlpbGXXfdRVFREYmJiZw+fZrAwEC2bdvGc889x3vvvUdKSgr+/v60bduWMWPGWNWjd4fY2Fjeeust5s6dy8GDB4mIiOCJJ56wCnIcPX616dq1K9988w1PPvkk11xzDZGRkdx8883MmTOHCRMmWK07e/ZsDh06xBNPPEFBQQGKqBAGOP4ZtMcd78UT1q5dazP1Z968eRw4cMCp77+tcRAmbdq04V//+hcvvvgiW7duNd99sefZZ59lz549zJw5k8LCQgYOHMgXX3xBhw4dzOs4+n0fPXo033//Pa+88golJSUkJCRw22238Z///KfWNrjDrFmzKCsr44EHHiAzM5MePXrw448/MnTo0BrrDhw40Fwz3zQ3QV0SEhLYvXs38+bN47nnniMnJ4fo6Gguv/xym/nvnvTaa6/h7e3NokWLKC4upl+/fqxatYonn3zSar2AgAA++ugjFixYwLhx49Dr9cybN4/58+czatQodu/ezTPPPMODDz5IXl4ekZGRdO/eneuvv77W/Q8bNoyPP/6YlStXkpeXR1RUFJdffjmffvop0dHRgGPHyxO/Cx09Ns66+eabCQwMZNGiRdxwww1oNBoGDRrEpk2bGDJkSL22LTUelWL6yyNJktREjRw5kuzsbP7+++/GbookNRl//fUXl1xyCW+99ZZ5wKckSRcf2TMvSZIkSc3IyZMnOXPmDE888QRxcXHMmDGjsZskSVIjkqUpJUmSJKkZefrppxk7dizFxcV89dVXctCiJF3kZJqNJEmSJEmSJDVTsmdekiRJkiRJkpopGcxLkiRJkiRJUjMlg3lJkiRJkiRJaqaadTUbo9HIhQsXCA4OdmgqY0mSJEmSJElqDhRFoaioiPj4eNRq+/3vzTqYv3DhAm3atGnsZkiSJEmSJEmSR5w9e7bW2X+bdTAfHBwMiDcZEhLSyK25uOj1etatW8e4cePw9vZu7OZI9STPZ8shz2XLIc9lyyHPZcvSUOezsLCQNm3amONde5p1MG9KrQkJCZHBfAPT6/UEBAQQEhIifzG1APJ8thzyXLYc8ly2HPJctiwNfT7rSiWXA2AlSZIkSZIkqZmSwbwkSZIkSZIkNVMymJckSZIkSZKkZqpZ58w7QlEUKioqMBgMjd2UFkWv1+Pl5UVZWZnHjq1Go8HLy0uWHZUkSZIkSbKjRQfzOp2OtLQ0SkpKGrspLY6iKMTGxnL27FmPBtsBAQHExcXh4+PjsX1IkiRJkiQ1Vy02mDcajaSkpKDRaIiPj8fHx0f28LqR0WikuLiYoKCgWicycJWiKOh0OrKyskhJSaFTp04e2Y8kSZIkSVJz1mKDeZ1Oh9FopE2bNgQEBDR2c1oco9GITqfDz8/PY0G2v78/3t7enDlzxrwvSZIkSZIkqUqL7+qUvbnNmzx/kiRJkiRJ9slISZIkSZIkSZKaKRnMS5IkSZIkSVIzJYP5JmjkyJE8+OCDdp9XqVSsXr26wdpjsnnzZlQqFfn5+W7Z3unTp1GpVOzfv98t25MkSZIkSbrYyGC+GUpLS2PChAkOrevOwH/IkCGkpaURGhrqlu1JkiRJkiRJ9dNiq9m0ZLGxsQ2+T71ej4+Pj3nfiqI0eBskSZIkSZIka7JnvokyGo088sgjREREEBsby/z5883PWfa263Q6Zs2aRVxcHH5+fiQlJbFo0SIAkpKSAJg2bRoqlcr8GODtt9+mQ4cO+Pj40KVLF5YtW2a1f5VKxTvvvMPVV19NYGAgCxcutJlm8/vvvzNixAgCAgIIDw9n/Pjx5OXlAbB27Vouv/xywsLCiIyMZPLkyZw8edLtx0qSJEmSJOliddH1zJfoKjiRUdxg++vUKogAH+cP8yeffMKcOXPYtWsXO3bsYMaMGQwdOpSxY8darff666/z/fffs3LlStq2bcvZs2c5e/YsAHv27CEmJoalS5dy5ZVXotFoAPj222+ZPXs2r776KmPGjGHNmjXMnDmT1q1bM2rUKPO2582bx6JFi3jllVfQaDSkpKRY7fvgwYOMHTuWO+64g9dffx0vLy82bdqEwWAAQKvVMmfOHHr16oVWq+W///0v06ZNY//+/bLkpCRJkiS1NEePwltvwSuvgNdFF2I2Gnmkm6jevXszb948ADp16sSbb77Jr7/+WiOYT01NpVOnTlx++eWoVCoSExPNz0VHRwMQFhZmlZqzePFiZsyYwX333QfAnDlz2LlzJ4sXL7YK5m+++WbuuOMO8+Pqwfxrr73GgAEDWLJkiXlZjx49zD9fe+21Vut/+OGHxMTEcPjwYXr27OncAZEkSZIkqWk7dw6uvRYWLYLHHgNv78Zu0UXhogvmA3y8uKRNWGM3o069e/e2ehwXF0dmZmaN9WbMmMHYsWPp0qULV155JZMnT2bcuHG1bvvIkSP885//tFo2dOhQXnvtNatlAwYMqHU7f//9N9dff73d50+ePMlTTz3Fzp07yc7Oxmg0AuICRAbzkiRJktTCpKfD5MnQvXtVQO/j09itavFkrkMT5V3talalUpmDYUv9+vUjJSWFp59+mtLSUq6//nqmT59e5/ZVKpXVY0VRaiwLDAysdRt+fn61Pj9lyhRycnJ4//332bVrF7t27QJEnr8kSZIkSS1MQQGEhkJMDNx3Hzz7LJSXN3arWjwZzLcAISEh3HDDDbz//vt8+eWXfPPNN+Tm5gLiosCUw27SrVs3fvvtN6tl27dvp1u3bk7tt0ePHmzcuNHmczk5ORw5coQnn3ySK664gm7dupkHxkqSJEmS1EKZOgajouCBB0QPfVlZ47aphbvo0mxamldeeYW4uDj69OmDWq3mq6++IjY2lrCwMEBUtPn1118ZOnQovr6+hIeH8+9//5vrr7+efv36ccUVV/DDDz+watUqNmzY4NS+H3roIYYOHcp9993HPffcg4+PD5s2beK6664jIiKCyMhI3nvvPeLi4khNTeWxxx7zwBGQJEmSJKlJioiAhx6C556Dp56CykIcknvJnvlmLigoiOeff54BAwZw6aWXcvr0aX766SdztZiXXnqJ9evX06ZNG/r27QvA1KlTee2113jxxRfp0aMH7777LkuXLmXkyJFO7btjx46sXbuWAwcOMHDgQAYPHsx3332Hl5cXarWaL774gj/++IOePXvy0EMP8eKLL7r77UuSJEmS1JSFhkK3blCZMSC5n+yZb4I2b95cY5nlLK6WEzbddddd3HXXXXa3NWXKFKZMmVJj+b333su9995r93W2JoUaOXKkebkpf3/EiBH8/vvvNrcxZswYDh8+bHe7SUlJcvIpSZIkSWrpwsMhLw8qq+xJ7iV75iVJkiRJkiTPMQXzkkfIYF6SJEmSJEmqH53Ofl35iAgZzHuQDOYlSZIkSZKk+snIgFatbD8ne+Y9SgbzkiRJkiRJUv2kp4PFbPNWQkNFDXrJI2QwL0mSJEmSJNVPbcG8RgM2Jr6U3EMG85IkSZIkSVL9pKfbT7MBkNXrPEYG85IkSZIkSVL96HTg59fYrbgoyWBekiRJkiRJkpopGcxLkiRJkiRJUjMlg3lJkiRJkiRJaqYaNZhPSkpCpVLV+Hf//fc3ZrNarEOHDnHttdeaj/urr75aY51FixZx6aWXEhwcTExMDFOnTuXYsWM11jty5Ag33XQT4eHhBAcHM2jQIFJTUxvgXUiSJEmSJEkmjRrM79mzh7S0NPO/9evXA3Ddddc1ZrNarJKSEtq3b89zzz1HrJ3yUVu2bOH+++9n586drF+/noqKCsaNG4dWqzWvc/LkSYYPH06nTp3YuHEjBw4c4KmnnsJPDnyRJEmSpIuPoshqNY2oUYP56OhoYmNjzf/WrFlDhw4dGDFiRGM2q9F9/fXX9OrVC39/fyIjIxkzZgxarZbNmzczcOBAAgMDCQsLY+jQoZw5cwaA+fPn06dPH959913atGlDQEAA1113Hfn5+ebtXnrppbz44ovceOON+Pr62tz32rVrmTFjBj169OCSSy5h6dKlpKam8scff5jX+c9//sOECRP43//+R9++fWnfvj2TJk0iJibGo8dFkiRJkqQmqKgIQkJqX8fLC/T6hmnPRcarsRtgotPp+Oyzz5gzZw4qlcrmOuXl5ZSXl5sfFxYWAqDX69FX+4Do9XoURcFoNGK0mKhAq9NyOPuwB96Bbd2juhPoE+jw+mlpadx00008//zzTJ06laKiIn777TcMBgNTp07lzjvv5PPPP0en07F7927ze1QUheTkZFauXMl3331HYWEhd911F/fddx+fffaZzX2ZXlubvMrpl8PCwszH8scff2Tu3Llce+21HDx4kHbt2vHoo48ydepUh9+no0zvTa/Xo9Fo3L59STB9f6p/j6TmR57LlkOey5ajxZ/Ls2dRRUWh1PL+VEFBKFlZEB3dgA3zjIY6n45uv8kE86tXryY/P58ZM2bYXWfRokUsWLCgxvJ169YREBBgtczLy4vY2FiKi4vR6XTm5Vq9Fm2xtvomPKbQtxCDt8Hh9ZOTk6moqGDMmDFEREQQERFBYmIiOTk5FBQUMGrUKKIrvwjTpk0T+ygspLy8nLKyMl5//XUSEhIAcbxuuOEG5s2bR6tqEzkYjUbKysrMF0S2KIrC7NmzGTRoEG3btqWwsJCMjAyKi4t54YUX+M9//sP8+fPZsGED06dP54cffmDo0KHOHqJa6XQ6SktL2bp1KxUVFW7dtlSTKdVNav7kuWw55LlsOVrquYw8dAh9YCCFtQSf0SdOUFJQgLYyRmkJPH0+S0pKHFqvyQTzH374IRMmTCA+Pt7uOo8//jhz5swxPy4sLKRNmzaMGzeOkGq3d8rKyjh79ixBQUFWudwhhBAXGef+N+AmQ4YM4YorruDyyy9n3LhxjB07lunTp5OYmMjtt9/Otddey5gxYxgzZgzXXXcdcXHivfj6+tK2bVu6detm3tYVV1yB0WjkwoULdOrUyWo/arUaPz+/GsfN0qxZszhy5Ahbt241r1dcXAzAVVddxX333UdwcDBDhw5l3759LFu2jAkTJrj1eJSVleHv78/w4cNlTr4H6fV61q9fz9ixY/H29m7s5kj1IM9lyyHPZcvR0s+lSqtFGTECakm3VcXEgNGIMnBgA7bMMxrqfNbW4WqpSQTzZ86cYcOGDaxatarW9Xx9fW3ment7e9c4mAaDAZVKhVqtRq1uPhU41Wo169evZ/v27axbt4633nqLp556il27dvHxxx8ze/Zs1q5dy8qVK3nqqadYv349gwYNMqcmWb5XU1qKRqOxeQxMx8eWf/3rX/zwww9s3bqVtm3bmpfHxMTg5eVF9+7drbbRvXt3fvvtN7cfa7VajUqlsnmOJfeTx7nlkOey5ZDnsuVosecyPx/i4qC2GCA6GpKToQW9f0+fT0e33SSi3KVLlxITE8OkSZMauylNgkqlYujQoSxYsIA///wTHx8fvv32WwD69u3L448/zvbt2+nZsyfLly83vy41NZULFy6YH+/YsQO1Wk3nzp0d3reiKMyaNYtVq1axceNG2rVrZ/W8j48Pl156aY1ylcePHycxMdGVtytJkiRJUnOmKLUH8gDh4VA5Dk9yr0bvmTcajSxdupTbb78dL69Gb06j27VrF7/++ivjxo0jJiaGXbt2kZWVhb+/P48//jhXXXUV8fHxHDt2jOPHj3PbbbeZX+vn58ftt9/O4sWLKSws5IEHHuD66683l6HU6XQcPnzY/PP58+fZv38/QUFBdOzYEYD777+f5cuX89133xEcHEx6ejoAoaGh+Pv7A/Dvf/+bG264gUsvvZQJEyawbt06fvjhBzZv3tyAR0qSJEmSpGYjLEz04Etu1+jR84YNG0hNTeWOO+5o7KY0CSEhIWzdupVXX32VwsJCEhMTeemll7jmmmu45557+OSTT8jJySEuLo5Zs2Zx9913m1/bsWNHrrnmGiZOnEhubi4TJ05kyZIl5ucvXLhA3759zY8XL17M4sWLGTFihDkQf/vttwEYOXKkVbuWLl1qHpw8bdo0lixZwqJFi3jsscfo0qUL33zzDZdffrlnDookSZLUNCkK2KlAJ0lWNBqoo4Ke5JpGD+bHjRuHIicaMOvWrRtr1661+Zwp1aY29957L/fee6/N55KSkuo81o6eizvuuIPp06cTEhLSrMYkSJIkSW70xhvwwAON3QqpuZAXfh4hozBJkiRJklxz8mRjt0CSLnoymJckSZIkyTWpqY3dAqmxGQyyx72RyWC+hZg/fz779+9v7GZIkiRJF5OzZxu7BVJjy852fFZXmVbtETKYlyRJkiTJNTodyNm5L27p6VBZNU9qHDKYlyRJkiTJNbJ2uCSD+UYng3lJkiRJkpynKBAZCbm5jd0SSEuDP/9s7FZcnNLTxeyvUqORwbwkSZIkSc7T6UQQl5PT2C2B06dlZZ3GUlwMQUGOrevlBXq9Z9tzEZLBvCRJkiRJztNqoU2bphHMZ2WJoFJq2uQssB4hg3lJkiRJkpxXUiKC+aaQZpOdLS4upKatIcdYHD7cMPtpApyeAfb06dNs27aN06dPU1JSQnR0NH379mXw4MH4+fl5oo2SJEmSJDU1Wi3ExMDx443dEnFhIWude8Zzz8Fjj7lnWw0ZzL/0Enz4YcPsq5E53DO/fPlyBg0aRPv27fn3v//N6tWr2bZtGx988AFXXnklrVq14r777uPMmTOebK9UD++//z7Dhg0jPDyc8PBwxowZw+7du+2uv2jRIlQqFQ8++KDV8hkzZqDRaAgPD0ej0aBSqRg0aJCHWy9JkiQ1KSUlEBjY2K2QPG3bNnHnwx0aMpg/dgwKCxtmX43MoWC+X79+vPzyy/zf//0fp0+fJj09nT/++IPffvuNw4cPU1hYyHfffYfRaGTAgAF89dVXnm635ILNmzdz0003sWnTJnbs2EHbtm0ZN24c58+fr7Hunj17eO+99+jdu7fNbY0fP56jR49y/vx50tLS+OmnnzzdfEmSJKkp0WqbTjAve+U9p3dv2LrV/vPOTATVUMG8okCrVnDunOf31QQ4FMw//fTT7N27l1mzZtG2bdsaz/v6+jJy5Ejeeecdjhw5QlJSkrvbeVH5+uuv6dWrF/7+/kRGRjJmzBi0Wi2bN29m4MCBBAYGEhYWxtChQ813QubPn0+fPn149913adOmDQEBAVx33XXkWww0+fzzz7nvvvvo06cPXbt25f3338doNPLrr79a7b+4uJhbbrmF999/n/DwcJtt9PX1pVWrVsTGxhIbG0tERITHjockSZLUBJWUQEBAY7dCkDOLek6bNvaD4tJScCbFuqEGwKanw4ABF00w71DO/KRJkxzeYFRUFFFRUS43yOMqtFDQgIMiQruDl+M9F2lpadx000288MILTJs2jaKiIrZt24aiKEydOpW77rqLFStWoNPp2L17NyqL3ojk5GRWrlzJDz/8QGFhIf/4xz+4//77+fzzz23uq6SkBL1eXyMQv//++5k0aRJjxoxh4cKFNl+7ZcsWOnXqRHh4OCNGjOCZZ54hJibG4fcpSZIkNXNNqWde8pzaLpQyMpybMEqjAaOx/m2qy4kTMGrURTMI1uGc+QsXLjB37lwKbeQfFRQU8O9//5uMjAy3Nu5ilJaWRkVFBddccw1JSUn06tWL++67D51OR0FBAZMnT6ZDhw5069aN22+/3epOSVlZGZ988gl9+vRh+PDhvPHGG3zxxRekp6fb3Ndjjz1GQkICY8aMMS/74osv2LdvH4sWLbLbxgkTJrBs2TK+++47XnzxRfbs2cPo0aMpLy9334GQJEmSmram1DMveVZEhO2qRU119tfkZOjVS3xGLwIOV7N5+eWXKSwsJCQkpMZzoaGhFBUV8fLLL/P888+7tYFu5xUIkZc2divsuuSSS7jiiivo1asX48ePZ9y4cUyfPp2IiAhmzJjB+PHjGTt2LGPGjOH6668nzmLWtbZt29K6dWvz48GDB2M0Gjl27Bix1b5sL7zwAitWrGDz5s3mKkRnz55l9uzZrFu3rtbKRDfccANGo9H8eRg4cCCJiYn8+OOPXHPNNW4+IpIkSVKT1NR65mXevOcMGyby5qdOtV5uSmdpai6ywdkO98yvXbuW2267ze7zt912G2vWrHFLoy5mGo2G9evX8/PPP9O9e3feeOMNunTpQkpKCkuXLmXHjh0MGTKEL7/8ks6dO7Nz50672zKl4Kiq/YJbvHgxzz77LOvWrbMa4PrHH3+QmZlJ//798fLywsvLiy1btvD666/j5eWFwWCwuZ+4uDgSExM5ceKEG46AJEmS1Czo9eDt3ditgPJy8PWVefOeoCjiIikxEVJTaz6fkSEGmjY1F9mFncPBfEpKis3BryatW7fm9OnT7mjTRU+lUjF06FAWLFjAn3/+iY+PD99++y0Affv25fHHH2f79u307NmT5cuXm1+XmprKhQsXzI937NiBWq2mc+fO5mUvvvgiTz/9NGvXrmVAtavpK664goMHD7J//37zvwEDBnDLLbewf/9+NBqNzfbm5ORw9uxZq7sEkiRJ0kXC1xfKyhpv/1lZEB3dePtvyeoa4FpR4fwFXXMKtFNToaCgsVtRJ4fTbPz9/Tl9+rTdgP706dP4+/u7rWEXq127dvHrr78ybtw4YmJi2LVrF1lZWfj7+/P4449z1VVXER8fz7Fjxzh+/LjV3RI/Pz9uv/12Fi9eTGFhIQ888ADXX3+9OcXmhRde4KmnnmL58uUkJSWZc+mDgoIICgoiODiYnj17WrUnMDCQyMhI8/Li4mLmz5/PtGnTCA4OJjs7myeffJKoqCimTZvWQEdJkiRJajIiI0U+dXx84+w/OxuiosBGmWWpnrRaCAoSP4eFibKSdqrcNRnuvEOzejXcd5/7tuchDvfMX3bZZSxbtszu859++ikDBw50S6MuZiEhIWzdupWJEyfSuXNnnnzySV566SWuueYajh49yrXXXkvnzp355z//yaxZs7j77rvNr+3YsSPXXHMNEydOZNy4cfTs2ZMlS5aYn1+yZAk6nY7p06cTFxdn/rd48WKH26fRaDh48CDTpk1jwIABzJw5k86dO7Njxw6Cg4PdeiwkSZKkZiAiAnJyGm//smfecyzHRQwbJiaQauouXABTpkBAgHgPrlAUMBjAy+F+70bjcAvnzp3L2LFjCQ0N5d///jetKnOkMjIyeOGFF/j4449Zt26dxxp6sejWrRtr1661+Zwp1aY29957L/fee6/N51xJg9q8ebPVY39/f3755RerAbBqtcPXhJIkSVJLExnZuMF8djb06yd+NuV4S+5RXFwVzCclwQ8/NGpzHJKcDJ06iZ9btxZ3bCzSjR22fTsMGeLetnmIw1HYqFGjeOutt3jzzTeJj48nPDyciIgI4uPjeeutt3jjjTcYPXq0J9sqSZIkSVJT09jBvCn1IyBA5HhL7mOZZuOuiySNRgye9pSTJ6FDB/Fz69auTxy1ezc0k4wTp+4d3H333UyePJmVK1eSnJyMoih07tyZ6dOnW5VElCRJkiTpItHYaTaKAmo1BAdDUZGsfe9OWm1VygpAaKiYwTUsTBx3V/LTTbPAeio1qrS06jPQujXs3ev8NvR6kV7TTO7yOJ0IlJCQwEMPPeSJtkj1MH/+fObPn9/YzZAkSZIuNr6+oNM1ditED3JxcdMsldhcWabZAFx+Ofz2G0yeLAJyVwbDhoeLuymeCuYtLzBCQsDGZKd1WrcOxo51X5s8zKlk53PnznH06FFPtUWSJEmSJMk5puDNFMxL7mOZZgPQvj2cOiV+dnX2V1Mw35QdOwZduzZ2KxzmcDD/4YcfMmrUKG6//XYefPBBDzZJkiRJkiTJSTKYd7/qs/xapp00xWDeaKx/akz1uxHNgMPB/MKFC1m2bBkbN25kyZIlFDSDIvqSJEmSJLVwpuBNBvPuV14OPj7Wy4KDRepKerp1Pr2jPBnMX7gACQn128aaNTBlinva00AcDubDwsJIT08nOzsbjUaDT/WTK0mSJEnSxakpDBSUwbxnVD+3prz53FzXcuZNA2A94cSJqrKUrrpwofEmQHORwwNg3377be644w5KS0t566235GyvkiRJkiQJ7px10xmWaRXBwTKYdzdbF2kdO8LPP4sSk65cxGk04rx5wsmTMHiw9TJfXygrAz+/ul+fmdksJyBzOJgfNGgQhw8f9mRbJEmSJEmSHGeqMQ/g7+/6bJ+SbbYu0prCXRh7bAXtCQmit719+7pf/8MPMH26Z9rmQXLqTkmSJEmSnFNRIXpYTVSqxumdz86GqCjxs1rdeHcILjZBQaKmf3PgzMRRBQWilj7AsmXQTAq+OBTM79ixw+ENarVaDh065HKDJM9ZtWoVAwYMICwsjMDAQPr06cOyZcus1klKSkKlUtX4d//995vXURSFBQsW0K1bNwIDAxk5cqQ855IkSReTkhLrih+Nla+eldUs0yKavaFD4fTpxm5FTbbuGjgazJ86Be3aVT1OTobXXxepO02cQ8H8bbfdxtixY1m5ciXFdr6shw8f5oknnqBjx47s27fPrY2U3CMiIoL//Oc/7Nixg7/++ouZM2cyc+ZMfvnlF/M6e/bsIS0tzfxv/fr1AFx33XXmdV544QVeeeUVXnjhBXbt2kVsbCxjx46lqLlcpUuSJEn1U71kYUSEGBDZ0LKzZTDfGDp3hmnTGrsV1uyVpQwPr/2zqSiwbRtcc4316++9VwTzzWASMoeC+cOHD3P11Vfz3//+l/DwcHr06MHYsWOZMmUKl19+OVFRUfTv358zZ86wfv16br31Vk+3u0X7+uuv6dWrF/7+/kRGRjJmzBi0Wi2bN29m4MCBBAYGEhYWxtChQzlz5gwgZoDt06cP7777Lm3atCEgIIDrrruOfIsR4yNHjmTatGl069aNDh06MHv2bHr37s1vv/1mXic6OprY2FjzvzVr1tChQwdGjBgBiF75V199lSeeeIIpU6bQs2dPPvnkE0pKSli+fHmDHidJkiSpkZSUQEBA1ePISMjJafh2ZGVVpdlIDUelgvHjG7sV1s6ds12W0l6Of3k5fPIJ9O8Pw4fDgQPw1ltVz8fGwqxZ1pNmNVEODYD19vZm1qxZzJo1i3379rFt2zZOnz5NaWkpl1xyCQ899BCjRo0iIiLC0+2tP60WGnIgb/fuTk0+kJaWxk033cQLL7zAtGnTKCoqYtu2bSiKwtSpU7nrrrtYsWIFOp2O3bt3o7L4kCYnJ7Ny5Up++OEHCgsL+cc//sH999/P559/XmM/iqKwceNGjh07xvPPP2+zLTqdjs8++4w5c+aY95OSkkJ6ejpjLaY59vX1ZcSIEWzfvp27777b4fcqSZIkNVPVe+YjI6Gyc6lB6XSiWokkOVqWMj0d3nkH3n5bVK8B8RkaPhxeftmzbfQQh6vZmPTr149+/fq5rQHnz5/n0Ucf5eeff6a0tJTOnTvz4Ycf0r9/f7ftozlJS0ujoqKCa665hsTERAB69epFbm4uBQUFTJ48mQ4dOgDQrVs3q9eWlZXxySef0Lp1awDeeOMNJk2axEsvvURs5SxtBQUFJCQkUF5ejkajYcmSJVaBuaXVq1eTn5/PjBkzzMvS09MBaFXttlOrVq3MdwkkSZKkFq56z3xEBDSFFNumXGlFquKJ83TqlMjlr8vUqbBrl/g5IQHuvx9iYmDiRNcmwWoCnA7m3SkvL4+hQ4cyatQofv75Z2JiYjh58iRhYWGe22lgIFx6qee2X0+XXHIJV1xxBb169WL8+PGMGzeO6dOnExERwYwZMxg/fjxjx45lzJgxXH/99cRZfPDatm1rDuQBBg8ejNFo5NixY+ZgPjg4mP3791NcXMyvv/7KnDlzaN++PSNHjqzRlg8//JAJEyYQb2PyBFW1L6KiKDWWSZIkSS2UVmud0hAe7rmJgGpTvXqNrGbTPGg0oiKSlxvDUJ2uZllKgwG++w5KS6uW3XuvqHw0e7bIk/f2FrnxzTSQh0YuTfn888/Tpk0bli5dysCBA0lKSuKKK64w9zxfjDQaDevXr+fnn3+me/fuvPHGG3Tp0oWUlBSWLl3Kjh07GDJkCF9++SWdO3dm586ddrdlCq4tg2y1Wk3Hjh3p06cPDz/8MNOnT2fRokU1XnvmzBk2bNjAnXfeabXcdFFg6qE3yczMrNFbL0mSJDUBnpigp3rPvEYjAidJcoQnZoG1vJDLz4eXXhITXF17LezZA3q9eO6222D7drjhBhHItwCN2jP//fffM378eK677jq2bNlCQkIC9913H3fddZfN9cvLyykvLzc/LiwsBECv16M3naRKer0eRVEwGo0YPTXTmAcNHjyYwYMH8+STT9KuXTtWrVrFQw89xCWXXMIll1zCo48+ytChQ/n8888ZOHAgiqKQmprKuXPnzD3pv//+uzl4t3cMjEYj5eXlNZ7/6KOPiImJYcKECVbPJSYmEhsby/r16+nQoQOKolBWVsaWLVtYtGiR24+10WhEURT0ej0ay5rGkluZvj/Vv0dS8yPPZcvhrnOpfu45jI895o4mmakKClB8fKoCJEBtMGBs4M+d2mi02mdjtMERzfV76anjqQoORsnMrKrpbklRUM+fj3HBAqe2qTYYMB46hPqtt1B/+imqygnElMhIjCEhGFNToW3bmi80GFCDU++zoc6no9tv1GD+1KlTvP3228yZM4cnnniC3bt388ADD+Dr68ttt91WY/1FixaxwMbJXbduHQGWPQSAl5cXsbGxFBcXo9PpPPYe3G3v3r1s2bKF0aNHExUVxR9//EFWVhYADz/8MBMmTCA2Npbk5GSOHTvG9OnTKSwspLy8HD8/P2699Vb+97//UVRUxOzZs5k6dSoBAQEUFhby8ssv07dvX9q1a4dOp2P9+vUsW7aMl156yXxhBCKA/uijj7jhhhsoKSmp0ca7776bRYsW0bp1a9q3b8/LL7+Mv78/kydPttqOO+h0OkpLS9m6dSsVFRVu3bZUk6kUqdT8yXPZctT3XA5cs4bdvXu7qTVC2127OOfjg9Fi8Gm7Q4dI+eknt+6nLtX32RhtcEaz+l4aDCQdPsxpDxzPsBMn4NAh8jt3rvFc4Pnz9Niwgd2XXeb4BnU6Rr7yCqEWkzwVtm3LySlTODd8OMHnzqH++mvyunat8dLgM2fwLSwk24X36enzaSsGs6VewXxZWRl+1fOTnGA0GhkwYADPPvssAH379uXQoUO8/fbbNoP5xx9/nDlz5pgfFxYW0qZNG8aNG0dISEiNtp09e5agoKB6tbGhxcXFsXv3bt59910KCwtJTExk8eLFTJ8+nXvvvZcZM2aQk5NDXFwcs2bNYvbs2ajVanx9fenYsSPTp0/nxhtvJDc3lwkTJvDee++Zj43BYOCRRx7h3Llz+Pv707VrVz799FNuuOEGqzasW7eOc+fOcc8999Q4rgBPPfUURqORuXPnkp+fz2WXXcYvv/xCgq2SUPVUVlaGv78/w4cPb1bnsbnR6/WsX7+esWPH4t1CbjterOS5bDncci4rKvB68kkmTpzo1rapz5yh59SpVgMZ1WfO0M3N+3GkHZb7bIw2OKJZfi8LC1EVFNDdE8czORnVyZMoNspbqpYtQzV1KhPHjAEfH/vb0Omqnj9zBk1cHEpqKsrEiRgfeAD/kSPpqVLREyAzE9WWLSg23ovq009RbrkFbMQ79jTU+XS0g9TpYN5oNPLMM8/wzjvvkJGRwfHjx2nfvj1PPfUUSUlJ/OMf/3B4W3FxcXTv3t1qWbdu3fjmm29sru/r64uvjRJU3t7eNQ6mwWBApVKhVqtRqxt1aIBTevToYTWJk6XVq1fbfZ0pL/7++++3mq3V0jPPPMMzzzxTZxuuvPJKlDoGEc2fP585c+YQEhLi0eOrVqtRqVQ2z7HkfvI4txzyXLYc9TqXOTkQG4u3SuXewYYaDZrqgZZGg6YhP3MlJRAUZL1PLy80Xl5NsqpN+++/x3vixObzvdTpRBqMJ9obEwP799vetlYLw4ahOXEC+vSp+fzZs6Ie/AcfwM6dIi/+9Gn473+hUydUHTvWHBAaFwd5ebb3V1IiSqu6wNO/Zx3dttNR2MKFC/n444954YUX8LH4Ivfq1YsPPvjAqW0NHTqUY8eOWS07fvy4uSSjJEmSJEn1kJ4uAqJqRQtahOzsmhNG+ftbVy5pKsrKiNm/v7Fb4ZziYqfmyXFKXQNgL7lEBPsmigI7dohBq+3awfPPiwvVTz8Vz586BaNHi8DeFrW6RVc6cjqY//TTT3nvvfe45ZZbrAYk9u7dm6NHjzq1rYceeoidO3fy7LPPkpyczPLly3nvvffs9ixLkiRJkuSE9HQYMEDMjtnSZGVBdLT1sqAgEYQ2NUeOoPdUYOwp1ScGcyeNxnaVpdxcUeY0JASKisQA688/h8sugyFDYOVKUTVp1ChYvRrmzROvc3XysNLSmuUsmyGng/nz58/T0caVj9FodHpU76WXXsq3337LihUr6NmzJ08//TSvvvoqt9xyi7PNuujNnz+f/c3tql+SJEnyrIwMMV19QwTzanXDlqfMzm42wbzq778pslVJpSnTasXxbEg7d8LgwVWPdTqYNUuUlvT1hZkz4cAB2LgRrr5aXBTUx59/ghsnQm0sTifQ9ejRg23bttVIhfnqq6/o27ev0w2YPHkykydPdvp1kiRJkiTVoagI2reHdes8v6+wMCgoELPBNoSsLNFja6mpBvOFheirVd1r8oqLRW57Q9q6FX7/HRYuFI8DAuCxx0QP/d1317x4q6+//oI77nDvNhuB08H8vHnzuPXWWzl//jxGo5FVq1Zx7NgxPv30U9asWeOJNtZLXQM5paZNnj9JkqR6aqh84chIkcfcUMF8QUHNOuVNNJhHpcLg4wNlZfUbUPrttzBhQsOkhngyzcaSwQBr1sBrr8GmTWLZ6NEiN/70aXj00bpf70gPvenOkeW6lhVxmjGn02ymTJnCl19+yU8//YRKpeK///0vR44c4YcffmDs2LGeaKNLTCOAHa3RKTVNpvPXbEb/S5IkXawiIkQw31AUpWbVmqYazAP64OD6H5+DB8FOxT+383SaTWmpCOA7d4apU0Ugr1bDddeJOwJ9+lgPgrUnNRXatKl7vdhYkXbWArlUp2r8+PGMt1EbtCnRaDSEhYWRmZkJQEBAgLl8o1R/RqMRnU5HWVmZR0pTKopCSUkJmZmZhIWFydlfJUmSmrrISDhypOH2Z+tvenBw0wvms7NRIiLQabUimE9Kcn1bERGQlmb7QsbdPNkzf/w4PPWUuFMBYtDrlCkiqJ82TSxTFHEnoi4nTkCnTnWv17q1GDsSHy8eN+RdJA9zOpg/e/YsKpWK1q1bA7B7926WL19O9+7d+ec//+n2BtZHbGwsgDmgl9xHURRKS0vx9/f36EVSWFiY+TxKkiRJTmrITixTmk1jCgoS4wSakoMHUXr2RFdQgModx2fYMPjtN/G/JzmavuIIRREpM+3aicedOokxFuHh8MADcOut8NlnYDmpk6Of3aNHYcyYutdr3VoMsB04UDzes6fq52bO6WD+5ptv5p///Ce33nor6enpjBkzhp49e/LZZ5+Rnp7Of//7X0+00yUqlYq4uDhiYmKcrrQj1U6v17N161aGDx/usRQYb29v2SMvSZJUH6ZceZVKlAL05CSKwcHg4IyVHhMQIHqUm5Jjx+C229D99Zd7LnYuuwwWL/Z8MO8OpaWitORrr4k7Cqmp4hypVKJKzRNPVAXtrpaXVBTHPtetWlnPt3DiBIwb5/z+miCng/m///6bgZVXMitXrqRXr178/vvvrFu3jnvuuadJBfMmGo1GBoVuptFoqKiowM/PT+azS5IkNUWWg/tatYLMTJE37ClNIZW1KU4OVFEB3t7ogoJQuWvyrrZtRWDcVMtdnj8PS5bAu+9WXcAEBopSkEOHiseRkaL338tLnDNb5800DsPeDK1paWJ2V0dUr23v6EVAM+D0u9Dr9fhWXjlt2LCBq666CoCuXbuSlpbm3tZJkiRJkuSazEwRxENVvrDU8CqDVMXLSwT2riopEb3aIHLLHcknb2jJyXDzzWJcwLPPikA8MVHcSTh3riqQB5FiY5oFNjVVrFddnz6irrw969eDK8VXmtoFXz05Hcz36NGDd955h23btrF+/XquvPJKAC5cuECkvSsnSZIkSZIaVnp6yw3mDYbm0ataPbWpPncvMjKqzqePj+jRbmoV+wwGWLFCXLQMHy4q7yQnw8MPixx5S+HhkJcnft6+XczwWl2XLiJNyZ68PLEdZ6Wm1m8gchPj9Dfh+eef591332XkyJHcdNNNXHLJJQB8//335vQbSZIkSZIaWXp6VVpNbKx1vnB9GI2Nn1KTm2s/9aKx22bp1CkxaZdJfXqELYN5gOnTG65MpS05ObBoEcyeXbWsSxd46SXYtw+2bIFrrhEXHbZYBvNZWbYnhKrtboZeb3/b9pg+G7t3w6WXOvfaJszpnPmRI0eSnZ1NYWEh4RZXQ//85z8JaG6zm0mSJElSS5WRAVdcIX7WaESvqTuUllalezSWrCyIimrcNjji4EH3BY3p6dC/f9XjVq3EOW6IMpWWDh0SA1qXLROlJTUamDu3qtb7nDmObSc8HE6eFD+70v7t263TdhxhGgienu54rn0z4NI9Ko1GYxXIAyQlJRHT0NP+SpIkSZJkW2kp+Pu7f7uWuduNJTvbdk8uNK186HPnICGh6nF9gu7MTDGZkqVRo2DzZte36SijUczSOnYs9OwJ778vAvm+feGjj2q2yxGmnvmiotonp/L1rapHb+nAAajMDnFYdLT47LQwLk0a9fXXX7Ny5UpSU1PR6XRWz+3bt88tDZMkSZIkqR481VvrycmEHJWV5dhEQU2B5Xmoz4WGrdKN/fuLwaWjRrm+XUe8/z7cc4/4Wa0WEzvNng2XX+765ywsTAyA3bVLlNu0p2dPcTfA8q4EuHZHonVrUe++OYy3cILT7+b1119n5syZxMTE8OeffzJw4EAiIyM5deoUEyZM8EQbJUmSJElylqd6qGvrmff2FkGnp2VnN480m4aQmAgpKe7dZkoKnDlT9fiGG0QgPHeuSI35+mtR574+F4ym1K+jR6FrV/vr9e4Nf/1lvezsWdEeZ7VuLSrg9Ojh/GubMKeD+SVLlvDee+/x5ptv4uPjwyOPPML69et54IEHKCgo8EQbJUmSJElyB3cE+LX1zEdEiMGpnlZZu71Js3XRU9/ylLa4q0ylosDWrWLQaseO8OWXVZ+XsDDRo/3ii+6vAlNXvfegoJoTgW3Y4Nisr9XFxsIPP9Ts5W/mnA7mU1NTGVJZPsjf35+iymmTb731VlasWOHe1kmSJEmS5JrqvaZRUe6ZgbS2nvnIyIYJ5puDw4ehe3erRYonLna8vUXwvXu3a68vK4OPP4Z+/WDECHFhYDSKc1wZ4wGiJ93dDAbXeveLiiA01PnXeXuL1wUHO//aJszpYD42Npacyl8GiYmJ7Ny5E4CUlBSUpjToRJIkSZIuZtX/Jrur1nxtPfORke65YKiPplKa8u+/Rb63pchI1wdg1va+rroKNm2yDr4dsWyZmEV25kzYv18MmL77btH2WbMgJMS1tjrq0KGax8ge0+yt5eX1uyszd67rr22inA7mR48ezQ8//ADAP/7xDx566CHGjh3LDTfcwLRp09zeQEmSJEmSnGSrko27gvnaeuYjIho/mFeUplHRpqioRg+w4snjM2sWvPVW3etZligNCRGDiVu3hueeE5+Pd94RPf0+Pp5pp6WCAnBkjqIOHUTNfoDffhP5+q5yZcbYJs7pajbvvfcexsqro3vuuYeIiAh+++03pkyZwj2mkc6SJEmSJDWejIyqCaNM4uLgl1/qv+26euYbO83G31+kjniiLGd9RUWJHnBnlZbWrGRTXWAgjB8Pq1aJvHdLFRWwejW8+iqMGwf//a9YPnmySKuZNMm6t1urrb1cpLvcfbdjZU779IHffxcXGX//DaNHe7xpzYnTwbxarUZtMVDh+uuv5/rrr3droyRJkiRJqof0dOvZQkH0tLpj8GVJif1A2d9fBJ6NKSgIioubZjDvappN9dlf7enbV8y+mpIC7dqJOu4ffABvvgmpqWKd1FR48kkx6FSjEQNoqysubpjyo46W1IyLs57BuKmkUjURLhXa3LZtG//3f//H4MGDOX/+PADLli3jt99+c2vjJEmSJElyga2eeXcxGl0bDJmSIkoK1lddKTSmYL4x2Qu+/fxEzre7tmfLzJnw8suiLnzr1vDIIyKAj4qCp54Sdd3rqrPeFOYSsMV0kSJZcTqY/+abbxg/fjz+/v78+eeflFd+KIuKinj22Wfd3kBJkiRJkpyUkeHarJye9N57YtbO+qorBaQ+wbwjOeeO+OsvUR/dXZwJ5tVqkZf/7rviLkrv3mKW1rNn4X//E73cdWmoNBtnbdwoU2xscDqYX7hwIe+88w7vv/8+3hb5VUOGDJGzv0qSJElSU6DTNcwARkelp4vJjTIz67+trKzaJ4wKDnY9mP/9d9deV11yssjvdpfagnmtVgxaPXiwatljj8GgQfD66yJHf+ZMcVfAUU2xZz4qSvTMe+Iiw6iH7J3u324DcTqYP3bsGMOHD6+xPCQkhPz8fHe0SZIkSZIuLifede/27OUUN1all5UrYcYM9+TTZ2dDdLT9513tmddqrWc9rY+KCjFBlLuUl9cMxlNTRQpN69Zw772weHHVc717w44d4nPgSn55Q+XMO6NvXzHmwBPKMiFzq2e23QCc/qTFxcWRnJxMUrUZwH777Tfat2/vrnZJkiRJ0sUj/2Dd67hDWBgUFro24Y6riopEYOtMz3BtsrKgWzf7zwcFOV9vHUTvd0MeF1coirh78NprogqNqcxk+/aiJ95dmmLPfJcu0KmTZ7ZdlgnljVxStR6cDubvvvtuZs+ezUcffYRKpeLChQvs2LGDuXPn8l9TqSNJkiRJkhxjrIBSN9R/d0RCgqgl3pBB6xdfwI03um97WVm11xl3tWc+M1OksihK/aqlVFS4f7ZUU3umToXvv69aPno0PPggTJzo3n021Zz5ugbuuqosE4wuDExuIpwO5h955BEKCgoYNWoUZWVlDB8+HF9fX+bOncusWbM80UZJkiRJarl0+aBvoOorrVvDyZPQo4dn92MKiPV6EVhHRLhv28XFtQeaAQEiGHVWZiZ07SrKOdanve7Ml8/MtG7LZZfBunXwf/8HDzwAvXrVvQ1XLk5qKz/aEpVngV8TGzDuBKcucQwGA1u2bOHhhx8mOzub3bt3s3PnTrKysnj66ac91UZJkiRJarl0OeAdXPd67mDqmfekgICq3PjqExi5K1+/tuBUoxHlM52VmSlyzdPSXG8XiIGotVWyUanqbp9p0GqbNvDdd1XL779fVKV5/33HAvnISHFx4oqLqZa7vgC8m3iKVS2cCuY1Gg3jx4+noKCAgIAABgwYwMCBAwlqirdiJEmSJKk5KM8BnwbquTbNjupJkZGiNKKiiAGliYme3Z8trgSiZWWQlGQ9OZEr6iojGRYGtgqGGAwiD37kSDHY8+OPRVWiDRuqLoJCQ2uv5FNd+/biTozUojmdfNSrVy9OnTrlibZIkiRJ0sVHlwu+bgzmbc3+2pAiIkQwv349jBtn/ZwjvdKNqfpMo66oq4KM6WLHxGgUkzx17CjuYmzZIu4u3HCDqEjzyivg6+taW9q3BxmztXhOB/PPPPMMc+fOZc2aNaSlpVFYWGj1T5IkSZIkJ7i7Zz493XOzvzoiMhJyc8UEUX361HzO1bSPhhAaarvX3Bl1pRJFRVkH82o1fPUVnD4tLoQef1z8/MUXokJNZqbrE4BFRYkBw/Vx6uP6vb7ZUIHShC80a+H0ANgrr7wSgKuuugqVxZWnoiioVCoMpjJJkiRJkiTVTV8k8nUVI6jcUK0jI8O9ExY5KzISPv0Urrii5nMxMSI49VS9cBNXc/NVKs/W4VcUOHIEliyBH3+E8HCxfP58UTf+llvEmANLzsz+Wp078t4zt0L7GfXfTlPnEyZy533CG7slTnM6mN+0aZMn2iFJkiRJFy/vYKgoBu+Q+m+rrhlSPS08XNRCf/bZms+Zgvna6sS3RKWlJK5bh9cTT8Dhw2LZBx/Av/8tfh4/3v5rMzLqV32ovgF9wRH3XWg2ZT6RlXfJLoJgfsSIEZ5ohyRJkiRdvLyCK3vo3RDMGwy1zz4aGFh3eUd7HOm19vaGd96xHUTGxFQFs67Q6907s6ot7qzicu4cLFmC17vv0ic3VywLDIQBA2DaNMe2kZEh6sm7qr53GjQ+UJ7drEs3OsQ3UrzP4Ea8q+Uipy+zli5dyldffVVj+VdffcUnn3zilkZJkiRJ0kXFOxj0DTTurHVrOH/etdfqdI4Nxuze3fbyyEjIznZt3yBy8T2RomMwuG/SJdPFQGEhdO4Mixahys1FGxOD4YUXxLG/7jrHU6HKymqm3jjD21ucN1f5J0CJi5+X5qBCC5oA8I1qtrPAOh3MP/fcc0TZuH0XExPDs7ZuqUmSJEmSVDtTz3xDaN3a9VrzWq3oWXaVqzXgTbKzHUshcrZ33XK7rvZkm8pImoSEiN73ESOo+OorNrz9NsYHH2zY2XdBlAZNTXXttYoCAQlQesG9bWpKyionjDL1zDdDTgfzZ86coV27djWWJyYmkurkh2X+/PmoVCqrf7GNOQJfkiRJkhqDdwhUNFAwX5+Jo0pK6tdLDPVLY8nKgujo+u3fFsuKMT4+UF7u+Guzs+GZZ6BdOxg71nrSqaVLYfNmlKuvdl/Pv7PqU57SUAJBHaG0nhNpNWVlmSKY9woS41aaIaeD+ZiYGP76668ayw8cOECkC7e+evToQVpamvnfwYMHnd6GJEmSJDVr3g3YMx8cLHLmXVHfnvn6crRn3tnedctgPjZWPK7L33/DXXeJWVqffBIuXBCvtSw76ePjXDs8ISlJlLp0hun46fJFoGusR5pOU1deGcw34xlvnQ7mb7zxRh544AE2bdqEwWDAYDCwceNGZs+ezY033uh0A7y8vIiNjTX/i/bEFbckSZIkNWXewe7pmfdkWUVwT898feTkiFrsjnDmWFiWf4yNrX3iqNRUUXazVy9RkaasDPr3h2XLxIy39ak8Y0t9z6mPj+s58/oCUTYVD3+uGlNZJvg279jT6SHhCxcu5MyZM1xxxRV4VY4oNxqN3HbbbS7lzJ84cYL4+Hh8fX257LLLePbZZ2nfvr3NdcvLyym3uPVlmqRKr9ej1+ud3rfkOtPxlse9ZZDns+WQ57KZMepQoUFRfFGX5WO0OG8uncv8fFRBQSh1vEZtMFjty1GqggKUoCBRVcZF6ooKl/YNoC4vxwh17l/l7Y1SXAx+fo5tNzsbY2Cg2G5kJKoDB1AsJ7xSlKqe2/BwvP76C9RqlKuvxjh7NsrgweJ5gwG1otR4f9XPpTPH39Vz5fI2jEbze1CV5qCog9zShqZKrSvGqHiDXu/w+2yo37OObl+lKK5d8h0/fpwDBw7g7+9Pr169SExMdHobP//8MyUlJXTu3JmMjAwWLlzI0aNHOXTokM2Unfnz57NgwYIay5cvX05AY/YUSJIkSZILfI15RBiPkOY1hHb6n0jxnliv7QWdO4d/Tg5Zl1xS63rtfvqJlInO7yv6zz8padUKbXy8q02k3Y8/kjJpkmuvdbDd8b/9Rnbv3uhCHCv1adkmtV5Pm40bOTN+PAHp6bT/8Ucijhxh6wsviNlaEcehOCGB0mozs3qVlhK3Ywdn6ygl2e6nn0iZMKHO1A6VXk/byrbUhzPHXFNWRsLvv5N6xRXEVPxBsTqeVoY/6/3ZbKosv3fu+A66U0lJCTfffDMFBQWE1PJZdrlYa+fOnencubOrLwdgwoQJ5p979erF4MGD6dChA5988glz5sypsf7jjz9utbywsJA2bdowbty4Wt+k5H56vZ7169czduxYvL29G7s5Uj3J89lyyHPZzBQcQlWegBIzEnXyGbp1rAokXDmXqq1bUSIioGfPWtdTnzlDNxeCeZVOhzJwINQjmFelpdFt9GiHe80tOdpulUqF0q2byBd3ZLunT1dtV1FQb9lC7w8/RLVmDarKPs9Jfn4oY8aIdey1IT0dFdCr2vPVz6UqO5tuw4eL8Qu1OXcOlaLQw4VzZUl9+jTdHLh4ACAzE5XRSM+JE1GlFqG0ugL1WZ3VZ7MlsfzeVf8O2tNQv2dNGSh1cTqYNxgMfPzxx/z6669kZmZirFZiauPGjc5u0iwwMJBevXpx4sQJm8/7+vria6O+rbe3t/yj1UjksW9Z5PlsOeS5bCaMRRAQI2qBa7zQ2DhnTp3L7Gy45BKxvdoEBKAxGJwPqMvLRWnF+ny24uMhP18MHHWWRmPzGNUQFiba6mg7NRpxPJYvh9deA8tCH1deCbNn4zVunLln3i6drtbjYz6XsbGiDn1d+f+5uaKUaH2/y61aoSkqcqxGv+U5NmohIAp8AtGoKsDLv37taIosP1OOfr4qefr3rKPbdjqYnz17Nh9//DGTJk2iZ8+eqNw4+re8vJwjR44wbNgwt21TkiRJkjzm9Gkx6NHV2dHLcyCoZrlnlzk6QNQ0cVSHDs5tv6Sk7mo2ihHyD0K4nVSfmBhRLcaVYN5RQUHOV+zZvRv+8Q/xs4+P+PmBB6BrV8e34Wi1H9PkWXXdOcjIcG7/9rRvDydPOhbMW74HpQLU3uAfL2rNBzv5eWmOLMdHNBNOB/NffPEFK1euZGI9b/kAzJ07lylTptC2bVsyMzNZuHAhhYWF3H777fXetiRJkiR53PnzrtdsB9DlgI8pwHJDxRBFqbv3GKomjnI2mNfr6+4lzj8I576vPZg/dsy5/TorKEhcZNVmzx44cQJuvlk8HjYMrroKLr9cPP73v53frzPBvCO13zMyXL9QtNS+vZjQauDAutfVasXxg6pKOv4JUHq+5QfzXsGi1rx3HelPTYzTpSl9fHzo6OgUxHU4d+4cN910E126dOGaa67Bx8eHnTt3ujSYVpIkSZIaXE4OFBS4/vqK0sZJXWjd2vna447K3l57MBQTI4JUT7LXM19RAStXwtChIrC9916R7gKiN/a770QQ72pRDUdLd0ZFiZ55R7bnjrr+pjsBjigurrnPgAQoOV//djQ11WvANNNZYJ3umX/44Yd57bXXePPNN+udYvPFF1/U6/WSJEmS1Kiys0Wd8eYmLEykunhiRlWjXqRm2BMY6NqkVc7UuK8ezOfmwvvvw5tvVt1J8faGq68Wx8HUE23JlXQLR3vmQ0PrdxHoLGfeh+V7ML3OJwJ0ue5vV2PTF4B3WNVj3yj3p741AKeD+d9++41Nmzbx888/06NHjxrJ+atWrXJb4yRJkiSpSSstBRuFGZqFBx+EZ56BJ56oe6bS1K8g4eq6t1mhBY1/7TOGutoRWNuFR2kG6AshpJN4bHnB8M03cOut4lyB2Ma998I990BcnEh3qVZiktBQ0WMfGupcGx0N5tVqxyaDcuckYI4ed8s0G2df29yUZYKfxWfKNxKKTjZee1zkdDAfFhbGtGnTPNEWSZIkSbqINXDA5O0Ns2bBK6/AI4/UHrDl7QeNA73imVshZgSkb6h9PVeCw+xskZ5iy5kVgApCZoPRKHq9TYFw//6iQkufPjB7Ntx4o3UVn8zMqtlfTWJjIS3Nc8F8U2YrzaalKs8CP4sLOd9IyN7VeO1xkdPB/NKlSz3RDkmSJEm6yNWzF9ZodD5IjooSNdM/+0z0XtvjHw9Fx4E6evALj0PclZC+3rl2OCI72/aA3bIs8A6B/Cx46y14/XXo1g3GjRPPJyWJUpPdu9s+PhkZ0K+f9bK4OEhPd76STHl5071T4+0tSmfWdRdGr697nZaiLBMiL6t67B0qUm+aGacHwEqSJEmS5CbVg8v6pFXk5jpWerC6Xr0gPBy2bKl9PbUPGCvq3p6nUjLspdn8/ia89ReM/p+403D8OGzdWpVWA9Cjh/12ZWbW3G5srAjmndWUyxomJtZd4Qfcm9rT1JVniTx5E5Uat1SVamAO9cz369ePX3/9lfDwcPr27VvrwNd9+/a5rXGSJEmS1KJZBk4aPzCUuV7dJj29ZrqIoyZPhrffFrXf27e3vU7sWCh8xf42tGch0FQ73gMBbUEBWM72vns3LHoavv8RjJXHMakVzH0Kbr8dPvnEse2Wl9ecPCs8XFwcNSa9HrycTqCwr317MT6gUycXN6AScwioWlA/sFEPmuZ/F8KhT8nVV19tnnl16tSpnmyPJEmSJF2cvEOgosj1YD4jAxISXN//PffA00/Dww/bzpkO6SxSWuzu/1doPbXygYODO53txbZcf+9eWL1G/Dx2rMiHb3ccut/v3DYtlZwXZRgdHaDqSVlZNQfm1kdiImzaVPd6pmNsNFgH7qZKL35urn4k1ZtDwfy8efNs/ixJkiRJkosqSsDLYlCpVzDoi6wH5DkjPV0M9nSVSgVTp4og2XKiIsugVq0BQzlobOSF6wrAJ8yxfYWFQX6+6AF3REYG/PSTyPG/4Qax7KapsGMlPPaWSKMBOHFW3N3Q+NndlF0GHey5F0Z87/xrTdyZYpOR4fqdFlt8fERvf11M57uiELws7oQEVE4cJYP5JqcF3SuRJEm6iKSlwbZtjd2Ki1tFBWg0rr9elyvqd5t4B4ueeQsGxeD49vLzna++Ul2HDnCyWmk+Qwl4VfbUh3SFtHU1X1e9F7cuMTEiV70uf/4JM2ZA27YimF+4sCrYzP4BPvyuKpAHiBkJGZvFz84G1nn7wTdaTOTVEPz8rPP6q3N3MA/O3W3QFYCPxefJv4VOHNUCyGBekiSpOcrKgv37G7sVF7fcXIiIEEGj0ej868tzRCk8E69gUSu90rnCc2zO3ezcNuvbMxwYKCZnslSeXTVI0C8Gim3U4c79AyIGOL6fVq3sB/MVFbBqlbg70K+fyH3X6URVmv/8RwSkFVpRy96n2sVLSBcoPOZ4O6DqmOX9CZ1nQfbvzr3eVZGRYgZhezwRzDvCdDyqT6jkHw+laQ3fHqlOMpiXJElqjoqLHatMIXmOqe559dlGHWXZM//996JnXl/VM59enE5uRSMMwqzee2sZzIOoamOoNuttzm6IvLT27ViqrWf+zjvh2mtFRRovL7jpJti5E+bOFTXi1Wo4vQKSbq75WpUKUJzrgTata9RBeB8oOOz4a+sjKqr2YL642PbMtPVV17ExPa/Lt75Y0viAsdz97ZHqTQbzkiRJzZFWK6pwSI3HFMyHhopKK84y9czn5cHHH4sBsBbBfIY2g1JDA6V81KYsG3ws7iDEjauZaqMYQG0xDE/jV3vgFxUl7i4BHDtmHdjfeKPotX7iCTh9GpYvh8ssaoEbyqCi2PquhqWQblB41LGA3ipVqtqAXC8vx3LMLTlzEREZKT5DtW3L3WUuo6Nrv4CwpC8QdddbKnupYRp/MZ6lGXE5mNfpdBw7doyKCgdqzkqSJEnu1RJmmmzu6hvMm3rmd++G1q1Fmk2FdTAfYjkAsaGoVNZBaXk2+EWJwNfLC4I7QvGpqud1BeJCxJImQKTC2KPRwMGDYsKqrl3h1Vernhs3Ds6ehWeeqarOYzkh1pkvIPEm+9tuNQIy66iZb5KTI85hyXmRRgIigNXli7sHWbVU76mvutJsPMFUnrI2puOsy3d8QHNzpMu1vkg18Y0UF9rNiNPBfElJCf/4xz8ICAigR48epKamAvDAAw/w3HPPub2BkiRJzVVybjIHMw56ZuNarWduwUuOy8kRAZmrwbypxvWJE6L2t8ZHpHpUKqsow0fVCDWwo6Kse4z1+SLALSmBgMrqOxrfqlSbjE3QapT1NrwCbfdulpTAu++KQatLlsDPP4vgMc0iF1utBv9q5TktK9+U54J/LbnkGj9RcQfq7ik35aVn74CoIWJZq5FiEK0rE0c505MeEdHwtezbt685wNmeimLwasG/Y8oybVeO8o0CXQsP5h9//HEOHDjA5s2b8bOYZGHMmDF8+eWXbm2cJElSc5ZenE5asYcGjGm1lT2Kzet2cJOSnFy/WuI6Hfj6imC+sLDu9asz7VtRRNlAnc7qaZUnJl5yRMeO1gGfooh0BMu7QXHjIe0X8bP2DAQlWW/DK7Bmz/zTT4s7EPfcA0eOiGous2eLGVuXLq29Taa7IMYK63Ke9niHgMZY45jWkJkpeuBL0yCgsmc+MBFKUkUwn+bBAZ9eXmBwolqRO0REOH43oKVNEFVduZ1g3uci6JlfvXo1b775JpdffrnVTLDdu3fnpKNXe5IkSReBYl0xJXoPBds6nQi6Ku+OSi547z3XetSrc7VnHqryouPj7QaOSkNPXtShg7jQMTH9rddqq3rmg9pDcYr9bWgCRM+upfR0MT6gfXuRVvP00+L/jh3rblNWlsj3LssAPwcqvMSOAcOpugcmm4J5m9sQPfPlFeWk5NXyXj3F3fny7timxq/hSnd6WlmmKEVanW+kSC1rRpwO5rOysoix8cHXarVWwb0kSdLFTqvT2g7mv/jCPT1yiYligKDkmtRUuHCh/tsJCXE9mE9OFsFz69Zw7lyNp4O9gsktdSAVQ68Hb2/X2lBdeLhIa6mupMR6nIbGF/L/huAO1uvpdPDtZhhzq6hCY/Lww/Ddd6Infvbsmqk0tTH1zJecF/XO6xLYBjTFdQfzeXkQEiAq9FjyjwPyoayMTG0mXx3+qu59uvOiq75zGNSmtljNcr+21vOPh1I3fGeagurzPJj4hIMur+HbUw9OB/OXXnopP/74o/mxKYB///33GTx4sPtaJkmS1Mxp9XaC+V27XEvLsKRSQZs2YqCg5JrISPekUXh7iyDIFbt3w8CBFsF8VQCloBDuHc6FYgeCp7w8x2dTdZVlzzxA3JVw4AkxUROI3vOFC0U9+LufgP1H4Y03qtZv3x6uusq1INUUzJdeEDOROiLQH4rq+J4pCuTvh/C+1sstJp/S6rUcyT5S9/50OpEu5Q6m99vQ6hqL4185C2xLoBjFjMbVqb1EdaZmxKvuVawtWrSIK6+8ksOHD1NRUcFrr73GoUOH2LFjB1u2ODh6XJIk6SKg1WkxKjYmEzp3TvTk1jf48vO7eMtTnvsOWl/t+uvLy8WdDU/mRNdFpRIDICMjRVBpo0xhhHcE6cUODMLMzfV8MF9SYr2PoHYQeRkcPgmvvSZKSJo+j7Gt4NbR8O9X7W/P29vxALisTHzey9IdS7MBiLsEzu+Bnr1qXy/vT2j/D+tlftFQngVo0Oq06Ax15N6DeytMeXLCKG9vcZ58fWs+V1xc+3sISIC0Q55pl+Qyp3vmhwwZwvbt2ykpKaFDhw6sW7eOVq1asWPHDvr37++JNkqSJDVLCort9EONxnYag1Mbr7ylfzGmN5amw7HX6reNkyehf//6nwd3qVYOskRfQoB3AOFe4Y4Nos7LE4MbPclWsNr9cZg6VQxgLS+HSy+Fzz+H5L/h3gkiz92e6GjnSz9Wr2dfm4TBcGFf3euZqgrV2JeYfEqr1xLkHVT32AXLaj/1tWMHdO7snm1Vl5RkPz3P8hzber8+ESI9RWpSnArm9Xo9M2fOJCAggE8++YS///6bw4cP89lnn9GrVx1XvpIkSRcZRVFsBwBhYe4LIht6cGRTcP4HiJ9ccxZSZxw9Ct26Nd7FkKJAmc527yiQUZxBTGAM/hp/tLpa6rWbuDvNxjQOwPLzVVIixnq89VZVlRi1Gh56CK6/HrZvFylkN98M/mG115mH2meBdYeQUNA6MljTzmcguCOUZ6PVaekS1YXzRXWkl7irZ37zZnHXyFM98927w2E7s9zW9R4uxs6DZsCpYN7b25tvv/3WU22RJElq+fR6kQvrjioqFyt9EUQOgMLjrm/j/HmIi3P99Tpd/QacVhTDsVzo18/m0xnaDGIDYwFxh6dOubnu7Znv0EHcvagoEmUek5Phgw+gd2+YNQu+shgQ+sAD8OWXMHhwVbDnSN5xq1aeDeaDg8EQDIUn7K9TngcBrW0/FzMcipLR6rUMiB/A4Sw7AbCJK8F89VlmT58WgfaECc5txxkJCTYHWwMizcaUMy8D92bD6TSbadOmsXr1ag80RZIk6SJw4YLoGatvz7zpD60p7/hiUXgcQjpDSHcoqCO4qkt9ghXTzKGuKs+Bk7kiOLbRnvTidGIC7ZRMtKWwUASv7tKxowjgf/kO/vmmSPn49VcoKhJ3NBwKWus4vp7umQ8MBJ/OcM5OJ6SigDYFouwU7/AOBj8oz8umd6venMyto/y2K8F8ZGTVxFElJfDpp6IOvyfV9rmvK81GapKcHgDbsWNHnn76abZv307//v0JrPbBfeCBB9zWOEmSpOZMpVLVTLM5e1YEQ9u3u2cnbdqIXrb27d2zvaYu7RfodA+ovSsHKLrIFNC4GrDUt9qILgcUX+vBn2o1GERVnIziDGKSnAjmFUW83l38/eHBB60HCHfvDq+8AmPHOnghVMexDQ6uf1Wn2mg0ognBnaHgCIR2s35eqwUfHfjH2t9GdAiqtDRCfEOoMNZRsUirFXd78vZDeB/H2hgZKT5LMTHi2D74oHvPY21McxxYMgXzhnJRerSlMujE75AWwulg/oMPPiAsLIw//viDP/74w+o5lUolg3lJkqRKNvPlz54VwVD9Ny7+T0yEM2cujmBeUcRgxfr+Ea5+XmwFNXXJzq5fTnN5bs2ZTGNiIDcZjBVUGCvwsTUo05OKiqp690NCRFAX4Af/dx3M+Q9s2ADjxlm95KcTPzGx00TX9ldt0G+dKrRiMipntb4KjiyuGcxnZEBkLWUYAdoPoNXhjagdmQnVFAgfmA0jf6x7fRDBfE4OfPQRTJ8ujntDSEwU8ywkJlovN6XZ6AvAO9TOi1WufWeakvIs2xNGmah9RMDf0N9BFzl9+ZeSkmL336lTpzzRRkmSpJYjJ0f8AXcXUzB/McjZBVGDLBa4GEykp1fly4eEiCDWWfXtmT93EuKSrJe1bg1Z5SJP3YIKG3d43Mk0aDU+3jrt5aab4PeX4c23oEsXmy/9/ODntWzYTcGeqXxlyQUxaZEzFAVUagjtLia4spR2FqLr+C52HUtsetXsr7Weh5ISIFf0ajsqKkqMP0hIsHuMHZK927n1+/eHah2yQFVFHl0B+ITZfq1vVLObIbWG8izwq+XOl0+EuHvWTDTQvRxJkqSLj0qlsl2a0p09WkFBdc9y2VJk77DOb1Z7iZ56Zx09Cl27ip/j4lyrNZ+TU3PAqTMB9979MHS09bLWrSGrVAzwtRDuH+7YLLDO0OurBq0OGgQrVojP0Zo1VevExECAEbxs914bjAb+zvzb5nOCmy5AzBNGnXd8wqjq4ifBhWq95ad2Qoehtb+uVQK+BaIiTkxgDFkltaR2abVQsA3ixosJiRwRFSWC+CuvdGx9W0rOw+FFzr0mPl4MAq/OYBDpSfp8+z3zAS1g4qiyTPCtJZj3jRLjWpoJp9Ns7rjjjlqf/+ijj1xujCRJUkuiKHbqzLtDc77F7QqjHlQa6/cd3BGKkmumT9TlxAkYMkT8HB8vBiU72ytaUSEqkZgEBIheTUcHQF7IgaR21stiYyGvHPRFVhVs4oLiSCtOIzLADXd0CgthyRJ4882qYM7HR/TCz54NfS1mQvXzg7Iiu5+1c4XniAuKq9/n3JHXmYP5sxB+iev7CbvEOp899SBcN6v216nVKIoKDDq6R3fncNZh+wOTDQZAL3p8K0rAu44UHhDHflYdbajL2W8hephzr6nruOsLwN9OlR//BCg45Pi4gKaoLFNMeGaPb2SzCuad7pnPy8uz+peZmcnGjRtZtWoV+U1l8g1JkqSWzGCwHiR3MQT2aesh1jpfm5DuUHjE+W3pLOq7u9ozX/2Yh4Y6X260+jY0GlC8aqTZxAXFcaHogvNttKW8HObPF4F8TIz4OTUVPv7YOpAHUZ7yrP2AJiU/hf5x/ckry3NP2+wxBfO6PPAOc+61lsc4bjxcWFv1uLwc/OsOuIu8IiFnF50jO3M8p5ZyqBUl4BMu7mRUNNDdMoMOMLo+WLX63STT8dLl20+z8Y+DUjd9HhuLvkCUXLWnmaUSOd0zb6vOvNFo5L777qP9xTAAS5IkqbG5c9r45qLwKCRUG2jpHyfyqOsjPFxMuFRfpmA+3oGcboMB1HYuwDR+KLpCVBb55nFBcexN3+t8m4xG+Okn2LIFXnxRLIuOhnnzRI72DTfYnbQKEOUpf/jC7tMpeSkMbjOYtKI0IvzrUeO+rsGUWVmihGdOPQddqlRifoKcvRDh+Iz1xV5hkLML35hh6Ay1lIEtOARxt4ne/4YK5s+thtZXw/k1da5aQ1KSGG+TlFS1zBTc1zYAVuMLxhZQDre2z9LFmDOvVqt56KGHeOWVV9yxOUmSpBahRmnKsrLagydHFRdbB/MqVeUt/hZKX2w7ZUGlot552c5WVLHHmZ75I0egvZ1yiGpfysoyCfKper/BvsEU6WoZpFu9/UVFIo2ma1eYMgUWL4Y//6x6/vHH4bbb6v4sJiRAhv0LHa1eS8eIjqQXp9e+ndqEhNRdnjI3132z27a6AtI3gPaMSKVwhEolgruy7NoHwOqLwb+VqE+vd2FQtaWs3+Hs6rrXK0mFwERQeUFdpTOr698f9tq5SKwoBY2fc9trSTQ+ro3HaSRuGwB78uRJKiqc/CBJkiS1UIqi1PzDf+6cGORYX1otBAVhNA2yczVVpLk4/wMkTHHPtrRakd/ubs4E83v2QM+2tp/z8qew+DyxQbXUPq+utFS8p5QUePhh8Rn717/E2IDQULHMlTKaanWd10qxQbH1C+YdmTjKaBQpSK70yttKI4kaBEdfgcAkx7fT9jo4+5X95w1lYkA2uCfNpvQC5OwWVWXsyf2zKm/dJ0ykxjgjPr7m7w3LY3wxpO+1EE6n2cyZM8fqsaIopKWl8eOPP3L77be7rWGSJEnNWbmhHD8vP8oqyqoGCJ49KyZ5MnG1VrNWyxl9NnuPfMu13a+tul3ujguFpqg0TaTU2KLSgNEAao1j2zp+vH4lAO1xJpgvLoZgf9vPqX0oKjlHqxgngu/cXDGIt2NHEfiCmLF19mzRAx/kwEBMF4X6hpJflu/6BkzBfKdO9tdxd1DZaqS4QPR2bMZco0oF6gAwlBHhF05eaR7h/tXuFKT/CiGVnyvvoPpXe9EVQPd/Q/J74n9bMn6Frg+Ln33CQZcLfvUolwpVFz8ykG9WnO6Z//PPP63+/fXXXwC89NJLvPrqq+5unyRJUrOk1WkJ9AnER+OD3nS71jKYDwoSvcQubVxLtqqU1IJU8bgl15ovzai9HnRQO9Cednx7lmUpTdwRuLgyANaWyEi0WVl198yXlcGhQ+LnvDxRXjIuTkzq9NNPIpXnvvvqF8g7UF6x3tWaWrWqu2deUdyTCmWp30sOn/eysCAxCLf11QwikyPZNgZdF52o+py6o2feWC4C9PA+IuWmuvJc8bzpPfhEiAHCzrKXZubJeQ0kt3O6Z37Tpk2eaIckSVKLotVrCfQOxGA0UKIvEbN5FhaKoA+qgj9Xgi2tlky0VT2i7hrE2RRdWCNSHOwJ6Qb5ByG4g2PbszVpl7OBS2mpKNtoyddXVMmpS1ERBAYAdiYWat2aikOZRAVEoRhstCstDd5+G955R6TWJCeLnvlWrURwb/p8uYMuH3yDqyZtslCqL8XPy4Gc6rruPkVFiQGudSnPFhVGnGVv3xUVInXHASWRIWKisUsuoY1az5bsowxpM6RqBaMBqwmyvIJF/rw7xI2FQ4sgYoB1xZqzX0PijVWPfcLFBYWz2rUT6VnOFjDR+Im8ei87d5ikBuV0z/zo0aNtlqAsLCxk9OjRNV8gSZJ0ESrWFRPkE0SAdwAl+pKaK4SFgavlfIuLyaKkqoKIuwZxNkWGstpLyAW2FYMA68PZibdycsyzv+oMOufSTPbuhT5d7Zf9a90an+wSvNTWfW0xR1JRbr1V3IV5+mkRABuNIhDLyxMXdO4M5EEE0O062Lzrczr/NElhSbW/Xu0rephr4+MjJrCqS6kLs7+atm9rhl8nZvDVRoWYc8t9ogcTVHTUeoWcXdaTmWn8wGDjO++qDnfCyQ+rHhsNlYPCLb4XpjQbZ1WfCdbROy3+8c23PGWFFjQOjJtRjFBaj/EgDcjpYH7z5s3obPQ+lJWVsW3bNpcbsmjRIlQqFQ8++KDL25AkSWoqTGk2gT6B7g/mtVrK/L1qBHwXJZW6/hcyzg4gtggE96XtY1OKE3esDx+G9lEiLcKW+Hh8skvND8OPHkUzciTXz3gR1WeficB36FBYuRJOnRK55u6s9mKpPBs694CTJ8WFg0Wgl5KfQvvwOnpzvQJF7fW6OHL+Slyc/fX66+Gll2qmtGVminx9B5SGBVWlArUaRXxptVrzOXtEyUsTd+eb+0WLz0tB5UVE2i+iZr4l71BRTtJZsbHiroOJo98l/2Y8C2xZlnXqntEARSche7f1en89Bb9c2rBtc5HDfwlMufEAhw8fJt3i5BsMBtauXUtCgmvTLO/Zs4f33nuP3r17u/R6SZKkpkar1xIdEI3OoLMdzIeGikGLLm1ci97Pp+71Lhq1ByD5ZfnoDDpi/KNsB1qmYL5yEGaFsaL2C6XsbPPYh+Tc5KqqQg41VYGKAvtlEX19UVdYbE+tRr19O0ZvLwqvvpKwR+fBgAHWryktBX8PpDuUZ0PHXrB3XVXFnEqpBamMbT+29td7BYpeUN961qAH0Qsc68Ld/5AQmDsXXnhBVPUJqezNzsy0HoxuR4WxAmNwYFXvvkpFqSZY9Nj6m8Y1KOKi0q2qfU4Tb4C/n4aeT0Lh4ZpzLqg1Do1xcHz3dVyQBCRA2iH37a+hFJ+C1FXi/zMroOCwmMPCUApBHeEqi1Ql30jxuavQis9yE+ZwMN+nTx9UKhUqlcpmOo2/vz9vvPGG0w0oLi7mlltu4f3332fhwoVOv16SJKkp0uq0JIUlUW4od3/PvMGA4qVBrVJhMBrQqDUtO9WmTqpac7MPZx3m78y/+WfkOJGmUl18vOgxr/TQ2od4Y2Itf8+ys82zpeaW5jp3h0SlEpPRhNioqHP0KLz+OlE7qno88zp3xvDGG6SMvIQU/zLGdhhQ83Wm7bpbebboua2oqDFRWYWxAm+NNwA+Gh/KK8rx9apWt94rQARC9VFcDMHBYCxyve55UBA8+qgI6B98UHz3MjJEikkdxB22IKCqFn5a+FDKUz7Ht/vDorc8pKv9DbjMRknNpJtFQB/m5o5Py98dps9RXb9LfCJcS+tpCEYDaFPEJF6l6dDp7qrnfrsBcm3U1lf7irQly8pY3R+HhMlNPpAHJ4L5lJQUFEWhffv27N69m+joaPNzPj4+xMTEoHFwMIml+++/n0mTJjFmzJg6g/ny8nLKy6vy7worJ5rQ6/XoHcm5k9zGdLzlcW8Z5Pl0v/zSfHxVvnjjTVZJFvq8PFR+fiimY+zvjzo3F6MLx1xtMGAwKMQExXAu/xzxwfGowsJQ0tLQh4UBLeRcGvWojdR5jFS+cSiFKRBgu6c1rySPvzP+piItHqVDh5o52iEhqLOyMOr1lFWUsfXMVsp15ajt9Laqs7MxBgaCXo9iVKgwVqDX61EbDHW2VW0woJRkoIQOEO0wGlGtX4/6jTdQr1sHQKiXGn1WFvrK4Ln8jjsIN5ay9fh3Ns+rI/t1hVpXhFHxFtsvKEDl42P+/BoMBnNbovyjOJd/jrah1rXzVfiilBfWmRNfa/vT0lCFhaEy5NXvPXp7w8MPo37xRYz33Yc6J8d8DmuTX5KPr9oXg0Ub20X0IC3jWxLKilFfWI+x3Uyodv6rvydnf8faPCZ+iaiCuqLEXGmz3a5+DlRt26IcOwYJCai8vFB0OtRGY93fO3zgzCqUeDfNAeEiVeYWVDk7UBUeRlV4BAqPoTKWAaCovKloeyuoxYWnOqwv6tIMlKhBKKG9UUK6oYR2h8B2osytwSj+ASq/NiglWeBV8y5aQ/3NdHT7DgfziZW9GUaj+27jfPHFF+zbt489e/Y4tP6iRYtYsGBBjeXr1q0jwBOTgEh1Wr9+fWM3QXIjeT5dpCiEHztGnkXJw505O/E+5U1hRSEppSl4FZ7APzeXrJ9+Mq/T7uBBUiweO6rd339zKAB0ATrOHDxD58DOhJ8/j7JiBfkdOwIt41z6GbMIM14g/VjtxyjQmEmA8VOyvPrafH57/nYulJzn0IE1nBk3DuX48RrrtPv7b1J++onDxYfppurGsu+WEe0TbWNrleftl18AOJQlUg1+yvyJdocO1Xk+2x06hBIPZ/f60WbzZtqvWUPwedETr6hUpA0cSGHwGY79/ru5l3T9+vUoisLO7J1Enq0ZWDiyX1e00x8i5bh4X9lqNT4FBZgmuD+UdYifMsU+T5acJFlJpnNgZ6vXhxhP46VoydXUPh6h3eHDdtsfdvw4qFSE646Tcrz+71HVuzed5sxBZTRyzNZdmmoulF8gozyDrofSzG0srijm18ICJp+fj6+Sx6njv4LRSNKhQ5yuXMd07Kpz9Htp7/XgB3+ts/maJP0hTrtwjHzz84n88EOye/cm+sQJ0n9aRXxFMmfr3FYMYYbjRO/+B6e8J2FQeWjGWMVAoJJOsPEsIcazBCnn2efzLxF8A/3LXqK1wXrMpgEfitQJFKnacvDnVehVpjkFJtHOoCIldyKYbywcr/xnLcRwCi/2kas5Zbdpnv49W1Li2EBql0dPHT58mNTU1BqDYa+66iqHXn/27Flmz57NunXr8Kte4suOxx9/3GrSqsLCQtq0acO4ceMICaml2oHkdnq9nvXr1zN27Fi8vb0buzlSPTXX81lUXkSwr2MTv3hUWhqaL7/EYPH76czeM0ztP5Wc0hw2nt7IiAsRKCNGWNU4V585Q7eJE21tsVbq06fp0QOmdZ3GznM7mdh1IvTti2r7dnRjxzbLc2mLKmcniro3hNsO0s2MFahTPsTYwfaxDPntJ0rUbWlTFE73KbZ7EU3n4szeMzzS9hGytFmMbmc7R9vyvJ3eexqAiQMm1n0+S0tRpaej6lFOz+WH0Lz7LgBKSAjGGTMw3ncf3vER+P5nEhMnTarxvTyz9wwTB9Tcvmm/54vOkxDs2tg1m+8z+TTdOk5EnZqK0rcvqNUol16Koiic/uO0uS1nC8/yZ/qfTOxcrW3FyaiKT6LEjrex9SqqoiK69esnUnqqP6dSoXTtitqwlm4dnf+u2DRpEuqlS+ngwHdvf8Z+tDotPfIPWp3bJXuz6euXiRI6mq5tJoJWiyonh+6V66iTz1i119nfserkVKffrzr5DN1dPEbqt97COHgwqqAglNF9UeVq6FU9L9+miaAvosvJtzG2GgPh/Vzaf3Wqc9+gPrcaVeFhKDqOqlpVpNix70CQGICtSsnEmNkGJbQ7Skh3lJBuEJhEoEpDIFD9U1X93NhVcg5V3j4UG8ehof5mmjJQ6uJ0MH/q1CmmTZvGwYMHxZesMq/KNHGEwWBwaDt//PEHmZmZ9LfIWTMYDGzdupU333yT8vLyGmk7vr6++Pr6Vt8U3t7ezf6PVnMlj33L0tzO56u/vcqCkQvqP3FNfZ04AeHhqC2OnUajwcfHh1BVKDqjDq+0NBg+XNzur1oJjQvH26BR4ePlTUJoAjnJOeKctW4NOTkoldtrbufSJl06RFc7ZjZ5gwrbx1JR8Nel0Sd+MKcLkulrb1tqtXi9Gnq06sEnBz6xf/wqz1teaR6RgZEUlBWIde2dT0WB338XVWdatwbNabjnHvjmG7j3XlQzZqAJDkYD5GQfJSQkBG+LQa2mc6nRaGy3qXK/z/z2DO9f9X4dx8oJ6sr3k5goKuf07w/e3uSW5hIVGGVuS+uw1mw4vaFm2/zCoFhX9/mbMkUcizvuqPlcfn7lAGXXvis2eXvDfffhSGKwzqgj1D8UTbVzq1ar0XS4XcxM7O0tavGHhFS9VzufBYe+l8YK8PJ2/v26+PvE/FqdTgzMN2rBP8qB710l7wjo9R80Z7+FMwdEKc3aBgQbK6AoWQzkzT8k/i84BCN/rqpYVPg3nP3Son3+Yk6J0O4Q2gNvv7Cq9nW+S/xz5r068t4CYyG7oNbj4Onfs45u2+lgfvbs2bRr144NGzaY8+dzcnJ4+OGHWbx4scPbueKKKzh48KDVspkzZ9K1a1ceffRRl/LvJUm6uKQVpZFTmkNUQD2nMK+vEydgyBCrcnemCww/Lz9KK0qhxGg1gLA+tDot0YGd0Kg1GJTKDhS1u6tpNAFlWaIsX31kbCLVvyuDfEM4UF576T6jYkSFCl8vX3SGWiaAqjy3J/NO0jGiI3svWAyosxyIW14uSki++irs2weXXQZLlgCnISFBTPJU7UI0vTidqIRWcO6cubqOIxRFYce5HSiK4v6L244d4aOPYNgwAFLyrMtS+mh80Bts5PaaqtnUJTRUTKhmS1ER+PuYc54bmlavJTow2vaA0BCLtKJqA4RrVKNxhr5QlJpsSCqVONZBQaLEpSv7bzMNilPg1CfQYSYY9YAKTAPEUz6Hw89B0bHK56opOFQVzMdPAu9gCO0h/gUmeqBiUB28/EWVm2bA6WB+x44dbNy4kejoaNRqNWq1mssvv5xFixbxwAMP8Oeffzq0neDgYHr27Gm1LDAwkMjIyBrLJUmSbDEoBk7lnWr8YF6vh8svh127RC8jmO9aqlVq88/uUlReTHRAPYPcZsGZkn+K7Yo2uXvJ9GsL+VrKg2op36hScSjzED1jHPj7U3k+k3OTGdN+TFUw7+cHZWUiKHrnHTFTq6mMs5+fqMoSEwOmNFgbQXdGcQYDEtvB2VNOBfPHco7RI6YHZRVl+Hu7uUxlu3bw99/mYPVU3imGJQ6r+3UaJ6rZREban8ipPB384pxosPtodWIm5+r8vPwoqyirmgW3pKRaMF+P77w+3/6kYp7SsSMcOCDmMNCdgVAnKvQY9aKnvaCyh/3sKjj6sgjaR62HViPEeooeCv4WP2sCKnvZu1cF7BEWlZqiB4t/nuDOEp5NhNOXOQaDgaDK6cejoqK4UFknOTExkWPHjrm3dZIkSbVoG9qWlLyUxm6GkJgIp083yK6KywuJCbQx4c1FW5oSUfO7LMN6Wf7fENoDFSpIyaCsYxLFOjszvfr5sTd5K5e1vszhXWaXZBPpHym2D6KHef58Ub983jwRyMfHwzPPwNmzcM01ImWkFjmlOQS06wJnkm0+X+PCsHIyp53ndjKh4wTnZqN1lL+/mPW2stBEhjaDVoGt6n6d2gsUx1JvmTQJ7A3iLbkAAS7M/uoGWr2Y/A2VShzrSp0jO3M8x2LQZI2e+XrQ5YN3mPOvU/uAoY4Zd+3p3x+2bBHvwV7PvFEvAvbynKplp7+AlYHwY3f4bTocnAf5B0TQbtRD4ZGqdWPHwog1cFUKXF8EV+6BwZ9A90cgYVKd8xEUlhc6N0GbLYbyRrvL40lO98z37NmTv/76i/bt23PZZZfxwgsv4OPjw3vvvUf79nXMBleHzZs31+v1kiRdXKICosgqyWrcRlSvz4zpoaraz+4LtIt1xSQGip55VX1u57ckId1F4OBvMdztws/Q7WGU80vgTCFdpk5k9/ndtge2xsejTt9BgLcIWL3V3ugMOnw01SbnqhZMq4xG1PoK8SA0VPzT6WDgQJg9G667rirn1miEOlJIFUVBHdZK9HRWE+4XTn5ZPuH+FrO9FhZCaChF5bn0jOlJflk+ccFu6MU2VlTV2waRfmFRNc7tqTwREWJMgS2l5yH6cvfuz0HmnnlTKlBl6dfu0d35NeVXereqrPmu1To8o2yd9AXgV3MwcJ18IkCXZ/0dcFR0tOiMCAwU56HkLGRstM5pLzwOSgVc9gF0+Id4XUCCCNq9AsV3MKyHyG0vPA69nrIuFxuQ4NosvpWytFl8+tenjGo3yuVtUHhE3A1oYZwO5p988km0ldMiL1y4kMmTJzNs2DAiIyP58ssv63i1JEmS+6hQobgxSHZJZia0quylVKnAYKgZsLm5x7xYryXCP6JylyqMilHURA8NhQIXpnRvCYI7QdZv0KryD31pmghqTGk6xjA6RwSx4dQe28F8XBwBu6qOXfvw9qTkpdAlqtrkTqZ0ioIC+izfCDe+TPdrB8DQ2eL4DxsGO3bAoEEuvQ0FBbyCwVBWs4nBcaQVp1kH87m5EB6OQg5hfmHu65nX5YKPRRnMnj09Py4jLAzy8iA83Hp5WSb4uSlQdpJ5cqyICNG2ymA+OjCa7JLsqhWr98yr1CKdw5U8b10+BNuYVKwuPuHOBfMGHRSdEIF6SBfxeywoCE4fgT9m2X6NV5DI6TeJvBSuPi2Cdsv3enKpWNeNee7FumJK9CVVE+W5Iu8vaO1Y1cXmxOlgfvz4qhJT7du35/Dhw+Tm5hIeHt74FSUkSZIa2uHD0L2yp6dbNzGLZ48eVukQ3kUlEOpCb1ktTBMaxQTGkKnNJDYoVqT6nDnj1v00GsWIU4MINT5QVgI33iiqoiQehY7/rHreLwZ10XGMdvJlzwUaSCqtqpbWObIzf2X8VTOY37NHVF6ZNYvLKzu2Ov8CvIgI5lNTzQNFbTJWmOtj2+UdYjOYjw+O51zhObpHW/Qs5uWRH6Am0j+SML8wjmYfrX3bjirPAV+L/PXbb6/zJfUefDtxoki1ueWW6ltu+MGP1ZnuHLRrZ/v56sG8pnLwr7cLpXN1+a7lzPuE25+VVV8IF9aKwN2U2150QvS0g5jtdOJEMbbDP05cUJrz2S3+D2hjfRdS4ycGp1bX9lo484X1d7CeinRFjE4azd4Le51Kh7OiL2j48QgNwKlvR0VFBV5eXvz9999WyyMiImQgL0nSRaFGzubx49C5sqrFpZeKYK+aoIw8kUddna+vqHhSD61DWnOu8Jx4kJiIKjW1XttrMsqzna9kk5oN//wnBGjg3Q2QmVf1nJc/6AtRq9RUGCtqvHRryRG6KlU90W1C25BaYHEsf/0VJk+GUaNgzRrQasnrkADvv893b/5LXLw5cmdElyfSIWrjHWwz9zkuKI60omoTMOXmsq80hSFthhDmF0ZeWV6N17mkPNs6mB8gBieaKv5UF+4fXv+7AjExkGUjba4pjAUJD7efBgQ1g3nvIKiwMz6jLoYSUYrRWZoAyP0TznwJf82D1K+qnivPhd9vgL//B2e/FukmSoUI2iMHgX883HmnCNS9QuC6Ahi/EwZ9CN0ehvgrIbCtzUHbNnmHgL7IrYNNi3XFjG43mt3nd7ttmy2FUz3zXl5eJCYmOlxLXpIkydM0Kg0Vxgq81E7faHTJ0v1LrXM29XrwqcyrDgkRlUywzikOzsiHy2wE86bgz+lc26rgpnVIa/Ze2MuA+AFiOvYffrB94dDclJwD/9bOveZUBlzbFUp+gv+9Byt+AG9vNB304B0AVNC7VW8OZhykb5z1RFTZZbkEW1QtUavU1ilcb74JP/4ofh41iuR7rif9sh5cnjgMv/0fo9VrCQoJsV9i0aQ8p86BfiKYr9kzH+IbQkH18pp5eZwMyWNUWBJGxUhBmZvSrMqzIahDjcUXii6QEFIz7zk2KJb04nTrFCBXBAWJYxgSYpGyVvPiq76ytFmi5KSjIiKgWrU+L7UXeoNepOFYzAsgngwCfTG4VFhI5VjQXKGFQ89V5bQXJVsPOG57nfgHIhCPGQnBHURuu6m3PaB1zX2pHNx/XVqNhoxNEHtF/beFmCQw1C/U7t21Orl0UahyPV2qATnduieffJLHH3+c3NquUCVJkhpIm9A2VT3THqbVaa0rWIDdPxCWaTaBmXlisqDqwsLEpDjO0OsxWuTkxwXFkV5cWf7Qy0sEQC1ByTkRaDgjtwLCNeJWelAs3HUXjB7NwA9+FndPFIVL4y9lz4Wad0+sepvPnYPHHyfkvEVO9MMPw6xZsHgxrFrF/p5RdIwUpSODfYIpKi8SwVypnbrUFRUiMK2ei27BPPbBKxi8KkSZS8s2qlQ1e8Xz8igP9kelUqFRa1wPdKorzwbfmu1MyUuhXVjNVJPYoFjSitNqLHfaxInw88/i59xcEUS7+c6/oijc8+M9zr3IlM9voW1oW+u7N5bt9KpHz7zpItJQJnK8T6+AA0/B1mtg/2NVq6l94cgLohRk4TERyGv8IGqwmLgpwSI3XKWGMZvE4NVucyp72tu4/dhaiegLefvdtrkiXRFBPkHis1b9DpUjStPEHQhn+ISJ3ydNnNNdWa+//jrJycnEx8eTmJhIYLVSTPv27XNb4yRJkuzRG/R4qb1oF9aOlLwUksKSPL7Po9lH6RBRs7fSSmAgFFv/EddUGERKTXWuBPNaLXp/X/GHXl+Ixi8Gg7GFBPCWStMgfoJzr/FrBYcXQed/VS1r25ad919N/4Gj4MRR/DXelFVYB8m5pbmE+YXB6QMi5/7rr8FgoPdNo2Ba5UqXXy7+vfUWhIaSfjzdXJ4xxDeEIl0RcapaqshkZIgBhuU5EH6JzVVyS3PFwGa1F8SEwPnzdb5lfXkZXr4u1pU3Gqwr1lg9pwNNzc/sqbxTTOs2rcbyuKA49qfvd60dluLjobLkdVXdefdWrNp7YS/ezpYntHGhnBCcwIWiC7Z/J3gHi9x3R1j2/CoKnPwQjr0Oxck101TC+0Kf58TPai/o/pjIlTf1tJ/9FrrYGbzaGPxiK4Po+ldYKtWX4u/lz7gO4/j+2Pfc3qfucRxW8g9AWG/nXuMfB7oCcYybMKeD+alTp3qgGZIkSc7R6rUE+QTRLrwdu87vYhT1KFfmoMNZh+keZTH4MCtLlHSzNGAA/PEHqgAHerxCQ52vTa/VUuHvIwax5R2ADjOt00FayvglpcL5etB+raBsr0glsNyU6fgEtofiFBRFqRqsqdNxesmzXLd8A+w7UPWiESPIGnwJxbpignyCrPdTeYxNqVTBvsEUlteRXpOWJmrM647ZzZlPL04XA5kBYsNQmYLaWpwrPEu/uOvrXK8GXYGY2Kf3AqdeVqQrIsQ3pMbyML8w8krdlK8fECBy0LOzIdRP3Klwo99Sf+PytvUvdZkQksCRU0dsP+kVBNqzVovUig7y94P2hPVAVL9WMHabWEmlgpLzUJ4pHnuHVk2qFNq95oVg9fPnju+/O3+HtJkGp5ZC5/vdsjmVSuX6+IyikxA3vu71LLXy/N8Vd3A6mJ83b54n2iFJkuSUYl0xgT6BBHgHUKpvmCm3C8oLiPCPqCqNduRIVSUbkx49ML7zDqqBDmQxhoU5XUpSV5iHEhgo/uCX2Bjs2giDBTec2sCY9mMcWtdgNHAk+4hjM606Q1FERZvBn1gtthqwGdoV8g+SGJZIakEqiSFtoG9f+h0+LJ738oL/+z9RH75PHwJSf+dEzoka+fXVBfsEk6nNrL19aWnQuzeU/yFqctuQUZxBfHBlGkBsOBw5Jy74anG28ByDY2tvn02laZB/0PnX2eHWIhhXXglr14qgskdUvWqTV1dWUYaPxsc6391R1d5jpH8kOSU5NdczlIlymhZpNprN45hcshXVehtpUGUZ1rMXt5kGba4Vwbt/fINdoJsvcN35O8QrQAzmtnUXSFcAmVtcKhXprbGYByJrh6ioU+fEYk2gKpKHuPSu8vPz+eCDD6xy5/ft28d5B24JSpIkuYNWpzX3mDZkrfkQ35CqXtijR6sq2ZhoNOh1pfh7O5D6EBrqdJpNfvZ5gsJioCzNZo+l4u+Pup4Vcpy14uAKyisc2+eZgjOsO7nO/Y24cAESEmr05pfqS80TQRHQBv7azdDWQ/j97O+ibvqVV6KNDIH//Q+efx7efhv69AFszPJphynNplbp6RBb2etuJziz6pkP8Udl57NhOR7DqBisAlKHg+qyNAhMEoM0G1vhMVGy0yQxUZT4zM4G/xLwd18wv+b4GqZ0mWL9PXZU9QnDDGVElqdCyudw7nvYOhW+7yRmRN0yxTpnXuOPCiOKd7iYAKvj3dD/NRi9ASZV690P6w1xY8VFTAPeaXt156sOf4+dEj8B0n6uelxyDo6+CmdWuHxBOaztMLadqbybkb8f0jfUu5nNmdPB/F9//UXnzp15/vnnWbx4MfmVv2y+/fZbHn/8cXe3T5IkySab6Q8NINQvtKqiSHm5qMtcTbmhvKpttfVy+fqK2UKdkJ9zjpDI+MoZOkUVHRWqqgAvNha/PDelOzioUFdISn6KQ+sm5yaLwaLudvQodO1aY3GxrlhUqfnhBxgzFiY+TfTew+YJf0of/zcr1iyCp54SF2bp6ebX2pthuERfgr9X1cWaQ2k2Op3tcRMW8svyRe4+2A3iLD9/Sn16UEvTIPF6yNrm+jbc5dx3cH6N9TI/P1EZqiLTgR5Xx6UWpNI2tK3197guFSWQu0/8s7T1Km48+wLs+D9IWyfehynPXTGIcpCVDH1fZq3/UiquThcpNQPfgS4PiEovAdV73xunFOeFogtcKEi1P47CVaHdxAVb/t9wZDFkboVO90Gne0RlJxulYuvSM6Ynf2dWlkk3GkCfX/sLDGVicHAL5XQwP2fOHGbMmMGJEyfws/gjNmHCBLZu3erWxkmSJNlTrCsW06w3kFJ9KX5eftazbNoJuEpaRRCZU5n6k51Naaj72lmUm05YZAKWf/AtZ6NUYmPxdXZQbT0lhSaRnJvs0LopeSmE+tWeOuLSbf7kZOhQbSBiYSHqN95kwqQH4aqrYONG0Khh717zKnu1JxiQNEQ8sBx8iZ1ebpWKU3mnrAY9BvkEUayrfw+3Qt2TLsUHx5sreZzKO0VUQJTV8w4H+Lo8iLwMCuu+82BSXlGOr41BsfXmFSiCYEtjx8KGDVBRJGqWu8GFogvEBYmBmKG+obbLeBYeg5RlsP9x2HIV/3d6PqwMgrX94eRHIjXEJKQ7ZeoAiB4metv7vw6jf4VpaXBttpjbwCSoA+Xq8CY9pqVYV0x63nFRZ97dooaANhW6zoGkm0VKHIBfHJSl1/5aG1Sq6rN/q2qvaV9wSIw7aKGcDub37NnD3XffXWN5QkIC6enOnxBJki5ONSZfcpJpACxAgHcAWp3WHc2y63jOcbpEdiHML6wqCLATOOX17kyrvyt7qs+epTQuyuZERa4ozs8kIqqyjrxPOJTn0jqkNWcLKwfbNULPfJvQNpwtOFv3ioDeqK+7koi+QAz8c4ZlvX+tFh58EFq3JvqJhQSmponxCY88Ahvmw9y5hPiGkF+Wz18Z/8/eeYfHUV59+57tRdvUVs1FttxxxQabjgklDoGQEEhIgZCeUBLykvqlkISUNwkvJCEVQhoplBAgmB6waca4925LsqwurbS9zvfHbNXONmlXks3e1+XL2tlnZp6dep7znPM7O1hYu1Bar75eim3PwaGBQ7RUtsQ/qxSqcVMUqq+o54RTGnC8cfwNWZnIvClQT7x1qJVpVplqn7nIZ4BhXSwVPIrR0gLTpxe+ryw8sf8JrphzBYQ82APH0bU/LEk9hjyJRvvugjc+Cnt+BB1PYgn1AaIk02lqkQZBMZb+hPuafwQXr4fpH4A5N0PdatDXjd5oL7TycRGpN9XTN3y4NBVSa1ZB45r0mHXjFCnsZhTMtM2UnAiCIIUmOXZkbuzYCdaFo9rPyUDBxrxOp2NYpijG/v37qRmp6lCmTJkyGdjTu0f+izyNouQwm2ZrM8ccx4rUM3n29O5hfs18LFqL5Jnv75c0sGVwVBow9Uc9te3thBsbipakGxwexFxZDwiSceE6nFoFtqYGbYFJtWNFKSgJi0U0Zj0dhWvMJ6PXS1rlTieemdM4/qOvS9rxP/4xTJ8Fvj7OmnIWb7S/QViMJjODVLyrJz2RNe7tjv7fMdyRSFQtGfIGXYOpIa7nPugdxKhJn/UpKPwmOiBMIRyQVRI6Mngk6+AhlpSYgkIryVzmou4d0P1i6rJf/CL3evnQ+xri1i9zSfvPMT69EB6qoGXjB5h36Iew58cwvC/Rtmol1J4Psz4Ly3/JYw23wHu7JU/73C9AxfREW6UGQVCMLdxpJCHX2GciRtmfSn0lHk9n4QPpsaBvGrUxv7p5dcIpVL0K+t7I3DjolORCT1EKNuavvPJKvvvd7xIMBgFpqqOtrY2vfvWrvO997yt6B8uUKfM2wtsFR/+cV9OYmg3ADNsMjgweKWXP6Pf2U2WoSoTZ7N0LC+Snbd1Bt6SyAFLYRkMDnqBHtm2hqLx+hIoKQJQqdDoPp3hrUakQIsUroZ4Ld8CdSDAtFoUUjPL54A9/gJ//PFGwSaGAu+6CZ55h3VP34v/kjZL+P0iKNsP7mFU5i319+1AKSfHBSiWMOHY1hkQIE04nmM2IiFJxpyTySsIOuUGZ77ESpXM5QtvcrDXHZ4aEUAjUqUa3UWMs7FqrvQB6Xk5dFugHbXVa07ahtqyeebvRnq7qozJKvzsXggDaWvB2J60rL7j34I4HUxcEXdC/CY78CbZ+GV6+PDV8qPd1hL0/YYZ3L7iPAiIRTRVdhrlS7HayutDMj8E7XoYVvyIy67N0GueALlqh2WBIKwo2apnETAQcYzOmlQYIj95xoAl58vbMP7LnkVHvJ46uRlL+GQUp17pSA5Hg2PtzklKwMf/Tn/6U3t5eamtr8Xq9nH/++bS0tGAymbjzzjtL0ccyZcq8XfD3J/SVcxArIAKkeqZLTDw+et8+mDNHto074Eaj0UuhH+Ewer2paMa8ZKhHk1+1VeDvQ61UT1jhqF5PLzXG/GZlw5FwqvGcCe/x3AomJ05ISatTpsDHPw4HD8Lf/574/l3vgksvxRXypCZKm2aDcz+CIHBw4GC6ROYIr2aKok28iFEWNBopMVpum+52KawgT0S7He2IkKlYTL3D56A2oAZbajGblJyOfJALc/D3yRrzcSnADNSb6tMrc6oM+RnzAFOvhvbsBmJEjPDTN35K+MRz8PK74PFmeNgEz66ADTfA3p/AiadSK4/Wnsc209mIy++Fi16G9/bA+3p4tOEmWHEvmOXvY0/QkzpQrayUqtIm0WBqoMOZSclvFOEyAcfYwlw0NqnK8CjRRnx5DSZ8IR8/ef0nY3+uCQrGkvBrVGnxhaNGvCJaTG8koshEhS6NFwUb82azmVdffZVHH32UH/3oR9x0002sXbuWdevWpVWDLVOmTJmCCAyAL/9qjzHDRqkocphHHvvE65XCOWLs+Un8T3fQjWrJMti1CwQBg9pQNGMeBClhbBz1p7PR6+6lxlCDWiETYjGCmJJITsK+1OTBZN56S9KCnz4dvv99ycCuq4ObboKr0iuTpqkeqQwQkjyXF0y/gBWNK7J2ZVbVrFRjvqpKtl1cy95shpGhqP390nqedkkeUwa5gY7Y1IS+X0bHHHij/Q3O0M8auzEvRwZjPhd1FXV0uUbkzqmMEJau/b29e9nftz/zBlQGSdnE1wd9G6WE0/bHokb7dDj+BIPeQa6YfQXbjq+HE2vBfUxaV2eXCvzMvglW/AqqEufVZ13M63XXIcz+HNjPB10NCkGRczbFHXCnJtnbbGnGfKwKrDyjMFKDjiIY84XnzPhDfjRKDZqIFzS5jfm2oTZuWnFTcbzzY+DixsXscEQHkDXnQO+r6Y0Kmek7SSm4aFSM1atXs3r16mL2pUyZMm8jZFU7AgNSifJJRiAcyJ60GfJC20Mw51ZQanAFXOjOeBc8JL3oimvMI8WU61NjtsdTaz+ZXk8v86rn0WyT8hZmV83O2DaWONo61Dq6nR09Cmeckfh8zjlSgSe3W1KrGWHYgox3FeKDoGsWyFROHXFdVmgqcAejnuW+PvyzZqAZzuydxmKRCoEl55DFqr96DkPN2bKrpc1wKDTQUIu+V35we2jgEJdFTofKVLm9vIz5kDdVpk9fD54TCQlIf9+olD/sRnu6Ma9MhNk8dfAp5lbPZU511BMedKYqkHSvkzzrW74gv4Oh3fTqZnPetPPY1PEKp6/4tVRYybJAmqXKwH8O/IfLZ1+etlzI4a11B92pOQmVldLALIkGUwOvtskYkKMl4ADjGJKatZWjMub7vf1UG6pR9/uk6rU5aHW0ckbjGTx54MlEsanRMoacg2laLRv8Ps4A6VroflHKv0jGsT29cu4pxqiKRr344otcfvnlzJw5k5aWFi6//HJeeOHtLdhfpkyZwklLHAsMZix1P5Ec7D+YYqSKiKlGX2AApn0QTkha2aFICLXJAh7JgC+6Me89kWbMTxQ97h5qjDW0VLbklKc8MniEZltz/gmD/f3w+OOJz83NktH+kY9I8pKvvAJXXy3FsssY8pCf3GPqCln61tdHq9rNDNuMzG1ixnwyMWM+7JW8zzJ0u7qxG+2JBSoTWHUZk5lFRKmo1IjfbdPlEcPt65QkAWOMjJv398veh7mMX61Kmz47ozJIMdF9G5g79DrNR34JL70T/j0VHjbDgV8mwjq0leCNhqzo6qByBUy5Glb8Gt6xHmZ9Nn69qYxTGGy6FmrPy2rIQwEzQiNI88zLhNkYNUa8XmfG+P6CCQ5NiGe+z9NHtaEahaAglE3iMUrsmK5uXs2LR1/M2X6sBMIB+Wq93k48Sov0TMl0n7uOSRViT2EKNuZ/+ctfctlll2Eymbj11lu55ZZbMJvNrFmzhl/+8pel6GOZMmVOQfQqPd7QiEStghIE0ymqqkQSMSWbGBqnRzLaYgQGoPJ06aWR3I9IBAQBozpLUqJSCeH8Q4QEAH+vlDgGKTHJsf2KsX2PAzG9/6mWqbQ6snvcg5FgPOY667k61Amf/rQUD3/11ZBcXfyxx+DPf4bTTx99pxUaqcS8HBpN5kJeTicH/CdSZCnTyGbMZ/nNKdVfQVLeCMtr14uIqBQqybCUCbMZ9OUw5rydknxiDF2N5I2P7yCcNkPm8Dkwa3OorASHsfuOwlBSRVN3K7z8TnhuFZcPPsaCgWeh8xkp5AgkffnYwME0B97xClzwNJz7CJz2TVj2M6m4UO25oLHS6+6l1ljLe+a+h8f3P57ehxGMRXkozTMvE2YDoPYFEgnWYyXozMsznhE5daI8iIXLWbRmul3dOdv7Qj70aj3L6pextXNrzvZZERQ5VcxcARcmjYwaja+LKXVnsK8vqkikrZYJ1RTTJTFPMQoeSv7whz/k//7v/7jpppviy2655RbOPvts7rzzzpTlZcqUKZMJq87KoHcwYwhEocRUR/JNxiyEbnc3tcba+Oeqo92w9KJEg8Cg5FU0NKYmE1qtYDRKOvjBDEmAsRjrDJ7lZDxBDyqFWgpNiL2cKmaASyoeNOAdwKw2EzCbJa92w/h47wVBQCWo8s5bMKgNeEPe1HMfiUhykvfcA88/n1i+ZIlUlbUxmhCrKOylLOtNNs0C5yGwyoSS1NVJ+5ua8OQKCETECAqgbbidd85ak3mHFgvsHxEX7nKBKbssXre7m1VTViUWqE0QlK8qa9FapKJVb22Trp/kn5ZPNVpvZ3q4jyhK/zLcf0cHj9Jsi4Z/RIKSeszwHnDslv4f2g2e41wNoPdIcesA5nkABDTVeA3NHBONLJ7zQSk0xjwPXEdAjNZgUGqg9hypH3t/KsVu6y5N6Uefp48qfRVqpZoBb26j9eE9D/Op0z+Vs50c7oA7dSCg10vqSSNQef2S0k1RyOJhzgelIZ6jUAh9nj4W2Rfh0Vk5PnycRnOOBPQkWipbONh/kFlVswreLyDlO/h7pHCvDDj9TvmK32Efy6eewxP7n2BezTywr4bu/8K0a5MaTXxuUakpeKgyPDzMZZddlrb8kksukdWfL1OmTBk5bHpbbg9iAeSUpwwMwaH7Rr395FAN67EumDcv8aV/QPIuNl4Bx59ItL3kEjjzzOxhNlYr5Fmxtdfdi0k7wig0tYAzVWveb7NJBuk4kCv0Qg6z1pxqcG7dKh3Pyy+XDHmFAO99L6xbB1u2ZPfCh0LS7EYGZHMJzHNStcWTkSkcNdUyNV4UKyJGErr0csh55mNkMdKG/cOpnkeVCSHkImAySYm3Sbx33ns5s/FMyegdMbhR5KN77uuRZCCTMc2MyjaSmEEIOKD3dTh0H75j/0iEF4Vc8PxZ8OYnYP//Qeez8UGsS2lJnV3T1cKK3/C7qd/GeNnrvFpzNbR8ShpMaCulWS3NiDAZQQDjVHAeTlQKjRKKhOLhFjEjMhMH+g9QX1E/aunUNM98rG8jUHuL6JkfK6McCAx4B6jUV2LTWwtWBrtizhU8eeDJUe0XkJJTc2jNOwPO9GdflJQ8EX2dJHEcI+TJnEx/ClGwMX/FFVfw2GOPpS1//PHHefe7312UTpUpU+bUx6azMeiVMeaV+tSKjHnSbGvmqONo5gbOA3nLXuZC5Q+keuICUWNepYewDzE2ZVxfD1OmoFfri2PMe3rTvVP6BvB2pFSB9VmtCN25p8rHk3AkHNdmN2vNOF1JXtXp06WiThYL3HQjvP4APPoonHdebuPk6FGYkSWGXQ5dneSdlqOhQZK9TCJFnjILoihKRp1bZhYmjxCwlNh+tQlCToaamxG2b09pZ9QYsw8ocnY0AiPXrzkbdn4XNn8BDtwLjzXCIzZ4/mzY+Ekau59MhAFpbFJYWd3FUtL3Gb+Di1+Dqwf4U/OdsOynie1GcwTCkbAUGjQS/4Bk1I+k6arMA64ol7VcxjOHnpH/iaLIQ7sfkk9yzpO0mHlpw2ntVD6/vDGfR/iIzEoFti8OseJpFRoT3e7Cnh3SehWjV1Ey5K4CmzHMJhOx8+TYBZbTsrc9BSg4zGbevHnceeedvPzyy6xaJU0Jbtiwgddee40vfelL/PznP4+3veWWW4rX0zJlypxS2PQ22oba0r/Q1kgx4arCEpaq9FWJ4j5yDO9nNC/KUCSUJhkojHyfh70J74/9Ahq7/5TytUqhyqwDb7HIVh2Vo8fdw/SR3ilBAaJIg6mBZw89C0Q9850ZjNUSolKoCIaDsolq7cPtTDVPgfXrOf1HP0DTMwCbokaqzQZPPSV54D2b0r3G2di3DxYtKqyj2QYIdjuMGAg125p5+djLWTepV+vjccSyxAZ8+aI2Q9CJq6EB4eBBkJkRL5jAoBQW0/saOA9KYSyLvhvdnxXaHk4P0TA0gXk+JwIapibHHV+2KeNuUtRNFGqCIZ988iJAcFDa90iUGlj5QNafo1FqCEVCUgjUiJjopw4+xeWzLx+TyoqsZ14GrS9ESK9NN6iUUVlORSGVRydGlSpGPjM7oUgobTB5zYJreHj3w3zy9E8WvlOdXZLbzYLT75RPYo72Va/SS7VH1Howz5acN+Y5MLQTpn2g8D6dZBRszN9///3YbDb27NnDnj2JcuxWq5X7778//lkQhLIxX6ZMmYzYdDJhNqIYrQjYW7D6QM6XdsAxqjLphwcOyyY8phgsyS+/ymXUBAoooGe1SgWP8qDX3YtJLZ8cp1FqCEYrIIb0eoQ8BwjFZLp1Oq1DrenHy+/H/ftf8Y6//Ad27iVu0u7ZA/OjicUXXCD939cBtmX577StTSoQlYGCw4BUKil0J4nYsQ1HIqgU8rKUJo0Uq57RmM+iMS/fD5MUzqI0jC2ZedvXoX+jFNc+cjaiYkbCmBcEqDoDbEukMJw5N0sx7VHN8c0b72VlHruz6CwM+Yew6qzxZW1DrZw59UPyK8jNEsSQ89iP4Pzp57Pu2DoubL4wvswb9LKvb5+sHGUh+EN+tEptznY1gpF+wYd95Bdqk5TQqi7EmJ9g8iiwdMJ5Ii2p2Kqz4gw4pXoJhc4aKZSpEqUyuAKujGE2AMvql7GlcwtnTz1bUjg69jfJmA95Uiv8nqIUbMwfPZplGrtMmTJl8iReSXUk2hrJazhJ2NO7hzMak7TNh4cRzJb0BM4kAgp9/pUcCwizcQacaBAzql3EDVdBmJCCUjF5yrgx390Nv/41/PrXLIgNLnQ6XNe+l43vW8nqmCGfTHCosEGXTNx4ytfZPJ2ZEj6Tl7W3w4svsnjHy3SddyXTrfIJ1iatCWfAiX2kSRdLLHW3F6Z1rdQhhL3Z24Tc0PMKDEUTUIf2SEo05qsTbbpegIG3Ep8NU6Trp+Gd6eEHp31TinHvfhmq8zHd06mvqKfL1ZVizB8fPs45dUtGtb1cLK1byl1v3JVizP9h6x+4cemNOddVCIqcxmc+nv1a0UhnZDjdmFdVSAOyU4xWRyvTLOnOlstnX85/DvyHK+deWfR9OgPO9DCbpPt3kX0R9225TzLmVcakUM1TP/kVxlA0qkyZMmXGgiAI8tO5uhroe338O5SBDucIabu9ewnNnY3D58hozB82LuLC9n/BzNwGBQaDfIx1BoTwMBiWpC5UqCWFkWKSTbc5ijvgTjkG0yzTeOFIUs2R116DO+4AwFlrxfTFr8AnP0mkQk3HviyyguMxEDE0Sp5qQ0P6d11dkqoOQFMTXHUVO+a7cVfWZJSlNGvNOP1O6UPyde10Sooz3g7JgM5A2gxC0jEQ1WJqxeGNn4Hj/4at3TBybCGoUJjek/g89zYIuyX1GMt8aaB04F6Y/fn0TlSvgkO/gwyzP/kQqwI7t3puov+IKQbzmIsMJSEIAkaNMV7p9+jgUSw6C5X63F79mPKPTZ9bSSobVeg5GB5kycgvTlVjfqhVdtZjdtVsntj/REn26Qq40kOeAoNS/gagVqoJRZJm1BSq4j8TJzEFG/OiKPLII4/w0ksv0dPTQ2TE9N+//vWvonWuTJkybyMiIWm6VZVZki8XKoWKUCSUnmgXk3LMoxiKHCmGx549KJbPx+FzJIz8EYaJX2nMv3BLAUaNgCCp8owsGGWcBu7W4lWB9XZLCiUzPpq1WUrV0lAI9eNPMGPPBlj+GWnZlVdKOvFXX81fpnTxubNuBaBCjMjPyhRKPkmlmTxz5rlSgqWcMX/77ZKUZNK50Sg1HOg/wEXNF6W3RwqzkZVKjGvMH8ha3VhElIo1xTzsQ7tRnHiWSz29KAc8sGMlnBn1lgeHwReN6zdMTRjqsf+PJHnip4+IF46EQMjgiVbpwXscKs7J2M9c1FXUsaN7R/yzL+RLuR9jyk75xKKPRC42HuDKOVfyxP4nuG7hdfx919/5ytlfyWt7Fq2lcGNe5n61hFR0RBzpbdUVoyjgNIGe5LAPlFoEIZjxWAMM+VLDqJJZZF/Ezu6dLLQvLGrXRFFM74+3M7OcZdUZUg7IKV4sKkbBaja33norH/nIRzh69CgVFRVYLJaUf2XKlCkzKgIOUNvyMm4zJVlOMU+JSwim4DkuJfIVA5cLU3UDQ74M8oNEjX/bYhjclrpsjAjBIIiudGO+Yqakm06RCmf5uqQY6xz0unupD+rgpz+Flha4+mrO+sW/E0WXlEp4+GG49loiqoQBqRAUxRl49PZCbfZk2Yz7qZgpFSySw2xOuw5nVs5kf9/+jImcsTCbNGLGfDK+PuhZHx+MiKLIRd1/hUer4YXz4a3PwoFfIrgOohMdCI0B2Lwusf78r8LFGyTVmPe0woVrpb9nfgyqzySSzSD0dUsJh5lQW6XCO6OkUl+ZMqjZcHwD063T45+rDFX0e/tHte0B74Cs4V1vqqfT2cnzh5/nouaL8o7ZjsX3F4RSCcFUj68qHCEgt0tVBQQLGLSKIsVJgBXyGugmdhuTIpWqz8ZqdoyGMxrPYHv39twNZTtSoLNlRCXjWmNtouCVbRkceaCw0LaTmII983/961/517/+xZo1WYpmlClTpkyhBDJI1MngDspIxpGQp4wXt4kxvB9Ms8Eto56ThWQ5xTiCgEVr4YArs1ShKIpS8ZL990gJhRTHyFZ7A6AJg3qE48Q4Dbr/i01nG708XDL+3nhV2Yzs30/Nd+9g6uMvgTsan1pVxd7Ll7MiEJAqqUaRO45FGXTs2wdz52b8Wvb8xVBqIJyh0qsMs6tmc9yZWT4vJcwmNhDwD8C+F2GpCTr/A22PSJ53f7RC5ZVtYJyCP+zHq4nOcBinx73sEXcHr/Qs5ayrPo76/gcTO7MtAo8HTJkHXBlDWbJ5M0EqtjNCXWZkOFU2Ru5zZ/dOzrMmChBV6avo9/TLK5PkIFb9VY4plilsOL6Bb57/zby3Z9Fasg7KZbHZpByXmjyK06kkedG8CRcpWVNVIe03z9wTZ8ApVfcNDoHaQpPZxPHh4xmPdTYsWsvonkHaaBViXQH79HZC5Yr4xzMaz+DNjje5Ys4V0ixvxczCks5PYgr2zFssFmYUqulbpkyZMjKkvPgLkO6LxceOZLp1OkcHZZL0XUck5Y4CvePHHMdoto4YGAgCVp011aMnZ5gKClBopKnrIqHxBsCgTf8dSg1EglLhqKjBKWq1Upz1aPD1SC/XTNx1F8ydy/S/PYXC7YHTToPf/x7a29n02SsJGXRSu6hgQoezgynmPF6qkSAIBfiYDhyAWZmrTnqCHtlB32hoMDUwtyrDwMHXi9mxhSndT6SGVez5MWz4Phz6CvS+Aj0vJwx54/R43QNXwMVR+5XwfidceRQueAqW/i9i1Zk4lLPkE54HBjJWDTZpTZnDmHIZ86YW0KV65lPCqQpERESRdL2OxTPf4+6hxiDfj6vmXsUXV32xoO2NyjNfWSkd+3xQFxgzH3DIy3QWisZWUHhPn6dPOq7R/ScXoCuUUc9A5lE4Ko1AarL8dOt0jjmOJb5ffu+ECAFMBAUb89/5zne444478I72JVGmTJkycmQqHiNDJmPeoDbgDck8myLBtEqS+bCndw/za9IVV8xac8L7FAmmSOulxOzXXyqpiRQBURRRen1gyPw7plim0OHskD7U1aXqpbenF/vLSMAhGQSxQYrHk6qFv3o1CAJHzl2I+MILsGMHfOIToNczzTpNqh8givDRj4LbzcH+gxkTR1PwdqaHEGXD50skhcqQS86uEBSCgu+v/j4MH5QSSN/6PLxwATxaA/+qRfXSxZzT84+U0CqsC0FbBY3vkgosrfwTXPoWXOOSjPbK0+P91BnqsyeeKhQQTqpVMDgoGZYypFTEHImvSyqaVQC97t6MRnQ2PEEP+hHVN2OeeaDgsIpeT2bPvFqpln0mZGNUnnk5Yz6TwajQFjaYz1cBKxfayoKM+V53L9WGaskzr7FQV1FHp1O+TkU+M2qjqQo9KmMeUo592kBiLIXVTjIKNubf//73Mzg4SG1tLQsXLmTZsmUp/8qUKVMmX1JeDAV45t2B/Iq5ZNhp3k3bhtqYYkn3KKcoJwQcKf1O6VvFTGlWoAi4g24sITXoMxvzDaYGOoYlY16sq5NUWUAKJ9nzowL2JkpqLwfegq98RVJ0+epXE18vWQLt7Tz9008jXHRRygs1Jk/J4cPwqU/BP/7BkcEjzLDlMaNbzNwGpPCBrAZe9Zlw6L7Ua0IUpQTg7pdg/y/hrc+BYycgnXd6XoZNN8HBX0HPOik0AAEqZnDUcJpkwKlUUlx184dh0R1wxm9h1melhOKq5WmhFE5/jn6ClJNw+HDicxbPfFZjPhKAPLTTkxmtZ/719tc5a8pZKcts+qT6EsHh9JCxLPR5+qgyVBXcj0yYtWaG/QUm28sZ86Iob8AW6hWOhrmMGY1Nco7kSZ+nL2HMqy3pyjBJjGWWJiv6+sxVmTMhc3wVgoLIKIUOTmYKjpm/4YYb2Lx5Mx/+8Iex2+1Fk5cqU6bM25zgcN4xnq6Aa3QvdaU+Wq01v/hfKUQgyefh84FWMoTiL+/AYKoxH3QnDLMiPh973D1Uowe9X76BIKBTavCHo9/b7bB1q/R394tQtVIqLZ/LWyWKsOUIPPQkPPE8hKMvxjfflIopqaKvjcZG6Ehffbp1Oi8dfQn298KaNfCnPxH0K9Gq8jAgPcfBfkHudnmSaQYnTtUKqSjTltukHIHhfVJMe2CEIWRbJnnZQfKmN747ST1mgVScRmVk7cZ7+XzNWWBuheFhqIpeozkKRuXsJ0gDqJdegtmzpc+Dg5KBL0NWY34U9Lp7OXfquQWvt6d3j6T+43g5viylGnJgQJq5yJNwJJyuVDUGlApl4YZfZaV07EegV+vxBD155xbIEnCAJUsIVL5obDC0N+/mfZ4+yUDvd+ScGcikMT9mFGoQ5QcQhTCnag77+/Yzr2ZeETp18lDwXfHUU0/x7LPPcs45o5euKlOmTBmQ5P78IX/U0BOlOHOQHuzhQMbQGFfAxTRrni+UkBeU0RjuWEXGPI35NPr7oVqKJ46rpIxI3HUFXKlx2kp9UgGT0dPj7qEqrJVi5uXQN4D3ROJzbW0iNGZ4H9ScBYH+7Alm//433HknbNqUWHbhhfCFL0hVVpW5p63jlWj7+yVj9uqrmfmnb0HMQSuK4Dku7wjy9+WvpOLxZA2xAelc2LRW8HalSD4ytBvm3AJT3w/WBdKxefWapDUlT3tc6jGaxAxA5TI4P4eWtsUCQ0Opxnzt+Vn7mfN6rq2V1HtiDA5m9cy3Olqzb68A8hpsJKFSqAiGJcWXrA4/f/6zcZMGk0kaqI2gwdTACeeJ/MLJMhF0FCfMpsCYeWfAKT2zwknPygy0DrVyztTs9p9WpcUX8qFTZd9WKVjRuIIn9j9RNuZzMWXKFMzmwkuilylTpsxIYlPudRUjYni11ZJhJ6cBTmY1GwCj2phqfLgOgSmaJBlXl8gizRclIkbSp877+uLGfBz/AFgSL460EKDqldD/ZvadCULOIk297l5mBQJgzRDvbGoBZ1IYhlotedLDfikRV2eXEluzGfM7d0qGvEYFH/4oXFkLV/wwe99zMXUqpp4hiESkuG93K2z5Ilr1mTKNkwZ0uTh4MOGlBun4JedGDO3htO2fw+LvkIykkVSfJRnzICkPzf0SuI7CrM9AzTmS5vpoiRnzMXIkFOcMB5Ijy2Cm2J55KCyx0V5h58jgkdzJx/5+adA0gRQskRq7V0fQaGosgjE/DKoi2FdKHUQyzOBlIN/z2+PuyalyE0ugHdOxGCVWnbXwPIhTgIJj5n/2s5/x5S9/mWPHjo1557/+9a9ZtGgRZrMZs9nMqlWrePrpp8e83TJlypwcZJRS1NYkVD9kyOYpbLY1pyoaDO+XwiAg4ZnPg/ah9nT5PDljPjAQr0IIMgMNywJw7Mq+M6MxZxXYHncPZo8TqqbLN6iYAa7D6cs7n4O6S6LGfFJC7I4d8PGPw5NPJpZ9+tPw/e/Duu/B/ffDnMb07eWB0h8EneSVi4gRWs9dCP/5j/SlYwcs/SmLHOsLkoaMI4rgOQEbHgblenjzU/D8OfBIJez+fqKdqoJK126UQYc0QKhogaYrYcHXYdVfoeWTibbaKkmn/Zx/wuDWsec5xIx5rzcelpVtoOYKuNJL1UsrZU8SzbBNkyaD5v04UVdRxyN7Hkn14MrlqhQYZjOZSc5XGTViZEKSNjMlrMolu8oWbxpBxnofxSTklkLkygCj8Mx/+MMfxuPxMHPmTAwGA2p1agGNgXwlm4CmpiZ+9KMf0RKN+/vTn/7ElVdeydatW1mwYEGhXSszAlEU6XX5qTWN/1RXmTL5YNPbGPTKTAdra8Cb+cXoDXozTuHOsM1gW9c2Tqs9Ldq4SzJk9++HfzwC85vgygUpOuhyyCrZ9PXB4hFFSIKp8miugIv6iqS4V0EBSJrfGbW/rVZJu7ois3fWF/Khdg5AZQZPpsoIIQ+iKKa+hF2HoOnd0gxC32YplOaee+Dll6XvDx+Gd79b+ru2Fr7xDUmtZQzUHuggvOT9KIGO4Q6Mi5fDv/dK+3G3QeO72WE9jxX774b5X5bfiChKCXGRAFRMl5Z5jsNTCyVP+xtABakFM4d2J/42TOGl+k+y6rQb0dkW5+dpV6hg3u3Q/oiUAIsoLTNHQ200eSYnWizSce3qihaMOpa1uSvgko21FlVGVCSpodjt0jbrsqvRxK619A1GGI8Ko3UVdaxvW8/Xz/26tEChlU+8DTqKk/BZAgqtgzCyWNYo9zrG9Ue7V1EqZJY0sLLpJUdLQdVxozSZm9jSuWWUnck+Qxkni8RqUfIXTjIKNubvvvvuou383bEXSJQ777yTX//612zYsKFszBcBdyDME9tO8Ilzy3UBykxObDobe/tkErV0NakSfzJkmhZuNDXy1IGnUhfu3QvPPw+33QxvPQP33SdVKa2rg8suk4zpERx1HOWSmZekLkxSEIl7s8TU0BBZpR1BhUGpxhfyoVfLGJUxY74ph5JLYBCM2dvY9DZc4ai2dSQoTbkPDcH9f4T/+wEcj8oCKpXwvvfBrbembiAckHIWIGv4T7ZCQrOOe2l/t43pwMGBqCzlBXZYvx7qpO0G1VZC9hWojvwF6lZL8ezdL0nnfWiP9C/ogGnXwdnRgkm6eimuV1BIhseUc5ISUecnZmCifd9jXMwF1WcWlogsCInwm9gxHNoLxx+PxiGLYF0kheJkkjuNeebzNOYjYkS+aqnajEpMis9euhS2bZOu2dHg7x8XT3hdRR01hprEPaoyRD2pI4z5CfJE50NBMd+CcPKLgQxsjkulQiJUZjTGvEVnKVwlCKT8icBgmkSxbPE3bxfo5Qe1y+qXsaVzS87Y/lOJgo3566+/vhT9IBwO8/DDD+N2u1m1apVsG7/fj9+fiAMbjiahBINBgiPKK5eB3iEvbl9pjk1sm+XjfmowUeezQlVBr6uXYDCIIhwmEtu/UIHC25v4PIJwOCytc/fdiFYr4kc/KsVjRwmEAvHfoth/HI48R+Rzn4NAP8I0E+K5H5Aadnai+MUviFx5JcxLTZgKBANEwhEi4USYgyIYJBKJQCRCKByS+hCJpPRzyDeEBk3KsRTMi6jr/y8OjwOVQeaxazQi9PUhZjn+4XCYSDhAWFSllZOP9y8SpsXawnrfeqlvg7uIVN+O8j3vQRH1xIs2G5GPf5zIZz8LU6IKK8nb83YiqGyIwSCCphbR2Qr69HCbE0MnqNRVyl4z1UozOxxHaLQ1c7DvICvqVhBcqkXx42/DJYOI7WsxqAwMqKdQKRxC+e+pCKSHk4iCEjHoIpy8j0s2g2Eait4/EFn12dQVIkjGd5RQOEQoNHaFDCrmSf9AGtwM7URx4LcQCSBqKxEbrwKVMX5dotWicDgQ29sRV65E4Q5nvJYBIuGI7HEMC3pUdCe+mzIFxdq1RC66KPV+kSHel2ScbQjqmqzXWd7byoISJV8762vxdQS0iL4hUJhStpfrN6T0IRJGjIhFf0ZlOvYOjwOtQiv73ch+K0IhIsGg7HGKtc3nGVvI8chFIduKhCOEh/YRqb4g/iyo1ddycOAgcytTC6Xley0Ues0ACJo6xOEjYE0NORvyDaFT6lKfqa52xJpzZZ+Fc21z+cO2P3BmvVxeTnEYr3dmvtsflcbT4cOHeeCBBzh8+DD33HMPtbW1PPPMM0yZMqVgj/rOnTtZtWoVPp+PiooKHnvsMebPTy/SAvDDH/6QO+64I235c889h8Hw9plOyZd2F+waULDWs69k+3j++edLtu0y4894n8+IGOH1/textllpDu7m6IG18e+ag7tSPiezu3c3a3vWMv3QIbpPP50pH/sY7RdeiLe2NuV785EjzN7zKpsuvx2efhqFGGRK6A1adyXCYow1NRgffZSeEXUydvfuZm1v6v6bd+/m6Nq1KfsY2e+3+t7C2mZFKSQ8joIYRHS+zlPHG6jRpCdC6ru7Mbe30z2UOXFrd+9uOjs72bRW/pgANAd30yHYMW7dwEtMZUn7Hjat20vj0qXMOXSIoTXT2XbRzYS1WinZdefOtG2Yw0dQ4WNg+1pMkRNoxL/Sr1yY1u6A+0D0j/R+TD3Ww8HXf0XTjodY4Hmd4OH/QxdpR+n2wIswOOO/HAhcQ+BggBpNDZcIFkRU+AQrvcolOBVTGVZMwS00EhlSQ9pvPpRyLrIds7U92duMHimfQhsZpG7bN2hVX5Kyv+ZduxD37qVNKdIkHqAtw7WcrZ/W8AFUpN6XzTt3cnTt2py/X26bNaGteBR23IrC4ulHexwPcUjab3gXXqEbl0IaFO7t28uT3U/SEtqd8R4fyVBoiFZnK2u7i3s+M/22nkAPx7zHWNua/t303bs5lnTsY+dCblvJz4fn+p+DLI/Ykc+SQnAEHViTqscWsq1dvbvYbRU5euCZ+LJAJMC6wXVE9icG2Z6whyNDR/K6FkZzzRgi3Zgi7XSrUkMs+wP9HPQcZG17YnvTg+s4ptJlTJjf3ru96NeKHKV+Z3o8+SmhFWzMr1u3jne+852cffbZrF+/njvvvJPa2lp27NjBfffdxyOPPFLQ9ubMmcO2bdtwOBw8+uijXH/99axbt07WoP/a177GbbfdFv88PDzMlClTuOSSS8oKOzK8cqiPgYP9rHnnnNyNCyQYDPL8889z8cUXp+VNlDn5mMjz2b6pnTWnX4bicCvzWtbElysOpX5OpnVTK2uWr0HR1sb8j30Mrr+eWX/8IzidiNdcQ+vmVtYo61Ec24f4tc+xZkrydk+wIHm7TifCY48hrkksc/gc9B/sZ83C1P0rWluZF23XsaWDixdfjPZoaj/bNrfx7tNTQwgBDm14kRktZzK3em7adzgcCGvXpvRB7jfXtw6wJlMbrxfFL5/gtL9+B8Xe/QS+fzqquXNYs3KlFJbxox9hOPwb7C1XZdwHgND9AqJhCpjmQMiD0P5PxGaZfR4UWVhhZargQhjaA2KQyNwvQ1cXgttNs+oWrIF+6S0TtQfERQp41ozl/JVcaL+QSn2llNsQOY5i6xfQTP8IpqqVWfsnbUhMORfZjtma5dnbFAPFwQEWzFqTsj9FaysIAvNXL0ZwGjitPnNoTKZ+hgamsOW1/6Tcl4qjR5m3Zk3O3y+3TeFYH2LTe0GVv3KOL+Sja1cXa5aM/jgKfTZEpQ5sSwFw7XGxctpK7J3HM97jI9nTu4d6dz0XTL9g1P2QI9Ox39O7h2nuaVw4/cK07xStrcyPHfuka1FuW7Hn2LGBY9zx4B385AM/yfiMzfbMy8WnnvoUv1vzu4K3FYqEOL7tOAtMQebNSm3fuakz5ffs7NlJrbeW86adl3O7o7r3wn6E1r8gzkhdb1/fPhqcDVLNgiiKQ63Mb7k846aOvHWENStKd++P1ztzWEYGVY6CjfmvfvWrfP/73+e2227DZEpMhVx44YXcc889hW4OjUYTT4Bdvnw5b731Fvfccw+//e1v09pqtVq02nSNZbVaXTYoZXD6I1iN2pIem/KxT8XtD2HUFq+oyXgzEedTqVSixge6SpTJ+1YqUz+PXEetTm3z6U/D7t3w4x8zo6ITtckAHzxLUrDJtl2bTSoGlbRsR/sOzrPa0o+FQhFft9JYiSfiwZC0LKVvI9Cp9QyKfvnjW1UlSQ1mOfZKpRKFQkAxsk1HB/zqV/Db30ra7oBPq0I9uAfFRe9B0d+fSJjMckzjhAahYqXUF7UFxECiX4fug77XYWgP7xzcjiaSlJypqUR52tdhyxY4+2zads3Haq7lLZeHFfNvAMt8hN7XQWVEsJ9JpdGJN+SNHg81rPg5CCop4TQXw8Ngs+X8LZnORdFR6VAqRPQaPREhItVNUCpBEFAGusA8I+u5VSgV8v3U2VCJ3tT70mJB6ffnPJeyv130QYEx0F2eLupMdWM7jjqLpCIV3YbdZGc4NExDPtdjFEfAQb2lvujnU6VSoVQp02KyA2IAi94ivz+lEqVSKYX2eb1gNKJUq1EqlahUqtT4+ehvXH98PfMr5mc+10ltC6VjuIO24bbU7ea5rUH3IE06PUq9Na39yGvohPsEp9Weltc5GNW9p1aDEEm7V3wRHzaDraDf12BuYMA/gL0itwzxWCj1OzPfbRcsTblz506uuirds1NTU0N/9EUyFkRRTImLLzN6hr1BzLqT17A8GfnSQ9vpcHgnuhsnFYIgpMk7jpoFC+ArXyGkVcMnPgHOgwmN+cwdSFu0r28fM4bekDTaM1ConnHEPFdK6pRDoZB02DMgr0wiwvXXw/Tp8IMfSIb81CmEv/oBvvK/18HHlkPzEujMs0S6KEoa8L2vSkb7ho/By+9KbdP2EBx5APrflAx5QSUlnk65GmbfLFVwbG2FqVNZX3MNkXMe4q3qy2HaNWA9TdK+ft8H4LnnMGvNqUlySl1+hjxIvymHoguMQkN8tNScBX1vYNaa0yUhPe1gzFz9NSs6OwZxhETrokWwfXtRqwtno9fTK1UHHQvKaAJslCp9Ff2ewuyFHncPNYYx9kOGCk0FroArbbk7KJPIHsNiAWf0PHs8krQskqLNoG+EOpeggEgYh8/BTP1MjjqOFrP7ALzW/hqrmkbmGuaQNY3S6+5lWqQvJfk1Ex3DHTSa8pOr1al0eIJjL5YHUelWrZx0a2bObDqTNzty1Pc4hSjYmLdarXTKvBy2bt1KY2NhmsRf//rXeeWVVzh27Bg7d+7kG9/4Bi+//DIf+tCHCu1WGRlEQKE4yTPsTzJWzqjk4U3thMK5H6JlkgiMohJkJCJv0Gg0DKxaLL1IQh5JsrFAImIERXAIfF2pXyTtz6K1FFSYR6w6E61ja8F9ARjyD2HVVpCSIyoI4PdLhaHOOw8efRQOH4GPrkRvNuOMiJKSSteI3zBy0LDnf+GZM+BhMzw+HQ7+GrZ9GY78EU6sTa1eO/3DcNq34ZyHeHDq1+EaN7xrN5z7MCz6TooKjkJQcHz4+IiXvyB5rEUx3ZgvhDzkGccV6yJwbMekNaX/puBwinSpHJl0vqXjKUiyjjEWLIDXX5cMykIpUG4RJGNvzEa0ygjhJGPeUEW/tzBjvt/bT5Wh+Eo8Fq1FdlDuDmQuTEdlpaRsBVJ9iKgxL6s1r6ogGHCgUqiYopsir941RrpcXUwxT4lX3QWkSrLB3M6GPk8ftWEHmGfnbBuKhFAr8/MUN5mbxq67H0W2qFqOa3maZVpBVZDDkTCHBg6NpnuTgoLdttdddx1f+cpXePjhhxEEgUgkwmuvvcb//M//8NGPfrSgbXV3d/ORj3yEzs5OLBYLixYt4plnnuHiiy8utFtlykw4gVAErVrJdYvq+euGVm44u3miu3RSIIqipIFunJq7cTJZytnbjXa6Xd00j8V7GQlJxYmM02IdTfnaqrNyYrgjbw+pXl+NJ5juAcyH/vYDrPrjWvjDWvjQPpgbjbv/znfgy1+GEcm752qd7FI0co6iH1pfgz0npFmBnldg29fgvZ2JQY77GAy8Jf2tUIOmGmrPTUg+utslD5+ggBmJZ/xgV3e6NGM4LBnrSC/zl4+9zOn1UY9f8vETBMmL7R9lYaOuLsgglJBMRiO52AgKEEWpWNNof1MGupQrmHfiP9B8rbRAp5N+fw6xCUEQpEFpvhV1M9Dr6WVlUx55DNmI1kCIUaWvot/dCxX5n59wJIwq35mbArDoLAz5h5hC6uxJVs98zJhvbk4x5hvNjRweOMxCe1LCuKqCre2vsLJxJZ3dnbQNt8lvM+yTZqdGSa2xlh53D43m6OBZY5OeqzlmPHs9vSzVGGUTSccyszXFMoX24XZmVeWYGc0Dp9+JSWMiHAnjCrgIhAOofA4GB48QCAcIhAP4Q34azY00mKSq4YO+QbZ2beVvO/8W/z7WNhAOcPbUs+Ox/x3DHXz1ha+yvXs7C+0LU7apVWl5/AOPj/k3lJqC74w777yTG264gcbGRkRRZP78+YTDYa677jr+3//7fwVt6/777y9092UKpOyXHz96XX5qKrTUmnTMspt4/VAfZ7VU516xjOSZty1JXRadns6oQ93TIxU5ksFeYafb3U3zKD2R1YZqiNSD90TiC7c7paiTVWflYPdmMKZ6XTMVmzGoDXSG/fkXRQHYtQt+/nOm//lPKP1R7+z998NPfiL9PXeuZGi7joKhKe4ZXyZso3rHP2C7Hw4C20Zsd3hfYlq9+Qawr5YMd1MLHPodzP58om37Y1KBFkOj5BGur4fmZnlDec+euJHdUtnCna/cyTULrpG+83ZIfZQOElqVFn+WMKas9PdLeQY5GLcwGwBtNTYhhCMWZhMKRavgjk0a06OwI7j3py50uTIOZGPEBksW3diKMg35hjBrxygwoUoNszGoDYT8A2BrGNt2i4BZax6dZ74tapS73RBV02swNbC+dX1qW1UF+7rWce2Z36RL6Mp8TQaGRlVAyxVwYVQbqauoo9vdnWrMB2QK8o2g39OPziAVWUo2dv0hPyqFSjKktSa6XF3s79/PM4eekTWOL5pxkVRPAtjVs4sHtj3Ant49PLb3Mal9WGofjAT53PLPcWGzlFj8WttrfOHZL8S3c626l/uf+iH+kPT5Jxf/hIgYoUJTwfrW9az+82pUwI1m+N3wN1N+y/++43+5/ezbATg0cIgHtj3AA9sekP3d3zrvW3Fjfsg/xF93/hWQknyTyVRpfLJRsDGvVqt58MEH+d73vseWLVuIRCIsXbqUWbPGPvoqU1xEkbI1P470DPuoNUsJ2me3VPOHV48yy26ixpSetF1mBIHBdA+SplIy8nUZpvizGfNGO1tPbARV4Z68TSc2sbxhOfT1gr8n8UVfH1QnBmcWnQWf+wTY8pPjNagNDCgskie8IsusTSQiSTHecw+88AIASiA0fyqqBfPgs2fBnh+DYzcM75EKGoU9sGYHWBdC2E9EMKKO+EGhAUM1TI162lUVoKsGa1IV2+ozgDMy98fUIuUeGBphwwZJ1/krX5Fvu2kTXH01IFXi3de3L1F4Z3AH2BalNC+0ymbSiil1BSYFdRdRc+SftGmi78KBAViyBDiRbS0g96BDrJgBzkPSuQCYM0cyKLNg1Vlx+BwJY360x5rMBdryRqGW8imStqeLuNOKA00EFq2FLldX2nJvyCtf4A2kgdS2bdLfbnf8XBjUBrzBRM6UKIqElXrE4DBDviHCYjj+Xberm05XZ8Jwdh1G6T1Bp+dxAuEAF8+8GKvOCsCbx9/klbZXUgzomHF8zHGMz6/4PPYKO/v69vHY3sf4zebfYA87qBRdvBY0pKz3l6v+wtlTzwbg95t/zzee/gzrjfC3h7+U9jPvuOAOOpwdzNXO5fnDz/OLjb/gFxt/IXtI/v6+v8eN+YP9B7nrjbsyHvNLZ14aN+ZdARebTmyKf3fIBMNuGI5GA7qDbtQKNWqlGk10JtCugv6IEqNah1alRa1Qo1VpU2ZSbDobLZUtTLVMRafSoVFq4u00Cg1L65fG29qNdq5dcC3drm6umHMFGqUGjVKDVqXNv3DYBFPwm+673/0u//M//8OMGTOYMSNRWdTr9fKTn/yEb33rW0XtYJkyJwvdw36WTrXGP39k1TTufekQt6yeVc5dyEUklJ78qK0Bf192Y35EoacYtcZafI69MG1FfvtXKiVPqkrFoYFDXNZyGfQrpZmBGCOMeb1Kj+jvTxuEZDJ8NEoNbZop0PtadmPe54XrPwoDg5LBetVVPHFZM+9q2Qd//A9seDZ9HYVGCoexLkQ0z2O/WsMLdedz/bnfhf7fwjlRT7u3G3rX559oClAxE/o3gukMKZygsVFWnx6QPMZRlTOdSscie5Lx7j4KDVF5xnFK3hy3MBsAfR3GiCsRZqPTRau/5jbmcyHWr4Gjv4e50Wq9116bc2YiZsxPIxomlkfs/niiC3tAM/oYeFEUU+61Qe8groArbuQme5gD4QAXNl8YDzl6pfUVDvQfIBAOMOAbYE/PHrZ2bo0byd8+/9uIoohCUPCHrX/g+SPPp2wvHPBzybrjPOz4X16ovg1rtPjat1/6Nne9cRdfe/Fr8fbzNSJVSrjhlV/wq3m/QkAKf/r5mz/nB6/+IN7/M7QQBjZHJ6u2fGpL3OB88eiLfOO/38h4LG4/63bsRjvrjq3DGXDy3OHnqFbChXrYNCKyLzlBW6lQslQHW3ypbWLGbJW+io7hDuZWz8WkNdFoasReYY9/r1Fq0Cq1aJSaeHgLwKyqWdx65q3s7tnNyqaVkiGtVKNVatGqtJw15ax422X1y/jPB/8T316Nazdf19UQNs1Fq9JiN9r56w7Ja76yaSW+b/jQOLYjIEJ15qJQs6pmcfeld7OgdgHTrdMztgMph+P8aedj09u4YPoF1FVMonycPCnYmL/jjjv4zGc+k1akyePxcMcdd5SN+UnEyV5d+mSjz+WnypiIIVYrFVx9ehP/eKud684sMB78bYRKoSKMn7RgGl0N+HsBeYOdvr6MBo1WpcXgOw7mD6d/KeehrK6WthdNqpQ1yPv6IGkGUhAEtBF33om7giDgVxpTp759fbD5X/DPR0A1CE//AYb3wsVecAHf+BWs+jTtG+9FKQ5LIUfWBVJITCym3TJfMrijBrpYfxlO5VocGkFmgFQtDZAKQWWAkBeeegrWrIGmJvjxj2F1bnWJr5/z9cQHUUzE5Y7BSzyZ0Sn1OL3RBFiLBaor4lVPM5FXXLtCLR27sB+UWmlAlQOrzpqqGOPrAn19zvVixIxRd8BNl6srxTAWBIH5NYmchVfbXqXX3ZtiRMcMY7VCzefPSIRt/eLNX7Cvbx+anpfY2HeQ9og23l6pUKbEJ3/mP5/hv0f/SyAcYNA3yLde/la8bSgSIvTNUPxe/cSTn+Bfe/+V8fd4vu6Je9rv23off97+54xtv7Qq4aXedGIT/9j1j7Q2c/thcycEtI54zLw35MU1Ii/GFYFp0dswFAlJseRD7Vh1Vuor6uNG7BJdgC6MqBVmtMpUj/Ai+yI+sugjccM52XO8pXML063TMWqMuINuLp5xMX96z5/QKZTMdrzKDXXvTlknuc7FtQuupbHz36y44H40Kn3cex07pk6/M35MF9Qs4P4r7ufSlkszHrcYp9Wext2X3c29G+9NOfdy1BhreNfsJNUsZyM4D0Ny3kEUpUKJUqGUruWRYZkyNJmbaB9qz2nMg3Qfnl5/Otu6tknOnJOMgo35kaPhGNu3b6cyx7RfmTLjySObj/O+ZY1jnyLOk4goolKmvpSbbAZqTVq2tg2ydGoRpBdPQaw6K97gMdIiE7U1MJxeXjQQDkiKCpFgPNlSDlNoMP+kWrsdursTCilyxmZfH6xKlX/ThT25QwUiYckrPbSHZQPPgnqutP116+BHX4bn3pKkp94BLI+u8x4tmOdCU1IYkXk+LLsL1tyS10+qNlTT4+4hJRBJMWK2YSThQEKRZiTHj0PUA+k9fTHNe15Njc5xOlNyCoDMyW8KhZQsW0JCkdCYkz8LRVW5GOPB/0ofLr4YLG6IpCZWiqJIMBKMG8aDvkFCkdS4+o0dG/EGvXgCHjYNbSKwP4A2AJbXvoSr7p0pxs/PXv8ZDp8jzSM96B1EEATOn36+1NDbyf+88jNec34rzWsdCAeYbp3O6x9/Pb7dZb9dxu7e3QB85cXUsKqplqm0fiGhFPKl577Exo6NssekUl+ZYtA9tu8xXjr2Eh80wTPH9zKYJK6kVaaGJJ5wnuDgwEHZ7QKExTAqQTJjYqEUMYNXq9KmhFYkH+Ml9iX0z+qPtzkyeITF9sXx9pqkxO6r51/NnKo5KdvUKDXMDb3Iu667Esv643Fj/osrv4hGoeGGpTfE2/39rV/w2amziTS+n+eeeY651XPZ07uH28++PR7fDUDrQ2C/UHYm8vLZl3P57PQCSeFImN9s+g3TrNPiy+bVzGNeTdQBcsDBkhGFoJIxaozoVVoqM6gVmbSmuGxn61Bryn5Khr4RetZlb+PrAl1u73mTuYnnDj+X965nVs4sqP1kIm9j3mazIQgCgiAwe/bsFAMpHA7jcrn4zGc+U5JOlimcQCiCSqEglEW7+lRn07EBplUZWDF9YgeZ75hv596XDrFkinXcBhYnEza9Dc/wHhljvkrWi+wOuKNJSdmTu4RkT3Au7HY4dowTzhPSdHHYm6aNzdAQjKg0rYt408JsKoKDsPsHknrM0G4p2TQszWOvCgDre+H6hbBzd2KlM+qhaSac+yXJ217RnO5VD4mgy19mc371fHb17GK1RiNJWMoU3EvD3ysNokbi9IIlMQvStXwuM575R2oy71tvwYoMYU1hn+RRjlFZCYODRb8fImIkLs/nC/mo0FQQioQ4PHA4zWMc+7vR1BgPZ/CH/Ny35T7ZdoFwgKV1S7l+yfUABMNBrnnkmhTDmLCPs0MHuXPn41ww/QJ+ueTyeJ0Dy48seINegpFgWr8X2Rdxy5mJQdrFf7k4VeIyKk1+mxU2mLamGvNv/IxOl3wtgSnmpIGEt5P1PQd5q/+IbNuR8eHJBq2AkGLMVupTn6mL7YtRKVQpoRexsIqRybMfXvRhzp16LnWd/2LZtI+gGWGEJ3Pn6jv58tlfRikoefLAk3x40YdT9qEUEoP5B9/7IA++90HZ3zaSL676Il9c9cX452we5NXNq1ndvDr9i7peFs1aAy/8Op4AW2+qp95UH48dD0fCaHSV6MQgQaXk8Z5umc5/W/+bvr2go+AE2N29u1lQm8jZKWVYWdtQW0p4TMlQ6aWZwGyEA+lKWjJU6isLkkBVCAoieWjzT0byNubvvvtuRFHkxhtv5I477sCSpHGr0WiYPn06q0Z4rcpMHA5PAJtBTa/Ln3E25VRnXr2Z7e2OCTfmAS6Zb+e5Pd1cuuDki8UrNTadDU+/THGREUlzMVwBV17GfEYUqvQYfbsd3nyTtzq8rGhcAQGHpNMcHtEvQZA8264jMLSbae5d8MYN0HQFTJOkA3VhJ2z/cep6Sh14ZxD6wgFUQxukZQYDfPSjcMstUuz//fdDzWVRBRQZPH4w5l/NcHbVbP6y6y+srmuUZh2mTk38hkxkMuZf3g0f+REgGbEHBw6iO2cp1kf/zNAFK/GH/Vg2PEPHde9m6vBxmsySak2/p5/nDj9HhesgkZCL9oFfEggHqO/ay+DaV9lfkxhsHR8+zrdf+jaBSLpSRiAc4IOnfZDPrvgshMP0+wZZ+n9T04zumPf15jNu5itnfwWT1kSvu5e5985N/01RPrbkY/zhyj8A0qzPTU/flLHttQuujRvzSoWSf+/7d1qbpVbY7XBIU/uedsnbGt22nCGvFJRx73KM2VWzcQVcqBVqvE4vtVW1aFVaKpQOLq9M1QO/YckNOP3OtLhktULNrp5diYaBAb536b34I4G4QRzzWmuVWgzq1NDZdTesQ6lQcv+W+7n5zJszHhOA3737d1m/T+bGpTdK239uL+ef/eWsbWMSj73uXpbULUkJ7Zk0RCIpydgqhYpQJIRKoWJL5xaWNq4E37b490qFUt5gjATzMlCT2dixkesWXjfanoN/AJ/SkLVJLDnbG/SmXSO50KsllZxC1ysWbye7J29j/vrrpQdYc3MzZ599NqpRqESUGT8GPAGsBg3DviD+UASdOnM4wqmMVqXAFwxP+O+fZTfx4r4eQuFIWijO2x2rzlpQpUB3MItkXD6oKiDkkoz1GGYzDA/TNuTgijlXSHHrGqtk1Ifckmzc4Qdg7e8lT3tEylJrBmjdBWoTTLsWURQZVNth+ockD7uvDmafC8ZmEBQMfb+RKrMKrl0KX3sgroIRESOEKvT4e47jq7KkGKnxokveAP0KP5sOPZvRy3zJzEtoNkvJtfv69/Hw7odxOqoJH/gDB1psUiJgYA9Pbnmem864iXfMeAcgxTzftPYmlgsDHAvC/qCYso9NHYuZZ5IM5dfaX+PSv0pxs195Bf53J4gKuOlN+GXwJynycEcGj3Ddv67joyb4d5JCxcIusPjBdNE746dg2D/MH7b9IeNpW9EQ9fr39RGpqaL9aHvGtoFwID7o06q0WHXWFMM1OYY4OZ5Wq9Jy9fyrU1QvkkMrkhN6FYKC313+u7jKRuyfe/ddvPddX6XK3ASOdfEZiT2f2xNvm9yHHd070q7/tz4p6f4Hg0HWrl3LmjVrpLLukRAcuDel7Q8u+gGZ+OXGX6Z8vnRW/rHAJq2JQDiAVlU6Na58HU2lqv46JjL0214h1bhoNDfyZsebfGb5Z+DQtpJ0YTQGdgqDW+jTjrI6cR40mZs4Pnyc2VW5C1KlkOuaKLKRnqyqFasIfLJIUsYo2CI///zzS9GPMkVm0B2k0qihx+mbFMbseBMMR1ApBS6cU8uLe3t416L8E79KxRWLG3hi+wneu6xporsyqbDpbRwL5phWTSKvB21wGL9CMkLCkXCK4VulNKAMOkFj5YTzBB1DrShdx7C3rmVaXS8dA49gdR+gxzCLmvm3YPKcAF0tDGwGh7T5ACp6lJUMBz3s081n7/E2rm05RJO5CbXCyIY37FT86kdM63Dzrh8vYkgt9UF/tY+BagMvntPMzKgh/5tNv+GzT32Wiw5D+6twYERpgsc/8DjKSAD8sGVoH5c9+LGMP/vB9z4YN+aPDB7hv8f+y/4hOL0Tnojm5Vks8PjQVt41KxGq4Ql62N69nQUm2OwGR5LjsMoN/dZKSRrR0BQPhVApVDyzUMWHDyt4ZpEBqy7ETFtVStl1m97GRc0XsVJ5giHl7IRixdQQcw8OstWcyGmoq6jjB6t/kGI8J4drxA2Cri6s0+by1jveSjPMY//0aj07undQoamgUl/J4Ffym8XRKDU8/P6H82oL8MnTP5m27G+9GznfqIDa0yRjPkqzTV7ByBVw5a8Fr1CBoBxzgaF86fP0STUXSoBWpcUddOdlNPV6eqk1ysvQloqcg4wMSdyNpkY6nB00mhuzFrpKH8iMvxfZP7CDgKF0xQ2nmKVk34KN+XFmwDsQry68yL6IHd07xiekqIiU3eunKA5PgJk1RvRqJd5gGOtEd2ic6XX6qTXpaLDqWbtTPp60mMRyFLLRYNUz6AniDYTRa95egys5Xj72Mvv69uENeqjo3MKz6+9M8QZ/b/X3iPmc7ttyX7xYSZerCwGBa97o5R+aPxIIB3juw89hr5BCUP7ff/8fr227m0DIx2Wv/y0+pa0ELArYdu0fmRJyQtCF4umlLAr0oFUAPdDoB6LScNuGuvDN+jzzvSfAPIu9htP48old7AnA0WAIkR4+b4F7h6TEv9Uz91P/5F+49t57MXZJcZoBBWjf2sqOmdEfogfcg/giEWlaPSnZzqEDa1QiTqVQxQ3ViBihIuKCiJmKShNLxaWJMImooRuLZ46FtwDMqpzFRc0XcVbtcs54YQ+rLjoLrVLL6c43WFJ1MedOOzfe9vT603nmQ8/Q3LuWmxqvRZNkUFf+8wl0V14BrlfBfgErm1Zyz2X3JGK8f/ITuOoqmLuH711xRco5bqls4YWPvgD7f8ln5ySFrwSD8MAD3GtPhJ1U6iv52rlfy33hdHWhnjmT5Q0tWZu5Aq4J8eYOqusk7f/6S/Jq7ww4E4V+8qHpSjj+eDysKxtjjaHudZfOiDaqjfR7+vMy5nvcPSUNsSlmcbEGUwNvnXiLAe8ANr286EGDqYFOV2eKnCMF9uGE8wT1plQnlUqhIhgOSgIBeeAOOKkyZq8RpFPp8IV8ozpGTeamjInR40U+98Dx4ePxGdAFtQv48/Y/l435MpODQU8Qq0GDXqPEGyitasRkpGvYhz1awKnGpKXH6aPWVDpPVp/Ln1dxqPcta+TRLcf58MpxUAWY5Dyw7QH+vP3P6AW41gR/PLA95fuvnvPVuDG/tXMrj+59NP6dOgSLh2DTCSkzMDlMIRTyslzpphtYbYMFGpivgTlqeMELAUELQSeoKzBH3GgV4BEFHBElG3w6OhU2qhQRXtQ0cbtxKniPARCpOZfaWWfQFDWctUot07qf5P8a13De315jyf++H4VHmmEIVVey730X0HbdGm6x13J7tP0T+5/guoXX0ezbD75uMDTxwdM+yJVzrkR7tA1NWweqy9akqLB0u7rZO7wTQkZWzV3JltO+kPW4BoOSgbygZgGfWf4Zzp5yNvWH/8XlMa35w1bOm3YNqBKhSlWGKklyLnIIpo54iQVU0DQH9j8PSOElKSoxH/wgfO5z8Pvfy3dIFEkzVNRqyaAn/1CLOJ2dcPbZOZu5Ai6araXzOmakwBAAV8CFSZNb5jOOcQq0HS+wU6Ojx93DVEtpZHWNGiP93v68FFIGvANU6UevST+e2CvsdLm6eOHIC/EwtpHMr5nPnt49I4z5wnit7TXOmXpOyrJaYy097p68B4eugIua6uwD3kZTI+1D7aNShkpWwykIVUX0GS1zX4gRCpnFUClUBMKBtOTqZDqcHcyrlhSAdCqdlMx+klE25k9RQpEIGpUCg0byzL/d6Bn2xaUg3zHPzr+3dfChM0tnQHcP+6jNw5i3GqJe2GhOw9uZ5fXLcfqd1ClCGF37+PjM81LCK5Jjda9ZcA0LahegUWrY2rmVs5TTaKnt5YPnzcAoBuJeeUSRHwz/CUWG99Oa+nkItUvAKxlDhoueA309BuM09u39JKve/33J23Xw13yg5dOAAAe3AJLH5v4rUxUv1j93lHNmfgbFtXeBKOJbMIej11/JvJvv4DSdjtNG7H9Xzy5Obzgd+oLg7QJDE3q1XlISqY3A7oNpCjxdri7sijCEDHEJvHxZULOAXT27SPHf6ezSQKJiRqbVEpw4ES18lEqKt6upCa67TkoilsPXLa9vLggY1Hp8IV/mSptyuFxpEphyOP3OiYt71deDp4N8jI5RxecapoC3syDd+NHQ6+mVrtcSYFQbOezJT2kkHAlL+uKTCb0evN60wZtKoSIcCdPpHOl5TzDTNpOXjr6U0djPh05XZ5pnvq6ijm53d37GfGAQR4ScYVQx7/pYBh4FY2iS7h+LTOK6v19SOsuTBlMDnc7OrIPGjuEOLmq+aDQ9nTSUjflTlFg4n06txPc2NOZ7XYF4ASejVoXHHy6pqk+P08/iJmtebd+3rIm/bWzj4+dMgNdwEnHzmTdLKhmDO/jXjgd47/n/J99QFDm/so7zFb0wtJsjkbeYfuhpFENtsDsMptmwJFoZUxBQmGbBoBO/aQ49qlqmTLk0XmBJME6VjKDhaBXEmoQXetg/zLLYy1GMpBrVsRvK7YY//xkOHYKf/QytSoerqRbzD34AK1eys8WAKJBZkSaGrg6GdqUus1jA4Uhr2u3uZolShICyYGO+pbKFl4+9zMXJC/V2qRJsFmPe4XPwSusrvHt9l+R5z8UHPpD5u8HtYF2UvlwUMWlNDPuHCzPm82RCk9jqLoIjf5KMkhx4g97CS8ZXzAB3W/7GfMgLisITWR0+B1adteD18iHmmT9pqayEgQHZr0Syv2vUSnVabYFiYK+ws69vX2KBoIyH86UxsIVWRRXn5jDmG82N/HrTr/nksvT8kJJhaJKUoCxzU5JTgYIHsbEk3GzG/MhEb6VCGVckOlkoeN7E7XbzzW9+k7POOouWlhZmzJiR8u/tRJ/LTyg8uTVJ9WolnrdhmE0kklrAaUGDmT2dw1nWGBt9Lj/VFfl52vUaJTaDmhOO/JM+T2kCA/gVRkk72LEb2h5OKHaoLRAcgtc+CK++H3Z+hxnOt1B0HoWKsBQqoq2KTr1GuXAtLP0p4Us28HztdTD/dmh8F1RMlwx0tUmawh2BKAjyhYxEEXbuhLVrJS/05z4Hd98Nx46hV+sZ8g3BV78KF1yAO+TJT2lHXyd55pPRaOKhJ8l0ubqkMAyPp2BjXtZoiHnms9DqaJXCmpK94IKQepzzxXVIqlArg1lrTtVTLyKlVmLJirYKHNvzLlpWsJNBXy8ZNflSYPXXGKIoFq/wVrJRJkYwqI0MekcpL1sC0ozGXERrJcglwu7p3ZOifFRsXAGX7HPGbpSUdOJobJIilxzD+2gXjVi02ZOvbTobW7u2jk/BqBj6RvBIs6eeoAejJum35lkwKsYUyxTahzMrX8kxt3ou+/v2F7TORFPwsOMTn/gE69at4yMf+Qj19fVvKx3PkWxrczCvwUyjtfhepWLxdo2ZH8nKGVX84bWjLGgorChHvoQj6dVfs3HF4gbue/Uonzlf3sh5W9D5HPS+Dl3PcdnQYXjoxwldeYUGWj4taZ77+6DqTMm7ZFnAa0ODnN3YAldfD3Xz0wtDaWwgKDGoDXjlVHJi0pRJRMQIfmsF9PdDbTThTxThtdfge/fDC7dKetIALS2SNrzViLbbjMPnYIpFkndzB9z5xWkrdXF5y1w4/U50Oq00pa8v/FmT9ozW1oK/R75x1DDpcHYwe1hNsKmBuE9P3wDeE3l5m1O3GZEqz6Z3rKTG/IRjmCqFw5QCnV0yavJlHEJy8iJWZCw4hEJbSUScHMa8UW1MNxpzYbNl9MzbdLacCZRjsZ02dmzkzKYz05YbNcZUmVONDQKDslVlESNEooVAc/UzHAlj041jBXN1RbxgnzMwIlzO2wnV+dc0qtJX0edJLz6YjSV1S3j64NMpBbkmOwUb808//TRPPfUUZ+eRgHSqYzfr6B72TUpjPnZ/xtRs3u4oFAJKhUAwHEE9CXTeVUoFLTUVDLgDVBrfprHzh34P7Y8AEH9NqEzxkBhCbukl5OuFM34dX23bxns5WylA3YIsyYZZvGyCIs3DfLD/IJXT50vFlWLG/IMPwkc+kmh0xhnwzW/CmjVSkRjPCbT6enp8jngTV8CVv0FQgCdQEBRS+xyKSZl3JUYr4gpSYRqZ4kXJnHCe4MMnqln3bgPxqF7TLHAeQtQXoLwCZIwbF0XMWnOqJ/EUIK4oMv8rKUnGRUWhAjH3cz1miCm9nSkhZROCUguRgPS/fwA0lYy68FuRsegsDPmH4vduMBzMHWJRWQmHD8t+9f3V389pJNcYauh191JjrJHuRyF/c2xP7x4umH5B7oaaSsmYHyMrm1aOevBhUBtwB9yFDZRAmpENunD6nakJ4iGXfGJsBkbT70p9JQNe+YHaZKXgN4PNZqOycuIrak4Gas1aeoZ9E92NrLxdY+bl7t/zZtew/kDv+HcmA++Yb3/7GvIADe+EGTdC03t4sv5zcGUbvH8ILt0AK+8HjSXqmc9wzjI9pAudLgc2ndjEbPt8ePXVxMIrr5SSOt9/Fvz85/DQQ3D55QmDOjCAztjAkH8ovko+Ba0Kns6XVip8nSiNpkYGdKJsPH4KYX+8wJEv5GOKuprdziOJ7ytmguuw9BvzfTGHA/LxulHMGhPOQHrI08mMWWuWfpO6oujFbQrForVIMx/+HmlGZiJRGePeVvz9UWN+cmDRWqRwuSh5FabLEjOfjwEZU7QBpKJ0yUXscpB3+JPGBgGZPgYcoLbkLV365RyVerMxxTKF48OjUF+afQvs/Skun+OkK+A0ERRszH/ve9/jW9/6Fh5P/hUbT1WqjBr6XIGJ7kZWtCoF/tDkjusvBXK2z8yaCo72uce/M2XkmXmjZLTbL6K9YoEkuZcWElKd2ZjPRMgpefizkbyfbdtY9rWfY11zFfzwh4mLx2SC1lb48edAp4CaEVPVgQEMFU04kjzzuZIZNUoNwRxe8TTGYMiDpMJzWOeRJB2z4e+TBk+A+cQAwsyZ0d1H96/SQ8greRPz1W8f3gdmGUUKgIoKzCFlYWE2oww1Gk9MWhNO/+QYoFh1Vun6zBTqNJ4oDRCO2g2BgbwVScKRcPHi9jMQ88zHyMuTnEHNJl9mV81mf380Ljs4BGpryvddri42ndiUNvgv6HjEwmxAeo4MbIX9v4DD9+ddBwFIqV9RKE3mpoJj1gFpMDzrM1iO3Y+phMZ8ttnUUTleJoiCw2x+9rOfcfjwYex2O9OnT5dKTCexZcuWonVusqNSKohMwpMdjojx8fbbMafBEwihz1Dx1qxTM+QJYjHkV1SjzDggCAgIRMRI+ktKpZeqXY4k230XGJReYtkIR+Bf/4J77oH165kXW65UpnrbtFowNEhFgAwjyqYHBqmwLcXZtnPEz8l8zxnUBjxBj6R5LNdO5ndpI17QNjLakISZtpn8U+3ijK4umJ+l8I6vJx5bW7/tINx6M6cNbmF3725Oq02IbPa4e/IvJOTYAQ1r5L+rrqZiyFuY4dvdDXX5Jb8VsxBQIZg0pkmTB2DT21IGmxNKsmc+MADayrzOUb+3v2RVaGNYtBaODCZmofLyzBeCoEwLi9KqtAk986BDmolM4q87/sqKhhXcveFuNEoNa2atodnWzO7e3fnHcqst0LNeurcBbEth1melMK1xosncxIbjG0a3sr6O46YlzO9ZC3WLi9uxKB3DHbKDldiMQiwfarJT8Bl9z3veU4JulCkmw94gZv3b11jtGfZjt8h7Ry9ZYOfZPV1cs7x4N2gwHEGpePsNmoqJRSdNc2eqmFgQuYz5xx6Dm++ADkkWT1SpOLR6MbO+ey9s2gRVVZCsmKdvkKbBR+IfQKGtJpz0ks41eI4Z83G5v1gcewylEkIhUCUezcbQIOjPYLTGvFKhxFVZAV05Eib9vWCcDoDW6QWbjXPN53LflvtSjPleT2/K56wEBkGbIZyipgZF/0C8Qm9edHXlbcxPFPEwm0mAVWcddU5CXnHjhZBizDskQzMPetw9Ulx5CRmVZx6kpHhVHsdIJuk+hYBDUnCJ0upopcncxPnTz+f86efjD/l5+tDT/Hvfv9nVs4tfrPlF7n2CNBsz9zYp32WCHHsVmgrcgdHPiHcqbCwy1UP7YzDlqlHNVCoFZcbKuB3Ojnj112SW1C1hW9e2U9eY//a3v12KfpQpIoOeALa3cUGi5OqvI7EaNHj8xdX37XX6qamYIAm8UwSrzsqgb7B4xnw0PjiejKhQJV5mGo1kyFdVwac/zb73X0iXRcms5jMlY14USUna1DdInrORhNygLCzkI5YMJnXOlJ7MNXcu7N8PCyTPWygSwhwZjirI7ErfYJ4EzAY4kGMw4OuFqjNSFmmUGoLhpLAgQaDX1U3N9Avz23G2JM2aGti7FwpxunZ1wYoVeTXNNx642Ji0JnrcGdSCiolCLeUkZKlsadVZJYk9ReEGUL+3nypDEauuqgwQjBm0YroKVQZ63b2JonAlwqw1p8XM51WV1+PJb3CZjzFvSXjbH9nzCLeuvDX+WavS8p657wHIaJTGdxV75sXamGfLtouIkZNi5t4ZcKJrvBJOPAU9r+ZeQYYGUwNdri5Zw/z48HFWNKQ/U6ZZpvGfA/8Z1f4mgomX9ShTdAY9wbe1Md897MNuyhy3XOwHWI/Tj91cYNGXMinYdLb8NadzeWZinnlRZMH2E4Tf9U74zncS37/znfCT66G9He68k23KXhbaFya+D7mkl28MtUlKDpUjGiKULynScfq6dK3wJUtg69b4x153L/WKCBgKVZBJ72dKSKBCk/6bgg5QWwgdPYynPmFh1xhrEsapeQ4G1/78vJbdL4Mty9R4dTX0FpgPkaw2NEkZtzAbXV3OegHxmHkZ/CE/m09szrhuQbkR+aBM8sxHUSvUqYNFuX54itwPGXQqHf6k+yFvz7zbnV/tB7W8MW/TR597QUc8AfaE8wS1xtqMsyLZDHmQCkflM5gc9A5SqZ88SciZ8If8aJVamPo+KWxPbS54G9m05p1+JyZt+sBNEISTKma+YGM+HA7z05/+lDPOOIO6ujoqKytT/pWZeByeANa3cUz4kDc4rr+/e9hHbYaZgDL5YdPbGPTlZ8yrvYFEISM5hrrgT/+C007jnE98F92zL8JvfpMoyKRQwBUr4omUaTG5AUdByhKFEAuzAaLG2IjQF5stRXWmy9WFRa2TdOnHwFTLVAaTpdZ0tYk42mQEgeEXniJ8dkLG8JKZl/Dc4eekD/aLmObZJ1UUzUbIDf0bwZ7Fg19RAS5XYYPrUAjUk/vZNm5hNjHd/2xNVHqC/n5ZA2h963oe3vNwxnV7Pb3FDW9RGRMJsFHykQDs9/SPu9GZd8y8y5WfMa+qSBvIAMyrnsfevr1SXlD0Hv/nrn9y7WnXFtrlOHajnS5X7hoEfZ6+kucixBhr/kr8GTHrszD9QwWvH6sCeypTsDF/xx13cNddd3HNNdcwNDTEbbfdxnvf+14UCgXfSfZ+vU1QKxX4Q5NL+nHQE8SWJHk4+SfSis94Th9K1V/LxvxYsOnyT9TTDzrlvbPHj8PXvgbn3g6fuxn27CFiNNL6kSskycl8jcAkL1mcIl1OKca8vj69CuwIut3dmGW8RoWyoGYBna6kWYAsVWCdna3UTE0o0FQbqun3RJMIBIGdlnPh4K9l141z8Lcw6zPZ25wEU/yjQafSyRcrKzZ5VIEVBIGK4KBsJdrdvbtpMDVkXLfonnmVIc2grTJU0e/tz7CCRESMoBxnJZ68PfMKRd7GvCBTdXpu9Vz29u6Nf+5x92DRWaQE+VFir7DT7c6dJ9Hr6R03Y75oCMKoVJmqDdX0uguXpbboLJMngTwHBRvzDz74IL///e/5n//5H1QqFR/84Ae57777+Na3vsWGDaPMWD6JsZu19AznV8lxvHD7Qxg1EyxDNoHkmhnTq4tbFTccESdFIaqTkqgOeXy6OQ/0AxmM+TvvhB/9CBweaG6Gu+7CfWQfL9/2Xpg1K7/+CAL4BtJk4mQdS1FjNNnrlGtaNsWY11ZJcpByRKvNdru6Mecot54PzbZmBly9iZsjizE/5B9KM/I0Sk1ceSOgNEDVCjjxrPzOel8D62l5T4cXNJV9Ekx7F+JICEVCozdUs5zDZEyhAVljHrKH4Qx4B4rrEVelh9lU6asSA8VJRN6e+crKPMNsTLJhNiMrtv5j1z/44GkfLKSradiN9rySnvs8fSUPX4pRoanAFciSM1BiFIJiVLMDi+2L2dG9owQ9Kj4FWyBdXV0sXCjFl1ZUVDA0JCWNXH755Tz11FPF7d1JQK1JR49z8hWOSn6hTIbX370vHeL44OSoTVBj1k7Kc/a2JDAImko0Sg2BcIaaDcpUj55+0AlWK/ztb7Aj6UF7yy1wwQVw76fg4EH44hepqGmUf4mIIoiilASW7HavqoLu9lTPfCgERRqspRjzggLZu3PGDDh6FJA0kLWqsc/6KAQFXfOnweuvSwsyGYLHj9NpUVJXkZrUd/7081nXui6xoPZccO5PD9UJeaHnlYI0rEtB0ZVYSoQr4Mov0VIOhQrE3Mn8FSFHilIKSBWPZ1XOYlXTKt5of0N2vaJ7xBXqtP7m45kfL5KfA3n/9nyN+VwJsEjhRHqVHr16bHUURg4QMtHn6StugnMWpphHWThqgplXMy9R2GuSU/Abqqmpic5o8ZGWlhaee06KpXzrrbfQat9+oQa1Zi3dk8wzP9lmryMRyWD5775xUHgg9++3m3ST7py9bQkM5K4EqauJe7ADXR3Mf2ojnHMOfOhD8OMfJ9rNmwcvvQTvWCxJPJLFSxrVr0/TGLbboXOEMT84CBajVHgnmaiXONkIyFeacuQ2Uli2LCUJtlh0L5gGGzdKH1QGCMuEgqxfT/uS5jRDeF61zEtt1mfh4G9Sf8Oh38GsTxe554XjCrhOiqqR49FPhRiKV/aN8dKxl7iw+UJaKls4NHCopPvPxmT1zOdNbS2Y85iByhAzn0Dg77v+znULryta13LhD/mzFrgrJk3mJtqHRlE4qsQEwoGsCcVpal6TmIKN+auuuooXX3wRgFtvvZVvfvObzJo1i49+9KPceOONRe/gZKfKqKXfVTYMs7Hx2ADnzqrGH4yUPDs8n+3bzVq6h8ue+UlBtHhMVrQ1sOUN+MQnUE+fSfPL2xJ64wsXyqyQxzWmMkHIyb6+fcypnpNYbrdDd2dqBdm+PrA3ZgyJKWT6VqfS4c2VPFpXF9eEV0X8kvxlMe4bQUBUKhOJwCMRRejrw2dNNy5jgxRRFBO/V6GGaR+Eo3+RPvdtBFNL7oJdo6WAY+AKuGQVKiYbTr9zHAYd6QNMb9CLQW2QFDvGe+5WjMT7pFfr8YVO4mfxVVdBQ+a8gzgKDUJE3k6o0FTg8A2iFJT5xemfhEzWBNROZ2fWvJGTiYLnIX/0ox/F/7766qtpamri9ddfp6WlhSuuuKKonTsZUCqESRHGMpnZ1THEx89pJhgW2dI2yOnTSqdMMOwNYdZlT3S0GTQMejKEdJQZX/wDYMhRlOPW/4W//QuQTABPfQ2G/70LrrlG0owfDWoTBJ0cGTzC+dPPTyy326FvOHV6p68P6mdKyiG6aKx+JBRPxNKpdPhCvry8XApBkTrgzOHJN4YcYDgNfD7Qjc2LVmWownH+TGzPPguXX576Zdgf9d56M0ptnlZ7Gm92vJlqfJpnwcAmqUx89wuw4OsF9yvvGHOHQ1L7yYOTyTM/3oOOkeXr03TJS00J1aLGnXyv3Szt5tXM4z8bfseH3p0hB+UUIN/Qn1KiFJSEIqGUWcdMBaOSiYWAjiUpeTwYcyDoypUrue22296WhvxkZTLliPmCYbQqBYIgsGyqla1tjpLur9vpy6n5rlAIRTtG5eqvY0QuzGZ4ONV7vHCJFLP+/vdz7Mm/0v6pa+HDH87bkJf1PEY988FIMPUhbbPB8IiXTl8fNM4BT5IMYMABasmwtGgtKQVnikI0pr8iNCQVjHK7s8tx5kFLZQsHqpDyCUbi7wWHEurrM65/3rTzeHTPo9QaRyQfT/sAtD8KMz9VeKfUalRhkXAkj4T0Aqq/OgPj4fEeO+Mx6Bj5dHrxyItc1HxR/HOs0uW4ERgATX6x2mNKEC6QcZ+hiDKveh4NpgbM2sL108vkT72pPk2y8/jw8dQwSxnOm3be+NSNGCOjMub/8pe/cPbZZ9PQ0EBraysAd999N48//nhRO1fm5OelfT1cOFd6+QuCgEalwBcsnZRnd5bqr6Wgz1Wu/jomQi5J5QKwdPTBF74ATU3wyCOJNp+5GV74Djz0EH3L5qAtRpxn1DOfhpwHra8PGuelanoHBuPhQTFFkLRk2nwQFCBnyDY2Qmen5JnXN+avZ52FmbaZHB48LA0KnCN+u68XthyH88/PaNRolBoGfYPpChiCAIu/D7pRyNxVVVHlFvPTZS/AmB9TYuk44gw4x9ZPhRoiWWJ6IyEiIyqtHnMco9nWHP98ev3pbO7MXDyqqIiiNBuXK7QuSr+nf1zlEyeiSJBFZ2F18+px3+/bDblQn153bnnOeTXzTgoJz4KN+V//+tfcdtttrFmzBofDQTgsvYisVit33313sft3UjCZPOGTrWJZh8NLk80Q/3zRPDsv7i1dImzXUG7PfDHpGfZTW67+OnpEUUpavfJKPvS+O+CeeyRD88knE22sVmiQXv451V1krn+loEz3/GYy5uUIBMBgkQq7xJclZhSsOitD/qF4HHJBaGskr/hIli4l9NZG9KJfknjMt9JkFuIFet797tTjC5IqzVAQr82UNVzoXbPeRaN5jNVok6mpocot5uf5KtCYf1t45nV12WsVeDvxqW2EIpKKjNz7QavSpilJhSNhFEJxFJzSCPRLsqx5MB7VX2PEwuXGnUg4qmxVPGKhU9mYqJmIiSJTEu541qQpJQVfQb/4xS/4/e9/zze+8Q2UysT01/Lly9m5c2dRO1emcDyBMIYRGvNKhUAwHMmwRunod/mxGVJDIRqtejqHSldQxRsMY9SOnyTdeM8EnDKIItx/P1zxQ7joInjiCQRRhHe+E555Bv76V9nVXAEXGmWW4x1yxz39MWTl71QmfL7ewo3vGIGBeKJnrLDIyFjkvJCrAgswfTqug7uo0Jolz3cRjPn4S6uuDrq7QVBKsf8gDShUJjpdnVljSK+ad1VxE8ZqarC5QvkZ8wMDkhRgHpwsxvyYE2BzFY7ytCEapsbDwHZ072CRfZFs02RDv+ga8zEEQfLM51KwitLj7kkP6yoRFq2FIX+Rw+XyYWAzWJcUdZP2Cjs97vFRjyslxXRO1hprT4ljkomCjfmjR4+ydOnStOVarRa3O5v00qmLTl3a0JFCGPQE0gxovVo5If17YW8375hvT1teY9LSM8FqMsUajPeWq7+ODkGAP/0JDpwAgwE+9zke/Of/Q3zqKbj0UqmyogxunxOtJstMSGAwTU1FtoiK2kSP4zCzq2aPrv9JoQKxMJu8C80kk6kKrCDg9DsTcbRFMOZTqK2FLTqufwAATLlJREFUYVVCoaezHeqn0jHcMb7qDtXVmIf9OP15zpLkeeOOj0rM2AlFQmNLPNU3pIZ/jcTdhto0M14Y6tW2Vzln6jlpzaZbp9M61Br/3OvppcZYAo+4KEJwKO+CYr3uEvVDBouuBLkv+dC/USrCVkTsRntafHgy+SbsF5OWyhY2dmwsaB1/2F+UOhsw+sJRJwsFG/PNzc1s27YtbfnTTz/N/Pnzi9Gnk45as27SVIF1eILYjKkvB4NGiXcCjHmnL4RFn/6iuni+nef35q5QV0p0KiWeQO6CK7koV38dA9/4Btz+Hjh+HO69l/CcWTljp4N9PWhqsoRayBnzcuXNFVp6nMeZUzWHvEk2JIMOUEuVWWMJsHmXgE9GZ5f3zAPD/mHMMaWTIiTAQpKn693vhnUHE4Wj3joEF1zACeeJ8TXmKyupcAWKnmA2ZiN5jCgVMqFdpSDL9QOAvx+jsSluzGc6LmdNOYvX21+Pf+51lzK8RUwLK8nkge339pdmhkAGi9YyMYmOYlgqAFZEZJ95SfR5+sY9DvzSlkt5vf11OoY78l7nZMl9mQwUbIXcfvvtfP7zn+ef//wnoiiyceNG7rzzTr7+9a9z++23l6KPkx67SUf3JKkoOugJYB3hmdeplfgC4xtmc6TXRXO1vGFj0Kjw+MMTGt9fa9ZOmgHY25ZLL4VPXByXG7TpbAx6B7OuoujtQ12XJWY76MjPMy8IuAOuDC80ASI57hcxYZDEYo7dQXfh3mB15mIyfdowJk/0EV2EBFiQila5A26p0I1fmTDme4ehrm5cq0ICoFSiU2hOCrWIQhi38vUKlWQMZsGqt+HwOej3ZDaMqw3V9HkSdRRK5pmXmVkxaU0ZB/GiKJYudn8EFt0EhNkEBksi0yn7zEui29U9buFLydx8xs3ct+W+vGUqSznDFhEjp0y8PIzCmP/Yxz7Gt7/9bb785S/j8Xi47rrr+M1vfsM999zDBz7wgYK29cMf/pAVK1ZgMpmora3lPe95D/v37y+0SxPOZCpCNOCWD7MZb8/8+gO9nDc788vgtEYLuzom7gVea9LR4ywb8xNPYkBnixod2dAPOhHs6aFbcWQ887EwGLl9pz3MxYhU7XVQZlAhKBPKITIvAVfAVXiYDWTMoD8xsxrtwQHpQ5HCbGZWzuTI4BHpw5xFsHd7WpvxMp5i6FS6U86YN2vNk+Y3xe6r5488z8UzL85rnZJ5bmWu9clSBbYkErO56HoR6i7K3a5Acum6b+3aypK6JUXfby6UCiVfXPVF7nrjrrycec6As2R1GHrdvRMyoCkVo3pqf/KTn6S1tZWenh66urpob2/n4x//eMHbWbduHZ///OfZsGEDzz//PKFQiEsuueSki723GTQMusenCNFbxwayfj8sE9qi1xQnpCRfRFEklCP85MzmSt48WtwHeCQi5i0MOJkGYGUkbDobg74MnnmFBsJ+9INOqMniMZQx5gvyvgSdiQTRkejqEp7sEYiIowuzydaVBi0cj16jRSgaBUnylADvugpefgt6e6FS8n5NREypSqHKT0Vkkil1ZcOkyextHm9ig9luVzd1FZlD1Mxac9yYDUfCKcV1SolsgjrSeyRnteQiMiGeeU+HVEdinPEEPaNP/h8jZq2Z6xZex282/SZn22KH2SgERTz87fjw8ZwFo04mxuSCqa6uprZ29CObZ555hhtuuIEFCxawePFiHnjgAdra2ti8eZw0b4uEYhyrwP7qpUM4fZklp0RRTCtiNN6e+c2tg5w+LXulRoVCQKUQCISKF/7T5/ZTlWcyarkK7CRghCSbTZ8lzEZbDf4+dA43VGUJAwm5QZn7JRVJKimfQtAB9VMSxrzfnyhOpW9IFI6SMSzzDbPJ12A2isOgSkoULMKUcKO5MRGzqtVCMATr1sGKljFve7TkNdgKBkE1fipVY8WkNU0Oz7wgoFPpcAfdOWdcVjatZMPxDSXvz8h7J5Nn/rnDz3Hh9AtL258k9Co93qC3tLKcyYhi8ZQYCmBU9TCKzAzbDBbULuCJ/U9kbVfsMJu6irp4LkGHsyNnwaiTiYKfjv39/XzrW9/ipZdeoqenh8iI2NKBgeye42wMDUmj4soM8mN+vx+/PxEaMTwsPSyDwSDBYHZN1VITDodL3odQOEJ1hYZdxwdZnsFYluuHShBxeQNF7V9sW3Lb3NI6wA2rpubc3zktlby4p5N3zCvOVNeJATfVBlXevzMUGts5C4UjiJHIhF97xSDb+SwZgQEERQVidJ9GpZE+d59sHwRVFaKrA8JhgpFIxph2RThMJJQ+CzXyvmgfbsesMafvy9ODUNsIW45L/erqQrBapb81tQgDmxAtS1FEwkSS1o2EIwx5h9CgyXkMR/ZFEYmkbCuGPtBPWNlCJBiUflee5ybXuQyFQ/HvFPObEB5/HPHrK4gEg+PyHBuJIhwmEhGy7/fECYTKyvi1kouJ+B3J6BV62lxtBV8LI8nnvsx4bQSHEBQGxGCQDe0b+Pzyz2fdzgzzDJ4+8DSrp60u2fETRCVCyJXSX7PaTLerO2V/4UiYTR2b+PJZXx7X8xgKhxjyDKFR5L6PC0WMgCAmHdeh3QjG2Xlf04WS6Rxu797OvKp5E/7eWtWwir/t+hsb2zeytC5dIRHA4XWgq9IVra/1hnqO9h+lRlfDccdx3jHtHaPe9ni9M/PdfsHG/Ic//GEOHz7Mxz/+cex2e9ESCERR5LbbbuOcc87htNNOk23zwx/+kDvuuCNt+XPPPYfBMDFTRjF2dwms7d9V0n0cd0NNUODf/22jxy7v3dvVmd4PZxAODQt4Dxd//uD5559P+RyKwIEegacdu/Na/+VOgcDR4vRr16BAg0GkM8/TsLtTYO3A6M+Zww9tboG1fYXVVwiL0OmBAb/AosrJFTow8nyWEmOkE0Oki95dawHpGbCpbxO1HemDO0Oki4pIB52dnaxduzbjNpuDuzl6IP373b27WduTWL7duZ3zlcNp26oK7yQgmqh6dQ/HzGbMx46hcrsZWLsWQQwzLfQix7ar0/azu3c3CNDQmVsJZk/vnpS+ZOqza/AQO1or6Hj0Uabu3s3RLL9bjkznMvlYNGt9YNAS2b2fY/ufYk9fat/Gg+bdu9llhLXdmfdrOXwYRTDIYJ7HYOT5Hm8GggPsd+8nsDf77F++/cx2X04L7qNt/xOIQurr3BQ5hkZ00b97LTtbd9Kj6mHt9uz72tO7h7W9a0t2/JpCB9BHejl4KLHtiBjhtf7XsLRa4steGXyFWYZZWe/1UrC7dzdPdDzBfvd+1rYXd99NoaMoldXxczk9+AxtqtVEhNL8xkzn8Nm+Z7mw8kLW7p64+yOGFSu/fOuXvM/+PtnvX+t/DfGgiF6pL8r+BoID7HPvo8/ax/be7TzfNfb3XanfmR5PfsnCBRvzr776Kq+++iqLFy8uuFPZuOmmm9ixYwevvvpqxjZf+9rXuO222+Kfh4eHmTJlCpdccglmc366taVi4M021pw5taT7+Oem43x0cT0Pb+5gzUr5ffVvaEv7zu0P8eyebtYsLV58WDAY5Pnnn+fiiy9GrU7E6L+4r4fPrKpgWlV+g6tiHjfnpuNctaQBjSq/KVK5Y1UIO44PMV8UWTLFmlf7PZ3D/PiZA2w/PoQ7EMaoUXL7davTwqImgkzns5QIA28BixErl8eXtW1qY83yNemNQ26E9kfwv1HP2Wtkvo+iONTKvJb071s3taZst2NLBysrVqKYndpW6AgiVi5H0SEwf80ahJdeQqyrg3nzottvZ37LGhSHjqXsp3VTK4IgsOb0zH3L1BfhaA/zplwAqtR75rX//oXTPvJRFnq9CAsWMC/L704m17k8tulYfP+KQ61ELr0cYXArTVXnMHhwkDUL89tPsVC0tbFgXoQ1KzLvV3j6acQ5c2DGjLy2OfIYjzeugIt/7fsXaxZl70OufuZzXwonwiywLgHDlNTlnWsRzfPA2IzysJJLZ16as99tm9u4ZOkltG4pzfETOoII3hPMGnGPtm9qj+/PF/Kxf/N+bjzzxqLvPxfHNh1j5cyVVA9U53W8CiHS6qNvp4sLL3kParUaxcHDzJ/1nqLuI5lM19aRt47wnhWl22+hdG/r5oIFF8jG8LduauW9p7+3aE7jcCTM77f+njWnrxnzM2K83pmxCJRcFGzMz507F6+3uEkpN998M0888QTr16+nqSlzDJNWq0WrTY+JVqvV42aAZEKpVJa8D6EImAw6FApFxn3J9cOkVBGICCXp38hj3zEU4LKFlixrpKIq4nGLIGDU519gYqznbMAbZkGDOWUboihypM/N5tZBtrQOcuaMSq5aKl3TFoOO149IYWgmrYolU624gyJVFRrZ7U8E43ovhYfBNAuS9pfxnKitgB9ByHEdK5UoZb5XqVQoVcp4LGxEiKBVa1P2LX3hAkNNYjsOByxdmminUKJUqaT/k9ZVKBUohMz3ZTIatQZBKSQSDI2NEO4HfeK+8Yf8qJVq1IsXS8W1MvyubGQ6l1q1FhRIeuNKJcqwA4z19Pp6mWqdOv7P0spKDJ4T2ffb1ydVCs6zb+PxPM6GVWXFH/Hn7EO+/cx6X1ZMgWAfqEcMdPxdYHonKNVcPvfyvPq9tGEpewf2lu74aS1AMO1aTt7fH3f8kY8t/diEnD+lUklADGDRW4q+/5DOioo+6VwKAdBUFHxPF4JOo0NUiGiUifdLOBJGrZp4eymZJQ1L2DewjzObzkz7TqlUotEU7/2oRo2gkN4hxbrGS/3OzHfbBRvzv/rVr/jqV7/Kt771LU477bS0HRXiIRdFkZtvvpnHHnuMl19+mebm5kK7M2nQqSXFGIOm9ElaSoVAOJKe6Ary+TRKhTAumu6hcATVKLzMoigjEXgS0Ov0YzOo2XCkn82tg2xtG2Rz6yCDnkSM27AvGDfmp1UZ+PH7FrJ4ipVZtaZJ4ZGfUAKJKqqlJqZhn1NDfWQC7cBAXAc/0caVdwVLOQxqA96gNyG5pq+TqsBWJIyxHncPJq1ZSlINBIqaKDfVMpW2oTZmVs4EBEmhp6KFE31t41swKkZNDTrHgextPJ7iVsAtMYIwPs9cQErM7n8rfbkYAmVhhtDyhuX8adufSvc8VhmAzPfgoHeQYCQ4blVf5Si2KlUcVQUqMara1L0Oakub3FtrrKXH3ZOS5Lmta1vG+PSJYmHtQh7c+aCsMV8mfwq2PK1WK0NDQ6xevTplecwgC4fzV035/Oc/z9/+9jcef/xxTCYTXV1SJTuLxYJeX5wYqfHCHq0CO726NMZ815APu1mSpptebeRon5uW2slVrnzj0QHOaC7MODPp1LJymuNBTLKzkAHYCYeXAXeA0xothCJS0YmP3P8mwXDixa1VKVjcZGXZNBvntCS0mgVB4NoVpQ3FOqkIOOJVVEtNrCJi7oJIQqrhHA6nq6gEBtLkL5WCklAkP/lXg9qAJ+hJMubroe+NlDbd7m6qtaUJHYzJU86snCn9juEDUH0WJ5wbWNFY3LLyeVFTg75tHAosTTKKZuzr7PKSqaPYvk6lo9PVyeyq2UXomAzmeVmLXP15+5/5xLJPlGbfeeIOuktSdVZUGVESjWpwHoSGdxZ9H8nECkclG/MbOzby8WWFy4iXEr1aUhGSo1RSuRNZsLJUFGx5fuhDH0Kj0fC3v/1tzAmwv/71rwG44IILUpY/8MAD3HDDDaPe7kQQ0y2fnqHq6VjZ3DrIiumSATGv3swbh/vTjPlAKIJKIR8vPh4+4L1dTm48e3pB69iMkkb/RBjztSZt1gFYMBxhz4lhNrcOsrlNCpvpHPJxWqOZ/9x8LiDNyFw4pxa1UsGyaTaWTbWyoMGSd9z+25v0su5ZCYSIqJSj2lPsxTa/Zj7ugDsan+mLSkwk9yH6kM/0XBME8KfPKJi1Zo45juXVl5gxH0dbA76elDZdzhM0x4x5jUaqAFskpluns651nfRBZ4feV0FtZsg/NDGl06ur0Tvefsa8P+xHpxp77QCpCmzx6ogEwoHSFdPJMhPXPtSOTW8rjVe8AMbFMw8ll6W0V9jZ17cvZVkwEkwJu3m7MuwfxqIbH0fSeFGwMb9r1y62bt3KnDlzxrzzU2l0ZDfpONBduhdSr9NHbdQzX12hpd+VXr3U4Q1gNUxMLFysYFOhg7sqo4YBT4DpjP8D3G7WZRyA3fL3rTy3pwtfMFUCUakQUCsVhCOJa/d3H10+cvUypWDQhbdydMamvcLOzh5JdejgwEFmVc6C8NHsITNyzyeFFrwnUkJiIFuV2XTSjHmFCkZ49YeGDlFRM1P6cNpp8Pe/57XtfNCqtATCUZWVmFc3et9OSLhbTQ16R/EKBQbCgZPCYHEFXCUrVT8Wzpl6zoQU0/nHrn/wxVVfHPf9JiMg4A66R1fJOReqClR4wX0UKkofUmw32ll3bF38czAcHLdCYIWiUqgIhoNSHk8SpdDDVwgK2obaTimNeRiFMb98+XLa29uLYsyfSlgNahwlLEI00qyQe+kOuoMTZsxvP+5gcZ6qLsnYjBr2dY69uEq2WQk5IhERpy/Ev7Z28NCm4xzqcfLY585GEY1jFwFfMIJFr+b0aTZOn2Zj2VQbi6dYxiUv4m3BU5ugkNn8fideWxZjPuSFDBJmlfpKBrxS8vH+vv2sbl4NA31SxVc5Y95qhUGZAlb6BhjaCZWpAzirzpp39UiD2oA7mN14Vfu60Vaskj4sXgyPPZbXtgtGZ0+bFRh3dDoU/kD23JkCBhnFLjRTKkpqzEdC0iBxFKyZNf4qQN6QlznVcyaFsVkyz7zahEr0IfS8DM0fLP72R2DUGFOcBps7N3N6/ekl3+9omFs9l319+1hoX1jyfdmNdrZ0buGsKWeVfF/jScF3zs0338ytt97K7bffzsKFC9MSYBctWlS0zp1MlNKj5QmE0KtzhxcMegJUGuU9UqWeA9na5uCGs6YXvF6lQUO/e+yDoF6Xn1pTdiWbnceH+O++Hja3ScmqTl+qN/RIUh7CLatbuPWiWcyoNsYN/DJFpt8lWwUxk1EXHvAQyVBQDoDAYFosewyFoIjPBPZ6eqk2VIPTDMFhQMYLabcnqsAmY2iA1r+n7ceisxCM5Ffcw6A20Ofpy9rGGHYkyrwbjfDpT+e17YLRVoJ6AkJrRqBRavCFfOjVY8+VcgVciXyESYzT7yxdP70nQH/ylKq/fvH10j05waiVatxBd2lmdhQaFIQQQq4Juec2n9jMp5eX6DkyRpbWL+XJ/U+OizHfZG7ij9v+yPsXvL/k+xpPCjbmr732WgBuvDGhARvL3C80AbZMfmxvH0rzelsNavpdfqoqEgaswxOguUQx+9kQRSlNZTRGr16jxBcc+zXTNeSjzqKL96dtwMPm1kEummePx+M/s7uTe186HF/HoFFiN+u4fFE9y6bZaLAm4ldn2bM/bEPhCIqTUIFnUjG9Fg4ehNkJ97xBbcAb8spqDgccYYwzs9QvyGLMj0QQBFCZJM+8HJmMeX0DeNrSVEKsOmveU/NpYTZSh1I+GkPDkspNjJaWvLZdCNIzWwGWBUXfdqHoVDqG/cPyxrzbDQUUBZys4SsjKWk/3a1gPHmS7SdSvSYZi9ZCp7OzZNsXCIEwMbPnYTE8KWY+5ChkZnOsNJmbODhwUPYdczJT8Jk9evRoKfpRJgsHe5x86MxpKcsWNJjZ2+nknFkJY37QMzFhNvu7ncytmzhPmC8Y5o3DfQTCEX7x34NsbnXQF80peOCGFVw4V0rmOqelhuODXpZNlcJm5taZePDNNq4fxYxCnytAdUX+mvZlZLjoCnhxfYoxb9NLEpJyD9qgO4Ipm70cGASNNf/9q02SBzOFqFFtt8NumSrG2mopAXYEFq0lb2PeqDamG/MjeyGGQVG6e7muoo4uVxf1pnpo+TQRMVKS+NR8iRnz9gp7+pfd3VBXl748AyeLMe8MOIvnjRZUEAkmrhl3GzROXNGskxWz1lxSo7IyvI9I9WcYXRr/6PGH/KhL+Dw5mairqGPYP/bQ3slGwcb8tGnTcjcqU1TkNOWnVxl548gA58xKvAyC4QjaUap9jIWNRwf44Bmj9wIVakJEImJ8FuC53V3c9LetBMKpiapqpcCCBkvKxlfNrGLVzFzShPnR4/RhN5eN+THRfCm470lZZNPZGPQN0mhODxHwCRosgi9teZzAIBinZP6eEUn3ahMMj/TMR7+vqoL2dun/ZARFWvIrQIWmIm91BFnPPMgo65SOmDxlvakeTDPpd/dOqHdUp9IxGMgwS9LZWZAx7ww4mWLOfh2MB7lCL4s66IjVKohd/4HBaKG1MoVg0VkY8pXOmFeLbrAsLtn2M7GxY+NJoeM+HjVnlArlpNPaLwaTc86lTJyYSsxIVEoF4REG7ESJAwXDImrl6I2QbN0OhSPs63KyJVqQaXPrIJ88d0bcmz6jxkggHKFCq+Lslqp4suqCBgu6PPIMRkv3sJ/5DaXRAX9boVRCKBTXcrfqrAx6ZRJPAS9qTJEsHu08wmw6nB0JpQ6VCUJJBmQkBEL0mlEooLcX5BL9raelLRIEgU8u+2TWfcfQq/XpxrymSvL468Ynbnhm5Uwe2/sY50w9B5COy4QUjIoS88zL0tUFZ+WfrDZZPPO51NqKa8w3gLczdTBbDgMsGIvWUlLP/GH1lSyfgPOyvXs7n13+2XHfbyE0W5s56jjKDFvCWVIqnfnPLP9MSbY7kZSN+SJi0Khw+UNUaIt3WA/3umipnbzJXK0DHqZWFjf2zOEJcP+rR9ncOsi2dgeeQGpM/ebWwYQxX13Butsv4OX9PVx/VuFyX6N9rvY6/dSUw2zGzooVsHkznCl5jWx6G61DrbJN/ZEgJmUWXe6QUzLQs7Cvbx9zq+dKH1QVkjRljOBwahGrvj6oljGu58jL5+Xr2VYpVIQjI/JE9HXg6wJdNb6QD5WytFPiZq0ZZ5In/ITzROK4TABZjfmeHqjJf9ZgshjzgiAQESMoMsy2FFU1ZWQV2LIhPyosutIa8z2qZSXbthxqpZpAOEBEjKBUjP+sfSEsrV/KG+1vxI35UkppLq0/9Tzz5co2RcRu1tIznCUMYBRsbXeweIr89L1GpcQfmtiE49cO9XPurNF5E0VR5FCPiy2tgzy5PRG7rFYq+NXLh3n9cD+eQBiTTsV5s2v44jtm85ePn8GdVyU8owqFwLQq46in5nRqJW5/4QVXQpFIuTBUMTj9dNi0Kf7RbrRzwjkyjl3CHw6gUeQYQGW5DsxaM1s7t0qVTwEUSim0JUbQkRpzPzAgb8yXwnuur5eMeaDb2YV5nIs3nXCeoL6iflz3mYy2woJ7KIPCj9ebXoU3C66Aa8ILD0HUy5slZCOboV8wI6vAnkI1XMYTi9ZSvHMyCag11tI21IZWOfkdT/UV9SnPflfANTFF7E5Syp75IiIVIfIzo6Z4XiG3P4RJJ++la6mt4FCPS4oNZ2KcMf5QJO9wFk8gxPb2oXjIzJa2QRweSc7vWL+Hdy+WpvmNWhWfv2AmdRY9p0+zMau2omTykHazjh6nn+YizqaUKQCVCpIUsFIKGo3AH/KjVY3+pWSvsPPWibcyy84FHKlhOmazvDFfCnR1cc9q3/BhrMbxNaz9IX9RZCFHi7ZuCsEemYTj4WGoKOx5Go5MDtWOadZptA61YtPnp7A0JpKrwIoipRcjPjWp0FRg1p464ZN2o51/7/s3l868dKK7kpORDrmTRWJ2sjDxT7xTCLtJx94iFEDKl7n1Jp7f3R035rNRClN4KEBWbXeHJ4DVkDCcLr5rPR0Ob0obrUpBvUXH2S2piYa3XTI+RclisykTIelZJorBIMkPGqVzoBAUhCKhVINMFAmE/WPyMNmN9uz67gGHFK4Qo6lJKh41HqjN0v6B4cG9NFnHN+SlVLGp+aK029Ed2pD+xaOPwvveN/4dKgIzbDPYcHwDS+qWjO+Og0N5S7SWSUUQBBoqJi53pNjYK+y8ePRFblt120R3pWCcgZOj+NtkIS9j3maz5R3GMDCQLtv2dsGsV8U9zcWg3+XPWAQKwKxT4/TluT9BSFGBKQZ7HQK3R0NsAqEIezqHJY97NFE1FInw1jfeEb92FjVZCEdETp9u4/SoPOS8ejMv7O1mxfQsxYBy4PbnV1RLjlqTjgPdrtwNy5SOc8+FV1+FSyXv0en1p7O1cysrGlck2rjdeLQKVGOI+7RX2LMneQYGwTI/8fnzny/ZdFea8Zy0H9/wIazTLizJfpMxa80M+YbyVuEpKdXV6N8acR+KIvT3pysKnSTE5D/HHXfbSaUxP9moN01cuFmxsRvtVGgqTprQIXuFnS5XF3UVdVJRtXKYTd7kZczffffdJe7GqUGxJZW2tDlYNjW7hyW2z0yqNzF0KgX+UAS9pnhJML4wPLWziyd3dLH9uAN/KFVdR6kQ6Br2UW+Rpu//79olsiE5NoOGQU+AmhwVXDPR4/RjN2dJjMyCzaDG4Rl7BdoyY2D2bHj22bgxv7xhOfdtuS/VmO/pwWszSde7TNVYiez3X42hhvfNG+HlTY4tHhkz3zAxHjptoBetKV3+sti0VLZwePAwy+rHNylPlpoadI4RxvzGjfHE6JMRhaAgIkZyNyw2njawlr6S5qnKLWfeMtFdKBpGjZGvnP2Vie5G3iyrX8bWzq28c9Y7cQVcshLFZeTJy5i//vrrS92PU4Zi2vPHBz28Y15t1jaiKCKKIsO+YMbYepAqrXqD4VEZ8+GIyMEeJ1taHWxuHeTbV8ynZ8iDVSOp2Ww8Js3G2Axqlk21sSwqD7moyYJBk7jEMsXWV1VoGHCP3qBOrv5aKKXWtC2TBzEDPYpaqSYYGTHj1NODr9IshaOEnNL/BaJUKFk1ZVXmBmEfZFPLKSKyBZqi16IyEgRV6ePXZ9pmsr51Pcvql01owSgALBY0rtQQPF59FW47+cIDJhzPcaif/DHSk5VTrTLo8oblE92FvJlhm8Gzh54FymE2hTKmmHmv10swmPrSNZtPneSRyUAuY7PeqqdzyIc/FMGWJSRHr1biCYSyhu3EcPlDbE3Sdd/W5sCZpPjynqUN7Dw+yKJKkeaFdcypM3P6NBvN1aNTlbEZNBzuGX2oS9ewd0ya74UKP4TCERTlQUBxqamRJAhrpcGrWiFJqsWTVffuxVlvlRJFvV2jMuZleRufx1pjLd3uboLh4MTL1o0Y0OFwgMWS9fz8feffee+8944pKbrUZBskFd2REKsCGwmVtHpwmTKlQiEo4iGI5TCbwig4kMrtdnPTTTdRW1tLRUUFNpst5V+Z4uAPhfMqxDS/3szezmEGPQFshiyeebUSXzBdxlIURVr73Qwmecb/vbWDj9y/kbtfOMgrB/tw+kMYNErObqni5tUtIEKTVY9CgAUNZt6/fAozaipG/XKyGtQMjCHUZdgbwqIfv5fXoCeY16CoTAGsXg3//W/845lNZ7KxY6P0obMT/H68laaEHrssY03inGDDfpzlBGP3a7e7m7qK/Cusjgt5JL4eHDjID175Ae6Ae5w6NToyhdrkKipVMPq6VHnKMmVOYiaLxOzJQsHG/Je//GX++9//8qtf/QqtVst9993HHXfcQUNDA3/+859L0ceTjmI8pHefGGZBHt7mJpue44NeHJ4ANkNmA1OnUeINRPAFw7x1bIDfrjvMp/68iRV3vsD5P3mZtbs6421Pn2ZjSqWe9yxp4HtXLuA/N5/Djm9fwoOfWMmXLpnDns5hLplvH/NvjKFWKghHJk5No9AxSL87e2JymVFQVwfdCUNksX0x27q2SQbu/ffDJz4hGZ8xz/xIwn5QnOTnRKmRfsc4c8J5YkKrv8aIOwNEUfLMZ3EOiaJIlb6K28++nR+/9uOMVYMnmnpT/fglweobwCNfo6FMmZMFk8bEkG+IiBiZFBKzJwsFH6knn3ySP//5z1xwwQXceOONnHvuubS0tDBt2jQefPBBPvShD5WinycNFVoVTn8Ic5b49XzY3+XkqqW5kz8EQUAURQbdQaxZPPP9Lj//+8x+jvW7CYZTDWeNUkGvM2FEzKs388qXV8tu51ifmymVBpQl0n2fCAodew24AtSaJ+/U/klNNLlVqVBKg+KHHoL3vhdUKumztgr8MvKSgcEiyPFNsDa3bmI8qx3DHZzReMa47zcjb7wBZ52VtUmvp5daYy0Vmgq+ce43+NGrP+JTp39q0imRNFubOTp4dHwGS/p6GNhc+v2UKVNCltQtYXv39onuxklHwZ75gYEBmpubASk+PiZFec4557B+/fri9u4kxG7W0TM8du+aPxjOuxgTSHHuOpWCXR1D/PmNY9z6j638fv2R+Pd1Zh2HelwEwyLVFVoumW/n62vm8uhnV7HjO5fwhXfMzms/z+zu4tIFxZ+SH+3QYMAdyDqIyQeDprAqsP3uAJXGsjFfdGbNgsOH4x8rB7wEBnphfpJcpKBA1uguijE/wejq8A3tRVCN39SyVqmldagVe0XxZtpGS3xG8403YOXKrG2POY4x3TodkAqNfeO8b/DHbX/kyOCRrOuNN822Zo46jo7PznR2cLeX4+XLnNTMr5nPbrkCcmWyUrBnfsaMGRw7doxp06Yxf/58HnroIc444wyefPJJrONVYGUSEytC1FJb+izscERk/YFe1h/s43CPix8/sw9PIBEXf8Lh5ZPnSRJ3tWYdnz5/JtedMZUplfpRxbcf63MzNeqVj6SH34+J0fpE93UOM79+bMmQhVaBdXgCWMcxRv9tw3nnwT//CS0tIIpc/HIbr378CmJzRFmv2dEa84poaMtkKHeur8fd9jhaU/O47bLZ1sy/9/178kxnDwxI4TU5nk9HB4+yujkxe6hSqPjqOV/l7g13T3gBrGSsOisOnyNteUSMFF/7W6EGTyvUnl/c7ZYpM46olWpCkVBZaa5ACn6Cf+xjH2P79u2cf/75fO1rX+Nd73oXv/jFLwiFQtx1112l6ONJRa1Zx86OoTFtQy7mPhIROdLnomfYz1ktUqEmhQBfenh7iqyjSadiWbQgU3IhJp1aydw6E1OrRi+79ezuLj5xbun1rwvhcJ+bM5pHX3AKoNaspbuAKrAiFLX4VpkoFRVSJViAv/+dmhs+z67B51nNJUCOXJSRBZ/yRWWCoHPcjXlZg1NXi9i/CeP0G8etHzNtMyeNN1tQKIn84x8o8gjV7PX0Um2oTl1fEPjCyi/gDk6uhFg5RRtP0FMaCUR3GxjKBaPKlHm7UbAx/8UvfjH+94UXXsi+ffvYtGkTM2fOZPHixUXt3MmISavC6cs/ZEOOHqcfq0HNG4f72dI2yKZjA2xpczDkDWI3a9nwtYsQBAFBELh8UT1OX4idx4e490PLmFVbIWtoGqI686Ml2Ss/mYhERFR5qP5kw27Ssb/LWaQelRkTCgUcOwYeD8K8efDm8/mtN1rPvNok6dZTzXiq2cyums1Dux/i/fPfn/BAKbUoPK3YKk8bt35MsUxBry69pn0+CNXVBI4fQ2fJryKtnOdOEIRJp00tN3BzBVyl6WfIVa7+WuakR6vS4vSX38mFMOa51alTpzJ1avnhEaMYU0O3PbSNNw73M1LgRatSMK3KiDsQpiIaEvLdK6UX//89f4A5dZk1WdVKBaHw6KsRltorP5FDBKtBzZA3mLthmdKzbBl873vwu98BkrKB0+/EpDVlv7eCw6PTnldHPfORIIxjqMklMy9hZ/dOvr/++3x6+aepNUr6+sFwgBpLy7j1Q6VQcfW8q8dtf9mIzGrBUTmbSSaSWRJi13TRMc8FdX6DoTJlJisLaxdy/9b7J7obJxUFv72++93vZv3+W9/61qg783YhEIqw+8QQm1sH2dI2yPb2IZ6/7bx4tdRIRCQiQr1FJ1VTjYbNzKs3o1HJe6FvvWhWyfp7dBy88lq1Em+gsAq1oXCkKOEukiLQmDdTphiceaYUM6+UroNzp53LK22v8M6WdyaF2QggRqLJsEmMJgZZFfXMBxygto6l5wWz0L6QOdVz+O2m3zLdOp13z3k3Pdom7ONcBOmDCz84rvvLhGLpMrq0plPOmNcoNakF0CihZ37e7W/rQmhlTg0W2RdNfFXqk4yCjfnHHnss5XMwGOTo0aOoVCpmzpxZNuYzsOO4g6d2drKldZDtx4cIhFK95Nvbh1g1swqAVTOr+dk1S2iw5j/9XcoY7hf3dnPj2aVNyqs0aBjwBGjU5P+bj/S5mZlnnHuZkwSlMl4FFqSY7rUH1xIIBxKVPrXV4O8HXc3Y96c2S0WoAg7QWMe+vQLRKDXcfObNvHn8TX74yg+p0S1i4bj3YnIwq2oWr7a9ypK6JVnbFb3YUomZaplKq6OVWVUJh4sr4MKqsxZ/Z/pTbShU5u2IUWPkQ4ve3jLnhVKwMb9169a0ZcPDw9xwww1cddVVRenUyUw4ItLv8nPfK0dYs7A+bpBvbh3kt+sSiWY2g5rTp9lYOtXG8mk2Fk+xxr8z61QFGfKlRqNSlDzh02bUMOgO0FjA797bOcy5s4pg0FF2Zk1WYqE17qA74cnU2SUDvCjGfDTMJugYd898Mmc2nclC+0KeOvDUhPVhorEb7XQ6O3O263H3YDdOvJRmvsywzeCo42iKMe8MOP9/e/ce3XR9/w/8+cn90iZNW3qjBQqyAivy5TaEyegEuQmOyXFOXbfjbajzMtnO1DOPqPwBbvM2mZu6Aztuvw0viIczFC0XEQaCIp2gArYUy6WlNL2kTdokTd6/P0ozQnpJ2iSffJLn45we6Cfvvj+v5NWkr7zz/rzfKLQUyhgVUWIrG1UmdwiKEpVJohaLBU899RSWLFmC8vLyaHSpGG2dXlSebsGhb5px6JtmHK5tQfvFNcstRi1+NK0IADBrTDZ+PL0IU0d2T5kpzjb3OgfY5xcxK5wHO54Vj4GwTLMOp5tcEf1Mi8sb951Yu3x+qFj5x1WmMRO1rbUway9+CmPMA1yngaAx7EH+kl46zcY8amiBDpFJa8KN375R1hjkFO71RpeuMa8EI60jsfvU7qBjMZtmQ0QpKWpXfLW0tKC1dWhLMirN/mo7bvnrxyHFrlmnRo7FANMlmz6V5KVj7fIrB+zzdJMLIzJjsGRZgss06/Df0y1yhzGgZhneQKS6OSPn4LX/voZZRRd3BTXkAfZPotO52gD4OrtH5mWYZkPBwinoT7WcClpjPtHpNXq4fcEbCcbsAlgiSkkRF/N//OMfg74XQqCurg5///vfsXDhwqgFpgQleekQAijKNAYuUp0y0oaS3HS0dnix41hDxH0eq2/DpKLEWY2gw+ODQRvlzU16YTFo4OiUb0UZk06DdndXYJWgvtidbhbzcVZkLcIx+zHMH9O93jy0FsAbpYGDnuLR08JVQBKEEKLfor63NeaVprOrE/pE2KiMiJJCxMX8c889F/S9SqXCsGHD8LOf/QyPPvpo1AJTgkyzDocem4estNAX5aw0PVpdXnh9fmgjWAf9vKMTeZbEmQ9qd7qRZY79H51Il/RscnqQYYreLqw56d0796YN6/+j76Z2D3Is/CMcb2atGWbdxWk2sZjm5PcAar5Jk9vw9OE413YOwy3D+2wjQVL87pA9+4QQEUVDxMV8TU1NLOJQrN4K+R4LS/Ow7Wg9lk4qCLu/gUal4s3e7kFWWuIVOcfqHBifP4h1xfuQazGgoc2N0QMU83anB+OieF4Kz7Jxy5BlzJI7DIqxkuwSHGs81m8xnwyUtiIPESW22M+fSGFFmSacbelQ9At3k9OD7H7esERTJG9hqhudGB3FZSlzLXqcd3QO2K7F5UGGMXqfCFB4Fl6xELlpl3xidelzyu8FpPht+ESxM8Y2BtXN1f226W1H1URn0VvgcDvkDoOIklTEfwGdTifWrl2LHTt2oKGhAX5/8HrpJ0+e7OMnU1NZyTB8ePwCvj8uZ8C27i4fdJrwN02K1GDG+xvb3ZgxOjPqsfQmkj/RPp8fmgimLw3EagxvF1iB2K7pT4PgaQZ0tiF2wpwmAr1GD4/P0+ftQghFbiZTnFGMmuYaTMqbBCA6O4UTEfWIuJi/8847sXv3bpSXlyM/P58vSgMYl2cJu5ivbnBizLDE2gTJ5fEFdqZNJNH+veMusApzaf6jUsyTEpx3ng/+hEYhim3F+OTsJ4FinogomiKu0t577z1s3boV3/3ud2MRT1KaNtKGT041Yfqo/ke4T5xvQ1lJdDZBSmZdPj9Hx1OdpOmeXqPSXty9lcV8suhvWqLS1pjvUZBegLr2gTfEIiIajIjnKdhsNmRmxmfaRbKYNioTh75pHrBda4cXGabEu9g0XiSEd2HYyUYnxkRxvjwpkCEX6Ly49GtURub5sUyiMOvMcHqcvd6m1GJeJangF/+bkqrk66iIKPFEXMyvXr0ajz/+OFyuyHbr7M1HH32EpUuXoqCgAJIk4Z133hlyn4mqJDcdx+rlvwAqkf+IWIxaODq6Bmz3VZ0jJivKSFJiPz50CWMe0Fnf/X9Os0kqJVklOGE/0ettja5GrmpERHSZiIv5Z555Bu+//z5yc3MxceJETJkyJegrEk6nE5MmTcK6desiDUNxykqGYffxC7LGoFWr4PUlbrFqM+nQ5Or74rceLTHahTXLrEdj+8DnpwRgyAM6Lhbz3lZu+JRExmWPw7HGY33engzXaSXDfSCixBHxnPlly5ZF7eSLFi3CokWLotZfIpMkCXlWA861dKAgwxhye1unF+YBdh8dKqNOjQ6PDzpN+O/h4vk3J9OsQ5PTg2KZptAU2ow40+zCsPTel+Ls8vmh4h/hxGDIBc7v6P6/8AGqIa4CpTYMPSaKiixTFuwddrnDiDoJUsLtI0JEySHi6nHVqlWxiCMsbrcbbrc78L3D0T1txev1wusdeFlBuc0rycb/O3gat80aGXLbV2dbMDrLENP7oZUAR0cnwt04VQgBn8/Xa0w9x6IZb7pOwpkmF7ze/jdu6iumocpN1+Ljk00oze/9/I3tblj0KkX8rkUqFvmMLQ1UHif8Xi9UPh/8Q4hbkgyAKg1CMfe9f8rLZai+nuOxeu7HQ5YhC6dbTiM/LT/s+5EMuaRuzGVyiVc+w+1fEoOcJOzxeHpdZ37EiBGD6Q6SJGHz5s39jvw/8cQTePLJJ0OO//Of/4TJZBrUeePtP+clTMkSMF72Nmr/eQlTswV0sVtmHsdaJGTqBXJCPxjoVUcXcLRZwvRh8Zma4/EBn9klXJXT9/navcDx1u7HKtqEAPaelzA7r/e+z7kAlxe4gjM6EkKx913UaBcH/h2s/K798EomNKq5bGCi2HphK64bdl3QMSEE3mt8D4uHDT7Xcqp2VcMrvBhrGovt9u1YkL1A7pCIKMG5XC7ccsstaG1thcXS97WCEY/MnzhxAnfccQf27dsXdLzn40Ofzxd5tGF69NFHsXLlysD3DocDRUVFmD9/fr93MpHM7vTi30fqsXx6UdBx+8e1WHbV4N4IhSvnm2aYdRqMz08Pq/0puxM5TR2YPTY75Dav14uKigpce+210GqjtyNq+4FaLJ7R9+Ow/6Qdk816jM3tf/R+sJo+rsXiPvKw/6Qd2Wl6jM2JzbnlFKt8xpKq6huMv2Jx4N/Bks7rIXQ2wBbZNT+JSom5vNw3n36DhVMXQiX9b0pgfXs9Ok93YvF4ZRbzzR3NeK/6Pcy+YjbaqtqwuHTg+5EMuaRuzGVyiVc+e2agDCTiYv62226DRqPBv//977hvGqXX66HXh85n1mq1inlyZGq18PolCEkdNHddrVbH/D6kG/Vwd/nDPk9rpx85VlO/7aP92A/0OHzT7MasK3KiuvtruOdv7fSjtNCsmN+1wVDScwlqNdRa7f/+HayCuYCkBqTY/E7JRVG5vMzorNGoc9UFLUN51nkWY7PHKvY+5Whz0OZtg1u4YTPZIrofSs4lBWMuk0us8xlu3xEX85WVlTh06BDGjRsXcVDUbVFpHt47Wocf/N/wuJ7XqFOjtSP8+V2N7R78X1FG7AIaBJ/PH7NCfiAtHV5kGPkinHRUzGmiKckqwbHGY0HFfE1zDeaPmS9fUFHS5m5Dmi75Pt0jIvlEXMxPmDABjY2NUTl5e3s7qqqqAt/X1NSgsrISmZmZg557rwQFGUbUt3YGpiZdaHMjKy32m0UZtd2r2YSryemJyRKQiaxnrfnePnESQnDn2UTCPQGSVrGtGNtPbg86Zu+wI9Oo/A0L2z3tSNeFN9WRiCgcEQ9xPv300/jNb36DDz/8EHa7HQ6HI+grEp9++ikmT56MyZMnAwBWrlyJyZMn4/HHH480LMWZPXYYPvq6+03RifNtGJcX+xd3o1aNDm/4xXyX3x/RMpax1uXzQx3jUXmbqXt5TFIAjQnoGvrmdZR4NCoNfCL0tSoZlnVs83BknoiiK+KR+Xnz5gEA5s6dG3R8MBfAlpWVpeyOmxMKLPjL7mrM+dYw1DQ68Z3i2I84GXWRFfOJ5lh9G0pyY/ump3ut+Q5kpfW+1jwlEEMe0HGue747kQJoVVo0dTRhbOZYuUMhoiQScTG/a9euWMSRkibkW3D0bCt8fgFtHOaB6zUquCMo5hPtfdbh2mbcND22068KbSYcrGnCpAS7VoB6YcwDHMcAbYbckRCFZYR1BD459wnmjZ4ndyhElEQiLubnzJnT522VlZVDiSXlzB6bjZc/OgmjNj4ji0r4iFqtkuD1+Xt9c+P1iZhP+8lO08HudA/ckORnyAPqdwAZV8odCcWARW9Ba2crrAYr/MIPCYn/+jWQYlsx1leu5zQbIoqqIVdGra2teOmllzBlyhRMnTo1GjGlDEmSUJBhhM+fYEPgMso06dDsCp2z3un1Qa+N/acXkiQl3CcS1AfDMKDtOKDLkDsSioFx2eNw3H4cAHC+/Tzy0vJkjmjoRmWMQlVTFTSqiMfRiIj6NOjqaOfOnfjJT36C/Px8vPjii1i8eDE+/fTTaMaWEhaV5mHJpPy4nS/R61SbWYdmZ+jymZ+easb0UfKtZNHl80OlgE82UopKC3ReAHQ2uSOhGOhZnhIATrWcClqmUqkMGkPQRlhERNEQ0fDAmTNn8Le//Q3r16+H0+nEj370I3i9XmzatAkTJkyIVYxJTatWISfdIHcYIXx+eZZhzDTrYG8PHZn/uqEN370iK+7x9Gh2eVNumU5F8DSxmE9SVoMVDnf3CmmnWk4lxRrzAPDtYd+WOwQiSjJhDxEsXrwYEyZMwJdffokXX3wR586dw4svvhjL2EhGLS4PbKb4b6Zj62OajRDxnfN/+SpLqbjmviKoDZxmkwKSZY15ACgbVSZ3CESUZMIemf/ggw/wwAMP4J577sHYsVxWK9nZnR5kmeO/PKPNpA0p5u3t7rgW0hkmLVpcXtguOafd6cYwLleZeNLHcgfXFKGEC/jDcfvk2+UOgYiSTNgj83v27EFbWxumTZuGGTNmYN26dbhw4UIsY6MYCPfPYWN7fHalvZxGrQq5IHhftR2zxsRvik2hzYQzzR1Bx+ztHq49n4jyF8kdAcWQWlKjy98ldxhERAkt7GJ+5syZePXVV1FXV4cVK1Zg48aNGD58OPx+PyoqKtDW1hbLOCnO7O0eZCXItJILbW7kWOJ3XUGRzYgzzcE7i7Z0eJFh5AhwwilcKncEFEOjbaNR01yTFMtSEhHFSsSX1ZtMJtx+++3Yu3cvjhw5gl/96ldYu3YtcnJycP3118ciRpJBi8uDDJP8xbwcOwRnp+lxoT14rXkh5LkgmCiVjcsehy8vfCl3GERECW1Ia2SVlJTgd7/7Hc6cOYN//etf0YqJEoBfdG/gJLeaRieKh5njek6VimvNEyWCImsRDp49iPz0+C3fS0SkNFFZ8FatVmPZsmXYsmVLNLqjBJAo15odrGnCjGL5V7FIkIeDKKWoJBVqWmqSYo15IqJY4e4VlNBcHh9MOvl3S+RAPZE8/MLPYp6IqB8s5ilhdfn8sk71kWO+PhEFWzZuGWwGbgxGRNQXFvMpRgnlqUGrhsvThf+eacWkogxZYrAatXB0/G9JPE6zIZLHj0t/nDRrzBMRxQKL+RSjkiR0+fwDtpNzUDrLrEOT04OjZ1sxcbhVlhgKbUacvrg8ZZfPz2KCiIiIEhKL+RRj1KrR2dV/Me/u8kGrlu9Xw2bWodnphc8vZJtmc+nGUc0uL2wJsEwnERER0eVYzKcYo06NDo+v3zbNTq8su7/2yDTpcLrZBbNeLVsMOel6XGjrBAA0OT2yPh5EREREfWExn2KMWjU6vf0X843tbmTLWLzazDq8e6QOV43Oki0GlUqC/+JUI7vTnTC74RIRERFdisV8ijHq1OgYoJi3Oz3IMuvjFFEoi0GDmkYnRmbFd7OovtjbPchkMU9EREQJiMV8ijFqB55mY293yzqtRJIk/HDycNnOf7mWDi8yOGeeiIiIEhCL+RQTzsh8u7sLaXp5N2q6c/ZoWc9/KSHkuxCXiIiIqD8s5lOMUTtwMS8EuBQjgHSDBq0dXrnDICIiIuoTi/kUY9Cq0TnANBvqVmgz4ezF5SmJiIiIEhGL+RQTzjQbDsp3G24z4kyzi7u/EhERUcJiMZ9iDBrVgMU8dctN1+N8mxsyboZLRERE1C8W8ylGo1bB52d5Gg6NWgU/HysiIiJKYCzmKYgQLF4v5fMLqDjviIiIiBIUi3kK4vL4YNLJuyxlImlxeWDjGvNERESUoFjMUxB7uwdZ3O00QKWSZN1Ai4iIiKg/LOZTUH+TRhqd8u7+mmgKbSa+uSEiIqKExfkUFKSp3YPxBRa5w0gY87+dC5NWLXcYRERERL1iMU9B7E43R6IvYTFo5Q6BiIiIqE+cZkNB3F1+GDgSTURERKQILOaJiIiIiBRK9mL+pZdeQnFxMQwGA6ZOnYo9e/bIHRIRERERkSLIWsy//vrr+OUvf4nf/va3OHz4MGbPno1FixahtrZWzrCIiIiIiBRB1mL+2WefxR133IE777wT48ePx/PPP4+ioiL8+c9/ljMsIiIiIiJFkG01G4/Hg0OHDuGRRx4JOj5//nzs27ev159xu91wu92B7x0OBwDA6/XC6/XGLtgk0+Xz9fl4+fq57VI9bfi4JwfmM3kwl8mDuUwezGVyiVc+w+1ftmK+sbERPp8Pubm5Qcdzc3NRX1/f68+sWbMGTz75ZMjxDz74ACaTKSZxJqMv6iW8az8actwvgC/O935bXyoqKqIZGsmM+UwezGXyYC6TB3OZXGKdT5fLFVY72deZl6Tg/UiFECHHejz66KNYuXJl4HuHw4GioiLMnz8fFgs3OgpX84FaLPpOUcjj3OLyQlQ1YvGV+QP24fV6UVFRgWuvvRZaLddiVzrmM3kwl8mDuUwezGVyiVc+e2agDES2Yj47OxtqtTpkFL6hoSFktL6HXq+HXq8POa7VavnkiIDJoINfUoesJ9/qdiPXaoroseRjn1yYz+TBXCYP5jJ5MJfJJdb5DLdv2S6A1el0mDp1ashHFBUVFZg1a5ZMUaUGo1aNDo8v5Li93Y2sNO7+SkRERKQUsk6zWblyJcrLyzFt2jTMnDkTr7zyCmpra3H33XfLGVbSM2rV6PD6YLvsuN3pQfEwsywxEREREVHkZC3mb7rpJtjtdjz11FOoq6tDaWkp3n33XYwcOVLOsJKeUaeGvd2DDJMWKkmCRiVBrZLQ5PQg08SReSIiIiKlkP0C2HvvvRf33nuv3GGklNICK7Z/dR5f1Tvg9wv4hIDfL6DXqKFRy74pMBERERGFSfZinuLPatJi+dRCucMgIiIioiHiMCwRERERkUKxmCciIiIiUigW80RERERECsVinoiIiIhIoVjMExEREREpFIt5IiIiIiKFYjFPRERERKRQLOaJiIiIiBSKxTwRERERkUKxmCciIiIiUigW80RERERECsVinoiIiIhIoVjMExEREREpFIt5IiIiIiKFYjFPRERERKRQGrkDGAohBADA4XDIHEnq8Xq9cLlccDgc0Gq1codDQ8R8Jg/mMnkwl8mDuUwu8cpnT33bU+/2RdHFfFtbGwCgqKhI5kiIiIiIiKKvra0NVqu1z9slMVC5n8D8fj/OnTuH9PR0SJIkdzgpxeFwoKioCKdPn4bFYpE7HBoi5jN5MJfJg7lMHsxlcolXPoUQaGtrQ0FBAVSqvmfGK3pkXqVSobCwUO4wUprFYuELUxJhPpMHc5k8mMvkwVwml3jks78R+R68AJaIiIiISKFYzBMRERERKRSLeRoUvV6PVatWQa/Xyx0KRQHzmTyYy+TBXCYP5jK5JFo+FX0BLBERERFRKuPIPBERERGRQrGYJyIiIiJSKBbzREREREQKxWKeiIiIiEihWMynsDVr1mD69OlIT09HTk4Oli1bhuPHjwe1EULgiSeeQEFBAYxGI8rKyvDFF18EtXG73bj//vuRnZ0Ns9mM66+/HmfOnAlq09zcjPLyclitVlitVpSXl6OlpSXWdzFlRCOXTU1NuP/++1FSUgKTyYQRI0bggQceQGtra1A/zGVsRet5eWnbRYsWQZIkvPPOO0G3MZexFc1c7t+/H9dccw3MZjMyMjJQVlaGjo6OwO3MZexFK5/19fUoLy9HXl4ezGYzpkyZgrfeeiuoDfMZW+Hk8u2338aCBQuQnZ0NSZJQWVkZ0k/C1D+CUtaCBQvEhg0bxNGjR0VlZaW47rrrxIgRI0R7e3ugzdq1a0V6errYtGmTOHLkiLjppptEfn6+cDgcgTZ33323GD58uKioqBCfffaZ+P73vy8mTZokurq6Am0WLlwoSktLxb59+8S+fftEaWmpWLJkSVzvbzKLRi6PHDkibrjhBrFlyxZRVVUlduzYIcaOHSuWL18edC7mMrai9bzs8eyzz4pFixYJAGLz5s1BtzGXsRWtXO7bt09YLBaxZs0acfToUXHixAnx5ptvis7OzkAb5jL2opXPefPmienTp4sDBw6I6upqsXr1aqFSqcRnn30WaMN8xlY4uXzttdfEk08+KV599VUBQBw+fDikn0Spf1jMU0BDQ4MAIHbv3i2EEMLv94u8vDyxdu3aQJvOzk5htVrFX/7yFyGEEC0tLUKr1YqNGzcG2pw9e1aoVCqxbds2IYQQX375pQAgPv7440Cb/fv3CwDi2LFj8bhrKWcwuezNG2+8IXQ6nfB6vUII5lIOQ8llZWWlKCwsFHV1dSHFPHMZf4PN5YwZM8Rjjz3WZ7/MpTwGm0+z2Sxee+21oL4yMzPFX//6VyEE8ymHy3N5qZqaml6L+USqfzjNhgJ6plNkZmYCAGpqalBfX4/58+cH2uj1esyZMwf79u0DABw6dAherzeoTUFBAUpLSwNt9u/fD6vVihkzZgTaXHXVVbBarYE2FF2DyWVf/VgsFmg0GgDMpRwGm0uXy4Wbb74Z69atQ15eXki/zGX8DSaXDQ0NOHDgAHJycjBr1izk5uZizpw52Lt3b+BnmEt5DPa5efXVV+P1119HU1MT/H4/Nm7cCLfbjbKyMgDMpxwuz2U4Eqn+YTFPALrn+a1cuRJXX301SktLAXTP6wOA3NzcoLa5ubmB2+rr66HT6WCz2fptk5OTE3LOnJycQBuKnsHm8nJ2ux2rV6/GihUrAseYy/gaSi4feughzJo1Cz/4wQ967Zu5jK/B5vLkyZMAgCeeeAJ33XUXtm3bhilTpmDu3Ln4+uuvA/0wl/E1lOfm66+/jq6uLmRlZUGv12PFihXYvHkzxowZE+iH+Yyf3nIZjkSqfzRR64kU7b777sPnn38eNNrTQ5KkoO+FECHHLnd5m97ah9MPRS4auXQ4HLjuuuswYcIErFq1qt8++uuHhmawudyyZQt27tyJw4cP99s/cxk/g82l3+8HAKxYsQK33XYbAGDy5MnYsWMH1q9fjzVr1vTax+X9UHQN5XX2scceQ3NzM7Zv347s7Gy88847uPHGG7Fnzx5MnDix1z5664eio79cDoYc9Q9H5gn3338/tmzZgl27dqGwsDBwvOej+cvfPTY0NARGHvLy8uDxeNDc3Nxvm/Pnz4ec98KFCyEjGDQ0Q8llj7a2NixcuBBpaWnYvHkztFptUD/MZXwMJZc7d+5EdXU1MjIyoNFoAtOkli9fHvgon7mMn6HkMj8/HwAwYcKEoDbjx49HbW1toB/mMn6Gks/q6mqsW7cO69evx9y5czFp0iSsWrUK06ZNw5/+9KdAP8xnfPSVy3AkUv3DYj6FCSFw33334e2338bOnTtRXFwcdHtxcTHy8vJQUVEROObxeLB7927MmjULADB16lRotdqgNnV1dTh69GigzcyZM9Ha2oqDBw8G2hw4cACtra2BNjQ00cgl0D0iP3/+fOh0OmzZsgUGgyGoH+Yy9qKRy0ceeQSff/45KisrA18A8Nxzz2HDhg0AmMt4iEYuR40ahYKCgpBl806cOIGRI0cCYC7jJRr5dLlcAACVKrj8UqvVgU9hmM/YGyiX4Uio+idql9KS4txzzz3CarWKDz/8UNTV1QW+XC5XoM3atWuF1WoVb7/9tjhy5Ii4+eabe12asrCwUGzfvl189tln4pprrul1aaYrr7xS7N+/X+zfv19MnDiRy2xFUTRy6XA4xIwZM8TEiRNFVVVVUD/MZfxE63l5OfSxNCVzGTvRyuVzzz0nLBaLePPNN8XXX38tHnvsMWEwGERVVVWgDXMZe9HIp8fjEVdccYWYPXu2OHDggKiqqhJ/+MMfhCRJYuvWrYF+mM/YCieXdrtdHD58WGzdulUAEBs3bhSHDx8WdXV1gTaJUv+wmE9hAHr92rBhQ6CN3+8Xq1atEnl5eUKv14vvfe974siRI0H9dHR0iPvuu09kZmYKo9EolixZImpra4Pa2O12ceutt4r09HSRnp4ubr31VtHc3ByHe5kaopHLXbt29dlPTU1NoB1zGVvRel721u/lxTxzGVvRzOWaNWtEYWGhMJlMYubMmWLPnj1BtzOXsRetfJ44cULccMMNIicnR5hMJnHllVeGLFXJfMZWOLncsGFDr21WrVoVaJMo9Y908U4REREREZHCcM48EREREZFCsZgnIiIiIlIoFvNERERERArFYp6IiIiISKFYzBMRERERKRSLeSIiIiIihWIxT0RERESkUCzmiYiIiIgUisU8EREREZFCsZgnIkoxQgjMmzcPCxYsCLntpZdegtVqRW1trQyRERFRpFjMExGlGEmSsGHDBhw4cAAvv/xy4HhNTQ0efvhhvPDCCxgxYkRUz+n1eqPaHxERdWMxT0SUgoqKivDCCy/g17/+NWpqaiCEwB133IG5c+fiO9/5DhYvXoy0tDTk5uaivLwcjY2NgZ/dtm0brr76amRkZCArKwtLlixBdXV14PZTp05BkiS88cYbKCsrg8FgwD/+8Q857iYRUdKThBBC7iCIiEgey5YtQ0tLC5YvX47Vq1fjk08+wbRp03DXXXfhpz/9KTo6OvDwww+jq6sLO3fuBABs2rQJkiRh4sSJcDqdePzxx3Hq1ClUVlZCpVLh1KlTKC4uxqhRo/DMM89g8uTJ0Ov1KCgokPneEhElHxbzREQprKGhAaWlpbDb7Xjrrbdw+PBhHDhwAO+//36gzZkzZ1BUVITjx4/jW9/6VkgfFy5cQE5ODo4cOYLS0tJAMf/888/jwQcfjOfdISJKOZxmQ0SUwnJycvDzn/8c48ePxw9/+EMcOnQIu3btQlpaWuBr3LhxABCYSlNdXY1bbrkFo0ePhsViQXFxMQCEXDQ7bdq0+N4ZIqIUpJE7ACIikpdGo4FG0/3nwO/3Y+nSpXj66adD2uXn5wMAli5diqKiIrz66qsoKCiA3+9HaWkpPB5PUHuz2Rz74ImIUhyLeSIiCpgyZQo2bdqEUaNGBQr8S9ntdnz11Vd4+eWXMXv2bADA3r174x0mERFdxGk2REQU8Itf/AJNTU24+eabcfDgQZw8eRIffPABbr/9dvh8PthsNmRlZeGVV15BVVUVdu7ciZUrV8odNhFRymIxT0REAQUFBfjPf/4Dn8+HBQsWoLS0FA8++CCsVitUKhVUKhU2btyIQ4cOobS0FA899BB+//vfyx02EVHK4mo2REREREQKxZF5IiIiIiKFYjFPRERERKRQLOaJiIiIiBSKxTwRERERkUKxmCciIiIiUigW80RERERECsVinoiIiIhIoVjMExEREREpFIt5IiIiIiKFYjFPRERERKRQLOaJiIiIiBTq/wMrjEUYzIV9NwAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Run function to display plots for each var_name\n",
+    "for var_name in [\"pr\", \"tas\", \"rsds\", \"evspsblpot\"]:\n",
+    "    plot_annual_forcing_variable_fulltrend(annual_table, var_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e4928a5b-24a9-4a05-a55a-58549d645f2c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f5ee351b-da2c-46d9-a4a3-9b181f07c50a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ca1cdc6b-dc2b-439a-97c9-6e3ac3d3cc24",
+   "metadata": {},
+   "source": [
+    "## 7. Algorithm checker\n",
+    "\n",
+    "This will be split into two sections: Defining start of navigable season (river ice break up) & end of navigable season (river freeze up). Each section includes the function coding AND data display.\n",
+    "\n",
+    "##### 7.1 Freshet start date\n",
+    "##### 7.2 River freeze up"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c11e114a-d02d-4d39-a0e9-0833075563ff",
+   "metadata": {},
+   "source": [
+    "### 7.1 River break up \n",
+    "\n",
+    "##### The first step is to create a function to calculate the future break up dates.\n",
+    "##### The second step is to create a function to plot a bar chart. The same chart can be called and used for 7.2 for river freeze up. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "65d86b26-ecbd-48fd-a80a-2eedad4cd1b3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "q_critical = 500\n",
+    "\n",
+    "def find_breakup_dates(projection_data, start_year_hist, end_year_hist,start_year_fut, end_year_fut):\n",
+    "\n",
+    "    freshet_start_dates = []\n",
+    "\n",
+    "    for scenario in scenarios_new:\n",
+    "\n",
+    "        # Select years and discharge data depending on scenario\n",
+    "        if scenario == \"historical\":\n",
+    "\n",
+    "            start_year_use = start_year_hist\n",
+    "            end_year_use = end_year_hist\n",
+    "\n",
+    "            discharge_data = q_obs.copy()\n",
+    "            discharge_data[\"Year\"] = discharge_data[\"Date\"].dt.year\n",
+    "            \n",
+    "            discharge_col = \"discharge_m3s\"\n",
+    "\n",
+    "        else:\n",
+    "\n",
+    "            start_year_use = start_year_fut\n",
+    "            end_year_use = end_year_fut\n",
+    "\n",
+    "            discharge_data_list = []\n",
+    "\n",
+    "            for i in range(len(periods[0])):\n",
+    "\n",
+    "                start_year = periods[0][i]\n",
+    "                end_year = periods[1][i]\n",
+    "\n",
+    "                key = f\"{scenario}_{start_year}_{end_year}\"\n",
+    "\n",
+    "                period_data = projection_data[key][\"ensemble\"].copy()\n",
+    "\n",
+    "                period_data[\"Date\"] = pd.to_datetime(period_data.index)\n",
+    "                period_data[\"Year\"] = period_data[\"Date\"].dt.year\n",
+    "\n",
+    "                discharge_data_list.append(period_data)\n",
+    "\n",
+    "            discharge_data = pd.concat(discharge_data_list)\n",
+    "            discharge_data = discharge_data.drop_duplicates(subset=\"Date\", keep=\"first\")\n",
+    "            discharge_data = discharge_data.sort_values(\"Date\")\n",
+    "\n",
+    "            discharge_col = \"Mean\"\n",
+    "\n",
+    "        # Loop through every year\n",
+    "        for year in range(start_year_use, end_year_use + 1):\n",
+    "\n",
+    "            # Select data after March 1\n",
+    "            season_data = discharge_data[\n",
+    "                (discharge_data[\"Year\"] == year) &\n",
+    "                (discharge_data[\"Date\"] >= pd.to_datetime(f\"{year}-03-01\"))]\n",
+    "\n",
+    "            # Identify first day where q > q_critical\n",
+    "            above_critical = season_data[\n",
+    "                season_data[discharge_col] > q_critical]\n",
+    "\n",
+    "            if len(above_critical) > 0:\n",
+    "\n",
+    "                first_day = above_critical.iloc[0]\n",
+    "\n",
+    "                freshet_start_dates.append({\n",
+    "                    \"scenario\": scenario,\n",
+    "                    \"year\": year,\n",
+    "                    \"freshet_start_date\": first_day[\"Date\"],\n",
+    "                    \"discharge_m3s\": first_day[discharge_col]})\n",
+    "\n",
+    "    freshet_start_dates = pd.DataFrame(freshet_start_dates)\n",
+    "\n",
+    "    return freshet_start_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "9df30415-2797-4600-8d2f-3912afba94a9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>year</th>\n",
+       "      <th>freshet_start_date</th>\n",
+       "      <th>discharge_m3s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>2000</td>\n",
+       "      <td>2000-05-17</td>\n",
+       "      <td>561.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>2001-05-04</td>\n",
+       "      <td>510.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>2002</td>\n",
+       "      <td>2002-05-07</td>\n",
+       "      <td>600.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>2003</td>\n",
+       "      <td>2003-04-26</td>\n",
+       "      <td>600.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>2004</td>\n",
+       "      <td>2004-04-14</td>\n",
+       "      <td>533.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>246</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2095</td>\n",
+       "      <td>2095-03-06</td>\n",
+       "      <td>573.481886</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>247</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2096</td>\n",
+       "      <td>2096-03-23</td>\n",
+       "      <td>520.442698</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>248</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2097</td>\n",
+       "      <td>2097-04-19</td>\n",
+       "      <td>511.132103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>249</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2098</td>\n",
+       "      <td>2098-03-16</td>\n",
+       "      <td>601.581833</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>250</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2099</td>\n",
+       "      <td>2099-03-12</td>\n",
+       "      <td>545.881703</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>251 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       scenario  year freshet_start_date  discharge_m3s\n",
+       "0    historical  2000         2000-05-17     561.000000\n",
+       "1    historical  2001         2001-05-04     510.000000\n",
+       "2    historical  2002         2002-05-07     600.000000\n",
+       "3    historical  2003         2003-04-26     600.000000\n",
+       "4    historical  2004         2004-04-14     533.000000\n",
+       "..          ...   ...                ...            ...\n",
+       "246      ssp370  2095         2095-03-06     573.481886\n",
+       "247      ssp370  2096         2096-03-23     520.442698\n",
+       "248      ssp370  2097         2097-04-19     511.132103\n",
+       "249      ssp370  2098         2098-03-16     601.581833\n",
+       "250      ssp370  2099         2099-03-12     545.881703\n",
+       "\n",
+       "[251 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "breakup_start_dates = find_breakup_dates(\n",
+    "    projection_data=projection_data,\n",
+    "    start_year_hist=2000,\n",
+    "    end_year_hist=2025,\n",
+    "    start_year_fut=2025,\n",
+    "    end_year_fut=2099)\n",
+    "\n",
+    "breakup_start_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "97f168cf-da9e-493f-8714-11f0066a7903",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_freshet_barchart_10day(freshet_dates, title, colname):\n",
+    "\n",
+    "    data = freshet_dates.copy()\n",
+    "\n",
+    "    # Convert freshet start date to day-of-year\n",
+    "    data[\"doy\"] = data[colname].dt.dayofyear\n",
+    "\n",
+    "    # Define 10-day bins\n",
+    "    min_doy = int(data[\"doy\"].min())\n",
+    "    max_doy = int(data[\"doy\"].max())\n",
+    "\n",
+    "    bins = np.arange(min_doy, max_doy + 10, 10)\n",
+    "\n",
+    "    data[\"date_bin\"] = pd.cut(data[\"doy\"], bins=bins, right=False)\n",
+    "\n",
+    "    # Count number of freshet dates per scenario per bin\n",
+    "    count_table = (data.groupby([\"date_bin\", \"scenario\"]).size().reset_index(name=\"count\"))\n",
+    "\n",
+    "    # Create readable labels for bins\n",
+    "    bin_labels = []\n",
+    "\n",
+    "    for interval in count_table[\"date_bin\"].cat.categories:\n",
+    "        start_date = pd.Timestamp(\"2000-01-01\") + pd.Timedelta(days=int(interval.left) - 1)\n",
+    "        end_date   = pd.Timestamp(\"2000-01-01\") + pd.Timedelta(days=int(interval.right) - 2)\n",
+    "\n",
+    "        label = f\"{start_date.strftime('%b %d')}-{end_date.strftime('%b %d')}\"\n",
+    "        bin_labels.append(label)\n",
+    "\n",
+    "    label_map = dict(zip(count_table[\"date_bin\"].cat.categories, bin_labels))\n",
+    "    \n",
+    "    count_table[\"date_bin_label\"] = count_table[\"date_bin\"].map(label_map)\n",
+    "\n",
+    "    # Pivot for plotting\n",
+    "    plot_table = count_table.pivot_table(index=\"date_bin_label\", columns=\"scenario\", values=\"count\", fill_value=0)\n",
+    "\n",
+    "    # Remove bins where all scenarios have zero observations\n",
+    "    plot_table = plot_table.loc[plot_table.sum(axis=1) > 0]\n",
+    "\n",
+    "    # Plot\n",
+    "    plot_table.plot(kind=\"bar\", figsize=(10, 5), color=[colours[scenario] for scenario in plot_table.columns])\n",
+    "\n",
+    "    plt.xlabel(f\"{title} date range\")\n",
+    "    plt.ylabel(\"Number of years\")\n",
+    "    plt.title(f\"Distribution of {title} dates by climate scenario\")\n",
+    "    plt.grid(axis=\"y\")\n",
+    "    plt.legend(title=\"Scenario\")\n",
+    "    plt.xticks(rotation=45, ha=\"right\")\n",
+    "    plt.yticks(range(0, int(plot_table.to_numpy().max()) + 1, 3))\n",
+    "\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "a6986d98-c133-4875-91f5-2dda53e802eb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_126637/3610468776.py:17: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
+      "/tmp/ipykernel_126637/3610468776.py:34: FutureWarning: The default value of observed=False is deprecated and will change to observed=True in a future version of pandas. Specify observed=False to silence this warning and retain the current behavior\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_freshet_barchart_10day(freshet_dates=breakup_start_dates, colname=\"freshet_start_date\", title=\"Break up\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0d3cfb77-d565-4e40-b812-148fd7eae55a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b3ab2788-80e6-469d-b77e-d7b56c641f1c",
+   "metadata": {},
+   "source": [
+    "### 7.2 River freeze up"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "acbc5f0f-9a45-425f-9175-a5798c562790",
+   "metadata": {},
+   "source": [
+    "The first step is to find the freeze dates using the def function below. After the previously made barchart function can be called."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "4fcf6ad4-1157-4fbe-b859-fc6dbd2ba79a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "AFDD_critical = 30\n",
+    "\n",
+    "def find_freezeup_dates(forcing_data, start_year_fut, end_year_fut, start_year_hist, end_year_hist):\n",
+    "\n",
+    "    AFDD_critical_dates = []\n",
+    "\n",
+    "    for scenario in scenarios_new:\n",
+    "\n",
+    "        # Extract temperature above surface (tas) data\n",
+    "        temp_data = forcing_data_all[scenario][\"tas\"]\n",
+    "\n",
+    "        # Convert into df to make life easier\n",
+    "        temp_data = pd.DataFrame({\"Date\": temp_data.index, \"Temp\": temp_data.values})\n",
+    "\n",
+    "        # Conver to datetime\n",
+    "        temp_data[\"Date\"] = pd.to_datetime(temp_data[\"Date\"])\n",
+    "\n",
+    "        # Assign year to each data point\n",
+    "        temp_data[\"Year\"] = temp_data[\"Date\"].dt.year\n",
+    "\n",
+    "        if scenario == \"historical\":\n",
+    "            \n",
+    "            start_year_use = start_year_hist\n",
+    "            end_year_use = end_year_hist\n",
+    "\n",
+    "        else:\n",
+    "\n",
+    "            start_year_use = start_year_fut\n",
+    "            end_year_use = end_year_fut\n",
+    "    \n",
+    "        # Loop through every year\n",
+    "        for year in range(start_year_use, end_year_use + 1):\n",
+    "\n",
+    "            # Start counting from October 1 to eliminate anomalies\n",
+    "            year_data = temp_data[\n",
+    "                (temp_data[\"Year\"] == year) &\n",
+    "                (temp_data[\"Date\"] >= pd.to_datetime(f\"{year}-10-01\"))]\n",
+    "\n",
+    "            # Set 0 as starting point for counting cumulative\n",
+    "            AFDD = 0\n",
+    "\n",
+    "            # Loop through all data points in a year\n",
+    "            for i in range(len(year_data)):\n",
+    "\n",
+    "                temp = year_data.iloc[i][\"Temp\"]\n",
+    "                date = year_data.iloc[i][\"Date\"]\n",
+    "\n",
+    "                # Cumulative AFDD\n",
+    "                if temp < 0:\n",
+    "                    AFDD += -temp\n",
+    "\n",
+    "                # Append when AFDD is critical\n",
+    "                if AFDD >= AFDD_critical:\n",
+    "\n",
+    "                    AFDD_critical_dates.append({\n",
+    "                        \"scenario\": scenario,\n",
+    "                        \"year\": year,\n",
+    "                        \"AFDD_critical_date\": date,\n",
+    "                        \"AFDD\": AFDD,\n",
+    "                        \"Temp\": temp})\n",
+    "                    \n",
+    "                    break\n",
+    "\n",
+    "    AFDD_critical_dates = pd.DataFrame(AFDD_critical_dates)\n",
+    "\n",
+    "    return AFDD_critical_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "d28d2ac0-7eeb-4027-85c4-88fd4c498611",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>scenario</th>\n",
+       "      <th>year</th>\n",
+       "      <th>AFDD_critical_date</th>\n",
+       "      <th>AFDD</th>\n",
+       "      <th>Temp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1989</td>\n",
+       "      <td>1989-11-01</td>\n",
+       "      <td>32.489258</td>\n",
+       "      <td>-2.629700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1990</td>\n",
+       "      <td>1990-11-12</td>\n",
+       "      <td>30.216248</td>\n",
+       "      <td>-6.528046</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1991</td>\n",
+       "      <td>1991-11-15</td>\n",
+       "      <td>31.900940</td>\n",
+       "      <td>-2.974640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>1992-11-01</td>\n",
+       "      <td>36.211761</td>\n",
+       "      <td>-10.461182</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>historical</td>\n",
+       "      <td>1993</td>\n",
+       "      <td>1993-10-09</td>\n",
+       "      <td>30.085388</td>\n",
+       "      <td>-0.323120</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>246</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2095</td>\n",
+       "      <td>2095-11-15</td>\n",
+       "      <td>32.214935</td>\n",
+       "      <td>-7.631531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>247</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2096</td>\n",
+       "      <td>2096-11-25</td>\n",
+       "      <td>34.426178</td>\n",
+       "      <td>-6.217194</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>248</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2097</td>\n",
+       "      <td>2097-11-19</td>\n",
+       "      <td>35.140442</td>\n",
+       "      <td>-7.922821</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>249</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2098</td>\n",
+       "      <td>2098-11-14</td>\n",
+       "      <td>31.264648</td>\n",
+       "      <td>-9.818970</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>250</th>\n",
+       "      <td>ssp370</td>\n",
+       "      <td>2099</td>\n",
+       "      <td>2099-11-21</td>\n",
+       "      <td>32.216797</td>\n",
+       "      <td>-10.493774</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>251 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       scenario  year AFDD_critical_date       AFDD       Temp\n",
+       "0    historical  1989         1989-11-01  32.489258  -2.629700\n",
+       "1    historical  1990         1990-11-12  30.216248  -6.528046\n",
+       "2    historical  1991         1991-11-15  31.900940  -2.974640\n",
+       "3    historical  1992         1992-11-01  36.211761 -10.461182\n",
+       "4    historical  1993         1993-10-09  30.085388  -0.323120\n",
+       "..          ...   ...                ...        ...        ...\n",
+       "246      ssp370  2095         2095-11-15  32.214935  -7.631531\n",
+       "247      ssp370  2096         2096-11-25  34.426178  -6.217194\n",
+       "248      ssp370  2097         2097-11-19  35.140442  -7.922821\n",
+       "249      ssp370  2098         2098-11-14  31.264648  -9.818970\n",
+       "250      ssp370  2099         2099-11-21  32.216797 -10.493774\n",
+       "\n",
+       "[251 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "freezeup_dates_future = find_freezeup_dates(\n",
+    "    forcing_data=forcing_data,\n",
+    "    start_year_fut=2025,\n",
+    "    end_year_fut=2099,\n",
+    "    start_year_hist=1989,\n",
+    "    end_year_hist=2014)\n",
+    "\n",
+    "freezeup_dates_future"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a77b9ec-a2d3-440e-8ecb-feb9517d880c",
+   "metadata": {},
+   "source": [
+    "The second step is to visualise this data (below)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "9ccf8722-04a8-4903-b2cf-a4fd4d08535b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_126637/3610468776.py:17: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
+      "/tmp/ipykernel_126637/3610468776.py:34: FutureWarning: The default value of observed=False is deprecated and will change to observed=True in a future version of pandas. Specify observed=False to silence this warning and retain the current behavior\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Call barchart function from 7.1\n",
+    "\n",
+    "plot_freshet_barchart_10day(freshet_dates=freezeup_dates_future, colname=\"AFDD_critical_date\", title=\"Freeze up\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "748ecf99-59bc-4a79-a154-a50f52eef455",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4d948008-25f8-4c84-866d-5e69348083bf",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/test.txt b/test.txt
new file mode 100644
index 00000000..e69de29b