diff --git a/Comparison_ModelLevels.ipynb b/Comparison_ModelLevels.ipynb
new file mode 100644
index 0000000..71eaeba
--- /dev/null
+++ b/Comparison_ModelLevels.ipynb
@@ -0,0 +1,2237 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "488c1841",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import warnings\n",
+    "\n",
+    "from src import utils\n",
+    "\n",
+    "import pandas as pd\n",
+    "from matplotlib import pyplot as plt\n",
+    "from pathlib import Path\n",
+    "from datetime import date, datetime\n",
+    "import numpy as np\n",
+    "#import geopandas as geo\n",
+    "import subprocess\n",
+    "\n",
+    "from IPython.display import display, Markdown"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "707b90ea",
+   "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>GEOID</th>\n",
+       "      <th>state</th>\n",
+       "      <th>NFIRS_start</th>\n",
+       "      <th>NFIRS_end</th>\n",
+       "      <th>years_fires_reported</th>\n",
+       "      <th>total_fires_reported</th>\n",
+       "      <th>max_fires_1k</th>\n",
+       "      <th>median_fires_1k</th>\n",
+       "      <th>total_fires_reported_sev</th>\n",
+       "      <th>max_fires_1k_sev</th>\n",
+       "      <th>...</th>\n",
+       "      <th>snap_past_12_mo</th>\n",
+       "      <th>single_unit_home</th>\n",
+       "      <th>multi_unit_home</th>\n",
+       "      <th>mobile_home</th>\n",
+       "      <th>boat_van_rv_home</th>\n",
+       "      <th>spanish_speaking</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>state_rank</th>\n",
+       "      <th>county_id</th>\n",
+       "      <th>county_rank</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>#_010010201001</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.342282</td>\n",
+       "      <td>1.342282</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.342282</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.183099</td>\n",
+       "      <td>0.820423</td>\n",
+       "      <td>0.024648</td>\n",
+       "      <td>0.154930</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.102113</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>2806.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>#_010010201002</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>4</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>1.581028</td>\n",
+       "      <td>1.185771</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.790514</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.096491</td>\n",
+       "      <td>0.925054</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.074946</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.046053</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>3159.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>29.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>#_010010202001</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>3.141361</td>\n",
+       "      <td>1.047120</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.047120</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.303109</td>\n",
+       "      <td>0.768844</td>\n",
+       "      <td>0.201005</td>\n",
+       "      <td>0.030151</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>1587.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>12.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>#_010010202002</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>3.777148</td>\n",
+       "      <td>0.944287</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.888574</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.172566</td>\n",
+       "      <td>0.821138</td>\n",
+       "      <td>0.168699</td>\n",
+       "      <td>0.010163</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.011062</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>2357.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>#_010010203001</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>1.269036</td>\n",
+       "      <td>0.634518</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.423012</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.082524</td>\n",
+       "      <td>0.995112</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.004888</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.037621</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>2313.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>18.0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>216022</th>\n",
+       "      <td>#_560459511001</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.372684</td>\n",
+       "      <td>1.372684</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.372684</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.054252</td>\n",
+       "      <td>0.711035</td>\n",
+       "      <td>0.053470</td>\n",
+       "      <td>0.228669</td>\n",
+       "      <td>0.006826</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>216023</th>\n",
+       "      <td>#_560459511002</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.632111</td>\n",
+       "      <td>0.632111</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.010724</td>\n",
+       "      <td>0.706250</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.293750</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.009383</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>216024</th>\n",
+       "      <td>#_560459513001</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>4</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1.737619</td>\n",
+       "      <td>0.868810</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.172084</td>\n",
+       "      <td>0.709910</td>\n",
+       "      <td>0.054054</td>\n",
+       "      <td>0.236036</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>215.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>216025</th>\n",
+       "      <td>#_560459513002</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.970874</td>\n",
+       "      <td>0.970874</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.075404</td>\n",
+       "      <td>0.720325</td>\n",
+       "      <td>0.160976</td>\n",
+       "      <td>0.118699</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>247.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>216026</th>\n",
+       "      <td>#_560459513003</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.625391</td>\n",
+       "      <td>0.625391</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.625391</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.075080</td>\n",
+       "      <td>0.688752</td>\n",
+       "      <td>0.015408</td>\n",
+       "      <td>0.295840</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>286.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>216027 rows × 54 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 GEOID state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
+       "0       #_010010201001    AL         2011       2017                     2   \n",
+       "1       #_010010201002    AL         2011       2017                     4   \n",
+       "2       #_010010202001    AL         2011       2017                     5   \n",
+       "3       #_010010202002    AL         2011       2017                     5   \n",
+       "4       #_010010203001    AL         2011       2017                     6   \n",
+       "...                ...   ...          ...        ...                   ...   \n",
+       "216022  #_560459511001    WY         2011       2017                     1   \n",
+       "216023  #_560459511002    WY         2011       2017                     1   \n",
+       "216024  #_560459513001    WY         2011       2017                     4   \n",
+       "216025  #_560459513002    WY         2011       2017                     2   \n",
+       "216026  #_560459513003    WY         2011       2017                     3   \n",
+       "\n",
+       "        total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
+       "0                        2.0      1.342282         1.342282   \n",
+       "1                        6.0      1.581028         1.185771   \n",
+       "2                        7.0      3.141361         1.047120   \n",
+       "3                       10.0      3.777148         0.944287   \n",
+       "4                       10.0      1.269036         0.634518   \n",
+       "...                      ...           ...              ...   \n",
+       "216022                   2.0      1.372684         1.372684   \n",
+       "216023                   1.0      0.632111         0.632111   \n",
+       "216024                   5.0      1.737619         0.868810   \n",
+       "216025                   2.0      0.970874         0.970874   \n",
+       "216026                   3.0      0.625391         0.625391   \n",
+       "\n",
+       "        total_fires_reported_sev  max_fires_1k_sev  ...  snap_past_12_mo  \\\n",
+       "0                            2.0          1.342282  ...         0.183099   \n",
+       "1                            2.0          0.790514  ...         0.096491   \n",
+       "2                            2.0          1.047120  ...         0.303109   \n",
+       "3                            3.0          1.888574  ...         0.172566   \n",
+       "4                            5.0          0.423012  ...         0.082524   \n",
+       "...                          ...               ...  ...              ...   \n",
+       "216022                       2.0          1.372684  ...         0.054252   \n",
+       "216023                       0.0               NaN  ...         0.010724   \n",
+       "216024                       0.0               NaN  ...         0.172084   \n",
+       "216025                       0.0               NaN  ...         0.075404   \n",
+       "216026                       1.0          0.625391  ...         0.075080   \n",
+       "\n",
+       "        single_unit_home  multi_unit_home  mobile_home  boat_van_rv_home  \\\n",
+       "0               0.820423         0.024648     0.154930          0.000000   \n",
+       "1               0.925054         0.000000     0.074946          0.000000   \n",
+       "2               0.768844         0.201005     0.030151          0.000000   \n",
+       "3               0.821138         0.168699     0.010163          0.000000   \n",
+       "4               0.995112         0.000000     0.004888          0.000000   \n",
+       "...                  ...              ...          ...               ...   \n",
+       "216022          0.711035         0.053470     0.228669          0.006826   \n",
+       "216023          0.706250         0.000000     0.293750          0.000000   \n",
+       "216024          0.709910         0.054054     0.236036          0.000000   \n",
+       "216025          0.720325         0.160976     0.118699          0.000000   \n",
+       "216026          0.688752         0.015408     0.295840          0.000000   \n",
+       "\n",
+       "        spanish_speaking  state_id state_rank  county_id  county_rank  \n",
+       "0               0.102113      #_01     2806.0    #_01001         24.0  \n",
+       "1               0.046053      #_01     3159.0    #_01001         29.0  \n",
+       "2               0.000000      #_01     1587.0    #_01001         12.0  \n",
+       "3               0.011062      #_01     2357.0    #_01001         19.0  \n",
+       "4               0.037621      #_01     2313.0    #_01001         18.0  \n",
+       "...                  ...       ...        ...        ...          ...  \n",
+       "216022          0.000000      #_56        2.0    #_56045          1.0  \n",
+       "216023          0.009383      #_56       23.0    #_56045          2.0  \n",
+       "216024          0.000000      #_56      215.0    #_56045          3.0  \n",
+       "216025          0.000000      #_56      247.0    #_56045          4.0  \n",
+       "216026          0.000000      #_56      286.0    #_56045          5.0  \n",
+       "\n",
+       "[216027 rows x 54 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "in_name = 'CombinedModels-FileStructureColumns-pop50-block_group-2022-09-04.csv'\n",
+    "out_bg = pd.read_csv(utils.DATA['model-outputs'] / in_name)\n",
+    "out_bg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "59d7186c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#in_name = 'CombinedModels-FileStructureColumns-pop50-tract-2022-09-04.csv'\n",
+    "#out_tract = pd.read_csv(utils.DATA['model-outputs'] / in_name)\n",
+    "#out_tract.index = out_tract['GEOID']\n",
+    "#out_tract = out_tract.drop(columns = ['GEOID', 'geography'])\n",
+    "#out_tract\n",
+    "#out_tract.to_csv(utils.DATA['model-outputs'] / in_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "9287172a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\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>GEOID</th>\n",
+       "      <th>state</th>\n",
+       "      <th>NFIRS_start</th>\n",
+       "      <th>NFIRS_end</th>\n",
+       "      <th>years_fires_reported</th>\n",
+       "      <th>total_fires_reported</th>\n",
+       "      <th>max_fires_1k</th>\n",
+       "      <th>median_fires_1k</th>\n",
+       "      <th>total_fires_reported_sev</th>\n",
+       "      <th>max_fires_1k_sev</th>\n",
+       "      <th>...</th>\n",
+       "      <th>snap_past_12_mo</th>\n",
+       "      <th>single_unit_home</th>\n",
+       "      <th>multi_unit_home</th>\n",
+       "      <th>mobile_home</th>\n",
+       "      <th>boat_van_rv_home</th>\n",
+       "      <th>spanish_speaking</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>state_rank</th>\n",
+       "      <th>county_id</th>\n",
+       "      <th>county_rank</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>#_01001020100</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.995025</td>\n",
+       "      <td>0.995025</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.995025</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.128592</td>\n",
+       "      <td>0.885486</td>\n",
+       "      <td>0.009321</td>\n",
+       "      <td>0.105193</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.066831</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>982.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>10.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>#_01001020200</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>2.979146</td>\n",
+       "      <td>0.993049</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.993049</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.234467</td>\n",
+       "      <td>0.797753</td>\n",
+       "      <td>0.183146</td>\n",
+       "      <td>0.019101</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.005817</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>696.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>#_01001020300</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1.275510</td>\n",
+       "      <td>1.275510</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.637755</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.111567</td>\n",
+       "      <td>0.900141</td>\n",
+       "      <td>0.096343</td>\n",
+       "      <td>0.003516</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.028360</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>851.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>#_01001020400</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0.876616</td>\n",
+       "      <td>0.767039</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.438308</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.034827</td>\n",
+       "      <td>0.946181</td>\n",
+       "      <td>0.053819</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.048244</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>935.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>9.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>#_01001020500</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>1.065891</td>\n",
+       "      <td>0.678295</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>0.290698</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.117928</td>\n",
+       "      <td>0.678928</td>\n",
+       "      <td>0.321072</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.005857</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>1094.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>11.0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>72137</th>\n",
+       "      <td>#_56043000200</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.327869</td>\n",
+       "      <td>0.327869</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.091458</td>\n",
+       "      <td>0.764368</td>\n",
+       "      <td>0.063218</td>\n",
+       "      <td>0.167385</td>\n",
+       "      <td>0.005029</td>\n",
+       "      <td>0.056990</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>81.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72138</th>\n",
+       "      <td>#_56043000301</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>1.202405</td>\n",
+       "      <td>0.801603</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.801603</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.064153</td>\n",
+       "      <td>0.831159</td>\n",
+       "      <td>0.099002</td>\n",
+       "      <td>0.069839</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.105229</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72139</th>\n",
+       "      <td>#_56043000302</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>3</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1.141118</td>\n",
+       "      <td>0.380373</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.380373</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.087787</td>\n",
+       "      <td>0.729391</td>\n",
+       "      <td>0.160394</td>\n",
+       "      <td>0.096774</td>\n",
+       "      <td>0.013441</td>\n",
+       "      <td>0.152151</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>105.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72140</th>\n",
+       "      <td>#_56045951100</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.658111</td>\n",
+       "      <td>0.493583</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.658111</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.031593</td>\n",
+       "      <td>0.708755</td>\n",
+       "      <td>0.027993</td>\n",
+       "      <td>0.259678</td>\n",
+       "      <td>0.003574</td>\n",
+       "      <td>0.004885</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72141</th>\n",
+       "      <td>#_56045951300</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>0.793651</td>\n",
+       "      <td>0.529101</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.264550</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.104706</td>\n",
+       "      <td>0.705882</td>\n",
+       "      <td>0.076416</td>\n",
+       "      <td>0.217702</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>72142 rows × 53 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               GEOID state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
+       "0      #_01001020100    AL         2011       2017                     5   \n",
+       "1      #_01001020200    AL         2011       2017                     7   \n",
+       "2      #_01001020300    AL         2011       2017                     7   \n",
+       "3      #_01001020400    AL         2011       2017                     6   \n",
+       "4      #_01001020500    AL         2011       2017                     7   \n",
+       "...              ...   ...          ...        ...                   ...   \n",
+       "72137  #_56043000200    WY         2011       2017                     2   \n",
+       "72138  #_56043000301    WY         2011       2017                     5   \n",
+       "72139  #_56043000302    WY         2011       2017                     3   \n",
+       "72140  #_56045951100    WY         2011       2017                     2   \n",
+       "72141  #_56045951300    WY         2011       2017                     5   \n",
+       "\n",
+       "       total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
+       "0                       8.0      0.995025         0.995025   \n",
+       "1                      17.0      2.979146         0.993049   \n",
+       "2                      22.0      1.275510         1.275510   \n",
+       "3                      17.0      0.876616         0.767039   \n",
+       "4                      49.0      1.065891         0.678295   \n",
+       "...                     ...           ...              ...   \n",
+       "72137                   2.0      0.327869         0.327869   \n",
+       "72138                  10.0      1.202405         0.801603   \n",
+       "72139                   5.0      1.141118         0.380373   \n",
+       "72140                   3.0      0.658111         0.493583   \n",
+       "72141                  10.0      0.793651         0.529101   \n",
+       "\n",
+       "       total_fires_reported_sev  max_fires_1k_sev  ...  snap_past_12_mo  \\\n",
+       "0                           4.0          0.995025  ...         0.128592   \n",
+       "1                           5.0          0.993049  ...         0.234467   \n",
+       "2                           8.0          0.637755  ...         0.111567   \n",
+       "3                           5.0          0.438308  ...         0.034827   \n",
+       "4                           7.0          0.290698  ...         0.117928   \n",
+       "...                         ...               ...  ...              ...   \n",
+       "72137                       0.0               NaN  ...         0.091458   \n",
+       "72138                       3.0          0.801603  ...         0.064153   \n",
+       "72139                       1.0          0.380373  ...         0.087787   \n",
+       "72140                       2.0          0.658111  ...         0.031593   \n",
+       "72141                       1.0          0.264550  ...         0.104706   \n",
+       "\n",
+       "       single_unit_home  multi_unit_home  mobile_home  boat_van_rv_home  \\\n",
+       "0              0.885486         0.009321     0.105193          0.000000   \n",
+       "1              0.797753         0.183146     0.019101          0.000000   \n",
+       "2              0.900141         0.096343     0.003516          0.000000   \n",
+       "3              0.946181         0.053819     0.000000          0.000000   \n",
+       "4              0.678928         0.321072     0.000000          0.000000   \n",
+       "...                 ...              ...          ...               ...   \n",
+       "72137          0.764368         0.063218     0.167385          0.005029   \n",
+       "72138          0.831159         0.099002     0.069839          0.000000   \n",
+       "72139          0.729391         0.160394     0.096774          0.013441   \n",
+       "72140          0.708755         0.027993     0.259678          0.003574   \n",
+       "72141          0.705882         0.076416     0.217702          0.000000   \n",
+       "\n",
+       "       spanish_speaking  state_id  state_rank  county_id  county_rank  \n",
+       "0              0.066831      #_01       982.0    #_01001         10.0  \n",
+       "1              0.005817      #_01       696.0    #_01001          2.0  \n",
+       "2              0.028360      #_01       851.0    #_01001          7.0  \n",
+       "3              0.048244      #_01       935.0    #_01001          9.0  \n",
+       "4              0.005857      #_01      1094.0    #_01001         11.0  \n",
+       "...                 ...       ...         ...        ...          ...  \n",
+       "72137          0.056990      #_56        81.0    #_56043          2.0  \n",
+       "72138          0.105229      #_56        15.0    #_56043          1.0  \n",
+       "72139          0.152151      #_56       105.0    #_56043          3.0  \n",
+       "72140          0.004885      #_56        50.0    #_56045          2.0  \n",
+       "72141          0.000000      #_56         4.0    #_56045          1.0  \n",
+       "\n",
+       "[72142 rows x 53 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "in_name = 'CombinedModels-FileStructureColumns-pop50-tract-2022-09-04.csv'\n",
+    "out_tract = pd.read_csv(utils.DATA['model-outputs'] / in_name)\n",
+    "out_tract"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "4e68c025",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#in_name = 'CombinedModels-FileStructureColumns-pop50-county-2022-09-04.csv'\n",
+    "#out_county = pd.read_csv(utils.DATA['model-outputs'] / in_name)\n",
+    "#out_county.index = out_county['GEOID']\n",
+    "#out_county = out_county.drop(columns = ['GEOID', 'geography'])\n",
+    "#out_county\n",
+    "#out_county.to_csv(utils.DATA['model-outputs'] / in_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "430b4b71",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEOID</th>\n",
+       "      <th>state</th>\n",
+       "      <th>NFIRS_start</th>\n",
+       "      <th>NFIRS_end</th>\n",
+       "      <th>years_fires_reported</th>\n",
+       "      <th>total_fires_reported</th>\n",
+       "      <th>max_fires_1k</th>\n",
+       "      <th>median_fires_1k</th>\n",
+       "      <th>total_fires_reported_sev</th>\n",
+       "      <th>max_fires_1k_sev</th>\n",
+       "      <th>...</th>\n",
+       "      <th>snap_past_12_mo</th>\n",
+       "      <th>single_unit_home</th>\n",
+       "      <th>multi_unit_home</th>\n",
+       "      <th>mobile_home</th>\n",
+       "      <th>boat_van_rv_home</th>\n",
+       "      <th>spanish_speaking</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>state_rank</th>\n",
+       "      <th>county_id</th>\n",
+       "      <th>county_rank</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>168.0</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>0.164841</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.127977</td>\n",
+       "      <td>0.728978</td>\n",
+       "      <td>0.089284</td>\n",
+       "      <td>0.180285</td>\n",
+       "      <td>0.001453</td>\n",
+       "      <td>0.022453</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>#_01003</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>758.0</td>\n",
+       "      <td>0.737388</td>\n",
+       "      <td>0.508544</td>\n",
+       "      <td>133.0</td>\n",
+       "      <td>0.122050</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.089366</td>\n",
+       "      <td>0.630123</td>\n",
+       "      <td>0.249631</td>\n",
+       "      <td>0.119252</td>\n",
+       "      <td>0.000995</td>\n",
+       "      <td>0.044759</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>#_01003</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>#_01005</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>0.761389</td>\n",
+       "      <td>0.211497</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0.338395</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.257016</td>\n",
+       "      <td>0.576597</td>\n",
+       "      <td>0.121674</td>\n",
+       "      <td>0.299441</td>\n",
+       "      <td>0.002288</td>\n",
+       "      <td>0.050249</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>#_01005</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>#_01007</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>0.388293</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.146243</td>\n",
+       "      <td>0.643781</td>\n",
+       "      <td>0.072113</td>\n",
+       "      <td>0.284106</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.014411</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>#_01007</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>#_01009</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>0.928212</td>\n",
+       "      <td>0.367782</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.315242</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.116018</td>\n",
+       "      <td>0.731656</td>\n",
+       "      <td>0.038784</td>\n",
+       "      <td>0.229224</td>\n",
+       "      <td>0.000335</td>\n",
+       "      <td>0.057006</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>#_01009</td>\n",
+       "      <td>1.0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>3137</th>\n",
+       "      <td>#_56037</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>115.0</td>\n",
+       "      <td>0.543404</td>\n",
+       "      <td>0.441516</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0.226419</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.044100</td>\n",
+       "      <td>0.616271</td>\n",
+       "      <td>0.158779</td>\n",
+       "      <td>0.224322</td>\n",
+       "      <td>0.000628</td>\n",
+       "      <td>0.093154</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>#_56037</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3138</th>\n",
+       "      <td>#_56039</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>0.488368</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>0.177588</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014235</td>\n",
+       "      <td>0.702453</td>\n",
+       "      <td>0.260909</td>\n",
+       "      <td>0.030319</td>\n",
+       "      <td>0.006320</td>\n",
+       "      <td>0.124490</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>#_56039</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3139</th>\n",
+       "      <td>#_56041</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>0.677704</td>\n",
+       "      <td>0.314648</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.048407</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.083410</td>\n",
+       "      <td>0.612454</td>\n",
+       "      <td>0.133782</td>\n",
+       "      <td>0.246122</td>\n",
+       "      <td>0.007641</td>\n",
+       "      <td>0.081690</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>#_56041</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3140</th>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0.611696</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.244678</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.081943</td>\n",
+       "      <td>0.776961</td>\n",
+       "      <td>0.103910</td>\n",
+       "      <td>0.113356</td>\n",
+       "      <td>0.005773</td>\n",
+       "      <td>0.102321</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3141</th>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.072122</td>\n",
+       "      <td>0.707261</td>\n",
+       "      <td>0.053173</td>\n",
+       "      <td>0.237850</td>\n",
+       "      <td>0.001715</td>\n",
+       "      <td>0.002177</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3142 rows × 53 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        GEOID state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
+       "0     #_01001    AL         2011       2017                     7   \n",
+       "1     #_01003    AL         2011       2017                     7   \n",
+       "2     #_01005    AL         2011       2017                     7   \n",
+       "3     #_01007    AL         2011       2017                     5   \n",
+       "4     #_01009    AL         2011       2017                     7   \n",
+       "...       ...   ...          ...        ...                   ...   \n",
+       "3137  #_56037    WY         2011       2017                     6   \n",
+       "3138  #_56039    WY         2011       2017                     5   \n",
+       "3139  #_56041    WY         2011       2017                     6   \n",
+       "3140  #_56043    WY         2011       2017                     6   \n",
+       "3141  #_56045    WY         2011       2017                     7   \n",
+       "\n",
+       "      total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
+       "0                    168.0      0.567786         0.457892   \n",
+       "1                    758.0      0.737388         0.508544   \n",
+       "2                     53.0      0.761389         0.211497   \n",
+       "3                     23.0      0.388293         0.194146   \n",
+       "4                    208.0      0.928212         0.367782   \n",
+       "...                    ...           ...              ...   \n",
+       "3137                 115.0      0.543404         0.441516   \n",
+       "3138                  50.0      0.887942         0.488368   \n",
+       "3139                  42.0      0.677704         0.314648   \n",
+       "3140                  17.0      0.611696         0.367017   \n",
+       "3141                  13.0      0.439947         0.293298   \n",
+       "\n",
+       "      total_fires_reported_sev  max_fires_1k_sev  ...  snap_past_12_mo  \\\n",
+       "0                         38.0          0.164841  ...         0.127977   \n",
+       "1                        133.0          0.122050  ...         0.089366   \n",
+       "2                         15.0          0.338395  ...         0.257016   \n",
+       "3                          5.0          0.097073  ...         0.146243   \n",
+       "4                         51.0          0.315242  ...         0.116018   \n",
+       "...                        ...               ...  ...              ...   \n",
+       "3137                      32.0          0.226419  ...         0.044100   \n",
+       "3138                      11.0          0.177588  ...         0.014235   \n",
+       "3139                       3.0          0.048407  ...         0.083410   \n",
+       "3140                       4.0          0.244678  ...         0.081943   \n",
+       "3141                       3.0          0.293298  ...         0.072122   \n",
+       "\n",
+       "      single_unit_home  multi_unit_home  mobile_home  boat_van_rv_home  \\\n",
+       "0             0.728978         0.089284     0.180285          0.001453   \n",
+       "1             0.630123         0.249631     0.119252          0.000995   \n",
+       "2             0.576597         0.121674     0.299441          0.002288   \n",
+       "3             0.643781         0.072113     0.284106          0.000000   \n",
+       "4             0.731656         0.038784     0.229224          0.000335   \n",
+       "...                ...              ...          ...               ...   \n",
+       "3137          0.616271         0.158779     0.224322          0.000628   \n",
+       "3138          0.702453         0.260909     0.030319          0.006320   \n",
+       "3139          0.612454         0.133782     0.246122          0.007641   \n",
+       "3140          0.776961         0.103910     0.113356          0.005773   \n",
+       "3141          0.707261         0.053173     0.237850          0.001715   \n",
+       "\n",
+       "      spanish_speaking  state_id  state_rank  county_id  county_rank  \n",
+       "0             0.022453      #_01        63.0    #_01001          1.0  \n",
+       "1             0.044759      #_01        66.0    #_01003          1.0  \n",
+       "2             0.050249      #_01        13.0    #_01005          1.0  \n",
+       "3             0.014411      #_01        37.0    #_01007          1.0  \n",
+       "4             0.057006      #_01        11.0    #_01009          1.0  \n",
+       "...                ...       ...         ...        ...          ...  \n",
+       "3137          0.093154      #_56        19.0    #_56037          1.0  \n",
+       "3138          0.124490      #_56         8.0    #_56039          1.0  \n",
+       "3139          0.081690      #_56        22.0    #_56041          1.0  \n",
+       "3140          0.102321      #_56         5.0    #_56043          1.0  \n",
+       "3141          0.002177      #_56         9.0    #_56045          1.0  \n",
+       "\n",
+       "[3142 rows x 53 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "in_name = 'CombinedModels-FileStructureColumns-pop50-county-2022-09-04.csv'\n",
+    "out_county = pd.read_csv(utils.DATA['model-outputs'] / in_name)\n",
+    "out_county"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "0ebab53d",
+   "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",
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+       "\n",
+       "    .dataframe thead th {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEOID</th>\n",
+       "      <th>state</th>\n",
+       "      <th>NFIRS_start</th>\n",
+       "      <th>NFIRS_end</th>\n",
+       "      <th>years_fires_reported</th>\n",
+       "      <th>total_fires_reported</th>\n",
+       "      <th>max_fires_1k</th>\n",
+       "      <th>median_fires_1k</th>\n",
+       "      <th>total_fires_reported_sev</th>\n",
+       "      <th>max_fires_1k_sev</th>\n",
+       "      <th>...</th>\n",
+       "      <th>snap_past_12_mo</th>\n",
+       "      <th>single_unit_home</th>\n",
+       "      <th>multi_unit_home</th>\n",
+       "      <th>mobile_home</th>\n",
+       "      <th>boat_van_rv_home</th>\n",
+       "      <th>spanish_speaking</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>state_rank</th>\n",
+       "      <th>county_id</th>\n",
+       "      <th>county_rank</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>#_01001020100</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>3.258706</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>1.492537</td>\n",
+       "      <td>1.243781</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.995025</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.128592</td>\n",
+       "      <td>0.886272</td>\n",
+       "      <td>0.009136</td>\n",
+       "      <td>0.104592</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.066831</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>1036.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>11.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>#_01001020200</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>3.475670</td>\n",
+       "      <td>0.993049</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1.489573</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.234467</td>\n",
+       "      <td>0.796341</td>\n",
+       "      <td>0.184018</td>\n",
+       "      <td>0.019641</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.005817</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>678.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>6.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>#_01001020300</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1.913265</td>\n",
+       "      <td>1.116071</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.637755</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.111567</td>\n",
+       "      <td>0.911790</td>\n",
+       "      <td>0.084526</td>\n",
+       "      <td>0.003684</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.028360</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>704.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>#_01001020400</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>3.926803</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>1.534078</td>\n",
+       "      <td>0.876616</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.657462</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.034827</td>\n",
+       "      <td>0.943291</td>\n",
+       "      <td>0.056709</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.048244</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>663.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>#_01001020500</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6.370640</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>1.162791</td>\n",
+       "      <td>0.823643</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>0.290698</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.117928</td>\n",
+       "      <td>0.676567</td>\n",
+       "      <td>0.323433</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.005857</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>1154.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>12.0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>72137</th>\n",
+       "      <td>#_56043000200</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>0.774754</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.655738</td>\n",
+       "      <td>0.655738</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.091458</td>\n",
+       "      <td>0.753102</td>\n",
+       "      <td>0.074001</td>\n",
+       "      <td>0.166853</td>\n",
+       "      <td>0.006044</td>\n",
+       "      <td>0.056990</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72138</th>\n",
+       "      <td>#_56043000301</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1.981964</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>1.603206</td>\n",
+       "      <td>1.002004</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.801603</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.064153</td>\n",
+       "      <td>0.843318</td>\n",
+       "      <td>0.092888</td>\n",
+       "      <td>0.063794</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.105229</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>76.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72139</th>\n",
+       "      <td>#_56043000302</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1.561050</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1.521491</td>\n",
+       "      <td>1.141118</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.380373</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.087787</td>\n",
+       "      <td>0.730794</td>\n",
+       "      <td>0.159841</td>\n",
+       "      <td>0.096028</td>\n",
+       "      <td>0.013337</td>\n",
+       "      <td>0.152151</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>67.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72140</th>\n",
+       "      <td>#_56045951100</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.987167</td>\n",
+       "      <td>0.987167</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.658111</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.031593</td>\n",
+       "      <td>0.708544</td>\n",
+       "      <td>0.025635</td>\n",
+       "      <td>0.262548</td>\n",
+       "      <td>0.003273</td>\n",
+       "      <td>0.004885</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72141</th>\n",
+       "      <td>#_56045951300</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>3.032011</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>1.058201</td>\n",
+       "      <td>0.793651</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.264550</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.104706</td>\n",
+       "      <td>0.703798</td>\n",
+       "      <td>0.066841</td>\n",
+       "      <td>0.229361</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>72142 rows × 53 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               GEOID state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
+       "0      #_01001020100    AL         2011       2017              3.258706   \n",
+       "1      #_01001020200    AL         2011       2017              5.000000   \n",
+       "2      #_01001020300    AL         2011       2017              6.000000   \n",
+       "3      #_01001020400    AL         2011       2017              3.926803   \n",
+       "4      #_01001020500    AL         2011       2017              6.370640   \n",
+       "...              ...   ...          ...        ...                   ...   \n",
+       "72137  #_56043000200    WY         2011       2017              0.774754   \n",
+       "72138  #_56043000301    WY         2011       2017              1.981964   \n",
+       "72139  #_56043000302    WY         2011       2017              1.561050   \n",
+       "72140  #_56045951100    WY         2011       2017              1.000000   \n",
+       "72141  #_56045951300    WY         2011       2017              3.032011   \n",
+       "\n",
+       "       total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
+       "0                       8.0      1.492537         1.243781   \n",
+       "1                      17.0      3.475670         0.993049   \n",
+       "2                      22.0      1.913265         1.116071   \n",
+       "3                      17.0      1.534078         0.876616   \n",
+       "4                      49.0      1.162791         0.823643   \n",
+       "...                     ...           ...              ...   \n",
+       "72137                   2.0      0.655738         0.655738   \n",
+       "72138                  10.0      1.603206         1.002004   \n",
+       "72139                   5.0      1.521491         1.141118   \n",
+       "72140                   3.0      0.987167         0.987167   \n",
+       "72141                  10.0      1.058201         0.793651   \n",
+       "\n",
+       "       total_fires_reported_sev  max_fires_1k_sev  ...  snap_past_12_mo  \\\n",
+       "0                           4.0          0.995025  ...         0.128592   \n",
+       "1                           5.0          1.489573  ...         0.234467   \n",
+       "2                           8.0          0.637755  ...         0.111567   \n",
+       "3                           5.0          0.657462  ...         0.034827   \n",
+       "4                           7.0          0.290698  ...         0.117928   \n",
+       "...                         ...               ...  ...              ...   \n",
+       "72137                       0.0          0.000000  ...         0.091458   \n",
+       "72138                       3.0          0.801603  ...         0.064153   \n",
+       "72139                       1.0          0.380373  ...         0.087787   \n",
+       "72140                       2.0          0.658111  ...         0.031593   \n",
+       "72141                       1.0          0.264550  ...         0.104706   \n",
+       "\n",
+       "       single_unit_home  multi_unit_home  mobile_home  boat_van_rv_home  \\\n",
+       "0              0.886272         0.009136     0.104592          0.000000   \n",
+       "1              0.796341         0.184018     0.019641          0.000000   \n",
+       "2              0.911790         0.084526     0.003684          0.000000   \n",
+       "3              0.943291         0.056709     0.000000          0.000000   \n",
+       "4              0.676567         0.323433     0.000000          0.000000   \n",
+       "...                 ...              ...          ...               ...   \n",
+       "72137          0.753102         0.074001     0.166853          0.006044   \n",
+       "72138          0.843318         0.092888     0.063794          0.000000   \n",
+       "72139          0.730794         0.159841     0.096028          0.013337   \n",
+       "72140          0.708544         0.025635     0.262548          0.003273   \n",
+       "72141          0.703798         0.066841     0.229361          0.000000   \n",
+       "\n",
+       "       spanish_speaking  state_id  state_rank  county_id  county_rank  \n",
+       "0              0.066831      #_01      1036.0    #_01001         11.0  \n",
+       "1              0.005817      #_01       678.0    #_01001          6.0  \n",
+       "2              0.028360      #_01       704.0    #_01001          7.0  \n",
+       "3              0.048244      #_01       663.0    #_01001          5.0  \n",
+       "4              0.005857      #_01      1154.0    #_01001         12.0  \n",
+       "...                 ...       ...         ...        ...          ...  \n",
+       "72137          0.056990      #_56        27.0    #_56043          1.0  \n",
+       "72138          0.105229      #_56        76.0    #_56043          3.0  \n",
+       "72139          0.152151      #_56        67.0    #_56043          2.0  \n",
+       "72140          0.004885      #_56         2.0    #_56045          1.0  \n",
+       "72141          0.000000      #_56        80.0    #_56045          2.0  \n",
+       "\n",
+       "[72142 rows x 53 columns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "in_name = 'TrainedOnBG-tract-2022-09-04.csv'\n",
+    "after_tract = pd.read_csv(utils.DATA['model-outputs'] / in_name)\n",
+    "after_tract"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "3399ec1a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEOID</th>\n",
+       "      <th>state</th>\n",
+       "      <th>NFIRS_start</th>\n",
+       "      <th>NFIRS_end</th>\n",
+       "      <th>years_fires_reported</th>\n",
+       "      <th>total_fires_reported</th>\n",
+       "      <th>max_fires_1k</th>\n",
+       "      <th>median_fires_1k</th>\n",
+       "      <th>total_fires_reported_sev</th>\n",
+       "      <th>max_fires_1k_sev</th>\n",
+       "      <th>...</th>\n",
+       "      <th>snap_past_12_mo</th>\n",
+       "      <th>single_unit_home</th>\n",
+       "      <th>multi_unit_home</th>\n",
+       "      <th>mobile_home</th>\n",
+       "      <th>boat_van_rv_home</th>\n",
+       "      <th>spanish_speaking</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>state_rank</th>\n",
+       "      <th>county_id</th>\n",
+       "      <th>county_rank</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>3.431023</td>\n",
+       "      <td>168.0</td>\n",
+       "      <td>1.172204</td>\n",
+       "      <td>0.750943</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>0.384629</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.127977</td>\n",
+       "      <td>0.736557</td>\n",
+       "      <td>0.085260</td>\n",
+       "      <td>0.176695</td>\n",
+       "      <td>0.001488</td>\n",
+       "      <td>0.022453</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>62.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>#_01003</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>4.452360</td>\n",
+       "      <td>758.0</td>\n",
+       "      <td>1.418836</td>\n",
+       "      <td>0.762815</td>\n",
+       "      <td>133.0</td>\n",
+       "      <td>0.381408</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.089366</td>\n",
+       "      <td>0.706353</td>\n",
+       "      <td>0.157369</td>\n",
+       "      <td>0.135164</td>\n",
+       "      <td>0.001114</td>\n",
+       "      <td>0.044759</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>#_01003</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>#_01005</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1.290216</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>1.142084</td>\n",
+       "      <td>0.634491</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0.465293</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.257016</td>\n",
+       "      <td>0.581526</td>\n",
+       "      <td>0.122152</td>\n",
+       "      <td>0.293386</td>\n",
+       "      <td>0.002936</td>\n",
+       "      <td>0.050249</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>#_01005</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>#_01007</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1.644760</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>0.679513</td>\n",
+       "      <td>0.558171</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.242683</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.146243</td>\n",
+       "      <td>0.642416</td>\n",
+       "      <td>0.068359</td>\n",
+       "      <td>0.289225</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.014411</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>#_01007</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>#_01009</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.539624</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>1.611237</td>\n",
+       "      <td>0.963239</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.472863</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.116018</td>\n",
+       "      <td>0.733611</td>\n",
+       "      <td>0.039209</td>\n",
+       "      <td>0.226844</td>\n",
+       "      <td>0.000335</td>\n",
+       "      <td>0.057006</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>#_01009</td>\n",
+       "      <td>1.0</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",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>3137</th>\n",
+       "      <td>#_56037</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.296880</td>\n",
+       "      <td>115.0</td>\n",
+       "      <td>1.403795</td>\n",
+       "      <td>0.905674</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0.475479</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.044100</td>\n",
+       "      <td>0.632603</td>\n",
+       "      <td>0.157313</td>\n",
+       "      <td>0.209544</td>\n",
+       "      <td>0.000540</td>\n",
+       "      <td>0.093154</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>#_56037</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3138</th>\n",
+       "      <td>#_56039</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.502575</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>1.243118</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>0.310780</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014235</td>\n",
+       "      <td>0.700322</td>\n",
+       "      <td>0.263987</td>\n",
+       "      <td>0.031158</td>\n",
+       "      <td>0.004533</td>\n",
+       "      <td>0.124490</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>#_56039</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3139</th>\n",
+       "      <td>#_56041</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.337496</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>1.113370</td>\n",
+       "      <td>0.871333</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.145222</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.083410</td>\n",
+       "      <td>0.624190</td>\n",
+       "      <td>0.131420</td>\n",
+       "      <td>0.236145</td>\n",
+       "      <td>0.008245</td>\n",
+       "      <td>0.081690</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>#_56041</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3140</th>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1.396134</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>1.223391</td>\n",
+       "      <td>0.917543</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.081943</td>\n",
+       "      <td>0.773465</td>\n",
+       "      <td>0.107375</td>\n",
+       "      <td>0.112616</td>\n",
+       "      <td>0.006545</td>\n",
+       "      <td>0.102321</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3141</th>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.126411</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>1.026543</td>\n",
+       "      <td>0.879894</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.072122</td>\n",
+       "      <td>0.705913</td>\n",
+       "      <td>0.048477</td>\n",
+       "      <td>0.244151</td>\n",
+       "      <td>0.001458</td>\n",
+       "      <td>0.002177</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3142 rows × 53 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        GEOID state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
+       "0     #_01001    AL         2011       2017              3.431023   \n",
+       "1     #_01003    AL         2011       2017              4.452360   \n",
+       "2     #_01005    AL         2011       2017              1.290216   \n",
+       "3     #_01007    AL         2011       2017              1.644760   \n",
+       "4     #_01009    AL         2011       2017              2.539624   \n",
+       "...       ...   ...          ...        ...                   ...   \n",
+       "3137  #_56037    WY         2011       2017              2.296880   \n",
+       "3138  #_56039    WY         2011       2017              2.502575   \n",
+       "3139  #_56041    WY         2011       2017              2.337496   \n",
+       "3140  #_56043    WY         2011       2017              1.396134   \n",
+       "3141  #_56045    WY         2011       2017              2.126411   \n",
+       "\n",
+       "      total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
+       "0                    168.0      1.172204         0.750943   \n",
+       "1                    758.0      1.418836         0.762815   \n",
+       "2                     53.0      1.142084         0.634491   \n",
+       "3                     23.0      0.679513         0.558171   \n",
+       "4                    208.0      1.611237         0.963239   \n",
+       "...                    ...           ...              ...   \n",
+       "3137                 115.0      1.403795         0.905674   \n",
+       "3138                  50.0      1.243118         0.887942   \n",
+       "3139                  42.0      1.113370         0.871333   \n",
+       "3140                  17.0      1.223391         0.917543   \n",
+       "3141                  13.0      1.026543         0.879894   \n",
+       "\n",
+       "      total_fires_reported_sev  max_fires_1k_sev  ...  snap_past_12_mo  \\\n",
+       "0                         38.0          0.384629  ...         0.127977   \n",
+       "1                        133.0          0.381408  ...         0.089366   \n",
+       "2                         15.0          0.465293  ...         0.257016   \n",
+       "3                          5.0          0.242683  ...         0.146243   \n",
+       "4                         51.0          0.472863  ...         0.116018   \n",
+       "...                        ...               ...  ...              ...   \n",
+       "3137                      32.0          0.475479  ...         0.044100   \n",
+       "3138                      11.0          0.310780  ...         0.014235   \n",
+       "3139                       3.0          0.145222  ...         0.083410   \n",
+       "3140                       4.0          0.367017  ...         0.081943   \n",
+       "3141                       3.0          0.439947  ...         0.072122   \n",
+       "\n",
+       "      single_unit_home  multi_unit_home  mobile_home  boat_van_rv_home  \\\n",
+       "0             0.736557         0.085260     0.176695          0.001488   \n",
+       "1             0.706353         0.157369     0.135164          0.001114   \n",
+       "2             0.581526         0.122152     0.293386          0.002936   \n",
+       "3             0.642416         0.068359     0.289225          0.000000   \n",
+       "4             0.733611         0.039209     0.226844          0.000335   \n",
+       "...                ...              ...          ...               ...   \n",
+       "3137          0.632603         0.157313     0.209544          0.000540   \n",
+       "3138          0.700322         0.263987     0.031158          0.004533   \n",
+       "3139          0.624190         0.131420     0.236145          0.008245   \n",
+       "3140          0.773465         0.107375     0.112616          0.006545   \n",
+       "3141          0.705913         0.048477     0.244151          0.001458   \n",
+       "\n",
+       "      spanish_speaking  state_id  state_rank  county_id  county_rank  \n",
+       "0             0.022453      #_01        62.0    #_01001          1.0  \n",
+       "1             0.044759      #_01        66.0    #_01003          1.0  \n",
+       "2             0.050249      #_01        14.0    #_01005          1.0  \n",
+       "3             0.014411      #_01        59.0    #_01007          1.0  \n",
+       "4             0.057006      #_01        49.0    #_01009          1.0  \n",
+       "...                ...       ...         ...        ...          ...  \n",
+       "3137          0.093154      #_56        14.0    #_56037          1.0  \n",
+       "3138          0.124490      #_56         9.0    #_56039          1.0  \n",
+       "3139          0.081690      #_56        10.0    #_56041          1.0  \n",
+       "3140          0.102321      #_56        11.0    #_56043          1.0  \n",
+       "3141          0.002177      #_56         4.0    #_56045          1.0  \n",
+       "\n",
+       "[3142 rows x 53 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "in_name = 'TrainedOnBG-county-2022-09-04.csv'\n",
+    "after_county = pd.read_csv(utils.DATA['model-outputs'] / in_name)\n",
+    "after_county"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "f465cb3b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True])"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "after_tract.columns == out_tract.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "2cf97528",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True,  True,  True,  True,  True,  True,  True])"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "out_county.columns == after_county.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "69e975a5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['GEOID', 'state', 'NFIRS_start', 'NFIRS_end', 'years_fires_reported',\n",
+       "       'total_fires_reported', 'max_fires_1k', 'median_fires_1k',\n",
+       "       'total_fires_reported_sev', 'max_fires_1k_sev', 'median_fires_1k_sev',\n",
+       "       'fire_propensity_risk_score', 'fire_severity_risk_score',\n",
+       "       'fire_risk_score', 'recorded_home_visits', 'smoke_detector_risk_frac',\n",
+       "       'smoke_detector_risk_score', 'SVI_Theme_1', 'CombinedRiskScore',\n",
+       "       'did_not_work_past_12_mo', 'house_pct_live_alone', 'pct_alt_heat',\n",
+       "       'house_yr_pct_before_1960', 'inc_pct_poverty',\n",
+       "       'race_pct_black_or_amind', 'tot_population', 'house_tot_occ_cnt',\n",
+       "       'inc_pcincome', 'inc_hhmean', 'race_pct_white', 'race_pct_whitenh',\n",
+       "       'race_pct_whiteh', 'race_pct_nwhitenh', 'race_pct_hisp',\n",
+       "       'race_pct_black', 'race_pct_amind', 'race_pct_asian', 'race_pct_napi',\n",
+       "       'race_pct_other', 'race_pct_two+', 'age_pct_under25', 'age_pct_over65',\n",
+       "       'disability_pct', 'snap_past_12_mo', 'single_unit_home',\n",
+       "       'multi_unit_home', 'mobile_home', 'boat_van_rv_home',\n",
+       "       'spanish_speaking', 'state_id', 'state_rank', 'county_id',\n",
+       "       'county_rank'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "out_county.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "9168813f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x720 with 6 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "county = out_county.merge(after_county, how = 'left', left_on = 'GEOID', right_on = 'GEOID', suffixes = ('_out', '_after'))\n",
+    "fig, ax = plt.subplots(ncols=3, nrows = 2, figsize=(20,10))\n",
+    "axe = ax.ravel()\n",
+    "scores = ['fire_propensity_risk_score', 'fire_severity_risk_score', 'fire_risk_score', \n",
+    "        'smoke_detector_risk_score', 'SVI_Theme_1', 'CombinedRiskScore',]\n",
+    "c = 0\n",
+    "for i in range(len(scores)):\n",
+    "    county.plot.scatter(x = scores[i]+'_out', y = scores[i]+'_after', ax=axe[c], alpha = 0.1)\n",
+    "    c += 1\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "84c9fa70",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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wiJkWNV/uptQWdk4zDAZtIPKhVCxFTkOgeo9nYdD6/S41NHGiwfviug6ju5I91+2xblPI/zHw+7p/uQkpdp40rGp9aeHkqoaI7W7EZifkYJqTljVx6LPeipBSkFdqmbOcf/7y+u0ItycEkefRCiQjpamVIQglAku/5fPbSY4xhqw25JVhVlRUSqOMpiwt1Q0IpM3fFQKpwe3wYxMkgSfZ7kUM0wqpXSVyuxcReO8mgrddEK8ae7vo88/jY2fHmznns7gv0dJFYIsCSSf2scZyNC150I2W/264oIKQl3x/miIs7E8KJCwrzQI4mpZE1zj3aGvR2pFHvhTEScg0r9kZZghgWlQkoUc3apHXCj/x3UKuS3ZHKbOsQApJEnlkZe12Ch7EHtS3EEe9uJbf4PcaAqwFMf/zoiWkqDVvRjm1NgSevFDw+Cq8T7xZTZjvOla2mqy3Am+pgaQtFybtq4meN//TYkFwZaX4ouR40ZXzqB8zzGrKWrNXaf7y+dpHmTBfp1+0WPuiOdlT1Zp43qnpe+5OVbVGyMsJOmclH9AO/eWY+c6KHuL5a1zUmu9PZuxNcjY6EdKTxKFPWpVUxuBfQX1LKYh9D3/eZXfTan/oSQJP8rPtNr7fRSmDtu7vV7E4/tj3CaVhXChGWYmx8LTfIvAkoe9RzTuuDBbPk2y2Q/5qZ0RW1uwMczwffr075dlai61eRFZpt7GUPQIpedxP+M3+hGlR83qYE3qSrFTEoYe2ht3jKa+HJQ96AZ04ouVDoQWhBC1B1RALiEKwBqr30Lt72Gvf/ZcbNPgJ4CYdRh+K7LnvQv594sfYv9ynluFln38TUuw8aWiuKZwsPntvlOMJSEI36fD61O0LsIKs1oS+IC0t//q7HGUsShs+2eicef7SomZ/XCz1+ba7Ee3I46vDGQLLOK04nmhGec3DTkI78phmhpNJiTKaw1nFtDRoDZV+W4y4DALw5P2VpBsC6SPBx0CQSCl4sdEm9OSZTcllL/RtFsT3mQP+XWDHf5fmnD80bvMsX/ezi8CW+D6bnYjjWcmsUEwCie9JducbwVoZlD+vICgnZP1ivUUYeDwSsDcueDj/zG7sM85r2t7lFXlw99QKKGpFJwqolCYMnDNCWrqKwrR0TFDiC0DSCiOsLZiVmn4rYpzXFLUBIegllkJBestNwu/3YEKD89DWEniSFxvtZVKV1/qdBOblSerI/nkHUKUNX2x3b7Qm3le8WV2bsYK9cYaH4JOtzo3GylaT9S+ucWFbTfTyqqZUBm0s3x6mbHcjXmy2b9yivujK6bdCWnPCpKw0wUrXzI9d0Fngqnt1Pu4Y64o+2kJaugr644HT3/lyd3xmzOy6uG6MZaMTcjQtKZU5U41f3Nsk8GhHPrUyHM9KOqFEW4t/g7zgptV+Y+bE5AricL52h5Jp8a4ItycEnidZawUMs5oklAQyZqsbIQTklSIJBEVlyWu91F/ypGCrHfKrWcmTtRa+JxinNXujlO9PUzwh2exGRL4EC7uTHE9YxoXbeBS1JqsrDmaGtu9x5Ltc4CT3OM1SRoUlqyqC0Ifa0k00hYV2KMkKg4+zDbtFfWGJrVZ8h99q0OB3E3dZn2+65vxYZM+PFXN+6P3LfWoZXobbkGKrechVhZPF/clKxe4wJwoknhSst0MOpyXP1hOebbSYFYp/9c0RZQ3dJGC9G/C3e1OGmeKPn/RcZ2vtyKNH/ZhOHDAran7xckipNf3YB2upa81pUeNjKI1hNFGEgaA2it1hgcXF6GFaMbtB0LCAttfRTDdHQyB9BPgxCZLzC1YceGc2LvfJvt91DvhDsOP3vVB/THPO58/thwxKN32WF5uCvVF+ZSfQamCLA4/tbkQ38vGEIA695QJf1NptmKQACxudkHAehDpxwCPrKgXfHqbsGMNJWvFHD7usd+NLg6WUgvVWyF+9GmFtThT6PB/EHE0r9sc5s7JmqxvjCSd4V9SG7X7Id8cCjHuXYk8wyis6sUelJZ4xeBhi4KZSdpsNg/STwupoV3BJMldrw+HknF7dpOSTjbN6dRfhfXXBVrFYm5VxTljH0wohYLvnkqLbrNMLPZ6rEAceTwcJ35+m/GyrM48FGntBF8oCFyXHi66cJfGiXQfKanfNXQT7V3Ef6+4Z3Sfp2uv3RjmfbLTP6Betxp1FEWi1urs/Lni2nrgMUsAoq+nNR8cW5MyqftB5XaXNbkTie1jx9ryMtbQjn58/6PI3u2NeHaSEUvL5dpvvTlNerAiHXobrqv1FrXl5nHI4LQHY7ITuXvpvK7hvRgVKGyLfW3bhrV6XfuzTsR5PBy1mleL/++tDTtISTwr+/osBD3ox7dBfxkoroFaabuw0uZQVFNrw2WaXtU7ANK35198P+fmjDvvDHG0lSegRBh7DaUEchPhCYSz0E49pZlF1CdLDWo3SlsSzCN8QCg9PW7SxlAo87kYeeYC8Qry8QYPfJ7xPAeRjHSf7MZsIfsj9y/tqGd4UF42mmTlBtHosq8/BIk/Z7kbsjXIMCokrwlTaad6VSnM0LrHibc6xN8wx1mKM5W/fTDgYZ+QK1ls+Vgi0hqxW1FpxPC35bLNDZZxzZycOMMYyzGrs/P/SUvH6JKUylgc9V4i2VjMrK/waBIJgLpuR5RV1ebNrEgNV1RBIv1f4sQiSyxasD8W+33XhXl0IpBCUSrtWvDuy4x9qof4YAtNlQuU/VFC6ybO8OMZKaQ4mJc83WvjexT97UWB70Is5mBTLhL+o9duxNil42Is5TqszG0YEfHOYkgSSOAwJfMHf7U/5U18Semede1adAo9mJZvdgNO0pqgUv9wZ8ydPeqy3QqZFza/2J6y3I7bbIcpavj9K8aXPejdinBUcpYqDcUkSBgicNacQEAdQ3FDwovOTN9f5ePChydjF5y8coT5EMnfZO3oTXbDz8IRA4MijyJdEc8vzk7Qi9FxFUVhHUlxGENx2LbbCOXguCOIk9EnLi+PlZdfz8SABuDBhPk+wVcppsH2y0cb35Y2O+b5izCpBdzwpHNFQG7a6Ed05AbSIO+eJoEUXUaE0s7xiVutlpbcVeKSVYm+Uczhx2eeiiyv05IUjf4tR84XewyImd5OA7W6ENppP1zsEgcdwfv9fbFzcFbaK8/nG6vq7N8oZ5RXd2KWq47ymnwTktUYVNbvDnMAXTAqFMTVFrflsq0PgyWXBYW+cE1jBwaTg+5OMVuSx3u5igDfDks12waebbxfZQRxwkpaMspqs1my0fPaHkmFW8tXBhCdrbbSoENpihWDQCRAnUOY1Va2orUXVgLDYVLE/LTDaPZtJ6NGOfawFqw3TWtNrh1hjODTq2hGEy+ABoffxjPQ3aPChcB8F949tnOxjmLL4ofYv76NleBus7h0mRcnJrGKjHbIzypfOpOclAELPdbQeTgpKpTlNazY6IQeTgmlZkxYKpQ1HacV6O6Sax1xlLOvtgDfjgqrSTEtNrTQnObRCSawlB6OcOJAYCw96Md04wJsTW9paCqXAwlf7U04mBS+HOQJLWrlx75fHBWldEgcBoSfoRR4HRc24vHnRoR3Cevv+OlUbAukjwH23D94kef2xFqy7LNyr4pmryW6lDfE11fbz+NDn/WMGpnc2PvOxhRcbLRL/XeeyD4FVS+iL9DZWjzHyA05T182zqD5c9NyvBrZaGQ4mBQeTkoNxgZCCo2mJAJ5ttAg9yXFavbNhXGuH7Azz5ehDP4molXULefS2El8rs7R21trw+jRjsxORBD6/3Z/w5c6IaVkxzmq+eNDjQT8h8uFwWs1/tyCrDJ1AcKyhqis8XyKFnrvxONed+hZqqd3kXm5Ng/fEh64QXiTKGPjywmQumM/Lj/KKShvsnCS5iZ7cRfEG4HhaXurUdRmkFGx2I3aGOVJaerE/HxHSlNqw2YnYGeUXXrO7rsU3jZfXXU9jLI/mieRq981qglvUejk2i3AujBdZva8e803O66ZE5NsOopzI9/A8d9zH03LZNQNQzb9j9Tq73yuYFhX//Ntj1toBnTCkF3ukpcIXgmH2lpwZ5RXBSPKoF1MpTeS7dVEKweGk5Pl6stRVOpyWyzW2KhXKWB4P2iRzUktqQ61v7hy4uB6L9X1BhpVKI4TAX5BX2pkieEagtOU0rXi+0aIV+ozzkl+8GqKtoROFbLZD9sY5vhQkkU9a1hxMcwatkCjw0MYy0RVpWaOtpapdhXlnmPP5ZpeTtKTSllGm0FpxMNJU1mno5ZViVrn3LvI8HvcSvj1MwbrnsNuSVMpwNM2R0qMbgEJSlDWJEAgkwpcUpUbkFcpcKHN2K4T3qG3RoMHHit9HvdGP5Zx+iP3LeS1DYyxCuO++79G5ZcfySXpGFNs5jmrGeb3MBWZljRSCv92bYDH40uNRPyKvDbFn+HJ3TC8OkFIwKWqKWvFPPt1EeAJrYb0d8otXQ0Z5hQBebLY5mZYcTgoOxzmd2KmZHk8rlLb8g0/W8CV8d5SireVwUmCwHIxyxkVFoTS9yGeU15zWJaWCQTtiklYM65q6tozK63WPVjFIoH+PZgsNgfQR4D7bB2+alH8sC9ZNsRDPfL6eEK7Ys9+WDPldO+/zuGrjcf7chBToua/jD2UHLqXrerpMb+P8MT7sxXx3kjJJK6LQv/S5l1KAgd1piS8FD/sRf7M7xho3evKoH3Myq3gySDDWEPjyTDXFmLdOT3Hok5e1qwh73nLzVdeaN+OCx2vO2nmaa05TJ5T99cGUrw9TikpTlIa80PzNzog/2O5SGUPoeRhjqJRx1XBtOJnlZLVFasNMQ1Ubcnu7BR9grdVUln9sfGji+aLPP5yWPB0kaNxDc1748cVmm2D0diTr8RV6dauQUixbtBFO/2WrG3E0LZcb9cW6WGuDnG+KL/vsdujzZC3BExAG7tjL2vB80GJvcvk1u+tafJN4edn1XHz3hWSgPKsr5KzeS6xxo1qRJ5fi2+ddHVePudbmDAFz/lquktQ3ERrfaIe8PElhLrT5aJCg53Fg0WW0OhJQKs3uaYaQgsATZJWmG4W8GeV0I83+RPCnj3tU1sWExT0vlGacllRaczSpOE0rHg0SnLkVy46vxfks1thaGzwpOJ6VSzLSGDd+eZONwOJeaG14NcyW48lKG/Ja05r//wCV0mSl4tNNNx7ne5LTtKJUhn/13SlFqUkCyWebbX57MGE0q4gjn81OyMNejC8lZa0pa813xzOq2s30PR60mJUaISAKJN04phP5POhp/m5vzPONHq9OZ2SFZmeU89/6ZJ2iVqy3I9qhZEdk/PGTHjunAeOsYFxo2r4kDB2RlVaajgcHqqaoLYFvaPsBmdBMc+e+dpfRtQUiD3L1Pp/QoMHvBn4f9UZ/H8/pMqzGb2MNa+0QrCs6fYjROTsnp1ZFsadFzf6kYK0V4nuSWml+9WZKL/IYZ24Mf5hlhJ5kqyexAoZpRTcKEAKUdqLZ272YZ+vt5dj400GCNoai0rwZl+SR5rEPlYJ+OySQkqJS/POvj/iX3x7TjQMG7YAng4RJUfGvvjnhNKsZtH22uzGTvCQvFe1IzvVdFS9Pc1oBTG9JHgFkuSt+dFv3Y83TEEj3jLuOONxX++BNk/LftQVLz5PYRQeJ9MSdiJ/ftfNewBhLWimO5loQF208Vjc+Ugi0diKzO8MMT8or7cDv8zhHWc2LjdZSx2WhtyGlG2cx1rp5ZJxDmicEYr6pvaqjQ1tLXivSeXuoAHqJTxL5RL4jgsr5uZ+faQb4YrvDr95MGKYlk1Lz+XabnbFrYfWl4CSvOEpLjrOS7V6ExG00v9ofcZppJoXrJjqYloS+IPYlVlg6sc/ptORv30yotCEvFZ6A47Sirg3j0lWX1R2vaaY/7mfzp4APTTxf9PmTouT7k9Q9PBYeD5KlFTu8tV6/bcwoas3hvGvPwvK9OxFnxz5r5Sp1C12Yx/2z37+AlG4kzIlbu/fv6XoLId+1rF29Zu8zmnxdvLzqfmG4kgxcJLg7pxmzQtGOfLa6EWHgUWqDhUvjRzHXKDqYlEsCxpeCWht2RznWWN5MCh7346Ur5FVEZFE7QwBPCGpjeNCL8aWreK661yzG3I6mjhRLS8VmO2S9Ey3/fZBEPOrHzMqacVHTi5z2gpqvm/ujnFIbnq+1eNCLGGYVr04yHvdjtruR6xD1xBktCekJIunxZK1FrYxzvBSCB/34SgOOBc6TX6OsJg4kg3aI8aQjv0KfYa6olMFYNwJ8nFast0IedCP2xhnfHEwZZyUbnYhJofiX35/QTwLiwCfyJcO0QhvD8/WErw+m/HJnTORL/uTpgKdrMV/ujXnSS+gkAVIIR5oJwSAJqA1UWqMtDOKItKrZOU05zSse9xNOs4JhWnIyK8jKCl9KYt+5tVmtMcYSCos20A48lLVUNWQVpBXcUL7iSggu1wBr0OD3CR+T3uh94ffxnK7C+fgNt9NevM0+ezXPAEiL2u2RVrSQtHHmBjunNbvjEqym1hZfCAatdYpSYyzsjVL2RiWt0GOjHbDVCRGAPz+OR/2EN+OCKJG0Ip9HA1eYK2qFJwVKC4ZZwbRQDFohv34zYZQXZKXlcT8iiQJ6GpQBD0tRu9isLWA1ee06oTVQ32HeeVLBuCzZpnX7X74ADYF0j3jfEYf7aB+8KUHyvgvWD+0WcF/Ez+/iQr2w694Z5oS+4GHfbUrObzzOd/9IIeglHovCpL3EDvw+seqatsBCn6Sq550+yvBmVFBqTTfyebbRQuLIpKf9BIUllBL/nCOSUoaTaUUcuG60YVpzMi35g8ddpnkNwm2sHg3O3s+i1svxRz3faP3p4x79dkRRKV6PC1qhR+Q5MdSd0wxjLEno9E9+tTdBGcu0qNnuxggEWln8UKCUZZIXvD7JKCrLaVYxzQpmhSKQhrR+v8oygDUf77P5U8GHJp7Pj35qZTiZVTzsRYxz5d6dScFfPl87Q+LcNmasbtiTMDjTmbO6LgIgHNk7zF3CtT9+9/sXuIjQWYykXnbN3nc0+bJzN8aJWQrOEj1i8W9cTwYuyDkERJ5cdlb5Ul6qT7W4tpEveb7RYn+cLwkYLES+RBuLtU4jKon8K4nI1c97sdlmf5zzepjzdC05Q86s6lC5fEOgfckwr+kkPtZa55IHzMqaYVaRBB6VNbQjj9O05mhast52xxN4knFR83S9xTSvedCP3RjbtLxQS2KR44TBXEtOCJ6utW6U+6wSfdpovPl1NMb9vScFn252+FwKXg8zAiE4mJUYbTjNKrZ6EbOy5rXJ2ezGPOi6e/Hd4Qw1sDwZBOwOU9Jas54EbPUS/vTpAN/36M/Jok4ccjIrqY1L1ruRz6/mxYDNTki/5ZMWzrFv9zRHa4X0JX/8qMdJWpOXmlJbDiYlu8MCIZ0wam1cd9ebUQbSVa3//EmfV6OS0NMM0+rOmkfnEfhOC6xBg58Cfii9ng+xz7nsM9/3nD4W19Cb4nz8vmkec9t99iLP+O3BhC93xozzmm4c0E/cuH3ge6hao4zleFqwlgQcTw3jrObfpSOebrQ4nFR8utlm53hGXWtyDJ3I5+vDjPVO6Eb5OxGjzGkm7Z5mHM5coTkJPLQ2fH+cYiyktcYH3oxSdoc5niex1nCYVnizim4SkGaK8czMO2I9MBYjYVLUeBLXkX6Hax5FIO5PQ7shkO4LH4MIGtyOILnrgrWosq6OTnxot4DFee2NcqffcIuRjfN4n4X6h1qkV4VE98fFsrU+9CTHs5LHg+SdcbRl98+8+l/Vmt3TnGebrhso8OQ7duD3jcs22ovzCDxB0omIA8n3J05f6DSt0MZyMiv55nBK6HvL0bdBKyQrndirMoZSudXvJCvZ6MxF7Ob233/+tE933um0eh3fjHLXfhr7KC15laUcpxXtOCAMPKy1FLWiFQWUlUvsh2nJJ5ttjDH0k4C0VISdkN8cTHjcT3i23uaPnnSZ5orCCI5nFdOyRiuDL6GoDLWF4h4W69C7xxW/wZ3woYnn8+SvsNBpeYwL5TRVkoBJXrE3zvlss/NBOlRX10VjLDunGcOsxpeCOAmZ5jV7o5zPti7+/ncSwhtcs6tGkxfHe36tvWoNPmMPrAzVXCBzYRW8O8oBN2Z2HRno+5Knay32Rjl5Vp2Jdc8D751jWL22vudcZaZ5zVY3Yn/iiPPDWckwU2jtRDjjwLuUiLzs8x4PEpdUrlzntzpUbpzs8VqLYVby+jinUIpRXvFkLWaWG7qJT2Usk0zRa/v8+ZM++9OC0JP87d6EqdBoDLEUjEtNICWeJ9lsh+xPzBktif1xwdN591nkS9rRW42k53NDjquwSpwC9GOPUa6YFDXDtKId+RzOStbbIaUyjGqNMoajtCYJJP044B88X2eY1bRCSV5bsqqmUIpBq4MnBZO8Iq8sm50IT0ChDEnggbUYICvqZSfWy6OUw7TkQSfi8Zob35sWNW+GJcY4ja9BO0EK57JZ1gV5VbE/ychKRegJWqEbU9DWkoSCZ+s9hlnJ6axkUimSQGKFYDiraYVQVjd35LwM1kJZNyNsDX46+NB6PR9C8/Cqz3yfvcWP6eD2Q2KRH3jC5S72hlImvhCM0pp25LHdizHW6QhmlaYX+0wKRTvwUda5oUWBYK0V0k88BnFAHPoUteK0qPEDiQVCXzDKKh4PYgIhlnqz652I/UnOrKjZ6ER8f+JcRK01tEJJP/LZG6fklaYyhghLbSHPKiLfIw5c8ceTsNGJWA99/u7NFGtqfOmx2fU4HFfcQkZ1iYf9kF6jgfTx4WPS1rkNQXKXCvbL49QJhc1bvWtl+OJB9wchyqx1iZ73Ht9114X6Qy/Sq0KiC42MxUZo0HL2xeDaLatav7PxWHb/zCuRShn2ZwVWWlrhnHFHnLGxvG9ctmm0826GxfsR+o642RvmdJMAhGX3NGO7H/OgnywFwP/scZ+/3hvjCYHvC0JfYIRhoxPSCny0sTzox9S1oRW9FZVdWk0b6zaP88ukcQFCzbWhNtohm52Qw2nJy6MZUeDx+VaHw2nOaVby8jhjVmjySvFgELPRCumFPtoa9kclUSh4eZhS14bAE+RWM8prcgXK3n1sbRV51WwMPgbchXi+6VqzIH8XVusGy8uTjFBKeq0QpQ2h7y0dza7TJboM13VSLeKBEW5srVKaOJl/fyBd+/Ql3TIXnWc41yeDs0LVC1w2mnyZI9x1CfiZIo7vCOdHvZg3E0dwrI7nVeotIb3VvTypEuf+XL1Oq+dutVtvKqUJfUeG2bmT48Go4GSebD7oReyPC3aGOc/XW5eOep2/V8ZYQt97RyhdKddd9bAfEa50S80KzYuNFp7v7sFf7445mVX0k5DtbsC4VOyOcwIpsRYnjN2LOElr6trw68MZf/FsQCv2qWrN3sSRb4vRZN+T5HVNWiu0NpfqQl33DrQjj1+/mc7jneDZRsIkU2x1I56stVDa8MvXI/YnrlP0QS9mowOVsjxfa+H7kj963OObw5TAc504/+DFBtIT/N3OmFHhRqg9BC9PMx6vJXQij2+OMpQxqDV3/WeVJgglazYAT3A0K7HArFTEkeTxoMVprhinNQejnN/sj/l6f8rL05xR6iig0hjK0hBKVwRRSlBpQ+j59NowSWvi0CcIJGEgyHN7LzFCeG/fpQYNGrwfPkRDwFWfeZEJwmV7i/Pr6W2P9XetU2kVqzIWi2vVjrxr99mVMdTGEAU+gSfdmHel+WQzIfI9uonP0bTi0aDFt4czgshjVpQ86HWZlIrA9zjNXDHIl85ldJTXDOKQQdvpCRW1c2hT2jDOFIGU7A5zWoFPK3TuodNc0Qo8RmnNOK+YFQqvEyGtpVTGFTJaPt3Yo5o7KxS1IvEF1vr0WiGzQhF5Tn7gtvj3PtukG9+P/hE0BNK94WPT1rkvdv78YlPPq4vd2F+e5+HUdWtEt3REu+67zv/bKnE1LRVK21sTV3clgT50h9niuJRxn/uoH9OJA6r533dip8PhbCct2sLjgduYLSyyz2uK7E8KHnZj4tAjLRQvT1L+8GH3ndGD+8Z14yxq3hVUa8vxzLX8I6DfCpYbrzj0mZYFr0YpUkA3ceM2lTSo2lILS4lmuxcj5uKyqzoki3sMkFWK/VGB58HxrCQJJVjYGWZ8dzTjQT+hl3gcTi2biU839jlKS04mJXmpyaqawBMYbYkDSWUsG3NtkX/x1ZCiUtTWcDxNOZpqtLb0Y8Fpfj8JvRD3t+A3eD/cZl29zVqjrSWvFFmtl+LzvdhnVmgmeUXoe6y1AipleHma4iHwPHmnMembdFJJKXjcd50l07wmDCRrSYCU7wojX3aei9HbVZvc86Npt3GEW3S63E6U22Dnh7sqEB74rpuo0objacnRtOREVBcSUqHv9AwuWvMX555XipN5l+P+RLHRdk5fCLcePhzEHMxy9sYFT9YS/uzZgLLWTlvpHCG0Ggevu1ejrFp2rRlj2eiGdKz7jI1OSBz5TnPOuHgR+pKW7/HyJGO7ExKHksh3WkN1bYgij61OSC9u8Wbs9On2RjnaWMZZhQW6UUAYSFq+5CSrscZyMC15JNzo1mruk5WKvXHu9JLmnVKJ72EFbpR5nPP9SYrvweOBG3tz3Z4eay03GnA0LRHCjTcOs4pfvBqy1Y3oxyGlcWTN51tdAilRxhJIwd64IA4EgRR8dTDD8yQb3Qim8O1hyp886vHHT7p40vLbNylSgtGWtU7AaVZxOi151G/he4LIkwynBXnhcTAtiaREI/jqIGVnXKCsJVWWUVYhjKHfCol8CH0frQ2zUjEtNHKuXTUIfTxp2epFfJ0V90IgBQKSC0ZLGzRocHt8iIaAyz6znseVm+wtLoq13jVag9f9/nX5w8dEOAkLJ7OK2Je0Qp9iXmj6Yuvq3wulJJCSSe6IfqUNWIMvBKdpTTwfM2sFPtpaxpmiFQd0kojI8yiUIq+cDt+wUvRiSVpBK/TZG2Xsj0pO05KjSYnGcjJ1wqeHc03Ar46mhL4glB7bvRAjBFHgUyjN0STHWtjuRTzst0gLzSSvqYwAr2aWK4pasdWO2OjGoAvKsmQ+yXZjRMDztc6NnHpviibi3BN+F7V1rsNFi82HOpvrFrZaOw2QdugtRx1uS1y9Dwn0ITvMVo8r8Dw8IeYt+T5h4DaOaekY7Qe9mM1uRDv0qbTh1Wl25potnsFKKWpteb7ZxvcEO6cZD/yIfsuJvt0H+XVVYLmoQr/djTiYFEstp5896PBmmGOt5fmgzfGkWrrFFZVy88lCLsclfE8iETxaS+i3An6zP2VnmC/H3cC18b8Z5cvNZ6U0w7Rm0PI5mJTsj0raoUfgu5nlTGlCH4wVPOxFGG14tt5mWtYcj3N6rcB9hxBYI3i6HvNmVHKaFszK+SCyJ1C1pqhBa0vgQ20sngBj318D6eFm/J6f0OCHxm3XGmHhJD2bGOXK8BdPBxymJcJCpZwQc+gL4sBnox0uiRUruHGCd9NOqlbk85fP1+ZubSClXNrDL0hrOCtIXdWaVycpT/oJr4bZGZvcShu+2D5L+F8UNy9zhKuMObMGO8MAl4BH0ru0iBNKeWlx52RWzdcKeSUhtSCjlTFnOmv2xwWehKzWxL6k1pZng4Ta2mXnkzJOR8r3PJQyDJIAayzHs2o5HnZVh9VF98oYS1lr/mZnTBJI12JfKcaZ4outLoEn2ZmPmYNzgGxHIVjJ98cp+xNHCn222SYOfbSFB2vxW72nefVzb5TTinwCKUhLzVorwPMEaVXzzWHJnz/r02uFeHPS5tGczH/YjylqzS9eDZECsKCs4dvjGcF8HO5gUlIqw84wdW5qs5q/96jHwaTEWsusdF1IldLEgUdWKk7TYila6kt4MyenjtMK35f41nWVltowLVynaT8JkRLSUhMFHk8HMUI6g4Rf70/ZOUnJa0srkHSTAF8IytrFoUobJplCSoHSlu12QG0Fj/puDOJkVmCN5efbXX57MOHNuIS04vlWmxebbXZPC9KqZi0JCQOJtoa1VkAgLUVliDwo76HBdLvrEYjfv5GVBg1ugvsmOT5EQ8BlnwncaG9xWU7xdJDc6Fjvsv/52EbjrHDre1ZrssoJU2+0w2WR6DIoa0kiyc7rnHE+pRf7vNhsI6Qg8iVSuA5ppQ3//s/WSUuN73kcTgpmZUCVGUap6yKqdYVSME4rBknAv/k+ZZprBi2Prw4rZlmFxdIOfbQxpMqw0QqZFBopLL89mCKspTaw2Y05mRVgBXEUMCkUaVGTVgopJQfDCqUtgQfToqI8cgZCs9qRN7cZYws9KLR2pkH+/ZBIDYF0j/ihhN1+CFy1WG33IoZphdSu5W67F92J1Tyv83PVwlbUmqNpySyQBL5HP7n9o/s+JNB1AWX1XG6zmTt/XMZawsBZDWtryQrFMKvZ7kVY4EHPLeC1dg5J0bkq/fP11tJa2fckvhRuJMZA7PvueAVU5duN112w2jF1kUPU+Z9bBKD1dug6Enxnv4wQHIxLBq2Iz7bbnEwrhmmFJwV/9nTAJFf4vmSY1WRVhbHODeo4daJ2i3GKg0nBaeoIqINJyfONFr7nNplSCj5ZbxN4kmTuouZJQVYZ5HzmOS2cpejhpOCboxRjDcO8RghIAkGpNUepwZMWg2R/VDDO3AyzwmKME9QWAjwBVkqkNNh72By02933/5AGPyhuu9ZYARudkLR0iZEUgo1OSBL7fJYE1Nrw24MJs0KRhB5pWVJrw1oS8P2pW4tuk+DdtJOqFfl8ttVZxrSi1nw7nC27/jY64fI8i9rZx++MXFfJ8bTiZ9ttWuFcF2dS8snGu4T/RY4s5x3hFkQQQFEpDHAwLpxTylybKJwfz9HUEROL6+H78kZjtefv0cIxcppVjEsnZK6t5XE/IfDk8h4Hwoljt0LfJbW+RCtHQFhjeT3OaAc+D3oRu8Ocb49TEt/jyVqy7Ni5qMOqUpqd04xPNtoEKwnfYk3NyprdUcanm22MdV2baVViBWfOuVYuadxoR9TasN4JqI1hvRUQ+BKlzoqD55WmVoZ+7PPVYUoceAwSn81O6AoaScDB1Dl8jrLajdX5kvV2wIN+TGs+jvjt6QxPCNqxz+7QGRPUxvKwGzHKa47Tkum8uy70XdHkb3fHPBokPOq3OJwWS/I+iSXfHxccTRWhB+OwptQGZS37w4In6wndOCAtan7xashpWiGBJPLoxS6mbnVD1loBv3g5ptYF46xm5yTlZFbybL1NXmlenaa0fMHPH/UZZ4pZVRP7roPs9UmOBaSAh4OEg0lJO/Qpa4vCUilDO/RIfEiLkq8PDJ+uJzwYDNgZZhjAWjc6uTcqqbWl35ZUE/PeGkhxGBHe06agQYMPjfskfD4EyXFVQ8Bdj/2yzwy8ywscq7gsp7CCGzUv3DYn+Vh0fVfhCUES+nRif5n7a/Ouc+vqPQLmbrLwTz7fpFYub499jzdzA51JVlPWhqNZyVa3y0Y3dARNrXk0iDjNNKEn2BsVdBMfBKyZEG0EW52EyC/45jAjLRW9JCAQgmnlTCGmeU3oS8ZFSR14nExKtIDQ8xgkLSZpRRT7SGupauegipUkniArLdJCrV0BZFLouRkI1Le8djMNRW3vddS5IZDuGR9a2O2HgrYWrY0jNYw9s9g8HiT4wlVoF6MJ7yP6ttD5STrRpZXe07RiuxcyK1wy/GZU8PNH3VsRV+9TVbgqoCzHGGq1dKhJQv/Ggez8ca0lAXuVJi8UB7PyjOXz69OM0HeisKtEyer9CTxJJL2ltfbiWm63gvmsdU6l3t672wbbRWAxxjDO63ccoq4iBk/TCikF+3PtjVbo8XgQE/uSTzc78NDNKy9c2Fqhz/7YOSNYEbjNmy8xs7dOb8ZYDicZz9cTkiTgJC357njKs0EL6Qm8eTdB4Hts9CL2xoWrTltLJ/L565cjZvNN+zireNCLSCIPbQwvT3OSQKAMVJXiYAZP11pIAbkqqbXGGIG2BjsfxdOAVYbAcXXU3K5ScB69qOlA+l3DwhkrrxSR7y2T28vWGk8IksCnE/qIOfGg7QoRrWGY1kSh08CxWPbHObUyfL7VWerefIgEbxHTslItO0oWI3VH0xKBS7QOJgWnmRvj6iU+L4+dWP3TG7hDnY+bF621yjo9s51xweG05EEv4vlGG18KXp6ky1ggYNmlubgON3GJW7WnX6zp5bxLZaMT0IlCtlvBUiB6sW4v3MKK+Rpi55+rjaVQmr2hM0FYjCYejQs2uyG+1wYu7rAqas3xrGRWONvehauZUoadYUbkSeLAY5bXfLk75ulai07k48m3RFsceGx3I/ZGORudkP1JSaU0j9dafLHdZVopZoUirzXPN9pLcfBFcaIVxSgD2hisdTG51oZRURN5gk7kUyvDv3s1dILU1t3DT7aceDUCwsBdVyEE2hiwllYcMM1rauXiwVY34WhSOcc733XZtiKf5+FbEfK/ej3CWBi0fcZpzW/fTN1z9nyNJHbkUxx4nGQVk0Kx1Qn5/jTnOHWWyy82nbhpWWmU0eS5M2Kw4Lp+paTSNQILwqMd+WS1pUydpsV6J2SrGxF5krTWHE1K1lsBnz/scvT1MWVm8aUgiXzSvCTTHmFZ0Qp8jMiojSUtFFJApS15pcnqimlu35s8Atho+4gfSS6hQYPbYGGKggBf3n4MexUfkuS4KGbcVQR78W+hJy9sMrgJAXTV/iUILv7cm/7+RbgL4fShmydW92G1NRdeq/P3aKPjNByFEMShTxz6/PrNmH/xzQmlUhht+eJRlyQM6EWS376ZOifoeYw1VhAHkqOJ4mjmJFRC30kIeEDgCybZvCMKQVlraiHAGmpraEeCSVqjteUgzag0WOGcUYezkof9Fr4nSesK6VniyMMoGGUloxJinMtm6IOuwHiQ17fXQLJAUVfL/OA+0BBI94iPaVb0fVErw5tJcWazoIxdutgIKXjUjc8k6XCza3B+0V/o/ASeYFxcXOm1wIuNDoeTwomgaus28tcI064ey/uOGV62CVm4AqSlG2PIak0n9m8cyN45Lin5y+drIEB4gnYcLH/ucFrybF5tPU0r9sc5zzfaqHk32KpA9urxPu4n7E8KXp1kBJ5wxJMUFx7jefb+IrchNSePzjtEPe4nbwXAjaU2hiR0ArULTZJW6LE7LPDn5M7PH3SdleW8jdRHLsWvVwPuortLWM4EwlLNBfXmAX6a1/zr74d04zHbvZh//NnG3KXGBZyNbsS2iJgUannc3VgyKiwaGKYlBynEUhAI0FrQCj02OiFlbZlkFZ3IQxgXSPO6RgrJVstnTzkyNA4g8AQnU0vowfvoYG/2mmX6dw2Vdp0Gh9O5PX0v4sVG+9K1YHUNMOrixEgIwUYrWK6RlbastZyTIHxY4wZjLHujfNlRUlaKg0nBVjvi4VrCwcSRssbCo15MICVr7Yi8VG7jLJ2GzU0J/4u6kl6epM7Sfr2FEJY49FzXhYXDScnz9YQ49KmU5mBc8Mm5632VS9yqPf2rYUatnU3voBXyaG5N/6jnupnS8i1Rv/j9VuBxklZsdEK0ZdnN00sCXmy22D3NmNWax/0EFXgUtWVvlPF8vU2tnQj2YtSuUo48ssbSjnwiT7I/LpZk0O4oJwkd0fPzR11+e5C6ZDOr+O/+wdaZMbfDaUkSenSTgE7k8+1xynrLaVmNi9ptIM5fIyvmLjPOsWZnmLE7zBkkARJLJjRr7ZAvHnb47f6Mw0nJk0HMdi9mXDinvudrLTwh6IQeo7wmK2u0tTzsOYMEXwqnfYcTVu8nAb5nedJPlppQC9FwcCQWwnU8RYFEVgLf95gUNYN2QDXvsiorjRRQaMvjQeyIKm3IS41pWay19OKQVuwRegKtIS8VWVXTDn3WWwHGwqRUzLKStChpRwFf7U/oJSEq9Pl7D/vMKsUXD7qsz2L6ic+/+PqEV8MpldJ0kwiLAeNIs5fHKbW1xJ6H53lYq/E90LnFKJeEW95v1Nn3vR9Nb7NBg5tiUYTwhFjq6r0P4fOhzYvOSzHcRQT7Jh1Sl+0tbrN/ua554bb7n9sQTh/KXW4VF5Fwiz2BmZviuOaC/Ix+4tF84mBhwJSXNf/Vbw9ZbwVsdFocTQr+m69P+O98sUZeW0pjUcbyhw/alNpyMM4ZZTUnsxJvXhQuasNWJ6RQlsiXmHkHqsCSKct6KyKtNEngU1SG07xiXNQYDf22T+w77cFaCbb6MWutgLKO+fYoIy2ciUg6rzp7HkQBTDJXjJbq9t1HC6y3omvH/W6DZmdyT1h9gS6qgN4nPjRRtUg8H/djhvMOkzejgo1OSBS91Ys4mVW0198+QjdtJT2/6IeBx1o7YG9YzJ22vAsrvb4UPF1rUSqNtdC+orJ92bG875ihlALM3PHErJ6LU/ZfjDFIIaituXEguyyA+FKeqZADRL6zR340SHh1knE8LRjnio1O+I5A9iKoBJ7kySBBaXPG6v58sD1jg63deFrgyzPX0BNuLK6qDd3EJe9SCLRylesk9JYjGPvHBZEnSeZjLMoY0tzwZBDjeWKu/VLyoJdcKIK9+F7gzPvViX2mhaJUxnUOGOuuReocj56vt9jqxU6T5TTjH3+yQS/2+f5kRuwLKgVPBjHt0COvNK9Pc3whmBaKg7wkrzUPe07IvFAKT3qsxQHfzlIAamuIIp86K7HCMioUndijG/ucTirKGpRxTlb6PcfYZLNM/05hkWh2Yp9eywnha8s7YsnncdXaFHhyOTrcjX1UYPh0s0U8f6/OJ3j3HSO0tSBc5ey7oxnTQpFWNZ9vdnmy3uKT9TbGWE7S0n2/tWz3QqwVrLWdOP7jW3aqribE06JmZ5gTBe4aelKilCOpS+Ws3X1fXtq5cxniwOPpIOH7k5Rn6wm+lFRKczgp6W0Hrism8ChrjRW8k0Sv3rMvVsaXa23mZELAZtsRP7Vy8eDhICGvFNO85rcH0+X4mLKWh/2YndOMWaFoR844IZx3Gu2N3Pm3Io+yUhylFZ+st/mDbUdCHUwr/u7NhNNZxadbHdepuRJnmXcNf3+SMUxrtrsRn2118KUTyn4ycAWb1Y1DONeHeDyI+XSzg1KGl6cZW50Q35P0Yx/di3i23sb3JFnlnGhypecEakVROw0j35dU8+LPVjdkuxvzsBMzmhNZ7djnDx/3mJZOrNTzJL3Y58vdCdNCI6xEGAsWOonP51sttHZE/7R2xL1F0Is9RrkiLzVvpiXrLR/Pd+PcB2lNr+UzyxTdVkCvrGhFHV4eZyQBSCuIPZ/vD51WU+gHvBkVWKAXe/zli018T/B8I+H5epvIz9FW8dl2h5NZwTeHKbNCEQQenUhSG0EQCmLr86SfYIGTtJhrbPgITxFaN/Y8fY84kVd62b3doMHHCGMse+P8jCnKMHe6MnclfD6UedFF8fMuIthwvTzHAqvx7kPtX676/bsW3N9pCFgZvVbW3st44XV7gnqu2SfggskMw3YvplZuUmKUFtg5ETXOa4JAklY13x7nKCvoh5J24IMUZLniNNWczkpOs4rYF0wKwaNBi7VOxHYn4s20oNaa9STAl4KjrGKUO0OObhLw270Jwlq68+JWURtUrVnbaPPJwxZ/8XwdP/D5l98cUilFVimMNi5nBJSGrHBTDAbuTIsGQGnfkm33gWZncg9YfYGUgTejnJ1hzpO1hMd3GBG6Cu/jInbTRWeZ/MYByXwkaTpP8s4Lm54XFL1uoTRztxjgzKIfeR6P+jFJ7C+P8aJKr5m3LT4aXM6cr7b5L4iL1WN5nzHD89d/uxudGVso5sJu142srF6PM4v2JRXyUjmvlu2eG/OTOELt8SBGG8uL9fDaMRaXEHvL379Ix2lxD6WQHE7c6MXzjfby3xaf+3jgOpqOpwXTUtGNfA6UYaMT0k1cx5QylrRSfH+SLu/5djdiXGgGrYDvj1P0nKj62Vxc96LnaG+Uuwq9L1feL1dh3uxEnKYVzzdaTiOrrBnmFc83BgSewFo37rc3zvi3r0acpiVfHUz5YqsDMsITTlMFLJO85mRaEASSyJMoC6GEXhjgeZJCaQqtyQpNUkt86ZFVmk7k4ceQ1jXGCOJI4gnDScqtnRIuQqnuWm9o8EPDzMeWlHlrax6H/nItu27dWawBiw681WTuxUab0JNnXM2AdxK821gC3xRLcrdUDLMKKQSx7xN6zu3xk402zzfaWAv7E/fdD/sxL9adfs9tk93VddHMXRt97y0J58bFJKOsYpjWaGN5dZK6zhkpz3TuXFfdtsLFvHHhHPCEcILlpdIkob8cKS4rvRSIvqqzaeE+dzApGWYV272Y7W7k9ALb0dIxMw58ns27phYdXk8GCc/XWo64Wgha67dOcmYupn6c1bwZFfRin8jzSCvX2VnUmt8cTDiYFvz5k8FyvNACu8OMbuTzoBfz2nPaRqEvnTj7MJ8TRt5ZM4ZSobSLAb7nikdbvYhaW2qj8aRkY25jrLTBzsf5jqYlndink/h8dzgjDgSfrHfQWLR2Y/DtKCCQrttJaUOpnGOZmndkrbdDjmblvHCUsDPMEAJCKXjSj3kzLhimFe3Y5/l6i4eDhCdrLb4/nvGb/SO0NXRCwSAJGeUVj/sxu5McrLNwboc+P9vqkYTu2Zymiij0EbhCUKkUSShZ70a0Qo+0Fnx3NKPS8Nlmm71RzuvTlDejktgXdJOQB13FuKhAGPLSkviSUHoYI/nuZEZtwVpNoRS92Cfw3Kb0aPJ+UUJpQaE1jVpegx8Kty1SLDpGVk1R8ryG+F0Nm5tCSpeD7wydmcxdChXncdke6y4i2Ff922W5wHV7qfeVSbno9xfnrOex5nHfaZrehLBaJdZWCzjGWqx1xd67jBcuni+rrdvPBZLEd/u5NyOnRxf5EiklR9MCa+HZeovQr3gzynmx0V7ew4UL6HYvIg5c/vBqmJPXiqNhyrS2DGcFQRCwe1rRjXzeTJwu4YN+TFHVjHI4mdUcTStenab8+bN1aq05GJfkpeuIVtbiA4WFg3HJzqjgaFpgjMBgnRsnlsAXzHLNOKs5TEvKOqOu3b7bAJ4n8IVlaeS8wvncNVJYYDjNGgLpY8PiBZLCPchx4CGlwRP343a1wFULy+I4LnrJb0M6FbVmb578nqYVjwYJvhREvrdM9C6qdp/fNPmepKhqCqWJ5x0z57tbamWW3S2PB270ScDc8eTySu9lLZ6L4985zdgd5csKbhx499LWetH1P5yWy3GFduQtxyC04drxuLu0ti42h4sN43Yv5mha3miM5bqKwmogqLU5Mwpx/nNbkc9fPB3wi1dD1lsBUeAziH3252MbSlt++XoEWOJ2yOG0JPCcy43Wmt8c5G4UBVetnxaKjba9sMqTlo48C325bE+V0mlOLDRYOkngNEKsZTSt2Z/kBJ7rHHjST/iX35/SCjwqZdjsRHx7nLrFf1bRiwMC32MfOEorp0XTdpu7SaHoBJKdcYGU4AmPh/2Ag0nBLC9QFmodkIQ+xgg8KenEkrouqbgfAknpZjThdwGrSdj+pEDCUrvsNlXRq6qPLzba76x550e9Xp1md9aEWBBX4Ajnxe9U2lDWmv1pRaUMD3oxj9cSp42jXWdNHHg8W28hhEuaF52StzVYWBXoL2uNtZaT1I3LTnQ9J5EEf/CwwyirebHRwgCvT1P2RgWfbLZ5MO/cWRB3i27Ri+LjRQ54UjjNorR8O1J8EyJsESNCX/J8o+XI7tOczU5ENw4YZwqUYaMdLMfEwJHtqyTOZidilNXu+4VYjiDvj3PaoU9rzaMXeWAFuXKGC74nEDhnuTejnMNpyadbLbLSaSsN05o/e9on8j1nIVxr1yU6j2ndOMDYt4WChRmDJ1z7vzFuBCDwJM8HLYTnjuvlScr+pMBHsN2PlzHJ9ySzouY4eyuI/njQQkgn8r3Q6DPWIoSgNobx1GkjHaYF8eEUX7rnOFfu9zd7EeOsRhvwpeAfvlijk/i0Io+DScHDXjx/NmNeHme8HOaMMsWzNddlFkpJK/bpRK5LaqMT8M1RyrNBhx0yylLx7WnKz7e7vB5pYiEIpBNJDwT8+s2Ev3i+Ri/y+Jffn7J3mpFVeq6LIfn54wF/9eoUgaBEE/s+40xTqopZqXg8iPFFiLSu6m0R5JVG4SrLAXfTy5sU9Znx9QYNPiTuUsj2hNONWWsFZ01R3oPwKWrN62HGwfxYHvbeTy/yOvLmLiLYt+2Q+tBjeZedszauI2wRExaaptcRVgti7fzotS8Fu6OCXuvtnvCm57GqK3s0d+tc74Rsdtx+blrUGGNJAleYEUIwH4zgYd9NZkwLZ/DQi33+ameEJwS+L5iWbpT8q8OZG73PKzY7CXltGWUF652AJJBkpeblyYxO7LvO0Wntjt9Y2trj73bHvD6ZYXD3eDgrmdYaYQ2TXPHpRoujvCYJPE4mBa1YEnlOi7UVeNRW8+1pwaweMq0UkScpaks78DnNKtR8PRe4fYTFETaGu+8pitI0ItofGxYvUKk0WhuMcQnhon3uvl78yxaWtHLizZfNn960hXLxs9E8+d0f57w6yXi6llxb7T6/aZoVNW8mhXOEWXF4WT2OShkez9vmpRQ8nGvyXNYueV2LZzivOEeBdC+9sRxNSx7Mu4Tet631MmHxwH87k/vF1s1c2G5zX1bPO5Y3cyy67FyvqiisCv8GUs4X5reE3uK4jXB6Q1Ho8WSQEIXe8rNq6wRC9+YVgqfrLQ7GBXml6PRiCqXZn5ZugyEEW72Yp2st9CoZuBJwK+X6+pU2fHeccjwriXxHREkpMPPzXfz8w27EN4lHWhoCz9JvhXRaASe5E787nBRoC4eTgsdrCRutkMdrCVmtEMKN08WBx88fdtmflOTK0Akln291EBi0tuyMMia5IhCgLCilsYGkVjUnJUj7Vs/ifckjgHbU2DP/kLjL+Nfq+5yEAY8E7I0LHvJWKBQ401V03eecd79crCvnCZnV9aHW5trk8/z5Lf67Vk6k/7xu02Jd7SUBn2+2eTPJ8aVbY8r5fKawb0ef25G/XIuuI68uOpaFQP8wq9g9detIP/GZlI4o6UQeQgiGs4rDmes+jAOPTzc6bjyqHToyeb421MqwO9dlu2izc5ED3sNBvNTYu6ujpu/Bi40206LmxYZzgVyQc7Uy/NXOaO4yKShKTeDLJYkzyuoz91xKwVbXubgJ4c7r8+0eVeUKN0dpyfG05PVpxvG0ZLMbEUjYOSl42I94OmizG+QMs4rAl5SVZn9aUGuDtYKfPegsn6PF87IoWLgOzopSazzc9dubFMv4HAXeUidqMTJ4ROlc4sYZp9MSIQWns4paGZ6tt98RflXKsPPSdZl9d5Iyzip2hznbvYhZXrPZj4l9j6x2ndHb3YhjKSg1zMYFk6zmeFbxoB9xMqvIq9rpPiUex+OKk6x0I43rbZLQ43haoq3lYFKSlorBWsB6O+TYWPpxyIO1hGmp2Bs5fcN+EhL5kmFW8ps3U756M+Fv30yJQknoScraMM0rHg4iXmwkrLcCXo0KTmc1oQ9V5SrT1lhEYGm3AsZ5gTIWVbsNggdEEqo7BA1twdxaVrVBg9vjrsLVqwTMqinKRe69Nz2ON6OcYVrRm3e9LzTYzuvf3RTXkTeX5c9XFWYv+je4PBe4qNNJzM9XWXNrl+ebnLOejxP6UhAnIdP5yPRnW51rv2dxX98ZvZ7LemRFTSsOlqYVN5nKWNWVTQKn16e14XhW0ot9jqZuvzspFA/6MXbe7eQJp633ZC3hySBBWPjqeIo2ml47ZlZUfH04I6sUTwYxWVkTeiGBL/E92BuXrLVDhCf5+eMWlXL6u6+HGZ50bp6jWcmsrACLJWSS1aS1Qmu3htdY0rLm1SinVJbID+i3IyprKbUhCSVR6KOUpTYVL09rsJZBK2JW1tTGUFZndY5C3H8r7r6n0EAY+PeqldcQSPeAxQv03dGMb45T0qJmrR2htOFBP7m3G3bRwgJwPC3PiIatLua3YbPPJ7/PN5wLyuNBQjRPuC+rdq9umh4Yy8H0rHvY3tiJb692KJVzq+PFAnXT+d7LAthWOyStagaxY6oXrZRlK7hWcPsmuEhYXMw7sDzvdpX2q1zubjrmssBthcEvqyicF/4dtHxCz1Xxy0ojPcHuKF+O7nnze7faNZYEPg+6bsyuFfnI+b/V2t2z06mkVortbsSDXoTvy7mDj2tV1d5bAdpJXnKSVqy1nR6WZD4mWGvyWjsBPeCPHvWYFIpSKcra8GStReRLrIEHgwSjDK+F4GCcUVYuAEeBR1bUjAvFdi9i97QgCTz+0Wcb7JykfHc8oxsH/MFWh91xzqvhjLxUSE/Q8iSp5yE9Sagsaa2ZFiVJ5DbSuXYL/X2h1RBIPxjuUllddGBqbYh8n1obWqHPo17sXA59j0obXp1mt9aH8z3JJC/5/jRFztf/q45pOWpWKcLAeydpW3SYLmLIejtklLnkbHecIyzLEdRhWhF6rlPEWOd6+HCQoKzrljmeFPi+h25ZduZOX7epnF50rT0plgL9wkISelRaczIraUUu6Zrkis1OSCcJGBX1sl0d4arZVohl1+JaErAzykh8751x5sX1ttqNSW+1PTxfLh3wVjuwrrv/i5h1PkYvxioWnxVJ56T2elo4O/vCCTgfTEv+0Yv1MyTOwlRggXbo83QtQQiWzn428HjSdR1Y//rlkINhThy66z/MlBPMFgLPl/PxrpSXx2587R+9WMdYy97IxTTgDOn2elKwO8wJPMGTQczeOMeTgkE7XI7cCdwYQTvyz3Tk1tqNkf9mf8pmJ6YVzcXOpxV//mztHeFXYywYy/6k5HCS891xRq01vcRnVhmiXPH0cYI2IcfTkjiQy5HjKPT4alohETwaRJxMS44mOZ4v5wS/IQ5iWpGHEJbjuaiqlJBWilFeY7Sh2wopa82DXgwG/uxJHyEEVmuk9BgXFd8cZfx6f0on9DmaZHi+zx8/7uFJN6Z6NC5YbyeMK0M7CHhVZIS+R61qhOcxLSsiEzCapZykjvDRuES8Bso77g4CIVC6IZAafHi8T4fM+2r4rK61C/kDKd9Ka1TaLDtiP5Sm0kX581XnddEUwVW5wPlOp4UW6bfHszu5PF9XEPOEwAqolCZOnGNZGEjnKHzD6xgHHp/MY/Bi9Dotaoy17IwKpHBx4cXm9cTeO7qyUcCathgLWV4zLWpn0uBJ9seuw3erEyKkIK/1cqLFAl8fTfnrnRHTQrHdqfDm45NprTEajmY1UShIiwprPeraYuZuobNc0Qp9/mC7w+ujlNdZjjaaaWHwfMvuuKBbur2IDyAFp3lNN3Eje7VSzApDKms6YcDjfkzsCcpaMUorpASBXI6CT/MaY2CSv2uoYHDklJj/7y5yeYkPL7YSt+e6JzQE0j0h9CShL3nYi8gTHywMs5qt7v1ZcF/UQrnVjZbt4vDuYn4bO+l3kl/zNvldPYbz1W4p5JlN02YvQsi37mG+JxGVvnQE7vw5XrdgLVzAvLngqe9JxrOSb4+nHE/dpuePnvTY7kb044BP1tvv/dJcJCz+8iTjUT9ekiq30Rq5iIzypLwT2fi+QRkuF/7d7kTsjXNO0oookDzs+2ht+MWrIY96McpYqvlYw2onWBz4BJ7kJK3IK6ctstYJmGUa6Xmst0KElIyzylWAk4B/9fKUjU5I7HsMWk6c+8WcCJ1kCt8TPBy0+M3+lFppvHlVflIong4StHWz0t35c3cyqzjZGbPWCfn7T/v8v399QBxKxoUTHN+bFLxYb3GaKYpao7SlHXu0Ip+dYYEnLb/ar52FeaU4nhbktQWr3GiOkMhAzkdBwHNcGJEPRt1P9xGArpuNwQ+Bu1RWV8etXg8zPMFS02at7Z5luJmQ5kX6cJXSnKQVL9Zb12qcwcqo2cpI0SJpM8by8jhlNO/G09rw/XHKFw86882AZVjUSwJJwLJjZhEXFmvNZivESmgH/vK4FuOkN+mGvKrTyhhLViq6ievGwboNwnYnotLWjUBJeWG7+qJjKq0UO6cZf3WScjQtebKWLLtjVrt289r92Yk8ZqVmoxOSBP6N3TkvIsGuIvTPj1hvtkNkL8IaUMY5aZ6P0atjhQ96MYfTcpkoL2LO40HCZitA1ZpcaSeYbTRauBTPEwKLZaMdzJ9NF6M9IdjohhSVJq80gSeX3+EJiALXYXM4czmGnBdMFqPFjiCTy4Q/r2v2xjmdyOdnmx2OZ04f6PEgwWinPXRRjAw8yaAT8HdvRoxzhbGGB92EstL40tJLPLY6Eaepoh0HfH3oyKnjScnTtZg4DNjuBfzr70fklbNbBsN6O2G7F9OOfNJC86gvGKaVIyZrQxJ5POgmzPKSvHQafr70KLXh66OUyIdX44pOKJnkCiEshbJUqqQwFp3VHEwrNuYFkXFeYqVwHdjDgtoY1sKAkxrKSjHJYK1jOE0tEijm578gke4aM2a1IbjHynKDny5uQji8j3D1dTm+UobKGEIpz+TtF+mPBvN9yqKYbufr0E2O5aLzvKlw9HXndZEg9W20YhdxttaG3VFOIAUH0/LWLs83KYhJOR+RHhdM83rpjidvuR/xfcnTtZb7nKJeHp/Tk3PGR9cZicDb52tVVzYJPTbbIVnt8v7F3nLR5LDo8F1tbvj+JOV4WlIpp8v328MU3xOAIQk99kduIkYiiAVkFSShK4yEacnDvuGf/vFDHvUTtgcRtTUcTEqm2YzhTNOLBXXtHNm0NnTjkE7kClVV7cgjg8Wzzul0lJYUtaGuobaKthcS+YI8twTCoKykH3uMc4PGjTMvRLMXchih4K0u0i2x3Q34g4f9W0sKXIWGQLonaGvRxtKJAza78bIq7c27gO5rdjX0JI/mLZCLB+GY8lKC6DZ20rddPBduM4eTYrlBWWuHtAOfoazPBBjPezvGdtuF+TxqZXh9kjHOK6SUdEOfg1nBZ5tt+tshe8OcX74e8ZfP1ni63roXxnXBiieRv3S3eXmckYTzBWPFeeC677uIjNobFfzZ0/6tj2s1UL3PwnC+qhSHvgsCU6fnEYeeG2WZ5G6TKyxR6BEaS640j3oxUeC907a70XKLZD8OaMceuzon8AVprQkrCUbwbCuZE39uLMVi+fpI40vJpxttNwbpuWct8iVriY+QIU8GyVLnxAq3yRVCsN2N+XJvjNaG07yk2/I5mFX8+59vcjQraXker8c5r45nrHdilFZs9yOsseyNSw7HOe3Io9JuU5eXmqLWdJKAVmQIpU9aw8k4J1WgDQgJee1G2oS5P/IIwDT7gh8Et62sriaDke9ag4dZxYPAQwiWwoc3+dzVzqDFOFngu+R4oxNeqnG2+v6Ds7of5zVJ6JJTY+0yaavnHSLd2J9r1CleD3O+eNBZijrno4LXpxlSQK0tvSQ4Y2KwWLsfr7cu0F4zbHbdCFGp1NKN9Pw103M9nYuuSa4c2bw/KTielQxaIV4AB7MSZS2P1xIOJ4Xr+pyTIg/6Ec8GreX6Y4zrMhnnNYMkoFCG01nlhMd7MQKcta+AcVY7O3cLz9YTamV5OnBVuus2UldtBi4i9Jcj4isj1sdpxSD20RbeDAuQ5TJGg3Of2z3N5oSIi9/P1lpn9JiUMuzPCak/etTjaFYzSktqKfl0vU13LiL9ZuR0Lg4nJVJang6cwHk78ghCdzx25XlNQg9vfuzCQm3MspNKaYM2lpOZEzFfbDrs/JrJ0OlGeEKwM0pR2rLZjZaaIeevY62drlYnCdmea18JAVltiAPJMK2ZVYpSaQQGZTTbnRA7z3cOJhlSWIq5VkZVaw4nBXujbB67HGE6SmuEECS+e159KdnseHzxoM1p6sYi6trw7XGKsJbvjjNCKdgZ5XhCOjFWarSRBBI8H7QxSGOQwhGbtdLUxlIaN35xMC0olaVS0I9AzpXxzj9RCx0kye0rzL1I0EjlNXhf3JRwuCvJch1GWcWXu2O0cZv+P3nSZ9AKL9UffdBzMhqHk/n+phvdSFPpqvN834LsVZ99mxxDSoGcuycIKS51eb5M3+82BbFW5POXz9fYG+UgQMp3zSKuwiJWhp4bSy6UmxDozIme5JZGIg/7MW9GOZEvGWc16+2A2lieDVocp9WFTQ7nmxvqWjMqarZ7ESepGzkbpjXdyGOjHTGcuUmhcVZQa0taV/STiEE7Ig6cucO/+OaEk7TEGEEvDpmWiodrCeVJhvQCppXG8wXbnRbtUHKSKYpS4Qce/ZYkrzSgGecVWaFoJz7r3RijA7KyptYCoxUpkq7nxt86EWTKuTevxoEA8DzuNN4QA3/0aMDfezS4t9FHaAike8NiA79aRRZwYzb8JrjMyvAyguiyrhJ/TvxctDgubI0vqgCcx4L518bNn4KbKboswMSBx/PAe+9OmYNJgee5zh0LHKY5tbLEoY8UghebbY6mBQ/uwX1oAW/e1n80LZzgp9ZU2hD5Z50HbmIdvQgi7bnLXVYqdoY5B5OCYVbfuJPpro58l53fO+ORzrnbieEKp/G1NypQWhMHPlttxbRUTugVwdP1FrE8G4RrbVDKEHmuO6Oq5+MpQmClI5/2x04TKQk8TqclSeSh58/W0bTkxXqLvNYobZjkNYfzNt6DaXlh55Y2hkHic5IqNrsR620nvHoydU6CuxOn2fX5wx79xGd3WFAbxfGsIs8rQJCEHjvDjKI2+J6lE4YU2jDKakJp0AY6iUDlFt+DooZc3a219Dpk+X0OxDW4DLetrJ4XnY9DjwdBzKNeTBh4rvPOntX1klJQ1Xr5fcA7nUHWWvpxwJNBMt+A5xce0/n3f60VcDh5SxApbTieVXymDdH8vTTWug2vdFUxIVgKN68nAd/iki/fF6y3XAeQMfadpBouLly0Q5/2uk9aKY7mWmcnonrHdlfgCgHKf3ccu5cE/KMX6+yMM6yCR+sJf+9Jn2mhsBYGSQgCRnm1bOk/mJZu/ZPemdGGwPfY7kbsjlyX0no75EEv5tVJyjCvOJyUdKKAVujhS4mWbsT1wmr3Cmlz3jhiYaGujFk6h142Ip74/nLEepLXZKVybmwLx7U5Mfj9KOX1acYwrXg4H/c9nhUI4LPNjtNKyisOJwUvh67aKoQj+x/0Y/7ocZ8/fTIA3PhD5EsMkFWaUebi1acbbWal5OcPw6U70rKTTBkGScDhpEAZ2Ow4MnCa1y52C9jqhowLRVlrXuY1292I07TmNHVi68YahBXkWlHrgGfnRsmLWvPyJHUbQGMZtAKkgPV2xK93J/TigLV2wCAOOJrWrLd8pPCZ5MoZNyQWKWFduup0rQyVsjxbjxkXNbEv2e6EjPKaUVbz88ddXsQB3x2nfHec8rAfMmjFhB6UtcYDNrohB9OCvNJEnmS9EzOrFCeTkkIpRrnFak0QCNqhoNLuHLLKkERuhNuXHp3Qp1aKduwT1ppCGKT0XPcskF2wpoS44sOt44h0roMNGtwVi7FUT7jR4fPOu6u4j67381DK8OXumNiXxHMzgy93x/zjTzew4mI3s8CXfLHddeNT3Gzs+Dpi5S4aiDf97NvmGBd146y6PF+l73fbglgr8vlsq3PluV/UHXbhPsT38Obnt3qewl6vA7nAwmVtbW44AbiCSytglNUXkperzm2KuUxI6CGAB/0Wjwaa18c5UgrCwGOjbTgcG4QLZ5RKsTM2bLYDEt8VTI4nJdNCUdQ1Wmtc/dxgdU1RGYSSHNUF3iDhxUay1ASujTsJYyVCCDxfg5CEUlJhyGpLV0r6ScysLDme1cQeSA8C6wiklTokNVDccSvwqO/2Z23/fimfhkC6J0gpeDRI7sSGX4dFhW5vzsietzc/TxAtKs4XdZWcpiXfn6SOrb2AdHBkxllLzItIiaLW7Awz3oxz0krTjX1i30PZt448FwWYm4yoXYXF5iAOfAZJNBdpC3g1ysiKmk7iqo+R7y3HR+4Nwo0oucXGbcAqpTlOK4w2RIEkEII3o/yMOPh5nN9QLoWhz7ng3JcI901wEem3cMYz1nVB/PLVyLkrBT6Dts9vD6Y87EV0Yp/AE7w6Tc90AlTa8PI45XDqNiunmbPa7CUhz9Ziitrwd8Mp2rhui2lR8uWbMT/b7uJ7El/CeFYwaPvMck0r9DhJK/7wQYdCW6ratff+6eM+9ZzIrLXh5fGMX+1PUUrRb0fUyjAtFS822vxsu0de1Hx3kvF0Peabg4xSOXHYftvjq4MKZTVl5VMoTV1r8tIwyjSeAG0NtRFo4zqPKg2VYk6gfhgYvxlh+yFwlw7MxXu8cKMUgne0hxafu3gXwBH9lTbE0ruwM2hnmPFsrUWUBJeKcJ5//w+mBfaKB1HPu35enc61bBKfP3zYxTLXDJKCP33Sp5cEFLVmlDth4ihIl6T4asfUVYWLk1k1j1XyTKxa1eqrtLNuL5V5Zxzb9ySfb3YZ5xUPezGt0GejHS3jiTGW709SXmy0lsTHYv1bLeYs7s1WJ2KjHfHJepui1vx6f4onICs1EkcCKJMsk9zVa5sW9XJk1/PkMoGtlWZ3nLPRDsgqt/4oY9maO65dJI4Kb/WptrsR7TlpNCkUw6yeXyP3TEW+JPBcCvn1UUo38TmeVkwHiklRcTqtOM1rwHI8qwilG2/oJx6+5/PFdhffd+PlpdIczUqGWUWhFINOiNVwmtVYoKxbTmNrfsyd2OdXbyYu2ZeCP37cpx36HEyc8HZRKQ4mFd3ERwBbnYi9cUEn8unEAa9PUv7tyxMs0I4CykpT1GbZ0WSMJS8V35/MGBU17chfisQKBMYa/uBJj8f9hFBI2olzjdueC4kXShNVrqvpYJyz2QkJPXf+u6cZYykJpYvVx2lF4As2uyFfH2Rs9ULSSs8J15pf703Yn1Vsd0K0FTxfTygqwzgr0UZwPMkZp4ppWaM0xJ5A+oLAF/ST0I2hJwHGlpSV5jQt2WyHrLVCJrlllGsqZYkCSaUtnpS0E02Wv/uOlteuUhdjs+30GBs0uCvSSrE7zIkCiScFmx2XX19GOLxvLn8elXFraBy6bWkc+qRVSWWMc3K+hHhZaMvdBKt6hRcR/1VtblWUPU82XUfa3DbHWP358y7PFxkTvQ9ZdR3Od4f90aMe7chfOiOfP4aH/Zi9UU5aqqXe4s4ov/barpo5JaHHq5MUa11R4TKDCTjr3HYyq2iFbr09mhSklWY9CehEMb6UzHKF1pb/+qsZldYY4WQnhNXEEUyymkNdsdmNGWUl7TDgeKqJA8neqCCOIqZF6ZzRrHGd2NKNJYdSECYRiSfYOc2Ylop+EuDLAG0MldFMcgXCIIRzjhZ4xIEjpoQxSPN2rFlzx6LCCh6vdVlvB5TWcH+iOg2BdK+IA+9WbPhNmO7FS1EpzcGk5PlGC987a2++cDGIz7UJvuNoVWtOZtUy6T4/dpWVin/57clyNGytFVArwxcPuhe3RgpBXrl5nb2hW+DejAterLUJEnnvAQbOdXrNF3/PF/y9R13GueJkVi5bX+9TLGxRVV610R5lFXmtOZkW5JVhrR2wO8rJlKaeV/WvawGuSkWlLM83WmcEVK8am7lqBOR9xiUvIv0Wzni1Mqy3Q56suU3W4bQgrQo0Ef3IZ2eUszvM2TnNeNiLeb7e5nBWMsor2pHHrKxphT4g2OoE7IwKNtsBD7oRnieY5TUnmbPSDjxJK/D47iQl8OHbw5StbkxaOae0bO7eV1aab45m/NXOCB/nALfVDsgqTS/y+MXhhAe1E9192ItIS02a13x97Fx+9scFlTZ0o4DjtERbZzM7TmumeU4r9kjaPqquyBV0QsEoh6xWBPOExReuQjA1bwXuFnfbcj8dSYFtKss/FG5TWV19j401rLVDsJBX+p3EcKGR92w9WXbsrIo5g9NvGM4Kvj1OmZUKz5P8/edrDFrhO8d0kduah2CjEzIrFZU2WGvP6EQczrv5OlFFUWsEgs+3usTzrlBhYWfkdrWTQiEstCPX2bB6rLU2vBnlFxYuLkvQK+WuySJW+Z57z5/MCyyrjpJVrRFSkOU1h9MSYcHz5RnHHm2dE2Tov7v+eUKw2Y0olOZ4Oh/96kY8nxNc+9OCjU5AWTvC5zQtebo2H19bT85Uu421DPMaKSAKPayxfLk75mEvYlIqykrx//jmmKfrLULpMWj7/PXOeOlcurr2LxzNdlcKTE/XWvzVzojYd5u2vWFOVim2ezHPN1pYLKdZjScE01zhS8Eor3l1mgIQ+B5GG2aFI8ilJ/B9yeebbswN3PjZMHNOL7501dDdYcHPtttEoSSvXOX/4SBBAL3Y3dPAEwTSx2DZH+e0Ap849IgDj++PS6ZFzVrbiXQfzInEMHAbvQeDiGFas96J8IQgrTTfHk9RagsL/HZ/wq/eTNmf5EiB60zy3Pm3fI+tXsRmK+JRL2JWuY1P6Hu0o4DNriH04d++HOErwbONNp9uJOxPS749mDpbZWPwfMkgDlhvhcSh5OujDGOcVp3SeinUPq0MutbsnBb0W5Jfvq6IQ8HhpCQQThC205LUNiAODE8GLZTWZNqS5yWVETwZ+AjpIaXr+lPasNbysQbqWqEsGO06tfu+B1Iyyl3X3WKjUN1inVpFBG4daOoMDe6Ixdhv4IllAXp/nLPVje/VtekqhNKtgUWllh1InhSEUt5pbO78/mpVr3B/UrCuNLkyVLUjjx52Y0c237Aoe5kT9HWkzW27t1Z/ftXleaEFG8zj1PuSVVdNNJzvDpvkJf+f3xzyRw+7HKf1mX3pQvi71gY7n8axxnIwn4a57tquknBKG4RwndKLPdhFBhPnndsizxn3/MWz/jyfSvnN/pR+20dpsNbw13sjTqc5tXF5fGWgqsEPBEEAKFekUtpgtEEheNwPqY2lG3so7aO0Qi3GDK1kWijCMCDxPHKlOS0U0nq0ghBjFaNCczwukMJpO3qeYJJpAs/DF7DeCvnuJCNTbjkPOOvGdlfsnM7YGfeW9+O+0BBI94jFgnWTNsrrxo8WXUcLdjfyA07Tiv1xzvON9lLIUnC5aOn5BcRYy0bbtaqfH7t63E/YGWaM8pp+EmKxzEqFsQWfbLbPMPyLFzz0Jf3E59Uwp9KGjTAi8V2C/lnk3+us5QKXdXq92GzjC3Gj0bu7YEHGmfn9VdqQhD6DxOeXOyNizyNXhqxwYyjth66iujPMLhTxXh3xCjyJP79WV1UJVp+Zi0ZAbtsiehGkFMuZasy7xxnOuwq2iUhLxVYr5CirOJq45COvNL85mHE4LVlbqYoaY4kCj3bgoYG0dELWG52IrHIbxrVWyCAO6LR8Z/msLXHgNprjrERpw8lUMC1qWr7kOK2YFYonawkAO8dTvjlwnRRpoUnm7leyVAwzyUYn5O/2J8S+Rz8J2RtnnM4qNroBfmpJK8NmJ6Coamal5nEvopcE7I8lXlGx3U/IdIaUPhLBSWapNCz4usXSfN8DZ+pDtjc1eAc3Ib5XZ/5XR34XVcjz75+2Tl+mNa+urhLFgScZtHx+ezDjq4MpnhB8vt2mHXrLFn7fPzsSdVF10fMknw4S9ifF8u8XHbALwmkxNmuMJa3U8tldkEwbnZA3o5xZ4YQrN1qB62Kp9FJ4erWYEXsuoZzlNaO8YphWy46q9VqRVk6cXlvXmXM+Vp2PlYNWwJe7Y7Kq5rvjlCeDhHFe00089scFf/l8jVbkX2p1nJWK07TCArHv8WdP+8TBW42EWhuExblLFhVJ4GGxPOzFy0LKontsMVZX1a4YIKx7F0vthM0DT2IQdCKfvKgppCKvNZ9tOg2s82MR+/MOnd52sBQVDXy3Ls0Kxd7c8exRP0EZw5c7Y7qJT1458WbfcwWJNFcInJBorQzjUjnSPRK0w4hKa0a5Ym+U82iQOLOBToQUgpN0jC8FoRQkvgdW8KAbM8qdE58Faq0ZZq5qqq0jHl+dZGz3Iz7f6LhOXGPpxB5ZrQjnTqKbc3e2yhhenaZOMLtUbpxhbrRRG8ObYcG3RzPakTOP+PpghtKGzW5MXimkAGUseaX4m72a9SQkiT2e9ltklVp2vX221aGqDa3YY5gr3gxzPM/jUT9hlNck880EsxxtoB0K8ATKOkefOBAoI/Al5LVmVhpy5QpngoC/eDJgf5wTBR5FbfjDRy0ORgVSwu6wptbaCc3aiv2Joajs3CnRzS4czSpKYwmjAN9YilJhgFxZhBSEHhjtNgh3JY8W8IVddnc1aHBbLOLTo0HC0bzrvFKWrW70QfL4i+D7kj950ufL3TFp9W4h+DbEy0UjyItunSQMwFp+uTNmuxMSBB4PWxH7Uydpn4TOaMACWl/s6HbVBMCH0Ie6KCcpSj0nTcSlwtfnNXMvO47rJhpWu8OMdbky1hIEEiktu8OMT+dj1bV2hiJvTnOQlod95xx6OC3ptVZduN8teJ83EpHSjfRb63Key/ZHq85tWVmTVk631NgYpc1yvLioYZSVfH80xShNGErQllpbpAXrQyeCtKhRCnZHGUK7DqDNbsi00KRFPc8/wFiBD3gCZqWiE4Y8WU94eexG5luem9aorSGrFKEUVNYdjwVsaihKy9RAryUZZ66LyZv/74Im1TvhcGoIsRzOSnpJeG/vdEMg3RNuo0dz3ct6UddRHEgeDRJeHqcMZyVJ6PN44DbOVy1Wq4vuosJcKUceWWOXFeaFgOsiCfGlpDB6WUFexepcbuh79CKfoO20BiyOxLiuE+Y2c8bnf/aqTi9nHH8z3EQk9Uw3zrnAsN2N2BlmbLZDlIai0pzmJV9s9yhqzTCrXZeYxekDXdCJFEmPBz1nkSwqjee9K153nkxcPDOF0k5/SAp86UYrbtIiehUue44j6fFo4OZ7J0XJyaxivR3y3XHG3sRpBbnNT4vEA7AcTEtCIUjnoy7Wwh886PCkn2AUPOrE7E0LdKGcnpW19OKAOJSUlebpWswkrzmY5HxzlPH5ZgtjYVLU7I2KZeUAaQk9j+HMjYB0ooDd4UIMUBAEkrxWvD7JSGvNejsmCSSdMMDvuc3n61GOsbDRjpkVitfDgtejjDANyIuSSgv6HYM1bpPqbKdd4BCc1a64b7pn4SrX4IfDVWvD6juysNgNfHnpO3eRu9r5RCj0PLqhRBtDGPkM85pn62Le8mzeWdeu1Jlba50htBakySrhkteKw0mJhzgzlmXm59yNPcracDQr0ZOctSTkaOo0CaIgYJhVvBnlvNhok1WK3XHOd/POqfVOSFbU/PL1kEf9mCjw+XyzjRSCamVk7aJ1bpTVPFtLeD20POhEjHLFZjukUhCGsDfK+Wyrszz/RYu8tk5/7693xm4dGiT4UjDMap6vvx0nWwpPz5NTMyeTAv+tAcCZDlHtdHV6ic+bSUFZK46nJbIDa21Hoh+nlevOCQRx4EamPtvqUq5sPrSd6zHMO8YWoqIASeBisNKGaN4NVtYCYxWxdHG/F3lEoQfWCaz7ypFS2/2Io2lB4EuscTbGgS94vtEi9OXS2S4JfV7EPg96Tg9qb1Sw3gl40m9xktZseW+dgo5mFbWxdIzHwbTEA+JQYpXhFy+HtBLJL1+NaUUez9bafLbZYqvT4kEvZn9SsDvMEQg+2WiBAGUN/SQg8EKkEEzziqNZRS92Halx6DEtNZKCdhTgeU6fIvA9pHCadkpJXp5m1Eoj58WGfhLw/ckMYyHynH5WrS1PNhImecWbUcajXoso8Pn6YEYr8vmD7ZCfbbWptOFvXk84mma8GVfUymKFy5FOZjW9BDwMnThgrRMCLsZmSc20ULQDiQgFaW2ZTgy1UVQKtALfB6wiDj2UsrQCgRd6eFhXHQ8kWa3wPVf1Du37EUhJAIN22DQgNbgzFjm9LwVPBsmS4G6HP+wWcdAK+cefblxaCF4lUlbdKVf3ABftr/bGbiuehG9FnduhxFjX+TsqFEkgiXyPWVEzzGoq5fRuHs3lKBaffd0EwHVE131oly46ih/1Y4ZZTVlr9irNXz5fWxYs0srFKgtvv0eebVJYHON1o3c+zrAiK53baV46p8+TWYW1gjfjgm7s04kCsI54O5wVTEvNr/dnfL7tmh6qWhOH/oVE0Pm8amEk0ptLe6SVwr9E3NtqS1EpZrnhq8PU5eUCerHHd0cZrUDSjkO+OphwPC2dKUOpGE4N1XzhlIBvYX+i0Mq5KUug0KAMTjBbOl1FXxh6ccAkV7hLKgmliwelcvmg0o7U78YhpTIEvsIXThtJabf25+VbveS8MlhToRZuCvasBtL7QFv41f6UUVqiNzv3NhnUEEj3gNvq0Vz1smLe6i+cT9QX7XyLKnetDe3Qv1b0etlVghtp2JtXmNuRz1Y3Igycba0/r4TPCj2vRNoLXVNWE+xu7LM7svQCD4u4UNT4slbSmyygl/3sRXPPtyGlFp+rtRNNXR2PuHTxPRcY0krxZuwWSYFjqLWxCCwnaYXEaUlEgbz0eShqvayoWlw3VTzXUFm4MR1Oy3dGGJWxHE8rtrohEsFmO7xV++1FuO45XgisL7RHfE+6KnPh0Y8DxoVmmFXEoUelBaGEvVmN5wk6sY+w7nxrbfmTp31Oswql3SZoLQ7wfMnOaU438llrh5j59RtlFd1IooxFGZBC83S9xfG0YH9cYrCsJSGldq2loecq5FiB1QbwOZmUrLdDtqKIOBRMMoWQrvPrYT9B2jF7wylZKyGvFd3YY5bXbEhBpQWRFBxPSiecpwyJ766ptlDWjjgKBC4hudHVvjkGSXjPn9jgKly1Pq2+I1JIDicFQrDsCj3/zl2WFK0SKLU2btMc+YSBTyDcePJ3xymP+gmhvJgUvyhRvYrcWpBEee0sdh/1YzpxQKU0X+6OeTZICH2JVoZxrrDWMk4raixpoXiy1qIduWrmw37Cq7kT5vG0Yi3x+WaW4XuC749TqloxzRV//3lCK/DJlaGfeMuOqIvW6NXOVt+TRKHPaV64hLXWSM8HcbY4IXDjZsfTiq1OgC8FkS85mpY8GSQY+24Fud8K2DkRrLVDBLDdi7Hnih7xXKNob5yz3g749f6UzXZIJwn448c9frM/Q3puNGyrE1Fr45zS5iLfs7ImCvxlHKyV4c2kANwY2UYnJPC8pcPd7mlGodxmaLsXczAueNiLeNxPeLzW4uujGVnpDAjqWjFohWhtmBXOdOHnD7sEUvKbgylbnZhRVrPZcW6hVrAk26yF7U5ML3ZdT/uTEqWdEUAncJX30JMUdcW3xynDtCLyPR70Ioa54mhaMDtU9Fs+ke8jLXx1mPJP/17H6aa0QyZ5RVpatroxb8Y5oe/E1X/+sEvse0wKjS9BCEHou4LTehKw2Y2YFho776Atlaacd649W28xzSp+uZsRBR61sURSzLuQK7a7IYN2yHjeiTQtNbUSrHVCDsYlSShpeRJPSH6zn/KzB23+4adr/OtvYZxVHFpNUThjDF9IksAjCkO0Nfx6b4oVgn7ss9EKiKTTOhyXiiedgMiTfH88c3FHMh8dFCS+68idFIZ+Es51VqDSFl/6DFqWrNTM5mVmn7uNPSeRe2bu0565wU8L58expRA8GlxcyISbiVXfFb4vry0EF7V+R1PwxUZ7OY59fn8lKrenWRRQ0rLm5WnGo25CEvu0Q0tRC/7sSYu/3h3jCUEUeKwlAYfTkueB62a/bgJgdfpjtZP/KnLrLtqli3PsxAGt0HdFh0oT+HLp6Lq76GidF1MualJY7dC6bPSuqDX7k4K1VsjXhzM6kU+pNWtJQOR7RD48HsREvsfDnoszR2nFrHSEz6RQfL0/oxv7PO4naMs7BaQzeZWUeLXb42y0Q+eOOe8IW+yPVjHKKv7dqyGvTlO+P0rxPeco24l9frU/o9SKvBLsjgpXbFKaUVYwzg3pSrIe4gSsmefxeQ3xfDI49Jw+kTaORMJKpqVire3TjiM8YRnlNU9D/v/s/VmMZVm65wn91trzPrPN5ubuEZGRkfO9ee+tS9WtakTTNE3TIISQECDgBSSaEiAeeGmeutXipZFaLRAgNa2GAqmREE+oHlqCAlW1iqquqjvUHfLmEHOEu9t87Ix7XBMPa5/j5hbmER6RHlmZWflJIfcwNztn2z7nrLW+//cfWBQVoXQ454hjSWsMVeN9cq8KRetbE5/eDJ33EVQNrBo/iN7I13xe5+upRvkQpN97/JoekN8ASK+lvqzb/eeZm20eS0pPpT8Ypjy9qfxBfd1yMvZGnueLirN5zV7fT/U+bwL+mYZomIKAJPD6fm18nO3BKPHNr/M64cc7GW/s9O5d2J6ntflY4ct151VxByF+GZU0kBAJ+bmm0bcXFRBUrd5SJe8DYk5vpRW9zPz79uMaa5lVftKwkUdIKb5w8d3EZ1+tGmTHQJmVPg3n0aTHJI+ZFop+6tN24jC4N8Lytm5Xdu+Di2XN4TDlctV4rXbX6A2y52Dio52c84W/vlEW+3v4BfTbz5vWvOoUAvzCh3jOZogCyYNh5gGtoqBqNEGQcDjIEAjSQBLGIY/GGdo5Pp16g/ZlrTkapJ3paMuFajDaYvHxmdbC1bKiNd4DZJhGKAP7/ZDTRc35ouZyUeGE4GbVkAQSgeN3H41oDTTG8WRastuP0AaGWUjdGta139RuCsUbOxkH45QnsxLtLIiQy2XrPcCEI4lDnJDs5AFCSppWY5AIa2iMw2h/nZsxQete32J/u163bvk39fL6ogPe3eS1258jKQVt4/X/iQzufay28++6/RncmELP14pvHQ74dFrQasd03fAvfmv/M0OBu0D55vPddMEGUQei3AW3NuaTrbUvROxKIaiV5mxZP59eNopVrVjWhiSUOOMQQjDMIuIw8JPqScYwDblYNiwazeW6Jg0DXJfEmYSSm6JhuBt7tk368rXntumnsx5kGSQh58KxrFqCQLKXx4TdcGJzb+NQEoV+P3z3qsFaSKKAQRzQdL5LW/PqWx4YTsIkixh2EdHKuM8MPS67ZMg0CjisFVEg2RvEYOHt/Rzj4GiUcLGoCQPBW2kfZTVCCq5WLb/3xnNT8ctVw24e8cG0oG29+f+/9O0Dfy+Mj2ne68XMKsWyVpwta3Z7EVdFy7gLqHgwSWmU5c+ezHk6K+klAbv9lO8eDUnjkKrRPNrJtzLJ2x4mBrcF224KxfE45XjkmQbrWjHdTGTLlnEasag0B/2YoLsli1KRRpKTnR7ni5JxHtNPQg6HKTdFw0fXaxaVpmgV75+vORil9JKQB5MEbQS/dTzijYM+QgoOhgnGWD64WvtQhljy9kGfLAlxs5KLlWJRtOwPky60wQ+MCu2Nxa11nM1KLtctzlomeUwkA6brhrL1aZ37g5gslpSNN4Of5BGLUjGvW8a9mEEcsG4tv/1oSCAd37aWH58uWdUtykAgHVEowAakieBgkBEIuFg2FMrw1iRHu4bTmWfApXFEFAq00RS1lyeYten8lhytMwyTmDx2FI0mCWBdGVqvuKYn/JT7q5hotwq+dzwieU2Js7+pX/76eZLCXlafx5x5IS2R57YRryvl+FVqc4a11vFsUTGvWgapX+tmRUvceZS+TN696T0qpTifN7y11wO8N2yjDW91EuajUUrS7blh4KPYVXcO2AAcrTJY3AshEJ/X92z6si/bK76s7gbxGG0R8nkARCAgiSRx8Nlhym2SwuZccrlqtvfnZWEdR6OMcRpRasNBP+HHZyvarqc4HKbYTqruGbSafhrxbFbicMSR5GCYEHa+h3cByM19aY3jclZ3wQ6WRhkGaYQIJa7bRx8GcusDZa3jR08X3KzbTpoOTxcVPzge8sZuzgcXKySCJJY8mzVcLBusMWgnUHe8JhwQSh/0YZxl3fqAHAUgYFE5rNHsjzMeDzM+XVRcrxqMaYkiicXy4U1JP9aIQGK0QznFujWEzlEbn95shVdObNwvtPXgFTy3v3Dd3zf+eD+vn6oDkigkDPwZ9nUBP78BkF5DfVm3+881N7O8EBfvnGOvH/Nw4hkfWRJ2aWwBDsO0bIikfOkE/L4m5rpoeTDyCVtF86L84Z2DAUfDlIuumThf1uwPEnpx+JkN5fYC+WCUvRBz/LLnPu0kdJW2Wzf/vFtYXxZ7XDSGn12sumh3xzCL2B8895K/Lwb7PvPv249rjGVatgTCN1JF7ZOPokB+7uK7ucbnQJ/38djrJ1SN5sE44a3dPnFYkcXBNiHoZbrdSmlm65brwpPY88ibmY97fkIdCC/DyONwO/WfFQ3rVvN44k1tb09Y7qPfGuv46GrN2aLC4dlWb+33AbYNlbV+0gvPtcd1q9HG0/o3pbTd6q7DUGynHm/t5Z08okJIgbVeerBoDK7WHPYTpkVLHgeMuqbtct1QKM1PL3wS26JSfP/BiIEJyWNJpS1KG9JA8GCSsW40PzlbUTQKa6HRhkkeczzJCXEM0phVbdkfJPzewzGjJOSj64Kbou3uteXxTo+9Qcxb+z1qZble1JyvGs8qiiTrpkVbnwS0N4hplI9yvlw1NErTGEeeRWilqJ03ZI0cCAP1564SX71a/RsA6RdVX2RM+bLktdZYLmc1rfaeRhvvmc8eFu32eTaTSSkFh8OUP3s6Jw8C3trvkUeexTDOX2Sf3XcwtdZxuqgoGsV7FwVHo5QwEGjr2Twbv7y6VVum6t2I3UWlGaVRJ61q+eByTd0aRr2YstUYGzBxjrr1DMLNIOJ8WW99yvb6MT89XZGEEmOdn1Rqy6Ly8fIbyfWGibVJeLy9/9xOnKlaw/ePh6xbw+EwJexCCe6aiGttPXPFweEw4XJRc1opjkcZJzvZCx5EGw+Mh2M4XdQekOqai9uvye1BjtbeA2lRKM4Xc6rWcLWuORnnNNpyPMooGu8Z1dqQ7x+NQLCVg2/eU6W2PBj5EIJ1q7gpW4ZptE2c6Y0yhlnER9OC3zoZsmoMrbKczmv2BjFJEPCXz5bec0lF1Epzsaj5rQcjAik4qzSPJplPBXXPPUyALdgWh5JZobZ7ShaHGOM4GAguVn5YgaNj4ITsBgHTouFy3XA4TDkZRqyqiKqxDBLfuKwqQxg0VI3lyU3Jk3nFummJooheLHlzr8/RJNsyayWCJJJ887BPqy2tMgyzmMYYsiTiceTlJeM8ZllrJpmXRWjtGOUx71+smFeKRan4ztGAVa346cWSdW0YZxHawe4g4SAQLErFqm6pWs0gj6laQxBqenHI2bKkahWwkWI4giAgDH1csrOOLJTs5QnjPKaXBnw6q9HW8ZdnCwIhiUMYpClXi5LWQij83qeMB4aUhTyWRC7AScu6tBSNZWZ94yDwQwfpfMMg8JPnjXnqq0jbjMGbmX9NjJDf1C9XvQ4J1MvqPq8dax1n84pZ8RywmVct0Vzy5u79A+bXXbcZR9r6c2GeRPQSD/TIzrR54yn4Unl3FFBrgzOOReP91qTwKaRJGBBLiTGO03W17SU2DHDrPAP+elljrKNRlt9+OHruyfcKLKPXlYy26SHvsrAq7W1Hsjh4nnjp3AvDlJeBWFEovzCsI01CDL5nejjJaLVhWWs+ma6ZrhWNMRjreDarWVReOfH2/pAoFAyz+PnQ6857JhCCRhl+dr5ECEEYCLIo4HReMci8ZUQQSJJQbvsTKQT9JGDdtkyLmnVjmZaada15/7qk0pbLpd/3jocp3z4ekMeCP/1k7s8xd+6pAmYtyNZi8R5E/hTWnfMDD+LUjUZj6Schq8Z7B1a197fzKZuGfiQxWJyTSGewQlI1xrOLjB82b8aCzsLic5QLryOMxwJv7qdkr1mS+hsA6TXUV0kI+FydrHgeF++6d9Vm4WmV/4AGgfDyBCFxQKuMj4/WfiGV7ssvFpualT5WV1ufvvJsVr2QKnPfAnmxrHkwzvx1dXXfc1s012sPJORxSNUormrN23t9rPjsRNo5x49Pl+RJ4D0IWs1Pz1ZMsng7mb8bg71B1O+af29qQ49/NvMgjwMGSdiBLv6Q+rLF9/Zj4DygIqVAaW8EfblqSOOwA3M0gTQvmNneLuHgeuUZL/0kRFvLolGEa8lOd/CPI0mjjEeNpWC3F/mYymXDstQcDhMOu3jpvV7Mnz6dv0C/vVjWlK3mJ2dL1o1B4NM2lDbkaYQELlc1l4sGZS3fOuizFoKrVcNN6X2OnIM39nrEHZCy0V232qCsYy+LaIxPXfqDt3p8PF3z/mVBFPiJSGu9qV4gJY938y1bo2k0H1wVPOqS3Z7NS55MS/pxQG28H9K6FRyNcxalRkpoDOwN0o7W6pN2HuBABry52+PxTg/lHI/HPsHoo5s1vTggjCSzdcuq8dHTg9T7YhwMEk6GGR9ernDWkQYCl0TU2pCHIdfLhhujfGqVNQgBaRCw0F7HnGaS3VxysdDUr9s9u6sk/o004RdVtwHS+4wp71L9J51x8NMbzwh8vJtvGYsPx9lnDotKexD9rjR2kEb84MGI80XJsjYstG+GzS322X3r7kfXa65XLUJ4ZomUjlXtZVXnq5rDkTdBXdeKZ4sKZT0YstOLmZdqG67w9n4P46BsNdZBHgco7SVwUvjpXxhIP8joBgXKWLSxHAz953Gnl6DMgkESkOYRzjla5djvp9sEtE9vyheYlf00euGAvdkXi1YTBx6I2u0Jz2i5NcS4fRB3AgaZ90C7WDYgBMM8ZO8W3f32XrRhtRwME44nGdY4TufeM23jsRAH8oVBzqpq+cn5kuNJwqrWXmI4LXhrN/epd9r7B457MT89XzFIQ+LQS/biQHqGorIMMv/7pmEn6dWGVhuSyLPBgkB6g+wkYpDFWzm1FIJKaZS1NMoSBoJhGFO2hqfzkrf3B/5NIviMh8nd3/32nmKNT6Iz1nG5bJmHHrDZ6cdMVy0PJxl56iVje72IKPDSvo+mawKRsFaGk0nK5ar1yTfO0U+9ZPHhjpf29ZOAm6Lderk1xnC1akFA1Woulg3Gwro1JJFgVWt2+j1uypYfnIxY14ay0VRKY7TlaOzfT6eLknEeEQYSWTSIYcJeL0YZx04vIY0DLuY1rXG0xlDMK4o05Buh5NN5hbWOT28qrhcla2UJAxgnMYmUnK9qVpVC9hKsg09vSgaxZFm2hKFklAZMC4XFEUrHqJ+itWVR+T2iH8POIPFpilJQGMUkDFHdYEdbL3nWHWt1w1x1+EYmlJAFnl30RVVq+Hha8f0T9xsQ6de8vogh+3UwkzZ2GVIKwk4m2XZr/8+T+nu3XnbtWls+nRbclP6M75zj46mibGvy2Kc+Wuu64e9zCfJ9/Y2UgjQMiKKASeCHs7XSfrC6OaPf7b82bBfnOLvpBsNd6MRmXbuPTXMfy+hl4NaXsZnY/E73Jbted2CStY69fsL5oqLV3oT6eJxu/01wvx/jbUbzfd6Jt8MvDocpf/LJjFp5OeAojfnwumSUhjyYpByNUt69WHO9rvnugyE7vfgz9ia3q1LG7yOR7IZBEZeLhkEVkUTeN6lUhr/x9q4P7qgVPz4tOJvV/NOPbzrpmUApw2xdEzjLbj+haC3KOtaVwljHddnQqperBTZfl0AuobSwNpA7LxdWWJTxYRc3a0WtFVZAgCOPAtI4QDWGwljSMCAPIxpjGGYRwhjWraVWMAhhrfyafx94ZPAJmxGetVT+HHPkfgjr0rCTR69V6vyFAJIQIgD+r865//5re9Zfw/qy0YxwP9p/Ny5ea8uTWUUgvbSn6ZBva72f0cfTNcvKd64COtSWbYPyedrW+55fGUurDVEQcr1uSMIAIewLqTLb7wn9h7o1lqez6jPR9fei7V3UdKUs89KbmWWR5L2r1Tba+XZjNenFtMaSOs9SOh5nrGt9r7HslykpBAIv89LWcVYplEmIpNwyiu4uvrdfUyn9BP7Pns6JpE8iskazbgy9JPR602XD3iB+6fbqBIzzkFnpk4uEEBz0UrR7bjY3ySJOW0PTGlprOVvULGtFHHlbu/N5Rastv/doggwEh4OEvEvAk0IwKxqezSufEJCGaO14NqtQ2nA0zryBaaUZdBKvRaNwBuJQ8M39PkIIbooGIeHROH9Bd62MZd0oTsYZSZd0BGyT18LAJzTspAk7eZfos3zOrItC/xoEgUBpx6rWLGvNk1lJ0WjyxDccD8YZwzTg4+uC42HEw50es0KxLD0QmUaSQRpxMsmJo4CqarkpG57OSoyB03lNL/VA4TCNcM5ysaq4XjfUxiCcZd1onPMTltpqTAvG+SZ+3bQkQciqNlTKJzRICcMUwsBSVI7yawKPAJLwN9KEX0R9kTHlpu4mmzTK4DrgeXPA3kTN3j4sAiDYevzcPfy/sdvjatUwygRZErLfS7b+C3flc+DXsPNFTSQF/cRLdAIZ0HZDhH4WMkwiylrzyY2Xti1rjXMKpS1v7/dxgm24QiCfy9nGecJOP6FqvSK/bA37/WQrkylazeWi5mLZEIeC/UFCHgre3O8xyWKCQKCND1l4NMkJpODZ3INsotN8Xq0a0ii4l8Y/Xbdbr7tWGa5WDb3d58eV20CeMZZQBOz0BL3UJyQqa5neOtxv9qKiVswqRdMatHWM04h3L9cvAIYb8G/TSCjjH6vVhnmhfAAFEgmkcYhQhiyS9KKAedESBoI4lATy+Z75oEvHW1YtcejTx1pteTor/Wu4ajgap8iucbHOEQqJxQcEHAwSzuYVjbaUjeJgmPHh1RplLDerlsOB8iwq41hptWXBbVjNt/fh23uK6BqmURbzYJQyXbfMKsUg8QlrpfJx93uDhJu1Yq+f8I2DPr/9aMT1skGGgstFQ6U0ofT7Sy8JWRQN1nmPuL1+ug19EA4WpebxjjfYfnpTEsoGJ33q2vXa/9s4S6haw826Zb+f8PFNzbpWfHS9JgoCTsYZ3zsa8WxeYXHsDlNE4RnItdZ8cL1mEAfclC1Hw5RGW5RxaGNYNYY//vCGHzweIYSX3V8sCrQD6TRvHuQMEx8OstOLPONstebJTcMgTgikYFo0zGrFKA452Um4XLU0OKyFXhwQxdLHO0uotEY6Sa0c2uDDF/A+G/edYBy+aXlVPbQB3rtY0ihDlvxmJvzrXJ8HTrTKfi3MpKADDKx122RK17Fzvyxz5mX1MlZV3cmy/ZnQcDIJSMKA/UFMWWsWlfL2G8Pk+XrX1X39zebrR6OUs3lFPwmQnTdPFMpt2vCm/wqEDyaotKFRhmfzijQK2OvFnOzkmA7QuZuQKvDg+AbYuT2AfpVecQMUdWnvBEK84MEkhe+jjHM+TbMbfjTaM/Cna89C3R+kWwVJayyf3ngLCaV933a734Ln7ODbSa47vZhZ0VJ0aZ+b+7xh1s4qjRTSs5UbzbRsORl5wsHJOOfT6ZrdLP6MvcntUsb6ROVxCs5xXSj+6OMZReNVBrv9BCk8E8gJT5iYdnvt3jDxzLCiph9FgGNRNIzzkCwNmZUVf/zxjKNhijEOrfy+9EWlgNWtNdjhzwNNa7lclewNJjzeSfnRWU3bei/UKDG0xpCEIbrRuNyntSkjcM5bX8SxIE89yyqpDcsGsk7BsGGkPn8vebaS+znAI4AkERyOMh69xJLmq9YX7jbOOSOE2BdCxM65nzdt9Ne6XrZgfZm6HRcfCMHTZU0cCgaZ97apW8N3jwdcLmuezCrOF00nNzKEoaAsDJNevJVOnS9rdnsx06J9afrNpjY+QhfLBiH827mfhEghSDoj04259Kc3vskfZzHXRc1eP9le4+2m6C7a/mDspXP92HG6MOz2ven2slYIfBN12xdpmETeSDaALIlolTcxu20sGwV+A5kVLbLTSB8Mk5circY54ijgh4/HnM0rLlcNYeAZWQIvbTgepi8svvfdryQO+M7RgHWjt5TWnZ5f1GeVBxn6aYTgxUjn2691L4nYH8REXWJSqy17WYRxdAlrkt97PCGQgk+mBXEoyeOQKJAUtcIIQdkq/uTpjP1+wqxUHEuxneyL7ve11uIcLCqFkKID+OBi3pAnAQKfLhAgKLXXL0eh9xG5XDeUyh/+rYNWerPRJzcl1+uWq1XL0Sj1+nPp2U8nO5nXJEc+1SIMJcI4nDPbyU4aBAzTiE+vC+aVQmnHMA1w1ifh7PRj0ihhWbWsGsWyNWSxlyG0xssgR3mIdYJRFnK+rClazbxQlErzyXVBoy27g5haGYy2fHi1AiGQzvHe1dpHlGtHJGFZGR7upFjtKc3zUpBGnnXx5KZhp59SL2oq66UJUnZ0VO2+1gScuvka0anf1LY+z5hyU3cPuuM8Yla0TAvFolYcDFLizo8uED4BcHNYtNbxbF5tQaa7wMkmSjkO/VQ16Bg498nn/M96ZmQS+0NqFAbUreZg4FmJQggeTXJq7Q++gyz6LEOzAyc3B2pl/Pr6neMBs7LlplAo42Vabx8MaDsZ8rNpiQjhYJBysaz4k0/mjHK/Lo3yiKK1SGGYFQ3vXq7I4sAzPpMAbRwfXK1Iu4PvQT95geW1eR3uygX2B8kLiYS3D+J7g4Q/f7rAOhDSmwqrDkhLpAeiDgYJf/LpjNZoFpVmkAT83Xcv2e/H7PU9HX9atH5oYf3h+tFOzpNZyaNxxkdXBeDQTiCcl81JAbXSKO1oY8v50q+nrfHywWEabZN5futkxMXSs9ta7YcBsmOOlUrzF8/mfHO/z+EopWxuSQW7Zuqt/T55GvB3f3rJs3lBLwkZ557terVq+d6DIfPKn469j5yfIgfi+T5ctwon4Hcejv375tZ7Ukrvpdgab/S+308QwMnINwx5GJDG4ZbpGknpQbc85JOp4WbZsG4UAY69YeJBtSTgfFFxUyiqTg7caLOVwgjRSbCtQEo/hQ6kNx4tW83qquHHZ3PeO1+Txp71M0wc1+uGYRax24vJY8lNqVhVimezio+v1+RpyMkwo1GGgIA8FrTaUVjLTi+iUZbTWc2yUoRhQBAEWKWZVgpzZaFjcBfXhn4ScjRIKWtFqxVF64cbO8QkoeS984JBGhHgZRo3RYO1jlXd0BpvYp4HgtbqDhz0oM8XyRI8zPrFFQBPp+VvAKR/DuplEqiN983Pa858X0npvUBbY1/wQLqPVf9V6mWsqodd6m8SSC8XqjTn86rzJZW8fTDYXsNXMfXeDNmN82tgFMqtOXYS+kHyBjC7Xvn15q29HsZaAukHCO4e+VnbeR3eNfh+FXALnp8xqlYzLVp2+zFp6AdD/TTc3qOnNyXTdev7oVts6V4cko2DF4KVrPUs20BAFgckoQebNn5ErbF8PC1QyvBkXpEEkiT2ycjr2itSNvds85pddX1TGgVo67hY1Oz2veRdOd+HzcrWh0mEXiYeB3K7J31GkSEEu72Yd6/WzMqWKAwYIsnigDwKGObekuKTq4IwkJwtSsapf75RHrJoJKXWzMsGYwX2qmBVaeJQsmpakkJwvaropYJy/Won9ttgjrYeeBolIUo73jubc7ZqqFtQ2p87Aufly9pqggAsmvOVIIsEZWspa9eBV84bZAsPEiWhT/C8C7Ao5/eBVyCifm7FgeCdo8FrD+R51d3mY+AfCCH+NlBsvuic+/de69X8Gtdt6iHwUvT5NujSao0yjse7uZevWcvpot76GO33IoTIWdXeT+Gon2Cs31DAu9g/m1Vbs+O9W2DIXbroZhFPQi8zOp2XPJvVnIxTHkw88wT8QiqBSPpJ9U+WFc5uJteGPA5faIruQ9uPpODDyxVPZh7NH+Vh5ycgtgysLeUzlPzWwxE/eragLvxi+YOT0QvGspvp/WZxemH6ek9tNuEo8A2Wsf6An3f35gjvHZTeinZ+2eP0kohh5psaIUDQybaUZ2Ntfuf7jPKk9ICaumeziQP5GS2y7DaKeakQEqalYpSGaOt9pGptORomnC1qjp1//a3zr1WjLK1pWNc+OeBonPNglHK5vmHdWBxeHufvhV8Wqlr5+FOBN8+NJNfLmicz5c0IG823jgYMUt9Ehx1AKIVgN/eGsEXtJTGHg5Rp0fJGHm/NvBtlOBqlTIuGctkQB/73WDYtvTTgat1yMpbMSsU3DvqkkeTJTclH12sGacThwEtQ3tjNScOAj28KlkXLt44GfHDZEEqBFmCs42JZ83CUksSS87n3kHJO8OzGR07v5CHjPKBs/NE+CiSrxptuXy1rtBYYZzDGbyoCDyDJLq3h6xQOFPo3ANIvou4ezq3xuvvNmn33oNsqn172xq73//rx6ZInNxXHo4zfejh6gTYvEVjhXsoGtdaz8wLpgRHPLqrY6yc+Mli4zwDyAjgapgQSP42T3niyF4dY4MEwJQwlkXNbVuDtstZRdeb+3NLgCyF4tNMjj0J2cg+SnExy4kDydO7Zize1/7xP1y07WcThMOHxJCcKBO+drzgcZ7TWcLNu+OBqzckk46ZsSRof3LCTJVwXDVWjeKotv//GzgvyNPAm0EkYEAT+/lyvms+A+Zt76xmI3ujYApfLF/2o0iggCiXjLNquDZ4RYpmuW6rWG61WjSaPvRfG5rXSxnVM2YB148H4NAzI4oBF5f3Ykjigl4Q417AoVfezhquVP6TflGrrqbXbizlbVIQSKu3I44B1o9nvJx4UymK0dVuzdXg+GW6U43tHQ358tuBklJMkXqoMcFO2ZJG/jqJW/MmnM447efPRKN0msAJcFy1HoWc8Ndonn4WB5GiY0lrLo0nOTdFwtWpodCfDnuSsu8edFS1JHGDWDicc2nlPkrd6EctKMclDlLUc9VNmlUII+HhastOLPAuo9sbojbb0koAgkOxkMddrxc2q4mxRcLVUOPxr1M8iKmXZ78dcFYr9kWBZafLE7xN/+umCt/Z77A8c8zLCCkEYSbQVFHXD7jBm1rQMMp86u9dPCCS0KuJy7e9bGkqSRGJaR4vzAGFgUcYzsodJwOmyZdVYVnWDAEIpcMLxzkGf67KhUgGHg5RKu+3ndpgExKFgUTqEdPRTP4BYfME49lWHEgJvcr45o/2mfn3rZXYZbsNa/DnNmV9WG3/UN3d7wOtNYXsZq6q13n9HCOGZI9ZxtqgIQslbuz1OOsnzpl5Vvne718migE+mxTZsQhtL2Vqf+tkN3PcHCVerhjgMOBimXK/9OboxloeTFwG6zWP305Bh7gfexnnW8quUtY5nNyXGWZaVIg0lRfPch3OYPx+g+MAdL9G6zZa+zVQC2O3FKOsBp7TzRtrr/E43vd8HlyuWtd/LPrpacTjKeLPXRxvLuxdrfu+NMaM83oJ7Gwb2yTjzycuB4LpuCWXCJE/YyWKezHwC5xt7PUIpeHJTEofyM/J928n09/s+STqPJCoJebyTMStaVq0nLiSJT3PW1nBTtlwsG86XDfuDhCQM6IUBHy4K7w8sHBbLBxcFb+ymGAvKGhaVl25/FUBG4SXFjdbEQnKjW7T1rCgb+j8b6yVnSQI7aUDtwBjDVeWZRIZOkoZftzdDedzzgcLmHS15bqb989Ykj78WefOrAkin3X8SGLz2q/g1r8+LVr6PZroBXVR3qAu7D/nZ3H8gszQkLFtWyieMpKEkkBIkLCq9NRnbJHUN0gjrHNN1S28nvJcuetvwNQzgzb0+/SQkCQOM9TKu/UHC01nJ1bLmZxcr1o0miwTHoxwhBJedD9Jdv6C7aHsc+CbiZJKSdWDFp9OSw2FC0B3abz/GOI/5g7d2X0DU71YaBS/QTu8u6hs66MZobxN7r62Xju30/Adsk0gXS/mZCM679aIfimMnT0BA0z3HQR5tH/NlRnlpFPDO4YA39/zGHAjhk866v2+uIeg20Vb51Idn85JGWd7azQkCSZ5ElK0mi0OORt6U1296kjwZEknB03nFMI04GiUcj3zs72+fjNHOMl8pWu2ZW4fDlPcvV/yjD665XjccjTNOJhlPphV//mzGOI/ASSa9mFo7Rt3v+Oms3LIocDDKIkjZJuLdFC3LqmVZ+6Sq1lgGacggCTkc+Gnus1mNw9FPA8JA8A/fn/JgkmKNN5srak+jPdnJOBqkOPx7v1Ca6brlel1jBdysPHsi6iIMNqyOdy/WaAM3RU0UBlhr2e2nJJHAWkGLomx9N22dB59mS++/tEnMUfhFfl5D2v39a2Ugtb8BkH4R9XledtY6am0wndcX+OSsjUfRqvHSm0Z7w+d5lxz4GdnrHSbIg47dsaoVp3Mv73w2r5jkMbU29OOQZ/Pqhb1ik6QWd8zNHz1bULWKea15uJtxU7UE4fMAhCwMXmBoamPJYsGPns35cFps6dG/fTJid+DlRptkMYdjWmiErPykUhmfKtL5YahWc75qeHO3RxwHPJr0uFg0pJHkbK6JO+aqVnbru6CsIwkDhpmfpm7jjm/dp/1BwtObcmsAvgkDuO3vd/fePhhnLyRo3vajeryTIxzcFC3KWoz2aVjTdcPBMCOL/Gd9I/3dvFYbiVkcCN7a99Pnuk04HKceGO8nWGBZKVaNnzperloclh+fGY6HGX/yZMbDUUaahDjr/B66argpWs8YHado6zx7RGwYo12qn3kePHG1ajkeemnho92cujHETjItWmpt2M1jekmI3TBghQe2BHDW+W5lcbAFL9+9WLIoNWWrmZeKfirZ6/t0NqA7e0i09eCaUobpuiUKBL008sMkCSGC83nLwUCwm8XEQnK2rBhnMap7zfb7Ka2xSOCmVERSols/6a+132t3hgn/lcMBf+/dSwIgT0KsNfzl1YrdXko/DRgMc7T2LK4n85JvHfa9LAzHpzcFj8YptbJEoffxejzJeO/CfxaFEP46tEWkglB6UMxicTpmpQz9OGbVGN/wCceHVxWndeuNcqVECkseSmptGPVDytrSKDhb1PTiACk1WRyhaTsrANmBlRZlLUpBEIPWkAhoXsPGEUporMV+rbvQb+qXpe4bylr78uHE6yopxb2eoq9aLwN4XsaqiqXcrl15EvKN/R5Hw4S9QcLbe/0X+oAvYyz+siTVqtHMKsW61hyPUg7H3ncPYCpa710XeTnxKI14c6f3mV7kLhiWxuG9Ccwvq2nR8CdPZp39RMv3T4YEUj73nlIGhODJjTfPzpOQg35CGEqa1rOHz7ohl7bw6XXBH348RVhACN7cywmE3CZ0Km15Oi/5y9MlgyxinIaEYcisUDyaWFz3+0TyRdY0sB3Cv3PQ78IdIkIp+N6DIcM0IgxKBlm0VdRcrhpOJulW1ne+qLfJbxugcJJHNDrZyt2MhcvViqrW1NqQxQHWeeD+aJzw7mlBL/aDeuWsZ4GmEY3SLEqFajVGpLy92+NiWTEvG1ZfJeqyq9rC9dIxTL0io2g8wBPwXH4mJCwKWNd+2qw7FlEc3kp1w4Mpm5/TDsYJ3DSQdb5Lrws8SvB+rbNSsWwUO2HyGh7V1ysBSM65fxtACNFzzhVf9P3/vJfWdnvAl90BNgoEUnw2WvllNNPNYv2go3HeZiNFUvqDeasZJRGl0p2eNebt/R7KOprKAwKPd59HzzdavxBHuaFCns0rjoYeUd6AT60y9JKIx5McJ8AZ30BdLmoWlU9wqVqDth3wJCVla2iUj6n+PPDFdIv8w0mP63WDsY5BGjHKIo/83yOzC0P5hZ5H99FCNxtL2Sg+mhbMC0UYCHZ7Cb/zaMyol30mkW6cRzydV6+0Gd0G++A5AHRfyt3tlIYXYri717pWZvu8qoto2WiUDwbJ9v8f7mTs9ENqZXm4kzErNXWrn4OA8rnJbRp5j6BvHY04HGUMkpAPr0uedr5aPzgZMUwj1IG//o3WfdGlGOVJBM7xxx/P2B3E9OKIvb5vrGrt788yhLNly4NRujWJrVvDychP0J3wr0PZan70bEko4Wic8WCY8k+fzkkCyaOdHp9cFTyb+00nDqVn0zlBFoRcrqouUlywP0w4GCS8tT/g4+uCs0Xp39/KsCg0VpddLLej1XC98lP3CwzDNGTV+N91Xvj0tapROCISaVB41lJtDG2tydOQcS8gjQQf3Whkd0Y3+AW+woNIXyfEk4S/kSX8ouq+w/nt+PfzZc2x8NJU16VIauMTJeNAEoUBWRxSdSbFd9ejzQF0wwS5XDUc4JmdofSDheNBStl6hlE/C0k7A8m7B65GG87nNTJwFI3laBAzKxQH/YR5qViitgEIGzlSpTTL0vDhZcXTecXhIGF/mHKxqHnvas2om1RtDnutcWSRn4Lu9wJO1x50d8CzWYk2ljwOGaZe6hwHkgfDDI3hcBhTtAZrYd3J7XZ6ERaYr1uyONomtd1lFwVCIITYghe686p71t03YAuObTwi0sh742hjXzA23UziEbDTi/jZ+YJ146WJYSiZlS3vHPYRAp9E2QH3aeT9m6pWsyi1P4BWqvPASHhzv08WBjyZlawb3SVoGgZJgLB+ymuc99n7yfmKg0GCkIJF6Zm0UsC8VkyfVIx6MXHg/YS0tgjpTUqfzStuygZlfBrb1apmrx9zuWp4Ni95OO6xO4gJEbx7uabsEuvuMmCLTgbbuyVxevd8zeHAU9oD6SUJG0Zu2xpaZTgYxt5ottU8bTQ7eUTRGtKwi2tuDFWrCYRg3WpWU90BlAGt1nx8tWZRG7IwIIkCZpUmDQMe7mQ8m1XEqb+XQnovoigQjLKIXhpwPmuwThAHAWWjWFQtTWvZHXgA73q94E8/nRMHglZZVkXLzbrl6az0Xl1uxcEw5a++OWHcT1g2mmfXBcM8weHTXM/mJatK82zZoI2GfkooJatGMy9brlY1WNt59kmMFbyxk/KTi5KblaF1ht8+GZN2XpFnS0eGl8CFnTRkWrRo46UNcegHIW2XwNaXsH5Fr6PPq5087LzFflP/PNTds+6rBvl8HSbbr1KfB/C87NrD0Ksmns4qpPQhBY92e36gfevStfbsmiSSZOHzvfJl8r37klQdjmnpo+DzOCCUwu9Ju+G9zN/Dl9iA/Dwpa1pbfnK2JA0D0tizYX9yuuL7D4YIvDpBWw+UIyzHoxSJZ5MeDhKCDmTapIdeLirWypBGEuEkDsfZouZwlNIoyzD1tg+R8KmYAbBsNJMs5GLV+DNIx8DavNVum2gfjVJO5xWXy4aDYcykl7CsFO9erHkwTv0+ogxhKKkbTd0NIBw+oTQLJafdXhEGATr0w/Hff2PHP24X9jPKIiZ5TKUMi6rhP/2g4ncfjxmmMccTHwj1zlGfRiuUdVS14mrdYq3BOsGzm4Z5oVFGIXm1ZMv7Snb/bc7+dev/ftuuLgCM7RKZjWcbbYEg/ZxdxJ2fA1g2/vG1/ey//Ty1eax50TJdN4yz18dGeqXORAjx14H/E9AHHgshfgj8j51z/5NX+Nn/MvC/xd+7/9A59+/c+fcR8B8Bj7vr+Xedc3/rS/0Wr6Fe18I6L1t+9Gyxjaj/9tHgXrR7M1n9IprpfWwkKT1S6z/gnulxOEy7phsedgDOZvoFbP1wlLEvTNG1dTydVTTap7stK+/tYJ1jr+8NrFtj+dGzBY32HkmhFPSzkOm62fp9vLPfI4oCjgbpvfHMt2uzyIbd1LhVhr1+sgWrfp7X4K5U8HxRo4zh3cs1750vEUKyP4j5ZLpmVrX8a98/pp9FPI7862Ot47yLfnxVLfldc7vN73zbaHfzs2WjOV1UCMdWWnA32U5KydWq9ulnnSfU6aJC4tk8jTIIoNUtT6YV437Eurbs9mKMhXEecbb0Brc3Rdtpxr2PVWMcb+7l26nAvFT0u8Ztc89WjeJyWbPb954jF0vveTXKY/YGMaH0UpCPrgs+viqQ0qP++/2EVTeJX9eaRhtE11Q+mVVIHHHon8frzAN6ccD5vMbiWNSKcR4x6SWcdGyCg3HCKI94Nq99zLLwU+NZoVkPFEkkWa4UF4saHCSR5KpQnC1L3ph4ZtzDHQ+6TouWSnla9PEk5Wdna/Z7CUkUMsokT28a3t7v0TSam1bTKEhDRx6FKGO2WuQN42gz7615Tkv9OmbAR+P8a3jU11vCa6QeOueefMWf/6XZJ24fzu/Gv0s6j7Tu8/uDkxE3RbsNNjgeZ9t1YMN4vBvxe7lqtkyQVhs+nRbojuV5Oq9pOrB1f5BwvW7Z63twpFKKp/OSJPCN9qc3FRermmEaMa/8dCmLAsJRxvmy4sEoJQig1YYfn1XsDXyylrWWLPESrMY4Vo0/hDWt8Wb+HZc6kt6DKY9DylYThJJJL+LHZ0tC4T0ienGAsZ69swHLv3My5KfPliAMvThESMGqUmRxQN06LlY1T2cl3zjoU+YRDycvmpFu7tHJ2MufWmU5m3t/hSSR23TQj64KklCyO4jJonCbnhZvjEv5LPszCQP6WUQaRT61pZN8D5OAyjiuVi3GOW+q2oU69JOIVa15Y7fHG0CtPTAfdkDTKIv48HrNT06XlK1m0ouRwLqxPJz4KHrhIIm8R9VN2fJgmBFHId/cy3k2r5nkEe9drhnnEbIWvL3X43RR8elNSbuNRi4703HvaZBFAfvDiFmpeNRJKQx+P0fAQZ5sGbBR4KUDm8amqBWNNtyUikWlWNWaRdmy3y/5znHIJ7OCZzcVtdH0k5g0lgQC1o2iaCzLWtG2mmEekScpvdRLARdVw/WyZpTHvLHbY6V8SMHpouKbh32u1zVYwR99POPJTcUgC/n20YA8DllXLevKf1ZuVi1SeibppJcQB16+bY3juw9GLErFdN1ytaw4GvcIJMzW3kR7fxhjrW9alVKc7A15/7xgVSs+uikZlgp9YfmdhxMu1g2X65ZeIkmiHOkcrXWUrT+XeTAsBOcw1jNQP56W7PYC4iD08oRFzdE4IwhhmHqX12XZYowjEAHKGNbKNxtt171sBg7ta+gSpICdPKUX/XoPGn6Z9ohfxvoic+Yvw9J5nfVFyXG3r30ziN1Id3txuJUmx9052bnnMueNyfazeUU/Ddnr++TNz+urXlQO+CRVrb0tSNSlW193e/pe57t3Ox30auWlvVPRfuYefhGL+fN6zLbzKX0wyZiuW0Z5zJNZSRxJTNcLLMp2G03v0OzkMUIImm4f3QycW2XQ2qdsJmG4Zf+O84hBEqC195G7WrU83MnY6ycsKk2rfFrYII3Y7Xtp2KRLbL07DE9lwG4v9t6sQvD+xZqjUUIYSUznv2uM5aZL9V5Ufp0dZglVozgrW04mGWEQbe+dNpY4kHxjv8/JOGO3F7OsWua1JlOGy5VnGDfa8sNHYx6Ocy5XNb0kYtJPKVvLP7ksOvAIRmlIpRTKaCye6fOV38c8B3Vm9f0ATwwvmNfdlcq9zPdu01t83vd81YqAqPPQ1Pr1Jie+6o7zvwH+VeBvAzjn/kwI8Z/7oh/qEtz+D8C/AjwF/lAI8bedcz++9W3/U+DHzrn/mhBiH/iZEOL/9os07H5dC6vWHmhJQ5/KVXeR8w/G6QtotxDPPyy3D7f3Oe/fZqhs2EiN1gRS8vtv7GCc94ZweORzg9yHeB+fzfdvpHPny3o7Rc/jkLN5Bc43EUp5Y8+3D3KUgWWl+cOPbzDGMswi+mnIslJcLSq+sddjvx9zsWgY5TFpHHI49ODRFxn5vbCAdzrjB13K2W0pw+fVfYvx3ddxtx9jOo8LZyxJHFB0EczjXgIWns5KvpUMtyBQrTRni5o393oesPsCkO++zfGT62Kr9QW2Rty1MvzJpzNkxyQapv7+b6R3G6BRGy+rE+J5Kl9VNFysauJActXFdgdS0o/85vD7jyYEkcQZx6czP415vJtzvqj4dFrycJKxN0i4WNbgfKMRScm6bvn4pkB2oM4mWvnj64Ky9RKzYRqw2485HHoGkjfObuhHguOTAf0o8ibCZcuy0RwNEgIB7196suLeMOZqVXsTXylZ1IrLVY2xhmWpORql/PhsyfWqwjjY6UHZ+g3gu0cDKmUQ4nmD+tPzJYEQ/NbJgLd2e2SxpFWaSjuiBsq2JQn8vUiTgLLW9BKfEqesIxOSw2HCdKl4tJNTKk0U+PSem9onGI17EZdLRa0MjTFo83yx3LwLbm8gtwGl11kZkMfRF37fP+tyzjkhxP8T+Ctf9md/mfeJu5T0Xhp9xiNtmEYe7Fk1W7nvXRbjwcCnNylj0dYD+GWruVzWLBvFfK04maQcjRL+/MkCZQ2tialbw/W64WCQ+JSqZUMQSq7XfkJ4Oqv41mGfQRZ68LZWlK33jgmkwFkvZ3LOazJvypaboiXq9h+AVnmzY4dfA4IulADhJ4V1FyPvrCOLQr57NOSjq4JxHpGEIXHgJ5Intzx7TnZzDnTC1brlYlmhO4ZWEgjeOextUxlD4Zk4t81IN/e8l0ZkSdgZEquttOx6WfsQgbahl8QUjZf6bfaaz5vEHwxTIhnQzyVBIJhkHhw6XzakSUAahuynIaeLaitR2OkOyVJ4k+mDQcKnNxXPOlmYtpaTUQpuwHuXjkXpjaBlrRAuZZhErFs/gRWBoBcHtMbwYJSireWgn7JuvQH7OE+wzlEqS+oc58vKeyUISausX7+xZGFErS3XK8W0aDnoxcRRwH7Ps75OxhmLbq+Twpvggh+ozKuas3lFpTRPbkr6aUgkBXkc8PG04CdnS7IoYFVrKmXIQsXBKOZ8qRikAcejjINhQtUGDLOIZaUZ5xEWR6MUpbL0rOGDq4I4cKRRzI6ARdHy8VWJdg7TxeBUSrE/iAk7VP7Ngx47g4T/5GeXfHi18pKI4zF54odjFos2hstFw8265t2zNfNC82CS0U9DjBP8wTd3WZaaZdUQSMlfPF1QtZpPb2oaA/NCkUjB3/3ZBXkkWSvIQkmrFL0sZCeL0NoQBwGzWGGM31u2E36jccSo0GfxrVvFpB8TWsH12pCEiigJsDhuVsb7YHTrydfBVO2n8PbxEBH8+jKQfpn3iF+mepk586uAOF9XfV5y3O1rfdkgdtP3VK35DCCzMdnudfJgP/iMEXw+6+cu2GatI7pec732sjDwSXNXd5ix03VLcitF9XRebfe9u2DYfSzmz+sxYym3e/bRyJv2D7KQ7xwOSTrw7L2LNXkc0ktCn4BWtnz3ePiCnG7DDFLGh0js9hIMjqulpjWOWaE5Hqfkcci8VM+tR6ioteTxJOd47FPpNte/CYO43W9p7fcjKbws+aZoWNSKb+z3WDR4E2nrJba18ivg01nFgXGsKk0aCk7nFdJBFAVcLmtWteZiXjPu+yCTQAoP/BjLk5uKLI745kGPdaX5449veHM3Z5DFRIHkr721yz808GBc0hpHKGCtLFkgur6pZvaaVoKX4f4VgHv1AIRNfZ3i4yiCKPVDtQ2u8LrqlUcWzrknd4w4XwUo+6vA+865DwGEEP934L8O3F70HTDoJth94IavVxHyQr3OhbW1XsqQdrrZNA4p2oZJL/Z6TGMZdZrQu4vh1nm/83LZ7cWdn83zheZlE4Zelxh0F9m+jeo/m1fbhW8zRd/r+3SqoGOfREmIxfHJtOJkkpHFAWXRcrlSDPKIy2VDEAhq7bguWoZpzHePhzzcybfX8LKNYuNzsbnGu7/L7YjJTcN1ewG7XZu0uM009cE4Iw7kZ17Hq1WzjZpMkxCtLdqBQ9BqQ78fIwOxlfVZa1nUium6YV62/M6jCXG3KN82sr1dn4nW7uQfj3ayrRHus5lnA9TabOOiLxY1Z4uaURY9NzfvqK9S+pj7zaRlVba8e7Fmpxdxs245n5f005g39zwt/3RZk8Uhe72Ei1XN+aJmmEWe1bXbY1UpLyu0jic3JfPCG5gOU5/g8819rye/WtXe0E74acfZssI5Q6stP3gwZCeLmdeeErs3SKmUplWOWjiGaUhtLKr2BqraOALZeQ857xGTxhJjwFlHa/z7vWgNn84KcPiNQPqI1geTnMNBQq0cAV7iUzct436+TQa8XDUkYUgoPTB0Oqu4XjfM1opeElEoBaFkuq7ZH07opYLTWUkSS3b6Kd8/8X4kvThgWWrCQHC19EBXEoY83oGLpaJsvEE6EgILDX7h3EjXNH5Dkbw+2ummohiK6ufNYPiF1T8SQvxnnHN/+CV/7pd2n7iPkh5K+YLBvpTeZy4LffJJiOB0+XwtKmrFP/pwStTJW411HAxiPropvbeX8+mD14VCa0MQCA6GPXb7ETdFS9+EhBIuFjWLWrEsFSCYFq2Pca804ywEITgaJrTaR/vWytO/f3axwuG4WFSILmK+lwScLysulzWLMuT3Hu3wB2/vMurFBEJs19g09Cb2PjLYMyBPF57N1Et86qYT3g9qM+wAb+79dFZijOVwlHLUT/loWvDuhTfUFtJPw9atplGWh91+a63bmmpu1sINg0Z0k1VjXWcw6cjjyMfDS4HtpmufN4kfpBHffzDkpmiRwidYGmuRoff7GSQh8w54cdYx7sU+ubKT0+2lMaeLilXdctjF3j+bVRS1l5jHQUQWQRpL5oWi1pY8CfnO0QApBE9nJYtS87SuuC4aHk56PipeP0/QisOAZdWShiGBAGMFQjhabRllAQ/GPWZl2x2wAef4dFaxP0x4Nqu27Oc3dnuf2UP3ejHvnS9ZNYo4lFwta2ZrycPdjH4asWwUH16u2Btk3BQtgYSnjUYGA/LEhwwsa8XhKONolLGbReiho2gMdSc/3+tHrGqDdprHO32ORgnaOFrtePugz0/PV5StoZ8GaCv42dmas3nNm3t9nt6UnHfmsNpamtbwk7MlO/2YvX6KlPCPn039NBXB0STF4mitoag0WRZijGO3H7OqWuJQkklBiKRuCya9mFWpuKparhYVvTigsZAnkiyKuCkbplHAm3s9PpqWpLHjbG6IJAgnGKWSUoVIgfdkiiJk4SWtoYS9QcKsaAhxLK0/b4R88WH559k7xllCP/71Zh/xS7xH/CrUq4I4X0e9iqxr4/EqBGTRc4+cx51R9n3r+eZ3yuKQ/UHCs5m3Zlg3mgcjnxqXdp5N9w2cb4NtUnqQ/WxRU7aekXs3yfPuPbwdUhSHwWdkefexmD+vxwxDz2j+0bMFRedn9DuPJtt9odZeFr9hKFkHyjgOurCMTaVRwJu7PfYHCR9ernj3co1zsNOL+c7RgLIx9Ls00+NxxqfTEqUth6PspanTd3+fotWczf0QZbpsMNbi8NYbRlvW2jGvWq6WDf0sJJJekle1no17PEmRUqKU5Z8+nSPxUjkp4LpouCpqDofeEmOSRXxwtWZa1PSTCGUcTxcVoyzmYJSzP4h4OmvopyG9NGCnn+KMYa0si8p7N2Itq4qvtTagUchzNcKXBZK+jpLCBxbNK7X13Hxd9aq7zhMhxN8AnBAiBv7nwE9e4edOgNuShqfAX7vzPf97PLPpFG/Q/d92zn1mLxVC/OvAvw7w+PHjV7zsL67XubBuEOS61VsGUiAFoRAoa3HWkUQBR8P0hYPdZoEJBBSNIQ0lpTL00/AzC819E4aXTR22/9YJhjdGbJsp+jiLOJ/XXC0bqswyTH36TNnRNK11KOsw1nJ6U9LPIhIpeTDJeGsn5639AUl0K6msS2O7u1EobXl2R9Z2O2UMXowgvS9BZrMwW+v45LpgXnm6uuv8gt7c693zOtotKyoJJDv9mPW0ZFW1HA6HvLPXJ95uBh5Nn1eKUEouljXvXax41N37u0a2m2u53eyEnckseIbR+bIm6bwRHN7EPIkkF8umk6QYAuFNAr+x1/feKJ28bZzFIKBoNaeLmt1exN4g2yaR1Urx/uWKOPAeR1Wj+btPFhwMY5aVIpD+fX00TLdeGKdLH+OZdkZ0N0XLMA194pT1JnaNNszKlkHqD9OtdlzMKxrjo1u/fdBn0kt4elNQa0tjXOevZRlmAarbVCWCSllGmT/MJwE8u6mR0js1eLuJiFmpqRrD/jBhkMYsqoabQvHDkxjZl7Ra80efzIil4LRUaGqu1g2BcPzlsxmP9/p8/8GQ7x6PWKxbpitLHvlx9rwylK3DINnrxaRpyCSPSGJBo2HcS/jJ2YpKWW7WvqGcly3rukVbxzgLO9aBo20hiXzagmr9BrEBj6DTLn+p1eLVKpIQ/OpMlv8l4G8KIT7Gp3UKPDnpt7/g535p94lX9Za47ZOktcXg2OunPrygbFlULY8mOWEgmZcNf3G6JJAwyhIGseR83TBKQ2TmvWIEgkESI5wgiyXXi4ZZpQglXK0akihkkgU4QprWsL/X4wfHI7R13lBTGW4KxbN5RdUYVo1mWSucg4NBzLLQTHoJP3w4IQgFaRCwqBVJZ0h5ufIpU0kU8DsPe9uvSyl4MHo+Eb4dH3xbVnC5anDWYYFHwwxlLZ9MCw98JCHjbpByPEw56QYAt+9ho8xWTg105v7JVi4YSNjrJ7Sdt5LrTGQ31/CyPVFKwVv7fRBrPrwq+OhqxaSXkMUBaRjw7sWK3X7U3YOaP3u64GSScjxKuVjW/NEnM5xxBKEH8JLIxww32nhGl3CM8pj9QcK3Dr3f1ckkZ1q0PLkpmRWKbx72cc5xOqspK401Pi2zbS0qcLiu2TkYpBwMU2rlQfzjLm2plwZM1zDOQvb7CY92cn58uuRq1TBMI3Z6Mctacb6sefNWfLS1Xgq9bg3jPGGQRZRHisul99BYNZqyVsRRQD+RXK8dTWvoJSEHw5QPL0smeUgcBGht+WBW4g4GHA1TwkDyyQ3s9hMeTHLO5h7Mz2KBs4Je4kM+sihg1IsIJBjnwaamNTyY+GbtJ+dLpquWxlh6cYDDe3rEoSQIYFm0XCxrjgaZly9IwdNZRRZIdnZ7ZIng/cs1WSRZ1x6MnZcGazxzaV405HEIImTZDb2ksJzPFTs9L0ENgE/mRSfpDMhCsf1MttZ7NLXasCgNN6all/g9N08CJJZeLHBCwMptG4kYDyLdBpI270536+9fBUgqlGLe+bf8Gtdr2yPg6+snfhH1Zew2Nt/rjD8PtsoQR8HXYrL9snqVPbRoNU9nFUkkt8ln1j2XNd+3nt8GpjYpZyfjjDf3vb/s05uSN3d72yACi3+sB+NsyzK67/GsdTTK+yqB2CZ5xoF8Ych7N6ToZcSDL9NjbgKDNsPm5BZLaeNyprVhrxdTa00/Dhkmn2WoSynoxSGDLOb335hse79K+Y9D1WqS0Hs9PZxkPBhnPj2623tv93W332+be/ls1qWIKs3PLtY02nsDDrKQUmnWjeWwH7FqNFj4dFEyTEPWjUGsG0QgOBpmjPLYJ3pbg7Pw44sFSnXrphMsas039np8/3jIh5crpsuaJA3J45A8DhDSp0ZrXdC0IeAZvlcrDc57EUdhQKG+WvLalyl360+LB1deZ0/wVYcMMoA8Cjkepdv3weuqVwWQ/iZee3yCX7j/38AX+h9xf7r13W3uXwX+FPgvAG8Df0cI8fedc8sXfsi5/wD4DwB+//d//7VtlT+P6dndehFBbgik4Bt7Pf782QIp/GRxEvo4xtsLzfMFRmLdc88JKbyz/M87JRDOLwKtNsTh881jVWseTjJWjTdhbrThzb2cf/jhlCgU9JOYcS8gDoRPzlo3LBv/PdNS88g5spdI0zYbxcb09QWJ17TYSh02UrPNAntfgszthVkZH3nfS4IX3P0f7+T3vo6DNOIb+z3+/ntXhEHA450ej3czTsY5SeebsTGO9vGZPn0rDv3EWQL9JNw+5vmi5sEwZa00s8KDWMr4RTfoJvB7/Ziq1V4O0kVyZ1GIEIJ+HHCxbKis95ZyIuTTm4Ki1WRhQNhJ3x7t+NjsQmmMtj7KslHMSw/u1cow6cVbzw8E3Kxb9kfeFPXd84J+GpJHAW8fDHDC+7Gkcci456PBS6W7VDe/YShtuV77BCVnHWVruVn5uNO9XkKrLX///SsWlTcSTEJvLv20VITCkUc9Pz0vW1rj2MkjLlY1rbEsas039/usGsN0VXex2gGBsJwtKqZFw6PdvPPGkihruVk1fHxdsKg0WdqlB16sySIBTtBqzaLWXC8r3jke088CogBaY5itOtkNim8fDZjXDd8cJpSNJpSSXh6wKlsGcYDpNs048M2KMdBoMLE3sx1FgrnzSWxGeeZReecz9nWNOcdZyE4/+5oe/bXXv/YVf+6Xep/4Im+JjYmndZZZxzS9WDb88ESSJSF1a5BSeDae9AfSQSLJY28Wv1aWVhmulGWnlzDoGHaLqgHXeZXVPhRhqRTLWjMJBFGU8dZOxtmqYbefEIUBTlt6ccgoi8mjgPevVoSBIIsDlPXm9nEUcrAT+4FHKEjDgKI1nC0qb1gqBMfDZJsadl20PE6e71d5EvJ7jyfeCFyA7BJTNsOQ07kHqvt5RLhq+NMncx/1bhw7/ZhWGy7WxsdPA2fLGvDrUyR9+kzZaq4WDd9/OGScJ2jj16bH45zdXszlsvYePsVzdtR9wN7dstb5Q7i1VLUiiQKcdWjtJ+AXqxplMpwTHI8SwkAQdbLbOJLd1ySXi4aLRc3RMKFRlrIxKO0Nnh/t5iSBn1jHUeD98IYpdatJQumZW86xN7JUrZeyWQGfTAumi3YrKTtf1jTaUtQGIb0Hz+P9jG/uD8hlSGkNjbY8mZXcrGsORjk7/ZgkCKg7QOt2at2GjQtgrCWQksNBRh7HDPOY2liGmTdD/eh6TasNrTYcDFMabZn0I44GKatGUTSKQRryYJSSd+/x7x4N+PSm9IzfOCQNNfO1T+L79LzxjNi9nCyUFEgapYkHMWkU8cZOn4+uCxCw7ky5w0ByUzQo41Day0nm65ZaWRZVQ20MO72YqjEIKQlDsFbyzb2UvWHMH398w6pUTHox06IlDgKKVrE7SJiWioNBhjKaVa2JAsO4F/GtwwEXi4pn84ZxHlEpSxV4oCmSEqU1jZAkAVTakkahZzFbx6r0kudpYbDOoIFB8jyp5y4LabM4SZ6zlL5Kg1Aqh3IGL6z7ta3XtkfA19dPfN31Zew2tqqGVjMtWvppwHlt2O0/94z7RRlpf94eaq3rEoPFFgg6m1ccDtPP7cNu9xut1n593M1pteVyWVO2hlppLlctgRAsGkUvkpwtav7KG5MXQKSN796Dccq08KxSAfzw8Xirbrgtj24bfW9I0X292t0es9XG70Mveddp57hety+8xuDtR5JI8KdP5vTikCQK+GtveRsTad1n7mmtvZftIH0OMC0rP6BZlN4g+2CY8MZuj0oZ/uSTGdfrBiHgO0cD3jkc+uft3m/OORplyKJga7r9yVWBMj4ZeZB59rKz8I29HOMgjz1jumoMe72E7zwY4iw02mwjkWQoSQx8eL3idFpth1XTosasHO/s9djpJTze7fPh1ZphEvl9oFW8f7HmdFpzufKSvXnRMis0oRTEYcwk9b3kevmLUbGOOjPUpQ9gI+KzPkj3VQik0nvi3R00bOqrMlSdg0kvwjnx2ocMrwogfds599+7/QUhxL8A/IMv+LmnwKNb//8QPx24Xf8D4N9xzjngfSHER8B3gH/yitf2c9WrTphftW5HzocIPp2VBELQS0NaZZgWLbt5/MJCs1lgjPYGv1WjCDow6YvArC+aRmw2EWUt59N6K43bHyRcrRoGecxvnYw4X9WUjU9QeTjJUMYnsbg44GSS8VgIrtY1j3ZCotAbTl+tmhdScKT0G8Bt8+jPSLyE4HLZ8HgnI419YsJ1l6v43JPjxQSZuwtzqy3rRm0BpA2LaLcfc71qaDpfpaNRirWOD68KvrHbwwIXy5rrteJk7Bk1m813f5BwU7bkcUQaSUZZyqrWGNwWtQ0DydW65OPrNZerhjiQfO/BkEgKTpcNe4MYo10HcimuVj6d4I3dPtY5dnsRUSi9jFH6Q/HlwjNq3j9fsztI+P23dogDySfTgkAKEHBVtIzzkI+uG9a1otaGcR5RNBqRhaTST0biSPL+xZoH45yDQcwwj0jDYLspb4CyDWsqEILDYYpz3vx93WjKRmFsyHRdk3j+CMMspmi96erFsmaSxQzyiKr1DUwSCZalAYn3mFKWm3XdpfhkHAxSdvoxkZBIKZmta6ZlS6s1MvCT6VXT8mQKjyY9jsYpdeMnOqfLinWt/VS6NSyKlkIKgkCyP/CAUNl9/WQ3odKOOA4ZOig2YFEUoozgyU3NIA1YNZqfna9ZlC1JEvLh5YJGKyolSSKBQJImjiyJiaxDG4MQPgpzpy89YFi8frO7+yoMIBavd2rwdZVz7hMhxH8WeMc597c6H4r+K/zor8Q+cR+IvzHx/PBqxbNFxTiN6aXeqPJ0UXM09iDJThZ3a7vm6axmWjSMMg8KT/KEPIn49n4f3a2XF+sGaWHS80kpWezT3d67rDHGIIgZpj7V6rdORrx9MADgycxDm2WrmZaKy1XLstK8c9BnpxczW7fUSnM+N4z7CWeXNaMsZFUrvvdghBR+OvmT89b7NgVe7nZXhuxjlfufMT0tWs2zbpIs8Idh5/whJo0D8lj6ZLMujniYRcShN5d+svDx7MtG4zrm1vWqIYtCrouWotE0rU910cZys1ZMBhFJ6Jk+cSDvNS3f+ApW2nT7g+HHz3xPqYyjblsa49jthxwOM07GGddrxbzy54GNLxwOeknMIAk5ndU8m1U8vSk5HCYcjLLucC05m/v9bJRG9BPNs/nGx8j72q1q7yG3bhRWWwSCstZcFy1h4FO6hHQ8mVYkkWBVe3ZLaw0fXBYIJxBScDavOF9W7PYS8jj0TGKl2eslWAdpKDntfJpkN7y4XPrn/ei6oJf4J/vthyN+8GBCayz/n59eMFs3PJj02MligkDy3eMhlVJo4+XNjyY503VDpSwXq4Ze6z3q1rVhmEcsS807+zmLsmW3H6MsnExyLH7v6SURJ2NPpe/HXoJsnSMJJYPEA27Gei/BQRJyMAxZNd7fa5zHPNzJqRrFutH04oBe5t+Lj3b7nM4KKqVZNyFBELKqW9SyoWo14yzg2wc5Rzu5N/ZetsRhQD+xKB2RhwHrRjHKIp4tSuYrTaMteSy9Z5PwQ5NAWIwNcM5ghUMZg9YBwmkkkgdjH5M8KxW11qShYtn4CGeNH0AICVL6YZWf/H+1dSkTkISSeaGRr1s//ctVv/R7xNddX8ZuY6tqkFAqr2rQBh51Z/uH4+wzEfRfd71sD934nh6Nsm0qszKOvUHyhX3Y3ZAhpQ0/vVh5abhwWGuZV4ooDFhWikUJeaz5+HrNd45Hnxni99PI9y2dD2l8xwf19vMFnQJCa4uyPqTobq+22X82g/Rl1fgesB/zdF59BgC87zU+69bwzdd+59GYsjY45/hPP5yy3084HmW8td8njYJtz7cxspZ41cmqavnp+YrjYUoSSfpd2px08OdP5xSN7nxjHe9frMF5dk+ehGgLT25KTuc1j3d96IXGYYCTnZxaeb/U05nfs9at4XCY8L3jEReLkqI1DNKAKAhQznaAZkRrPKmhaDXvXxeUreGmbEmjgEXZ8sZej8t145Uw2nIySdjv59vXOQwa6sSfz6/W3gT9aBhTKMvFsqLWjkEeMZ4kTC+ar5zA9iqVAdKB7t4CoxjKV3jCXPo9QIYg2vuR8q9aKb5v+fiq5Hce76Dd60WQXhVA+t8Bv/cKX7tbfwi8I4R4C3gG/HeA/+6d7/kU+JeBvy+EOAS+DXz4itf1WuqLJszw5Wijm8h5ZbwpsRM+QcV7LvhDz+2FRkofHf+jZwvq1rMq3j7obU2xX/Z8XzSNeDFByOvkG2N52B3epqJFd+bS4ySkbDTzWmMtHA9TLHC1rLEOeknA6bwhDRVRFPCdwwGNNnw89SlcUvjfYV6qz0jVbqPvjfZtdxy9KDXbHyRMu4ho4xwHeXSv0bi//6AaH+tprEMKvPSr+57bOt6y1RjrSLKIs0VF2oFfzrkXKP55HPLN/T6V8o8rBOz2YiIpt9det5oPLgsejBKGWYQU8NPzFYfDBCG8SezF0su0vnnY53iYcLFqWdfK+4j0fILZ9x4Mma4b/uijGVermlEesjZeOnY2rzgapvzodMHR0E93d/OIi3VDKDzQM84jBmlMGutt7HMgfXz2Ty+WaONjtt/c8737xoj7eOx14ZfLBue8tOzRJCeQgg8uV/TTgEol1B17atkoLtcNhbYMkpAkkoROkGcRwyziuvvdHo5TdgdeDrmoFOA4W7RcLhtWreZbR30ulpoP5muOxxn7w4wkbPnJ+QoJpEHAN3Z7zErFziBmb5iwaFo+uFrzyXRNJCVlqwhCySgNGeQh16uWtmN91dryF88WGNNn3Shi4ZsQ6/z7S0gQOFrVIrKMjy4Lns5K0kiybi2t6Q732mIcDBJBEoYEAThnWLUa6aA23lS4bP3CuaGqfp1VG7ipGob95Gt+pp+/hBD/FvD7+DX8b+EHMP8R8C98wY/+SuwTd2u7vgpB1VqE815c1lmUcbyxk/BwkvNwnPPkpuR8XnG68CmWv3UyZFEplpUiCgTfezCkn0Rcr2ou1w1Rx2a8Lho+vC45HKYI4f0eHu8N+O7xgCwKUcbyeLdHEgWsK9XR7h3L2rDbi3lzr8fPThd8elPyaJJzPE5593LFw70+H90UTFcts0IyzAJOZzVHk4R1azDWEoUecJ6uWx6NDdfF86nowSDBdCaj1jlw3vfoeu3ZpnHH2JyXLQ92fKy8dZaPryuu1i2TLOY7xwPPnsTvB1obzoqGvX4KCNJIcr5qCLs0tDwJWDYKap+AlycBrXYMU8FHV+ttcEEgBQfd9Ppy5UGV61VLqy29JGCvFyMlPJ2W9DNvJDovFXUd8V/93QnagsFitOPN3ZxPphWl0gRC8r1jT8t/czdnnEe8e74kCgN6HUX8k2nJD46HZHHA6bxmXeutlLE1ligQ/IP3pqxqn0o3KxVPZhUnOz0clvNFi8CDbU3rwysM8GzecjJJ0cYxqzzjrNGWSHrZ8OEo9eupdOgsYZKHnXdVQhwGrKqW/+S9G8ZZSNUYkkBQ1IoolHxwVWGs5AcPR/znv3XA3/vZJfuBwNjM++4VigeTnO8/iHnvck3RGhoD+/2YWlmSwPB0XvNbJ0NWjSEJAopG81ffmrDb99K/fhoxL1ve2etxWfj0IufYAnSns4p1q5mXijgM6MWhbyKHCTjII+XN3rOQb+z1mVcK5yxv7fvhTCgl1+uaVWNZVC39LMZaxziPaFvDtfIsjFY7LktNFoXkkd/jtPHy7VWrqS+LLmAiQCSwGwtq5f3x8iTiwSDhfFnRaIcyksZ6jzqr/TnrYOINfK9WrV8HtEXIgJ2+wFoNBkrt9xsHYHys9FdtbJyDvV7K2wcD7K/GnOGr1q/kHvE668tIoTbfG4k7SZqBxDiL+yVSxd+Xymyc93Z9ldqEDB0NU/7Jx1Oa1jDIYvqx5Grd4pzvY8a5D6WIA8H1ut16G92+htt+e0LcH3YkpcAZ74H08bTgpmwZZxEPxhm1Mltm093+bK8Xc24tb+zkWxnhXQDwvtd4Ufo+bdSLMdaRxRFnC7/v1q1lXRverVcAvHMweCE19sj5VM7DoeVi0bDbj0g6FcTFsmHUhSN5AM5fQ6MN712umdc+1fV3H01YNZo8DkmjAOEcSlmu1zWzoiUJBG/u91nVijAQHA4ydgcxl8sGIRoejnsM0ohPbrwnosP3HtYYzmaKg7FPexumoQeWEv9eLYwlmgkOhwlhKLlctzRaMys0zlm+czTkZJLx49MFbeu9g3txwHtXSw4GnQdWGKCNw3Y90Vepl0nHgu6/DWNIA+rWN76KYXdPen/V1kIiwQQQOtCvqbEwwMEw4mCUkEcBV+uGQRq9Nubh535ChRB/HfgbwL4Q4n9x65+G+Hv3ueWc00KI/xnw/+q+///snPtLIcTf7P793wf+V8D/RQjxF3jw7d9wzl1/pd/m56jP8xH6qiltz5lFDoTwBxX8126XtT5O/Y1OwqOtRenPnxK8yjTi7mIUR/6w6cRz5tUn1wUXy5qLVc1eL/YTuVHIxarGWm84fTxOeTYrKRtNP0kIpeB8XoEUvLXnZUutNvzo2YI3dnKyjll0XyqOwDN/rHXI4Pni3ItDejvhNkL5ctV8JjbSWkdrLeMuOafShlBKnHOEUmwZTdN1S2+nMyTtfKkWRc3lsqZVjlnZsNdLkFKx38V0RoHk0W6P6brZGp/t9r1/xeWqodGaVhtGaUgvjVk2FTiotOZ65Wg7jfms1Oz0YnAw6iXQXfcbu/lWPlg0hpNRxh/LG3b6CYMspNE1q1qhjOHJrCCUglHuD8GlthwME55ODZNuEzy9KblaVeSJ1wJnccCPT+fEcYBFIJ3jH314wzf3ez5RIZDEgeTN3R4Hg4SrdYPSlj99OmeQBrx3UfBoJ+NkkvEXT2ecLhoGacB+P+XjacmpLTkapry11+NklFG2BoFvlEtlmFeaeeETorQ29JOASsGqVPx/f3zJDx+PCbsoaWUsUeybQm0MO/0YZbzBrTFeDvRHH06xwChPqFpF2RhGvZDjSY/pqqFu/VRmr5+incBZL3FxxlFKx4NhjF41COuBoUZpnhYtrYZ+GtIqi7GWVamRAsZ5yE3h9dptq8kTP9GPAukNx6OApFUdkOyNtH8RVdaaf/Y2fK9c/w3gd4E/AXDOnQohBl/0Q79K+8SmNhRxpQxRJBnnHlhYlJ6Z2M8CguC52fajnRzjLKXxrL00Dsni0EuD8pg0DDxDddWSBAGDLOLZrEQbSz8JuVlVWAQ4x7cOB3z7eOhDAbp0s3Wl+MNPbrhc1cwLL/NpTMbvPByz24v5i6dLnLBcrRRv7w/YHyQ87eLHjdbMKsOiWJGlgnXlWY5SlOwPEiZ5xPmqJosCwiBgXSv++KMbWmcJpeiCGQRP56Wfho4zH2BgHdo6JmnEtfHx7zu9iJ1+zDiJWDdmK6uuGt8I3axbKmU5GKS8udfj2U3JulHs9FN2sojLVUNrDc46+nnMbN1QK83HVyVpIplkifejSdfkYcjRMKFovDx1VmomvYibSjHKYn7SLLkuFIGEN/d6jPOYsrG8ud9jlIScLmuWlWaQBkxyLzv76fnaBxQMEt7a67FqNALB7iD2/nFFy1XRMr/ycqYsDtgbJGRxiHSQSMmkHzPKIq4KD2op63jgHMvKA/dRIFkU/jD+4dWqM4qNKGpDngTe20dqgsAzuJR1zBufhPa94xFv7PWQQvDRdbFl6U6LFpz3Z5r0G+alZl7W7PT7jLKIMIAfPVvwV9/Y6dJdLUngZY+hrPjG/gAcHI40TauZ9GKMxQP2EQySgF4SMeiAm1WjuFz4vTQKPbgppWDRau+VkUQgPAPseOhl5MfDhHev1xjluFjXvL3fZ1kr9voJ80ow6YHVjkWtcNby/YdjTkberH1RKfZ7CWkYcL2qeDYtCYXDIvjZ5RKlgEAiw4CyVkDAKAbrAlwoCIWmFwUIIenFEgveXNZY8kgQRAlVY6gzg5QBSegIQ8EnT5eYLlxjlIYsLiq+e5RTtopl0VA00IvBGUkUBayM7c5kfqFb8moSh5dVKOH7xwN2ewmx/PVFkH4V94jXXV/GbmPr5+PcZ5I0f1HeR/Bqg/fPS2V+1cfdhL8cD31vFktJGEouVi2DNGRethSNQQpvdK/v0MdvX4MxhmEa3ht2tHnu80VNngQM84hA+mSzm7Jh9qni9x5PSKPgs/3ZskbgQaENg8nesijZqAMEzz1Vp+uan5ytUNaShtL3BMZijGVZK9LYG0cXteZ0UfFoJ/d9qpSsa8V12dIaQ6O8RLdoNOfziiwOqawlDGBRKZz1ssEokHxwtaYX+yRWrR1/ebrgeJySRSF7gxik4HLdcDTy/cIff3zDj58tQMLb+wOOJ1nn/SoYJiGP93rMy4h3L9fowDErWoZJxLOll1fOKsU3Dns+cCIO0KbzE5QC6+BsXqOdZ1qCV7ho69jpxUyLhrNFSdl65YfEMS8trV4zrwyBkDinMO45YPFl19uXYTm3V9te4Jk+yn653sBYn1YXh9A2oLvrfF2BPBaoWkuvex02n5vXZZz/RRBvhJcghHhTuk0tgf/mqzyBc+4/Bv7jO1/792/9/RT4L73KY/2zqFcBal62SEopunSAikkebae0Fl54EZWxtNpskcEwkBirP3dKcB9SXSl/8N80LV+04YQdBXO3743Mkijg2cLHUu70YrS25ElELCXL2rA/SIjCEGctZ8ua7xw9nyBL4dlAovv976N93jZie5lkUHamdY+j4N4YzEZp3rtcczSKGaY5Vat4MvMeGhsfqdtTGSkF7xz0+XvvXlI0inVjeWPXH/x3e17ytmErvbHb28ogbhvnHY/SLU31fFEzL2saZTidVX5TcI7DUUYoJcZ6Sd5bez1/vzvjO9GZ822uT0iP1D+dl1StJY0k2kpKZcnDgINhupX0rWtFEsQM0pA//nTGstJcrpuuyRPU2vD0xh92J0lMICCJI+93IbyXxlFnJm6Mf+2OBgmV8ptS2Xr3hctlzfEwY6eXcDTSVErTS0K+ddgnDiEOQ8a9iEoZJI48iRAIJr2ENA65XFbUtWKUhwgkiYR51XYG2yGPdntbmm+lHIF027iCUnsdtXWwbBT9LEYbzbLWTIuGLJL0k4jjUcoo8yavG8P5j6ZeLy+DgLcOhrx/uaJRlkhC6wSLxlAbR9VafnqxxADKWlrj0NbrxJNAkkeSQluUAlnWGAv7o4hWwaKsqTRYZ8F6uurXHOrgP+ea7WfsV6Ba55wTwiuthRC9V/3BX6V9YrMWFY3ip+crJr2QovYsvbN5SWss4UryvY4iv/FX6EUhozTidFbx49Mlk15EqwzaOCrlfRFGvZBWe7NTZRzX64amNT5iPvLsGfDyTOcA52VrT25KLlc1ozRGtZbpuuD9c8967MUhbx/kyI7x0ShL0Xjmk7MOGUW8M0y4WikWpY9h//7xkDj0AEIUSETH5rPWcbGsOV9XWOdDHyZ5xFv7fZrOn22YeolSow3DLNqGAeRxQBJ6sH6pDA97EY2yNNqvq9/Y65PHIdO190BqtWF34MGFYRoipNgOcqxziC70YJJHrBrFTr/H6dwnxBW1Ickl14Vn9GRJBGsfDGGMxTnL3iD2/nRxyDCN2B8kaOsoak0chXz3aMiPThesa0MU4SehUnhmTD/GOjopnWebaONlyouyZVVrrtYtvcjvu8ejFGOglwU0yh+Ue3FIGXvJQT8NWTeK84WXr0dAlvhBi8UPniwWQYjBawKPhpmXklUtZe1DMXx6arhlZ1rnsMb5tNVAsipbPr6uaBpFoR1C+Abi0U7OolJoHJNezI+eLbZmsePu7NIay9WyodWGMAgYdD6E0gpWjaFqNb002iYVvnPQ5y+ezbnumKiPRhnL0jDMQ866ZiqNJMZ5dmWWhvTikJlqkcCiVhS15vFuTi/JUcp7RvWikOEooGk171+vuV61/ORsySgNGecxv/Nwggh8cucHF0uCQBAIh5WCde1T92qlaR304ojWOnYGGcaYrV/SR1cFWmufMuhC4sDwcCdnpxdTqAopoSgsYSiROEZpRBJJbgrFn31yQ218wzMahKxLvwcGCoQGI7tkHP1cBr0ZWn3Zai38+emC/9YfvPELlyT9outXaY/4OurL2G3c/t48CrayqVf1insddV9a8ssG75tztu28fDaS6Jc97kai5QTs5DHLWmOM5WrdsptHlNpS1JpxFnE4TAiE97Hb7ycdgzbeWjps+ow08lLo03lF3HmX3pdKdpvdVTeGpzM/jE3jgDyC0/mLQM5mHUX4NKyrdbM9F0xupZ5u9jalvT+qdPCTsxUHw4Q49D5MZ/Oa43FKLwm4Llp2o4CLZU2rLbX2jEelLReLitN5xbJWDNLYJ2/PayZZxJNlxWE/JYokD8ZejrbTj7kpW6YrH7pxMk45GKRIIXj/YkVR+/fbyTjHWu/596BjvT7e7bM3VIySmMp431htbMekDVHa8u75aiuXM9pxWpXIQLCqLTNVsT+IGecRy7Kl1gYQKOWY2xatDW8d9tmbZF4mnUUM8xBrHP/4gykgmeQBSQh/9mTBXi8iigKEUzydlUQSKuPX19dppO2v0nsX9VPf07yKZG1TIZDEULfPU9uC7hpf16fT4KXSe/2EOAgIA/laweMvApD+LefcvyyE+L5z7t9+bc/6K1RfRBv9InZSLw55OMk8SyboICP3XCu78dA4nVfEYcPJJPcftC+YEmx/vtXEkZ/gni9qhOOF5LKXbTi1MnxwseIvz5bEofcgOBlnTPK4k31BIAN2ezGik4qlUeDBFGPp13rLNNqYfwfSNyQE3Ev73HhoxIHc6oiBezeL+2IwrbXMKoWxjg+uCt7elx3F1PHpTUmehNtEIOFgVXsfIm0sR/2Ux5OUHz1bUiofRfyNvR6O52BeGgW8sdvbbii1MnwwXTGrGp5Ma7JYcrVquFm3pInE4Xh7v+cT85KIadkySEKGaUjRePPQnX7Mj0+XyKIhDgPGaQhSEEvJo92cMISLZcO6duzkCQ+GKXFn7PrTixVXy5pGO76xl3NTKrCO/UFM03hzuEA4kjDskskkq7MVbx96LfRuL+n8EWrKRjHKY/8+Fo7zVYOUMExjyqLBCXwEaqupW4XDsSi9ybYQIIOQPAzopxHfOujzxl6f9y+X/JOP5tRKsyg1b+/3WTeas0XJ+bwhSzzYCJLZusVY6CUh/TSgbDWDJMImgnnpmUMP9zL+2ls7vHu+JkBwsaxQDsxaMMxin1xXaypl+fbhiFWrmC5rBI4sEgi5MedzpJHkwWSIUpaLVUsgHPO6xhoPAlWtl5TksWRVadbOS1+kAyugMVArOL3xQFKl/GLcqC5VR0Dgvn4fJOv8oeNXpP4fQoj/IzAWQvyPgP8h8B/+M76m11ZaW2ptuFjUxJGk1pajYdpp9gV//Mmcb+z26ecRwyTgw6uCg36KcY5V7Zk12lqmReMBktYw7EUIAYM0ZFEpbgqFwK9/l4sSh+RonJEEklWj6ScRjfZJb6LzEAIIBKwq5SXJSUAahbTaMitacHiD0FFK1VoGacC0VMQdI2ScRaRxzLcOfTqo1tYPOaxDG9jve8Zi2b35vaePYFW1TNcNl0tvYJlEAf0wZFG13jeuiw5elooAmK4bsjgkDr2R6CAO+e0HEzTeo6if+YNfGEo+vCo4HCa8sdvHGMvpvMZ0ww4hBKezklnZMsr8/XPOT243+7AQfh+sW4UUXraxkyU+fnjhwYtvHwyZFoqsY5zsd3KvB+OMQHj/wjj0B/8kEFwsavYHCTuxB4Ge3JQIBHuDGG0sxjh+8GjEH340I41CBqnEGLhe1zyYZDwYJjyZ+eh46/xalcURgzziatUQyYDvn4yYrluqRnO9qGi1BylGuQcW59qHDWxYswDHIy+b+uHDCbVxW+buD05GXCxqLpY1T2c1rdL82aclz+YFSjviSPLeOfzw8YRG+cRYrS0/PlvSGsOiVIzyiFmpCKRgum7JIr/Xl0rxs/MFv/NoTJ5GfHeY8OSmQsoabRzGGgRwtW7YHyb8wf4uzjr+5MmcnV5IIAXPbkoq5b08PrmuOF+WXCz9Z+NwnJFHPhnPAVI60iTgYJQRh4IPLtacLSsSKfjBowkPxynL0rAsG945HFApnx7XS0Peifr8+HxNAESRl8oEBPRDQS+NqRpFHErmpaasW06nBXXbAt7DcVX5I/2bQQ8ZSLJIsuqSTgdpSKkcjXFcFxXKQBZ6lmsYSurWkIZ+n3AGauf/DIGom1pHPJdAfOk1CTCt4Y8/mfO9owlx/CszbPhNfYV6FbuN+773HccLXqVfZ1nr2SAfXa1Z1uqFtOR3DgcvTTDdmH3v9mOSMLgXvNn0AqbrBWql+bMnc354MmKQxxwLOFvUHAwTSOBwmNKL/fDyYllvh7gPOjuH273bxqcoi4PtwP22mmFTtwfz005e1kvDrQx2I5ZS2nK1qre//yiNttI48NIlXBfCMStJIkkSBAQClHXs9mL605BKWcrWEwPiUPJXHk86qfaUj6/XRGHIJI89u7ZosfiwhJvSS9CkgPcvC57OCrIwQOEVLv/F7xwQSkHVaNJQ8tfe2KFQmr3hgkj67qtqFLuDmN9+MGbZaJSxWOs4HCRbf6Us9d6ugzQibPU2yfpgkHA0TPnwcsXZwisG3rtec7Go0MbxO4/HCCFZFg1X65rdXkJRaZaNQQSOnTSibL3Eu7bwRm1463BAFkmuli155EkPPzwZsagVN2u/ju8OEta15miScLkuaRTU+qsB9J/7Pu/+NBaq1lGpV1/DEzxIpJVnLEmeg0avE+SK8CEntTLksX/fv87P/xcBSMdCiH8R+C0hxO9yBxhzzv3Ja7uSX9L6PBbPq7CTpBTbiZ6xHmT5wcnzyfQmkj4MPDhRtoa39/scf8EL3RqfnnW+8OwbnE8g6HcTwM113LfhbJJyll2SSiA9VfNsXrObxzzYyV7wkFDay8bCwLOHnHMcjTMf57ysQXgp2Q9ORsxL9RnpGXxWBnifX9Jd/6bNNW/SYxaVIpaS3X5C1QTgHMZaHoy9GXajDKet4XvHQ57MSp7OKuJQcDDwaPvFsuZ4khMAFsGi8hTQu35UEkHZaP7xR1OuVzUfT0tGaUQUCnZ7Ma22fPOgx8WyoZdE0HlNGOsYJAFHo4w3dnsIB5/OSo6GCYtas6oUn0wLvnM04HRZczhMCYXAWDgZZZx0yWvLSjFdtwgLx+MUa30zFwaCKJQ4B8MsZmcg+OCqYFkp4kCy0494dlOzKg39GIq25dObAqMtIhD84HjMyThltla02k+krXEsa8VulnCzbrla1dysWnppSD8JuGoV69owyEL2ejH9JGZR+mWyUd5bqNEeXJQBHOcBq1pTNJaqk4LVylC1CiS8sdtjkIf005D/33tTRnnI4TBnmIckoWcZpUnIvkv8+8U4Dnoxv//WDpUyCAS602Cva8NVoUiikKt1S197CnA/jVDGMS80w0SShoJBEpEEIYu2ZVkZ0ggmeYTAR1zW1hGHgqLzALPWgzez5sXp8HbA4CCWUH3NJkhCPjeX/2Uv59y/K4T4V/AM1W8D/6Zz7u/8M76s11LzsuVHzxZd8lfL9x8MMdZLgoJAME5DLlct3zjs+7Q1IZiuG5aNYrb25pVpGPg4+kHC1Vrwg+MhvTxmXSn+/Mncp28Fkunag82PJjlBJPnkusJ1fiqHw5h+6te7Z/OaccdIypKQPI4olQf/wfGd4wGjPCJEgIN1a3AOPrkpOR6mPD4aAo5Z6f14jkYZT6cls1JxOEpojSGPQ84WFWfLmotlg9KGq5WfeFrnk8Nq5SVlf+Od/S41s0Fbx7zynkkPJxlHo4yfnS25Wtfs9xMmeYITvqlJAy/308b6KXA/oW4Nb+31fThAGLLTj9DasjvsptQC9oYJs0J5lqcQLCrva1ErwziNqBvNTy6W3fcL3jrok0UBP3w4YtUYRDfUQTikk0RhsJX71tozaoQQXK8bZqX3ZhimPZIoZL8X82RWemly4A2uP7kuSYTfnyTQakngHBrBbh4zyGL2laFRmnXjTUaNdUy699DhIGVetB3LVbHXjwgav97ncYAyhlmheDvss9c1Wf004MOrknEW8v51wfceDBmk0XZPmxUtDycZ4Pjp2ZJaaQZJwnAckqcBN2vvu3c4SPnByajb74332LCWQhn28ohzYzvg3XZMrIzACfIoZL8fEwaS61XL3sCDYdOyZV15v4uzRU0USNIu6fPZwgcsNNqRxpK/PF1yPq8YZBFZ7IcLda3o9WOulg3Xq5oH44yqtQxTx3vnay/xTiMWteaPPpryxl6fUreczmsa63hzp8e8bn1UdSw56IVcFC2ztSaNI/b6Id886FM0hhnOM4RkwKxsWXayxMZY+qlEKVCdRP9wmDKrNXWtMVgC52hqhXIexB3nEqUcIAkdNNphrCAOHOv2luxB+O+fZLCsvnqKpwQaY7leNhRa/wZA+uegPs9u4+f53rv1ZXxfN7U559dK85enSx7tZOTdoPly1fDmXm/rO7R5jo3Z97rRhBKm65ZAwLNZxcNJxvEt5pJxnkE6qxShFPSTiEvXcF209NKIfhpx7GDSj1mUimnRMisVB4OER5MceD6w/vSmfKF3O+3CDrLYD2Ve5jG1YXc9nZXkUcANjjjwfeIgjpB0g3OvOO8GHH64EUcBj3d7W6bVvGz5cLrmYtkQBh5cCqWkUZZJHrFuNFnkLSqKWlFr54GkOOCvvrVLIAVJ6JOYD4apT4MWgseTHldrP9B+clN2/kQBD3d7aOtQWvPxTUkSSDSO60VNICXH45RJHvPJdcnTmWdT7/Vi9voJSZeSnYYBCqg6r6rG2O1zv7HX49E43ypgrsuaf/LxlOt1y7ryygs65u5HVwVhIMmTkFHq/RovVzU7fT908iEPjmgo2c0jZpWCiyVFazkep1ytHcpafnaxpBeHWGvZ7ceEAqJQYI0/JyQBrNXX51da44GgL7OGN3i20SYVzeL7jNd9jWkIWeR9f9/e7b+S9c6XqS8CkP5N4H+JTzz49+78m8PHZf5a1+fRRtVWz/5ZdtKGbSOcP8Q9GKdEUoKAeakYptE2kn6QhmSxIJSwqDUHfd8gvGwB3wBPy8ojzJvI3rwznQu7yettOdtGY9sogzIWpQyBlBwMU6brFgcMs5DvPxoxzuLt8z3u3nx7g2SbkBAGkp1evJUHOLyvUZ6E9OOQ1tqtBnlzvbeBtlYb/uLpgpNxShaHWOdeAN7ugk0HA2+k2SrLIIt8alDl6YkIyRu7OXv9hCiUVI3mpmwJpSCJvO/PTdl6z49ZxTgPWNWGSc8nC+z24u3rdVuS+HRWMi8VvSQiDgTaOlal5mSSo23NrGpZ1to/Vj9Eae9tMkhCHoz8dONsXnG2qOmnnhmlOsbCOPdN37xUPBhnGOcYZNHWGyvoQMcw8Aj75cqbXmscb+32uVzVVKFmWSn6iSQKBPvDFAG8fdBjmESE0vH+ecEoixn1YmZlyx99esO0yDkap8xL6CWSs3lNPwt9asLAm54/CUtwjse7Pd7c7/EXn85IooAkCjDGctFo/uLpgv1+zH4/5aPrgmfzEm00oQxYVC3fOhpwdlP6Cal19LIEYwx7/Qjl4JNpRRb5piKN/GL/rZMBDsGjnYwPLrxB6um84p3DAdpYlrU3fzVG82xRU7eGPJTsHvRZlX7ynUW+gUtD705nHBSt4Wbd4IQHE6WrvWTIWAyCNJFkIiAIHFdLjRB+098Qf+6bXCheNMz7uioKIXnNi/7XVUKI/7Vz7t8A/s49X/uVqttrr7WOHz1bkIaSYRZRNoafnq04GWfUrU/6Szq2RNN5TZjO4+CmaAkDwfEwZdlons5KhIBhGpKl0da7YVq0THIvU83jgJui4XCQsaw139jv8dFVwbxqeP+y4K+/nW3fE60ypHHIbh6zHCZcr31TeTzO0dYxXSua/z97//Vr25bneUKfMcb0c9ntjz/XxQ2XkdmZWVlVdDVUCRqEhFEL8dQPSIgXQKL+AVqYfuG5HxFSqQVCPPQD4gEBjVGXmsquqsyIDB/XH7PP9nvZ6ecwPIy59z33xIm8Jm64Iod0pXOPWXuuudYc5vf7fj9fo9lUPdM0YJ5H4CzaQhr717DGEcUKa9xt59NYv5F/0lakoe9cTZOArhdsasmy7NBWcHeasqr620LL/jhm0/TedpaGnK8btrUPMghDxSxU7OS+iHbz/Ly6xgoh2Mkjv6EXwq9Z2qKUpNYVB5MEIWBTae5OE29jyyMkgj+6n3t1oTZsW82DeUaoFJ0xpJFEIZhlMUr1vHe6pew0h5OEb9+bsJvHdMbybFHR94ZfnG05miR878GMF4uKdrBmHYxjql6zGCLlAykYDZwkJ33a2ZOrkvkoomgM81SxabU/MNSaezsZp8sa53yCaJootpXmk4sSlOPuzCeAhkHAfhxgrONq2zHNQg4nCb1xvH+x9QWQxvDGbkYahzSd5mcnG/7BG7s+Wn4Ah0ah76jvDR32vZFEW4FycHee8ucP5/zJgx2CQHK5aThb15ytffLfxabheSB5tJejEKzqlvN14w9ojWZ9tsEOh55l2XFVNjxfVFxuO+7PE6ZpTG8sH1wUfPfumNkoYpoqfn7S8mDHR24/uy75xdmWN/ZylIBgUBVvO8uzRUnVO8JA8HBnhLaOi23Dm/sjolBRNJqPrgvyNGRZdhyOMvJQcbZpBoh4xEXR8nTZMs8UeRaQJyFp5O3YV0VHGgXsjSVFrenzgKuype56bA91Y+kchEHApulZNz2hlHTGkgeKy6r36iHHkJhnSaUADJVxSCyzzIeXlLX/PGIBhfP25FEikMoRDBaLL6s11UBrHU66P5i0zr8bnz++SvHm6xxfhfv68j5fiQAlYFH65+tXjRuHh9GOk7Vn8Jyuar55Z0wcKoTwlrB7Q2FfCYET0GlDkkaeoRdJtLP+PKb9bm1V9cSBT1Db1h3/6sk196YpYeBdGUp61mw4FEV8I8FgnLt1ddw0Hl7nBElCxeOdHBw82stYlr1HRiBu9/QCn1h5o/yqBtv5jQqq640PqJinJKHfi4dKcGeWYpXgatvyYJ7ybFHxYlUPbKiY1loiFOMk5I29EUL4dEjrHHZwgxjnOBjFXJUtrTFo68iTkDwJqDvLKFFI/LyaKsWz3tveF2XLWwc5oRSMxxFV57DAh+clR9OYUEl2RjGRkVyXHQ+mKetO+/cG3J14bm+vLb84X/PP37/kF6cbZllI0RsSJUljxSgNWBaag1nMqmwJhE9WfmN3RBgojp1vZE3TkHfmKduqIzTebr1tDBdFQxIoNo1mU7asgp5ZGnJnmhJLON+2lHWHtl8sCe2rjJsgnRv10Je1IRt88elmvGyxC/l6lEiVhsttw3fvzThe1SRJ+LUWkf7WApJz7j8B/hMhxH/gnPsPv7af+gcwXvXGvk42+qvUSb22vNjeUPI1p+uWcRrcempvHvCb0WrD5bbjclvT9JZ704T7O/mvVOi8XHgKlCTSXvJ/wyAomp7TTYMbNnZH0wSAp1clF8N16aHIM05D9kYRVSe5M00/Uzyy1rFtek7X9e113Jmm5FHA8aq+Jf3fdBcO4Pb1X77mV22AnbacrmsC6QGbn7knltfC53ZHEafrhs2g1tofRThCQGCN4WLoUgohEM5PqDcFmV5bnHXcGSfc201v4aBN59UE16WfYW4kszfXq6QYVD+KfvDl1m0/LCpyUB1ZysZgA5jlIZM04Pmy4qroUNJHb1pjOVk3WGfJ4/A2ta7V/lARBeozUPEbn+qm6THGYga43t4optOG5yvHOAmZZRFtb6lazSRVfHheUveGJJS8uT8mCRRJ7BeaPA745LLg+bLmaJbwzl5OkgTcmxh666W6ZW8GyHdP2VjWlebRXsbRPEcIx6psKaTi4W5GoATbznAwiVESzjc1WRSyaQyddnxwtiGJQ0IBkySk0z62+/mqojeQhIJYSfrOUlp49zAlDwMezjOEEnz7cMqm7fnBsxVF2yNwxIGXAseBT+jZtppAQGwdWRwRB77gFirJptKUbc8sD9mfJIPNxnEyMKdGcQASygFcO04F11uPv/NdID85ftXO8Nc1xpEi/AMpIAH/LvBqsei/+Zrf+70eL2+ewSdQ9sbeFn7vzlM+uigIQ0HV+q5XZxyHs5gfH3ul6W4e8w/f2qXuDaHwn59zDuEE41Rx3fcUdU8QSmZJwImUt/OuNtYnEqYhL1YNQjh2RyFpJFlWHT8/WXNvnjHNAl8gbTVSSv7hW3v0Q+H648uC03VNHAZDAihclz3bVlM0mkB5xUzZeXC8Bf7Bmzs83M1II8XxomJ3FHO+aah7Qdn6jmgUKPLYR/tWveFwmjBN/cZ0GilvSRIQKL9uqiHF5ro0zHNffJMCzjYt3zwa33aDX15jhYMPLrZsGg9evi46dkYhD+cZZ5uG40XNLA0oU6+i3B3FfONwjDWOe7sZwsHH1wXLquN627FuevreHw4mcUjdaTa15mgSY4k5miae5ZS+3OgI2B2FLIYo+oOJ507sDdL954sK56BqfVHBGMcbeyPuTlP2RvEt/8GOfGjFdlDmPpxnpHFA0WjqASh9umop6o5tp4mV5LJoOZrGTJJoSG7t2JaabdURRQHtdUGn4cWy4Y2dnOnBCGsdSRRQdp6NF4shGlh4W3nTGz66KCiajusSZlmIjBR38hhtBQ5oO8NHVwXvnRVsmg7rYJxECBzbynOpnlzXrOueu7OEbx5NcAhWVc9OGvDJVUkaeeXd6aqhaDv+0TsH1J2l1wYhJd84GHNdtrSDwks7x/Gy5HLrpZ5RIGmanlXt7QjaOA6mCVJIwkBiel+wuVi1qFBwXjSsKsPFsqbSlr2xB68mgQBr0dpQ1j1JJAmlYmeUkESKnSzgF2cleegT++JQ8Z+fXzLLQvI4omo84L1znlPhsIMy1SFCgUBQa39owkGmfBBD2Wl644tgde8YpSHCCdLAIZW3RpsB/WeBsvP/kwXeZiH48mtO3Ru+ezQhjb9oqPLfjd+n8Wqx6KuG9nyd1/N5zorXjZf3+Vb65/Zi01IONraDSfxLuArh8E3JbUOkPk3RXJU9BxOFc16JpI0lGoo/d6cpZ+uGbd0ThZK3dnPONi1Prsqh+eCbsfmQ5vWL8y310Og5Gntl+14eeeWTEEShZJ6GmCEI58mqwjnH4SThjX2fZHwDvX6VcXs4TbjYNH4+FYL7c3+PXqxqzjctoeq4M0sR0luqb2xyrdZY55s1CEHbeTYSwDgNOJqknA5WPSkE7+znJJG/H5cvcVvvzPy9qHvPQ53nEefrZvgZllEU8Hh3xCbzDe915csSdyYpTggCIVmWPjm5N45l2fPe+Zams3z73pTeaqJAsCga9sfh7VklCjzepDV2UO07dscxL1Y1SgmOlz51No8DDmYZRd1St5r5JOVg6pl3o8hzaKNdRSgle+NoWJcTFI73zoxvzqQBi8qHQFwXPddlS9EZDvKQZWvAGA7ziHkSYvHNnAfzlA9aj82Qwu/lv4460stFIs2gIgJCAZ375b/L8Hd+1Zz+qwpOX5eNLQT2s8HaKL7Yc/xlxhdacZxz/6EQYg68AyQv/f4//1qu4vds/KoJ/FUp6OvUSTcTRKgEUkjO1jVF2zMfJrXTlQf+KiFQyvMTfn6yYd30BFJxdx6xrntWx2se7f5yotmv+uDHSeDtZbUvHt2dJrdAy9NVjXHeUjBO/Ee+qXt/CK96kH4TdW+QePbG2yWeXpf84PmSddkhlWCeRpyuGv7k4YxOG+LwU6ln3fecrOvbpJ5uADs/3s09W2YotEkpuBgWi3hQR718T14tNmnreLGs6bRhlgX+YZXSF1es5ZOLik3TEweCf+cb+3zjYMLZtkEby/445ul1wcXGQyznubc23QgFhRSex2EsJ8ua54uK+7OUvXFMKKU/pHSGvdy/zu4optGO+/OEg2nKbhYRhpL3z7Y8mKfkccjzhT+UhYFPYFpWHdeNpmg9Y+KP7saf3gvhYYE3ctiu6ohCxf15RtMbni0rjrct2lpGUYjWDhDsZgFv7I/I4pDrsuVHz5d8cFZwvqkRUiFEyNmqIk8DFkXrE4Qs7OYh2nmY3tWmw1jH4/2MbxxMuNh0PF+UrIei5bZpKYUiiyX744iuN1S9IQw8jDAbJLUfX1VoY+iGBbZoDPdnMYuixwlvD3u0l/sUuMGffLFuOF81OCm8dcBYfna24c4k5fmyYj6KmMQhe+OEf/vtPZ4tSo6XFfPUpy58dLWl7fw1CG1YVy2jWLEzyrjctMNCGjNKArS1KBzbxnvTk8Ar9preMs1COuNAeJhsFgVEgcM4zzMxIdj+61l4vuoIFYT8fneWhRD/Y+B/ArwlhPjRS380Bv6/v5ur+mrj5c2ztnC2rnl6bVgUHZHyKSjOOo6mCd86nBIqz0k5XlYEQvLnj3fQ2lL3hvfOtyzLbgDoW6JAEgSKPAqZHoSUraVtfffu7iym6f1zdLZqOBon7M9SrsqODy9KdvKQn7xY+2ez1oyTgJ1RzMOXOpw3a0MgfCLad+9PuSo6smjMhxcFYeA5SY93M5a15sWyJAgC7k4Tiqbnw4uC+zsZWnulxKbxkeqxkvTWcbau0M6/hrW+aywFpEPh6OcXBUp4e20wNFfyWNFqgxs6s9Y5lBIYA/deWc9ulLLbpudquN+9s+zmEfHARnq0m7Nteh7MvV375e5rL/3zDX7eOe9rPrwoPLhfCUZJgBp4AKuqJQ0DDiYxgZSUrb4Fd8eBX9eyKKTXXs0knGDVW55RMkoCb/mbxPzLJwuySFK0Bm0tf/V0ydEkRipJ1fbEUQDCoZ3jMItu12QhBEVrySJIAsnSeZDs3Z2McRZwumqptCZWio8uSr8m1448Crx9eRRies2PX6ywwjJOYvLYd5/PNo2HWw9W8eui5WzdMEkjJmnE1bbmquh562DEg52cg1HEJ9ceRr2s/MEjDnwhK4skbSc472tO1i15pIgDn555uq75x986xBrHJA3pjGG58rCJUELdGC7WDe/eGd/atJPI923nWUzbGz6+LClazYOdDJxjUXVcrmve2sspjUMKy6rqOZpa3jvZ8HAv4/4s5f2TDdo5AgR/fH9KngS0rWVb96SB5GenG87XHXtjn+I5T0OiUJBEilEccDTN6UzBJIl4tJfTD5/JddnhnPP3Eq/wCwOwThIon4gaOJ9+WLUOa0EF0Du4LHqyQDKOJaM4JokscQCbuuNqa6heIy+6jXr+ip2KGJjE8b/xAO1/U8fr1PY354cvU7z5OsZNIcta90sAaKvtL1m5Xh2vNtTvTBKchXnu7bavYjlu7W7acrZu2ckjiq5nnPh92SwLudj6tXichJ9xKvzpwzknqxqEL5IfzQRZqIhChdaWp4uKLPYKyrYztL1jVXYsq47Huxm9NuyPPHy77Q3HrR4YeJIklFSd56ceThPOav1LZ8FbblOvudp2zLLA4yzwDfA4kDzczThb1zy5KrkzTbg/z8ji4DYgSAwBGKeDfffePKXvzZC+1hIHklkScbysuCpaDiYJ++OYVpvPcFtfbrwcr2pGScAk8wEdvXXsj2I+uSr4yfGKq6JjbxSxM4qJA8V11dIazemq8YE44wiwnN2EUXQ+8S2UvrjnnLfelY3nNTZdz6bT7KUxT68qdvOIx/s5zjk2jeec7mQhSjic8w2CWR6zrXtv95fewla1hkhJsHBnnni2UhxSNh3PL0uui45ICRxePV21mmvpaFrH7sTvD65qXzAqtWBRasIwZJRYloX+2qxh/gT22cKP5ZeLRzd/N+bLqZK+7tHgnTs7uWcZZlH0W01hA0AI8T8C/ineyvY3wD8A/pJ/Ay1sX7b6/qo66SZRLQ5CzCCN3B3FAwjXQyr3xvHta92fZ5yuanBeYrg39n+30ea1iWY3KWUHk9jbCFrN1bZllAaEQ0SwE56JoY0FAXXnJ0AhxC3wOhiKVw93/OE+VPJWvq+t5XTV0OmeptNY4cGP2sHZpuavPvGd32iruDdLiQIPTBX4ybxoehZl59O9BNydpuyOolugda8d3zgcUXY+gag37tN7YvlMselsXeOwbBqNNn7j9p07E842Dc8WDTujkHkeUjQdl9uWadrQD6k+nnEj+d69CePMxwvXvWEvj2432k1v+PnZxncUe42xhpN1w94oYp5HOLxN8Ft3x9ybZyRC8mxdkYaKJAq83FUpxol/MC1ugIOLoRCj2RuF7E9iH0NddB4UO1ghjHNUneZs1VBrjRoOXU1neftgxNv7I1pteH5dcTj1k37ZaK6KnrgxnG0aAqmIA8Ube2MabbBW8HxR842jCUXb8+yqxArBwShiU2nGseOyaLgqPf8iDhS7o5DO5fzw6QqB78A/3suoO69Kuty2OCSjRBJIQWP8oTqPlGchWcGmdbeJF3lqmWcJo9R3Sg5nCbMkxBrH3zxZgRBksWRdtXx4WfHGPOH/aWB/EpPFIUfThO/dnzHLIu5MUy/hDbw0uWgsznllWVEbEI5HOxkP5jnSScreQwGlFFSlpmp7tLYYHEWrfSEucD6NqvHciECCUd5O11rHettiHYxC7582/OaB2a8bxoqvL5LhNzd+BPy3gf8Nn1UbbZ1zi9/NJX21cVPAllJytWlu42h384gPzguqXpMGAd+7P7vt+LtBJSilIAkDrHKcbr3FMg4Ui7Ljatvw1v6YP7rnlYEfXhUcjiOuqo6rjQdsH44jdsYRu1nE4TThZFVzXfdsyoZF4Yvu81HkIf299RZM54iHoom1jrLTvFhWLEqvcFrUXtUyTgNmaUTTW1aNoex6TpY1WRIghm1RNMjAN42m7gxdb/nm0ZiLbcvltqFsDWEoeWN/zLJoeWF8l3WShuyPYt488HL659c1y6ql7AyzJOJwEpPHyvv8nVcR+lQQecuCuBnWOi63LVEgiANF6CTPNhWHKkYN68LNOJwknG8atoNl7uUDyuEk4Wcna+pW01vnGULWsZP7ovLpuqVutzxbxLcWtPN1Q2ccedyxk0c0reZnp2tCpZimIVI4jtc1bx+O6HrLouqYpgGhCkgjDx5fVS3gN9zvX1fetjtO2M0jPrwoySNvoTLG3Xa1a60By97ER8VvG8NOGjDJIxZFy1uHE3bSkL96suDpdcndmWWaBTRGeuVk0dFr2NSSdw7yoYnjD3+ryicPHU4Tvn0vxllHawy/ONvw3aMxrYNF1fPxVcEk8de2N4oomp4744QolCSB5LLoEFIQRwFFb2kNaOdYFh29cZSdP1ClgWScRRxOYVNr9sfednc4SVnXPXXZcrFt+d6DCRfbhmeLEucE7xzl4ARPrkqkdahAUjUevt40motNwyTxhxEQnK9qis6gteX+bkarHWlk+eC8GHhhjiAQXGwqNo0mlN5K0/aWO7Oced5xse5oes8lWVUtWaS4LH06YSUU+7nkYjuAzmPFVdEhJOA89683A0q7HwABAABJREFUkEegrbc7SwF5roiCwB/yjGNbGSrjgyi+THKnwm/OPy8SOlSwP4k423S0vfk7FdIf0HjdWeOLcni+7vFyIUvgk39fBkDP0uhz05t+qaEuJX/6aE4YyFsreNVpokFte/Pe90Yx21mPc/DO0Zy60ZxvO6xxdNrxcDe7bS7c3IssDnhzf3Rb8HqxqofitLfs7o4i6tZQdNpjQcYR4yRkVXW8WNaEgfSAaSk4nCR0ncFYz2vbNv2g/Gz5V59c8+7BmDjyhamTVe2VsOsGJXwKaRpKX/BS4jOfX6DgYJLw5KrEOp/EeiTFZ8QIewNaA2HJY4VKA+rOq4n2xhHvnRecrGqs5dZadl10vLP/Kaz85TX05eZ7EgWY1qtc40DxaD/n8W6OG5ouj3Z9SO6zy4p+4Apumo5QCmYjr8KsOse6btkZx0zTkCwMKYfApr1RyAcXHeM4pNIGJeG6brmrvcpT4EgiQW4k21pwZ5rwrbtT7swSXlzXbPuey0qjyo439kccThJO141vmFhLHEqeL2tWVYuSkst1S9n6BM0oVGjrfLiCBGMtkRAQSi7XFReFIVEWow29+fqcBDdPwM0sq/Eqn5vC0qtqo1fnb8Vv9xwhgVVveHJZsy567k353Of4y4wvutr8U+DvAf+Fc+6fCCG+Cfyvvrar+D0an5e69rpxM7ndxFaeb1oWZcfRAPx01iFCnzyD/KynNo8CHx8fKLIhOtIOxSijfYTy6xLNHu3mBFLwfFFxOIm5O6S3raueXluebAva3rKqOkZxSBTI27SaRdnRDMWbe7OMLPLdq5sJPVT+4V/VBiEkSng7V9X2XG87tLbEg5zybN3wnXsTHu3kPL0ueXG5Ybn11oPdUQTW8f1nS46mntGTD9yNVd0TKMk0CQhHPtL45r0djGNO1jVGW9recyciJckizz463zQ+/tcarPP3bD5KuNx2PNoxjNOIbOiKH05jpqm3nnTW8vSq5OOLLavaJwooCUngf/5FrUmUYm8iyCKFcYq398e3saI3qQ3OwfNlfZsWcTDxFryi7vnZsVcJ7IwTRqGkaDWH45ijaTpYOvxB5yYZqe00P3yx9nJQ7dUHPz1Z89b+mG/dnfj33PT87GzD+TYiCHzc/Itlw+7YJxIdjmNOVhXjMKAoNFJ4pcPuyHc1rHPc3UmIpEJcFTxflLcg6U3rv0N5HPLu3pii7ilbQzLETK/qntNVQxIH3JkknG9atHGMIsWjvYxGW6TwC9i//viaquvZyWIe7OTMs5jLTc3VpuVkWXF3nhMIMAIwmuNrzcm2HiKbDX/9fMleFvFPvnVAJAU/ebHmLx7tcLKq2dY9F9uWRdVyfFVQ9oY0DLg397Gr11WDOwdj/GHwraMRzjr+3z8v6bQbYjItVePhi85ZNlVH2RkiJWitpNKWVmv2xhGjVKJrSxYLROAwBg8i/pKwvF93dMbQmt/7FLb/yDn3Z0KIbzjnnv6uL+bXGTdd1K73G0o1wDEnScjOKGI3C8le8ZGrQUlorfNF7iHgYNv07O7HzHL/nDrhC/pPVyXnm4Z10w2WtgClNGEoyIKA0TzkfNWwbnqaxjDOIq6K9haYPc9iztY1kyQgiQI/nwAvlhXPFxVh4Defn1xWrOqevTziziT1HTwH1lqa3nrLURgwjgMc8Kztefuw4/4sY56F/Oj5CoPjzizlzf3c89zigDRUnKUBB7OYURygraNuze09OZrGlL3izd2cLPad41+cbqkGKHWvLVVrSQJ1K+u/OWTcWLuPpuktc2+chEzTkEXZ8mJZeVXqwisV41B5LsbwWdx00f1aE/C9hzMC6aFm67rluuxIQ8UkUTgXcjLcRyEidrII5xx1r/nh84pZHhIpRRz6gIs39nIui5am6bkoey63NctSo0TLvZ3cS/aTkKI2HEw9XPqD8y2B8gmYeaJ4dl1xfzcjjxV12/P9Zy3OWTrjiFVPECge7SRkUcQ0Vvyg6tkfR2wbw3cfTCk6zSyJqBtNlirGScJbBxlawzwPSYJgSCb9VDkQDmpfrS1RqGirlrI1fHRdkcUhSeDtu88XJRL5aSS0sfTWoQRD/DW3hyucj7H+wbMlj/dyemOYpIrjobBTdJ5a+uTSp+C8edCjjbdnlJXmqmipGt+9L5qOf/3xgumQABsE/lnaTUMui4Yw9HufaRryyVVF3XXM84SdkeB0XfOT4zVpFBBHfp9wtfVFqjvTiGXl0NrhQsdhotg2lj3jFcH/8J0dfvpiy1++f8Gi7j3UXDuctRhrMEoipEIKSaMdwXDwPZxEqE1N33m7c5ooqs6gHFwVPVnkEQHxsOeS1n3pNcPgDyafd+DQhtuEq5exCH83fn/Hq0qfl88aCIOD14b2/Cav5zOM0t5wXXYDQ8ivGV+0dnXTUH85YfkGFv1ykNA7ByM6bQiVZ6DemaUcL3yEfBAovnd/SqSk57e9ZO1+OcDopml/s0Z3vW+6O+tIw4C7kwQnQDqHdoKi9euPNj7VrAkMUgqK2ittO2P45LLk/m5+a7X78KIgUpKqN8zSCOe8/feGm2SdI4u8VU4K3+y7+fykFFxsGtJQMU2jX2K9WusTqXfycGA2KZxzHIxjIin5+dmWKJTs5jEv1g1/9cmSd+9OeLyTUWvDybLm2aLiumzZG0Xcm2X+Pihze44En+J7sW2ZptHtd+qq6Hhzf8S7RxP2RhHnRYvuDUEgSZQPbjiaJygEUTQmUV45/XgnpzYGZxxxpHzSzMB16gwsi5bzUYsxjnmWcLqsqXpNFMAfP5qzm0UoBMnAyp3NIs8jtWCM48E846+fLIiU5Phqy5OrkqYzzPIIbaDpNUcTf6YpW0Mv/GdXNpogUKjeg8adMVTa0Fm/X5d8PYDql+1rDK8bD9Zkx+efDX7bO3kHWAOV7vnoquAff/Pwt5rCdjMa51zjIwhF7Jz7hRDi3a/tKn7H4zOT0a/gGn3eBH4zCb8sXXy+rNnNQ842LYGFPA6ZpyEX25aHL6UK3JmmaOMG36pBScE0DXh6XbE7jsgHRcbLH3wyWJ1uNti3aWedoek1Z+uWq6JFCeFVHLOEZ9fVbSLKPI8QwI+O19yfe9vWrX/ZDZMDMEkUz5c91ll6A5NUgZRMkhAhBelL3YXTdcOibFlUHUfjBGcdi7pHCYEALjYNz5YV+3mMlApjHBfbju/dn96+r2aY7MBbzHZy3xEPlC/AddZwutE45yeuWHpG0fmmomgM7517q1kSKtJQErwkwz1ZVaybnlhJD3Vrey5WDRb/vgVwWbZM05AoVNSdn1BvDoc3i2w68vaotrc8nGcDx6HiJycbdsYRsVTURvPRVcXDnZze+qnr5jqEg7NNg3OOy7Ljqmg4XlZMkpA4kFwVmo/ON9S95o/vzfjRi5UvDBrn3zeCvVHEfh6jRM8okuRJwLrqKRqNAI5mCfuTlGkSoq3lzd0Rzjl+dLzm+aIhDQXLyiJEw04qePNggpMpB6OEn5cbr4LSljQMkJElDkOs8x7rnSzEOPjovGA52FnWdce9eYbFULaGDy8qRknLwTjmm3emfHix4dl1SaRA93aAVHtGRaACsiRks265ci0fnhc82MkxvWXb9ZxtGvI44PjZEmsc1ZDWtKpbtp1mW/YgBGVj2Rkl2Nrw/KoiT9RtCkbZeYbIqoUQxzi1BLFCSfwsq6AzmqoDZx1REDJOenCSt/ZiPrws6a1fAL4sLO/XGU4KzG+D1v3rjV4I8c+Ae0KI/+jVP3TO/c9+B9f0lcZNF/VkVdP2vrt3NEk42zRkkWJ/mqKNvbXnBoPS7c4QC3y+bijbnqY1dNqzxeYDZ67tDM8WPrnl7jTluui4rjqS1tvghBXsZI7DUcT3ny5JI899eTBKKTvDnUlCpS3nm9rD5ue+iXC6qmm04XpIC7sJENjNQrJIEQjQ2vFsUdP1ml4bsjDgjYMRx4uK984K7s5Tvnk0RgGfXBV+jchCLsuOWRKRxwEP5jfWYYfVjkAqlJAs65azVc3l1qfnaOcYxyHfPAr8xlwb1oN1LlCSs+EeCQlaG77/bMmdSYJS8lYdGg6Wt6437I1i9vKIv/zkmg/PC892iBX2HL5xNOLtgwnGWN47W5MFASqQmEGtemMJudr6gtw4DgmlJA4D7gwq3fk4pGkd55uWs23DLI2oOsM8C0ijwFvMyo5F0TKKFItaI3AcTjJmsea0aL2VSUqwlt75w8dHl6UvxoeGRdFQNJb785iu93L9+zvejqetY1k2nG18WMKzK3jraMTpGi6KFuO8ZF9JwePdlEhJLoqeZd3zjcOQJ5e1L75ZxzS1XJctQgiMtexknjvyzsGIHzxfcL3pWLeae7OMstVY1/J01QKeD6Wk44cvCoSx/FuPd8njgA/PNwjl0/LWTpOHkv1JwtEsJY2kV1Gva9a1JpS+QNi0hmkWkcY+xe/5suJbR2McMcfrkkAqyl6zO4p5saqoup7jVc3BKOatoVC3qTuqRjMdRd4WHkquipZtrTmcxazLHil9Gl+iJOfbBuugc77wtW6sZxAGkkkcME4DkiAYgk16ynZL3fY4BHHgO/urqqPXxu8JrSONFSEOA4wTRRKF9NpQ6U/TldrGd9+zWJIoRzcU3zaNRRt/yFAC8hTqLypBwh9GPu/AoSRUnWFVNj5t8e/G7/V4la/XDw2Hm7PGjTL9hpPzaprxb2K82jQXA3Li3izF4YtA7fCdlk58Ltj7ptF6Y/vaG1Kok0CSRAGbuuWff3DJLA59yuM49kEwo4jDSTIodlucgJ1ssJm9dC9eff2jacIsC38p6TqKFI92cq6Ljlj44IpRrPj5acG9eULRGpre8PS65L/yjX0C5Vmy56uaw6m3UQVS+JTj0IfDzLOIZdn5oAztQ5TqtveJxsMZciePWJTd4EZ5vYKq6/17MAM/1t9N8RnXSvdiTagkVa95e39Epy27WcC2MZyta07WFc8XJUoKXiwbQimYZtEth9ZziTxo/HLbkoQeKv7ykFIwSSPe2Mn58HKLsY7KmoGxGjJNYhD4xo+xPFtVAJwXLdOBg/h8WRIEkjxSTLJPGbqjRJInGe+fefbev/zwekhzjtkZJz7t1FjuzFOU8A11JyyhFLTacLFpaXuLkJLeWNJQUfeSRzt+P9RnltaEbOuebecIO0sWSra1b8bVnUVrxzjw3LniN1C9sUBtIBHexvzq+CIcVYlvFHxd3KOXh8Mn3aaBvAWcf53jixaQjoUQM+D/DPynQoglcPK1XsnvaLyOd/SrUtf+tvHyJBwoeLibs617jib+3+axB15LIShbTdlprosOYyxOwL1ZysOd7DalZ91olBJcFi2PdvLXQvQ8V8YXfCS+6GWcY9MY7kxjlPCFpk3b81Y44v4s5XCSkMVerh8PMkAhfHHHWM97iALFbhZRDOk5Xe9ojVe2ZFGAVB78XHaaWRqCgOOVt3W9fTjm+XXl75eApu0JQsVV0WJxbGpvAaHXvLmbc116RdFN1OaN//sGzu03cnC9bVm3/W3q0eOdlLNY8bPTDQ54uJdzlER+wh1UJdel5jt3JlyXHdp6u9IsC+m084kOUpDFAVdlw0RJ1q1h5BRCeqvhy4XD1ynT6s57kZNQcTRJmOch+yOvOvvkeosbeB8X24aq1dyfZygpve953XjQ7PAZPrkseW5KHA4hJG/vZ5wsa9pW8/75ljT20tY8CSjqnvloxN7YR2H/4rRgmkbspdFtnObff3uPvTz21f3OcT58vj7RSHNVaupek4QBH1/WHM5yms7QGocxvqvyYJbRW8Oq7tkdhWxKTWslTe/T5kZJSG8dz5cV1jiE+rSTcH+eclU0lJ0ZJLgeYD2JQ6JIsq08DE8bmKZq2LRblAyYjgOvDIg9EPB03XBdeGtiEkpva+i0Vw71mjCAptWAIKha7u+kbJqeReUzDpTysZ517ye8JASEl/9mkaKzlr7Ut1aE54veK9NigcJRa00WKurG/NYlqIGUBOHvPd/ivwX81/CW5r/+HV/Lrz2SUPF4N2d/HHO1bemMpTd+I9hpy1XRUgzE2/vzbEgSVDyYZzSd9iBJCb1xnK8rNlXIO4c5b+3nXnWZ+WLSddlyuak5nKbsj32k++WmRQmQDiSSx7sxy7pnbxzRal9kKlvD0TThsmhIwmCY6zqSUFK2/vDbGsujvYw9pdDOcr5p2DQd10VLpALevRNjrWMnjwcmjFd9SgXvnxaeY2AhjSQXRcNf7O4SBJKnVyXPliXPVz4C+XLbkYWSk3VNogSjNObN/Rwz8KMe743oeuPnQnETHmBYlD3Hq4p1pRknijhStL3hb56vGKeKs9qwO45Iw4CjScyLZcWq6jDOJ3H22rKqe94/3VK2htNVTdUZHu7kfPfBlDRSGOs4XlWcLBvq1nB/J6XTjtOmJo0CwkCgBtt02XoWxjgOGSXe0rSoJONE8fFFyfGq5GJd8827Mx+2kITMs5D3zgruB/IWAlr3Fms9gyMPBWXr7VYfXxTM8gCwhAOINA78WiOs5+fcn6eUjaboDD94siQLJevG8OSy4LzomAwq0HeOUqRU7I29dWmaQtc7ZnnAT16UhEp5NYGUlI2mNYarTcvHFyXZUEjZNC0/fVEQSjhf12RxiHOO3VHMOAmJlCSNFC9WNRbJstBUbUcWKd7Yy/nOvRkXW5+ec75pKRpDqx2xCohCgVIhQkpOlt4eIaRg3RiKvvIMEe3DJww+FOFgHHG+9Z3054OlX0h8QlEUetu0NuyPQow2FHWHsZYsVMzSgFEagoOqt0RS0HZeDdj2hiwOmE9i6t5yvNgSBZJxFtJ2vnA3zRPSQFB1PZ12FF2PFIpRrNgfRbTWDh12C86yqDRKePaRNlAamIX+kLJtHYvGK14D/FohgcaB/RLFI/hiStfWeq7IKI3Qv1Paxt+Nzxuvs6z12tJpSzvsN28YOzecnK8jhe3zEt1ebZq7IbTlZF2jpMQ5N8wF/u//bWDv173H41V1G0JhnaPs/Bzp0Y4+VXF/FKGt4rLwxZRl3dNpfzb7k/sz4kjd7sWfLarX2v4e7WbgoDWGy03DKApIQsUf3ZtysWkQg+pnnnnnQBwo2l5TthGjOCQIJN++O+XFqiJSgqqDhzs5J6uKMFBoY3hjN0cI71B473RLozXb1vDWQe6RHY7bUJ7DiS+SSHyh0A2pbsJ96vaQQmKsZVn6PaeUkt44DvKYg3GMEo5HOznrusc5SxgE5FHApu744Lyg7jRZ7BlDL1Y1rXa8fTAiUJIXy4q6M+zOYw7GHhp+OGWwJAZeAWcdWlsqrfnG4cifJ4HzdcPlpmNd+pS7N3YzllXPg7k/x45jyf/jZ2cUbU+rLTtZRKwk/6W35kShwmiPQ4kDiUOAkFxvOza1x2ZkUcCj3RGzLET3hqerlvkoxA4BAz8/3dD1dijK+Xs6SSSzNESqIRhJgnOS/VHKDvDRRcGyrOk0BE7Q99D53jLNb3BqFECgIDVQv/JzvsgcfhOo8Jsa1sA0jeit+9qbDF8Uov3vDb/8Xwoh/j/AFPi/3fy5EGLunFt+rVf2WxjWOk5XtZchh+ozEsPXpa79ba9jrf/m3EzC1joccFm0XG471nXP0TS9lWNeDVXiZd3T9pqTZc137k4wAyQ1HA4am7rjbNvwZhx8Jh3t5tqOpgmnq/pWWr4/inm+qCmannWt2TQ9Seg7rWGocL3hdNVwOUDaJqmPkn6+qNjJffV6N49Io4C//+Yuaph0rXW8WNe0veZfP11ytW0JA8GbexkSgRAQhf59H0xijlcVRePYtIZ5FlK0BuG8ZDOPFVWvef+84Gia3ALyTlY+2jhU/npvuh/fvjvmB0+XpKGgasFYw796uuLOLOHP3kwInCON/ftojKNsNUkkKBvDj1+sfSEKf/hatxqtDceNYVnWVL1FOni8N2ZnBG5gGLXG3iYqwGcXWW0dZ2ufmAfDIXJYkDpt6I3l5ycFdd8Th14FsxIdUgre3BuRxgGXRcPFuuGNvRGjOPB2AWPQVrCbKc43HWEg+OBiC84xw3/W2lp2RzF3xwnnwwb+YByzP5kg8fLaZ4uaUHqw694ook8sVetZQaNIcTRL6K8r8jCidyAkrIYN+b1pTBROudp0PFuV5EHA5bbhZ8drRknA2/tj7s5TtAVXaxyeu7KbxcShL6rVxnF/J2VRtJwsGu7OY4reK+tEAKuio9eOd4/GaG358Kqm7RtGWcS9WYI2UDWauzP/vFjreO9kTdVZ0lgQhwHW+c94WTX0vUGqQWVW95S9ZScNmeYhB5OEZdkQS0kSe1Bt2VlsByKwhIFgWTrC0N8HARjrF4SqdsShYVUJauMhqPGwGP22iki7aUKkfr9T2JxzV8D/SQjxc+fcD3/X1/N1DCmFTzoZQaPNAOscumTWkccB8aCmebiTYa1XIW7aHiXgrNQ8X9U0bc+DeY7ey7g7y1jVPV1viCPFuwcjrooWbQwn65qdPKLV3gp2fyfjfNPwi7MNo0Rxb5pxMI0JpeD9i4JQ+Oc7VpJF4ws0q8qHNSy2LZ3WOGMZj2N+9HzN2doDR7WFi3WBcZZYyVt+w89PfNTuJ5clba853dTcn6VkccgkDvjkuuAbh5NhAw13xjH/4qMrnxplHZMkpOwM08xb6nptKVvNxbpm3eghnbJmmnl73s44JAkUV7pjXTmc8UXuy22DlAlezOO4P0txAnprETicEx5KbQyrqqHrFMfrmhtd4Bv7Oe+dbvnevSmdsXSNZV33jCJFFgfsZCE/PPYsorLT3J3m5KFCTrz1KY8DQqV4c3/M1aah7X3nfTdL6Kz1qaQrwV88zhgnEfujCOMiHu1kVJ3mctsxShTXL9YYIbg3S1g3ms1FgROSw1lKqy2XRUPTWtJYDTwk4w+R0vMprsuOIlD01qtbZmnAwchbGI8XNVmkKFpN0/o0ubLx7Ijni4pxrNgdJfzR3Qmn25ZlsyGU0jexpOD5dcX5tiEJJKfr1u8dlGA/i1nXnU/vDBTLsqMz3p4sFWRJyN7I25NPVjXryhe93jsvyGNvC9wbxVwXHc5JstCvh2qwRPRac7JsGSdeBeYZeBqloNOOUezTeUIlGcfKpzJJSdF2XJeGZd37ZoAQ9Noxybz9bpbH4LxtTGN9F1wJqk6zKHwx53xVg3VY5xUWRWNQ0sPNN1WLjRXX2/a2gRYof7i0xKShREjJ2api2zvqvidUiix2dJ0lHJLVIuFuE9bArxE3G+xEwSSGoIbt33KY+bLJn96e4Twg/jdoc/q78euP1zUhw0Byd2C3vXzWuFGs/LrjiyS6vcouEsB8FHo1u/AIjstNy3jfW6ZvikSv48K++h5vrFQC3/QLlGRd9mwbjXOCzvgigdY+eTQPFUnsiyRJGrGtvQL9zf0RUnoVzKuA7xsunpSK42XFddHR9IZtq8mjwNujlWR/HJMOISofX5TebuYc09Sr9AO8avds7dMfO20Yh4q7s4wbys268TqRF0ufNjaNIh7vhQiEd2QM/Lkb1c8sDfnF+fbWyfLde1OvQNIGnOR80/DJVcmi6PjmnQmhEpyva/7GOaZZyPtnBZdFQxYo3tgfsZdFCCn8OikgiRRF23OyqBknft14tJcPRfxPG4+P9ka4q5JYecB02RlWtWaaBjRac75uODGOWe6VR0rCW3s5lTFIBNfbnlGmuCo7ykbzi9M1x8uK+zsj3ph4pl/RGZz1zfmu9ztkh4Nhb9JbQ9FbMuUbbnXbc7qpeThPOVm3XBQ1+RAadV10bNuOUeRLHtLBuvJBSj853hBIKFrLOAtY1oK+17Sd9gEfQhAi6fHiiJfn5N/E0EA7TNoRfifyeey63+bQDmZ5zDgNcF/zEvGliXvOuf/sNb/9/wL+9Ne/nN/uKDvN8bImDr0y6OU4eV85/vy73fS++9kPINVeW8Jg+Jdu8ATvelD2s+uKe3Pfbb5YNyxrnyRWdpbrouFk7TfYTWt4uJfDEF0pHLcMplcXhFkW0gyVejnIDLX1PupZFnK5bZHCYhzcnSY8HxROvhjihq7vEuN8Ee1oHIMU3J/9stztvhR8/9mSh7spq0ozSwOWleZP7o+4KjsyY/nouqTr/M/bm8e8dRCxrHtWVcl12fGdownLuvfyTuM4GMW0g6e27HvWpQd+b1vNOA6wDlZ1wKLo0M7ywdmGOAo80FU6pnnMg8FzHYaKJIRRrNDWd3X2RzEXhS/WzbIQi+Uvn62pOs00i9jNIwIhwVke741pesNOFvF4J//M+3/Z2vJiWftugJKcbWqeLUv+4tEu37035cfHa55eF2zbnm8cjigarzQIlQebKyF4uJtxMEk4XbUsam97/Ptv7rEsG45XDXVniKVkEsaMYm/zOl5WnKwbdkch37k7Iwold7OUNPTd+1B6RlMaBXzjcHyrfLPW8XRRMp2EuMHKUvSWvPTeYWMdQSD58Kyg14Z5lpCnIfNxwLNnBR8XG6rOJ5UFoaTUmlXTI5zj/YsCKSx97wBH1fasyp6zbU1R9wjh0M7Qdpqy7tgbJeSRIpGKRdUxSyOEgzz1qUNSCH/YKntiMdzbRYmxmjgMkNIfsqquZ1P1BCJACNBY2tZhekMvIA6gCRVm6AQlAVgcEt/0ioSgND5BJwy9PaF/KWrNAcL4wzYdjGJ3W1j6bXuYHxx4PtofyHhPCPE/Bb7DZ9M6/4e/u0v6aqPpDe+fb3j/rMA6xzQN2B/FFK0hjwP2xzFRqG7VpOcbDwRelh2fXJdo7UgDxTiSOOGIAs9DcMBV0dEZz1jKQ0UcSQ7HCQ7Hi1VLqPyh4mRT02uLkhHaOn78Ys3RAI6OAom1gjwcs5dHtMbw4XnpoaFlSxwGGOfYyyKs88Wv+SjxxereUHYaFYdMkhBtwWjNouzB+u/6+aJmVXrbWZOG1L23UAnhGRNhoLDOH/bXdctOHvuCupOcrCqk8AWF86Ll8U5GHOY8vSz48LKgaHtqYzyYWcAsCdm0Heeb1qdkDUllF9uWN/d8I+Fq62HN66rlxdIDybrekoUhEm+Z2zQ9q8p3cn96uuajiy1JJImk8CrYssM4L8ePA0nVCTZdx1uHMwIhfeMk9ND0VhvyPV8cwVmyWPH2zoiy1fTW8nRVcdc5ZnnkbbWd5nzTcnfqrXhxKHGFI4gEgYAgkIxDSdkYYiUQTpKEjuuipestRaMJAKsUgbIEQjBNQla19Ymp1qECRR4G1J2maCFPAoJAcbGt6ToPLM1Cn8Z6sq6x1iuSHR6o2mlLpPyhrW691bjuNRJBrCRF74OJ78x86MX7Zxvq3rI3SnB4NsrFpuWtwxGrqufRbkanfTHv2WVDGkqWZQsCZqlXGfU4MqmYZiFPriqCAHbDmMW2ZVV3rMqOQHorw+EoZlF1xErRGUcQ4G3HZYfG4QJFKgQyDNmfBEzTECvEbWLRg/2cF4uatjcYJzAIpFRI4Q8wd2cJiVSU2lK1HUezjKLxBcLrqhsYKQPAWsI4DumMRiAJnAXnsEYjHDSt8SojAVnkn69YKtatvt01hnwKWR3FAm3d31o8gq/G1+uM4/FOTvxbjHr/u/Hlx02Br+k8BNgOipQbTtAXHa8qin6VwujLBAK9HAZUtf5cdMMBGie++J9FAVHYszf69Jx0c0a6Zc85PtNofbGsaLWH/q9Ln4R7XTW8tT/ibN3SG8vHVwXjKEAIwf15SqAE37o7QxtLFPqu3s3PUgND73xTe2+O8M0LJQTPFyXbRnuVuoAn1z797PHeCGsd10XH/VlKHCgOJ75Y3Wm/p3y2qG/fx7fujNk2GiEFH10WvHM4pm69pdnPd56dOkkjtLFsW0MeKaT1RUGP4WhYVd2tMrVofErnD49X7A2BQqu652AUkYWKp23Pz042SOloWh/Q8K2jCYfTmL1x7NOzneBk0/DtOxN28ojzjWJRdDy7rkiGQuQ8j/n5yYY/ezjHDu4Sax1tp9kdksCTyJAECgf89GTFVentbYXRXGxb1mXPsmlZVz7d+u48Y28UsSp7RnHAuunYNoZN09F2Pacry/44YpKEtMYiBtbUN4/GfHJV+iZt3TEKAvLIN63O1g1BIJgnIb21aOOT8q6LjkXZcWcSM7chIT7wYpIG1G1PpzVnm5IAQY9jWanBtuioekPVgTaOaWJoOr/3X/2a3rDPQ1aE+Ibzb8Ii9+uOCJinggd7Ma3+VOjydY2vK7LhD6718XLaSzRMlC/HyX+e7PPmNZ5e+0PDzUQ+TUPuDVDT50vvF41eih++N0sJlcQJvHyyszjnO2NZKEkDRdsZng7Rj/ujGKU8Z0hrz96IQ0kaBHTa8JPjNVLCfJCHXg0S0P1xfKsGyqKAB4OaJlSSN/ZGHE48yPK9sy1Vq7k3T7kuO4xz/jDzmrccBp6LsW0FeRAilGAcB8SR4kDGfH9ZMUtDglwyTQOuip67Sejl/mnIf/HRFcfrikT5DWWvLR9flTxfVvTaR07+vUdzzovexyY3HaNQ8fS6Qyo4vmi4LDqS0AOUN61hlDryULLo/CZ/XWtmWeDjKsfxLaNEIpDCS0QnacTRLEZJ5b3WOK7rjrKz3J2lPNzNX+sVTUKfOtdpw7bR3j99VbFtOq63Hf/ut4/480dz3z0NBNtG+5QZYJaGnK5qfvx8zcO9lL084cFuyjSJEDRs6p4Hu3N2RxW/ONsSSTFEVEt285AolHTaMU0j7s8Sj+0ZVFEH44SzdU2nfVTmnVl6GzX65LrkpycblBQcTmL2RhEPZikSuN42+GRAx6bt0ecWZM39ecx6q1k2DfXwmkkU0Guv7kpDzarsKBsfmzlOgiEJQrKoWlaVvx/gJ6x+ANtFKsA6Sx4HjIyHkxa9RiC4P01RgS/abltN02tOtzUSSd1pDicpZdfywemWddURSMeyNpRNRxAEzBOBBsqy9x0o60iCgG2lGaUK4SS7WcJV1Q6WTz9plY3nAPqrffnZ9sWizsHYWGKlkMLQ/4a7Ga+OCEckf+8tbDfjfw/8AvhvAP9r4N8Hfv47vaKvMOyw8f34omSSBgRSUnWabaM5nCTkceBTQIz1xZZNgx46nhfblsuBl1R3hjj0yX7n25ZOwzeOxry5l/PJdYHDM3o+ui54cl2TRZIsDHi6KDmcJAgEB5OEIPC216dXFdvas9D8JjjBWMui7v18W7XgYGcSgxF8fFlyVXTUvWbVaKLAF40f7Y3ojOPtw4zLTc/puqHufBxuZxzUvqjaacPpskY7x9W282tXqDhdNYxixabVNK1hWXYI59kXTd/z3mnD9+5NiZTiYtvwi77gm4cjrIRt19M7x7boiAYF7LrW/PDZCicEd2cjemO52DRsG80nVwVNb3B4C9Gz65Ky0xxNEtI4ZJoHiCGZVEjBk+uSoul5sJOxrXvmWU6X+C761bqma30xWg8Hnct1y/vRlm8eTtjNYy63LU1vuFnyIyW9tbUz/PWTJTuZYhRH4Lxl4O40wVjHi5VPcEM4nIW7s5RNbchiycWm453DEdYJWu0TRe/PM8rO4IS3v2WlYln3zPKIqnU82su4WDecLBt6oxFSoltL63zy5v15xqbRzLOAZ4uKeRajHTzcy3xDyDryyFuDtYHZyNJrwYuiQQivkr2/m7HYevthMXy353nEWwfeHm2Mo3eWVdmz2XovwCwNWWw7DsYxR5OUj642fHJZ0hvL4dRzRaZpyHfvTxjHIR9dbhFCsNh2xJFX9X14tvERz0nEn7+xi3FwvPS2lDthTG8drbbUrU8ULDvDJPbJRRaJsb1XKMQhk0SxqnsiJfnOnSmTOMJYr7b9q0+WTKIUiy8gXWxa7s8zul6zrjUqaMmigHEieHZdkwYChEJYzy453A853WrqrqduLeumo2x88poRoHsogVz5Lq9zvvyTCL9uGPxaYQCFoHeOmL+dbXRTdPoy2/xpIsiTvyse/b4Pb4W2vNh4fcLBOObRXv6likevayCvqv61CqMvGwh0k4K8KDtC5dPCrHN8eFF43EIoEcInI++Pk08LYq+5pst1wweXW5rOcjBN6LVP6L0zSzkcJxSdJiw6Xqx8gThVAWkikEiuy5ZV1d4yY6WUn1HXdcZwvvaF6l5bJmnP0TThxbJBSphlEXvjmNN1A86fy27ee2d94/fxnl9nfDPGIxfqTvNsUbEdksuyOKBoegIJf3J/hsHzzQR4OPPgNqnrnkkcoAbl0YtVxfW2ox+sr9dlx5t7OQmKn56uWRQtu6OY81XN2bpmW/uft6k9s3bdGEaJ4oOLAiXg3TtT7s0zf/5b1nx8VfCDZ0tvDxvUwAfTlHfvjpEIPrkqWTc9o1ixbjT//P1L1k3PJAnJI4m2Hruxrju+/3RJICWHkxhtHALHtu3oDVyX3r7/N8dr9kcxj3cz5nnMe6cbTtc1xkKjLYETXKxb/vjRjDd3RwjlP6v9UYySAqMN+cBfUtKiLeyOIpzxBaOPryoe7fr1MhDQa8eDnZTFtqG3gl6DcT3r2mBdz7K0GAN54sUCRaeRAkIpGUWOqndsO3DW7+N/3eLE583FPZD8GnWZzytQCXyhRvLllU0BMMlSXlx3vLX75QrVX/T1v47xB2e+fl3ay02c/Osgba/z+/qNbkseD+lp0g10ezBD9V8JQRRK5mlIFKjbbsPdacrJsmZbd2RxQBYF5HFAEineHo/4yYsNZacxW/juIMc/Xla8WNWMkoC9kY8fbo0hEZJWe1ZN2Wq6znBnljJNPSjbDJ1i+FRSOkpCsI6PlOD+TkYaKQSeZ7A3il8rhxYOllXvYXhZSNNpllWPcL64dGeS3HqVvYe6oag7RmkEDuTAgHISQiGpreVsVRCFvjK+WNX88HjN/jjmYLBoLfqeq22HxfqJzcI88N0S69wQ7xsRBb7gcneWsDfyRbOLTUOnjedMAV1v+OiiGJJ2BLieTd35fx9KyqbH2vRv/d6Eyk+Eda/56LKgaAxSSDaN5vtPF/yX3zlgmkUcjBPWdUEaSJ9sEEoWVUcg/b1a1T3TOuS7d2bcmaWcrGquCp+YN0tDLH5x3B15Nsoki9jLY44mCUGguC46xMgv3kmg2B8nns0RDSk82vLJxZbzTcOdScKq6ThZ1uhJwj9+94Cfn675T39+zvXWs0PuzjNGkeIHT9b84nRFIMAKgZL+u2t6wxYwo4hF2RIowZ1JDIFglsR01nCybNhJQ5ZFT60b1rUlCwWhChhnIau6xVSwm4doA3bggUjrWNQtB0mKNZZt3Xnv9ihCCn+vUiXY1j2rukcJn26jLYRhwE4agpQ4a+i1JY59kpDuNWkC7x7lnK0aytaxL6IBHutVep3xC4Djs0kNNxt8BdS9A+eLRy9v/D9v4v86xrLxm57k8//q78N42zn33xdC/Hedc/+xEOL/CPzff9cX9WWHcV6ZifB2IvCbb+0cB9OETa0pW8/HGyUBPztes6j8hlE6KOqeou0Ypz7ZK44k4fA9DqXf9EWBom41P3yx4dl1wabpORjFvH04xmrHk0sPnuyML2KcbzvyOKDuLDujmOui5eFOxvmm5Y8fTBmnEW/t57x/WtD1lkh5VlmgNMbC/iiiHrhhoyRgnkYYA3t5BMJxmAf87GxL3RuMhUhC7yxJ5Bsa2vqEqXfvpNRxz798smSxbTjdNl7V2Gr+e3/6gJ1RxJNFhRGQRoo4VFxsWn7Yaa423rb1YJbx4WXBk+uCvVHM33tjl1Gs6AxUfc96bQikVwRfbht+erq9Ve3mScgkj/n24ZizbcPFpuVomnCxrr3SJpT8yYMd5qOQHx9v2NQ9SaQ8xDj2628SKl4sa+reDKomzfGy4s/e2AHcEDQhBuWOZzPdppBuGg6nPZPMM3c2tS+iXxcNl2VPJAQOx7fvTnljL/NQ6d4SRwHOQaQEWZT4hLaLkmiwu+dJyNEo5k8ezylKzc/PN5wufXR92Qs6bXi2KjmcZry1l3N/d8TJuuF80+OcIwp8pPTlWhNJwe4kY5IFrKqOVd0gK0ep/QEolIqdXHlFDTBNQ0aJt3pEgSQJFE1r+Pa9CRcbb0PeG0UICaMkpGg1j3Zzzrc+VjkIBLM8IR4S4JSAPFA8X9T0BqJgsDJYuCo7FnXHstREkeJ41fDNO2O+ffeIbWtoe8MPni0RzpLEAW8djDjdtFjrIaraOrTx8PWy7dm2Pv57L/frq3FQa0eoBMbCpjVEyqKEYt20LMoWhoKjkhIlHVkUMo4DklBS95a6tfRtz4dnW1atB3ELFGkkBy6HLx5ZIMYz9pIAjPFqpNbByEFvPaMoURBHsFn7fzMKoe590+LV8WWb5SlwOB3jXlKp/934/Rs3aqBRHDA5CGm1GeaDL94cel1a2k9erHm0m5EGwS8pjL5KINCNYvHOLOVysHR2xvHde1OqznMqO+3YH8e3TfNXVU7PFj5l9P3zgnEccDRNCKXkYut5rqPEP299b7guGvZGMfsTb/6pteHxXs5e7hW+UsrPMGh7Y1lVmke7GQ44XpSsyp43d3N2xyHn64ZJ4u2vXkruPk2lFIJIytsz0I0lLg4V2jlWjeaiaFnWPW/uj8DC4TSl6wyLuiULg1vI9zwLWVY9VddhHdwbGvTPrkuOFzWjJORolnC2anyjYZZwufUponvjmKNZQhIHVK3m7izhpy/WnK4bZnmEcZZ17dMo69ZysqpuE0CVhLN1y9E4ZdtpjiYB71Vb7kxjVmVP2xsP9u4021bzs9MNSgge7WYIAT94sgAEYSD4xemGouu5O8lYVZpt2zNPfDra4TjhZF1zvqnRTnB3HFPUPSebmt08IVCSfOvn050sII8TdvOIp6vKc5XsYEmMFK1xfPvuBGP93ujZqmE+S7kqO7T2Z8h17dNRpXBcbFoC4UjjgBfXNSr0DpG271mVFud8kb3roZWaSSxIopBRFHrIt/OFI6+n/e00fLe/xg/5vDNEKr374csWj2LgYObFHEpAHHz9aY5fVwHpD27cTK6B/DTtxThIAx9F+/KEeLqquTsoh16t4HXaUrT97aQUKS9N9TGyCcvKP9QnneFPH85v/30WB/zpwzl/9WxBIAXG+YdNCcGm9hPk3VmKte42TS1WnmPght/bG0UIJzjZ1Gwq7eHTYQBS8LOTDTt5yN4o4Z2D8e3PfdnrbIDDccoo8cqdXnto9uHk9dBwJ2A3jwapoLc07GQhnbUECJzwCVYdjqdXBeebhquiZTeLwAnuTTPmo4iuN3TGEmjBPI+ZZhGX24ZREvpkE+n44GLL7ihGCsGm6Yik4mCSghMEyktXnYNvHo2ZpF7C2mrHLJUsq55p4nke16VPsdnJAsreIAS8dTjmctPww+PtUJwJeXMv91HAoeBkXfPm3ui190BKwdE44cOLLSfLmr1RcsuROt+2NNoX7+pOc7puOdxJUQ4sgqui5WCcECtFaz3878OrLZMk4tFuzuPdnGeLksd7GedFy+my5ul1xYPdjDhQzLKA59c1O9bibd8OKfwCe3+SksX+ca5azU9PVvyLj65oOss8j9gbR0MaWc/xsqTSljuTmIM84qrsqFvDjy9WWCEJpEBJRd00REHIpulYGq9gWrYaV/cgoG79/TzG81LiEE637SDxVUQhOARh6JMp1jhEEJAnkqp1LKqex7s5Xa+5Kv2hwDq43HaEgQThF5RGGz6+LmmMj5fW1hLhNy/COZIwIIwEppO4HEaJL3L1xmB1wItlO8BkHVkYYJ1nYAxJ07fciQC/qRf4hUfgC0aDE25wwX864f82quZPLkqqrmeSRb+Fn/Zrj5vzz0oI8V3gDHj8u7ucrzaUEN4O4nyBVuDVOHkUM4lDZml0K9f/4GLLddWxrDo2TY/WjnfujPn4rOB81VJ1lrf3R8xyHwHcakOgJL0xnGwrLrc1cRiQDgyBn59tGachaagwzvPeVKhwxpCmPgFxbxwzihTWOLSzrFtNayxPryueLgokPo0lUpJ57rlJVac51zV1b8kSnxiWR4I8Dums48P1lihUCAnzNGbd9HRDSpaUHi6/bXs2dcuy1Ty7KhilEX98f07RaJ4uSradZk8m3JumXG27W36ekr4Yc5NSYoWHVlvrUIGkbjVnm5ZxrFhW/t882PXFl1BKBI5V4aPn8zjw7AznUNJ3Oe9MUvZGMWXb83AnR0iJwhegjNbsZBEH08QDOB384HjNk6vCg1QjyeWm4nxds6g6Dicp0VBIeX5do41llAYYC4uyJ40kWRzRa68+/s69CSerhqo1rMqWO3Nv7z7f1OyNY+6MEnrreLSbESk1sJy8kudnZwWtNhjjvAq26ikqzb2djG3f82gvJS+CwXYgKaqecRZytJPx0cUWY6EfDqKXm45ZHrEq/dz5aD/BGrDOgIvZHydclw0HRxPSUPLR5ZZRqDgYJ4RK0PS+WbFte358svb3bBwzSgPy2Bdu5mnINI1oes3OKOTytOBsVdF0lv2RJIskzxc1zsGzVcWz64ZpGvJgN8cYWBUNfWdYVZai7lgVPgb6xSrgcJTwnTsTemspmo5n1zWjNKBuDY1xLLYdle7pjSBV0FnPt3trL+fjq4pto72tXQlOlx1hCNum5/lVxXwUMYrBWA+AnWcRe5OEREpUKFlVLdtWEwaSLAqpus7HHzvPNJJOEErhPycxhHYqkJZblfAoDanbnsNRxLJuiYIYKyxl1VF1sCwtevj+9+b1xaOvMrIIslixbQziD66N+/8/41U1UBoFlO2vVgN9kdcQ0icvyuFQ+KrC6GW2Ud334LjlLf2q8fK56N4spe411kIeKkZDaqUQXkn4umsCeP+sYJ4pwFF2hr/8+Jo39lK0FbxY1xxMElZVzzgNMc6rbD0DTVJrzdF4wtv7Y4T61YlvQgiKpuf9i4KmM5xtaqyDdd1xsW1593DCG3u+qLMqWoQS3Jmkn7knxvhi8DQOuC46JB6afblteH5dcm8n8wERq5q615S95Z3DkQ8BEjBPQ5wIuTv1in/jHPemKc9XFaPAn+V2RxHPr0s+uSrIw4BZHhMpf97KQsX5quZ83dB0mjvTBIlk23cESmAd7I19s3VTdnTaK5Yvi455HhGGksOxT0n74LxEKUEUSA4nCS9WDYeTiERJqt6ybTTz3LNmtbNstz7xbxSGNL2h1l6FWjYS6yRFbemMxiLRfc9V1dEOwRVZGHrcShoiug6jHaGAtjM8r0qKVg97ZcfT1rCpeorWFx+vipajccK9nYTTdT2wgAUGL4BII8k48c/GWdGAgAezlPfPt2jrGx43Ck3roOkcKvPNAucsbe+h2/ApnPomzOAPdXqs7Jcr1NycXcYJGAI6Y0hCvxf8nTOQfsX4g2t7vDyR2CEB4e7MW7denhC1dRwvPeMoCtRn1Eh+svVqI6GGyTzwnYJO+yjELAroraUcZKbe6uNv1ygN+YvHu5ysah8PWfWD9ch7Ss/WnplRdz7K+GCSDF1ZnwI0jgMmWcDl1nE1AJXjSPO9+1OOVzXvnxd8cF6wLDv+9PEOsyzygNZZ+mnRx3mA8iQNMFbyZuZTWF43lBCkUcAo8ZvaG+6DuyxYVj2jxKfnNL2HtD3ayZF4b6pQkCW+uJZEAU3d+i65FNSdptWWNBA4BJMo5Pjae67BL1abVpMnkge72QCaDTicxLy1P+aq7EiigKrzvuWy6nh2XZJEkgdxxjwLvVx12zLPY1aV377dm3k7ShZ6IG0USJIw/gxz6tXR9IarsmN/HOOcQA2fe28sZad5cl3wYJ7zaMfDZo2xLNuep5clznkafhRIXqxqcLCs/eGz6jV3pymn68ZzQOKQv3ic8a27U+IhIvRnp1uyyEdLt52h6iw7eUAc+O7Ow8G29tefLPjp2RpnIQoFZysPVb87zXh/teWji4JAejBoKAWOzsckK4lSijDwHftYZUjhN6jGWh7uZYQKTjZeXhyFkrbVHK8bJomP9BT46Pmq8soHi0GKFKMdAkEkYF33SKTvXitFIARv7gm2teF87ZUBSehLNVdVRxIq8sGKeLFqcQ62jcU5TRyGBIHAat8dP5ylSGcpmpZlqamxKCWweKvoKIkIJZRtQCQ1285DsQM+q0J6uXPxu7Q2d9qnQ/2BjP+tEGIO/M+B/wswAv6D3+0lffkhpeDePGNZtfzrJ8vbtLK/eGN0a22VCNrecFV03J0mbBvP/zLOJxTujCImxvLtB1PSMEQNdt/ni8rbWowlcAqHYDcLGWriLNueZdlSSB95XPeGKIR7uxldZ0kjRdNrirbH4QiV4mxVc7ZpBstbxotlyQfna+7MMh65jCQK0cZxfzfn4SxDKUnVaM6LlnWtQTjGSUBvHKFUTJKIOJAcL32TQFswxnC2qshCxTQNvAJH+GJ7EnqFZawUd6YprfZ8o03TYYE3DzKkk+yPIn70Ys2Ti9LP+cbx7LJgsW0YxRF/9niHe/OEn5ysOVvUBEMhR1vLddXTGYMSkixRVI3BWcmfPdrhaJZwvKj4yYuWJ1flEAutyGOFiAPePhgxTqPbhszxqmIni+msZVNp1g72RhHbVlNfFlyVLbPUA81fLGqQEAq4O4mpBzVr3WlCIdhUnnkjBAh8ISaLFL12nK9rOm2ZpAEnq5a9m1S5aUIgBEeTmE0jWBQd69orIi+KhlYbQiGJw5Ak9AXz59cVowEuO4kDllVPFkm/oXaOUAru76Tc30l5/2TLJ2cFz9cNxlmUkENnWuBGgjhQPNwZcbmpWRUdh5OE+7s5kRScrBve2s98ymqvuSwb9iYRbe8Lppu6Q0rJ1cYzg6zzMd0n64amMySB5K2DCXXv90DWKp5cVnxyWbBtWtIgwDnLbJxQ946+6Lgz8zZjCyzLnjj0e6Z10dEOTK5IOaZ5yt4oBAKc9RySOPTqbWMs2jmks1xXLb127OYRl2VL3Xm20d4oJokUcjh4F31P6hRJGPDu4YgXywbrDOM4RqReHVLbll5bZKAwnSOS4IxP8uwNhApwPmFJSUHVOaQI2MtDkkjxXqNRytLrW2QLgYTA/jLv6Ga38WUOOmEosHh13dd9OPi78fWNr6IGenncBNkIPrVO3Xzn7OCmeN1rJqHiYOxDbZxxnG0a7g6Ig9eNz5yLnEUKyduHIz68KAbWjAdBvy5cxicTa3pjqXrBLIuoO283y2PJd+/OiQPpG6l5TKcN7x6OWJTeAXJdapxzLMqeTxYlj3ZzwpcSaG/4LfujiOui4+dnGwTeWreq/Tz85t6YPJVI/DnrbN1wvm4QwquJHuxkPNrNb3lPd2YpJ+uastWMkoAHOxn35imfXPqEyg/OSw7GIY2BHMGTy4o/ujfxTNlZShwqb61eVFjnaLWhajUfnhdIIchDH1pT9xYjHNPEJ8NVneayaBglHutQBgFCKiaJ5KqCOFS8sZuzP6Qq39vJyKoeKUBJwbbpvWXOeMXwd+9NyOKAXhvONy1In5QdRwHb1s/NS2e52rZEgSRWkjjwica+serPHA92Uq/O1R3HixZnLXkWUvd+LZylAZ1xfPNowo+eXfPeWUmgBEdFRxAIlPC29Fr7Qs5PX6yIAkmgFFkUsG17ZnnIi0VD33lVaRoFrCrPNa07xzTxVscHYcaTRc1l2REqSRapAb7u9+du+C9REXdmMSeLGmOgfsW2drOn/6oFpJedCa+OYPivwfOG/rbGwM03+ebavsyu/ouy8UbKNzewIAPJ/ihknkXsjFPazn7tTYYvXEASQvwj4B3n3D8TQuwDI+fcJ8Mf/1e/3sv67YyXwXEvA+luJkQpBKermigQjAeVycsS0d5YZnlIEnm5pBoeyuOVj2mPg8Hrum442dScbhuOJgkPdvNbq1EWB7y5P7rtaBvn+PBiy3tnWwLprykNFeuqZ5aGJKHicBxTJwEHo5izdcPbB2NGSYhxhpNVy1XZcbZpuTdN0BY2jebHz1f8+eMdv0kdEuCkEBxOE5QSdL0hCtVnksdeHS+DpPveH0DuTn3KTBJItIGjacwn15o0EHx4WWCNpTPWq2SmKdvOUNc9OMGfPJjzs9M1/9l7l35iCyX/8O0dEqXYGyU83ElJ43CIp9Y82E3B+Xjsb9+ZUHTGA8sFbKoWhKDXhsuiJZKSSeYhd0VrBnaPYrIbcrZueLGseLQ/ou+tr26bij++P+XNvdEtc+plMODN5u9Grnt3mvH3Hs/54LJAG4MSgmka8vPTDf/io2vuzXzxBeGoWkukFDujmLNNw8XWoTU83Et5culhpz9+vubxbo52kPSGnWHzu5vH3J+kVNaAhLIxnl/kfOESAVHoeSv9EGmq8TDtaRZxtqop257romFVNHQOdvKEWSapGsMkDfj7b+zwg2dr0sr/XhhKFmVPpAT3d3PmeUjd+ejwsvV2jrLVBL2jaC1H05RZHtMPTCWFZW+c+GtyjqruWSmYpxFhoBgJDyMsW80nF2uyIGCcR+yMI4qup+g0oyRCCoHRjs4ahFPkSYhQEDiJih1ZmGAspLHiLx7vMM8SfnGy4i8/XqCEVz0459i2PTtpwGIA/1knEMqhe8+ueHmBuSki9fx2WUe/ahgnvBrrD2A45/53wy//OfDmq38uhPgfOOf+49/uVX21ESnJTp7wX//WIWKwAzS9RWuLE3x2kx4FvHM44nTVsKw0RLA7SSibnp+fFkShZHyleLw7Yjby6WP70wypau7PErQVxL3vwDljyWKv9HDOsahar8LoDFjfucZZ1rUBIZhnPlXmdNXwYCcbLLwh33+ypOktP3i24t07Y0Ih2RvHXA28Pm0dD4fY+E1nSCPFSFukUGRJ6BMj90fkkQc1l62h1ZrTTYuU3uLwfFHTdh5+KaXg6aLk7cMR4yTin7x7wMmq4mLjO8LTKMRKD8y+XNeE0qdHBYGiah3T1G+KF4VECcmy6bkuO/JQkUWCqvPqw/uzhDjwYNVv3Rtzb5Zytm14el2RRF6de7puOBgnfOfuhIfznCCURNJbiXtjeXN/TBQo3j9fs6kM206Txh4yXWpfVKpaH+yQRH5NX1UdF4PqN1YKKxyTPCKKJNvGcbVtKJqeSME8j1hXHRebhm/emxCoHCEcXW94vJMTKYlxzlszcDxbVOyPI9I4YFV5gK3Dh14UnWG1rKhaw3fuTYmkt0JqY+i19A2CbYfZNPzRvSl5EqCdY1t3hFJgjaCoe4wxPNjJkdJyXbTsjWPu7cxpGkMzsLycEESBoNVwsq44vi7ptGGShBzOU5reMIkD8iTECJ9gtpv7plSoBNeiY28U8+6dnKJ1OOsPVjujiN08YZyGXrncGqZxgAoEB3mMUorTTcvzZc3+KCYOJDt5zGXRcjAKeWs/572zLau6Q0m/riWhxFmvqD2cxiyKlrbvkEoSIAgiiXSKLFRo6QHdRWvYVj2ttVS9xfSe23Q4ibm3k9Max6buQFqyOMJZgxTesqKtowNCJbBKMIp9w8QYD9NujGY/zUgTb6W7LFrGkaLuLEX3adc8ZOgOK2gGJdLNQcLh7Qr1l1h47kxSskCxbvo/CAWSEEICP3LOffd3fS2/zfFq0tkNGuOLMEleZgz12u+nwwEH8d17U1ZVf2upPhjHHs9huT3PPF9UrOrOByA0Pb22vHM4/pU/+9Um88mm4dFuduuyWFWepyPlL6ucqlajjeF8pUljRS8NeRJyME7YyUPOty3LquXJZcHj3Zx370x5dl3w8VXJ4STi4W5OGgYsy45IeXaslJ8NDxJCkMSCJFDs7kdcblqq3rNfd3PPTLquOpKwpTX+oXDCv8bFpiYQgjf2R75hKgT3pinOOqJAoqSgbw2h8tbli21DoATLqicOFKuqxVjfyNHG8nAn52pgRkkhfQO0tdyZJeih2XxnNuYoUjhrsXgea9H1NF1EEkl643gYhzS99cX7UPHtOxOyOLxNBl1WPdM05LpomWchP3mxJo8Uy63gwW6GQHJVehjDZdkyiX2y3N1pzHVR88nllk3de76TDWilYdMYjPWKsjQPmYcKZ2GWR0yzwO93HEzigKq1SCV442AEznK2qfngsmSSBzC4RP6vPz7j8W7GNIvZyUKmWUjd+fRU7aBoel90F4pOa0ptcM5QF5ZGa/bGCQJ/5nq+qLkzjRmlitXW0GmfWDrLLEXrCyF2sMnPsoA0CpnnLcviU37pzQgG28CXVX3euA1+1XSc4BsJ2kDyBVhLN01qy29OcdMasAamMUzjiEkSE0cBe6OQ2Sj83SiQhBD/C+DPgXeBf4ZfB/8PwL8N4JxbfL2X9dsbr8Zlvjwhdlr7h3uYPKUStxLRTdXzo+MVZ+uGSEnePhiRBpIni4o08lGOp+uGjy62KCVJQ8Wm7vn4ouDRquGtg9FtJ+Dla5BDl8EOBSk78IVmaUitjWdUDOqYs23D2abh3jzhcJJwsW3pdM2m6RjF/hqEcEgBz1c188stq9pLJW+Sbs43DYEUHnA2FE16Y3+ldNRan0LQGuvjM4dCRjYogKJAYYzlb56tCANJqy3WWsree5unaQiJr957n7Lg33l3l6tVy7rVXG818zRiJw+RSlK1mvkoIg0lu5lPThBC+A2gdSzLjqtNy5NF6XkRjWZ3EuHcp12RbTMojuYZ14UHgJad5iCPaI1jnPqo+iDwhZPHeyOa3kdrd71hUfXsjiJCJT1jJ4+oW02ehD4C1FiyKCAObjqQ8LOTNdMsIJCKN/dTto3lm4djnHRM45Cfnm64KjruzVMCEXK+aTleVfzp4x2utx3PF7VXrDnHD49X5JGi7Axv7We02ieeSeHTm26Knjfe4yTwSi9jLFL6TbFxg2xaG+pVRVErpJIUjebuLOfPHs9pesMPn6+43rbESjLNPXRvs+15cOATHtZVOURCS4qmx1jDTp6yqjvGScCD3ZxNHbBtNHEUMEt8Z/loHPPNu1P+1ccLisH6tjMK6a1jOvLqu1JK9icpy1pTdT04x/25947vjmLWlSaWCiv9vZ8nAavGEEvF06ua0f0IJwTzNGCWhWx7g9UWYyxF76POrTZcVf7XQSBIraPqPcOi135y7xnS2vj6rAZfdczSACX+MApIX2D8U+APooB0w8jL4vC2wbCqO55cl36+Fl55sZOFHkBvvAqgaCXbtmfdeCVRoCRjG3K87Xi2qPjugxmRVPTGW4XjR3O+/2SFc455HJDNMsQA/G+1pWwsodAkQcCD3YRISi7KnlkWksderZqFip08ZBT55CuvTIyYj2JGUUAaKpQU/OD5ilh5Vc/uKKSMle+iVh13pgk/Pl5TdYaq7ZhmMY/zEWXrI97LVvPtOxOeLmoC4Q/4z64qWuOYppK3D8fs5AnOOu4O4O9V3fONw5yPLks+vNoSCMmfPZ6xrHo6U5NGljhQFLVmloYYbXm+rImVIBAOYQw/udjy7tGYtw/H1J1mloR878GU+3OfOnW8rHi+qNHWkUchYNk2PY92Mu7NMhZ1j60+ZRlGShIG/n0v6x4pfPd7Nw8xwCfrLXHo5480lJyuGg4nGaM0IlYBZ9saJSoCpfj3/+IB719VRHOBxXGydJxsWjrrQyya1gxcii2jJOSnxQYhBJM0YpIEPF/UfHix4eS6pmk10zzm0W4+hGp4S/TBKGRbBbydRYzjkN1RzFXRsD9JPONKSkZRQNV5mLl1MEr8WrwTKzrrcFYwjhV35ilpFHC8qBgnIYFQWGGZJiFxqBA43jOOuvcWvOvC84JGcchi24BQvH2QYq1gU/U8uyrJYsXeKMbYiFpbpFRcbDoQgihUzNMYZyGOJG9MMp6vKiZJwDSLmWcBF9uOutWsip6TZclxEvLmfs6fP57zyVXJTu4bCau65Wrbsql7n2YqYVVqksgrkGZZiHGgBFylXvW0m0fsZimbpkVKycFI8t5FS9NZokgRJsqD1vOAbdWxrrSf9wMJ+CRYjGOeSXYyv6fYtIay6WmNJZSCSRKyP/LWgMM8Y9F4ODwCFk1L1X32MNMDW+030PDLXfH+S3Ytniwr3j6aMIm//ojm38RwzlkhxA+FEA+dc89+19fzdY+/LXzndQ3rL/J6n2EMBT5d+N5LSI1J4teoXtvPNIePpgkC3zAeJ8Gt8uli2/J4LyeWr1chvVysuSla7Yzi2z9/1Xp3o3J6dl1yVXYcjmM+ua4oG4vD8b0HE+ZpxKL0zYSrosU6HybwnbtTAumVMIFSRIE/t8gBOH5TDHv5HpSuZ1sbXwDCN8GLWiMlCOn5pEKACiSitwSBRBufeNloz/PbGxhOPkQHam04Xtb+uS073j0cUfZmYJe2FI1hbQelVNGybnyS6Yt1zZ1JyiQNaY0ZClwOJaWfjPChF4G2LGsfvPOtozHvHo352cmGPFZE0gcB1J1mkkf8k8MxeRzy4rpiZxTyYJZjnOMHz5doa7laN9yZRARKUnSWnx5vyNOAaRKipGASh1St5q+fLHHWMYoCHjxIuSg66s6yaXvOlxVV17OTe1VsEiouip440BxNE3aziINxCsKRBYpNo7Eo8iggiwOOr0va3jtBAuXVt0XdI/CCh1XVe+VX4Chby4PdjM4aJllI22nCUPKtoxHGOn5yssFYwYOdlIt1Q60tSjrKThNIgXU+cdta6DqLxN9aDVS9DzSSomXTOP8dEP78fDOqr1BY/9tURwI/f08y2MtDTlY9nf3091/l2CV86moww2t/lbTNXzVexmr0w8+ZpAGH45hJFrKXe7W4+hKKxy86vqgC6d8D/i3g+wDOuRMhxPhrvZLfo3Ez0fdDASIYJnovyXaY3vKTF2uyUPHWwYin1wX/+YeXvLGXcb7teOdgxCyNAMu//qQglpI+i5ADPLVoewSfVTPdDON8ws79eYoQECkfFQ03SR6Wq23HnWkMCHCOn73Y+M5dKHm8m7FpNedFQyi9R/Zs07KTh+SJlwpel91gD4OTVc3j3YxRFlE2Pd9/tmQ/j7ACHswyRumndraq1Xz/2RJtDetae1lk1bGTRfRaI4QcgNWCLFYsyp5N1YHwC9ez64p/9M4+0zRCDlwO47xksU4d83HCddlyb5bx9Lqm730U6KrqyGM/OVpgkoRDXKZPaUlCyZ/cm+IGO2HVWI6mMetGU1Uecro/jomU5M40oe40WeRjnau6o+0tB5PU8y4S33n48fEalAes7uQhZWvYzxWfLGtO1xWr2k9u92cpZoB5SxHQGs3ZqsVYn8AUKUPZefnx3XnK+aYlChSjKMQaT9xptGVvFNE7S9v7CfzDiy3zLOLFqqFqNU1nCZTjX3x0zTuHY5Io4M409mwR45hlIWebhsttx7bqWBQNTxcVLxY1++OIWebhp4u6J1aCspbsjEK++2DG3WlMGCgWZce370+9wqHS1G3Px1eFj/VsGx7u+K5VHEmut17pJvD8DWMtrfEAxke7GVndcziOWdVeu99ZQ6MdkzxmfwzLuud8XfsNg5S3Hd1JGnBvllAOcchC+gNfaxxn25o8DVCNZRJFtKbncBTjnOF822KfrwhDgXHwbNUgnKPVvqhmrCUIQ5zzKT7WgFR+sUm8qAOJj+PMpY/+/Don+a86ktB/7/8NGX8wb0QJcZsGhvBzf28c3zj06pWy6fmb45W3x2pH3Ru+fXdMGPgi8/PrgouiIwsD7k5TLouGsrNUjSYdBbx/tmUnCzmaZPzjb0Z8clWQxoF/1uqObS1Y1z3vHGTEoU+Ce35dMUlDNpVhJw/pLUM3Gr73cMbxdc3Tq5Jtq3m466X6SkmmScCHFwWTRHmwcN2zaTrmWYTBd9CUhMNpQigFRee/+cu6IQoUzxcFi9J3ue/NUvI0pDeOe/OM+8IHCzSd5UlVMElDkji4ZRI9XzVIBJEKmKYB29oDsqNAMs08w2+c+FS75+uGuu0JlGKWBiRxxCTphvcPbx6MCKTgjX2vuAW4N035KC+o+54wAGsl28bw8WVBYyz3pylRpDDah1A8mGccjGNOV5Y8lNSJRKmI5wtvETucpiSBIgkkTkiioB12aJaLsvF22ihgloccbxrePsh5tqh5+0AxTSI+uS6Qwlv6ml7zi9MNd2YJUdGRhJJ11TGOA370YuUDNKKAKAx4sao53/p1o9OOcaKYZQk7o5Bt1bE7zggDwfm2YV337OUx1lmyKOLuPOH5oqZsDXFk2NReARMHilEYgHDM84A7E5/eGShJoLwCLA8l16Xm3aOEZdHz9v6IZ9cVJ4uaqvc5YteVoO8Nd2cp50P6TtlZys54e35niaRgb+wtZu3AkxzHimvhSEPFo/0ROMF+HpOniiwKabVlXRXsjxO0tQjpo7jvzRMuth2rquPD8y3jNKBqLG1vuNzUdFrjhCAQgr1xzG4WUksBzlK2mkXZc7lpBr6GY2/keU6bqicJQ+LAoZTEWIc1luui9/ykSIJRKAzLwicQRVJhnKDqYZaHpBqWVtMbQxqFjBJFFIQeblu0nK3rYf7wIRg3qtaXzzAW35hQ/DLk9eaQ8UXPPK73BYLrIQnxD2TcAX4qhPhX+CA7AJxz/53f3SX9+uPVNLLXhe+82rD+vPG6JLWbJvLNzvwmPe3Ftv0Mu/Vs3XhGDl6JrY238b88Xi14vQ7Ufbb2VqtgKM4Y4z7zXbPW8XxZcVW1bBpNPJyfil7T9T5FNpCCDy59wMPdecq21lyXHT95seJoEjNOPaPzYtNwOPFN0RuFkHF+D6ekn1OvK2+X+s7dCR9eFtSNYZqFlJ1P7dzJYt46yL0SZQBKr4Y5Mw4Uzlj++tmCQPhmytEkoWx8AeogjwDHttF02jJNIt4/39IZAwgmsaQ1fk4ZxSEXm4bzZU06FG/aTrOoet5IQqJYoiQ8udzyxw/n3J0mNNoHU+RRwP4kZl317Iwimt6Cs0gEsfLKSYMjQnK68QiKTy5LsjjgF+fe9RBKwZ88nLM7jrguWvIkYDePyNOAi3XD43HIutScrmsutz2BFGRhQKAETdOjlODNvTH744gfH6+ZJwqlJNIJ1rXmzUMfPqOtQ0hBLJRvyDjL2bZGSMG26hhnIdsBgfH2nRHr2qCtZZoGzIOQstSMU8nV1p8ZQyVxwO444WiakMUBl4PSqogUeRwglWQUCF6sG4rGUHSOomnZdH6fnkWgtd+3V22PED44p/OmjF97oxnilUva/TK82uHPBk0P27rHwm2qcxB4eLVwsB06BxaIhU/mdHz9PKZXX0sC60ozznqiyu9ljHacbVoe75lbVu7XMb7oK3XOOSeEnzaEEPnXdgW/p0NKQSx9p/Js3bCp/SK9O4r4ZFl6z2zss5F8iodPI2lazftnBd+8M2bdGIQUFL1B1y2LsueN3RwxKH56424r7DeTuBICpSQ7uVdlFG2PHhQmSaSIUZyta352tsVa532uoabsNaebnm/dmfLOwZh5UvBkUbGsferMWwejofrf+RS2SLGo+iHGUrA3sj5dqNOcbar/H3v/Eatrmq5pQtdrPv/b5beLHTYj0hxXrqua6moKqRv1CAYMgAmm1YAwaqlHGIkWPUBiQCMEA4xaMGBCg6BpJLolqIbi9KlTp6qOSxt22+XNbz//vYbB+++dcbIy80TkiTyRWeKRQpmxYu21vvXvf73mee77uvE+gLj/7gdH7BUJxoR0BZynNwE2bp3nYlnz5LpkMI6TWca2HTgcxzRDTttvSaYZXWdACM4WNX/6csXfeGufPNHEMkhGe2MRQoTYa6V2XdLw2qwag5KSPFHEWnK6bJll8evN+sWipupMACkrQR5r3jzIYeeNDs+ToJUMk4MmXI4ORnFocNQDk1RT9cG7/MOzNefrhrZzJImi7Q233jNJLVp5PrxcA7BtApRunsdoKbnZdKz0wLYxFIlkcALnHc0gaPuBSGskAWJ+UMTMsojvn28QeNJIsKpCtPCPLrbEUrJuDYWWfHa55fFhgfACs1t5EimJY0XZOt4+iClizemqIdaSg1HM7358zbbuSbXkYBTYJm1vWDaGkZZYB9ORZm+U8MY8ALvnSfBiY4Pc93rHx7jaBrjg1WYgjzq0FjTdgJCSB7OMRdlxV9ZsWs/hJA6gQu8p2wDXG2VRSK5qh9e2uFES0Zgg520GyyeXG4wE6cPmte0CR0sqxYNEgY+42w6cTFIGYznvDIuqZVX3zMaeYXDkqcaYoNTQWiCNQEuF9yYcdgRoPJW1lA2oCMQQktzMrnkU7/zDxoR//8tKcPh55bz9NWq7/Ln163PFgZ1dNqSJ9CZc7N8+GKGV567u8d4xTgPw+sWi5s2DAi0VT+4qHu7lVINlLw9rlUJQpBoh4LYMbLvOOiYqAK8PxmlQm44D7+zlLs1EysDlu6u61xZprUI6otYeZSQHo5TjccpbeyN+59GMP3mx5Pldw4WqOZqktEKQKkkxyXi5qOiMpR3s62Y8hEtApRSf3pVM4pDEcrao+PSmAu+Zj1IWtieNJe8cjRglitYE+LUHbsoAzT5d1oxixctlzdWq2dn9JJu2D82TTDNKIyaDIY81d1UHPhy0/8abc5Z1xyeXFddVTyIFg4PrHUvoeJKQyLBvQLiwXZcdygeAp7Owbg2zXDMfxdTDwD950QYmgA8NwWankjXWMVjB1aoLyaWDY2F6TqZhiDFKIgZnqQdHEgmu1oZJqpnnKUoKyt7z5KriaBTA6q2RZInlZtORKEEkwwH0dNUCYJ1jnMXsjxLETtEFgXXx/knBbRXx0cWa752uGaUxSgpi1fDN+xNuKkOWDJjWMUo0bz6a4Yzj4+uScaqIdEwiJTpSCA/zIuF00XBX9rSx5eE88Ib+yfMVB0VMogUfXWz4gycLDvKEb9wf82Ce8/6R5tmyItOS57dbWmPxfjd9tp5yCI3SqrN4B5EWzNOIZ4uK+5OUeZbwwcmY67JnFEmyVCOE5GJVB1VrpHh8UPDbb8zZNAOfXG9e2xHPl0FFBnCxahBCsNh2vFzWbC+CpXtSRDjreXlXEUdh/3p2U3O6qLhYdeSJpO0tN9uWRd2RRJJxrElixXXdg3GMUsmmsxhriZVnnCVgLULJwCeKBHUP3sPgApdRKU3dB3tONwxY69FSUERBTQY75dO2wlpBZ4OdrGp+voL1pw0oLGFi3XzBJaqxcFf1LKoe6/2vSyrO/+jrfoCvun5aGtlPGxB/2fpJxlDVDlyuW8TOofCqSfXTGk1tP2C9Z5Iqnt7Wr6UK7xwVoen/Uxper5hKr75OHCn2RzGbZuBy3bGse2Z5SAl+vB/suHVvuFq3jFNNHQfHwdmm5YPjEdYFZs+i7rnb9kGl31nyWLGoOl4uB5QUzLIYL+Bm25FGA/dnGfdmIRG57gzPbivK1uCFp24MaaKJZpIH0ywoyaVEqnCviqSk3a315d3Aou6pGsN+kdAP7nUwxuEovHbPbkuuNh23ZYMQEimCLb3tg8JmbxRRd0GVqLVA4KkHw+2242LdcjiNmarw51oBeSxpjUPaAO7+5Lrk+aImjTRvHeRcrgPHUwrBJNU476k7g1YRkZR8fFWyrFus9UzyhG07cLoMrMG6G0iV5Kbt6bzgu2cb3tzPmRUx8yxinkV892zNqh7odsEIRRLR9CakFmvBugzw8HvjjFkRc1sOOA9Fqni0X3C9DoorsQtuyrRkmgQAd9UbkiTlN9/YJ9aaP36+QLRhiLQ/jfnh2YaqNSRaUsYhffnFsiZNI8p24GSW4W1Y5xRwPE4Zx5oPrzacr5oweEhDA+3NgxHrbuD5rcO6EBLgCQ0d2RMGRgLK3jHOPUUSsW4Ng//xkfnnKYl+XnXwmrX008oBmyG4FpQKa7kF/G5RF/wY3h3tmkfhHfTLLUW4x2RJYEulieKvvLHHbJQQ658fEPWL1Bfdb/5dIcT/GpgJIf414L8K/G+/kif4Fa9XfuBni4rHe8Gfuq46nt2VVN1ApBRV39MMliIqeLBXcLmqebGokAgOioSqM9SDxRlP3RveORyHhA/rKHfR5B5eL+KvOEPjWCEyzfE45a7qgwTVOLatxRoLSlC2hst1x9tHBXsqIVKST28r9kcJaaT45v3ACrpatTsbD9xtW/6kNxxPU6xz/OBss+ueCq7WIT0uizUez3dPV/y1N/a43LRcrMP0E++Z5jF3yzYstolkfxzjnGdT9QgEj/cyPrkqqZuBznjePx4htcR79/pNrLXkOw+mfP9sHVg17cDj/YJl3WGMJdYa731YdGAXT29ZVu1r+Ku1P94QRknCtu2puoTvnGScrhveORwRa0VvwuH+wSz8bMY6FnVHESvOVk2QuE9S1l2YfOZxxOWq5tOrLdvOsp8rnJfM8ogP7k/48GJLM3hS49jPFfdmGWks+OHFlsF6siRiGCwIz/W253feyGl6x/44RkrJg72Csjf8o6cLllUPHh4fFBjveH5X4pznU+E5X9Vs2oE3DzKUkrTGBsh2Gr+eNKdztTsESG6rlkgLDiYp12XL6bpDAcVhzjBYOul592jEyXTEph04WzV8dl0iPTTWcTyOuVh3rJuOqg+APuM8vTE8udvyYJIyzlOUhKZzaK24LUODcFkbNvWGUaaZpjHNYFESyi4kRpV9T6wC6FsKGKea622LGQw9nsM85mJleLRfEMcJOLjZDkgV0qis9VxugyKgtx6hYFu17I9DMlCmNFdtHWC2nd0dBCRl7TA9bIewiToRIKZ+NxqOgCiCea6pB8N2CAujVCDtl4/P/Cpr01mM+brbWF9Z/dq0wgYb5PexltyfBkvW05uKs1XD8STh5W0VQJWq4XiSomSAmgopsMaSpzGHo8AcMg565znIY0ZZxM26Y17EPL2pqHfvU+fhtuy4P0vRSjCKNL2zLMqWLA5xv3ujhMNRQh5rPr0pmaURh5OEb96bUPUh3S1LNJM8prsqudg4bsuBD05GzIqIF3cNHkHVBuXnJ1dbxlGEJdim7++lZInkYtNydl1zMs95elczSiIiGQ5B3z/dcDRO+ebJhJNpSId8sWjIYsU0jwIIvOmxztMax2fXJW/uFewVCauq4wdnGyAocRHw1sEopGKNYq62PYMN+1Cys0bPcs22MbTG8gdPLP/yd044XTfsFzF3VeD8vHU0YtMZqq5nmgXA8pPrihd3JcZ57k1TeusZJxGraY+X4cK3ajvWdY/3YZ8XCJyDb5yM6QfPsun5xnFKEQUm35PbCutgnMRM8witJUpJbquGSAp645hlEYu65+WiZt0a8BBHIXWy7oYAPwXuyo5VPVD3liJRSBHW2SJSO2t5T6oFD+YZ7x2PkMBNafEYjpwHKUliSdVb9mPF4STjjXnGjy63fHAyQQvBsupZbBu0lORxAMSO8ojf/dE1jXXM84goFkH9tGqYHE+Y5zH/uO4ZnKfpLaNUUfcuQNK1oO0dT25KskghBIznOXmsuVi3VMbRW08Wg8vCZDnWinkW4QQczxKaIUCut03Pi9stzxcV/e2WURSzV2jySDN4uLirySJBphVXfUvfB2OAUoELN06jcJkYTHj/aYVSmkVVs6gGRrEkjqOQ/lYPIWmpHoi1QjjLXRNSqR5pTW8BG/awrg+208E58kQH9VEz0BkHwmMGR7+DaF9XjkhLIq2pXQBlC2Fp2nBx+FnNI0GwR7+6dHy+DF9O+SoJ6UNXmwZjQiT5r3p57/++EOIxgan6/xJC5Pzsu9qvRf20Bs7nE9F+0fpJxtDluv0zCIpXTaqfbDSV7cDFpsXiuasG5nm0W3M9kQxQ/ctN+xpw/OprPZxl/xTsO9UhPTKNJG8fFsjd2uKcDxBpY7nehobt/ijmfNnQ9EGxo1VoQlx1LQeTiLNlRxIZ6j4o+lKlXifDdcbynfuTYKveYRierypeLGpWVY/WIZX3dN3y7mFBlmi63nC96UISYhohhQsDYxfCd/7mW/sI4Nmy5HbTczyNWVYDQgoWTY9Uno+uNlyuWpZNz6N5jnVws+mYFFFgu5U9ZRdsVIP1rKqeN4/GZFqSRBI7OB7sZUgE9RBUNg9nQfn67LokjRWRFggBH11suT/PGKfRrvHWM0okd9XAG/OUcgiK4qtNz9sHBeer5rUr4nAUcbEKr/NNOTCKFbl1TNLAS+yM43tnG1b1gARa41hU4bVpjQh8Kud5/6RAHBeUXRgkTbOIbkiZjQKDT8kgVvjmvRF/9HzN8Tzh4TynGxx/9GzBNIn49CYE8RyNY9QuKXWUaJreYpynroagLDWeh3thoF/EkmU18MHJmNa4oELb9gzO0vWWg3FKtEuBvth0zIqBdnB0xlINhqr7s8E23kKmA592lkV0g2c/T1j4Duug3w2CG7584+aVuu/PA103HvQOffGTsG5PGAb0PnwdwS/e0PqiJQDroO0si03LLFZUgyVqemZZ8XMDon6R+nMbSEIIAfwfgQ+ADYGD9D/03v8/v5In+BUuYxy9C8AuufP0O+fZdJYHs4yLdUfT15wuG947KljUhlEsORinryFrnbHMihhR9xzcGxErRRoLntxUDNbxp6drjsYxb+wVgOdiFS4kwb4TYoxfAfOMDQDXcaZY157rTYPYgcQkIU1tEQU4d6wlUkQ0g2OSav7RsqJIFFkS8cFkwqfXFatqoO4snbE7YHiAIBeJZrDBkjRYx4tlRRYpRqlGCfjwYsOi6nhyVQVZfmP4rUdz4gjWvaUxNVLlfHBvzMvbGoenNo4U2HZuJ3EPb+JZHvPbD2c8udnifQBaL8qOSEvuTzMcnot1w16R8Oym4umi5I9eLhHAo/2C42kKQrJueppd8t1eHoCtcpdE8Kq6Hew6JCB0lG3YSB7NU+Z5QjMYrteOwVs2jWHbDGxbs+NROK43NbEKi2QUKTrTI7xDCvBesKoNkZTsjQMq02qJ3TXTqs7yxg5QPs00N5uWwXr+2uM5p8uWVRPaFONEY0ywta2vSsre8PF1ydW6ZW8U842TEXkSDg+xVq+lxFKEDVjsGj7X64abTUvTDkgpWJY9e3nEW0cF92cFV5uOLFE8v61wznK56UgjzaVzwTIloGwMvQMtPFmssSawrx7nAZyHH9guLcNgKNLQxNk0gW8UCUFrPLdlR9WFZJ3jac7JJOaz64pVPdB3wRbUGk8eScZZjNaK40nCi2WLlpK9SYwdPEvZMfSOujdkcYgbj1Dcbnus7xAyqDOsCyDY3ga7qfchLaf2EEvIEkEkPZ0FKUBHYVEvEhWkqW4H0hZhg/q66UPtzub5z0j93tf9AF+k2sFyvmq4WLcsy44HeznKeY5GMc1g+PgqTPzD9K6js5bDUYoFusHiheSgiKm7dDf5E9wfx4zSmKaxzHLN24cFt2XLH75YMk71rpHh6Y3j6e2W42mGIkLiGWywbz2a54ySiOeLit94MH3N5qv6YFt6eluxbQZ+77M7JqnkMMlw3vNsUfNX35hR9wbvPHmqebxXcFf33JQt9+bBhrusDKerhidXJRfblro3XG96rmSPM+G58yiitZarsuNkkqC1x3tPNZhdApDidtMhdxPZSEoWVcdMxHQmwPXfOyq4LnvOFhVSCN7cz7neDghCqtb9acYPLlYsth1RpHnncMT+joXTdJbzoebpXYk1jjhS+F3q6fWm43wVANr7owg83FUDg3XclC2Z1lT9wDiPmaaajy+2rFtDEkluq45o19Q6GifcbAYeTDPSWDNNFMtq4Nv3JyyqAak8m3bgrzyekWrFOwcF63bgYlGTJZq58EzSmBc3JVEc9s1RrNm2YSpc9Xan5On54fkWD4x36pmjUUJr3K4RZyhbw71phrGeB/spyktW9RDUl6OIIg7w7yiC822D8Q7rg/3h/l5BtLvkdENQGby8qzhbNhiCamaax9xtOn54saY3gRfycJ5zdzxBSYEXgrQ37OdBabMsO5SEUaxQWvHh5ZpYaUaJomws/+julnqwvH8y5nCS8WCaMCBIleB61XJvmvP7n91xdlfx8WXJOI8Ymp6ruqHqNP/yt0/ItOb0tuJsPVA2BoFg1QyokFWCkpJl1XNvlqGVCsk/eUzbh9QoR1CPKyHphaXvLa0KF7h2sOyPNEJ47k1ikjhY96+3PVrDojZESoCz9M7jrMfhsc4xDGEPMQaWQ4iplnTk0RCGWFrRNo7O/Ria/cqS9qpenUZ+Hpz1y1S4mDhGyVcPSP1l1W4I/V8D9oB3gAfA/4pf0zAe+IunrP28eoXUaE1QYbyy736+SRXt1EiX65a2D82j+9OUJFKBgacE9yYpxntOd3zNu2rgjf0crV5Z4wZ654LFd93Q1T1JpDiapFysGpQKP6OUgfl2uqp593DENI85niQ7XlzKNNV842jMyTjlYttyvmm52oZmVaIDRzaNNId5wr15xrO7OqAnOos6FNye9gwuHMQezjNiJcgSjRaC+Sih7YOdbVF2bDrDuu7Jk6BakVpyvqzZHwXGUbF7rY5HGT842+IcLJqewyLB4vnDZyU325amt5St4WzVkUcwzmKORkEJuqw1mVZs24E4DXbeSAau7H4W4NfbtmecxCghwv1NCKpm4HLb8c3jEZ2DprNcly2/9cYM5zxnq2bHZVK8uKtY1yHGPovCGr9pewZr2ctzmpllnGq+X22ZpIo39zJGiaZsDZ0dmGUJB3lQQ79zOOLJbcl3X65Io+BmeedoHHh1RUxvQpre87uaz262HI1T3jwoSBPJxaLBKqg6x4vbhm07MGk0TWHBwxvznEXVUbdhqKMjTSoE0yJ5ncQ8TiM+ud5Q9cEy8c7RBIHlcu2xPnCt5lmEFB6pwj3jtgxDdC9Aa82s0KyrjiySKOXp6vC78Oq3yQFFDEUiWTUhrGGSxhxOY5qhRyJYtQ5jQfovl3hWKCgi2HTQfYGj96u1PAJSCb0LLCJLGD5HhP3A8fOfoxDh+/1F0BmGoHhyAsqu5weXDovkeJrx+KB4HRD1VdWf20DaWdf+Pe/9XwX+mW8avapV3fP9szXWeYSAeR6RaPl66uUR/Ob9CTdlmCZfrFv8XYg0/Otvzklize2m43tnaySE5JppxltHBUMX2ALzLGIwjlU9sGxWnIxTOuOoO8OsiMkT/Rp6dzROuN52If5ZKh7vRSyrjo8uN1yuW07HCe8cj1k1A6NEY51nr4h5dlfR9oYX1xV744QHc4VMFXVnKCLJOIsYE7FpBsZFxNldy5+8XHI4Som1pG1dkOXHiqoxXFctm27gfNkwSSPySGOc4MWiJE80B0VCnmgeTFJ653kwTvkHTxdEWnAyzdgfRSzrHyeGOOe5KYPapbfB6+zwJJHkyV1NpsEhEE6waoMMVghY1gEAp0XM/ijiaBxzNElwHrJEv/76ZpcCd7qouVy1bKqB1lha45hkEaNY8vFNydHIUHaWUaqJdMzlpuW2CvaMJAox9uM0QUp4sawDJM978sMx1liWdUgRiCJFkUg+vij5zoMp92cZd1WYYMjdNOPpbcVt1aGlZJpHRJGk3QRGR6wkq6ZFK4XYTbUPJwl5LLk3S+mMZ1m1JJHmII9fLwj7o5jrdcvgIVGS3joGF1gUkVYYJ5gWMUeTnLcPc+o+pGU8vauIpeBs03N/LFg2PR/cm5HooPb68GKLQZBHkpNJxsk0wwtJogTN4EiUxCUReRyFZDblqHrPu8cZi6pjtAPKC4LyTUuYF1HgV617+sGEA5eHi2XN4AQjDf1guW4GmhuH9p40Ubid1cwMFik8rXeoJDTMYiEYekOSRiFFzTm2TQDuCRnSbYQEaz3tEBbqkQ6LbUhiExSJItGSO3r6Acovs+v8ksq7X4GH+IIlhDgG/sfAfe/9vyKE+Bbwt7z3/w6A9/6//bU+4Beo11YEKTgcxXx2teG67DkYx0yzaPc+7hjnAVy8bcMB9lv3phSxxjnPO4cjzpY1V5uWt4/GPNorwjrfBhj/uwcjbsqeugtBAFVnuVw1eOc4mCZUfWCQPdgLk8p1PfCde1Ma46h6g3Xwxn7xmq9Rti1Pb0quy5aLZc3FqsJOUkDirENKQXN/zF6RgHDMi5ibTcuqHRhmGbMsWBRebCr6wVN1A9u652JZgg+cmHUT7DsP9hSzLExxM634k+cbThcVWknuzRL28pRFNfDt+2NA8Oy2xjrHfBQxijWt8SgtqbpgD8hjjZQShCeLJN99ueV609Jby94oYZzGO0CpJ4sEn1xvOZnku/UjhByIHW/GuQCPLLuBZd3TGRvA23lYn5SEs3XN0eDZ1B1NPwT2QqxII4X3QXF2s+kRKlyUut6g8xDJXg0a53pa6zmeJBSx4rbsqXrDuukZ8IziCK0E+6OEdgfuL5IIBTyaZ2RJAHG/YgkdjxPumo6mNVyuWxZVCCMwu8bFoux5rhtOJgn3xzlX65bbskPvbAUvFg11N3A4SfEOrsuWWWYZRYq7bcs4C5eKLQOf3pQsq47tMJDv1MAv7ypuy451N/C90zV7k5i/9dYeR5MksLKaHh1rFIKDccrT6w3Oh2HV+/dmSA9FrqkaQxI7HI6ZD+rTu02LAB7uZUgvuFjXfP98xabpw5RcBXXQJFF4KSkixboxxKPAvYulxQsYpQopBP3QYazgeJJgrGVdd8xzTZGGi9S2t0g87WBIVIibbgdHL+BoqnEIys5gveKw0ESxDo0pIRC7ZNFRqhjFiqaHdWtRCro+ALOJPVVH2FNVsCiKHbMqXCDCWfEVRPWnhTBYwqE7jkANX9yq9tMqAdIYOhOizVP9ayPi+W8BfwP4AwDv/SdCiKOv95H+YvUXSVn7ol8/1YFR87OaVJ9vNHkBRRpsR3EUFEceuFoHZMW0iNl2hotVw6N5TtkN3GwDR6sezA6E74mVCqw857lat2gl6U0AyWupmOU9R1Lyxn5BO1jKfiBWipNpSmcdF+sWLSBSgXW5V2jePEgxA9zfy1hWAw9mgT/6clnz/C4A/o31XK4bYiWIoqDQ7K3F2ADa3h8HpuxMKKzVzBLNDy7W7BUJnQkpaNaG8/8rWHaiFFEEuhXB4rprNjnnWdYdkZJsmpbeKureMi00Xe+5K1t647i/l5NFgSdzvW4psjjwmbzn+6cbDscpbx3kOzxJ+NmN8VSD42CcME01nbEY63i+rfjRxZpEh2b2/ijmbtOyakJjzAO35cC66bF2zd4ocO6yOPxd7xVxaJrFit54nt7WGOeQUhIryTSL+Y0HU3pr2XaWT69L5nl4Xc9WDUfjlGkRcW/ImKQRo0QHFezg+fhyE6Ds7NS8t9swDFKSeZGQJjKEQwHjJMIYy8tlcL3onYKoHaBqBpyAlzdbauPQSuA9PLnaEinF8SwNzMd6YNMaXi5C6uc4i/nOyZgolnghSLQGZ18nJMc7L1ikQxr2KBl2KBTPy0WFAUZakkeO0ob1VvDFGzPGQiNglIDqoP05DSj9ua8r4fXw4FU5/nwHgwCyHYu1/UkC95eoV+om54KgtpcwiwVehLPTZzcVH5xMv7I1Cb64he0fCiH+uvf+H39l3/lXuIwJkOxUy50X1nCz6YnkDurmglIkiTVe9EghefugII00VW+4KXt+40HGn75c8a17Y8re0Q+Ojy43dGbgdNnRGc+7BwVRrFjUPfMiQNikFNxWPXvjJCgogMEEDsrDWRbSPiYp//jZHafLIJ1/fFCwrQc+vdhwby/n3mQKwOWqYdsYtIR7ezmbZuBm29AZy8O9DGt8gCrrAKfrB8ckkxgj2DY90zzGS4tHcVd2XG1aFtuO+7OMcRyhNFgLg/e8WFQc7KaA0zzCekc/eN46LJjlEZGWoftsYVIoqsGQOYXBv2ZyXG+DKqjsgnXqaBIHu0Cmaa2l2pjg64wV29by0eWGb5yMOR5nxFrS9C6ksTjPxaZlsI5N0/PpdYUQoJWgd4aXy5ajSRJAlx72RwmHkwRRdigZOvZ3Zcs4DclGLxYtgwmHU+NgHIf3xdEkIYslvfOU/cB9nZHHEXuF5vSuCZGiQuyiMgMgMFaSqjdkWrFuDemON/HHzxdcbXqSSJBpjd/FXDuveGOWUaSaSRoz3wG9w+HYBujpMrTnhRR8cDKm7AYuVzWfVANxFBhMbSS5WHe8dWj4/U/veHK7ZdUa+t6HJIhd6oxxjqYLKTpRFCCsWRqgpwhBkYTkqb0i4cE848OLLXUXVFqJ8lRdhMFzvmq42jTM8ph+CBHSQsKmNVxvG+62HcttiFSeJAKDY916ikzz+08WRJHmYBQjveds3VKkmiwKqoZ1bRmsoRw84yTIg8GybC0j5/BSIYUi0u51298RFlVvd9JSBUpDb8OC67XBGGhNUHy82qwiwiXg69IAxXHEVxyc8Mus/z0hpfN/sPv3jwnq1X/n63qgL1vWhxSq7e5CvzdKaQcTZNSt4IN7Y57dlAgheTDP2DQDp8ua01VFLIOKrUhijiYZf/JyRWcc5+sWnCPSCi0EV9uO690/SkqsC3G51nle3lYMg+V22/D4IA8gXue4rXqyWHE8Sf9MsMNi2/LHL5d8eLHFOsfttkXLoAIqm4HBwfE0YVs7Yi348LKiMx6lYJ5qrsueRd2xbQ3PbsqQijVYlBRsO481IVlGS4FSimks+fCi5I15ytmqZpZqJvenaCnorGWcaVaN5KYKF/PHBzk3mw5rQ6pcLAWX6yakw6QRSSTZdgHMuto1T1Z10P05BNuuZzJE4ILiI4s0iRLcbA2bpqfpwvPdVh2HRUoay11iDBRRUBRt2mC7dl6wrgasFcyLCIMIE+bWcKwlqZS8fzKhHgyJkJyuWqTwnG8a2t7yYJZzPI35/umGi1XDf/j9C/7qm3v01lO1Bu89QoSm+iSNOHxjxs0mJA4dToI1ZLDBOxuUMo5+xzFcNg6pZEij7AaKWPN4v2CcaapuoDcxzsJ7xyPK3jBYx7NFzboe8M5TxBqtJUkkeLEIz3tbdcFavVMJd0Ng/bx9MGZd9yxLy9l6E6z5O4D17z+55eOLDW8fjjmZJGSJpO8dzQ5gfbnpKWKFVILzVU0sBGd3NWU/0FsoW8uDWcLxOEFJhZJgjeeu6dm2lqtNw7yIcT7YydqhJ41jIuWZ5BHOObwUHI9j3C5iurOWTHsWtWek1Gt7tBZBOeG9COk73mEczDPNNE+JlGDbAU5QxIpIhfdVGnmMhcEEduS2CiltiYL7sxGJljTGsKhCQMjVpmFRGWLhMcZigkCXaabD5zrHSIdLupQ/Bqr+5IVFE/6bBPoBchUYRn+REoTL+ftHY7T+uvWyX7g6730vdhubEOJVwvWvdf0iKWufr5+X4AY/u0kF/Jnk5HQXTPKq0TTPIs57S93/OFVa75ANH19uWbcrVtXAySRBCPjsukLt7hX9YPnh+Yb5KPA+z9cNT663jNOI+7NgIbtYNxyPE5JI8WiWke4G3+u65/405nLb01tL2Q3sFQlaKA7mMYfjlOtNj5ThnjMvgjp9nsckkURuPS8XNb/1aM6mHXh+11C1hkkeGvKnyxaP527bcSUlsRZoATd1xz98suBolHI4CenJV2XH+8eBqaOkwdhwwjuZ5mEoVPZcly299RyOEpQWlLVlMJ6jaUo/WOrW4F1gttW9JUk8y9pwPEn51r0Jx5OE23IgHguua8M41WzasFZfrFoOxzHvHY+4Kwcc4e9mFEue3taMUsWqNbx9WLCqOx7v57RDSGrdNsMuXCfjeJKyP4qpesem6sjjYL1+MEu43Q68tZ9xuWkxzpGlESdJxvmq5gfnG6rO8Nn1ls54ukPHw3nOfp7w0fWWN2Yp1RDg4L115ElE1w1orVlvO5wXDN5ztqi5rVo2bQjHkTucRKw1y3og0oJVa7g/jdl0lr1U8WJVI4WnGeCwiLjxnkhLTvYSpBJ8fLUhkvK1WGNddTy9k9xVPQ9mGXkk0PLHQTeheQSHecLgPQejhLIz3JUd1jsEklUbbJJmp+iJ/qnfpp9dHezsyD9fNSQIilJB+Dzxcz7355UnWOG64Rf7868q2n1/JWGUBiWXkhIpPXujZJds/tVeJr5oA+nvAv8NIcQzQmqCIIiTfvMrfZpfkepdmAynu6QyIQW3VcfRJEZHmm/dn/DhZbg4W+tJlApqlkSFhcnDxSaAP/eKlFEq2DQ93zvtiGOJlBArwemq4d40gIG9j/HAg1nGy0XNYttSDUGNdFf19NZRJBEn0wBV7Z0nj0P8416s2J8orPXsFzF5GtEZy8Wm5XCS0O98qOerhkxLslgFZoN0dBvDtnFcrju+/WDMYMPE7fliy6O9gpeLlrf2VYhF9ICQCCHYdgOuhf0iCQ2lVCGEoB2CV/pi1dEOhrobmBXJzlIneHZXUV0YXu4ioN86yLnd9rvmmqUbHJGUbJueeRGiKh/vFXx8U9JbSywVd2VIrykSxcN5wf1pihSC1lmW255iXwebU+c5q3oOxyEC+WIdpLtZ1CNFYI54D7M84s29giwK1r2TccJgHPM84cWiZLCWureMU8UoUhyNUw4nCQ/2cpZ1sDRcbwS3ZUusFFcbz13d8Ucv1hxOEsp24GichFhLKbgrOz64P2Fwjqd3JT84W9NbOJml3G5bmsGBN1gPrekpYkmkBFfrhmXb82iaMS8i1lXP2TKk6J1MQxNtVQ9kUjI4z7SI6XpHHns8gjf2Ur77cs0o0qwai/CSsm3oTYAwtoNDR4LbbcM3TiacrzyzccwwBB7MJA1MqmmmuTdLeHt/zF9/c5//4PsXnC4b8iRimkc8XzS0vWGaJexlEWd9S90N3C4GTkbRbtMNkyKagbuyQSvN0TgmlYpaqSD9Ny6k1kWS/TymHixlZzA+gHD3dPBqD9awaR3eQds78tiRao3TMryWCoYQBhjewiJMMWIlWLY++KkbcI3BOYhk8BF/kenBL7uKKPxe/ZrUgff+3xVC/PcAvPdGCPHrI6EipGfclT1KhMOMFFC1A9Mi2dk2YVakbNqeu7LjxaIB5/hHTxYUu2bfN++Ng8pyp1ytOot1jntphBfh9/+giPnIOu42DQ8PAldCRxHOSaa5YtMZ8liyaQxKB4vuphV0g+VomrKuB2xv+OHllqNJyo/ON2xaE5RBkeB81VJ1knGesJfFLOuWctcEkSIo8Z7cVTRDUGf2g9ut8Y5UC/CaWRr4ZuNUg5TUveVsO5AnJfNMc7PpMIS0rfeOR1S9JYsVv/FwStVa+sHw6U3L20cj3jkaUTYDLxc1decYnGOaxJxMM5o+yOHPNg1XmxDVnkeah3s5xnj63nE0SagHg3WhIefwfHq5RWsZ4PitZZI63poVnK87lPSM05g35jnbrmeWhaTJpgvR71IKsgjeORozGEuiJPvjhFGqSHWwBT6YhmbdtuvZIBAeThdhD52kIUDgdNnyxn7OySzj6a3h/jznZtthjaMnWC+2bbBD7e8ijM/WLWfLksHBph5ABH7FOI2IlKTpDIMDJ4M1+jceTplmmsYYytXAsurZy2IGwlnDOE8aB1Xx1bbjZBqUuELAi0XN0SjBusDIKgQ4rRjtuEvrtmHdtGw7Q9kbYiUpa8PtuiU7LHj/aMKq6bldNfyDp0vyVAa+UmsoB8e/8N4e68bxh8+XQEgScj4Mhd49LlAIxlnEtjO8dVhws23BwSyPoey46EJ4xVuHI946KrhZ9by8qSj7YIU4HKfcbVuSWDO4wJjaz2PSSFF1lkkW0Vvw1jE4Q9kOKKUoYng0LyiHlKtNx11lGFw4T9VdUClfL1rq3lH2PeMkYWMdsQ6K8qq1aCkpO0saR2SDD2cKMTAMoVlW9YbOCJIoWFfrPkCsX8FTX+mBXlnVfrKhZL6C5tEb+xlH0yxYJJz/SqfLv8T6+0KI/z6QCSH+JeC/Cfzfv+Zn+krqZ6Ws/XnNoS+S4Ab/dJOqt8G+8/k/FyvJPI+42rRIKdBS8lfemAcwv252ChHL5brhdmdJFUJQdpaPLtfU3cAoC5iENNas2wbhI+7PUs42FXujmDQKYQgfX1ekUUiWPhyl5GlEO1jOVjXP7ipWZc/hOOFonLJpBrrBYnxQTk2SiHuzFOE9cax4crPF2oDUuFn2XK5a1q0J5/5I8ztvzHZMTsfpqiVPJFfrDiXg6U3JKNV8dl3y9mFBHmvyJDQhvnk8ZpQo1l1o8nsgiRVpJNgfJ1ytG6T0WIKSf6+IiSPFLI+Y7NRX29bQ7FRJ5Y1lXiS8uZdTG0PVhQS3PIlolw3nq4abbU+RhLTOTCvqwbJfJBxPUi7WgRkovODDqw2LsqPpw991MximWcTJtGCwNrCfdh3pB/Oczlq0VNyUFdXgeDjOKNsA+2mG3V3ReeZFzFt7OcvasG4C+H/TBDafAya5Zq+IWDWGaaaZ5AlTEZSleaIQwrNuLMJZ5nmEkp6LVYfbKS4jLfHWM/jAEh1lEdp5GmtJleTNozHGOs4WDe/sF9xUA8YH639uHIMF8Hzr3pRVZXDO0eyg5UJ6Vl1ovG36gU3riGOQu26OUvBwPyaLE+q2RcSawRpmWYT1ilXdU7Y/Zg7Bj1WhX7QUoaHz887/u2yewFDVIcFZdZ+LlfwS5fmLNY8g7C+ZAC+h6sG0BiUM1eDIpebhPH8dQPJV1RdtIP0rX+l3/RWvV+lg7S6x5XzZkGjJfJSAh7Kz/PbDGZeblnGm+fiqRMuQhnE4iUm0ZhwF9UnZGmItuVo1jFLNfhZkrTdlQ9VamiEcOt/ayxnvEnuMdfzgYrtbOAT3psmOZRQSSqz3jBLFNI/ZNAbjLamI0FFIenkwyRBKBIaLhNYFTs9eHlPEIYUrUoKXq5pUa+aZ4mCUkEWalek429TEUWiIVb3h+V3JX3/7AO8DE+nZbUlnHXdlT9UO7I1T/sX3D7ncdJwvGhb1gN9N3F9B2QbnOJ6G7vhbBxmrJlgLPr2uaPshXHzisFJ66xilmqMi4p3DnNuqRwkCHHmw1N1AHmvGaZjSvljW4D2LquNm03G5bXm0V6CE4HrbBe+326VY9IGlUHeGsrcMxtI7i/GePJZ8dFXTO8emNTzaD806KeBi2ZJEihfLms4EBdDNpnudAtday8WyIooijkYJ0S59xjjH3iji4+sSZzx7oxhBYFHsFwlni5o0UtxWIR6z7R1ZHOSiwgsy5Sh7y9myYhxrpqOE58bzowvD/b2c202Hlp6rsuNwHLOpDJNUMU4jZqnlrC6ZjZOdjVJhXejSB1lxkDkvti1FGpGnCiUFZ6sW4yWDhVhpettzuWpYN+GC+vSmZG+U8Fcfz3n7cMRvPgw8FmuDhPR2ZxNUPqjT+sHTDI7DUQxS0vQ1vdUMxpFFik0flB/WB+h13EtaY4itpLPB7365aWmHsFkfjSJAUvYDF6vQ9EnjwAbr+6Bms8KzV2jqXrJtWuzuLOZE2PAccFv514u2/ZxveWe//5WoONEk6tfGmlAJIfbZvXxCiL8JrL/eR/py5QWMEsVnNxWfXG+pOsO9cYDGaylYd4Zxqrje2JDeZUyIkt297yIleHobeHnzUULXW2IFKMlN2XNbdSEBZhzzO4+n/Ec/umHbmJDapSReeO5NMya9YTCe3oQUnVVtqNqef7xu+eDhlFxrHu9n7BcxgqDuuVg11L1hriKKOMHimOThd+Wjyy1NH6J140iilKAZDHmUcrlqOV3WnK+aoHaxcG+WcjItqPqBm2pgloZprRLwct1zfx7WvE1ruNsGW9/hNAME37w3ZlWVXJUd225g2wx8dLFBK8V+kXAyS8micKDftj11b+mtwRgf5PdFaOAv64E35xn393LuTVOaweGd52xd8/d+cLtLBIpDmMQw0JighHwwS9BS8q0HE7rB8eyuwjvBtguA/qo39NYz0tHrIIlFFXgfN9uewTie3pZ842SEMJK6s5yvWzyOdghBCMZCmuy4RsaExLMBHk408UyQxZpRqmgHHxJGh4F13XO6bLDWYb2g7S1Vb5B4eieY5ooiUdwRmj+zJICiv3+2IovD4GJvlHBQJGgZpu2P9zOuy45F1TEMnn6wbOoA358WEU+vQ/jHXQ1v7uecrVo27UBvHLkOauNlb0gjKLvwLEUSwOqZ1rTGhtcYQZYEADpKME4iprkmiRNE2/DuYcF12XK16nhyU7NuLfdmGb/9aC+ktRXBWiyE59OLklRKHhxkvHGQMU6DRXtRDbTWcjhJOJGS601QGLx3MuZwnGCdY930XG2C7XB/lqClQomej24rqi7Y20eRZtM6nIC9LKQTna8brFc8mqd457guDQejiLNVixJBuTUrIjZ1SK6SUrJfJNRdaPAViWaUaU7GGc/vSm6roKqLNAzG05qwb6gIJimsW8L5zf1s1tFfmIEkQcvAPJG7uPOvCo76S67/LvCvAt8D/uvA/8N7/89sKM+f1xz6sglur5pUxgTsQaIkWazpB8tn19ugqKkGcJ69ccz9g+x1dPfJJOV0WYckN+F38GnNxaplWfZ8dlOybQfmecJfedNyPEmCOsR7vnu6pmws7eAQPjSgZpnmsEi4v59xseqYZYbrsuNu2zOOI5KpYNs6mn4gjYP9WRImeb11DMZxuWlxxtO6IP3+3U9u8Duu05v7BVmqMH1Q8Tzay9FO0A6Gy/VA3Ybz+7btyWNJFmmySLNpQhr0i9uaphv40S7cZn+UYHYHPCMlmRZMMs28SHFeMM40jfGMc7Ub0mv2RjHjWHFXDeSx5OVtzXyc7Fh2DuM8h6OUYbCsG8MoDdbswTha53nrXoEVcDJOuSk7rjYdWgqmeUhguz/PqAdLpBVlF6DlH58vcUIwz2Puz3K2bXgPhQahD7gIYfnsakvVG/70ueFkL+M3H02QhOaXkpKbbcP5ombd9KyaLgwjPTy/LkOys3G8cTh6rWC9WrfESofQGu+5qYPd+cOLLeump9ud2YtEUWQxSMGtF5zkEa2D3DuEl0wSxbPbHmMdjRSs6o6zVUWkFfvCk8UxrbGcL2uOphF3m4GDUYwlDLecCZqerre0/UAeCSAIFKyDLEpp+p6m9wg61o1DCIf10HTBNSCBWID+BbhCli/WdGqBRIRQnkH8xfhFf9GSBLtdLsJeZGwYQikCj3ZRB/D9V1lfqIHkvX8uhPgt4F/Yfeh3vfd/+pU+ya9QvU4HO12zqDvawfJbj2boXfeuM4YkVrx9OMJ6z1v7I05XYVHWQjJONXGk+Nb9CXdVx2A9ozzm/TwcPGMlGMUR0wxOphmzNOJ75xuKWFEPjg9ORuSpBue5LDtGaWgsCRkAbgAP5wXLqudPXiw4W9TMRwkn4yDbjuMA+z6ZBYhqZxuu1y1CCKTU3JQdj/czTiZZUPvsIMfff7km3cEw90aCPz1bsVckvLyreTgvmBUx58uKZzclWRoxyzSzIibTgpt1y7Y1DCbE4zqpAE+cKiyEA1kec5P2jJKYbRdaxB9fbpgViixVPN7L0UqwrDpWleXJbcmnNzXfuT/hg/tTHs4zvne6ZpwpBgPvHo+42jS8uKtCol1vWdc9L+5qtBS8sZfjfLhw5LGmH0JcZqIVl+twON0rEtrB8bufXJNqxb1pysN5zsnY8aOzTSD8FynvHI25XHe892CE6R2LuufDi2Ady1PNUZxi8dyuW5DBopAKuFi1u8Qyy9EkZrCWdT3wg/OWvSKh7y3DYGn6ntJBYwzGKbSE944KLGGa+nLZMs/jXXJCYEVNmyFMmQAdKT45D0yjbxyNd/LPFGsNZeeojaXvewbr+eR6SzcEW11vHHGsGeUxqYRNHwCwdR8S1JZNy6Y2bOue2obXz/qwuP/ocsO2M/TG8sZ+ALb2w8C9UcIk19yUAx9erFk1A6s6LMr3pymxCiqyqjcI70lFSPSxznO2Co26wQqaNhAk0lhRtQOrqqcxcFcahATjPc6HtDQ8IdFqB04fRZJm8BSxIIpi1pue2obJQu9CBOfn61XzKCIokCAAteHP+pz/MksA3U799WtS/wbw7wPvCCF+DzgE/nNf7yN9uRIetm1oBH1wb8ST64rGhEPLLItYVQO3m45ZHrhxoyTi5aJCSMGq7tFS8NHllm/fn1G2gamybgb63jAdxVyve1btwI/O1/y1t/b5K2/M8TieXoeI3JGOyBPNOIvxwnOzbbE+QTDwpy9XaCF4fFhQREH6bl1IOtsfx6zbhOmgMM4zKyKEhFGkGMzAzbbFe1jukieN88zymHroGdzAR5cb0kSRxpKmMlwsKx7uZUyLlDx2TFONw+MQ3J+mQXbde86WNVVrmOYRkyJmnCg+vSnxeNIoYhQP/OBigxYhqXOSavbGYYJ9u+14elsSKcFHlyXTNCLWkm074AnJnb/1cEoaRzjn6ezA6arl06sA6Ix1UEX1xhEpzVgrijhCiT4ET0hFrAJ78KCIWTQDsQxJME9vt6gkYppFFGmwXJhd9PM0i+it43vP12gtGOcJkYKzVcvLRc31RnEyy8h1SLZZVYZPr4L1wkqIheL5Xc3xNEXLYHkvm4GLTbAcbAbL/UnG6bLiNx/OqduebW93CSrBjhYpicVTtgMP5yGF9HrbB06gsXTG8417Y263PbGUO0A6IYZaSrII6taxVwSw6yhWDEASSWZCcbE2r23C/dpwt21x3u14KYbTRcPJOCWLcowMjf1ZEbOterQQrIYe0XjqqsW4sA5b48kSwUxpZokM62w78Ml1yf1Jwtm6pRssnXMUkebxUcE4jrjZNjy5KVFSoRXkkeKuHpgXmqYP4PVmcBxNMvCCVdOz6nuGlWeUGJ4vGlZVy3XZkUeKZKZp+4GrTc1/4t0jtNR0NqiiRrtI627odg2coIy+WrcBIyBCiIOWCi8827XhcBJxMMqIFJyuGiLlGWeBd9YZRz0ABuIUmoFds5lfuvU4ErweqgBfKRz1l1z/He/9/5zPJTkLIf713cf+maov0hz6RRLc2sFyuqg5WzUUiWaSaVb1wJObEq0Ej+Y5idaUneFy0/LmfkG/46n6nRrq/iRjWRu0lAzWcrZuGKzjrYOCZT3wT57e8XCe88+/exhCdYxlWfYs6x5PGELfn2UcjFNWtXk9cF5UPb2zPJhkrFqJEkFN+8ZejhCC+/OMqjU8udlSdpYkkjxfl3gPcazwryzd1rKsAzpDyZBUWjaGxhg+vSlJtWCUxIxjTWcSusGyaluySHA8TfnuyyXLOgxUk0gjhcU6T6xDMyKPFIu6o+4sD+Ypszwi1pqzRb2ziId101oYpTFvHYx5crPl4V7G9XZA4lFKBObhugksmzi4NfJYsawtSSRonePBJAtNbOdQAq63Hc/vBhKteHyQUXeOTWP4vU+uGKeBb3tvGpRm4zRinEd8elXS9JYn64ZYS17eDZyvO+o+OGEiLfn+6Ya//e4BxjqEhHqwPFvWlG1Qf1kHUuwURALSNKxjSGi6sO8ejmOiSGBuK0ZpwbDjIl2uG/AepRSTTPHBcQx4EI5VN2C9YBgc01yzqgyDtSybAbNpuC0HNo0nkoZ4dw/tesm6Nbx/b0IeheHVs6stRgia3pDHEb0JKqe29YzzYJmrBnh2vQEpMM5T9YJIhYRQb8MwGHY24l8QSv1lmvvGB3h2pMKzvfref9mn9kBWDhylWIfhRpFI4kgyyTUCQWMt8VcYePmFGkhCiH8d+NeA/8vuQ/8HIcT/xnv/v/jKnuRXrNJIcTJL6TpNrPvXzInPg+teTQKiTPJuNKbuLc/uKs52Vqn3jkb87bcP6Z3jat3SGcv3ztZ8dhXihY8nMc56PruteHlXoVRIkppnYcGIIwUetk1HpDXeha784BzX65qniwqBYJTFTPOYzjo+utzy5n7BKI15fFAQ77r4z+7KXTxwy9mi4XbdsjdKmGYRN2Vg83jg/iyjH2w4mMaCRRl+I354seK94wkXmw6hJNNMsz8K6QybduB605HFEdu2Y3BBXlskEaNUs24M+0VEZRzeey5XLXd1z/ldzabtMS6oLM5XLXhPPQw8mOfcbjuu1sHP+3A/52Cc8duPJZump+scUawYdk0jD8zyhEhJfrRd86PLLZ11rOsB5yGZKfZGmlmuMc5xs2mJo4iqH2g7R9kMHE5iYh0iNfdHMa21fOv+hBeLBmND198iWWzDa3JvltFZi7HBQrCte8qd19w6SCPJou5ZNy2JfpUK1DHOIrQUPL+tMN6HqMl2ByDUQcLZDo7b2vBgFnIq2y5MKIpEcbpuMINjMGGRvalaJIKyDVOeVWeZZpondyXOekZZxNujnLoPk6BNE5ggHpgWMfenGQ/nGeva0m8aplnE6bLGekGiBFI4RplECIkTwff9YAZX246+t9xVHR+db3h8NOb7FxWZEmz6gRd3FS9XDdM0XIqFFPSD5WSa8Ol1Tds7Ig2jVLNsBsqmZzrKGEWCSZLgrUUKS2cdq2bAAYmCqvOvrWiZ/rH8cxgI4McMPrg3pesHzjc9+1lM01qqrcXIsLhiQrf+VVl2gG5AuD87ffi6pgr5TpVSdYb98df0EF+whBAK+Bd3/7xP2EM/8t7/BbCAf/nlRbC0LuueWGkOxxlZJDiZZRzmMZu7mgfzjFmR8HJZU7Y9H12ucR5SFazBG+uxWKZ5xE3Zsah7rjcteRlYK5M04nLd8PHFlvfvj5GIAAUtoYj17pBaYK2kak1oksrAUkNIVlVIhxwnmjySfHy5RSuBkpKjWc7zRc280GGS5+BsE5pH759MuFw19M6x2LQ8mmdcVwbnwu+Y6vyOyeIw1rPuHPfGMefLDqVDstWbhyPuth2ni4pNZ+g7g3GWZpBcrmoORzG32y5c1tMIByzLlnmRMkoUWaR5flPzrfuKbnC8swOKxzLY9N7YK0h3LJdISdatQyvH2bIliUF4j3OC3hicF3jvSBNNRGC2CTzfuDchVpK2s6yajjRWpIlGNYbntzWHk4S//uY+227gYt0g1kGVOMljPJ6zZcvDec7Lm4qbqkdIwcP9grodeHkbEiSrznI4Dkk/Qnj28oi3D/Pw8SIOQQ7As7uG43GMVAIJVF1IhRO7YdQkC9YQKQVPrreUraWINe/fGyOVZFMPHE4Tnt7UpJEMbBMRUn8GY1nWLXmkyBNN3zumuWTbGBIt2LaWk1nKujXsj2O6wZNpibGB4aelpPX8OMm07umHYI2f5hHb3u6AvIJ103MyioLCqTXUvSNSnn9yuuZkkrKq29dMLyMtgxPIqy2REGzrgb93tiZWgjjSvHdcYF14PV4uSp5cb5FS8vgg42zZ8tHVliJRSHSIqo4VVW9Z1j3VEOwj61rQDJYXi2rXQBswBpyGqh/wTtC0ln6wGAVH44x6MDjvqFqHcxaPoDPh79JaqFuDYSBaSR7vZTgXrC6dgVRbbhvLOBLUrcRYQz9A1YYLDkDb/PjiEIkwgPhlRTaHoAhwPvx9/dqMGEL9l4CfbBb9l3/Kx37t64s0h75sgturplQSBfWQs46PLrYcjCJSHdaIZT1wPA5nemND8vHLZU2kBKM8Im8HFlXHXh5xV/UYG5JwZ1nOo/2c+K6m7h374zQ0H0xofCAIXLbG0rSGeRG/5lwuWsODSYr3juW2Q/ofJx8iBJ7ggjhfNlSd4Xrb8cZeTqyDVXRR9QigSDW32579ccLZquXeJAT6nC5rbrYtB6MwKD9dtkxTy3QUMwyWo1nOuycTrjYNf/xizTyPePd4TJpEDDaw14wN4UJnq4Y8DrZWIQWzLGKWB0xEFEkkgSW1P05482BEphWLpuNPTtf01iOFJ4kUeSTJY0WiJFEkiVT4jX9jL+cgjzjftAzG8QdP77jctvTGczCOOB4lnK6C22RZDgzW8/HFGgdcbRuqzmFsHZpNeceDacrfenMPqQWTTPLHLzdEUjFOJFooWutJI8XT65JqNyR/dzf0PpmkfNL01F0QIRyOU9Io4nbV8I37Yz6+2gb3zCjmetuybQwnk5RYKrQWGG0ZJYoii4LIoQ8hROvW8PbxmFVrQ9PPOFCOUazJtKBqByIJjfMYG5wVSkg6H6z746hgUfU8uQ6YkLcOR6x2yXqLLgyItBSMEygJNmXjdo3ELqx9UQS4oBjdtiGZLY4gNrD+S1oULVBZkPbH1mXFPx2g8JdZbhf0IIVACs/NNvQwsq/YzfBFLWz/KvDPee8rACHE/wT4feCfyQbSqwU6i4IVKE005+uWo92if3+W/VRp6aoewEPVWbph4Hu95eE0Zz4K3tcXy4qDIuZoHDPOIv7o6YrTRc1nNxXGBzmnINgB/s4HR2yMZ9sY2iEcVqdpYMx8//mK//cPr9l2HYPx7OWBU3MwjgNPYrB8cJK9hioaH95AV9uWF3d1SBtoByyO758tGSURaRQ4TgrBbz+a8X/6ozNs6Yi04LBIuN4ExczeKA5MhE3L6aKitZ5xrCkyjXPw+KBAqxBpn2gZIi093NUdy6oji+WuweI4X4fYY2s9cSpJtOduOzA4y588XyKlZJSEqPofnm/4rYeCpjM0rSNJFALYH8WMkojbbctWDFhvwzTUWqpdo2SUaB7MQlT1ouy43jacrRtipemsIY8V92cZWax5dlszWMvtNmFdB3zyvUnGzbbjct3y1mHOg72cddVxUwaVz4dXJVU7BMB2Inl22xBrWJQB7HxQJBweKG63LR9db3n/ZIQncCSqdgiHZa2IHOyNAgfDmgDJXjYDCkGaRpStoe4MN5sOLRSJClLVbRdsXEmiORilrOueTd3R9oa3D8fc38tRQvD90xXr1pFnmr4P0xNrYa9I2LaOi01D3VuaeEBJSdn2bOqeZe1ItCCJodASYzwvVzVD79gvYrRWbFvD+S69ykYKJQJYdi+LOZyGRJ+2t0ghmGYx81HP1CguNw2XrcUBeR64HBbHqgrL79E4p4gF66qlM8H/7G2At2sJ+W4SXHaW3oZoaikt55uG3ng8ns4KjPVYGf7cOA6T4p+sV+DsIoF19/Xb2AIY1v9UFsKvWnnvrRDiP+O9/58BP/i6n+cXLSUEo0RzOIqJtGSWai42HasyKBvb3mCt4+3jMUejhG3b82CWU/Z2pxA03JtlCCTHk4SrVUMRR+xlhmrwOG9ZbO3rpuqLm5pF1dE5x7tHY4SAi01L1Tru7yUY72m7gdkoNCHySBFpycWy5sMmpMPNi5g0VjzUgutNQ5YEKf8gg+oiUYGDEWvJ/iiwhHCeTCuGvqWxlmkW0/YhRTFVEXiHRCAIiTqrZmCaC07vaiaZ4mrd8/HVlsEFzp91AXY/zcoAIu88+W7Nak24nByNUlrjqHZNCCEgiTRaGY6nKeuqI4kFsVeMk5jfeWNOGmk+vtzw+5/dgfVcbmvSJMKJgK6sekviHV5HVK3hru759ixjv0j43umK221PlmiMCfL5tw8LHu3ngce3qLg/z8Lhsxn49LoKwQXO862DGUrAqOxCw6LsebmsMQRuxrbpOVu17BURSRQaLjfbDiEl8zzmvcMRSM+z25Lndz2jJAoDmY2ht45F3ZBGmlhJ7s8zjPFMHwel1bY13NYDTd9RdwZj7A4MLomkQBCYeJ9eVTS9pVKOaR5TORglkljFHIxiPjieMikUPzjbMBjLbdlTJBFlO1C3PcJaUg2Xqx6t4N40ZTaKORml7E8Cs2SWR6GJMjh6A3uJJlKCx3spzeDpTQjeqDuFEMF+kScBCHtbQXSzobdBWeW1IlaST68qjqYJLxYV1+uWzlrmWWC2pNrzyU2NMQ6lFe8c5IFFKTy9sTycZxRxhLWGy6sGZ0MKHFKhdeAvGQNKevI8oh4cTy62HI4Sul3c9stFjZQy/G5ojbGWLJUM1hNpHYY1QnK+bTBeoIznqhxougHjIdeCdvB0vccEDBWecJh27AYOPgwhflmaIAlkEWRxGDZqfvUtbEKI/wLwXwTeFkL8+5/7T2Pg7ut5ql9ufZHm0JdNcHvVlMq05mCUcLluqHrDvog5GKcsqo7LdUO/Uy+nkeTT2y0/Ot+SxsGaeThKuNp0zPL4darg6VKglKDvHctmYF4kzIuYURZxerml7y2JVoy0Jokc0kd4PKuyJY41Ho9WgiIKzoSrMvDO8ljyzfsT8jjiatMRKcHRJOXT64qPrrbsFRHLskftfl7vBdt2INWSsh3IDgqc87x7NOaz65JJprnedry1n1N2lkmiEQ4ezhM2reG9kwkPZ4Y8UWzb0PgqYkXbB1TF3SbY9drB7mD4ERer0JCb5jHv3xsTa003OJIo3D8+vFzzxy+X/PB8y+EoJokUXW9ZlD2P9gtmRbJTsXoG61nWPZ9elYxzzdPbCrOz6ykh2DaWZVVxOIo5mYVBw+22Y9V0eC9ouuACuCtbJkWMvC0DeN86TqYZgwtqoXoIKaJaKQ4KTT0Ed8O2N5yMU35gDad3NXuTnINxihAhnXkUSSIVmuO3pWWwlpeLkkWpkUJQD0GNdrWumecJsyJGyXC2jpUgSjWRhod7OQejGGMKtt1A0zue3pTgGoSExwcjvn+2ojcOT+DltibgV5rBsmr7wNhqes5XDX/8YsV+EXM0TrkrBy7WLamSzIqEbddyXYbhrwN2+D/6Haeod5YihUwH2LdVINqwJv9lTDA/P2R+5WR4lYr2ZWtnqPiZf1bx03lJrz6/J9xzYgWdseghNJr/1jv7xPHX00D6ScC45Ze3N37tZX2wCEVK4XxIi9kbgvxRycDVOZHiz1zs+l3SVp4E+9qy9Ly4q/kPf3jBu0cj6t5hnGNR9nznwZRF1RFpQWcsl5uGSRIhZPC83pQdmzp4/d85LBinMbM8MAS+d7ri7K4hUYKKYJtoh8DWUVKRxZJVG3z8mtAMu163GBtSVAR+Jwd1fHpd453gjYMCawIX6JOrLd+8NyJV4JFhg7FQD55VNTD48Ju7qAbWbU8eR8wzhUSw6Q0Ho5g80ty/l/Ni0fCjszXrzhIJePO44CDPSOKQMhNrQdc7BhesGt84GqHUwM124GzdEmuJ9wFK+/yupBkMUki0hAcqAOX++OWCm3XDi9uaJNFs6wEhBZtacL1uiHRoHj2c51xuGj693FJ2BkGIqa+7AWMs7x5OmKYxPzhb0wyOWGtmo4Sn1xWRlByMY945KnZNOb+D6zmqzpBHAiUkUnmEV5xMI5IoYlF2OGF301SJkJAnCukFjXnFIQqxm5EQqFgwy2KySOKAfnAUWmFxjKykdZZhcExiTZpoTqYJgpAw8+l1hVKgdtCmsrfU7cDZqkF4dof6gVhA5wQCR6wV92cJd2XHXhHinseJ5qbscQTeyDiLqYewmRtn6fqQIqelQ8mIJBJcbDuOxiF1IS80l+s6JGnE4cJQ9xYtJEY5cq04X9dcb3rqtqczoaETJRHGOJZVTzcETlewbzVhiuYhjQTOQa49vQhqJGPC79XhKEZ4y6qxbGqPHRoMYZqvpWCUxjR9G+Cn3Y/TEz4/JYgIi/DyS5Kzf9GN4s+rzsA7hyOK+MtkSHyt9XtCiP8lIXntNUvQe/9HX98jfbmSUnBvltHvYoVX1cA4VpxvAgdvUQ8sth0fX9c82kuZFTHffjBl3QzESrBuDEWi6EwA5Fe9YZLFlFKxqiucDyyl43EA5o8SjZeC/SRmU/d0vWVbW0ax42YzsCh7msHwrpJMUs1gPJ9ebai7oA5xuwP6ogprmbOeb9+fsSg7Yq2p2p5smnJXD9RtsCqvqo6jacZsFPPYw9Wmpmwtt+1ApIOK5/F+jpAiKPoixYEMwFahPHXnqI3BeEi02gGNBzprOVsr7k9yVk3D5qLDGk9nDLdVx03ZBsh/rHi2ECwrAzjqnYLV47EGHu0XvH0YDuUvbiueLcIB3DrLpjOUxqIQOESwbHmYpCEZ7G7TcTvqcB5+eL4liWCcRmgtOV+UPNgPYRJ3Zc/1puOd42C9HacRH5yMqTrDk5uSqh94+3BMGmvOFxXGhcNzFimMtRyM013qC5wtGoQQXG9bjscpRSR5tJcHq7vWjCJPHGsWZUdnPW/sF2glOZ5m5FGw3V01Dd+6P6Y2gcekpWBS5Hz35YZ2cCgtmcUR227gdtszWEcWaaY7W+XpMuxLZ0uDknC9jXjnaMwoU0zymBe3FceTjHEiWdcdd1VHbT3GCFrreTzOgrogTqiNY+49vXU8vw02mffvjZiPEv7wWcmmHRilEUejlHGqOV/2IGUAXVvP9SawMupuQAuBEw5nYdsNFMmIi3XNsuxwhOm7E5DFmsVtxaYJARePZgVKSVaN4cOLDfuThJvdNF+rjh9dbLnZ7IDAfYdCcFAERZjxAoGn74OqoRssQgiWTWAzprHmZBJztW5xxqA1HIxjjPF47yjbnnVnaAbPvXHEsrV463GAN5bTbYDSOgIfMRJh4rtzgjDS4HY3CsPPPvD/RcoCSRSO4LnWqEj+OljY/iFwARwA/9PPfXwLfPdreaJfcn3R5tCXSXD7fFMqjUKDvxksD6YZjpC+3A9B7T/LI+62/Y6TpIilYNMapAicu0fzMFxsjOVH5yv+4OmSl2VD2Rq+eX/C0TjFWIczjk0blDLjNOZ4kvLh2YZFOZBIxSz3dIPlfN1wW/UUcUTTW7IkuCiawZFq/zrQ5nRZsz8KNvDeBHvc/jjmtuy53DQggl3p4SzjeJpytW53SqYQ5rKoelb1wKoJdmXrPWVjKNIoMCOTYLU+pWHVDBSpZi+Pud22ZInCeLjcdMRKks+CrdoYhwS2rUOKgfuzjKYz/KNnd1xuArN2kiguNm2wPieaWSapusBSjXS4Bx1PYprOAJ5hcNyWYRC9P4pZ12EIPHjHO0lOpBUPJhlaSvJI0fYD3luM28m9driIPFUsqoGXy4aq7blYt1jrsQ6qrieSsFcIikSilOK27PjBRUc/GLpd8zKLFWMZ8TuPZ1ysGy43He9nEYejhJeLhuttxzwLCXdtb3BCsGoGkkhwWw70xnK9CVd/IeDd4xC84YGqt1hriVRQnH10ucUDV6sGpcARbJNpFBhMuVZ450mV4OVdjbUWt2P1fnwZcC5CRBjnOV+21H1oBEnzY6uWBeJXvxQe+p6QtipCaM5XAab+svVKgfrzGkB/Xulds67dpUcrwt2k3f33P+9nkrvPiRSMs8DQ+k9/54THe6Nf8Il+zrN+wc/73wF/IIT4v+7+/T/Lr1E085etwQSfshKCOJJMU82iHng0y1Ba4ncKpc/7mGMpg1yzG6h6x7LuGWchDexPX644mWS8sV+wqXv+vx/dsD+N2XaGl7cVVWfY9JajPEB/EwXb1jBJIw7GGQBlb4mk4HTZhJjpPqSEaCUp2w4hBW/vw8N5TvSaPR+SQp7eljy52fIPP7sL3nwk96cpiZQoLXh+2zCJJV5IBI6rbcdeHvPJVRUSqgiKnrNNzf4oZRxrNrHEEXEwThB4nt2V9IPjINO8dTjCe8f1uuF4ljPuwgXi6U3FvXczhIEXyxq587paF57zat1ytm7ph5DKI3ebSNsZ9kYJ7x6OuNi0nC9bPrsuWdYhHrTuLb2H1bIhT1XYXJ0HIcl2yWF/74dXFIkiTyUvlwNaSZTwaB0ue5frmutNw+W65Wgck2hB3Q0s6p5NNyCFYNkYJonircMRp8uGzsCmadFSvr54Ge9J45h5FhMrQRL1eA8oGGcR7+kRDs+mDJPocRYRS8HJTJIohfUEmHQkgpVqBxO8qQKYdJwKJlnCcRoxKxKKKKKzhqNxYE+dr1ucF8RK8WB/wuW64Ympgt9ZSkazjGd3NY3xGGeY35/QWc8kS0ljTdW5wMia55yKaqekUOSp5mbTohB842TC24cF3z9b8+Kuohk8kRCs2wElAlDwYJSQxTGx8jy9KRmcwzsRLHjLlkgpkKExtOwg84YkEpSVobeSNIoZJQKEZD8NE3DvHHd193oBVSr8fiqjcF5Qdo7ehkO9jgTdAFVnGJwgjwV5JlHKsWn/6anxq/9ff8m1QhMWe+O/+s0qjcIG8GuSrAPwz+/+99/63Mc88J/6Gp7lF65YSd6Y5+A97xwUWO95sijZtpZYKyZZzOmqBJdwWCSkWnO1afj0uiGLFL2N+ObJmB9dljzcyyn7ECsfa4lxIYjgtu54c69gnEfclQN3Zcv1oqOIJbNCc1P1TGIHIqjQNm1InpwUmrNVx71pwvmqoe0Hni36wJyxHu8cizKhM55RKohHKR/cG4ffwZ0EvMgixokm1ZI0kgzGUw2WvXHKNJFEkaJsDHka44Rj6AM4NVaw6QWPpxH7o5RV2WMsKBkSypRSvL0/ojdBmWKc52Sc4YSkagf+6NmS+3sZ7x2PmWQR15uOP3mxZtsO7Bcx751MUCJwevIoQGEXdcfz6wqlg53aOcGm7pjmAap8UAQLdjN4HqUhyfRi3TBONceTmFgrtp3ltmzprWPWGp5eVWgpEVJwU7aMk+g1KPbBLGOU6GAXU5K3DnIG45AKtueGNJI71pUMjZYsYtsaDnZJQ28f5txUPYiK623HJNNIIbkqG14uapJIcjhOmGQR22ZglGqe3VZ893TJs9uGcR5+bu9BKcm9aUZvHM0wIAU8v6l36XyWm+1AJGv28piyU0ghkYCSmofzjGgX7PHGLOViVeOc57bskUJwve05niTMC4XxCQZ4ez9j21rS3WDrYJTw9K7iYlXzYlHjnUWrcHH11nG+qpkUMVrAvSKj6XouVg1ZqniQ5VRDSFjzIkDeEyn59GLDYB3pVNG0ls6Hw3HVhjjwaaL5xvEYIRS3VbBeaiWYZzHvHU84vSv54W3Jtg62/iSS3Gw6Ui1I45i9ImFZGzIdWHinq5p+8Cy3HWXTkajQaOut57buWJQ93sLdukVLQTWES8627lAinIU8u+aQ95Q7VWsSSwrlKeugU3U+sDes2yX48OM95Ys2kL4MN6OQQdVVdRbj7evm2a94/Z+9939VCFF77//+1/0wf1n1RZtDXzTB7VVT6mIVrGCRkvz2ozmremAwlsNJym8/mgW1gYcfXqzZNANSwmUZzlmRgG/dS0KSmwu/m/ujlH/pm0cIwvk8OCnCgPvBXs7jgxFX24ZVFRr+4yziZJISacn5qmFZDTzYz6g6R28sL+5qHuwFtee2NbSD4839gk3bv2YGdYMl1iGpMdaSrrPcG6dEkaIfLFU38MfPFiRRSH+eJBF/9HxFP/Rsu6Bm6Ywh1prLTccRgkwHlZUXBPX/KFyi00jxyfWWshloB49bNngtAs5CK5blwJvHOft5zGA9i7oLw48yNGzWdbfDP0CnJQejsObPck1nHM0Q3A/Hk5Tvnq7JE41WgjSSnC5q9ouIh3spH52tqQbH9y/WvH8y4eWq5nrToqRkUfVse8O6Cc6Iq03Le0eT0GCvapZ1SxZrHs5TPrupePuwYNn0RAIWdeChjRNFOTiMtXjhsYNnlCrefXOO957GWE6XDWVn+XCXmimVAuf47DYkSTvvd3ffiEgpJB7jdiqkHUPqetWihOLZ7ZaqdXTGIITnetOhBTghibRgMLBXRAxG4J0jSQSx1lyXHcu2xnpJpsJQ/WrbsagGprnCuUCDNrvQG0FoorxqkEAYAOe787d0YAWMUkmtHfS/PAvxz6pXz/bKxvZl7wQCwIFQkBIGEIYfN48AMhU+p/E/Tvr8/PeRu38aAyeJZppH/Paj+WtH0ldZXxSi/W8LIf4/wN8m/Iz/Fe/9H3/lT/MrUM75kNw1TVnWATx22g6ME835jm0U6+DLr/uweEdKorXkG8dj/r2z9S49BL79cIpE4rwH4VnVPYt64K5qMMKyqgfmkwj0iJtVw6IKDJx7swytQoJb0w0UaUzTW6I4pIgJBPt5zMtljfdwb5Jxb56TJxEQkqWsC1L8F4uKH11u+Oy6JNHhzzd9x6btuT/LORwnfHZTUjZiNxGVGBsmdvtFQmNDtK+RkkRJLlYNxlgOJxmZgtaE9JZFNTBNIlrjGKcabx1JpEm0ouxCxOK2NayrgbILwD0lBVoIztc1b8xz2sHRDjYkE0xSVk2Pc4JVa3gv0RgXVF132548knjvqRpHrAUPDgqeXW8RCA5HCdYJEulpe8NoltI7x+P9gic3JVIGULKUkkmk0Sps3gLBW3sZi8ZwvmzobeD7/OnLNf/JDw556yDnk6uS7mLDvIiII3C1ZNsZpjJsZI6QIHBXdeA90c46ksiQfPTGXsEnFxuKWFLEMZGCbWfJtdptxopt07NsBipjOciCPWTVDBSJJNMRxlh+eLlisI5v3Z+ghOS3H0+52naMs5BuUPWOq1WD1nIHzQ3d/URBJgVOBovJXdniLDjrEELS9OFnWDcDvZPEUvD28Rhjg3VnL4+Z5QnG+B2Q1JLEgTsxyyKKWCN1kMFOsvCzzPIYhGSea5QMDCvjBLMsxdiWqoVeBtuLlDBYRx57mgES70gnMY/nGeeLEu+g7UOTzRqPwBBpwaL2SB+697EO78nBgNbQdwObJshdIUyMlSJYK3aLcBaY9b9QF+iX0TwCuD9LeLmoaQdDlnzRXv/XV977v/t1P8NftF4l5vTGcr3teWM/BxusxW1vGaeaPFVAsOL+ycs1j3cJNFmsiaTkeJzQO883742xzvP7n93wo4sVzsNvPJgzSjSttcxGMZc7MPNt1bCuLeNEE8UDI614ug2HuTySrBvDJE8YHKyqjtsyNLqv1gPLsqfpQvLJOA1T1jRWXK1bkljxx8+WWA9vHeaMU83pUnO2qljXAzdlR90Hpcg0ixmcYxxpiljTD46rTRcSqvKQQBp7h8PT9Y79cca6GUiUYogU9/YylFKMIoGWAqXAesv9ccyyFewVCQfjhM56vnu2Bud5NM/YdhH35zmjJEII2DSGLFFcbRr+4MmC803DXp6EvcFZhAiRxVpK3j4ocM5xOI52r3s4EB+MI07Xmrb3FIngYmmYZIrWOMrOEEeSUaJ5uWjph4q3Dka8fzwKTYw84p3DEU1v+O75mlEakn3+znsJ/9GH14ziiHEWMU0jNl2Y0IYknwQPHI819yY51js+uezo7ID0P459/4ef3TIvgq030oHl8fbhiN56rlY1VWN4996EYbCcLRu0CE0/SbBG1L0gjcPeeld1yM4wHRxZJMlTzTxPUAg+vakYJ5pYSx7Ocqpu4LLsGYznzYOCURJxvW7oBof1hhe3jjyLKeKYwTjuypqbTYdA4pznrhqYJsHmMHjPqurIY81snNDv0jLDRUQEWHeRsCh7JIYndx2tF3jhmeYhKnucKLaXJU4J+h3cwgjPqu4YJSnWOKJIcpDH7BcJL+5qtr2l7A2NFcTCESN2EOGIb9+foKXgcGSDddnBquwwDvqh464KKX1prFhsWlZtUDulqaBuPL3zCOB4FiOkIJURxhgGy+41cnjvUFKQKUkcaTrZIhXEscYMhrINA4xchwM8hEvMK5VqyLML+8VPsvW+jGW6ciB6yGfwxrzgZhvsSL/iTSQphPg3gW8IIf6Nn/yP3vt/+2t4pr+U+lnNoT+vfl6C26v3i+dVkypisC6o2nWAw9ftwLYJiqO29wzOcn7dM38c8dnNlkXZo5XcDRcc8yKs84/2C17eNTuFUOD9HI4SIimIdIsxlsELkHC57djWPUKCs56mN7zYNtxseo4mCW8ejPF4Njt17j/4bMWi7EIiV5GA8ByNEi63Lddlz3tHObM8QWvB9842jDJFNwQOjzWe1gw0Q0AwjLIwgDkaC04OCt46yNm04Q4xSjSTRJDEinUbeEfXmxYh4N4kpeoHzpcNcR4xSRVVpzhbtHz3xZpRFjFNY/YLzfmqpekCT22wYViax5LDUcIHJyOWjWE/jxFKcDRKGKyjt5ZZHrF+9doPhlXd8+S2QgKRlpStCarVacqLRcN3Hs3YtgPPF566C8OFqnXclh0HZUzVWm42HdM0DMffP5kw3yEsLpYt7dDinGPTBitdT7AT9s4yyXLeOxrjPfzRixX7k4T1TbNT/kIqw5k9TzS98HSdoewCm7VqLNvBoYUn0Zo0VUSEhORl1XE8ybn0FWfLcFbojEMoRW0MSnha43lU5Oxlms54Fk1PkShmJmZRhtTrrXE71VqPMVA3lrf2Mp6vW7z9sRUtGNf/bLO9CddrNAFvQe1o/rI7R7va6cboCM8j+GIM1ZTQDHulrBKvLHo/5XN7G4YumYDe/9PNI8suGU6AdZYiCee5X0Z9UYj23wR+8MqKIIQYCyH+Oe/9H/xSnuprrFf+4lEahShG67jdtvzgfENvPbGWxIowwdoGKOrRJOHRPGfbGN49KuitZV31PLupeHyQc73puNuG+PiLTcvJOKGII067mrmOuTdOKCLJXdnzaJ5xMssCq0hLvnu2ZpJGHE1SPrg3551Vy+my4tliYFpEPJxnvHlYcLpomOUR96Y5h+OYs2XN/WnG1boFHNZ5Wuu43HSkUhDlmvuzjNNVzV3ZkSead1PFurG8XJVkSjJKFbZzrOuOk3FGESu8g7M6LDorYBxrlBR8+96Eb5xMMM6RKMmbB2Oe3DWkWpDEKb/70S29tezlmr1xQhpplk2IlD8apby5X/Bi2fBonvEnpxvyKDAXHkxj8kTRDIYfnm+IlAhxzYQkryxSKCUpuwErBNaFhJoilURSczwNU8lEKzobDq/bLiSfDc6SxwFAWqQKISSdUVyXa54vevaKiONJhvCeP3254eE8JY8ksQqa9aZzxErwYtlxtmyRMnz9/SJmMJ4o0lR9z6P9BI9gL4upB8dsHLPpBtb1gPGBI7RXxBg8x6OYd0/GXG9aPr0uER663uB9kKsuqx4pJUp6Bmt4clMzySJWOwi1cyEKu2wHbrfBBri2lnGekGpJNziU9CRxxMk4ph9CYpwgAGk/uSyZFRFxrPnGKObpTUXfDTgEH5xMEAjyRPPDsxWNtewVMfdmOcuqQwrJtx9MsFZwvixZVkG6+3CeByWuEjy7LalaS2s9eRysao4wuRUiNHlCBOXAJJEByurCob81niEksL62n61bmCQ+NIUkbPsQX0kQL+FtSCWQInyfAZAeoh1DKdFhciEkdD/DuvbzJgmOX86UI5UwHaXkcfCLz38J3+OrLiHEFPg3gb+z+9DfB/4t7/3663uqL16fT8xJogDSfn5XhoFBpHhZ1/QuHCSLWO2A94KXi5pF2fGdN+aYIajgVtXAW4c5v/fRLVerhm6wREpxvWkojsZoJZjlmu+fd7xYlJStI45CkyH1sK0FkYRRnlB1Q1AbDZbffDgljSVX6467XfLHKFUhHTGOMD4cVqd54CJhIU8j9oqYzjh++GTBNIsDMNh7bsqWeR5xPMlJteTZXUndGbJYB2Vnb+mMYLA9kYa9ImVRhgbVNNM8mGSkiWScTRkninXr8DtrW28dzxc1oyzkftybKS6XLeNUU7WGeR4jlaRIIp7fVHzn0SwoTqRgWw3cVT3vH48ZpZqPL9d8el3ifQgFsINlnodmxv444WZrsX5DphX7RcQPLkrK1mAGWHUto0Ryb57TdBaHwBhY9oYsEUziCCk8P7zacnZXI4Tgw4sNSggc8NZ+sWOpeb71YMJenrBpA4D7dBXCBrRU3JtmNL1DI1lUHetq4HrdBF6GdwTjMIziiKY1qN17px88UqVkytMMGi8856uaqjfcbjsORgmzUYKUkEWKbRuaaMuqxQnH42LEo1nK+abHD+E9fLNxtMZTRDv47KbHYxks3N9PmXUx27ZnWQ+A46BImaSS3ngkPjTpbVBBpSpE1TvnUVIyyRRNM5AnEe8dF6RRxGc3JZNEMxQxaSRZ1gZEaORXbU8aadrBhvS+wfDitiLTIaHoMI2II0k7xGAdzxcNko5JrjmcpiglOV/VnC7KnQVSMljoB0uqQ+N0XsSczHOchTePJf/xh3cB1Lvp8DIcppX0IRRESgbjdqoliXBAapF92CeEEFS9pe17euMZJ+Gyl+/2oFgKBgcjpRCRRNnQ/BonMZFybLqQiJfF4TXsbVAMSRUcKc1PbCYaXiu9v2h5wtdVUsIOq/DmQUEif6V5ef95gntBE7hH///6OfWzEtzuT1JOl0HNWCTxn0l2SyLFvVnG09uSy3WLdS4McfuBpjNsW8OsCMPYP3x6h1Sa+7OUujNcb1rMTsF9sW7IleLhfsYk1UgBZ6uGu7Jj2w6cLyvSKATkWOfZdD33RinXuufeJMVaS9eHQWTdm8BGShR3246jccLD+Y+5ooN1RDsF1CxvuNl0rFuLs5am7RnHGXdVz82mpXPBThpLyShPSHVoDq0bw8WqYVZEOBdeOynE66bq5bLi//bxLVLs3BwKuj6oZja14XxZ01vP05uKvSIOg9+R5x8/XZBGQd17tR2IpOfb98Z84/6EcRKRRJrf3h8hlaBuDX/4fMnVuuVq2zLOVHiN6p5vnIz54N6Y//iTO7I4qH+lFKybgW+ejPC4nX0+DymwGj44mQIe6yTXm5ZFNaB3rpGzRU2qNeNYU7eWe7OUw3HC1arme+drut6itWAvyxklGiHgwSTlsux26AzF4Sjm2U0ZcBRpzCiPKKKAnNgfR1yuW0pr6ZzHW0PZWW6HnjyPSKXiWKbE2vLWYc6PzldIKWlNCBGKkrBXaAl+cJRdR9NZvnl/zCiLqHtLmjj2Zc4wDJyuO5o+nB3uz0KA0WbnulEpNIOn/RzM6PNr5ectY1rA2n01/NIvowh9VTvX/+sml96po36yPn+nSHeNoM9/mgni859693jFD/I/5+EiAf8/7v481tZ0z++DPs/wjutdwx7PVHPd7nu723abtrHjEJQgHEiCBCJMUhASIiIKEUJIkRBC+ScEIewIQRitEAUFIsE/RApYiQ0xQcZg43a327e771xVZz5nD2te7/SM/PGsXVW3uu69ddt1+9b1Ix2ds/ZZa+93r+EZfr/v9/PNj/Z4rSTX+4GTn4FK9YuWpf63wG986nb7OV/7B2J82l/sQuT5uuXDm5ZdNzCtSgTwbN1TZorqnkrSx9YQQ+SDmwO3raHMFK9MwAZDJH2A+8Gxs2miFEJAjDiXgJmLumCwkXfPG/6hr52ybh2H0aGEQB2B12fTJDd967SmLBJ/6TAkJtH5pGBSZDyYF1xtB9atoXee7aVh11u60bM8jLTGUWcarcHZwHdf7zibFnzjwQwlBC82PSdVzmmVEYFVl7pa+85SFhobYdUbDkNEkDaDlU4e7PNpSZFLsIIQIyqT/CO/dM7f+N4N336146zWPDybIoLgr3/3mq/fnx8ZUJHOJFh0oSWhyHj/vGbdGVatoXc5780qCILnm44iU1xOCx4uaiot+P51S6UDq85TaYXOc94+r1EIhBRMywwpJX/yrQWPlz3bznAyyakKwUev9uwHS6bg8dXAtNYUucIDg0uMCSECWqY0svYIqx56l6woITDYQJ1pnu72REGKU47xqAqrMN7zbDWiJXzwuuWX709ZHgz35zWIAU3AhMi7lw2vVyOTTPL+Zep+P1rUPF7uOYyW0UaIFqVzTkoJUfBwXvP9m5YyT+yVJs8w3tMowc0xHU+IVGwyAd6/qFExY5d5yiJFPt+baZyHqkxWkLoQicHkAvuYUtpOm4IYocx0AsgOliJXYOHRokIqSV1kNLnk0bzi91/tkFLxYJ4UDfYIBBchMhqPwzMYz7ZPxaJZlSaiXZ8kspNSQUwA4CrTKAHWenofcO4ODncsCIUExB4cNDmUOn3P0aUYyyiOCW2fqtR7QEUYPTQBhIZcpILo540fpy76WTU6cgn9YDi5nLEo8p/8gK/G+DeB3wP+y8fb/zWS/fmf/rld0U8xPpuYczkt+c3HK86bjLcuGk6nOR+8brkyjkIlaO1EJyVqkSuM8eRZKnYPLnAx5nzz5TYpB7OMKOD6YHjvMsFuv/l0x0mVM60LpDAcxkCeJ+5bpQVeRD68OZBlAusiy87w956tmRY5gUjfO6pKp66wlIzeIUwqpjoXeHBREaIi0wLvPK/XHavDwKG3bI3nstEUR7uv8R7jU3rWZZ1R6KQA0plkUWUg08aoziXDKCiE5OYw8uikxnl456zh5Sal/ExyzaNFwbNNT1VoZplk9JHNwYAQvFiN9MbzcJEsFnWm+M5+pLreU2War102HKzD+shpU1CXiqe3B5pSowWIY2z9YB2HwSZO3sPEFXq97bEhrY3LvWFaKZoiY1omq3DRaJZtsh4PDs5EzmlTkivJajcQicQQ+cHVHh8j55OSxVEBU2fQ6ywVE1cdN7uBe/OKWZlhXeA7r/d8/d6U3nncGHEeWhfY9AbjU9jFwXrWg4UYaMeUQulDStIKEZaHgfXg+NX7U946m/A0O9AZS5NLlEp2Lhscuc5ZNBmZFERnaW2gN47rrWGwARMC502RmB6jgyiYlYoy1+x6y7zMWO0sNsSkblaOgxVY6xBS8M55w80hNXgGG7hoMkwI9INnszSYEHjztKHSGZ0JDM6jhOKNs5rbnWE/DBxGhyQiBSCTtcQEj3GRm4NBC4EAehcYg6QuJKsuMM0kdVnwK/envHlec7NPTMdl74gxcFKVtH3L1gaMN5w1BZdacV4XLKY5/+Hvv8Z5j/GBi1nJYByHoef2EMmOfAmp0ue9lGCROB+ZlFBnGcPg2HSOKk8hDpkWXO8MUkJwgZBLvHdsBnBjQKhUzBpcAJ9+htQwzxPTJQDTUjCpEsdJ+R8+9DhS5/inPaxE4OYw8vvPNvypd8+/rGnwZzZijN8F/oIQ4psxxn//5309f1Tjsxa0Lzo+L8FtN4x8uDxwtRtpygTRLjP1Q8luzqXUZ+s8B+PZ9ZaX6463zmsKK9BK8uFty653PFwofAjsjUuoihDJcsXuMPK061iPI+uDoyk0T9cdX7tsOJ0UDNbx0U1HbxxlnhQOXsCH1zuerQ5M84yHpyUhCFpjyZUizxTffr1HyaQavJgWbPqRvg3MqxRGcDEtWe9HBAHjI4tJOvccRs/NbqDIJZKAQFIXmt2Q0AbOp7TPv/2h453zCb98r2HVWqpM8WTV8v/9YMmrVcf792dIEfnwtiP6QFnkfG+7ZQyBbnQcjKdQkk1neb3tWbUjJ02eAiWiJ5eade94fNtx0Xjeu5gc09U8v/dihw8BH0HryN99suGts5qm1FxMSz64btm0luU+qZW1knQ2JYOuW8O+swwuJCafyLHHdUGGyH4wGB+wPqVYWx/RWUyBM70l08mCbUM8vlcEvQ08W/fsyoy6UDxZdYSYHDbWh6MCViGlwsaICCCVpNCJDyWFZFoo1n1gNCnpbPQONTiKIqV7dcbzN753w25wzCYa7xUxCobRogvJaD1SSLrRs6h1chDYwEmtj9cd2XaBWaGpco2xaa8zr3LOJ5pNq3i57X+oePTpkfHDkGz/JRWP4A9RPCI1fkef/i34pHiUAbM8FX1MgCJPbpDBQj8eodsKrE/rwZ1SFT7//PFZVVN+/NrdNUsNF03CnORSYH34mYQsfGGIdoyf1LtijEEI8dX3VPwhxqf9xR/cHNj2FgV0FrLM8mAx4TDaVF1UiZMgfdq8fXCTEgKIkiJXWOt5c1GSC4lUgpfrHuuTz9NvIj4GSl0kaJZM1fIYUhy7kILzaUGdZ2lxCIHffrrmYlrgHFgfj/YbgTm+NOvecRgtp3WBcYEPbg68XPfII1wxRQhHLrKSB+clGYLzSc5ZUxIIfO/1gXvzmn0/shksUiZvalMlIPQkzzAucjHLOKkyylxiTILr7a/2vNoOPJyXLOucyabn3qzkz75/ytWuZ9tbPrhuE0jUpk3r7cFTacHbD6aUSvFy6NEqpYLdHdCaKhV0zmc5N7uBB4sSgMOQuEjfUDJFQzrP2STnrfMJ8zJn2xtOm4y3TibMqgQmXx4Mj+YVY/A8vj4whEgpBU/WHVe7kegjD89Swe92P/KDq0Oy2inBrPRczirePJsgReTpsmdWZuxaw3Lfs+4s01LjZOC2NXifbGzr1lBkmjoXjD7QWUep0wHnet+jJGiZsT44skzyeNUznRR0xqNk6uB4H3nrtMT4wLI1DGPk1x4tmJY5k6wjhoiIR/tXiOxGx21vuJwmuOKddPet04JXe4POUgfiYDxXuz5BRQlsDiODD9jdSJimDk4CFMJ5kxKhRAyMxvLexYSX647N4MikoM41Qgh+cNvxct0xyRW3x8XycloxKRQ3+46Xu4FCCcoiw/U2MYuAMaaFQAPz8k55FEBKjIWX257TOuMweHr7ibQzkKwCd5V679IknhWpiHSwnz8BW45KJgVjSBN9IWD41Krx4zoQd27in1UByXvY9o4//8cuqetfGIj2+zHG/8Knbv/LQojf+XldzE87PpuYY5zH+sC6tUd48cjVvic4KI6WpUzDro1USvB613NvWtDayK+/MSP4wKSQaCQPFhVPVwe8g2fLA3/6vXNud0Pido2WdeforQOpmWaarNC40eBjoEBTFgJrPVfe8njVoxEMmaSZZMyqglkVWbdpndAqo3Oededox5Hb/YgZHR9tBkQMTIoM4x03u5iK9jatOdMy46LJkUj2nSUiGYzlxdijhOD+vMC7yL15yatN4snc7ke+fq/hZpdc+ufTnEJrlITt4Hm0ULgAB+M49JazWcG8Utybp92UlIpppXn/vOberOTtswnbwfCtlwcCgkJLfEyBAyd1TqYkxz0yZZ54TWezktNJwc3OMBhPqz3r9sBiUiBFqnytDiNjrtj2LhW0XTyymhzRO56vLNveECLcHAb2vcEFmL+dse0My0MCrr5/MeHpquXmMOKC4J1FhQuR0QXmpeKkzvjwtqMuFIPzfO2y4XY3oJSk7S19SKCcPNNYnyxV3ej43RdbikwmK1yVoVVqTNVlxveuD7iwYVGnyOw6T2zF/ZAYghZ4uekTl++4vkwrTSYEj5d7Lmc1szJj0xt+9+U2sa+0QmkYnePerKSzERlS0llTaJRSfP1ew0dXLa709C4wLzXzQrMfFZ11hOh4vet4sKh4NK/QRNZDsnmeTHJmueLDm45prbk9GKpMoFBMtCBEQTc6zpuCdW9QMuBcpMoVZZkxqzLyTKERnDUJzv1wWvDRsmO/M7gYmWRwOa8hpv3AB7d7fr04oSkyujoyhCHtrYJASEWmXApTsAHrA0hY94kTUueCaZkz+IgIkSKDKs9ZdwO7ITB60CGgdGou5QIyIpNCE2TADmmDro5etUMPzhlGCyjwPnIYLSF8sq58zPI7/klI+S8+pEiKtO+93vOPff2STH35jIufxYgx/vtCiP8M8Gsk98bd1/+HP/pRv5jjx1nQftL4A+uR9WkPuyjTvOiP9qYmJ4SIiCkI57efrhPMej9S5QmovOktctnTjY75JGO0gZvdwO1h5I8/nNHZxDd7+6xmsI4ntx4tI6+3BkHaf1V5Ktr4EOhNZD+6pGaR0FQJT+ADKA86k8eiaCQEuFikkJ9VTAzA3nier1JAjffpuq0PKCFp6pxSSwppWQ+eXTuA9ykspSyOKc6R28PIu5c1Z5MJUqb0a+MDwUc2fYJV/50nbVoHe0ueSbbtyKttx/V+xPtImVuWuxGVCcIRSr4ZDdMiYz8aZlVKOFz1DiWgF54mT2ByLSX/x7/5lK/fazhtcp6vWm4PI48WFbshWYqdj8go+ObzHY9OCmKMLPcjQo5se4NWikWZ8cai5gfXe6pM0RvP2bRksD41SYw/HtSToGBe57xZKQ6D5/3zVNB7sR7YDamscNoUvDziTYyxdCLy0Y1A6yWV1kBk1xuujknFD09KlBAM1vNq48iUIIbIYlpw6EaMC0gRUVlGk3ukEmgtKJQiItkOBusTTqTUKrHflGCiBVsD2THtuR0D69GQacWTdc8wWqoy46xJSsreerROabDn04JNN7Lqeoz/0fPip4tHd7ygn9e4u8YiS26KTEAQgm6IRKAuoClLbg8DTVVwWmuu9obBpHqCPJ5BQkznm4If/Xt/+mxyp2CVwEQlPEdTaaoiQ4TI/sgkE19WZe1T44sWgT4UQvx3SKojgH8B+PDLv5yvxigzxWVT8MHNnnuznO+8Niz3A996NfDu6YAQgncvmxTV6jz7PiV9GOd5unIsKn2c8B1P1gNdb5lXBblWjD5w1hTE4OltijcOMSWNCZHiljkma11vDVoZNr0lhMjbpxMenVQUUqAkPJpX3LSWj64OXMxKlvshyfiUYlFrlm3iJRkXUpJWplEiMCkV+97x9mnFw9MJ719MeLbqQAiUiDxc1Lx6tqYfDEOhOK00r3YDPkReb1pOJwWjjTyYF+xGz+U08Sl2/UiMkT/9zineB37ryZpdP/Kd1zsyqcgzybq1+BDpx8RW8iFQFZLTKmcIDudh13dMyoxy9KwPFudbrAs8Oqs+Lr4I4L3zBoHgzfOK15uBaZkx+sjyMPB3n26A1MH+jbdOmBQKHxJc2VuJVJKLpsQ6Tzt64nEj/+T6kABmShHwCKEYrKfUilxKWmMgCIL3rI2jyAU+wmldcH9eYlxg2xsOIm1axwBj74ghLb698fSj5fm2Y5ql722C4/n6wL1pSW8c/89vvaIpMlqXujBZlnHRaOZVzpNlixJJufW96z1KKT5ctuBFUkQ5aAlEn5IStBIopSiVZpLn3MSOXOdoIkEJilxTZ4pvPt1xMCnyWiN5uurQSvLOWY1zIaVo5JJvPtuwM45Jrth1nkcnFdNaI6NkUkqUkmRa8nuvdhQalgefgPBV4nONxlHUOYUQUGo8jlkuaE2kJ6mRpJD0zlNrzXsXDcF7DqNDS4/5lNb/rkqv5ZFlJNPELWUqHg3uk8n1s+NuLjXHVAepPoGeus/c5/PGz9pi3dSwqDSZSPyRrzjb4m70Qoh/JMb4NwCEEP8xoP85X9MXHp9OzOmt5WqXULivtwO/82ydQKTAH3tzweA8625ksIH/yFsnFJli0xp6G3hUKqSUxyCFnNvtgFLJHV9XSQ7/at0TY4KIgiREj1aKLAqklHgXMC6tA0rC2STn9pCs0CeTjKYsiCGybR1/5mtTcql4sUoBCzYEdp3lI7cnQNpYCmgKQa5yJImH4UMgCIXUAhEjj+YVWa5QwAe3LT54pIRJrrHAGDwvNj1ndU4kcj6teLbq6QbPk+XA5axgsIGvXUwYxkCVCXob6Y3lw9s9tVacNSXPVh1NoZgUGb/ycMJJnTE58nj+1odLnq47rAucHe3GuQwEUiJh7zxPVy0xRk4mBQ8WNbNKM600H94cEtBbpJj1H9wc+GMPptS55tmyTWqvKkNax80+Mi8zmjonINmOKS1m2zqIkWXryBV896rlbFLyetfza/dn2AhFpgkuYEPgyW2LjZFKKd4+nXBa5/wgtEdeRuLORSH52mXDi83A1Dk+vOpwoyWTEhNhUmgezgsWTVI4f/PphherA0JJSqV4tJjw9nnFprUM3uFjsllJKdiP6WAVo6QqJNcHT4yCqoDXh4GrzYgPgtf02BDZdiNykix4503OaZUzn+S06xbrYVbmFJnGB8+H1wOLaVKg7jvD7z3fsOosnfEsypxcSgYbyLTiP/0nzvjND9c836zpZYKl7sYAMjKYlNaz6xxVqZmUBYfBczYrOW8y9saybQ1IhT7GZqf02J7DkIp663Y8ptRqbjtLHCMByaG35JkiDyl17e+9WFNoxfuX1bFD7tAiMo6pKRHica23MC2hKRQ2RKzxuMxzUeUMmaBQjnVvElPCJ8XqoYdJDrUWjD5y03mig6ZI60482rDboxV6tKnT3BvYB4hjgqN7PuF53CmRDJ80Jb7oyDVM64K61Dw8qX9R1giEEH8JqIH/BPBvAP9F4G//XC/qZzB+lAXt0+E7P258NsEtcX0Uq87iQuKhSQRt77iYFzxdJ0WQFGCO0gfv0772oimoC83gPB9c7ZkWyR56s0v780IJfvXNBct2ZNOniPvRBZRIQR6j9eRKHVWfjhAihRb4EHm565n0yQFR5wIfBa/WPW1dMC8Ub57VvHPW8OzYzF7uDS6khNyHZxVyA7c7gz7uYXMlee+y4fW2B9GzE5rWah4IgQ9wVhW4CG8sCk4mmrNpyXZwlFmqzrbG8bvPN0wKTWvStQ4+YF3gybpn2Q6sDpZSHeH3MbLcjCgJs0qjpEaRlOyndQpoqfMUklMpiXWOSErMfrVOKqX9aD+2rl3OSqwPbIaEGbmcF3z/6sDrzYD3jihTUVAJxUmZ05vE/FtMct6/SMUoHzwvN4bFJLlBziYl33y+IVPiGOIwQR2h/1+7nLLrXUq9m5eMDsQCrg4jw5isZ3UeWO0tzg/URcZFk7HvHS739KOnyiW9DQQf8JngcloSkRxsSsnOpaA3hkyln1npxOfLi3S2cCI1wNatIdMCSYJpjwayPCIKRbCW5U4iBXgfaMqcNxcFH6x7JHBSarbGsygKZoXm6aqlO3Z6f9Q+/o9qfLaZnPP5fKLeJzbR6CBoKFXk3klG21t8BON8wmn4wLZz1JmkL2AYkzLp04wnwU8+v0A6r+jjnyyHJlcsjp/3PNM0ueL2YHi67ni4qL5wAfuLjC9aQPrngf8F8C8dr/2vAf/cl3YVX7ExHOMolwdDZ3yCIecqSSmN5+FJxbTIWLYjV9uB29Zw0eQUSmFCsjCVWlJMKpSAR6c1q4MhV4Jpqbg3q/jweoeWgt3oIETawfHevYbtYHn/subxTc/v3S45GM8fezj7uPj0wc2ex7c969bgZlBoAQLW3YgPMCsUTaFox4BCMJ9k7LuRs7rkZtfTW8/Vuue9ew1lprjZDXgfcD7w579xyWa0XG9HRAicTEoO5m7DDsYFMqUYfESrwL43FJlCyKQaUipFPX/z2Zq6yJjkCTB9b1ZytTUgPLvB8uZphZBJ/rg69Lx7OeXFuicieWNRMFpPOzjO65z7Tc7oI9Y4Dp1gLx3OJWmnC5HrQ8dyGBFR8Ho/MjrLi9XIrMxoKs1hcPy7f/c5b5/V5FozLRW3+zFFbvvAzX5gsIkRNT3GfPY+IAlcTCq2g+WyKVFKIZTgt56u6boEyZvkMhWIbKCzgXXvWNSaKRlVJonRs2lHpkWeAJ2jZ304MPjAzd7waFHjY+rSfHDd8mw1JJuCSB1aFX067I0GW0hW0bKoM4QUTJSidx4tFbkS7F3g2y93qUNdaM6ajMGn90A7Gh4tJjxcFLzaDQzWcNkUFF5yNslojUOqQKE1lVJsh5FDH6nLVEha7g3vXjacH2NIi1xye3A451kdk4S2/ciqTcW7D2+TfLouJZNMIUXktFKsekedZxxGC1HgQtqgdBaEkpxPFZmSFIVCWMHDRQUx8K1Xu6P/O3VdHTDT0FSpur+3qVp/x1HiCEm/S1T7cQyjj6Mxj3f4bGEo4xPe0h/luG7hbBJ4tUuMgK842+Ju/LeAf+vIQgJYA//1n9/l/PTjLjFncJ5xdHy0jHz/asdgfbK2Ws/zdcdFU3De5MQY+eV7UyZFRoiR56uW33y8St1gH7g/K3ixbPEmMC8zHizKBC0N8HCW8XLdcTHNyXUqSh9spMklZ9OKQomU/jIYVr3lMKSDwMWsQiCwR0Die2cz6krxdNnhY2SWZ4joWXYjUqaGwsU0ByTL/YBAUOaeaAVZJjifllxOcgYb6e3IqrfsW8ckz5jXkm5wdJ1hGKDIFLm1ZEpTZZLzRrMfHJNck2nJ9672/P7LLW/MC+qiYLsf+MH1nu3g6XOotj2CyMtt5E+8ueDpquP+7ISX254nyw4XA8NoGUKgXzveu2xSBPMk4zsv9/SD435TUZ4ozqcFZSa5PytZHoYEga0TK6i3jperjkorvA9olTqjX7uc8OFNx5unNefTkoumoDOWB4sCH+Cvf/eKVWcpM8XpJKfUgh/c7LhoSlaD4+blmmXrKVVKx7s5DKw7xy9dTvHHAIuDsdwuk00vEjk7NhceLWo2Q0r9erJMSXDrNhUpX21HlEicvtNZwfIwMoyGQkt+6d6Um/1IoSWEdPBctwZBhBhwXrJs05qWITiMhgicN5pplTrpda4ZbGDTO7QUdA6kSIer985qTFNQF8nmd97kfO/VFoRgMcm53qaEpcF6BFCqZLM00QOaOldYHzmpU/rb0/VAZyLLdqTKFJ31vHM2YTCWRZMjjoWfzcGxPvR0NimP7s/rVIAZPHUBMaaAkl3n+NbrPfUxmend84oPfOQw9NggUTHxKCc5nDYVjxYa5yKzKmfTWS5nFYXKeO+e4uWq5ZUdqXNYVDkegcQhc8miSsWYE11yve95vbd4l9SpmUqHg2hAu0iZAUeO3s6ktccAi8QVpsgSiy/Tia+XK9h1P7y+3B0Cwmf+/qKjt6Bj4NffOOF8Uv7kB3x1xj8cY/wTRyvbvyyE+J8C/87P+6K+7PF5FrRPW82+yPh0glv0kb/1eEkuBbMqI5PwdNXzqw+m1GXGYFJiWK6SXbUbJdvBAYJFnRFJ9uJplbOosqONuKS3juAFz5Y9L9f9cT1TKVE0ROpMUZ1UnE4y1q0jRAgx8v5FQ2cC67bHR0FTJPj8aAKTpmBeKlqTrHvGe27bMTUlNEQreLHu0FoymHT+yTPJrz6YsRs8uyHFz8+bgoenmupGcrUbudoNyFLRKMm0zjA+8OHrltEHvBDEGDn0lgezkj/5zgkhwEe3By7qnKfrntWuZz+aBGUOsNm1OJ+SxSZ5zmA9hXJIoTmfJaXWZhwZLDya5tgYuToMVEWeQo6O+wEpFYVOBfVvv9qBD/Tes20d3399SMrKXLAdFAsPe5NYc1rCYTRsW0OWKT642jG4iEJw0eRMy4xNa3m965FEcpUa1pmMnDUlSqRz2Xv3GppcMZ9qNgfDuocyk5RSsx1dYqa6QGsCm64lIkAEZBQ47/FBUGmBk4oYAw/mFd+/3nM5yegd7HvDrncYm7ihWxE4qSRFkMwmOTf7ge1gMQ5Os4y6kDhvkEU8YkocknQ+nVcZV/tkhQsEZpnm1aYlSkEMgp13bI5umbvAgZE/HJPoyxqRdI4oJQwhqYvMpy7mzkpnAeWOyWk2OSIGZ0FB38FBJfFDCBZkchCdTHK20jAc14e7M0ck2a3vgNo/alQyFZ8SZlZwMitxDpo8NdZ+5dGMRV2gBD9VAfuLjC+awnZNAuD91EMI8U8A/xrp+f83Yoz/k8+5zz8G/M9Jz91tjPEf/cP8rC9j3HUNylzxcF7x7dd7Nl2K0P21N+acTwqaUlNmgmkpud6nLpaQkrNpQbdOkc2lVlzM8o9Bbg/nFYNxmHAn4Yz88mXDsjdsR8tgA9+4P+VmP/Bk6XnrrOLts4bHtzs2neW0EcxKzZPbHi1TAYUY+darPZNMsh8sQgieucjDzjApct65mJBJ+N1nG/Z9UjLFEFlZw2lbcN4kVse2s3x4e+Ct04oq05xMso+7DgcTjulqicFzPsk5jJ4YoM4VZ9OKSZGRa8GLdZ+uI8QECy2Tj3Va5RgbjrJzzXI30A6BaSFZD55X2wEtJW+fTxhc4JfvNXzr1Z4yl2w7T6ECrzY968ExrzKaImPVWozb8Wo7UhcS66ApU5TWaH2KaQa60dOOKbGnyBSvdynOd28jr7c9z5YdWsG0ylhUOnWmc40Ngd5Zgk2dhjeaFNW92aWi2ZtnqSPc9yOP5iUH4xhdKkTNMs2Dk+po+VJs+hHrAiY6ZnXOZV5yUmsCMXm+25HWgPABLRUuRl6sWkKE6STDOclta5hXGe9eNFgX2I+OSZXjfeJ0NIXjMCTmVTumTbM2nkInwHiuJN95taeUklc7Q3ARGyVvnVSs9yOji7THYmk7RrxP7+FMCdbdiHnhWc9yXJT0nUkHWB9Z7g0nleZqP9KPjsGkjriSYKxLh7lOkeuB1giaSjHsU6KbcbCoEjQ3IDib5kzylHK17y21ltgIgUCh04QcQlpQMgUSicBTypS2Zn0qBMkjr0WSFp4v9Ln/nK/dJSj8PBatCFzvx5SSF35ey+ZPN2KMvwP8uhBidry9+6KP/SqtE1IKiKmD9/TmkAq2pWa/6TE+8HJ1wFjPfrA8WpT83otd4sBNcr7z+sCmt2w6x/WmY9MbHixK+lEwrRMfoCk111tDN1pG75lXOYgUY1uU8HBRUmcKHyOH0TMpUrpOkSmu9wOtcSip0BLGquD1tiXbS5zzrA+GZ6ZjcJF5pQkeloeOfW94c1GhlSQXQJ0zi4IHi4p2NFzve0YfuT8vkUKyHgzt4Dht8sSNkXBSZ0yL/GM+2fVuoMokm95xf57A3id1zstNz7KzXO0GTBAgBJkSHAbDk2WC5y8mBZNM4fH8f35wy/uXE0KMfHDVsukMuRZIJfj+1T7BtmPDH3/jBBscIkoCARfS5z3PFO9dTHm+SR3XdT8SfKRU6TlxIaCzNIeuDjbFrcfItjcQI0LC1+/POW803369pbceqRRnTU70EeeShcT5wJPVwM12INOCr11MOJ1knE8cb55WtKPlb35wy3df7Tib5Gn+sJHbw8Cut9yfV6xvLRdNzvV+pLOOQgoWTcEk13TWpWbUtOTds5qX62T37axn3SYYrSDwxkkNWQLbfnTbEaMBIXnrtEq2QCDEQF3muODY9yO7ztEai3eebQdIyeAk80LTu8CjRY2NScn03Vc7Xm4GmjJn3Y5c74eUwKck1wdDbz3TPPD+fEJdZATg+arj5jDS+6SpmVUZLiRLCALev2wS5yQXPLnpeL2KZEqilKKzI61LKlMpBNvRYbznZTRHCHUKvNhZR4iC7113TCtFO2p6m1S6VSZ5uTFMsoyPlh2zQnFzGPjVBxPeOJtyvR14se1553KCymIKcjDhqNBOlu4yVxSZSt38waNUKgJpkYpHgaRYkDoVjmxI9Twh0kZfx8Tcy44ngAh05pP//zSH78s4DAXgybrjzbMqRbb/4ow7VWonhHgILIF3f9KDvkprxOeNz7KOPmtBcz4gRfr6TzPuEtz21iZLdecQB8Oiyo5pwOm1zzN1PG9kLDvD5bQgU4L7s4LWOFwILCY54miz3B3307s+MfxiiCxbw0da8bXLCU9XPc57dkMKQhlM5Bv3G5aHkbNJxu3e0FSJr7KoMjwR00cMkXdOKnKtOCNZ9777es+H13v60XPWZBDi0RqerLtaCG4PA9eHgn50EGGSJzdGnWn+3C9d8O1X28RXlZArBTHBgae5TEmiKgWYZ0fW2m8/XvHwpKbQgt2QIuYvZiW10bSjZTARJzyRQFMk263xFmugHz1XIQXXpOTiyMttT6YkQkrmdeBDIXjnbMLjdce0SGv1rz6YsuoN651hN3ruTz02RHRwvHidklbXo8XZwG07oEVLlMnxcG9ecTnNyZRiMdFcH1Ia835MrztCcrsdUZlk2Wa8dTbFR/je6z37MYUyPF52CAXTXDIralbtwE3r2PWeKCy7fmTXWaalotCa0Tj2NqlWH55UKJk4gusxtUznVUHoLa2QOJvmQq0gxsh+sEgVabeOolBUPnBaKYJI9nCPxHh/tBinOe/lejgGFFhiFOwGQ/SRItd8/eGMQio+vNlxGDx1JhnGT6Lq72y+P69xx06d5KmQJD3sjx66T1/XXZoaQBfTf+buE85dJBV8KgVKp8JeriS5SPwsQ1I4BdKdf9I6oSI0WUr+vJjXFEpijGdWaB6d1Ikjq0Ticxr/pbKQvmgK218E/kekif+vAL8O/HdjjP/2T3icAv7XwD8OPAd+Uwjxf40xfutT91kA/xvgn4gxPhVCXP5hfpEva9x1DSqteeO0ZtkZRmshai6aCucDq9Zw62H/0lFl4GKKLRZS8vX7U1YHy6o1vFwPvHPR8HLT042e82nOaCNNqbA+0FrHWV3iQqQ3A7//eocxAesdN3vDvFIUmWbXGUKMDCaBGs/qDCEj33u943vXO6SUnNYp2azOJRfTkirTVFqy7i0u+BQDfUzrGgd4fLtjWivO6pJVb5kUmlVvOReC77weyCUMNuJDxAswPiXzvD5YHs5yfJRczmou5gW3W5Mo+S7Z+Na9Zddb6nxkP5TcnxW8dJ7WpGj3VZeUObdtYJIpXq877i9qHt+2aAVvn9ZIIdj3lpOJpu0jCOiGBPP7aNkyKxSvd6nzPdgEd32x6TitMzZ9KoxZ79mPlt54Wps6HN1oWXWpClxnkvOpZj94jA0s94Ym10yqFGHdDqnwZGxkOwQcgSAik1zhXPw4EjgvNMpHxsGyIOPhWc2izvhw2aFU5N6iYpYl0LVWkrxQSCuPEamOPMu4nCq2nWNvUuTzfrBMyhyF5KxRvN6PvFdnHPq04HWjR0vBcPQnP172hJBYWlpKbvcD75zVTPKM0yZnfRh5uhxoipxvPGzojOd2b8ijwyGOHSCF8R6XmKtIEeltOqgFAYPzbE0qPrko0CKSqWTjlEIgFZgQyGRK3xl92lTPG0WmFcpY1mPqwI3HGTceYefGQTsaHswr7s1KbrXh6fLAbvDc7hKwXUmoSzh0qWDkgseLZF/zJk3QFtj3nzAmFGmSM8d/C37YN/3jxs+7bFNpSZlnv0jWhP8x8BdjjJvj7RPgX4wx/ks/4XFfqXXCucDLbc+9acnpNM2Pow3kUrIeDR0RF3oi8OZ5Kny82vRsu5HloSeGxETKM4kyEhnhMI5c7QJFJsk2GbmUfO28xlfF8TMbWJSKIFI0vVCCj64OzOqcRanYG4/3ybpkXaC3nkIJ3j2rWO4MO+MYfCREgfMR7x3Xu5TWlTYhnqvW8HBaUGjNDM+rveP5ak9rIpNCMdpULg1R8PZJzUerjs6keT/PJFJIzmcpUe35pufNs5pcSorcsD3O+UWWIqQzAdd92iiXmebq0IGXeG8gpgrvRzcHci0plKbU8O2rPYd+wIWIDJJd5xkyR5VLOufprEVLxbzWbDvLuh0ptUxdWB+ocoWIgWUnyDLJw9Mkw5cCmkyjteT5tqcdHE2Z0g0Pg0uJq6Xgem9567Tmxaqj1pJ+TB36wXrmE8XrjaEpFKEpaIrUkJBC4AJ889kmAb8LSZ2nBDohI04APhXcOuMSILWqeNg7nq5bJtOCItdUWmCOoQEP5xVCCq52I8vOsR4c7ZBsDtNc4X2KQi5zxaLO0CpnfbBc70cmVVLCNbkmF3A6SXuCkzrjb/5ghSetGSeNZtMZQgjc8wW/dDqHmCDqxlgOVWqiPF2m5MEmy7AhMsk1VaYQIgGcR+OZFAkA/no7Yr1FCkGuBPNaM6ZGK6+3yaZwtfeMxtFUBQiYFoLWjBgjUCpibCB6x8m0ZjNYtkNi/k1LwZj8JukgbRWIyMUkpRwNNhC957bVKKE4aOiNI5xMebRIIOxXu56Hp5P0em3X3OyT3UcrKCaKl5uOeZkx+kCWSRZlzq03WPdJIk6Tpc3/ED5ZX+LRPu19+jt62B4lq5GUsrOzX3zd+SJDAPcayckk469/94Z/+J2LXyRW3l8+zuf/KvDbpKfpf/fjHvBVWyM+O34U6+jTFrS7r/9h1vMQ7lR2mkWZMXqPtYFcKcKRgRpC5HJakGvJu2cTlnvDNx7MsD41ab9/fSBTgt94+4z1YaQ1Ww6jw/nARZEOl5nWXK0HHsxLJCkN6mSieXzb8d5lavCuO8eLdYvxSVUrRaQ1CbQfath1I02ZHBujTeliw5isO511XIiC17uOvbUMbaQukm06xMj3Xmy56ZJt9f684sE8KesGHyhzzTcezXh8c0CJyKofcc5ziOB8xBIoJORacjqtiT5wvR2PgP/I1y4bXm67j4sW00oQfMIo1GWGVoJIhlGOaZ1jjlyoITjWO4PS8HA2YVpqDsbRO0ueV2gglwolXPr6GEAJfvliQm8j6+sd+8GCkLyxKNkPhm9f7/EeLuY5Sgi2gyVXkVmZcbPrWNQLvn5/yqv1wO0R0i2B+TQpSWqteHx74O3zmv3geHhSsB8892cNr3aK4QhPJ0ZO68S8q7RiHwV1JulMZN0NKCkoVTrLdIOlyDUP5ynRLTrQWhJixIW0lzAexj4pKwvpqQrNaB3zWpMpTV4odoNDx5TqHEMqwoeYCiL7MdJag5JgbWRapj2Nc47Xq44ml0wKjQmJpbdqDaP/+aqP7kYJBAnRwjampsDd+HRxK/DDKAw4Nr1l+jwpmdbEPEsIjb1NqZ1SHhOk+WKOhztQd7jDE+icQklOJgXWDUQB+86yrQx//NH842TCn7aA/ePGF7Ww/adijP89IcR/njR5/5eA/xD4sQUk4M8AP4gxfggghPg/A/854Fufus8/A/w7Mcan8LHa6Y9kfLZjEEL8uNvvfKAuNL/2cEaZSW62A7eHgXZw1IWm7S3Ge56MPkmrfaTWgrNZydcvG1rjqDLFqjXsBkMm0wfj/rzAhMBbpxO+c7XH+XCczANX25TWddsZ1r3hpC4hRoKQyMFxUqUizzTXrA8GFwKDjcwKQQQykXhHpVa8d9mwHy1nk4yHs5rvX7Vsh6ROUSoVvV5vRzSa/Wg5nRRsWkup0kGpLDS965NXNZcEn2FjWgQASgXbfqQznqbKmGaJlq9lkrc/mFV03jMvNa31/Nn3zlkPIx+9all3BqUlpdIUx039vM7prMe5QNt73r2Y0I+Wj26TrztTEp1LQoBSp7ZfiCnpJhOBXGW0g+P+tOTt85wXy45vvUxSzUWdcbszjDZyfTCUmSQX6TqbKme1H49FDQtOYU2CY9a5ZlIqBIIX6wOZTovsMzMwqxTtkIA8J6UmhHSACVKw7Uz6nYqMosy53o28HC3RW6qioBrdx9Cz01LR1BmvNyM+pgQIf1cIIlLmSWkTibxuLfMiWeWaXKZI5CF1KKZ5ihpvR4cicts7nq97XOg5neQse4PSAqEFxsD11iYulM44qQLPlDz6byVVllhD3nu8kBQyprQNLen6xHFwAc6apILYdIlfUWvNRhi0ShOjiKA0lDrFJu8Hx751VHlq17pj6sOiKdB9inu+3g7sB/Ox71xryc1+TKyikDbr8phGJALUOslcR/OJZS2QJvSc1CmeZGkDH8PP10f90wwNjC7yaF78wsBRgX8yxvg/uLsRY1wLIf4pkvX5x42vzDoxWM/zVceLTU+VK37l4YxpqfmdJyuMdZxPcx4tKrrBE4VgdbBMMsO0kgSj2PSJodO7gPEBYz2r1iCkRBy1yId24HRWobTkYV3xcj2gtKLJM7SCq/3A1c4gRaQpBFGQVJ0StBaUOoGpKy253hl8HFFC0PnAbkhhAYMLlAKyQlNqxWld8N5pybwu+MaDKS92I4EDj5eOTMG+t1jnECLZTkcfudfkRCGOSsDAYfRc70YumoI/97VzLqYlq9aijgERV7uRQOSNecmLraM3ju3gyKVDRIUUgSzT9MfGyW70nCjBB8sDe2OZ5ApNydV+JIQE0M5yBUIxOs+T254Hi4LnywOdcfQ28Ev3Znx02zOYxNZDpE6/calYb3xAS3AhclomGPOffmdBa1KwgHGBRa35/32wZnUwGBe4nJXHjV5S8/zJt0/47ssd17ueOs8osqSOGmzE+ZRaNqtTqpCxns4Ynm46qkyTZ4o35xXPVwNPlz15JokxsuoM285wWpW8uSiZT3JG4/notmXdWXZ9AoLfnxVoJXjBiPeWF1uD3Bm0kojeHnkWJW+fwvN1x+mk5LIp2I6O28PAg3nFo5OC621PnUvqsuRm17FtTbJRLkp6G/jgakcMScVwMJ6zaU07WswxWez+omB5TO8BRVMqXixbQh3Zvtjz3nmNAjZD4GAdInjqvGBaZZSFRAb44CYl6SklmRSK3WB5ujQ4lxoOb2UTKg2ZVlRlxnqwKSTEWdpRYkJIajQnj4dTz8aZJN+PkaxQPFv3nDUFuY2YCN++2vL2ec2zVU+dKzIp2XWGwTi05pgKBMu94XySk00le2NpCkWMkYmGQYJNS1xa11RaixQp/EEDMiR4qXOpoaFJB4wQAZHuV/KJZfrvdwiAGJmWKdxiZy01vxgFpBjjv3L85/9FCPGXgTLGuL37fyHEPx5j/H985mFfmTXis+PHsY4+bUH7aVPY7r639eHjFKXTJuebzzYsj/v/33h7QWc81qdzy8OTikqrtGbcSw3xF5ue06NzYnUwrPcDs4nmH/3GOd+72vODq8Mx8UsfLUORTWv48KbljUXBg0XFOB643g1EBE2ReKYPFyWrzuGjIATP4FLh/DA4vvlkcywueDadYT8EhIB97/je6y0HEyiVxEpPqQRP1j0XTcbj5YDOFFoJCg3rw4irc05qQdc7Nr3lZj9iXUpzlFIwKTIWE51CcBY1ZSbZjxYfBYsm45eaho9uWj64bQkhRcX3LhBF4ic1Ph7XP8OkzHjvbMJ+dIwEDkOkrmRSEZJg4u9lE6KAUgpeL3uaIrGhtoNFIqgKxa4NvHQDSqTEuRRGE/lw2bE59ISY5pHgAvs+qUK0lLx7hN985/WOX8/mFFkkk4qgYD94GiXZ9oYqt3S7nsNoWB4cu6Fk1zsenNT8/vMtpZIEUjry6AN5rtAqFWtSoQyIIu3lI+zHERM8KgouTip+rS5573TKbz++Zden146j2jLENA9GBfM6ozcRZx0ntWZSZjSFZrSBEN0xDTM9d5Y0N+JBHxWdrYFJGRkcfP9qYFLCtEgN56tdn7hy6Ud/El/Pj8dS/KzGQALEh7triJ9cz2eVUZ+9Hfik6SCPv5M/NsI1yQ43fipBTpAklHdsPPmZ73nX0MhUshQKBJkM2OB5fNOyqLMEqCfy+PbAn3xzgZTyD13A/lHjixaQ7lamfwr4P8UYV+KLVbEeAc8+dfs58Gc/c59fBjIhxP8LmAL/Wozx//DZbySE+Oc4cpfeeuutL3jZP3p8tmOwqDNWrcEdJ2p7jFPMlOLPvHPGs3XL33m8Sj5P6xESNp3n0FpMkSSQQcCs0IyexD8IKRmryRVaK0KIfP/qkCruInLWZPSjxZMqhYWW1HnGWZWzGw27LqWwfP2yojORVeeoi6QuuTkk29ejeUrnGm1AVZHWBpb7gfuLinvTknmVChj/wbdes+8tBFBakqvUyV62PVJrSqWYlQFjU/VdxYA7bpBN0MyqHGMtJ7XCusi00FztDA9Okk3gB5sWfKQudEoQU555mfHGaU1dKqaF4umHLYN3SKUx1hIcxOBBCIx1LOqCWZWxHwy/82yDc46ut5w2ZZoEpWTVDigJ8zqnLip2naUzgV1/4DBYnm96FnXGYpKjJSzqjHVvud4M+BhostRZ3Q5JYqpJMMpMZZR5waNFzdNVz4c3OzIlKJ2iNQla+I0HE07qkie3O0bjmReCpiqICAbvmVcZ0yJB73atTfBOEygLRZ2X7EbJ82XL4CLvnk84KTVSK773+oB1IdnvXKTMBBdNwWlTpEPabuS0KphlkjzT9OuRwXq2xwhr4yOHwXJzMBSZRJB4Kq1J/I8YI62xRCk5dC3bdsR5j1I1J3XGMFoup8kj3+SK7ZAiU9sxYo4cJimgLiJlkaBsg0mpd50LTKucGOHpukdIwaHz6bU9dnd9lAgkUkSqQrKocloXWO8Now3c7noOYzqs7a3Dk+6fZ4JV549R16l45NLbhcHG1P2VMJg/2N39tFVgOpG02/BzT2n4aYYgsdO0/oWyJighRBFjHAGEEBUJT/WTxldinbg7CBSZpCl1SjdEUGnF/XmFILAdPMvWJlVeSOqYRaG43UdmtWZRaX7vxY51O7DpUupSbz0+BEbrmR2TnqSAGAPtCFWuaErJrnfc7i0xel5tEpQaoTiMI9vOkmt4sKhY7Xt651nue+6TWGJVpni27DmfKi7nJdtDz7qLTHQgK/Nk8dkbOhu5mKdDxmGwnFRJWWJsx7KzLFvHxaxg6jxlriiFwCEwJtCNARFTOuZiknO7N+xHy7P1wC/fayi05OnywIvtSJODC4KzWrMbYZJJbPQ8mJaY4MnyZFNNz3vg+arDBrg/Lbg3K0F4hiHyxklJnUu6wWOc47zJsAFWvePQJ6jnOxcN296w7xzvXEx4KmDXeYoskmuFj4LLWc57FylB9dl6ZLSGF0fL3bK1LLc9BxM4n2juz2tiCETg/cspJ5OM3xos+87gI8yKnHVrOKkjhVKsB0cuJdveUmlBeVT/SiHoR0drHWqUKBF5vXFc7XuIgjJTTErJk1XHmQ187WLKmzHQmYiWAS0Fq3Zk11s2XSqiL+qcstAEb9Fa8fXLCTbA7W5g0zuUdmx7y7TSuAAPFiVCKOpc8dZlw80u8RCXrSOTkdEGRhdoxxS1vW8tq95yWsC81EgpmJYZX7/f8NuP15SFphsdT1dtCo9oCjad5fHykAqgmaCICq0UIQTuLwpmRYYNgd95tmHXp7hwSeT5ZqBQkRihyDU3m5HzWc66S4W83jqMdzSFQsaAOVoW78+TPbwYLL0BH3wq1MTAfgh433FSF5xNSw6D5a/83itEDBRFxuPrPc+3I+NdGINIm3vjwcf0HrdesNxbTExFKGOPBx+X1sH8+NAiTwcKJcHZZKGWEqoCpE0hDhLoj36GgXT7x7GOPtu5/pFzFbBsI0XWURf6F8bm/NlxXCs+6zT/C8BnC0hf2hoBX+554rOsIykF5pgqVkj1sQXti467otEdi/V6Nya4cUzW1MPoKDJFFlPy2HmTQhZWreFmP/6QAir69G4rc829WcWzZccPrvbMm5yTOufBrMI+jFzvB1atocol755POWly6k3P9cGw+XDJoU9cuNGlRKdnyxalpiyqLEHpjWdSauZ1zrY11JnGucQY/eBmz8WkIM8UPnqeLUeCEMzqjFwJ1p3hMFoyIIiAQKEijDamNCtj2YrIdrB01tEaTzsYcq1ZlDpZeyVUOqVDSqG5mBXMy4zBJmh+VUDRKaaTkkqlNWG0jqbKeKPKeL0bsM59HANvjoEC7ThgbCAQiSIF8eyNpcoy6jyjd5HzWjORil1vuG1HdkOyHe8PhtFBVWiE9yitOHSWuhAoUhHmtk3BQUgQjPzmhzecTQuMi5QKiiLjrMl4sbEEAvtupC4lN7sRBMjW0o2Obz4dWPeW3/poSWssVaFRCJSUHAaTCnbSs+nSWuVFCptAgIwSIQPnk+NaawLD6JnXGSfTivsm8HJtU1BA/MSK1eSCOsu4P9Pc7kaUAh8iJ8eQDSkiznUcxvgH5rS7/bkNad40R8mNFLDtPWXmGYZUVAn8sP3r04//WQxJYhwR/+DE9OlzxR33SAC5SKy79kdcWPzUY+8g2SamdaNQqdmQ80kSdcLggHRHnl6E3EMfP162KHRae+7NS04nObkS7EaPt47eRLaDpywymiKJDd5YVGj95Tajv2gB6f8mhPgOycL2LwghLvhizZTPmzU/u9Jp4E8B/0mgAv6mEOJvxRi/90MPivFfB/51gD/9p//039dq+dmOgbGe336ypsrT4duFyGmd8c5ighKC55sU2b6oU1zmujN4l0jqp9OcTAqEkMxKxXevDrzrU2rXzb7n5jAek04KqjOFcQGlJQcT2LaWutCc1DnOBQTJmxgFfO2sYQgR7z3fu+55tCjZdCMxxDSJDoaqyHEk1oMncrUbKTLNfJJzNslYt5ZSStYHy688nPG3P1pjvEMiuGxKtIIy01xOcw7WsahzlruBOhe83IxH65LicpIsDHshCERkDDxbdow+cH9RIWUkE5J5nZbJx/uRsHGcT0smuaIpUsT7pktx1dF7rIvUecQEqLMEE3/7csKLdc+qdQwmeXo3Y+RkKj7uJlsfuZjXLCY56/3AqjPUefpQnEyyYyVf0FrHbTty21msCxRHFcy8ybAOlMjZjwPLPj3+/iRJPF0QXM4K1m2BkPDGrOLVIXUsRwdVljb+5dG3fdGUeCEIJMUIAjqXEstOy5xRBw7O07t0eHz3QibFWT/SDiO51hhHksWOjmmdbBEPpiWr3hFiYG8DtUoR875PfuhcQfCKzTBSKsWbJ8UR6ucShFtIvHMsmpzrg8GZQFVJ+hDwo2FW5dxrCm52I4PxnExKNp2hNwERI4WGbkgTW1lIXIh0Y4odDToQSQfJ86agziSr3lJmCUTYdpayTI/1EdaHHoGmKXIKHVGZJD92JjIfKbQil6koe+gMLpMQoakyKgn5tPjYyuBikoJ6B07AVEoKGRg/Z1d+PFOw7QN5st2jwycdhLtJ5Itu2v8oR6nBumTz+Y++c/6LAtH+t4G/JoT435Oe3v8G8G99gcd9JdaJT9uXz5uC6/3Ay01PoSVvnzb8zvMNq4NBKkGTSVYHSy4llVY0VY6WkvkiZ3F74NkqkEnJ1jrEMclkWmpMiBQK2tFxtR3pjOOtsylSCG4OqUh0tXNYAdd7wxuLijyTnFQJ2P942XOz7zFHRcRkMFS5wrpUaI1Bpoh1FJMycN7kiZ3UDpxUOeYY/ayQDM6x7wJReF5uDe2QPier/YB1OQufUTQ52z7xCs6mmndOG5at4Xefbri3qOjHlG5TZhlvntTsRsv6MBDIKLWgLBVSWOaTnEPveLAosd7TFIpnG0Mm4GZnaI1DK4EPgVIJmkIyLVN88rKzdDatj/M6Y9tbVvuR1jg2ned62zOvS6QK/O7LLTetBSk5mxXMMgVS0pQ5IcD11jCrNL1JatbtwVDkipf7kULBsovYCHWuuT8rKbTi2y93LNtUPFodk22KXKFEAnNfTAsWVc7NYWDZWkolee+i4WZvmRUaqSWLSvPhTZtYOQL2xiGkpsyTEjaTAq1CYmQVgqttUlYikv1tdAEXBF4k9mCm0h9nA0gotOSt8wmb3tINjmWX2HyD9djgeLIauLfI2R4MuilYtgatUiLSuhsplObhouJkmoEPDM5z0qRGzO3B8ltP1zzfDGgRj1bJSKEEt7uRPNNEkVgfo4vkKilmm1yhhWS0nqe3B3ZdAnFnOsF8lYqcTXJ0lqGAZ+uew+ipjrZEKdSxuZPUuDoPLOrEQLQ+JFuIVIzWU2TQu6Q4HSyMPvBq0+J8ZNcZJkXGfjMkboc8Sv8DEI4HBgmDdXSDpso1QYHt06qQH9nluUrWDa0k7RjS500JgotU1ZG9RzqAOff5lrWfBMr+adahAESpOJuklKfL6Zd/QPg5jc9bD760NQK+3PPEp1lHLiS2pnGJ8fXgp0g9CiHSGseLVcfVduDlbiB4n9YWJdl2I693A/Myo8w13is+uk2666SkzD9mLd0poO6ubd8Zvvtyx7N1T1PnvHM24Woz8MJ4fuOdE5atYXUYU4BArth1llfbAReTImS5T+ojQeQwBl7tktI1zxS/dNGgjsr5EDwOyDLJs9sOY2NSkPtA21maIqMqFRJBNzpW1nNS5rx/3uC8Z28Fo41UlWZ1GNFa4YNidRh5vRtBCKyLSKGoMomUCYHQDZbFQjErNb31GKvYY3m56dkbz/YwgJDMas07l1OmZcbzbY8Qkn1vcS5S6gytBVf7AREFeZF4sO1geTSv6ZxjsJH9wfJrX5uhtSQjorXk4azke682KX0zCKQkuVVyiQieSaVZt4YgI62N5FlSIG0HqDQfv5OXnaepA3WWYX0kGE9TZNS5ZtN7DoNhDDqpRXPJ6vaAi+ks6mKgGxJrdr2ylFnaI4QAJQ4rkvLoYAOLSpLrHERMhUMhUBqKPGOwhtf7nj54JJFpmXE2LVn3luwYFOECCCVYtQOHMXHuHk0SBzDXgse3Pd1oaG1EHRWYn7ahRZIi05NSKyOpCENMzoWb9pP7aP5oo3wFIGOaiyvS35+dyyOfFEAk6ZxzVitU7xndJ9Dvu/vejTu2kT4+/g6aHfwnhSEtUsEIkVKp81wlXp+K+PETJRbHhrqMqclZZJr7c82L7UBnE/ZjWipGG9HHusKXPb4oRPu/L4T4C8AuxuiFEB1JPgr8SMkppC7Bm5+6/Qbw8nPucxtjbIFWCPHXSYylPzDpf1njsx2DKOD2MPLopKQdU/zuq03P5bxkkmmMS+2qm/1IazzPNwOKxKGoc8Xg4a3TjNuDTcksrWWSKZ6uOhal4qRJaTF/7+mat04mTPLI/XnBhzd7JqUGIXjvomHXOwKRJs+4d1LRW8+z2zYlN/jAqk1JPJjUfHEAAQAASURBVJshVexLZXh0UrM0los643ye8+BkQmcDf+ujFZfTkuV+YDuOvHfRYJ3n9X5k1yd2zEld8mffP+W9y4YY4LzO+HDZ8q3nKc3r1hsqKXi5s0g50veeps7ItWT0gSgiz5YH9oPHOU9VKd4+qbk/K9n2Bi0k17uBVxHuzQveu2y4aHK++WpH2Q4MQfC104JJlexnf+ejDXUmaQfP6FLXflplLA8dmdKcTErqXHM2TfGZMST5a5PnTCuFkorOeAotePy6ZdMa5lVOIHK9H2lHz8W0QErJo0aRCygzQZ0pusGS1ZLWWO7NCrJM4lzgqh2IPm2aD8bwamPIlaTKNTfbkWW/Z1oIMqnYdoZ1e0w+QvA0DBxGy+AD3gfePGu4PaT30PowMisU57OMkyZjdRiRRJxLNpX5JGc2yVBC82AKjpjk98NIrqEznll5BDPmGbvRMZvklE6ihOT20LFzkA0pq3RWaapcJWuUT4vezngGO3IyyZEeBqsYTeRimnPTGcwxczjPInmmOG8yRudY95EQAp0ZqHJLpZIKQh9jqaUS+BGQqWgjgEmeUxeS7RAZTYL6lVmqohvnaQ1MC/AidSUyJRNzqfdkMkWeChx1LmgKTT9aWgsHFxiPM/RnZa13lX7nk40tZilF56j2/nhRuNvefZWKSMan1/w3P1rxn/31Nyi+xOjNn9WIMf5FIcQ3gT9Peur/lRjjX/0CD/1KrBOfPgiUmeK0zlBScG+W85sfrZnkitsYyWLk+XpASsl+cIw2sOxbtt1Ak2uebwZyBWd1QdkniH0qgKRC86IuOZtk/NK9GatDz/k0S5wM7xgM7LtjO04IPND1FqEFSnqsc+QSZJ46V4fB4n1SLQYkeS6T/acd6A1kQiZ1Z5nxaFHiPdzsDaN19C6yt45dN+BDTPyeQtANiVV3sSjJpeLZsmVaF+z6yKvdyKTQbDtHU3qKXFJq2PSJh7M5OEYvEM4hjzbhr9+f83LXE4Db1nCvKXBRMCkkL7YdSiUly3iMAZ7VGW+cVbxYGw7jkBI0lcIHz3deH5gUCillYsAZw81BsTtGpH/j3hRjPWuRtOYmRvb7kabQKAmbwbIb0jwyyVLAwfNtn6xoeU6Tw4tNz0n1SXf86brjMFraMdCUgm1v+PWLU2Zluo5tbzGZp1KS05OaN8/q1DF9tUMQGI4BBb31jM6mQqGC271n2xsWdcaDeeIN3exHygy2Q9q8DzbZ74SEWklGY+mNoiOyKCWzaU4/Bu6daKyL7FvLJM9w3lFkGe3oWdQ5VS5Zd4aLaZK2v1y1HGwgBkceJIe+52KWQch543TCvM5RAl5tRhaVYj8KzmudooZNUtblhUbKxMjIoiDKwLyQ7EbPvWmBlAot4seHuEzJxMYbj3bxmF6fQgpChCpTLJqceaY5aXJciCz3HcYJrPNEIdkPI4hIpiIPZiUvNz1KpTVDi2RXHD0IERFHZYQNEAmYYwhDdvQEHNIlkMmkJvJR0FmHF5FSRZSM1Eqi85S+61xinfjj60FMYNI2OEqlKDKJDZ6h/eEDx09SHf1hhwTemCfo7mG0mBDQ/ANRQPq8gs5XYo34vCFlUvy83PS8WPdkSvDWWY2W4iemHt1hNKwLvNr2fHSbrGK5VsfQgZ53LyreOZ9ic40UksUkpYWVuSKY1Khb7Q2nTRL7fjrtLVOSy2nB33m8Ym8teaZ4OC/ZDwmq342eq13F/XnBos7547ni917uAMm01GwHx27wFHmGd45X657OeqwFVYpjs9Yz0wotYNcb2sGya0e+f7VnWmnGlISCC4HeBg7WczktkmJRJHv0W/MJu95y2kie3R4gBqpCczrNcdbzvZueVWepcokPgdZYtJRo4YlIRuN4sRoxNvLW+ZS3zyd88PrAYDy5SHviZWdQMs0lh8HRG8vgUmL2HRbBxUCTK6pM0xTp7PZyM3B/WvJ80zEtI9vOsOxG7mWaB/Mc4+CD6z2d8czrlHaa2LPpdb1tPZdRkCnFxSTZ3INPxTYFzDPoPJgxqVKs8ZR1wWgDl5OCXIKNkUWpOKsn7LuBV51liiLTGZX0XO8stQaXCdyQ5hsbIBznOInnZKZpipJIYFLkiODpXUpG00rxcjWyLz1FplgdBvZDsrefNxX7ISV57qMlRxBsRMXItrco4fnlBw0Syabz7Ed/PMdJiuO21Rg+xnbczYUROK8TTmV75NwO9pPmriRZuP6o9+WeVLC6s939uJ8vSEBtSOqrIhdEERE2FcRs/IS/+kON64/ZlDD4T3hGpUpr0eCS06LINBeNZt06zpqMJ8ue0YI9OjyKLIVHzcqMziYW7SRL4RIhBHwQPFzkH6fIf9njiyqQiDGuP/XvFmg/9d+fJzkF+E3gl4QQ7wIvSElu/8xn7vPvAv8rIYQmFej+LPA/+6LX9YcZSggECbJYaIV3AQFsWkuVa3xIMbm/+XjFJNOMLrAfUjRuLiVvLCqe3R54tCi5mFWs24Hrg+XBLKXpbDrL9693ZEoym1RMK8WmTckiWQaPly2r1rBqR3IlmWaSKldMCs3b5zWH3qeKfZ+ieqWIxJhiLctCMicnxsBok1Lq0aI6phOk3+v2YHDWcbsfaErN45uW988bFk2JDQKtHQ9mBUWmUFHw5Lqj0IoYQElFFElyG0mTgY2RR3VJm1kIgmmuMWXg5jDwYugJBIiCIUaia3l0PuHXHs3wHpat4eWm58mq5RsXU+ZNzvmk4KzMUCpBlCOCrz+ccbMdeLEZOBjLrMx4sjJse4cQ8OZCkalIQPCD13ternuUlAwusBgsC1PwKw/nCFIizEQrDjLJ0jftSJYpikygheCmHbg5BIxNrBJI4GnvA9vR0fWG5W44JsllnNQ5Wnu8i4zW4UJypF4uSm73A0JodqNLE2zv6IxjWikOxjItNbkN9Cbw5PbAaD13tYA7aaYSRxlkoZER5pXGukBV5ExLSYhJpnu9Sza81gTyLIFL931igdyfZviQ0g8KFbBHaX1nLT4EpEjJgUVWMPikjni+6TDGUShJXWi0dNz0A8uuox9SAoUDchup8pjA4UGyKFMLd3kY2HaOdYgpnUakTvhdEafKEqg2RFh2hsFrFOFoGVVEoXHesW8D/ihllTHgRAIrhhDJFczLkmkheeY9SMFgItshqYsyBdMcKp860Hc/W/HJpD2YVKiKMf2xHIF4/Oiktjvf9U+78f+yYH9KgCSB1zvjmE++iBPs5zuEEBPg/x5j/CtCiK8DXxdCZDHGn8SP/UqsE3cHgTvoaTc6CgnP1gP70bLpLMPoGEUqoFaZYlrnbAfLzX5gJQWTKuN63xNRKGmxRzvztC6YlTqlq/nIo9OaSSk5mS7YHFJE+661hKNVp1CCIASbbqTMFRezghfrnkOfIpOVjtRFxrK1jM5yLjPOJpr13jIpI7VWVEVGnScuWp4pLuqMD246okxMuUWdsz02Pao8AWGMF0d7nqTRmifrjtFH2u1wtPg4fv1R4gJWWeTrDxecVhnfe73ng9sDg7NURY71Hu8cxRHCmWvF5VRTlzo1B1xkUeV0Y2B0I7UWzIqcV/sBfEhNjuiRMWJCpClzqizF27eDpykEzkZe9560Z0+A6SfrDkHabBsfUTYVEwJwsx2wNjA6jxY59xcly36k1gpRSDatY9MaCi1493xCbwK73rI6jIiYbIchpMJVCNCaFGgQI5zPCg6953xW0BvPi1XPujXMc8W7Zw1/98ktz7cD7eC5v6jZdiMQ2O4cl5Oc17uBfnSs2qTSageXJOpK8mYzYdkbnHdsB3+0XhQoCbc7w+NVS6klhRbkuWCS5QhSIMLokup5XmZcH0acSs0yrSQToZgUktFFooF154kkUO9JkyTxRSZ5tTW82o301rCoCgoN92cVg/cI0nvtz33tjBDh1W5k83zD03XPxaTk199cIIVGqRbnB86bnP3oiC4glWDXWYwFGyL3pgWVUtgQ+GjVpfnXRXa9xRGZVxmzKq1zuVQ0leLleqAqJL0J5LlkGAOntUj7Oh+wLq0/my6tMT6k7nJRwCSkglKRQX08IPfWUajI1kE3BqQA4dPaFEnNjtFyrDxFdHTpcOw9RM9V+8mB4+6w9LMoHkHavL/aWx7M7VHF+w9E8ehHja/EGvGjRpkpHi1SyM60/CT4YjCWwSVHwmeLSHcYDRfuFP2ej27aI7MoZ5or9qPjyXJAC01TJhh+mamk/lGRWZ3x9lnDi82AsZ4y138g7U0Ai1oTqTA2nVrXraEpktpucJYnK8/XLhp65/HB0w+Jy3PZFEghiARu9/BqN6RUOSmooqId09723csM5yKb3lPlkhe3PYPzDHtPodMaBBKVCVSUNGWGC555ljHPklLxtMy5OgyczwqEkJSZ5GozUBwVjdMqwx6t1aO/s7imFN8YBTJGNoNn2huW+57bdqC3ASHu7H+CTWuptaI1jkmRM6sF1ni2g6fWkSrLECowLXOqUlFnmhBhXmYcxgwXIpnSXO0so+2IsabOU1FoUedkOhWzkmILtM5oosMEz6JMad0+pjRilymiMqyOUGovUtGhNZ51a6hyzXkMPL5t6ZxHicRiWvZpDZuKnFxFDiNkWiKEOJ7aPMUxOdWJZJWzAg424txAkWVk2vHWvMbL9Pw9vm3pRk83gpKBzaARWISQDD69i2alorMeFUHLiA0RZxw+wkfXbUJZyMAwBMYQ2HQjUgpyGcllCh+AT+xopYYsz5A+UOpUzBLH/y/E8fr9z6+x60n8hR/38zV8bHvctIFMQVUKTsrIukvfpDoiOO7OU3Bk4939m2SZCzGtR00uefd8wvrQk+eSeZkzOFj3Mam0XSSvU0CRyhTGeQ7GcbVN+9TOBO7NcqaF5nyqebiY8MbiRxex/37GFy4g/YTxuVcWY3RCiP828FdJ57l/M8b4+0KIf/74/38pxvhtIcRfAb5Jei7/jRjj731J1/W5w/iAcYHrfTo6nk9z3r9s+Oi2xUfL9W7gtM7ojeekzIhCYLvk1Z9WmoeLgkynosPFtExUdSG4mBYcRsv3X+2TV1QIqkzwejOy7EacC/zgumN5GHAu8MsPZjy57bDeM6s0/9D75zxa1Jhp4K/+7msIkSg1p5Xm+aaj7Q2zSXEEZAlWveHRyQQIvNoOlHniB9zsR5b7gV95MOOsqXj7LPL9qx1SJ/D0e+cTrnc9wSc11a88aJAycZFcEIQYeLZuWfcjMQomecbgPE2esxssy8EQBdybVdzuW/YjnFSaIj++nY5V9CebnuDjx4lBr7YDvfdoIXj/fsO6daw7gyRtCO8tanqT0mqutkOysR2Fsx/c7tn0lgfHTs/NYUSKgJCS0UiWXWJi1GVOPzq8EPgAq0OKAlYqYkzgw+s9xkPvU0c0k4LDYLk+jFS55LwuGH3gbFqiiGwGx6413FtUnNSaw2CxPtJbxyRL3dYq19w/qSh1SjLqBosPIiXPRMG0TIXB33myJoRIU+UAOBfZj5ayUOSZIjta4Q6jIxK4FILl3mGOwEAbI7NMcxNHoofV6CkywWH07Hp5LHgphjGl25V54huNDq4PI61RFEfYts4UhZI0TcGr/cipS9HgEFjtE7srU+m13DuojOe98wm9iSgtMS4i4khrAxOdKu0JdCdpCoXzKf3CBjirNVWhmFUZ3RCYFnC1N0gJhy6ws2lilQbmlcC49Fkrs8TTuj4M3OwjWmWM1pLpFOV6h7HQmSSIlMAxfiq+wPFJEekwJNltJElGpYBaQfcjVodI2oHC5xeYftSQfDn+7DrVotGSXySI9l8H/uPH9LX/APg7wH8F+K/+uAd9ldaJO+jphzd7/t8/uOXxTcsPrraMIXK7GShyQTv6FCGP5b082Tu1EggEg0kdUec9g02F1igEpYTgI9VEcRgdQgh2vWcS4WBsOtRrQW8idSbItOayyVn3jkWheLbqCSFQ5DqB8oXgZm9xLm0+gxAchnDcaCusCUSR0lcyrTipc65ax9XesDwY3rqY0OQZp/OKICKr/YCQkuIIOB582hg+vW2RAjKdOsmvtj1llhSSt09HXu8M07Lgcp7zcqvJMkWjFIOP3O573j6rKFS6jiLTLCaKl2vPaCKnk5SKaR3oWmFjgCCYTAtKrVHSEaTHWA+Z57wp0BKWYuDVoefluse6FM0sRGDTeR6dVGRSMPrE1ysyweAlh8ERheB0mvGdF8nqXXm4mOQ8GwdUjJxPS/bDwL1pxb2m4MW2ZzMmOHdnQrKjKcH9ecF2HJmGDKUSS+L3n2+YFjn35iVP1gOCyDtnEz5cHvjtbz6H4NFSsR8NchuYTXIUiuu94cmqxfhk/yqUwIdIOCZgnk1yvEw8IpDM84BQgiaXqciTKS6mORJJb9LmMROON09rbvYjhUppn1nKXqbKNMkNW/F626MlrAeLkJEqU5Q6KaperjsezgterDs2hyH5s0Jg1w6YACdNzmVTAgKt0xo0n+TUWVrHD4NhXmccRptscaJiNySgrgQsER8E6mj3qKRgP6TnegiBYTC4IDmdalyMTMvELXlrUfB8M2JCQLjkP+uG1DAZTIK9lpmk0hqZw/Jg6UwCmH7c1Q4gHCnQxAZyLXARHiwmvN4NRCFwo0XE1Hy4azo02SdriA8QXbJfzErYj6mh8fdz2PlprdQ90A2WR2cNv/H26T8o9jWAx5/9wldpjfhRI1OSXKdUNEnaV77apTQkfQTY3tnZPo3RUFKy7ka2vaPKJIVStKPF+cgslxjneb3vKHrNSa1RIiEPLqcF719MybTkclYkC+lRZXPeFMnm2Vp+9/mGl9sBLeFimvNk2bFuDe9fNjxa1GgleL3r+XtP1oxHldBbpxUmBl6uEtcy4Qgi80qx7Y/sNO95MKs4a3I2reUbD2dczhJs//Gyp1KavbHMS1Kk/Sw1UZadZd2aBLAuFM9WHXk7HIsziddWZIpnq5ar7UipYTsEChWZlBllLplkKW1uMI7Hy5Yq04w+FYs+ukmOiHaw7EZPk2uMj0yLxGudVxmZgkmR+KhvXTZ888WG1jhqIck1DMGTh8Qc/fr9Gd9+sWZnArNc8s5Zxc1hxLpUYF7uh5QynCtCFLzuDSJE7k9LeufJM0VnA/k0w0fJ2+clnYF9PzA4wZ5ImSXlZC5FKo4Zz+A8m4MmCuhGR62ht5IoLCFERmNRuabUgVlRMaskzzcj+95S5YJMS3oXmOiIyhS7zhMEzCeSTGoGF3m8apnXGaMLNHUOkZRiOViEFOQy8OzW8MZJzaTIOQuRQ+fYe+jMJ41WGIkiMpjEekREBp8aAOHI8RHAtJJoBe2YFKH4gA8prS07Ii8cJHWOT1wh/fc5r/79jFyl1+VHjU93RhWp2eBsxB4b1p6E27jrOcDnN5ljPDohIjgEq86w6hy6h23nWZQ5jxYFqxaemwEVQWlFpTV5ntbsWZV9/B4abORP/eop59OCP/P2KXXxZZV6fnh8Wd/1RzbdY4z/HvDvfeZrf+kzt/9VUqTnz3zcTdxNqZnVGcZ6fISLScF3Xu94uuy52RvuL0pyLXl0UqEQPJxXKCF446QCUgX/fFpyf1ZifeA3P7xFishh8NgQaIqMR4uCp+ueQgm2reHr92fYCEoUfHTT0o6WQgsendSEIHi67Nj1yRKx7g0P5iWVELxY9QgE0zqjHywbn5QwUqToekHE+MjzF7sUeWwih9HxeN2zGRzb1hJC4M1ZzUYmCPisyOms4/dfbBmt5d2LKa82Hd0YGEbHJFNUef1x6lyda3IlebJpMaOlLnIEkV1nUTJBwk+rDE+gzASbzrHrHFImrsUQBLlKHdFJXfDopOYbDzK++2rHy01iR5xPM56ueyoNuRJ4Hxmc4/68xsTArjc0hWCwnhDD0W7oEREuZjnrQbIeO86rIkHFBHz/ukXEQKk0QguuDmPiF6mUkCdFSjyLIXUoQ4zsB4fCkueKWa5YjylRyPmIkpJnmwO9CSwPhkWtP45CLfJU2LvtLJkStC6w73v2Y4ZUgkWlUfJY6ClyVjaVJjIhee/hFCE5bt6TTLHKJLshMkRSRHauaJ1nUeUMxjCOljKXzMqch4uadTdw2pQs9+kwqoXABEUp0vMpSRyocpIjRLLESZG6p89XBq0lrQ/JvxtgolKRZQhHDkUmuVl1Rw6RoLNp4tdK4kLAhdQ5WDQ5QgqCD7TW05QZo4uIqLhsFNvRIhBsWvNJYpo6FnuEIIbI9XZEa8AnUHapQWcRF2R6PbWgzCTlUdEx2kCh0jWLmBaiu6JWrVIRKJIKRyIm+acLP747fFc4+nGJD5Ifht/9NMWmHzd2A9yP8OtvnzApfjHSdQARY+yEEP8s8L88Wtr+7hd54FdpnTDG89e+c5Uiy3NJEJLVvqN3gXWfNkPTIs0hV7uOGAWHPhFzz5uKk0mSHNfHpMR5VVFmGfNCYl3kbJKl4ngO33rZsu4GnINSa4iCKlecVBlVkVEVhm5IG+PWODKZklOMSZ3k40OIRw6CDYHrzYgncDop0bliruDZquWts4qLWXG00A6c3supAlxOS8ZjbKJ1nst5hUDQm1R4aArFSZXzcpO4d4sqZ3UwOB/JZKQbPMv9gAmBznmcBESytJ7WBfNac/vcsHcjp5OGEFKRa1Jm/OqjBU+XLYFA2zseLSreOK0ZQ6R2mvM6Z9NbbluLkimtsy5z3tKK5day7Q1Pbvfpd1UxHcJygNTQybNkEX+x6ZiVGd5LZpUi14LzqUZSsu08o3P0JnV5q0zyYtPzej/inU8KJu/pjeD9e1OaXPLNFxtAUheKP/nmgsOYYot/cLXl6bqnVJLzacG2tdzsBs4nqfhVaMnBpLSeMSRJZG8DuZJYbxmsYDYYZnlODIFCCU5rxXoXONhAnWd87V7Dy83AundMXaQfPVUhebSomNUlxjvOJiVns4IYIh/edtRCcDmrGK3j8W2HkpFd79gNjhBSYQkig3EJwO0DL9YjT5ct+z4BXL2HKpfMyoJfuTdj2SUbyb15weW85NW6J8SAkjC4dAj68KblN94+odRJMXu177jZwWAEnROUKtlHRutZ70fePKtxLtBUiTepZVJ0d8ZRFzlP14G9ceRCcr1zmHGkN0e4dZbijFNxdmTTOjr3yeY0AJWCN080MSpOp4nvJIFGC6pcp+chBFokJoZkOxBJtSRE6hBrlW5LlaCpJglj/8Aa8dMqjxw/nDKk+PFxzpVIaIB/8o/d+9i+9IswhBA18C8Cb8UY/5tCiF8Cvh5j/MsAMcZ/+vMe91VaIz5vfFrBOphUPHo4L5mU2Q9xiaQUP4TRMM4nuy+pKbvqLMu9Q+D5lYdz1p3h3rxk01neO59Q5Blvn05YtsfkSR+5NytZt4beea73A49vO1wIfOvFhjyTZEc25yxX/NLFhEenJeOYDu/Xh5Hf+mgNCO4vSk7qjMe3LblSnE9LjIv01lIXCucjVQ7tMDBYj1aShycVMUQmuWYwhuvDyCxX6HlGPaYC2EQLikzhQuS90wqtFZUWfO92z2VTJHWGsbzYDLx1WtK5wMtVR2sDIZdMcs26HQgxqdovpiVaaUbvOIwghE8uDaMIwFmTc9GUvNxuuNr15EpyUmmWvce8XKOV5nziCVJx2xoGm2LqGxExjpS4WuWI6Hm9HhJWpElNooNxtGNSgj5ettS55l6hWcwn/OB6fywkJ1V+RKJk5KTMuT8taY3D+8TSizFBwvMMqixjUkZ6F4kuUBWSPEtNFyUlr9Y9q70lCplYTpUiRtiNlhAEf+bNkm+8fcLVuud3nm7pjU0JpMbx5tkErQVPbjq8D0gETanoQ7KrIVLxe9NZiiIpqPaDY17nFFlGb5Ofqs4VUiZFtQ8pYTn4pJzZDnA5E+hc0o6OdoQ6gyITjCo1fOelYHTQh0D0aS49GI/3CZatOCIn7j7LpL21JDV9BV8s3v7LHHf2sh83l9/BtO+4SIOBzHwyl3vS2UAAhUzrx8b+cNHEAFOV1pLbrUfiP7bRycHTmZ5NP3I+zSlyQaU1ISaRRDt6jIO3zypO8oz7ixIRIxeTnEcnNUX+s8Nf/GzKUl/h8Vn+UZlr9oNl1Rnuzwq60WFdxFiPFvB7zzacTUtOjwlbg02b9AeLinmV83zdc7UbUFJgPBgXWQ+WiOBiVqJj2jQ+nJcs25F1Z1NCixT8/vMto/e82moWVc43Hs0RQnAYDNfbkVofI85T848Hs4pnq479aKiLjNNK83TVUuWKeaVwwbHu0iawt57vvrI8OqmICE4KxbofiC7yqk/X0BSaOpeYEPnu6z2bzvBk1VEKkFrzcFHy7nnDZnBkGrrBUSuJF4pSSa73BhfAek9vDcsOvnF/ym+8fYoLAflUcBgco/N0g2WnIo1XbLu0YP3GWwuqQuGcx4XAcudxIbIb/bFIlHBhnsCuc1RasGoNdSZZd4LiqKgKAVrrUvejdeyl5bYzFIpkZ5jkIAXbzjIYT12UdCbFjRJCkuMrgT122K0LuBC4VCU3o6fKNLfdSC4EzkemRc55o9h0Bh8ku97wYFGx683RFilT1V1CJ0GLyLPbFikFWSYZTToMKhF4MC9597LBOE9wgpM6dd/70Sd1koJ1F8izZCpctYZdb3A24IRAOEGmBXvj2HSOKrfsektvDZnKcT5lmjVFgVQBJTIGC1kWEVIwrzW98SwHQ55FKqWYas/BJdn+nXR/8Am4qoRgMBa0xLnUmG5NQKkUazmtCoSPXDY51gVOIuyPqjLrWt6/nHFSCWwIbNrk0y6PUh8hgCPAe90dE24UuAFaAYvMkRcKpRSFFGihUUowupFZlaGlRCrLvgsfg+qkTJJSYSPxCEF14XjgjuDND3cHPj3uFo4fpyiSkOJN4+dDU/+wI3W5A3/s4fwXgn90HEII8edIiqN/9vi1X7g15uAcgw00uaY1jlmueBXSFiJwTMWw6T32fGVZVAobBdZEnm16plqQK0E7WO7PKspc8no/cr1xVGXGNObsh54ql8Qo0ufZJeuqlAKiZ1bVVLnEOcV+tOx7n2J8C8lprclUslFtB4sJsOkMg0mF2EF5cqk4aM/9GPn+bZ+KIxvByaTgZKLZdZ7lbmRSK5QXnDUlkzwDmWzFmYQyl7z7/+fuz2J1S9M8P+j3Tmv4hj2eIeYci6rqbnc3HsDYAiMQXFhqEC2hFkIIbCEhM9hcAIILyzcIYcQNAmEQYrgAIYxskAyyRau7wVfQ1d3VNWZlZUZkRJw40x6/aU3vyMWzvnNOTpGRlRmVGf1KESf2jn32Xvv71nqH5/n/f/+HS/ZToqoMzmlQiu0YGXxm9JGbzlMZ6IbE49OaGAuqSqhSWFSa7111nK7EahdLwdkBHzOrxpJK4bytOX/f8cGDBZ9e9WzHyLIx+MMEObNe1XzwcMG6qkglc7UXe/Oyqfnuiz1nSdSe971I/v9D31igkVjoBNx3I23lUEiE9ouNZ1lrSsr0U6EPid2swIGCVfAHz/aokqidJRWYYqappPN9uTD8wbMN58sKpWQj97uf3HG+rFlUFqsUm4PMKMcD3RQTm37ipoDRhW4sOJ0IUZQ845QoFtpKANb7MfHwxLJ2VhLXIrx92fJyO2KV4q4LrKziqvNs9iNFa1aNFM2v9yO//daad84XTCHx5K7DoJhiwllNPyVUUeyHSEHR+8jjdUNTaUKSdS/kQirgdCGVLPygCItKURnNsrW82PacLGsuFjW/+ViS6n7343tap4mx8M5Zy91hYlk3XO8nvv1wRR8i1/uBccqghdNSUiEjyVJdSOyGgDaGEAVCi7I0TjNOI/ves6sAZVjUhu0Qha9ylP9HiLZwvjQ0RrHzUaClRZgRrYbWwaKp2XQTzzYjrRW7XoiJYQqsnOblPrCfpGCmEBVoKrCbTy/1zPbLXjb4c7jt53bJK+Zu9M+Ye/QbX/ezvrap4OvnK/7uDza8e7Zi1X5lGg3/e+DvA/+R+ePPgP8r8P/4lV3RL2kcFaxjTBQFy0bekze5RGRepebFlLFGc7503OxHcsl848FSWJ1K8e5Fw3sXCyqjsWZk1VRMKbNsHEpLkdwZzYvdKEy4kOinhNawHz0fXXesasNmCGgFIWX+xoMlK1PxDz+54mo/0TqN1Zq20hyGgFaFu8PE22cLvvVwhbOaj68PfOfFHmUUtihWtRSEf+OhXNtq4ThrHU/ueq53YpHNk+Zy7bg9jFwuGlFbGcVtHzE68f5Fgy6Km4PsnPopcnPoiDG8Ype6mRaccmbZWt4/a7jaDxzGgGnFpreoZpYUkIJgQq42knT5YFWRd5GQoqh3SuZ+KJw18P1rz0nreO+s5fHZAoekQTYaPrwbue89YyrcdxOXq5rTpuKT+56b/UTtFO+eLrFGGs99LLzfWr55uWDTTbxz1rLpPb2fSFnxrQeSMJ0KHEbP7WEAhbgBtKxBZ0tHpWHZVDxY1SgUPiZu9geu9iO1M7ROXAoxSQPEakM3Br5/O3IzXXG5aPjWo5anW01JiZf7uWgxJ3aHJHbrYUps9gOnraijjNGE4tE+oZUUTsogaZiN1fRT5LfePuX5vsceWTpzAyvM899u8OQEi1pUtHVj6EZBdjTG8PZZw9P7EZKiz0X4QpMU3ws/rtKxzGw7Pt8K/MvCRvykcUxZ+7yRf8LXvHkWOKq0aivrUFXBIokSNvJaGdsnYSBVCu7nxeS4pvhJLNW7aaSxsFwahikRFZwuHN2QuDpMvHOqqI3BWoWxGo36UthHx/Fn3ty/GdfMT5Cc/rqON0Gpx8SCnMsMypYX2hjF3X5ia+By2fCNh5bKGU4XDqVhnCKdUpwvKp5tBhZW6PYnzhLrjDYiHz2Ms6lTFW73Ej8ZYub55Ak544yhNoZU4NmmRxvNWycNSilO2gqnBUIdY6KPmbfOGv7i2yc83fQchsCDdc2isSgUT+8OHHzB+yjSQyv2n2GIaKu4jolVFO/0YYpUxlAZL5DWKWCsVLRtKUSjsEUm7SEmTmrLt99e8Ox2IuQiBYc+kHNg1ThWtQCujQatNQ9WNb//dMvFomI3iOJpjAkTFCUVTtc1o/f8W7/7GSdNRWsVl02NMoqLRcW29xREVTIG0J1n4cTMZrRmP6WZt1PhkyD8NYabLpBiIcVCSAWfEhdLh7WWwySw2UVlMChKETbClCJ3g5ckhpSZUnk1GyycJyqojebQR4qGFIukFSjNaXvkRTkGL6qak8aBkkPhonZkRHabi/CWQijUrtBNUNc1ATUnzkjyzOXK8YObQCSzrkVN9Py+Y5gCqWRqV5FiYdU6CjAlKc7ddhPnS8cQoHYanx0XC8uLXWSKmVASVVJUTvPWZc35ouGj2z3OKB6tK3a9Z8qywK9bTbcPTMjGt3VQUubZ1rNwYsmrrSKmiLGW0QsHoqot334oCr2HJw27PlAo7AY5GNz3k6TgGIVCc7Y0bCeB3Y4RdAZXA0Um2z7I546beK9kg5ADXCwqVJFO0TBmHpzWks6WNIPLXLaGlBJTVPTxtQdbK7F/qLnqsyWR/Y9v/lsth4PD57QeZocfsbzuHv8yhgKWFSwry35I5Fy+FP/ylzD+FeB/APzfZnvBN4G/8yu+pp97WKXop8CnU2Tfe246Se4yRpSfU5h9+rmwdJq6qiBlYgqQIqquWTl4sZ14sR/EXpQThz7yXu3wU6b3oqp4uGpRWLROPN97TBE2xugTxmjOFo51Yxmix4yFEDI+FU5biXO/GwMqz5yDmelyUUNlRUF01Y1UxuBV4flm4Nl9DxROGscYIk1SZBS/+WjNR7c90Uvh+u2zlvsuSOKPUaCkC9whxYXOB7op4bQizFLt51vPSaNJE7x73rL3It8fpszDtWUKCaslBvrT247r3Uii8M3LFfvPdpLko8Aaw+PTBWPM3A1BDusLsW2ct4b7IXIYizAUrKVVBa0d5wvDEDLOGiotxY5PdxMhj6xaiVmeYiImTW3huy93LCvF+2cNN0PgZT8w+UhSYm2bfCHFzEnreLSuaKzh+dYzBAk66KbEwSR2Q+TxuqUPibdOGlY+sukmrg+ybj1cyzxubKFWlsuloXGG5aklJmHNnSwsl03F3RCprOaf+dYDoHC9C1yuHc+3I4cpUXLh+U5SYWujqRpLVVnh34XCy8PIO6cSmf3kfsSQ+I23llhleL4deBr3+JwJSQ4GWhuMVaydZTN4lFa0znFSG55ve8hgrWH0iZAKlVU8WtaSkOksWsHD04ZPrg+0tWXpNN95caBQqJSksn503bGuLS+2IykVhlTIMTNNnq5ASpLc5rQokYiZbSr4mOlDwBhNF2E7FOwIRkWcjTL35rlANP93HMC5xGpdcd7UvIwTFmFZpCxryu22QztHCYW20Zw2lpAMzzcDBy/Nv3Wl2I+FqUh3/s0uss8CTg28tik0FuKPLCLm+He0NFdU+dlFoS9qfzYgipACn9x2fP9qx19+/+Krsk58q5TyN5RS/wWAUsqg1Jd4yvlzHlorGmuwWv/QOUMrRYiZp/uJXAohSYKls5pHs51LQNGK33y8frWHerYdmaKw1p7cDYQsxfuU4Wo/cb5w3HWBt04b/FwoDlHmpULmezeT8Gt8wlL4m9+55i+9d4Iqch4qWTFG2VOva8efvNhDga8/MJwsHPsx8Y2HS55tBm574ba+c7ZEaxiT7LWnFPnBjdihvv6gpfcNn9zIPEBbUzkBAnufZjYOOKfoY2DhJETGaJkLN0NkN2U0mW7KTBGaStFazdVhwirh/VRG4VPmfFELT1bDZEQUsPMZtZc0qilCzIriPTlLimUsipSF+bOoFtxtA9dj4nyZOGscZwtBQJy0lttu5NO7jrdPW94/bwlJ5sLNGAilsLSiKPvkWpwJpYjlOcdCzIpWQd1ohpC46zyrRpSr1hhyFseGD4WT1rEbRAm86ScmrziExOD9zA2SBDofC7VVWC18O18KD5aalArfu9rRTZHfenuNj4ZTn3i+nThfSorboxOxLqec2E+iLNJKmmGqyL0bM5RcUAXq2qByoZuExTlMiSnPKdBKAggO833fT6KoSjMA2o+JGGSuiqbQh4LPmZgKarasjSLC/bFReK02skjATjf95CL9kal0/OeXPY7FrMKP/3zBdry+jiMM++haSIhSVBs54yQE1VE5yHP1JCLODTnH8ioU6EfHBJQAj9e1qF61xiixy7532fJiM3IYEzf7kd98WxjE75y1X+qa8IUKSEqp/10p5V984+MVAqz7T8JPl5z+Oo4fBaWGmMmlcLWb+M7LHYfek9EwAyofrhpqY3i0qvmDpxvxyBexOr3YSerC1V4iLZWW6l+IUi3XRvHtx2u++2JHzNKJzKUQc8Jg+I0HK7qY8DGyH4Q9JBXXjCqJmBVndUV7UvP7n234o6cHHqwcocDNkNg827JoKnJKfHLbo7UcJMSaJ3LVlCNWOaZJAK2HYWIqolkMSeSzJRtWjZMJTSmJ/EMA1DnDYml4cjNw1wV2o2c3BqYo/+9kqXHWUjvFurb8pXdPGYPI2O86T4qZR+ua8zl++bONl2StSuGUVEpfbCc+3fQ0WpPR+Jxn+n9NN3mMlrSh1llKgct1jdOKyoK2FTkmxpgpSXO+rDlbWMyY5gkXlpWmtjUxS1Ev5oJV0k0upWEMZYYHztXg2eK0GaJY3eLEbowCJtSFpaq43U3C4Cly0Pep8N55TePg9hBpqiPEVLq9y8ZSG40vER9EPWW0TNRP73vOFo67Q4BSKKXgjOLlfiCGRM6ZUAoxgdWRkDNKOVrnyNOE1RmjNa2TDng9QwlPFxXaal5uJfmtaOkcGWtYtpbWCKxbKc03H695cttRsvzs90+sAMxnGF/IMPlIjjIRLhtFLooSJV1qSoWvzdacr1+uOFlKoWszRk4bw8v9wEkrBdh3zhr+5LMdxlgsCe0MsUgyYCyFyhguamAv0swCpCTJU6va0U2B7RgEPq4URcNhCpQsUZWPWs3pouZqP+GDdAIXC4OZrW5GK6wpBC8qAKvF2uDD647AspJEiJqfbEt7k1eh+elf92eao4C2kgW66PKVSdcppfz7CAfp+PFHwL98/Fgp9T8vpfy3fhXX9kVHzoWXu4nffvuU/++H1+x84r6faK1hNwVOW7FG1lrSDE8aSy6FB8uaj/sJrQ1OQ06aYSoMk9yneu4+7YdItpGdzxgFISeCjzzbTywd1G3FqXUcfEaXyG0XqZ3mejeRKaxtRWMyfRAasDOKMitnlNSvSEWgws5q+jG/YvZtuszNQaD6Y/Q8WmsoFTEntlPg5jBA0Vij6AN0g6fzmZXTrFrHb7214g+e7tkeplmBlKC2rwD6SmsJctAw+EBrLdshCBduyrSVFCzS3LDpvIBaVRn4qx+ccbqQzfpJIwCBs0XNy93E1Xbk+Xbg4aphXWmc03SjZ9uLSvikbWkr0MYxelEW1ZXhej/zR5RGFcXz3YAPhWVt0R2sa4sPhlwyV5ueFEVts3IVbeVYVoXPNsLie76VotthCFRaMUyiQe+HiAHqWrHEUBvL5dJSGUVRQdbrDPshoBEL9OmyYorSd0whMkwBq+Frp0su160ogQo01vDeheFPX0jC3+ATu7nI002Zy6VDKcVffriS77uwbKdAZTVP7npCytyPgfN1w270DDGzqCtqm2isvLZGG/Z9QuVMiIVlY1FZlF6bTlJ4DBp0oo/gjIB/v9lY/vGvnXOzn/jDT+/5w2cbrNLcJkkWenkYOWkdTzYD523F3/v4FoWSdMNVLVwlpeTANdvC1nUFSpNyolIwqUxtDdsxEo5F/tlKNr6R6nMs3iekmK9KEbhvjChERctsQ8sJXu5hUQWUgWkH96Oomrs5HZQia4Eprzvjrw4G6rUy1c1yoYyw9I7BDIXXHeecQc2nj1r9MKPvFxlWSWrc1WFk3TqebQZ++51Mrb8SalWvlGqZz3tKqW/xy1s+fy3Gj54ztFI8WsuexBmFNYY4s1gvlhV3nZd9n05cLCvaykp8+rLmYlXxu0/uOW0dhymRUua+DzxcNzRWsxkC993E7WHCaiWpjUrUTU4rSk74IBbb85OW0Qc+enlg1RimLAoh4aUptDG8s674+qM1WsPvfbaVmxhJ/o2xSKG4UoQkuIHD6Pmjpz3bYeIbj9ac1I7DNPL4tKGyhpPG8g8+vmPlNB93EyFlvC8sKtmzPb2f8NGzmJMycy5USvZyxvBKQWk0qKw5XTpykdQ05gTHptIUFCe14sGq5cW2475PLJylqRTDWMhFs585cetFIaWMT/A7n8jcNcVEjJq7gyg3Th9bBq+IMXN7mAhZ7NurxkqTv3b0U6QPiZQL90OgdYrn24mUMlkVxqnQF+D5nuEskrKCrAkhMcyJ0U5rXC2YiIWGLiV2fWKai+gUyFoJoNkaTmrZszdGcBs+JD66Hrhc1sQM28Hzdz+6x+oMynDRVjS24qQRPmtjFaU4UqPQiOPj0ElXrG4Mxhe8lgZ7DBIEknDsRg8FTmpHow3Pd54xioXrbCnujKO6f1Vr7g5ZAmvUrNT0iQcrx/3eM8yq0c8r+BzLHgmZ749SI8frv2eBxgkvqfuSWEmfp346qoc0rxEWbxaPQH7PKcr8XxspnDkDk5J53Ja5WY24LqqfUu8xzIUoH2hqSUnsgwSuTKHM84bhL79/zuOTmofriupL5qd+UQXSU6XUv1FK+ZdmQOr/E/jffInX9aWOo8w0pMynNx2xSOkvhMjHdwMnlWaIAhLeTIFE5sldx+9+ei8MBmcZQ+J3fnDL45VAOylwu5ND8vKYhIB0U5vKcd9H1o2jqQyLxnB1P3KIAR8KsYg8/KQV6HFTOd69WNBNgYNPrBeO9y6WPLvvebLpcVoUIX3JlOK570fGBGurcSYzTolIpkqGwxA5Q5MS+CGSUKiSKUo26W0lG/rOZ3KKAoNVigfLipIKv/nWmstVzZ883/FyN+GD2Dt6n6iMQGPXtSh7nDX8/Y/vKEoWz5QLm2Hivo9861HLTVcwKjFmjUmFH2xGFrWhcoqbTeDFFLlY1qIsSZnaapSuSSjOV5p1UzGFxGVreXdd8+FNR8pQ2YrLtWE3CBvpvYsFuUjRadt5hpDY9pFlozEUaqepbSGVijFmpjSRkjzUlTMcBuFiTTozxUw0apZrarSy5CIpCIvasW4lyeJ6N/DRTUfKiTFIUemsNaxrRWUND1cVV3svAN6iWBjDFMTmsOki/+S64bffXfDZ7YEpZiYvnfrdmKitJiaDRwplukinVpWCQtPWht5ndmPAFJHyaAyt0yzqhm9ervjw6oBPgT7A0hk+vDqw9ZFpmmiqCqXhwbLmpvdMqdAazcmqEoi5UlzvvLwv82TXDQU3s0bUDBZ6cQhsxsTzref984b3L5ekPvF8P4HSLCrLorb84OogKQxaESqNVoqFtawaw4vNRCkQ51175cR2tqoMGYNGWEs+F1YOKmNRWlFKwVpFP4pN6Ol2QunCcmF5Z10LtHFlud+PnLVysA1ZYNX1/Aw0tpCRVc0YmEZZBI4S1DcXkTcXqowsHJrX0Z+/yEhANwAnwkb5Ryhd55/9VV/AzxohZT7b9IDi/QeyRuy6SZIM4RVTpTKK1VyofHY/0g1eNrJWSeGiSNH1GBk+YwTop0DOUtg3xnJ3COQsnbps4DDI/B9z5qzVTEPmbpwYR7Gs5CwNjkLhYV1ROctYEqeVYV8CYeazZAqKRAiKT28ODDHNbBVRnkwhM4XMZ7cHzlc1n9we0FozhYTRik+vt5yvGj64aDlf1Dy5PTBFWFWOm5BZ15opgCmZnPUcra6pnWGKhcMYqCtFHxPeJ5wFozJPbjtu+4kH6watFOumoveB+8PEbpjE1x89qMKyrnj3XPP0bs8PrgeudiMni4qHK8t2SFyuhcXkYyRkzW89sixqYTY4U7HrAg+X1fysR/ZDZDGz0/a953o38c3HSxpjGFNmOwZKgWEaCUcwupKUmocrx36KWKt492TBH77ccRgimcJ/+OsX1Nbxcjvyci+afEvhtDFcLCvGkHn3ouVyWUMu9DEzepnnnFNcupqFsfQpc+gm3j1b8O5pQ200H94cqKyArqcoM9BpI9bkVV1hrDRqlFY0leFsUfHRTceLjSTOKSNq5n4KvNhNnLcCce/mnOAHy4o+BGJSLBrLbozEKBazxoidM+XCwhlpgGXFYYr8xqMVy0pzQ+HpZpA1k0g/enaTgFSrdY0PkSd9YNlorLG82AmX0WQlHBPlXzEEqYSV4bRm3TrKoUjBMUaGeTdu9euiznFePm7gDVLI3A6JmAohC+Tu2BFuG3kOxyhFYO3BE+k93OvjIWcuQvHDaiADWCfg7EqJdWNRK3aDLIgxMvMURQE8+UxRSJNrfv63P6N4dCxMfRGYdigwBkkNvPyG5eDzK1vUV2D8a8C/B7yvlPo/IevCf+VXekVfwjieM1IpGKV+DJ+hlRRGrnYjTWUYYmZVSzPSasWL7cijdc1t59Eomtrw3lnLTefJpcgBW8GLzcDZyrHvIpVRPN2OdGNgM4ia7mLpyEXz9qolx8zV3tNPicdnCy5byx8/ncgpcda2PJob1OdtxYc3HdteGsaPVxVjmG2mY+TDwVNZafY+WlZ8fNvRT5FhToYOKfPtRyvevVhKiE5lpaHnEz7L3jzFwsXa0rqCs5bL1grPMmbqSqGKJZbM188aihZmpvcJvarIpXDwBV0Ub5+1bAY56yhknT1raza9ZxfENRGzJHqlDFAYY+CkVpytKnTK3PQjYyikYjlf1BxC4rP7cQZDJ672A2gppq8aw/PtyL7yGGM5bx1dCJy7Gh8SD5Y1n217tgfZYyqECffpbYczmjHUVNbSDYJLWbeKk1ozTJF9iPgoTVEyLGspVmkl++zdJMy2ZSPBQftBQn2U1uSSuNr0dFOhqRIhwJjEBVM5xZgL/eB5sF4whUjtDClLkW0wCe8zhy4SExyiqCoLei6STezHiu0gc7WrNO+cGm72aX5dCuuVox8im67Qk0kIk7R1irq2DEFS3Q7+NZ/0Z40Zg0r3xtRWeF3UqdT83+VXA9q2iBq1qQWif5gyfXhtazuaijXyep4sHEoVDj7TuFldZySoqEZ+1zwXlX7090lIgWkImVAUVkk3xVpLHxJWK946WfDopKILieuDp7nreO988Qre/2X8/j9zlFL+VaXUv66U+l8B/wTwPy6l/FtfyhX9OQ2tFbsu8LufbdgOgcoo3j5dsB0j/RjJiBro+f3A7z3Z8GBdcd9N1JV4f/sQ6HymaSxNI6yEysHtPrCY7wSjNS83PZcLx9VuYEyJw054C0orPr450IfCuractg1WK5xWnC0s1hoqK8qNF1uRjVprSX3kdFXx1umCP3m65fluIGfpVqacsAa2XWbdSrXyYunwMfPwtOKT654cM0OCpYtoY1jWipQFdG2NxmmRVz4+kQ3++bJmPyUermtKkcq3LnKACqlgYmYMEUURqw0whMg//OSeR+uaunKUPvLZ3SSWoiyduhQV6MTHNwcqawgpU1nxiYe5kr2oNXFK1FYOLjEI9DOVwqp2/IW3VzzfBlE3jYG3zzR3XWRRGYZQeLCseL6d+Oy+x6fMdlA0znK6yDw6afiT6wMxZEKQNIUpiSJAmxmObDUxZk4ax85nKmNpazn0+BAYI7TWkrIoYWLOPFy2dJMwqELW4n0PiZvDxKb3LCuRnU8+s2w0WgkrJM78iT96vp+tBSJRfLkbWbeWhCLnwjBKQWUI0r2vrMbZmota89HLHakUWmtZt4aX+8DDk4bnOwHcXixbKqf4w2cb9kOkdY7NkChdR2Utb5/WnBVHW2ku1w3fe3lgDIlUMtZK9XyK4JQAYEOEqWQprmS4OUTeOnUMg2w6XuwH/uoH54SQ2XlRHFRWcd15STeU/iOHKfPWaU3CYOuEywpjCqfG0VjNo3XFD257+snjjGzUQxBLGzmA0YwRahvZTYAKaCVx1gcfGaMouLoxobQiFcXDk5p+kNhmpTKVs8RZyhtiopv7oYU5tQ0B5H3eyLzuVP8iW3mNHDqmCN+8XPyjlK7zaz9yLjzfjDy567jZjzzfemIRAP3lrKKMaU5Uqy2bfpqVDgpd4L4TRUpECkghg46iXDBaGHn9FNEGFJHzpaMgc46PsGwV9wdP1mC0IwLTrIzrPXQeEplKQykDD5Y11ylRSmHdWjZ95OAzToOrLJECGfZjwieoNHRZntntOKFmNa3IwDW7PrA3c1E0JT7bDDw8XXA3JvrRk+ZmRyoWoxO102it8QEuF0bmqgQpF0JOknJlDNooxhTpo2x2zfz69KNHabjvJ7791hqtDNebjggsK0k+2wzSwW8rsc3+wWc9msLJsmbZanLRPFw63r084S++u+Lv/WBDyFJs3/lIiBKNy9woGTYHzha1MKhS5vefbvFRmDdaCesmpInHJ45vP1oz+MKm93gfCRSe7zVvLyu2VtM6g0+F713tZ5WRsJPGUHh82nIYA6va8e1HJ0whieVgjEwhYpXCWMPaWT7bTKKkUXKwfHrf8/55wxgLVsO6MuQsgRHOqLkAJ82Dd85bamtonOatk4qbg6etLTf7A23r+Oy+QwM3h4kYDI9PG57ngdoZnFVcuAatMtZafEjcjgGrJH313UVFnzIURWM1522FtWo+EPXc957zZcVN5/njz7b0s9VaK3i5HTldOHIs7DZe9jfOkkJiNwVSrkiqsKidFOpnGvyjUzn8NXXFNE4oC24u3BiEz2FhToZ6Pe/WVopDjYaC2DyGUKRrG8QyUNcKm8urTT7IptwpYZs1FaQgUNfjhr4g90XOczKmOFbpvDQeLxfy3IEwyNrasqwLbaXZjAE/SYx4g6whP21tOEZGf5EGRAamCfSJoh8iq8p+JexrSikNnAN/HfinkeXyXyml3PxKL+xLGlor9PGoPFvo42xd+2zbE3xGG817560UaitLP2MowhiFcWrFIUApbKco9qCQuT5MPLvv+Oim5+GqRgFvnTZ89HLPuxcL/tK7p9zO+877zhOCxH3/5Q/OuDtMKDJ//KKHknn3Ysll69j6SEqJ777Y002e7Sg8pSkV1o3FWc3NfmK1sDIvHgaudyOVlWL5ECKf3SWWjeG2CxQGuimwqjTbQ2LTB7rJ46whlMR9B0YbTpdWmhxZMBJ1kbOQUxltYD/IfG6McNtA8e5Jg1GKh6uKZaV5VkZyEaVoUaCGQJ8KRoGzUgB3RtRKY8h0U0EZT4nSxC9KnmufxUHx8d0BqzQpRaKHYUwYPDcHKQjqtuJ8Uc0No8Kz1PP2SQMqU3J4xTOziKIRBWPInCwk+THNxaWcC51PbMdEbeQs54uoj5Z1RSmFMUgQkjOWi2XFxaritg9crlvGKXC9H/n+i4DSvNpLFBEgobQ4BO52Yp3MSwlu2I4RSyIVDUnOu3gplBvkexxGmddUhm4I7DrPFDJnK4szjrqaLXsT+CSJz4tmBl/P6WPGiKXSx0xOUFcwDT88Dx5xEG82aY/76OPreBxvFlb6AuanTJhHy/HP4pj+POPYtKg1DFkQHzHLXh0yl62iNgUlLymqCCPPalAOIpl+TLROcdJIsXicEvWsjj2qao0Gl398LThyoVZOk0vBaMXmMNHUBh8KfYw8uZUzY7uSpO034f2/7PG5BSSl1JvWtL8L/Kvzn0Up9ddLKf/2L/2K/pxGjJk/erbFKol9rYzm9iAT0G4IxKwwBipjuN707PsJtNDzT1rxHC8rQ2UUF8ua672nqSxvnTkuV5YX24kUM20jm+fGGvZjIJdCYyxfu3Rc77zccJVBacWfPNtz2jqUMTQ2c9dNPL0dcFrz3uWCr1805CwV4HESUPI4gXOyqb8fZJNTlCTrJBTL1nK1HbnfB/og6pWSoZsKqUhUs8awbAyP17LRXTSG33hrzQ+uR+4OI1ppDmPCWsP1fiBphSoaoxKTF17Hd54dJMWkMTilue0GBp/ROnO+rCFHNkNmVRmWteN623NzCLRV5FuPFjTOAZm2sgyTJ8eCVoasE4cpc9ZC01QYo0BrVClsx4yf5f5aay6XFVYpPrntWNWSjjaGidGL79YjgNCrTuDkDxeOz+491hicTbiSGcKsetGKalbHjPOCEkk4W6MprNqax7WlNYbbbsIqxUllWVTCakqlcJjELnW+END2fgqELByPXYwwaZrKcraseLYd+fj6wDh74ktWhBixVlOipMCVDItWcdYaYswoMjmJP9npwoOlwxdojWHZOhbW8PT+MNtZFNfdRK2F9XBSO3wWX37Osjs+TJGT2qGAm93ExaLGKVlcP/JbUCKPLqoQo6SzJWB5BFMDU4ism5q9z1xvJz677TlMnt2YWVeGj286dl3AAa7SoDQxB4wulCQHlz4lzuY0gZPKspsC5wsBi/skXeIM7P18kCBT1ZKmt3ACrEy5sBkn1m3FYfDsRymuPljVxJS47Qq6FLSx7EdPmAIPTjXGVhidGX3hYgn3nSxYGlksPq+JrJFi08/qhPwkRdObo0ZYWI/OGvbTV4qB9I/EGH3gw5s9tREbas6Rw5gplFfzqzKKgMx/5wuLKmLherHxrw6sx01RQTpkPkGVRZUQy+yJ3wfeOnU8WGbuh8RhzPNmBPYETlv7ynv/Q/dLhn2XKATO2oqQC40VPUZGUrWmGOl95qwx1E6e1X62/jRKrtEpuO0DjQWtrLAptJLUxKzwPvPh1Z5KK5armttumuPm4b2LJe+f1VwdPFP07KbIdR+oZ/tGVobzhWbhRCE5TNBaKRRspkStCxnDSWu56wIfX/e8ddpwuq64PwT2Y2DwcS7MKO66SCmZm0OknjfJZ6uKYYp88+GKdy8aTuqKrz9Y8uH1gUenNc83A9vgOQyFxmkyiSFqDmOQsIIk7xtaFIjGGpzJLCrLw7UUZra9sAWWjWEaIi82He9etJxI3BvPNx1jEO5dobCsJV3sMCZiinQ+81feW/O9a0ksrbX8/BgUdQW7IaEQW/PN3qOAB6uK5ztPrRUvO880JW7nr9Ne9hG1STxYrmZrc+Zq53m595ASIRwtgoonITFMEZ8KWkkCamU1D1ctjU58fDvSh8L9dsAXUV69c7rgfFGxHSa6XZqT7eBu9LTOsO8DldYMQTwLuy5gtCQIjl6sIZRCyVleXwooCYJYNRWHKUiQhDFoJZtuq4Tr46zl6tDhQ8J72XwbPVsB8uvEy0crud+v9mkueL7mVJw4g0+ZKZZXLKJcYBwL81bjhzrgY4HoRTFozesCVZ5B2qVI8fVoia+swGuHIN30s0XFbe+pnMUneLyquOs9JSt8nC3YWp7/n+bVisxspc/h7r05tIKLhXAPE/lLhaX+skYpJSul/pullH8TcTJ8pUfO5ZXC6Get0VqLje3Dqz1//GJHZTQP1w0lF17uRlGneCmWj1Pk+VYYcetGOHj3s5p+XRt+sBtF9X7ds6w0hzFSWcXH1x21NfP3kpStZe34jUdrPrzp+c1Gc7le8BuP13z4cs9tF7hcNywqw+0YeXbXoecCVULz1rqiC5mr7ciUCmdLi1Kay6UjRbHJ7aaRkmFAFLxGK762XnCycKLKT5HRF55sR7wPLCqD1bIWnbSaVeMIsTAl2Ws6JYydkjON0xx8BiNMuyGJ/bk2lspqKis2zsMYXzVonNV8a7WkVppPb3tSiRitISeMhYU1jEGYUsIk1dSlMEZRV7VO44ximhJna8Uua4zL3B88VmuULjS1Y5wiT+YzXVsbbneTKLaGwFFClAHUrH6S/+S2CxiKpLUpKUoXxN4a9FFlmWeLV2ZVG9q6JsRC4xTFKDZjYpwSWiVRZiXYJymGK+CkkaKV01L8KVnUY2etYUrCXbo5eJZO1vouyH4+Aq7IHsUfg3Si7BM+vRuZEXWEElE64mbrem1FcVkjc3Up8nvEWTFTlMIpjbGKYRDrVnyjgqTe+OdY7PnRP3/a+NyE5DnZ7BctIBnkNTjyTuMM945ivoCZ6VRZw4mR3283RQYv5+3aiqvibkyUAlMstEnWziHI63QsloGsVc7O6iYLCYWjkLSekSKZu4M0HuMysS4Nq1rjQ+HZpudRrvkrH5yhtWKaxQaaX/768LMUSH/tRz7+XeSM9NeQ3/crW0DaTYGr3UTlNFe3HSkXbg+BdaNpa0dMicMkG6/P7iIXy4r1ouJmP3F3kI3iP/buGSFlnm17xslzdT8wxcJutJy2FTFnrrvIg2UlCouUmIzi3fMGjeL24OljYkiJdj64Ww1/+mJDLoreZ0pJxCyRiaAoRXG1G0gp04eCs3ID38y8gsopKiWpZJXWhChA7ZRl4QleFD3bcQaVBVgJ9xifFXd94KbzPDxpefus5h9+fM/NfqRymndOap7cdExTkOr27D3tR8+owJeGhycVPmZ0VlQmYa3DWo33itZGdj6SVeGkreco48zz+wFjHKeLCopiShmLYb3UaF2RqoIxkEpiP0YerSp2PlJPYkcQKBxcbXtQim9cLrDa8PR+Pyc8zEUmBSUrujHy+0+2rGo4DJGTpeNiVUFJXG0CS6Noa8t2kk79QlseLAx9SHz7vOFuiixqSwiZ6zFIMk1lCXkuaCUBua4NaGPYHEYOPkuaVoan9xNTApUTldZ8thnIKQpzSWmCFW93PwTeO1uiVCHpkZAy5wtRlPVTpq0tISX2U0LlwhCDbFYLXCwCl+uaMCXZgAOHMfGy7xkiLGtFjlE6QTFzsnCywVfwYNWwGwOPThruZ+/3yaJF6YzTmbs+yALj50kvvY6r3A4FpwMxJEk92oplYQyZrVHC1SozKDgVUk7ECE/uZXE6XVguFgIIf3rbc1dpsW4USQLq5s31sTuRgbUVpd3RTmdVpjjF7c4To6e1infPWxaVofeRu96jKSyravbSa4qVzpefRlSRw4jvXidDHH+/zxsZ2UT9rHH8fp/3fTSad84atn0gpK8M2+JnjV//Ew7y/MjmrtCNgbt9YJwLy3HeGFmlUEUxxEJbWWJJ7DovNjEDdZB7oQAtYpX0CXZJ5txq3ikMCZ7cCSepAKctnNWaLhZ8Ktz08VUa1JvKtowcXH2I3GU4qY+FIxijFgtPEqvrHmishRLxc/G1L8JMOqZDUYF1UWxoleXxicUYwxgTm8PE1x+v6cbAbT9JoqLVPKjhfoi8e9bw2aYwbTuiUqyMZvCJ1mmMkabCzWHEGC2q16biZj8SMqwrzcWq5uFpw1njSDmzHzJfu1zhLFxvJR11OwSudgmf59hfQOlIP2liEnXkReuYcsKnTIiRs7bGaDnYXW1HThY1lELlxTa1bhTd6GfgeEErSRBb15aThWPZSNG685HKScjESSvr9HnrQMH3r3p2g8dHKTxQxKYYtGHRGpypqK3i49tRGHIl8Wzby/ySC2oGu9a14sl9wiJF/xdbQ6WhspasC6d1xUkjQccpZg4pMBlNSonnm55Va6mtoVKwSwLEBYVSmf1Q2I2eXITQM8bMNy5aCoXPNhNP7gemFIUzUSLKSsNj0ycUkaIy110BJXuKaqX5/s1B1GczDHjKohQoGVpnCSXSOovBYIxin4XVpXXhZE5zq53DqCKHv6IIFEIM7IaI1YpspWGBkYKn1nAY5YYtQB9kVjYzdOLxiWbwBaNFwTyEjDXCtztaWGKRPctxs/4mS0MjXeM8M5msEQC25nVyZyqw95m1MqIY00BRtI1mFS3vnrYMMdFNiTHkefP+uij009YQ9cZ/LGcF4PA5C45DlAKr1nG2djitSaV8VSIv/6ZS6r8D/F+A7vjJUsrdr+6Sfv4xBuGB5VLQM7bh86wiY0i83I1cHSaMUrx3scBpYW+lWFg3mu0QOV84Xuwn3jlv2M5qxT99MXDaGGIuOG15tKo4DEHCdqxmmiUuIUli5vV+5CorHp/VfO1yyW88WjIlSRZtawe5oI2klJ21jt/79J6Pbw4UrfmLj5ckZTDAZghcrBt6HzGzxTrmzOA1F23N7TDQjZk9khCZkYZ8N3qep8z1bmI/Tig0jVWk+dlrjKGZ3RG9z4SYJHTBCk5giAlXFJfLir1PLGqNayzn8x5VW8MPbjq2Y2QMkYtFjdIanRPXu4Hz5SlGA6qwcBVvndciDChSbD1fVuxHjzVSQHmwdMSsGEJkPyUpIFtFxqCU2MGLKjhrKCTePl2wsJpn256bvWfTB7QuxFH2DOdLgzYav5P9bkIK0n52H9hZSQ+yRteVwVgpPBgrLg9TZR4tHR9cLvno5oAusBsCCoi5iAshypxV9Ouo+wz001zEMeIW8VGxqhVaC0x9Ch6rFO+dN/zp1SDvybzB8OImxtpZeYmAncscPb8wYt/ddIVs4MGJpTGK7RBIKtPUjn5KWCsJdYZCyoWLdc0UI/fzXKoRVWYBVo2oeI6NtuN++80p8NicPSqSfpbSPwArI3v5X3QUZO4H2TPN1A6GIkWzoiApxc4nnDZs57AVPzcDfZQiElb2florUBljDZNPr64X5Kx20khAyOVCOEdTDLOCq9BNBa3EGhhywefCfT/ycL3mdCFrgdGKm90EeFIpvHPa4r4EHtLnrjellH/hl/4Tf8UjZ9nw3O7EFtYazcWy5vtXey7XklxVW/j9JyOVFb9/KInrLvD1B0tCjDy563Fa84O7A60xbMbA803Ppgs4pyk97HqxJyyt4aOuJ2bx9mql2I2BB02NtYbNdiKTMV2kdnC7H0lkamtJaKzK7MaIT/LoPF5XpJIIJXPaWu4PUTriSOfYqEJdWW4OUQBdfeDxumbMinVr+GxI6CNPQMmNP/pEjJknIRFy4u11w/V24qObAzd7sSOtakPvewH9WU03ZXQQhoO1evZ8Fj6e4+obp5iSopsmQtZcrDRN5Xh0WtH742RaqJ2RWHgKQwgYMv2YGWMk5SwbNKWwBkIsOGPYTAUfMh8deha1oRvFjjcMHms1ldVY7bkfPIOPjDP3oLFQmSSvbYbGOgJeuj9aSXdXg7aa2mqWWfFgXWGNgAoXznAzJImLV1q85YeRpTO0leZqP3K1m6BkWud4eNZy00+MGXJJ5KzJUeB0y0ZhlOaqD7heFumYMplC5yWVLVM4aTSDjwJg3A6orLjvJgGD6siycoQYuR0EAn5coK8PkYWDVAwUeHY/krOwGtatwkcBhPchsHSyaFurWDrhFF0dRp5sBtpZaruqNbWt0Hj6EGC2e+gigOC3W8VdJ4fWmz7hNFSl0PtEawSYHmbwegYO0+xiLlIcPasNRUMImS5LYkdMhZvdRMwCtTaWVxIgM/9jjVgPjJYKfUaktrFIJ2TdOkYf2A2BMWTa2sxpRxP96JmKQlGYMuRRVrVx+vEu8S9iSft5hwH6GChFlGxflaGU+nop5eMf+dw/VUr5nfnD/9mf/1X9/GNRW84Xjo+uDsSUZHNWwTDKgVHmzcxmyHgPOyXd41mkym58Xdw8RtBOSTZG8JrXIsd5uaVdkTn8qofzNnPSWPqQGccsrLGZG/AmuN0pGGPBpMCiqmi0pU8FnyJnK0e3D+QE15NI4/PcWYzx9c8O8/dBzRsbBX5KHBScLzTvndVUznLWWG7ue0CSe86XFUZrbrtRoNw+8ui0ZYqFmJI0CrLlfKmYfEGbwlvrmm6Mkl6TM187b7lYNxg0T+9H7u1IFxJfu1zzznnL3X7krveslzUv9uMrFkTrCqHMtkClaWq4PQSuDl74F43h6UbeE0XhpDZcU3AqsWgqxpjopoiPE2+d1rx9vsTHHSGKYkes3IYHy4aQBaJeGemErxcOozWdl+CNmORQ4SwM8051ClCbxL5PLFxh1TgqrbjroPcT21GKYGYuuPgMLhYOMWKNwFNXlWIqisMwElBUZ4aTtmKIiVVtaSvNEOB+EGXxboxcrmuGlPnsfhAGD5lUDEMMZCXWZq012z7wVBf+6vsVU1vx/mXhs/uRnCPbAeqSuZubRpVxrGpHSJMkt1rNbvTcD5l1YzlrK24PE5XJPFjWGAP3By9WrJTovTRbrBbLZBkUY+NQ1tBajS/CmhwmsUOGVBijp3HyPtSuUBtN69RcvE0YpeljJEbhzKxqUTxZa7moRN2Vc2LdGNYVhKIIQaylVRELXIU803GGcztkfXFqVtXWEIvhtLWvFN+xwOnS4JShS4E4B5asW4tBY22a9wmyF4gJFvXckc/S4f9J4qIjdDXO84RRoog6MpF+dCjksLdwhlwUX7tc0FZfkdKRjH9x/vO/8cbnCvDNX8G1/JlGzoUX2/GHgNifZxU5fr1SwrXxqXCzn3j7rCXlzKOzhm9cruRQmhKVGVm3FcZo/ujZwG70hGRYN47vvNjPLCWFs5rD6AmpsHBSZH3npOH71x1jSMSS+Sc+OJcErJj5wbZDa+hDJifhSX73+Z5nO+G+nTeW2yERY+SsdTw+r1lWYps6X9YolfnkbsRPgVQkpbN9ZBmmwIvNwH6MdBRU0SxazbNbCX9IWZipqShGH8gp0VbiKBh9pHWGVaU4TAFnNJUWV8TdFDirHZfrmhebgbvB46wWnqxVOKOIQYpKRmuigiEUPrnZsx/EspazhFc8OqlRJdP5hPdi+1zUhv0QuOnFRWCNYlFZUspUJtP7yLp2KGVxBhKJD84b+jGwyTPkGgm+sdpwP43EzNzgdZwtE5suvSrsVMjz3RiNajKH8XWKY7WyDD6hkVTO3VBIwJAKKRXQsrZu+vJqb6HF9YtRskcO8xmgdXDWGtrGkpOaWbMW7yOHKbLvM0XD850nJ2mOUUQFFZF9/eoYAnC8h5nnKQUUTWUSSoui6+AjQ8gsnGLZyN5dazhtjVj0QiKkKMWQNO/fFa8SXIcR+p/xzB25d0eb1xcRam78F/u6nzQU8hrX5rWFOc3NBaV4pRRPwKkDhcIqOG+1oDR4jbQYsjTcmwqaSjhI911k4RJVJc28MnMy20oA8cYoMI5HS831NhNjpijZG4wJQilU1mK1QinNsnK8f7Fk1Ri++3zPNx6KG+TRwnG1n/jAmV+6k+GLprD9T4D/IdJU/feAvwL8t0sp/8df6tV8yePYMfAx8XI/8a1HKz66PjD4yLI2/KX3TompcN8FtoOnrgxVZWgwhFS46QQ+11aOt9YNGtiPnt0cH7+qBSDah0hjNetacfAFpwqFMm+oEocpcGVHVo2jdpq7Q8SHzGohkLZAwY8BZxTdTBs7jFKFL1mxsIbrMWMqaGtN5+URsUpuuv0kJ4SmlY1wnLuiU8ysGi3y1DInHGipVodSWNeJF3cdRsHL3YSzotjIJXO3T+SShGmQNbpMdBFMKVTO4WMi5sJZYyhacdJUPD6r+dMXHSEHcqpZt9LR7obAmKUyf5g3wOsmoaeMM5plJXA+n8GHwFljWTcLBi+y920XeHxaS5SlhZgKOQu0bXvwHCbPg3WLn0vZCyeHphihWTjOWidKoZxZOsvtGIiqoFXhpK0wKnPXJbTKjNEQxjDD0A2Tj2xi4S+cNowh8+S2R2vFg3VNTMKMenziuDlIHPbkM1YVhmJoVKYvMhGZAk1j6XyibgxWQVs7hiEQSyH5xGmrebqdeOe0YaUUhyHyyX3P4Odut8q0Jr8CSndzckxGpPfPd5HTRg6OzMoJ4xCbYIi0tZWUiBzRWrOsNW3j+Ox+YOHE2vWiy6SUWdSWp3c9gw/0Xg6irxadKD72x6vCbkz0QRaxyYKf2RDWgNOGYZQuTGHuos6Wgaqq6EMkUmiMpBzlIiyiWIRL8qOT1XFhsEazmUGyi8phjaYbM42FMEfwDD5iVGHXB0qWSvxuAmME3FrNGw1+htz1iy5cv8gYkQ3nbpiEM/YVsCbM499WSv21UspTAKXUPwf8L4B/DKCU8n/4FV7bFxp6TirMpdCFyHb0AnQ30NaygZjmTdC6heWJYRwTN4f8Q2lQYq6REXhthVHzx2/aVMz8tZ5ZnZbAGYuNEW1FBVnN7Tc1H0LlmZG5OwHbyXO+aFiR2fUTT68DxmrOVgY9JHIWbphRP3z/WuQZ9HEGx2fxpa5aUQHufOZMJz65OnDfB6ZQaJ0mJxhzYDck+qEjoGR+URItGwtkk9iOSja4wNP7EaUKF0tLbRWPTlpyKXx0s8MYw6PHa/pYuN0PfPf5jv0Q2A4BYwqNsxilKcWy94HtPs3qQYFtv7VumEIkxcx370cOU2DbBw5TwGCwWrGfMtf7AxGZ63KWFJv9uOek0WRnWTcGpS3vnDQECtd7KUrddoH96Ik58v7ZglVt2AyRd85qntyO+BzRWtQ3ei7zJRL7IRDXFREt7A0vTDyf5L20Wg59y0qDM8KIMIUhFqwS6XlIhevdwKYPWK1YXjTc7D3L2hIz3O57QlKcNaJm2PYBozQhF1IIbIfEutY4K8w9axRnixptHU4XDApnoS0ahaGtDXd7Ty6KurI8WFa82E0cSmTVWKzR3PeJp/cDF8uah6sGrWHXeXqf8anwwcWCu84zhkDnBfJ+UEY67yWhlcRaa0S9hILLZc3LzYDPoGLhrUXFmDPBJxqr2c0qMasNJ43mvpNonm4SXiJFsawslVXc95GTCoqyXB8mgZXWok7+05cSvmEVaCfPhTLSIW4rTcqK08YwRCgl0zpNyhrvCxfLGh8zh52wVVa14WzRcLcfqY10hG9mwFIusH9DxXpUOf0o1+K43hztd768/vinjaSgaE3JYic/X7gvpcP8ZYxSyjd+1dfwi44fBWJbI/zOn2YVOX596wxWC0/vyX3Phy8PZAoPVw1DEEZQzJmX+2luxEqh9bnPUuzwYYbWS9LvofeMKXPRWlaNw6fCzke+/WiBUoaTVvNiO9E4xZP7HlUKhynwweWS612gtZqq0q9UVEdVx270LCvNi53n7RPFW+ct75+17IZIP2ZiYxh8oo+J/eTpxkTSsp8CzYv9wNoLJLyyliFmDhPofIQeF7TOLLUW1TwCwNZa01YQkzQdL1qLtYoPr3oO4yQpmo2hGwKnC0M/JULRdNvEeWtorOXhynG1nShKEjdra5gCnDaGkMTS9/S+Zz9lrNaUnMlF0ywcp0ZeiyEpGmXYzYWDylmayjBOgef3nvNVzbceLGms4m/9yRVWG252E/tXhYNCUYHRC19QzUXkwFG5nzlfWkoRhfGmT7SVyJBLyeSsqC282I18dN0Ri8xTzsjeu7ZSbNgP8346vFbtGGCtwVjHSVuTYsI6g4kR7zMhxFdzy35MjLPyxxl4sBCANln2xIfwOuWyMdAn2Sv0MxJCKzj4SM5w2tYsKiVc2FpYVFPK7EdPGQu7Ib2y8jnkuo+NrJ9VPDqONxXYX+Rrf5H2a82sQNXyWlcOhkGUoe6Nr4sITkPrzNJpjNGctpb9kLC6iI0NaUp7D5RA4zTTfCbVBk5bRe6lYBiiJMulnMXdMynOlpa31zURxbNNj9aJ3iMhWEWYmC92I9aWmYVW88HZkkXj0FrRTT99bvpFxhdtW/ynSyn/PaXUfw74DPjPA38H+MoUkN7sGNTOcd979mPgWw+X7AdPUZmX25EHy4aTtuLrD5fs+jDT/kUSnlKhcmJXSqVwc/C82A3ChSmZZS2+3DLLxH1WUkXfTwxhnqRsIeRCSYqcJTmjthpFZvJy09QOugmsKmJrWAnTJefE893AwkkncAqyKDkNj5aOWGAzBlISSn9IhUKiyoaTheNqN2E1YBSrRtJY4pxIUs9+/14VPro60FjH2cLhU+K9iyVP73pyERn/22dLiZEMkaVzLCrDZlL4MXE3BjSalGE7M3Xa2tBoRVaKB8ual4y8mIFupRTpuniRzof9KKDW2mJVYYqKqy4S8kHi1hvH+UJztqjppsDoI4ex0FSKyiliD8nDfhiprWE3CKz6pBEAX2XBp8LDdYtPmS4UWhfkUDfBYRBQbB+OSgOPTwWlAiFYkpLIRB8Lq0rjyegE0xxLHWNm1VqcKtz1AaPhnYsVuy4QUmQKE9pBUgLGE9BaJihojSZXhgdtxeLMkeYCSm00m37ixX7EaDhfGnxMjCPsCLS1QKTjbKM4Sj1TFrluCOLFjknUOps+UDkwOfPopGJMmUfrWvzku55NH0ip0NSaYUqsGmEuOasISdPWmdFD6zSNBe8KU8r4ObmwqYAsigvrBEqaIiSbiLP+9Dixx2PXI0XeOl3w9LbHB2HB6Fny+5O80Ecpq7PyO7dVhdGiRBon8dA3htnOMndmihw6zxdS4AzeU4wszNVM3Cvl8wtIorT7yQvT0RLxi2qGMgLbDKEQU/kqWRP+a8D/XSn114B/HPgfAf/8r/aSfr6hCnRT4mwphUiR3kuyRp8E5Otma4vV4KfMOBdxFm/47Y/3gFazLPtzfuaPSrVDhJwji0phjCUnSZWiwIOVwxlJPhtixNmCU5AjfHyz53JRcb6wdFMkZ5HnV3aWuTMrn2YLWGY+3Ca5d8+sw6SAsYZx8jw6k9Swq/0kB5ba0E9Rips+sjKKGCNZiX1m52VTuW4qCpnK1CxnaX4Iis1+4OykZekMVlv+9MWBkCSp86SxvNz2LJuaVDIf3x7YDJG31zVJibo2KEVjrcDJm4RC42fVZimFP3y64ZsP12xGz7oyvNyOxJiZcuKtswUUYRK0DrSu2A8TXUisnUarmq9dLvj6wxW3h4nWCdvu+jCxGSIpBgKakGZLUlFcrGq+dtEyRXgyN17aCqy2PFzJZk8ruDoE3jqpqY3BzRvSVS3q32GSjenjs4baOq53A2MWe/OyrjmM02tPJVKc8UnWppvDhNGSErQfA7/ziTBPtFaSeINYG0KCuz7zwQLOlzUhI5G/VnGdM5thYpwKkcy6rXn3vOW8Gelj5qSVfUVlFfsh0o+FOBd87nvPd55teft0gTWWBytNUXCxFN7S5aqeOXtCdm2csPykpp9J2qDIOKWwtWWIBeUUNYVKwxCT8O0cvH3WMt4N7Adh9TkrhcllYzitHXeDRG37kjipKt5eV7zYe07qxMNVzdZ4CorDlFg4h9ERjaYfE6NcDlOCocsCKY6Jk8aymxKmiNVez3PD6BOdh9OFYvKCMChJDqOHIbIfj/tFeb5+dD1x83P4k0IZvsjBqNGiDnx4UvP+ecu7F43Y478iQynlgH8J+I/Nn/p/A//rUsovGmD65zbMrIaMScJnYhJ3wU9r9rz59ecLx4s5/ObxacUH50uUgn/45F7UZM7waF3x5L7n8arm7hBYVxYfCp/d91ztp1cJjyh4+7SRJpgyfLYdWDeGy1UDpXC1H7ne7fj0bsBHaUZ8dtfz4fVAiImmtlwuK1H0GEsshdvDxBgy2mnOGst+jFTW86dj4r3LBdYqNofMfRcZvWc7eG52XvZOCk4bhZ7ByanAmJKsOXOC6VktyvCYIld7JKlYWbqQqbSmdpbL1mCsoRRhD5Yi4OkQiwC1AzN/DVAZq2CrC5dGsZ3keV06S+2QVEgvOzelDD4FuiCFodomWmdplObRqpICR0rURqPJND7hHFy2lttDpLLCb1K68J0Xe1oHsSRS8oT591PIXnvTF9LMFTqyiY4F5N5DLpGHKyfKmpLwsRCChE84rSjasO0SU5K9rJnn8mPAip7Xkrnn82okZB8iQG7NPhdUyRymzH6MjPM5wM32PWdl/tNaWDuPTisRUvSeyohisyA23uMs4yOsW8vlWpTIRkFtDUUptp2EBd0Pnikk7g+RLkmxoXXQKrHEfdmN2D/r0MzpcfWsuAqyh1NBzjMh/DiqojHMYoZMykUa+aUQg+y1DK/teocAOWVaJw29rYfSl1eNQikgWUYvKek5SUHxaoi8fd6wamuGMbKbJjQFZQxGy3P7ux9vefu0xlnDk83ANx4abFGfOzf9IuOLnkuOBbd/Hvg/l1Lu1FenKw78cMcgF+Ec/P0f3HE3BJkoKsNuiITYc9JafuPxmt97smHVOEzvoUg0cVGFQObmMDGFRCmZxhruu8gwDnMEpuPdiyXnjePl3hNSxkexE0gBoGL0mSc3A0NKuEoTolDwl5VMEmaGKTrFPPnNvv2S8EoxeZF8G2PRSNwt0dNaw1AS2yEzJQS8FUfeOm95uGpnsFnivhdZpVEz7FVDFyUxKAGrKpBLRlvF7WEilcK7Zy033URtNO9fLmeoHKwXFc7Ay5CIOaOtgDH7cSLGwsXCYLVhSJmHK4kgXlaGzzY9vdLElFBKEVLGovCpsGzczDAwlBy4XFX4kHl+P7FeGKxRfPvRihf3HbeDFDwoUiluHCysoygFKvLeuQBP7w49MWv+8rtrpqT56HpPPwmoOgSRdA5zeoFBihOHKTF5URtYZyAVxuD5B5/e8XBV4X2mAM82PblIUfB2K15wqzUZseOtF47tkFk0krJhssI6x2k7kdAkH/FpToHqAo+KeGCNymzGiNKa3gtoNGUBsRkn90k3ZsYZ5hlmr60zsFw4zhuNrxW6F2mt04q7UWDAG51os8Jozd0hzNBw6IPIjWMsHELkvvdcriqBvQOXTnPbT1gUtbVcVJbrw4BWBa01OWVRXSAH7X4+8NgEq0rgvUclRWWhrRW9L9ST5xuPltzsBjnczck7R+tOQibhVSWWxD4LT+agC22VySHLBiDCwcN+en2Yr5Gf6QM89QlHIgALNVvgEAXXz1MAerOQpJFJ8qcBUn+eYZEFxBjYDNNXJp65lPI7Sql/Gfh/Ieej/1Qp5fpXfFk/14gUVo2RKPCYOPLTShGZuTMyL4QIrXUMOpPHJIDqNyxqIPe3L683XT9rKGZVnuXVIdQ5w6o1GG2wBR6etYwxcxgiZYDTRrMZI1YVxpC5GzxGK/aDFI2XlWK9qPBTxJnCMBasA/WGIgpz/N00j9YrXuxGtmOSNI9GsRsmfFIsUsYaxU0fiMBNZC7aJs6WlhBh3TjeOq8xamYtpEKKsB0im5CJnSfELOrMWDhbOIzXHHzi2Wbi8anm8UnNwhlu9xPbPqAtOOt4UGdebEZUKWhtWdaaEAtGaT657xhDoR+TvB5GobThbKnYjRmlFDkLbynkI6BUUVJBN5J4uveZ718fiFkStJ7e9Ywh4XTBVpYwBlRx5JTY9oWLpePZdkSbwvnS8dtvnfN8O9FNgWVjefd8xRAjOWVOm4rTpcjNP77t8CkL7FYnKldhrKELGVdbTBIe2xQjVWU5XUia57oxhFiIWZRJo08S2lAUGcXu4PnWW0t2ZA6jNKwWTnG6VOhcUGjGmLloHeva8cn9wHY/cZiydLST4nLtePtkwdmsRI054bNYKguIZUNJ1HCYY4ScVfRTFGXOFLgfIgun+OB8RR+ER+VjZIqZkI4dfThpLboU7oaIIjP4zNo5vCmctfJ7+aSxGl4eApWWzUqDwhpLUws0tz1zrEvkYrmUfZGFuylL6lvl+PpFyx+/EDae0YbTtnDbKS6WomA4WimWs72zzKfA214SrxpbqLRi9IW7/fTqQJWyRGPnEHlrXXHwErahjawl+Y1nOvDD4Qq/SOR0zhBipqTIxUnNNy/XUoT+kkCpX8L4N5CX5X85f/xfmj/3X/2VXdHPOfQcFPBiOzLF+IqB9NMsIlorzhaOP3y6JWUpeH/j4ZJ3zxb4lHm+HXhy17PtA6tZmW4VhKXj/Yctv//plpgC297L/Idi1RpC1OzGwDtnLavaoS386cuOXGDVWkaf+P0nwlR9dFLxyW3PdoqctxqtFfuDFKPeOW35wU2P1pmFdSyqTNdHcVw4w1lrySHz8dWBtlLSgJ8Cu94TQ6b3r5UavY+cLWumIIWLlIswfZhtmhluDsJ+A7hYtywqy23f4ZHn9jaIwfrRScPzuwPbIZJyoQK2c5lxiscmKZxWEHziKheslnCgyUd8htPWcr6q6KdADHKGc0qi4TeHxMHKPvTRWc1+HNn1kvhmjTDYDlPms7uB85OWD04abvYjT28GVq2lcRUGw34OeDmOkGdrOq+t4m+OauayJaVIMVGKEjVwBVMo7MZI5yPHGpnPohCmiAK6zJZ3rV8XpM0sjy8ACrxPXO1HyJn7JBb1ohVKFfYTLJzsK52C5RJWTjSSWSmcTpzUmkYrihLW0jgrb457IKMF0h2BYfT0xtBP+ZVNsx8994fyqlnlkf330db/6zgq5HzxYN2gdWY7eLqjVU0wkq+u/bj/r5HzRp3lnvzkToQaCwf3/vXXVnZOyJvgZAFKW4HfK+Z0VXl9VIF+irRWE1KegeSGti48vR9Z1ZoP3jnhdNez6wONgbqqmGLmajtwuXD8Bz84ZzsEPr7p+OBiwdtn7Z9/Ctsb499RSv0JUnj7ryulHvKzU61/rcaxAyAgUM/3Xuz55F4SC/qQsFNEK803Lk44XTpSKXzzcoGxltaKaqmxcNcHrrYjuUi6yMpJBL01BV/ULFc0XKwb7nvPGKWCTpFkMucsPgcerB0+BpyGVht0a9nv4ivo1ulCNuALKw/u+cIxRmHr+JSonEFSTgoe2VRaLWkMIb5+cyZkc7TpA1YZdmMkpYIiC+1fz+lS4Uc2OBF6lWgwPNtOvH1SsawlZWy9cFyuaj5VB75/3QlYdRIx4mFKrGrNyymgFNTRg3KsnNgjrvYjQy4cQmLMRQ5pSmxoRUOKBaM1o/csayepDpXwQFKSVAYLfHbboclECl87XfDiMJET3JbAYQSnPKumZllBFxKpjExJ7ClNVfP+uuZ0afibf3RNUdBUlpcbzzhPwKeVqFlqowhRvOJ3e8+yFZ7DNCV2xs+2BcMQCyZnYlEYq5nGQEBJBOc4cbrM+FBwRrNuas5by27yGC3Ft5Q1TkVCAJsTSldUBrqYud6N5CQyxVTmdIQshY/KiY2vdnNEuJdq+PnK8u0HJ+ynyMFHelvR6EIpUNtAbSDFjEcUb4MXpktjLaYUhpS5m0T6r5VYDReNANJDTNztC0onFi5xpqGxikMAh6JoRTfNBb0i3fY0W/eGCdCQtfisrYHTRUWlFUZZYkzczakSInWWxXHhJA7zqBSqtPzOKcs9cztGOXDPUPmjVYg3noMSeKVqOnaKhgALYNXIAeFoLYr89ELSUclxtCUc//wii+IXscBFYIiSIJTST7uKX5+hlPp3+OGXawFsgf+tUopSyn/mV3NlP/+IMfPxdc/dYWI3JqYAo3/V6GRRA1nNHZ9AUa/TRH7a+/p5ijbzxv8vzOoYNcM0nWYYI+MEWkesNuzDwPnS8f7lAnXXMfrMSS1KjnHKGFewWnPi4HaEw1CIyVM7w6J2OBsZp0Q2sik9qy1NJZ3azZDYDV7kzhlyztx3SZ6JDBOJwUsR4GQBV0HUTFWCVRIg5OOzBWeNnWNsozzPg6QsVgb2XSCMAW00C6eZvBQnhiDK3KebgQ/Oaw4hoZXi4ANDnxl94tGqkqaHMawbRZybHSFFfFIYY7jvJbntatcRCmyTRDiPPlLPUOYUM2OQA8nZ0vL1B0t2fWLbeax2LGrHzX6km8S27ZOi94FSYPSFl/uJ2onauK1EKXtWV/ikqJ0oae77RNsE1rXhYtXw1nnDnzzf89FthzaWhcmcLqQpsmwtj9ctz7ejcEYKrOvI1X6irSyhFE5bURsYLTYYZROb3nPwkjDUWM29T3x6O9DUZrY5Z9AWk8Wm8vXLhcT+9pHPtgNtpeliYl1bVrWlsYoxK1YLwzsXLd94tOK7L/c8v+uxFhqTGadEUxsMioLmMAU+u+s4jJnKad6/aNF65Go78mE8MMxevd4naZIlqK2wW0IUhfQ7JxW1dVwdBhKKt09rHq8t33nek1JCV5bRBzazGuibj1ZMSdbSKWZOaznEHabAdgowzspsZdnsR15YTa0L2hgqY9AGqilwiBlt5FmOc6fhqNTN8z1vnaxZzhXOlkYS8xSctcJaPPhAjnA/JlLJ7MaELq+5IWWeF2p+uLnwpsX152W8KiV7wmf3E3/w6T3/9NcveXS6+CpZnf+pUspfeePjv62U+r1f2dX8GUfjDB9cLL5QClvOhU0f+NrlQpRIOfPkbmD0kee7UQJ2gshGPrnrBdw+J5o9ve/Z9ROf3A/EVIRzajUfvuyEwaQUU8g0tvDO2YLBZ24OIx+97NAzaH3fJz67G+imJM3wqWB05n6MpJuBb1wueHxSkXJm04t6ccqJEAqbwbMdPYNPVFrx+KSmHwMxFla148ZPNDWvwh46D4s6sq4NFEsXJOAnzOrcLsgeNc3K12EYSLHGaY3VmkXthI0aIrf7gSFGcSrAnDgoKpY4L7gJObgrDSZm0FmYaVozhiRgcadEfTNFKWLFOU0LqOa0sU+u9+z72W4G9FOZrUeS3jaNns9u5YdOMWNCJqYBpYXRNiWxk0ZeN42OFq0fHcOsyHl279Gz6n1ZQVWJnfgwCgcNXs8VY5R5pK5kLxLLrDD1r23w8/aamGA/BS6spmj5nHUG5+WMEYDdnBTrNFTJYFvHbe9RWcIqauc4JDBGKuY6CxtuTLKH3k6R86XwRCcfqKyb38PC3SHQ+/Jj6mp4fc58kwN5/D1/0d2u5Rcrzqv5X3eHUc4WZYaTO9nrjG/M7bOZ4tXPU+U1LiUBYVarj2m2JmdRjybkc0sj7K7ja9AaeV8MsOsKvkpUqfDumSQatlXN7UHwLOcLy81hIkRRPGhTOKkdtRXcTu0MjyrHaWN556z90hSqX6iAVEr57yul/nVgV0pJSqkO+M9+KVf0JY1jhOY/+PSewUc+vRN2zQ9uD7xz0qKUZl0ZPrzp+Jpq+eS6Z/SZJQI1a6wQ+u8OnrtuJCMdrYxi33sBPhd4sK4pudCPnpwLjYGztuI6DqBEqthPie8fRkYPixbZUGslh+JKigmV1SxriVVuY+ZiXbPto8TMWs04CVuABM5qILIbCmN8DRhOzLYaD/sScTrx8LQhJuhDwA9REmdq+Hjz+rGrkGr3QoucUSvNNx4u6abC5brhrDU8ve85TGmGE0uCy1FdsnBiuSil0E0JYzRKSQLEJzcDlVPc7ke2h0goMoEVxB/qKpFe+qQwc/xgW9u5aCcFhMHLYrIdAm+ta9armotkebLxVFYsGVlpeu8lNSElDkE2rc4afM788bMd7523fP2i5fYwcNdFqnlRmxBbVaEwaFHrnLWWhEgPfShoHbnvEqVIKcEYqborYBgTQxBpbM4whIAPCW1F7TOmQu4GYtI8WFmS0pgYyEVzVkvMZoiFfY6snaY4OARJzLjtvbwOWiajYSwCAdVgjeGkke65LYrvXW1Z1XIgWp9rgWPve1Ix+JCJqTAFKVpqrSR9Rss0PoYkEtkZGBcK7IaRKYqEUyvpQMQC4+RJRbGsJE68RgqbteMV68PPaoWMdHp9hsGL4m3fR1ZtRUme7SDpbJWWDcJxQdTz5iTGeYNfZMI9Qq8DUpBaO03loNvkV8WdNxewI5O6IJHiVkFTIwfaeuY3/YwVyM3X5PQcdzofOI7JEp9XIPoiRaY1kkaXS8GZr8Sh4H/6q76AX8bIufBiN1I7xe1+IiS5cwrSPdPAtoNAeTXHGvP5YFz4/I2R+pGvLUo2sIepEIf0KvnDGGhtYr2oUEXx7H5iSorbzjMl4XgVfdzEF6JSLGv5fGM0lTNcnNT0vZLCSIZaS2DABw8WfHoz4KOA/letRQO11eSiiFOiqeSw7PMc4ztv/o+bqMELg+56N+C9QxmDmhsXIYvdIGMISMJNToVMAZUkkceJwuYwZp5tR4qyNJXmej9JN70W0L/Wek76cUza02KFnlEKayew1FKi2EDzMdElsZ8UPqg57UajkqSCqaJEDVSDHwtni4r9ENkNUewTylBKkEI6ECtJlMmlMPjAfkrc7Sfa2szrtUIXWDhNaxSVUkwxM46RkBK//XjN/sRz03ue3w+ct46z2vDh9UA3ThwmS20UB59AaU4XFeM8T2995uHKsRsjy0pT0EzTBFpROcvlUngIIUgTp+RCP0SwiserVubwPnC+cKwbx8vtyLYLnCwcWUHWmt96vOaf/dYlldMc+sCfvtjjnGG7iziraWrFwlnOFzW1M4Qc0cqAFl7D803hMEU52JTElAIhSRKQMgKpra0mFUVKYqnZDLI3mWLhtBWp/fde9tz3wp/yRd6rxojSSpoohfNGC7DWR3qfuVhWktw5yPe1RiSld+OeVW344GxF2xpebie2XeZipVksHCEHfBKVkVaKIUvXNyKHXQ24BN0oa2JMcr8ffKbMDaeUIpuhSANQy8b6Tev1m3NBhRwsjJE15OYLtGKPf88ja5/VcL5uUErz//vojv/yP3P6pXSYv6SRlFLfKqV8CKCU+iY/fx3t12Jorb6Q6usVA8naV3+vsYrvPN/yvesOq2QeSrnwg5uODy5EMfDJbc+LbT+/5xpK4bYbeLoR5dA3Hq5orObFrscaNRddRrSSAJhFbfn+tGdZZ5QykoLVi3OidoZ1DZDZjAOqaP7Jr1+wnxLfuzpwtfd4H3BWcTsFUi6krBhCQiF/hpQ4TIXKKha1QuWMzVBrxVtnSx7ExPdvdmy71+cRg6xTTSXP0mGCExNoXIVPhcPk8dliEVTE6Mur9MTjWpvLD6vFvdSNME4O8lMseJ/kcF7gB37EKvk6q39Y/eCRb3R7kOcyR1FYHr8mASsNXchgpIhdW4XVGW00efRoI1Dp8Q2w8lF5+BPvB2QPn2eLW0aAz+eqsKwMnUqY8np9Hefft65EVZyKQoXXatCMQPqZv9eYIAxQucz50jHEyGY/Mab0Y8y1Uwdt5Rhi5tFJTW002ynQjYkcMwtrcY0UKUNKtEoseDHC8+2AUoqFsXhE9XzfJQqZGH+2In85p6QdCyeK17DuP8v4RWfAgOBjjvt4hezH1k7T5/xD54kf/XNMcOLkzJSznCFfOXyQz+UiNvcY4WrwKCtN75x5xc+ag0aJHhoym36krSyrSrMbEmPoGEPNGCLaFEKK5GxAa1KR4vGz7YDThrN2/aWy8T63gKSU+k+UUv62Uuqvv/G5N7/k3/6yLuzLGM5qHq9qnu8zD0+qWW438nw7itVmUbGqLNteIM1//GzkD57e04fMB2dLhpJ4fjfyYFVxsXR89/mBwzRijSZkMNZilKLPhefbUVKinOGu99z1Aa0kScyaOWYR2PVyA5VSeLR2rFvDdowchsCy1kxRQHClQD95tNYsKtmgVyazGyVVLimZQI8TVub1jesz2CyeVy1VLBqt8U4xxJlJwGzzmf9uF6CyhW0XOF02aDS1KRgKv/9ky9Ve+AvDFF/J0ndBFoTrfRbPbqVYzuqTGDMvhwmnFbtJXoe6Nrg5lnnwkoKitUJpjUqJKSlqBdv9xHaUCv0U1QyqVWgdeblXXB8m+piIIXK+FPilJhOzonJGuoIGTlc1F6uaT246Xu5G2trw9vmCu94TSuBsWdNWgauDTITNHGNZtZq2NqQkCisULGsnyqYUKRN88HBNreDq4KHM8NOSqYymUYZhSpw6iY2PY8CXwllraeuK7TARombwYndMBbwPnLY1trWcrWr66wPaKE5bSYjwsXC5dLw8eIKHbGBZF7opU1TGLWrGMRByQCnFW6cVnU84bQWAbQq7KVCSdFmWlWXpZipeyux7iW09jpTFBnLaKO5zRmthMxkjXA6nC4vaEIMkJK1aSVzr5kQzO9+UzZwUsbQKpwur1tE6Q86Z3TTDR/NrGKBCng+npKL/JoQovLHKHDtahyFzoqQ4NMTX9/OxCABzfKiRhXiKhV0PqUr4ueNw/LZHafBxETxuVgKzn1lLRywXkRJbZLPyk3g3X7S7YgHXwmljuVzVnC+rX/uDQSnl/wOglFoCQyklK6X+A8BvAf/ur/Tifo6RSpEkxAynS8sYHIcxMvjXG4c3D4KB15/40ff3zS5V5qcXFiPQ8tpT3/vXtkuFpC2FIt2vnMF1I7EWFt0QInqWPqv5eegDLKpMVnPRVgE5o3XhrWXFxz6+klM/XDVcHzzP7keWreaDB6fcHkYp6iuFRjPlIAk0Wrh20xQoQDe8/p2clrV17RQK4cq5HGmsYgqRwadXqSUFARY3lSYnYXxtp8TFSU0uipNGoLF7nyhKsagdKUamUASsT8EajVGZGAoTkXNr2U6Z+66XjTWZRVXJn0URU2TRSAHKadDGctZUPN0MdCFxtZvQBS5XFTFGlAGKKFy6aXoFH6+tojKGXciMwbOsF4w+om2hHwX6f9Y2PDqtebBqOITEb75zws3ec7Of+MOnO85ax0lT8RfeOuFqNzEl+Ph2YAxJ0lQAnwshFs4ay5giH5y0xOI486J0DkEKHpoi60kqKJVYNRUGRYyaRSV/dzt6VIHTppL3q2SGmAn9yHYIDN4zxsTj05alcygUf/hkx8f3ez67G9kP8n5PKdL1gdqIjdknYRPFJOrNWivufKaLI94nzhYVpSiMdgzBk6LckwsnG12VEocp0WjNuw8XhKwY9wNTKNzEkf0UBEwcEoWA1ZqLRoI49oNnPyWMVfzHf/MRFPi9j+85jAGtytyAkoOJBpZamhdXh4E2Vmz7iLIzKyRKQXDdCLtriEEs1lqaC0cl7DQf5ur549HLurAyUtwcQqKb1RFVhkUlLMYf7UUc+YQlSeBFVJ9/0Fzwei1Ey/duanj/YkFtDQ9WFauFpXx5Z4QvY/x3gb+jlPoImea+BvwLv9pL+nLHmwwknzJP73o+vunop4DTmjFGShHFesqZ7zzfcdpWLJ3gILSSJNxtL89jZeBsWVGA5/uJfozc7D3jnAS5mlM8l5M0ib93P1BXmstlJVzXSdhkBcvCGjKWGDx//5MNy8qKJe+k5naX2ftI7xONMzhriBk23SR2TS3rT4yFxhRMpXFKuo7Xu4l98IwSTPxqTTzez42WfWuIcL3LnC4Ci8qwHwuHbfcqwQolzY5xtpe+qfY+FqSO33fm1/+Q8k8p2XNaK3OVT+UnylQmZJ2NvG40HsH3zkha76NlxRASo89cH8SWK/tJxaq1oCS+Paef/kxzvL4iP7NGmuZjkga8UelVSlkssLCCF1lVcLGwjD4yzOEqF0vLVIkDZdNLI7s2ShoAU6KpFGiFVsLyPbwxJ+n5OmKCdSN2qbtDwCoBYxcFjROVrQEqa+gG+R7Hgsh+KjQUSq1QJZONZvAZa+Xe+LyOaULmaObXoPAaWXHc//y8haRfFKKWef2ezCJUyJBSptby/Wv1mmv5xnEEgG6cuVTztZT5d3FKnBhnC8Ndl17ZN8mi5rK8ZiUd73urZG+1HxP+pkerBSethcIrhbT8bM313jP4zHsXhkVtybmwXn755NSf9RP+OeBvA3/tJ/y/wlesgGSUdMFUgYtFTT923HcTlVactAJevOkDT+8GbjvJ/6ucYwwTt72HnBl85HafSFHqxovK8vZZy0c3PRTFYUy0taUPicfrlhAzhz6ynwn0Pr+e3BazZ7i2chC9WNeElLDKoOeIRJ8KYQzcdYG2EpXSsjWkQ2RC4WyhUlK9PE56xwniWPHXGs5bw6oxjCExxMy2C4RZFfJKgsdryV2lmIs9iczEd14ULpcCa6wrxRQDSsmhIsyTZTVvsiyznDSLuSfEWQKpFdZZRi9JeEdLUkqwbKV2sWoc3eTJWTOOmeSkEKDVrD6KYsMqsTBZTTeOLGor388LeNMq8VkvDFRWc1Zr9kGRU2bfT1itOV9aKJmU5cBhFThTMMZyGjwhSwFpTEAppATvni95ct+xcIqsDSdGIJzowhQSl6c1Cc2UElM/USnFqnX4oOh8oh8L1kgXvTWKR6ctj1YVmz6yXsL9kDkMc2elgjwELk8aLJrTxvJiO73aVFsLxRgaZyhFoIJTkom7RNj3gZikS7odItt+4t2zltppLpRlN2TOG8UYIzEk7rpAbyW9x1lNW4ltU2vFboyoIoyo3udXaiI9T58hFoIG9gOLxuKD3FH1bDtj7rLY+RBJkQIigLOFpStYa7AqkXUUGOP8nFgtxZ5xXvgW1ZwkVaQ4ZWbb2rq2DD6yD6BH2SikodCnHy/cGGTxO/jCfKls5zjVpZMDvSpyT7bW8nQbf2xh8shm3s/3/PGaFD9cEGB+zq2RAuvnDTX/fKsVPsGqcnzzcvWVSdcB/n3gP6qUOgf+FvD3gL8B/Bd/pVf1BYdREh3e1hZVtDB1ZgD9j47ED28cfvQeS0iRsa6kKPR5b/3xXjlCFg2vv34sr2XZqcB9V9j1UWT2SRRL2oi03CaRWg9eupEG+WZjhqELfPfFjuu9JyWx5txP8nBalWhsxX4I1M4RpsAYMyixS3XJc9dPhCL3sc/SJauRZ7p1svY8XFTEoqhqw8pZKcwYQ11LZ/yo4vEGLIYHK0PtDErJ/JqVzCVdKNzM63JRwoaIJbNqrBR4szCCGufQVhFnW+2RwRZ8ImjhG6GFD9g6x36KZC1FrWXlQCnWjcWg6CZPFxIv9pMcOJIUm4qqOF0UThDujJstZP0U+PSmp20N68qxj4GcFZnEdoBVnWi0ALSf3e05DIH1HFt5uxv58GqP95GLM8sYNVufiD5RO1FPxaKkcDMmnjFw1jpKUdx0YlH3yeOLFJBKgTFkMhMPFxXFajZjoPOBUODUKe76CV0KYxawa+8jt7uJomBZG+47z0lriSny8d3IEERBfPCRbggYK8qgqjJUztDWlspoNInDFNkNgZwzIRd6X1BqoijN0hkqo2kbUbApVVhXBqcr7tTAFOHpZiSkNMNYM32IbPpC66QCNARobKYycvDNKB6uGgzw+59ueOe04e3zlhc7ePt8QdkM7MdMTrIBr500XQYfWDeWi7ZiCAOHMbKwBqcl3OObjxZ8fNdxGCaUhs38EFpkPzQUeS5bO1urE6yXGqM0XZ9eHTYz8gz+JCHrsbGXECWfRg4Xuvzkbn1//Pkzn8kZUQC/3I88WFdMMXEYIuqLdCd+TUYp5W8ppX4D+E1kGv2TUsovAx/4azuOzKQfXB/4o2e72e4YqCtNow2hy4wp8XLrCUEYd0YrNp3HakVIUiC+OcjHxRqc1uyHyLbzXK5qKJKC9mI7oVXD1kfuDrLfn3Li1BrOlzWrxjGGTGUN332xAwWjjyzqilwSq9ayyoUxJjip6G8yhizW3yJA7DTbcWIRRbmuDYcpoWLGGBhnZqxPEpKjzesAh6PyZd46c7KyYtUOie0gQQzDJOtK7eRn7IfXBahmlpY7BdsoyryjWkgjTZexzOvfvEgbJUUSpRQ+ph9au98cPykhUSs5h7110vBoXfPdFwc2h0DRcDIXXnwqZJ9o5FghzKLy0wsgljkbYb7EMBemfYYwvlZXGWA/u0qmCDeDWNoLcNKIE6N2EIfCenZv2NqikXNu7eyc1JhfKYaP41j86CJcbXuGOYRnWQknWGy9CYcBqxn8xNVe/m5Rcg0hipJSxSSWwiCvoFWfHxzy5uvtgHUtxSRjpFi4mc9Bn1dc/zLHcTKqmG2WXrh9qxamOdfilUKJ13D0AK+KZtX8/14VxYoosd3sVtl0wr2Vop8olo6NScvMz4xwutBcrB22FO76SF1BCHkORzHUTrNA8XjleLSqeLhuUUphtebm4HnPR9bNm7lxv7zxuQWkUsq/ppTSwL9bSvk3v5Qr+HMcWisuFhW/84M7rg8Dz+5HSRBRhZPW0cVCTjBEUQDlUhhC5HTRUDvF9W5gSpGSoJ8C970Am08XgXWtJRUAgIxGc9IYProZmXKYoYuvJxSDTICxyGG1ZLjdS3KYMxmjFNMkEmmQCUZ5sfa01uLrQlGR04XmrpswJhOK+HmPlVPHzMM5qXiwNDRVxQ+utmwHIIniJ0Z50F9JBzOzRUBkjTpkUkn4KWDWFYOPVErLhDabno8P0pjlhgrI75MQeWTMctqZAjgVybEwBenuHWfxUuSB2fcBbUWxgxIlVJh9xekghSmyXPvkJWHL6ciyseyHKB0+NU/iFEpK3HsYUyZGw+Azq1ZzsWj49PpAUppNn0Ernm/FjzzN3Xw5xMP/n7w/jdltXfe8oN/djeZp3mY2q9vd2WdTp+pUnULaBCLxkyYoQowG+y+CZTQIEmNURGP0AyoxRkRNJSIYCSYCYpCYKBUVDARKClJ0xeHss8/uVjPbt3m6Mcbd+uG6x/s8891zrm7PddZap+5kZa63e57xjOa6r+t//f//S2vNZghYO9IYxZgNw+RZOGGMLTvLZeewSmNM4XHbEFLieu8JKdAYxbqVDnApkc4oHi4tZ53l5X7C6YyfMtEfA1JjFKkUBp/42bhj9IlYCpetY/RCJT0cIr1V7LwAK+ddAxqeXHtKNV7PRboaL0hgBnSVDkQkwOSiRKMbZDrAuiscfJRutlb4KLLJgy/4qQI6rppXexk5vVoo0e2OYrqdkoCiGqHppnoPawTYs8jm2rSgSmSKmtYVtCns9wIYJiQAXy41BcV2Ejry5GXzMkquTWPEi2DjI84olhQWHcQg8p02yf3dzee1FYoyRu59VQvgUM3ThyCb2cOVxVpDipmuTl443cwy1cOpft0YeZ/pXsagkHPR2COA9CZ5U0sd7+4L05T44bsrfvjO+hvPQDpZqpRyUEr9ncA/XEr5B5VSf/HrPqjPu7RWfHDe0xjNw1XHEALbQSY0zt2606Tz02o2YfVVU/7P+f6zJ8PMvIMjnXt+74CAt7Nhty31fq4d1ncWjqsp4A81jylyb04Jnmw8MRzfI+aE0fDRzcTaF3xIPFo3dTKkjB++2Xs2U2I3SHJZkOfjdpJ7OgPLTsCE7z1a82I3cQiFl8FjZgDfKrRu+Gk8yJS6BDlK8qSN5oeXC14OkZwCmyy+H1YpYkz0naM1ChM1rTUMMfHOssVYLTTxmPE6cqYKh0nQtOIMwxjp2wZNQmvDdgw8WDd4n9hMmWdJsnBVFPsYsc4whEgJMgFnjn9dLjRGcfCZQEYVTaclDR9CxDWa7ei5OQQMhRAb3j1v+fHTnTSJXu6ZYubJ7QAokRoW2PvIedcSi2LwmWlKlAQYL6ye1jKEzG4qDDHycuu5XDfsxwoweU+jHcHIGGqNIieFz5qUAjkXHq4atmMkK8WLrUxsCSmj1p0AelkmiZ4vWnLOjCFzfQhc9g2dy1zvJ0YfUToTvdAsV43jnbOGi67B58xmgP3gOYSM1oqV0ziFSKTJDFNFSVCkrLBO2BRto3mgWjZTIoTI4AuaRDQCwHmAOjGvJOg7UEozTpnLdcO6M3x4NfLJzcDT2wNnreXjrecweDLlLp/JWSa85iKJ/ycMhDodJ2W4jYnzHrpG8cvrgae3E6nKoufnViH7ja7EhZCOzYKbXaaQOdR9zZ10p0H2sHASK2Ymkcvip3Y7yX7WGjBZBkPcXwkpIgGWRRomhymzd4mUC997sODl3rOqI5u/6Usp9XcB/0Qp5d+qX18qpf7OUsr/9jP+9Fuzci6/4o3UGI2tHkKLxjD4xHaMXPSGs4UlbCMpJy6Xjt0UKEWi/naKYlhsNQ+WkltqFC/2E7uDlxpCKZQCZwxjzNxOgdtD4HYILJzlR++u+PB6ZDMNrBrNw1XPz6627ELkDEvjROVANsL6U/Du+YLtsw3OKXptZHADtRZRks+sGsUQC3GUaWVWi/VDUmL9MNahLqvGkKIYTc8gxhgELCg5SSM6i31ArGDKJkCfJIccqV40wFmrudrnO9kTWgyM5/1RK2GJlCzHmVV91sfMutN3IO6bnArmnKxTcL6Q3K8ARhV+8XJgComoZN/dT8JUbRvFMAgwFWpBZOsx3AdAqo3n3R4/yEdgUX2iZmnbzIY5red0EVA8ZIkzmyHjk5AWSIkhF9QYeXfZ8fBBx1lv6Z1h3Vl+9mwjsenkgGYyw2asx1ubxCnLdfAetlVKbLXkz4dJatZG1ZoticS3UQKyjKmOute/Gv9etwLim9W1FYiJR3+kmZBwKrv7w1weaQC3Dn74cMHTnceHyJSPx/OmY/LIkB7q/bjq5dkyynC5dCI9vZX9HiP1zMYfX9cge0NjxFvqagyUDDnJgBAq4LduHVqJMskag7OaZePYT5GLheP5dhJW4ddhol3lCP914FsPIOVcuBkCH5x3OC2G2ttD4r3LjkdnLbf7yKIxvNx6nu23TFNEKYVu5ULlCvZsKkXRI7KxX16NtZC1NNaxai05ZfY+sRsmxkkeRq2EpTMXBEOSxGQ/gXPwYhtZtQnXGNad5qNrMW+eUeoCFJUIKfAn3l1x8ImDT0QfWVjF1ZAwrRTZM3LfWaGXXw8Fv9mSs6J1wsyY9bpzQeuRgLBEjmcKgbNlR4iJQyz8+x9vcU6zbi3aWdqQcSYJA+kEJGjreEIFXO0jvcu41rF0Mo4+pnw3yWTMsLICVjVWAKRpTAz5GEROA32T6wZh6vkrsIswHeS3tIG1g6wthynydCMmBlYBWVhgveuZQuSnVztyVpJ4Fc1NlTCddwIkHKo8qcTEorXEOiUnTiJr2U+TjEBtHdeHwIvsWS8a8YWaEvsp0TfCJMlKsR08PooJYlaJIQ3EKI4qt0Pt8NcnMhdIFKYknlmPz3qGEMVbq4gB+i4ETKxUR6MIJaNTNbrzcn4yUmQuDGwGuVYz4qcQaZ9DWAExiozn8VmLMxalMjEZ+gY2k2zyCuh7hdXlzpyvVbDx4gtjK+Nhqh3aebMOVCkO0kUtShIIHxCvqkZ+P5yAMgoYp4z3UjQvTZURJelCfe9BR1GG3TCi0MQsqLwuhmLAlkTWR+C2AHmC9UIox74p3FbTxCGf6OkDPN9FzvpCaxyPlpl0KwlSrptjvLtGcryDf33HpSBSoouloR8SQznxJuM4+Wc+vtbCo3XDX/Mbl5gqafkWLaWU+hsRxtHfWb/31bj3fUWrbQy/8WjJ7z/bsh0alo1i7+XOuH99G44Sxzk+55OfjVE6ip/X1PGUOXoKLM4A/dxBHE5YdXMuGLMUry/3QXzHkLgwS9lQMr1FIbEzFtknrBKW1BgSmsx2SISSZGx0SmzHxFi1/FOqnzdLkms0PFw4OqdwxpByYDNFYiyMIYLODGNh0oZEENmrhvXC0hvLZghiUL1KPF62/PImYJXlw6sBrSUhzbHw4hBAiUTgvWWHUZqcMw/PWlKGZ5sD1/vAFGU4xSYpSmN4sDRkHKUkGU9/3vHLlwMXKwhTZBsCIRYernu2PjFOhaIQSVMKLBuN1Yaoi0gVCtXAVnGx6nA2sWgUn9xOjKHInjd50o3Iy84XLS+3iTEEburU095BYxVnreG8M+ynyG704rtmhK1mFCitiEmjdOAwFRpreb7xPOwN2lqaheGXt56+MSy1JKODjzxcGKag2KgssguVKTmhlEzze75NwgrIAu4pZaBkMoWSM1MI/GIIbEPiejNyO0QBT4z4mowhsZsylIhPifOFY4qOEAM+K6wxBB9IGZYdhDn+lsS6syycpnHzVLmOl/sdV/vEIUmynYoUfRRhEYxewP9H654fvbvmd59sCTHzk+ejNNe0ZrP37L0Y55Zo+HAjT9JceBwmiavrhYxbj0nu/zm32nvwIQlLtoJHp3E3IHnevGYj1YI83+3JczuzDmb7gPsFhtJHrxJdC9OQxSdQWymEE6/GjNO/91mkceul5uGqobGWMWammL5NU9j+TCnlfzN/UUq5Vkr9GY5T2b5V6z5YdJgiH98OqALGaN477+icIZWC0opF9cp8vG4ZfWQ7BvZT5MdPtmSlWDjDqmsE7AV6p/nh4zXffbjk5Xbix0+2LDrDz1/usEaUBRTwWUzuU4GDT6waRSpisPKTp3uZoGgKISk6p+ms5bceLXmx99wcZDDAdx92bMfIECI+ZJyxXPYtV4ehjriX57NxIte5GQpNRXZSkXsz5VILX1i5aiAcElt/lGwbJTniNsO0KTxcCnP+EOUZmu/5/QmoOu+Lz/YZhxxDyZJzKg3bUZ47X/cnXZGalMG0kj92VgtI4fNr9+WWKkHKAvRPVa71aO1YLVqGcWJMmRQgKVFCaA2uFmmjP4Id8349cz/u9mqOMWP2NbPIQJyFK1VaK3nhHHYUsu9Ovn62u4JQfNnWrSZnzcGLefXtOPH4siXnwvcfLugaw0+f7wklvdLABNlnUz6xZihF6ot4jHO6yLVfOckZQhFGJhwnzY1F8uD5mFOWn62c5PqfxiTKReLuohUw39cGsM/HXHn+9w97hQxpgt0U6J0mN0dSw/17SPEqOOmL7PlOwVnfonqRTFutWXWKtU/ElOlay67KU2dFQ2ukHrxYirXIZh8x2rDQBms0FwtLU60F3rvouFy1nHeO6yGSSibFwqPVCuAr2xs+r0juzyml/lvA/xnYz98spVy99SP6CtfscdE6gzGKrmnIJfJs6xm8JL1nC8fkE3/s8ZIntyO70TP6hNXiO7FoLb3LXA8ZW+U4JUMx0jVc945l75hC4pObA5upEIIEiTloOF1HOCI3WAs8WFp8FCPSzml2Q7gLnIrK7EnCBPn46oDTRrqtKeGVwqAxWuRbbS8JdojQOcWUYbcfSRrOnGa8Nxb8NJisjTzEPil8LlgbWPeWkBNFFVQpvNxPTD5x3hl6p5lCfsUnxhg4b0UCgioopQkxczNNLBtNiMfP1DVwvnKUmGVs/Hjsut+nf87YhzOw6gx9kqln21GAtpRlIkEwmgdVrtdZxX4Sj6jtKA/yZhxo7ESoZqgpB9p5ktlMT6ynKClIAXSJpLZwbjSNUfzw8YqX25HLlaNRcLG0bH3hZj9w8NVQfdWwbDQxabbTSKmIQ1SwnyIrpznrLdf7KN0SczTNi7lwsXIYBee9Yzd49iGwH4XSoLQEmZRh0TrOWo2zllIiZ63j+XYgDbIJKi1soSnVoGQkqN3s5c1UI1+PRVhXqRSIge3gMVaTYmFtFcHKxmK1JmqZzpSBzVDYhzrWs1F0iCGktbIpDBz9tWa6bkI2wnUDygpok+smfDqOdExy/K2VTXW+/u9f9Pzmu2c8306kXAh54vYAFPEZKKqIndN8Pud7E3mvIZS7UcvDPRPTKcOlUzht0Crhg7CaNsPx+sxdJDhq7uef3V9Dhpc7+cmydqitkRhw3il2vghzqUBnDMu2IQNXO8/eR+kufTvW3wv8fcD/tZTy71Zz1P/P13tIX2yVVPjw6oBC4ZzGNYYoNs2vrBYB2XMW6dgpcUDB3cTELzsR5H6iNCd99++vGWQH6fJGINZJUKkGUo/4KBSO3csZkOqbCoimxMIpboNnmiCvRBa7nypgb6UTq4CkRcYjDYiCNY6Hq4afX3lJbLX4eIxT5J1Vy2YS+UNjYdVYzhctXacZY2LhDD9+uqNpDD6IfMJYMFoAkRAiP3jQs+4dL3ee0Xt++70Vyhh8TGzGxKox9J1BqaZONdGc9YaLRcujdcfH1wNLJwaTH1y0pNJyCJl+N/Hx9Y6PrwcBuus1E9P/JKbiRfaGzlqWjWXVWxaNrdMsDcM4kasWQSlpOowxsLCKXCamGMl1rM+QRIbQ2MK754YxwXac2AwCiP/o/RWHMXHwgYvO1AaUJAqFBKUwNoaFzbRNw2Vf8DEzpoLVivWikbHQlel0CImSE9Yo3l03XO/E0Hy7F4RkOxR8I9LAxohcMMTC9cETU2YbhH16tnDkDEbLxLLBB6YQ6JqGJ5uRlKRQ3uw9N4NMqzvrLa01UAIhZTqrebzu7optp+HJZiDlTN9I4ZJTlbWoI7szI4Xo1T6wmxI+FjbTxJgindasWsuUYZgmDpOmM4pOUiMpqoPkGO+sHGMqPLnJdwWbRt5r7+GjjRfWUi2UTgu3uWCaC8IZFJq/nouGwtE/w1Ypy3gaGODofcGrbKMBpKPMp8eMeR+zyNTB55uRT64P/NXfu/g2TWHTSilVhGKDUsogtfS3bo0h8eR2JJeCVoqz3vKXPt5UywXD5cLx5Hbk+w8Wdz5IS6d5efA0VkzyG6f5xfMtv/PdM3yEF9uBn1+NPF42fOfRkpgKV4fAj96VfHHRai4WDU9vDdchkkfxuXy0arjJMv5bFcXFsuWjmw23h4GEYeEMCkWzcIwp0xjFw+WCRWP5cdqRU+bJ1QBK8e5KWIq7KXI7BTpjaG3kUPPsHCsTHAFdUzqyh+bBJ6E2Oloj+87pMzJ7wxhkf3q5PzJt7pPw5t+b/5sl39ZIrZFOgB5hNElupYqA2M4IaDf6RCiKVDRW57s3mo/rbg/IJ3LSIIy/zRhkvHoUj6MJeV8SqFjuujx9IzEsnZyHOT88XfPrz543BSAXDlFiRuIIPM2vMe/9oYIqcz7fWMt+KmynID6JBvrWcb1PZBI/fr5nHD1947jdp1/JIcYiA2laVYfi5GOcmo97BpJm2xNdjvFrZgrN123OSQoVNDqRAr8ptk1AW2AaoekKF53UxsN0/Nz374vPWqdNuF9nReTcPLkJrHvN2bLjYiW2H8/3rzYJZrLHHfCGAKLOGSYfePdyBRkyRYYAoUAVxlAosYCSWvCsl8EYjbEoFOMYWTeO9cKy7i3RZ37j8RLnHClFutZhteyxyzYTQ0YZzYvdxINF+5XtDZ+3Mvk76r9/18n3CvCbb/dwvto1e1zsp8BPnu+hFK4PEw9XHeve8O5Zg1aGcUqEpMm5cNlZbqfI+cJJwvpiZDNJ8iySJElwSpGA4oN4z2ymSEqZ894QXGI7cDdRx+dXH4bGwn5KtE6z2SecjvhY6OBOPjH//mGEyRR++mLLg67l0arhRw8WfHxzEKmCB19/WxLiAlHGMqcMoy6fak42JVjrGpi0YdloRl84TJHWWlpnpINpxKdh59Md0gySuFmkQG9sISRNqpMaQoQ4GzBXJFtpQdpLyoyhiOyjblD3EetZj1oU7KbE+aplrcGniaHq8CJwO2RQkVVnhUpfpPsekQDZR9iEjEGosR7RpRoNhwKH4ZgU7qoeGS1MpKebgfcue9ZdczcNLNRiQpfALhSuD4FGw4Pe4Zzl6WYn3kZKCq+QxWH/443n4crxbBdIdbNdLRQxSZf6r/reBSlnfnk9cgiJl5vIUNkFLdD3lSFVErloCoW9V/zgQc9q4fjJ0y2HsWCsJMm6Xh+NgGkZubGcUtwMdZpbguudF2ljhL7LLBoF1mKJ6Fy4HeWarxpY9o7NPtx5Otip0LmCs4r3z3te7DxliGglz0hMx/GkMQujTFUpWU7QOkWg3IF4OUmikJLcFwphWHXW8PMXO7TVfHDWMqVE3iWGygRoKgsuZzirPjS+3vdjTQosr7JK7kDNem/bXNj4yBgLw3R8Bi/n6SFJ7vumJjGvkx/MHahWQ9OJlr8SQnBGfJhUOUr9xpSIMTHGwuNVy+0h8GDZfiukCdVM+188+foPgL/n6zuiL75eHCZ+cXXgdz+55hdXAyHGVzyJQDqoXSsJajavMoKggotSO991GD/vetPvvy7xmjX2CrhYwrp3DFPkgNzDM6tuZry5Ssko5djNDVmS+ynC7VDuvCSm3TGxRslzmSiU2oF+uGpoNCzaBihMMXK1n+gaw7oxjNaiQyEURdNYVr1ItXwKPLnZU4oil0JnNVaDj5FGa4bBC+CSM6u2oSCd/ZglIDw6b/nB4yVTzPz5P3hJyGLmf7FwTFZx0bX0Fl4eEi+2E0opdmPkctEz+cztfuDlWHi0ammMYdFYNikyTFL05yL/6iLnawiyP/VLIx+8KFIuGC1Nkc0oZqNtK/GyWkCQc+H2INIppfNdEaSRvfUwBorLnDWGEBKLznK99ywbR0YJyJ4l7rVG9vGSJU9476ID4KxvmELi3Bj2o0cjAN2DXnO19zy93qMoTLFwPUzsY2FhpTFUagJgtTQrTB0HPgRhvA7e01uFXToenXVQNK1RtNbgUySWQkyJwWcuFo6YLed9QitFToltEOZS14hPn9ICam2HyLKxVY6cyaWwaiyucVxvB2yReHkKtBgDOWV+//kG74OMsJ4KO2T0eYgiFbU6E2s7vGTJq4wWFt7TTcBa8W1R+eiZYos8Bz5IbjDvCaehfFGbF05LfjQXf44jQ3plj6PBZ42OVsfu/PxMf1Ys+DTwaC40I+L1+Mn1AeccH1x09M58K/aIuv6fwD+plPqzyEf6rwL/j6/3kL74yrnw5HbEGWHe+Zj4tz68odGas74hplkS6mSoShRZ6L/70Ybb0bNsLGe95cMXA7/7yZZcYNHYmotK3nbWWWKN2YdRpkDHlHl+fcBoxdIZXuwmnIYrrfnORYtTlue7gWe3A7spME6QTSKlROcstxNsnkZ+49GS33u+YzcEVFEsHLjW8vR2FMalVgyT53ovk6ineARFXK2aM5JPrVrJbTwVyOHInF00lUmihAU0nOT2p2zsT7v37zdPWg0Lq3ixk7x1lo9aLQ3JEqUROHjIptA6mWi7nwJaabpW8vy5GdhbebZjfvUZnRDQxEfExqKcMCjq50tB6iqrpblilXiXNUjM8Pno9TM3wU8/V1M//xikRtD1XMyTXw0CYMyMn0Jl8RfJa0mR4E9eW8F+EOXFw65lM3jx4Gs1w8oQtulu8ttsy1ByZVSV1wM18/kvUSTsd+/9ht+FY/7gkOuirTSyXwcSzufaUD2VCgzDcYjIm+rVN60Z2P+sv5sj5qcBTQWpm2KGd84aUdsUSyHQVX69DMiSzzBbBBjkOjkjQHPMiT/5geXBqudqN9JaxYNFKxJln/mIHYwKoxW907RG885Fj9GK/RTZT4lnW8/LvbAFv4fmr//OOb+4PohfGcKSknrV8WjVokRq8pWtzwUglVJ++Gk/V0r9R0opf+7tHNJXt7RWvHfW8e99tOHlVgJ/azSXvWPVCdJ3O0xi4Kk0RcHtFFm3hseLlo+udmynIxMiIwlnE2G9tKRYuAqRkEZCko6EUpqhsjNyquZi5cjIiIiJWYiFw5iYCtzsMyFJ56wtcmMe5uBRJJAP28Lz7cj1NPGdBys2YziaUte/CRFULvgszCStxBumDrt67UrA851M6bpcFnxSGKNlpHNO3AyRXIrIGnTCKVBOgrVRkvBqLWZ1JWamOtUoF+lIDOkYWGZzSGUDi7Zhyh4fXjV6O10e6DXYOhGhREiu3AEFrprrNQb6Ohnn+iB/O29OGQnEGel6NhyvZUqvyqdmRsmDDrrWUFLmyaHQbgfGKXHWOfZj4OOXO6HsOsM4iXknCp7vwx041Nu6OaXapSnQBrjZB2ylzOoCw1C4WGsu+o79JFPudofE1d4TTs6dB0z1A7reZVKa+M7lgofLRkzTm5YPHmR2gyelSPAZZ+Ua+SxdEifgN9tJJtc0CBNpH6o5biP329Wu0FjZ8ku9Sc56RcmF3ZhoHZzXk6YQkLbRitWi4WYv8k6VhZ4cgb5uVBNSJJUs5tHJSjEzBLmGjZILY7U8IyCfv28sT7YjOy/dtpu+4TBmnKtTcwps/TGIT/6YzBSkeJhZcIYjm+iOMqtlstFQAi8Ox/g7JzrWCM123BW0EcPuwZfXAkizbv/gZSOM9XtWVZpy/f9c5NxrYDNFbg8jf/z9NUqrb7w0QSn1vyyl/L1KqX+O1+zFpZS/7Ws4rC+8Ysz8+MmW/RTY+0yMke3hmOTOlzcgUy2tksKz4VUD3ADke55Zn3d9XrBJIyC8KsIOKkqK81m6PMajt51BZGrRH+U3vZWOsVFCu8/33nvuHirqMAJn6BtNYwyPz1uWTvPTFwPPthO5JBprOPhMTIkQHUYp+say9xGnNbFoduPE4AUIaRq5TZ5tJ6zVOCXITUHzzqrhfNHydDtQUuHJZuTRqmU7edS+8C//+DldY9BG86Du2z99sWEI4rGxGxO7KbBsLVc7T9PAJ7fiJnG192yniPeBh2cLzhaOp5sofm1KMKJ9EEaxL5LUa4DNhDYaloUH6xULq7kdPJ3Vsh9PmVLjadtUWXFbfSSi7MnWHq+XMYqmcSycZlSBaZQJcz5F1o1l3Roaq7kZAqveMfiMNpm+1TzshWnUWHhn1THGwv7guVy35AxPNwdiaXh6O9JozdookTGSWbWafUh0RrExhc6KvGThhDU6xcT1ICO7VZC+/NVm4p3znpATJhVebj2PzzrOesd0feDFZsKZQlaWnBOdcygfsEoLoKQFdLs+RG6Gic3B84Hu0TqzcEok8QZ2Bi5WDZMPjEkk0mdW4v+QM+PGM0Y5j8bI4BAXhQmoqZ3zCvTbLJIQSpEppVnAvVl6OT/MmTr0oLyal8y5RincGVSvWml2TPVBmZ+tiOQerRO5XCp1aijHTvx92ciXWafby36C1iQuVy1/4v1zfnZ14IOLBda+KXv6Rq3/DvBfAf5ryGn854F/5Gs9oi+xUhEGu63jarVSlALaCAvaGs3Be4oSVcOf/+lLfvxsy36KnPWO0Uee3I48ud6z9WLCfgiJq/2A047HK3ix9Swaw1/3w0uudx6lFVeHxM1+whklQ3mUZKu9UbzcBd5day6WDf/+ZuQwil+LyZJfFSIojUbxfDMSsvgpuQaU0lxvPcEncBqjZWDQbCcx5z8JaZ5RvzYZXg7H32m0PJ++7oEpz8z2CoafIEXzM/d590lFBVy0yOe0kmet1AdtH2t+1YgVB1qjyFwdxCdgipCR5vHaSpyf2aOG6ovJq0nMXb5deGWy2NzQBqljWqfZT1kGxSDg0dKJNYOOwoYa/a82GjNw2cKyE7n84Ks/LEeQh1Lrlcq6iqWyvmp+rCvzyhiJdddjZsyed856Rp9JJTNFGRawGw8M4VVG0FQEFHQGdDqCWPdXQT7DfC3m8/S6enJm4DgDucruFs2xmX36N5oj43T2WBrKsUabm7+n7zs30GbQ8vS1DNJE235G0P28DCWDXJ9HqwXjPIxJGR6uQWFJKXK7TyKpnEHEJHVPQmo7gJ+82LFeODZD4L2zFtdZXu4mDJkHZy0P1i1KKamfOsuiteyGwEXfsNkfZCCV0XQLw8vdyJ//2TXnC8uDZSeDhUbP9x8v+dMfXBxtDmL+2iVsn7X+Z8A3HkACoWGvWsPvfPeMj64n9lPgD55vePeiZ926SvPX/OL6wLObEWsUnPUY5zlM+Y41M8t3ANAyxWCqj1zMEjwThcYkDuEIVMyGILOsZqb7TchNtq6Tq+aL31hhz8wX6nS6E8CzTWGctjL+UUshMXoJiKpIYI5Zit4pyfdOi525QzazIixSyBpD3WgyC2MojeV2PwlCXRBWCmKCak2mUQqDGDSvOsNZ39C7wr/38eHI1uJId5wL+SmC8vBwpbgaFDkXinkzwFUynHVCxR29yLlmdolOksShhIU0F0X3g8QMJmQk8PZaktKUZJPVFWAqWYK/TxCnRIqyOTbGcDN4nm08TZVyNBbClOidrlp3QespFSRTch1n936NAArGizEdSqSDIQFF4RRc7SYOk0xAivWadtXwOWbZRI2W74eicc7QOcvl0grQlzKttSxWHTkdmFKl31YpilMyaez2AKHSjEOp2msFq6XQlQaf7hh2MVfWWJ412pmsYdEbWhRNo9nsPMY5ntwMQuFXtZitwBEVMJnvA40UqDEWzhqDJdxNpVBmHm0qMo/zpRRWw+jJWZhfh1GM6EKUBCWXKi2q99h8/U+T+LlQCPV7rZbPX4q8z94LG64+BnfU4JhgN8j0uIDcM9vpOM3tdWtE/D3m7k5CumS5AtFGVRp2EDnheW9YtWJ+d/kV0k/f4vrH67//86/1KH7N5XOWwQAFQoporRgpr40fQ81429dUhnNMv6eM/Fzr8xaaGel8qhq0dYZDiWyno3H3qTfL1eHYAV1pWDi4iQK09hXYmAHqOT7OHbTewePeYNuGxmqslsJJ68gUEz5lYipYJeDvFPwd88SHwlgiIcpAiN5Jcb+J1ZdOQ6xNBkrAaM3VXkymrbUYndgfPCklYZJcTTxnpGnkGbFLBbqglUGXyBATnQPnGmEupYxNQh9vGiPyOI/4BDBBSSxaKYKiEoavB1TdK+cu5hShI7NeOC56x7OtZ+EMC9dz8HvG2qAxlrvR1tYYcs5oXYjxmFg2tmG1kExfK8u7y46fj4mQRK97sWgZYmE3ei66BooAFKMXP5SJTAwih1l0FhsKThduB5nC8GTrSUXMd1ur8ElYms8PgawKqRh2IdfmkqHVhb2PFDTWapSSaTFKFc46J0Xr3nPeO1CGnY/ovceNgTEEOqdx2uC8Z+cTISQyMlL6g0vxG3y2ESrX0hluxsjPXx7EOFvJyOi2bThbyJSjwVucDsSc2PvMlODMKbZZjHnlvpQmkqrM4bnho6m5D+J3klLBmcx+quzS2sghH4uYmVEwFzBQ/c2UfB2yNPN8rgVb/Z2I7BlrB+eLht0QWS8KPhb2kxRlc+x4WxF8Lp4yoErBoPje5UKGkOSMfWP77ZuzSikZ+LPAn1VKPQC+W0r5PGHvG7VmSdoMFuUihsqPFg3XQ2A7BhSK99Ydn9wOXB0mFs6RcmY3BZ5tRi66hmXXcDtFPr4+VBZ54rfe7Vm1rjZBPRe9mNanBI+Wjv3oOcQI1eTfnkj2P7w+UMiMUaZ1LhvFbhQrjZxAlUDfNjIlLUYOIdM5Q+scPgfJ71JkCGJTcNpMmNd8X9uTf++YunUDmZ/FOV9V9et5atoXZeeeLqcqyF8BW02VxnFkvRQFOYuPlNNHECLOnydKfj/TeJV6vdxs/rrVM5h9PIZ5r7QKWqsZ7wYpVaXJJMdlkb3ldTlBZDbTL8T86iCWGSC56ITRHKket21t+LYWpzN7n9mNJ9L5BD4WrjYjY8oMU+B2L58klmMMmQGqOS/tlTRSxvKrIA/1d+ZG6P01AzczEyojzKmu03RWcwiZ4ZDvWF/3X9sjjCNOVAr3z9dcr87XZGafzffn/LkM/OqFfM06bQK0vH4SJlTlRCh8cjtw0Vu+e9nTNE4aLntPzAVt4VELqii01uS9PD8hyv6ttGazD/yFn75kCoUxFR4vG/rGoJTlOw+cTAbtDA7xCtxPke+8t+DqMPFv/vIaX8dT+5j56FaO9hAbfvPhmkVnebmTxv6L7YjP4reUi1h+fBXTnN8WgPSNr3BOl8+FwWdaq4lR8ckh0hiPVooXtwd+eT2w2U+0FST5+ObAz5+LBj+mI9o7exlRxPug17BoDYdJRhqK0fGR5tzqoyZ+fgDnWDELwOfRjlZJoFgu5XfWnXi13H9wA/ByvuszdLUopVRPGiVFuE/Hh2vW/xt9lJDNoEamBv0M8RDZaXj3zHDRN0wxVvmTdC1KybR16oPRCo1mvWg5W1jOesfNYRIPoVKTazmsVzSic3fOuobLReFp9DglgWNOCPtKIZ83m90k3gwZRdu09C6Rs7zPWLXQVsPFUpOqF9TwmmAyTxHSqiLvSlD4WQ43+yAdAqzrObEKNmNiX6e0KCWJJjVoH3Kur2VYNgWlFK3VvDiEO1R/DtiLRkCDYRTJVTtLtXzi43SgbRzbQ2AMQomlQPa1g61FVnLeOtCK7RR4ejvxeFX4JGcao1l20uU6DJFdjIxBEPGFka5tzLCZ5B5aKLhcWXZ7GVm/rKDJ5iBytb7VNKrwyabQWshFoZQkJRHEFFzDolimAiudGWLmMGSiEunADjHUcxZiEJDKaarRaeJs6Sg5CJOs3iRTPJ6r3s3gXSBF8SOzRrOdknRZsoBwMUtXOSdo0gk19uR5m8FFU9/KWAEil3Wc6FllFWmqzMdKYT4nCz4fi8vTe/P+mr3Peid+UDOdN1bQc6mhaWR0q9LwnQctD1Y9mzHybDPyN/zmo2+8NKGU8q9XH4s/U0r5L37dx/NlV6PFO+L64OmsxajptTnInPhojkb193/+eTtb95dB7pHPAp80AkIaQFsZJTxN8szOifl8HHOjYp5gGbOwa6yV5IYCJb1Ksb/7TLXL6bPCoTkMgZeHwG6SlE1RqsG2AG1GVY81qzEUvnPR8fz2wHaWgGoIStgg2h69K5yTLm0whb7J7D3YEDiEJGxAH4RBW+lgTYhspsjVfiSkjNHSdZeCRdEYhWsM05iIOXKIkaeVNg6yh+8mz6IGY2dlSpdWImty9sgQVAjjsLOGHAuxZF7uDig0U4xMSXx8jBHm7RjkXMQEUywyeagI4D8lCGMglMLCGVqbuB4yZ62hWEtvFLejTJRMSdE1hil6emNYNULMf7GRCU0fXUX+zQ83PF40rJaWEgvPDxO9M1wfPE4rrLFYA5/cHIhZ0RjN5CNTlFh53miWXUNrNYeQyD4QQqKzhrPect5ZvnPZsRkjq87x9HZElcJm8Fz2jhAzjTPsQiHkgkeKmFXbcAiJn10NdBYerlomP/H0ZqoNgXK3x573Da014u2QoaDoW4sPUqS/OAh4KNLuWvRYjSahalNjfl7mPMYZ8X88FGi0gxyJiMdipJrF8mrB4Ouzp5H9xtbcaX5GDrE2QDgWQHNx2liF0oXeWgqRNpe7Tj18+Xhwf5WTf5UWVv0hRM5cS6O/+eARgFLqXwD+NuQ0/kXguVLqXyyl/De/zuP6oktrxXvnHU9uR8mNleJ3vnPO083IwSdyKbyzbjgEMco2SjGlwC+uRnyI3B4C/WNDSZHrIeCUZioJozUv9p6HixZfYNFonmwGfvlyjzaG84V0JFuj2EyRmzHSOsdQPRX2ITN5YevtJ2hdERCjSMyV+DTR2EYA2gliTAxe8uhVbzCqEKbj85T41XtYIwX/WI4/nyVIdyBO/VuK5LgpS9OyrXWR/zTd2qesIRyHsahy9Aajvm+McoAZeY73Fbzpaz2ikGb8ouZyFrhcyP65f0P3evZZnZevr3OxgHfPFrzcHO7k4XAy1h2JLZ9m8uWBFyebvq2fw1l5z9YYDimRq90DSWITJTFFAdYDR59Cg9SoP38xSu2lZY+9rTFpJjRArbGcNKRSrWvHdGRXnZ6OT/Mx6pCcvqn18VAErDI5kxFfXrQ0kMq917p7jwKrBaTDq++jkTzaI8yis1bycu+PNfVpo3jdiX/SZy2HnM9Y86Hyhlw+FXm/F4fAFJIMT7CacYJHZw3bQ0SXiVXTsugsGo01BwYv08d7qxljZpsyU5TnNWVhHO595IePlvyH/+Q7XO3EwF6h+PB6wCwUBx/YDQGjFZdNQyyF3UGo0Y9XlnwI/P7zLR9c9nx0PZAp/MVf3HKxdPzJD875wYMFz7YT3/8KZM5vC0B6W/vjV75MHfGhUDxcN0wx885ZyxgTv/vxlpe7iethwkdJ6oaQ2Y+B21Ho3rlIUVuo062cUNs2Q2HnRZueahCZRzHCEbx53c05Ayqeo7QmFwF/xspG6o1Cd4WxBpk3ySNOC48mC11yBrDgiBIHBIiIJ1TUudi49scg1Gm42o0cponNodA20nUpSjqDTot84Z11i0FxsXI83QbSMPHk9nBHTZy7GI5XDY07I9rb2+3A5bqjc4rdmFl3maebJKPR4xGhnNHrksWTI+dE4wyZJJtRqoaXWhB4bUROMgNW8znoK5VWGQnSzlpWzjL5yJgizczsmWBTpJuYs1AxD/54TnWQwEMSnWzKQnWlJJS1GAU3o+jQtZbz2VaBuLOaUrIcdwUhranyMqDEJO918nR5BNVfOFj1jrOuEV13UWwPnsYaVgXWZ52AgyHzYhhZdw6tEuTMIYCpG6yq93DjwIdC0zpWOdA5OEQZ57qoO98his67KEHATb1xz7sju+32EHFGPEhSqZ+l2ofMAPhYmVhEKE6ug60TNa738preH4s3rYQenosm5cR5oyitTCO63ctUupjkOFztMO9GOF/JJLndId+NLj0Fke4ASiPPwsKCNg6jEq2xhOwx8SgJnQuGQu1Ka7neb8g37t5PI8BgUzvjrZ3lpCITXHSWKUZJPhIsnOXRuuXRmUxv+TasUkpSSj1WSjWllC/bWPxal7WaHz5e8Gwz8mI/8WL/5t9teXNMd6/53uddn/fvMhIXlo2CkumMYijlzttgjrfzSkiiDJWVV8f2WiSxtKZKrU5uZkP1rygwxMKKxLN9IKVQ96kio5irdLTTsFhavnfZ8fQ2cEiJ/e3EEMrds3yYTjqFRd43pJr4WuhMYTdGAcKcsP0aIx3auVl80UjzwB8SL2qi+2CtaDU8OyRaVbjoO27HgEIYITlLjGi0GNabUtmKSfaIUCsRY6Crz+G8T7VafJZ6p8go8cGYMrfDyDhJwfTuquGd845nu4llA9vBc33ItE6AjJIKIcFFp2mcxVhVx1oXOmtZdI7dEGiM5XaM9M5grUzVEQ+/xAcXHbeDNLFCEWDtZu8pKbP1lu9eLtAoNkNkDJmzRcPBR1KCQyhcLA3rThoOagpoAw/POn70cMEvr0ZuDoGb0TNMmZQzRkU6u2TvE//+0z2NMQKGaUVO0DWWg8/0yvBwbXihwRFBa4zOpBlmyZqPb/eEkJhq42Vf7y+n5FdSLjy9DZx1Gh8zT24lk/GVvRCzTDuiCIjjQxLGwL2iLnEEmQafcNbywXnPT15s8Sc+dnX7+xW5CvV7617L1KlSUKqwqfffLHmeC2OfIQzgy8R5I15Py8Yw+HhXMIbXvMevuzKSh7ROc3MI/A0/evxtka8BnJdSNkqp/zLwj5VS/odKqX/r6z6oL7M6Z/j+g8XdFDaAq73nNx4uyMAfPN3xL/zeM8iFkArX+xGnFUEpHiwd+yA+ajeHQMmZhbNgMykVPr4Vlt6qt4Rl5GoITGHk5VYA4lUrkrneKRmUMgT2PmG04jCJnKsgsXXek8615Jm7CRrjsaqOkY9SLyxaKCVTUOzip3vJzCz6mQXSKu5ymL4D7WQ8fK6x1AToW2iNYmUVNz6jamHyeZ+PUj9Hh4Aet2PNLU9YMQFwtVHSt0fJKUgeD0eZasqwbOQYr4aj1Oj+ajmyl+BYszkNrbGokmVIQnozg/iL5ATzPq4LrDp4uLIspswuFHyUXNoaJZ6fHKXWc1wD2ZPn2NMm2Uc7ZP9P3AO6KqDnsuyLF3Vy2txQmtfpZzu9NxaqXsMZ6DfcTWG+GsCMUXxHlTRM52vSzmqGk2O6PVSmWjlep4WDVaM4hIJSYK0iTYWmhf19WQ6Sr6fPcVN55H0apH55XQS1HAkQphS2PlJ2mj/13TWXiwZF4aURA6vdNLEPiaUzPFwteHKz5SbC6DNtI3vTsnEYq9kMnpgsQ4isO8vvPtkRYiaWwoO+wRjN2mlucuHZbiAXaZQ5axjGTKs1j1YdvbPcHCY+vN6zah3ffbjgslcYrbk9ePSjJSl9NTK2twUgfWtWUfDBRc8YMjEnzjvNL64CORVuDxMf3xwYQiJn8dDJVTcrtLEj0GKpY8kz4MudJGqmat5HaWP92emaEfr5wb9fiJoiD9KylU6mta9SBOGIJL8OFZ5N2E5fN5/8uznxiVkb2JxEhxlMKgiavw2FrGCM8lSOXszUQixcrhylwD4mrp8F1p1jPySmqIip3JlZan8MFPMx9Eq639dTJOuRq32ks+IdNUucApUKWRPG2wl6V8iImXbM0FlF7xRjyKja8fVR/J7mIKpO3rdkAXLOO0NGEVMEbXiwEg+hYahyryLXyWRJeqeTk6nqscV6X3RFvIHev1gyhMT1MDF6ZEKa0WQfOURhHDkLLYXzRcPj3rBLkcNUfbOmIOO3pywm2QjQRpq7rzLx76ITCuUhyGhO5UQHf94ZQgKnFYVMiJHGybjtg5fAuk+VTWNmuZeiNVIcNCsr8o0pYrWwCg4+y+QMLawpp6VTo6ieSrUjtA3QVD7pLJe0CHg2T7hoqhQsWukkzSDj7SFg1JEB1upaaGbQFM57w2bwnC9bcirkXPBBirSLDh6d9zzbjYQgo1BLKXTWEexEyrIJNFo2r7k5Eeq1TR4ueth5MRvc+nQ3Gc/EV5+v2c9sNvX+tJWRAnOIch7PV5ofPFzwcjuRt4FDELmUAh4s4HsPllwuHY01fPcrop1+hetnwL+slPq/8eq0zv/F13ZEX2DlXJhC5nsPF7w8TGgVX0vjhl+VEp+uXxc9e9N73l+tRqaHJiiUuxHJqAp43/v903t4pqJr5HleOEhG9oF55K5F5LmthqthYvCefShiOJyP1G9d0aGsZXiC95ldCHRGs50ie/+rPlKLyrYsphqfVsZjSNU/IwsrDyVeN/NS1KZK3XMbA4tWPHaeboVimbThdgyEXGiNSO6cNThTmFK5605HDQXx6XlnbdmMkX1IlFQnRUbpTHZWptp856In5szTnWc3SpdlHggRUsKHyHln+O6DFb/78Q1j8mKCmxVZR1wR/zZtHDmLKWZMhQcrR8ywbBuKyqx7zRQiPmVSLhwmMbF9sRNA7NYHplzorEFrAdVfbD2XrXhUXS4afvJ8T9toUjFocjX5zAw+45xmURQgRuC/vBl4vvMsO4PPhpQyY5A9/uV+lL0RRcyRm72wf1tnWDWG7kHHdvA83yf2Y2K1cBzGSCma1hae7ROaSE7CyAkcZfwFKTivB5EgG6PQNNwOnmE6ArRNjZ+lIvhWSXHUVNn13h+fG5Brd7lQrDvHspWJuKaynWaPP3j9czpLmveTjAp35mhGP3fMZyDzFIzyHjYlsUgJpRRVTSj7dUWpTnOqt7GUgu9fLvkT769Z9+6z/+Cbs6xS6n3gPw38/V/3wfy6S2t1V5iFimY2zvCLqz0f3g4snWXZGf7Shxs+vB74jccrfuuDFd857/mXfu85j987A6V4vpsE8A0CkN6WOW4pnu0928GzaBtux8DNEDhMhWXnsFqxGQPr3rAP1bhfHZmo831nqP6t8cgY2sWjKiEXAexvKBhEot9wvN/v37eRY5MvIlLOKdZGxVhtITiymEakIdvHQijlTgr2hc83koNNFZiy5dVmSeYoaepF5Xf3rM9vOX89N0RTOYJLc91REMDlrBeD8NPzkep7XHYwpciT2yiS7C/5mV63MhLnZPBTZjepuxHwRmXx7iySh8+Eg9kiY2bXl3uvdfrap//fnfwNVRlw4Njon/+08PrXmCppYgZhcqrNU13tXoo0TAsC2PiTF7Enr3/niVXZXaoCUaVIA3v0kiuU6pU6g1inS/PZjd3TdXcs6fWvZRBm1ZyXlJzZEjmMkZhkKvmNF59ZpSyqDudatRZjGhaNx9f9oDEarZUcX4oko/jgvGPROjpjeLqZ+M13FoxTpjGZf/fDPTf7gd2U6JyoLS6NpnOK7zzoOF80fOdywYvdyLt0WKM57x3PN56+UTzZjPz0xRZn7FciY3tbANLP3tLrfOXLKMWydfz2e2uebkd+eTXgtKJxmt99OhJzoTeWXQrcjsfgB0cK4h37BO6mMc0g0ClN8bPYmfcZRPeDdEYkRgsnhfmiFqzzhIM5mL3xs/JqonP6ui3HB3zIr+puT9c+HzvXnYOzxvBiJ8yg3SQBGD1xi6ZxcLVL3Na2oTavytUS8vutOprwbSq7qImwapIwkrLowLWu3eDKkglJmCqz9OkQQDkxHBdfnyITWrIEmRSPyWrDcbNTSEAqFaX2USRpBz8xZYv3mba1JBXxqQIfHBPIuRCaP9N87Roj99duCgxTokVjbGZKmlLKUVaSpShLCWJO+IWl0ZoNCV1KdcKTaDa/R4tIPzoN68Zx1hm0gsMocpupiKH5LzcTuxDpXOQweWIpOCMTPHwpIjVUotdNCc57LX5DqjCEXEeAGg5TFuPqei7RlZFg5Z6I+YTeXNlXh3CUBcw+UvPJ0UaAQqNlU5j8MZm2SMIzerkuoV4fl47U265RxCRFz+0+0DrNEGJlDhkSiq33NEahHChV0CQshst1D7uBWGDhZIRrGeuGUDenKcL1Qe6x/ZRfGUV6ukkVXjXmO31e1Xw+Tv5fIWBdCzw+N1jjeLmNtLbhbAHjJCN4lSlcLBeS7CT44VnHe+f9N16+dm99XP/TwPprPpYvvFIpFAWdczRao9VbzQd/Zb3J7+jzvucQjlNxTiWap4zFU5r46f4yFxQgz6/XAoS7RrrQQzV911ko4ibBppRXZNBzMR2LGJL2bi4acvX7Und+E/OzdJfQlpqUFQHlY66MwBmY1fK64eQzUv+dytH4vrUS90vR7MbAonegxEi7cXA9ZFaNprMWuzZsD8JsMRoWzjFMHtcadhMYZZimVOWylnOVCTFz3lsulo6YExeLlt0wSRKPoulr7G+sJN7O8nI30jiDM1rk2xoMilgU2ynRVtqNr90mqwohKZxOVZ9guBo9+yneSeGcFYaBaxQ5Z6zWWKPBB57vBGDZj1u+96Bn4Tp++/0113uPKpnrfaJzRsZYp4lF29KahqIj+zHyaOVY9Q5V5JisVrStYu1EHjmGyL5OW50NXJda8dOXex4sHcNUePeyI/bgUyRHKcG2IbNw4g1zNQojtVc1/sfjfR6S3A8rZzj4wJTKXRE0f/51BeuWrTw5KSXp9qdXWdcRASJVKTTWSA7hDOehozOBlAqlpLuhDK9bCtmLBgVtBf5PmdPwatwvyD1cJmlkdfZYlMyTmMba/OmR4z19xl8nFfms1SI+lM/3A//OR7f81rvnuP5b02z4HyOT2P6lUsq/ppT6TeDHX/MxvZU1+yL5kPAhyzOXM1f7iZ0PHHzi9jDxybXmUd/yYCW+X8+2E0+2EyEXiipYbVhWY+spJDZDQKnCYQqsO0PODh8DmyHSOY1Rhe3giUGaunPuPa85j9yE49en00Mjr+4bmSMQM8ft14FInHxv6+tgHF1N5ONxfzsFIIx9tSnwRdfM/FP5zSzweY8K6vXN+XntMzC9eq5Of7cg8U5XALpi2Hfr+iA/m61HvqQi741LJkBmYhSlwnln2U8yjbmUIoMD6u+esqfuR4K51rQnPz/NPebPZZSwZGZwJiPM+VMLEMWrEyjh1es7A2wOuRdylrovZImL/t7FOAXyT2P5XFugarO+1hetOdYfM1A4S4rn7+UvEkxPjuN12fbMNBP7mkSjFYvGojRsDoHbIbCvZvVOJy6XDdYYrg4jrdF4Y1ms4TBFnLU0TrGbMkYVfMl878GCzjliNUndDZGPb0Y+frljiIXNKEzalCNaFRKKP/XBikMqrJyhtwZLlb5rxaJx9E7z7HbkcuVYtI7Hy/YrkbF9LgBJKfUXgH8M+D+VUq7v/7yU8p98a0f0FS+tFe+sWz68PtBYQfKc1vzy6sDkRZYTc64m2LLmxHzuRM3rfjdJId3KMX65QHI/OM8P/eyjtAtHT6ApSbJ+7kSus3vNA/Np4NLcaVtXH4pP+92Zohoj7Emv+A1MGeKhcN4nNqMEIFVqQjsdN55WHx/O1khRfZqMeeDJbbkzFJ471rPsbaqJXKkBaczSTbnaye/MRVRBOgrd7GmkxW+mNQJC7cfjedXA3if2o5zTvsqYdkNm1RX2RbrLzkiH8T77a149khTHDM+3mUWYeP+8Y91oPrydsDnTdY3Q7nXV3RqRKuU63lUpxaq1YkCaEhl4tHIYFUQ2oCQJjVmYOqUKobeHROPkbPWNhewpxfB8O+KsFBkPzxt+75MDMcPZUnHRaUYKLYrWiQmfNYq+1cJQytJB06OYMOZ6sY2VaXTOgk+JcZLrvwsidZk3lnByjjpkA0q12lz3AjQx3xe1SB+n43Wc762AbIqDh8kXlJoEgHTqzlx+6aBxlt0wsRngvDEsW0d2id2UaG3i+6uehkxCk2Lg9pDvpCm6ApSqHOWcGblXAG5PUN7TBEpz3Bw9JwatJ929WfJQkE05ZmE5+ZR4vG5JJUHJWBTGaqyB33iw4E9+75xSNDcHz8Nl+60BkUop/6NP+7lS6h8upfzdf1jH80WXUQqrNevO0DfmK9dlf1rM/Txrjo1zx9RwvBfn7vPpPnT/85yC34cq8x2nV4Ee6uvmucN4729nBuyUYLeHyz7xLApzpmTFqpHC4vT9ZwBfa4lrXREfDadg1VnGENE1o93Vv5kLgvm5a6140hiq95xPtEYA8RebwBQzfZyfaUfrxN8qZCm8G2tIqWCtqhPjZL9q7vzXCtZYss74VBhj5mHTcL5w/PzljlwkHi4by+ADMUTMsmHtND+7Ghh9pjGQY2QIcLly/M575/zbH92wO0wUJRJkpTWbKbEPQYZXFMWiUi9LAWc0rs3sJnCmcOYc+8lXdu3EUI1xnZJzuQ+JKWdaZbEIk+jBsmEIhTHJlLoHThFCxhpHZxS9czS2sB0jqihQGpMTY9JMY8BpWDWOycu+k0th4RSNMwyhoKxhO0Q6a7jeR6YciCFzCBmtNCnlo79EFgbEfO8sGmm8+AxLpxiiZufzr+wlCdnTz9uWXcocxkTTWBIRG1/dkzNwcwBnE21IpB4uFo5bMi92ExlYN1LUbGoyMxcPhSPTOSJd+Fm+MjNlMyeGwRyBWI9IraeQWSrY12cmpqP0bZ6GOBdNXX3TuUH1RSSsfdvQakNRik9uB37U2m/FXlFK+aeAf+rk6z8A/lPz10qpv6+U8j/5Oo7ty66cy52M7b3zjo9vBkLK3Bwm1q3l49uRp7cjzhpiKvzs+Z7DGPnjH5zxye3IfoqMIXKYIg+XDh8zmxEa63HZopWwO0NM5JwZY2IMwpJ+6WXKct8aVi7xInA36awgz9mcW81x2yH59GxWfH9vmJ+n0z1qZpy+ac2MJHJl5t/72zkv8v7XZ+Hd2RvkN/sFduZoIfC69SZmzemagHTiPXt/P/XAqp6YXwMTe+1SSOMgZwGxAIYQBYzOIi2/H/dO1+vyi1Pp7mk+O+/tsUh8bhQ0ncL7cqe6OG3GzzH501YAVM2Hlw2M4zGmf5ph9fzZG47KhUUjANT1KIoBoyV27uPrj+PL5lavew6UEsa0aaRR3RuN0YrdKFPJtVLELABXUEKEUCqznQqNlW5Yg2LRGBlYApx3DusElfzoduBHjwzbyWOdJhXFbgxkFLsxMiaRtV0sLZ215JSZcoEie/AYE61z/Ma6Q5XCz14c6BvNB5c9f+0PLrlctWil2E/xrcvYPi8D6T8L/JeAf+0ETPrnSylfdY791tdhivz0xY4nNwMf3Y5MqfBb75/x0WagZBijIBt3BXDtfMX06s31uhu0IDf064Ls67pMb0L0769T+n9EgiZFitVDFpDki7bK5/ed4pGaeZpE3f/dgHSkw0lBPf9vKZVZkuByqdn6fMcwmv/e58oCyvDyNVnSzFw5ffMZWS717zyi0+5b2I51A6mAzJQlEU1ZjmdXAZ9sBATSJ3ShuVs/1c6u0fLZpoPQUX2CMYqkaxML+1DBhnpMnZIu+Mw6i8hnV1VyNU7wyfWIedCh0WxDqC7J8vdJy3nXSsxSxxD53sMl+ymxyaJxvlw09J2ltYIYjzGht55hrKDN4MWLokgX5KLLjEEoO1ZnKIlV61AKtiGTKwtIKjdF8tLGL0r+Rht4Wh32jNasOkMqAop0jaGzis0h4ivK4qME9IQAaI+WjrEJpKLZDmJo7YGuhfNFy81hurtXTs1FZznYfF1svfBDfQbnzker6iaa5HqmnJii+KQcQmZMla3gEkRVaaKFKSZ2MbH1mTElFlZxtnJs9gHjFMtOcT3ku+s7b9arTrHuG9Kz6a6Ive9ts3K16KzH3rpq3ljXaeIyRIjbRIqJpnGMsXA7RnxIMpHOw+0Y+dE7gZ+9GHjvfMGH1wPvnffiW/JHY/0Hv+4D+LSlteLdsw6jDRetlWl8b7ul+JbW6X7iEGB9HgAzxyTN55t0M8vVXgeOKyRB3iT5nbmAPn1NTZUMA9cD9E0hZWFXlvxq4TG/htESr6d6oG2RMemNEdnxKUB1mmgqJSD02aKVKUKp0Col/gAGhjGzHXMFlYQ1i0/84GHHZu95kaUQO/iIUZplq9hN4hP0ncue7z9c8Gw7ME0RTcIkxcW64eHa8WLj2UyeoU64HCcYxkRjoRjLGBK/vB4wZDZT5rw3GGtpyVglAx1+9M6KlxvPZvSklNEokpLOVGsMhzGjtMRgFNxOGVVk/zTA9iBxv2s0hzrgoLPcDR4YQ2ZzEB+jkAKbwTNGTcyFxmhcI4brIWdM0QQFP78eaI2hN5rGaMbB45ymtxajMj5J0Zqqce/lwuFsw7KRvam1mt0YuR0mbg6jyPS0olHgTCYgYJ/WlU1dJ6JpAz7IZ+s1XA3xrqkQy9Efq0WK3XVnebafaIxUhloVxno/zROY5jUWGGPkfNnQOs3SaD4Mmd0gx0H15Vu3lSU6HWWpdVgRDUfPkPnenRtVM4Nvfg4LtSufhVXWt4pQq/OZzbqoXmN9BZEaVX0os+yBXySZNiBsYqtorEx+/apGNX8N628HvjUA0hgST25HchFZ7aN1y/cvF/RO87MXe373yYaPr/ekVFh2likU1r1DaXi5nfjw5Z6cC2MUBkHOmSlkSsp0rmUfItYoLjvL1oOPAT9F9kFAYwooJ0zsAehdEuA1HONtY4T1f8qkNhps+vyyyk8zUL6/7v/eab10eAtV47xPvUlKbhCmv3LcDbm5vz4vyDB/ltnE+f5L7aPEirddDGuqL2GZ1QLgnOZmzDIciWNdeMosKhxj4ut+dsocmtcdsKikvlx0Io9vGwhe6q62dqtKbQZbXu/DC6/KlBMCHp2ytz4LbCvIdeudSJQbI/6JBdkTlHrVG/erXL2Fdx40qCwDsqxRWFN4cfD0VnMbpHk1VG/Xq13ifCUeRAU579vqFm8Q4P+dBx1XuwlnNDdbz3SeeHqT+eHDBauFpXOax2uRpL08KG72Hq0M2yGw6C0xFpatrT5HgUerVuqHR0serFr+1HtnHGKmd+ZuUqRW6q1PdP5cAFIp5feBv18p9T8A/uPAPwpkpdQ/CvxDpZSrt3pUX9E6TJF/9acv+Ph6YAyJEDPXe89P9hOqZB6sLB/fxFcYRLF2Rk+lKZ+GxL/p+6/Ddz5vwLkvdZhd5+en800P8ZvWHHhmregp/vRZx3T6+ea4PDNUfILtkI/Hd2/NyqwvsuZCyFW5QygSjBJH47aYK9CkjqZ+kmDJ51t1Mu6zFAlEOR39oVT9/EMS9pGrgep6J3IuVeaHXn7XBgGKrOLO/Ho+f0OuXk2t6H0/uhpJuXb246udfR/B+0LTFHLMpLxn0WpSglB1zsNU2E/CFeusYdkLjXHwcEjQd4W+M4QhMUbobea9ZY8mE1Lk2fVI1nDWGhpbp75FCEHGwQZTyFMi5oRRmoJo7htrsUrRWjHpbLRmCpnGWR4uLL+8GolRrqeqCcgQpcelFKw7AW8OXgwefZ3eF5KYZCek01/qPXOfMjx3zeavjYLzVpgMPiOGqspQckIlaDvx+biZhE2WW5ECDl6OcXcITDFyfSisLhxLY+nWIutzqmCy3AzGHP0srnaFzmXaVhKxKb/KXFtXL43Z48lYoWxbC65ubHNXeS7MlYZthEuTiSkxTpH9BA/Xhhhk5OZHV3veP+8ZfaCxPc+3E8vm29FZ/qOwOmtYNZZQ8ivmm9+0NSdjijqh8TUxV/P5GQ2n7KLTVZBYMzNJdX1Tm4+FhzPCUNI1FpYsRXqp4MDpnnEKuA8JlkZYGSHO3ksyhWjw+Sh75kSGUCQ+tyaydpbsZPqVtpFpymymyCHJcZxZeeYOPnO9DQwRvv9wwW6MfHLr0SrzYNFiu0Kh8J2Lnqdbz35KoAy904SSuRoCL/YepSzGZG7HID5twFkDCkWMkV9cyQCBXD1wOp1orOW9847NlBhDYdU7xjYzJjGq9qmwHTN9Y4SJUpO81mnyThoXSwfPDtK0aIGuaShkLpeKPIr3xrYOadAxMk0R12hUEmD9EBJ9I5ulotTJpMJyXWnD80PgzBnePe/5695Z8Zc+3jLFjI8JYxUG8VXSVZ4t0vDMo8slvmRebkae3B5QCrTWXCwantwe8Ll6WaV5zLX4HLlYeHzm2E4BC9wMtVGQCo9WhpwTIckeujKSlMcImyFKI68kUoIpJ7b+WLyd5kkZ2B0yvcvEmHgRJnQpXCzE90nkKJrzhWXnAyoW2nQPrKTuU5Vd0FdPAB9PJBpVCh4qi+jFQdjO4rt1ZNsppInQIp9FIQyJ3ikKApouWmFUz4Xf/XWapxkjPojvrDpUUTij33px8DWub80Hybnw5HbEGWEhfHIz8OH1wPsXHSFlfvBowRgiU4z87NkOnwsXC7Be82AhE5XOFw4fEyEWJp/ZTfFuYvMaYRrkDMoafvNxyx88v+U6VesAWxtqRYClMcmgG5XKnXIhUKVAdc0WGLEyF+NnJf0cQdBfZ831wh8G6yBRm5D+7cjKDG8GPcqn/OxL9PbvVldBkvl1xgRTNdKt5JW7953ZXRaJP86Cmo756XzuNVInzQ3w+fsRiWdzjbAZq3Q9nuSxSWowo4UFHHmVUHC6EgK+o6q1hwbnP38+AtXWovrQ3o5yj8/MzxyPU2O/KNvoiwChBmF6PbkNtCZijeGss0wxE6MM0MoFrNM4n1k1Mv1NoznrhP7gcyGVxMO+oXOKm0PiJ0+2WKP5/sMli0bzcNVitQzhevEy8nTj6RtDUvDOqqWUxLq1XO8TDxYdy9byvYcdn9wcWLQGY3p+650lBfjNyxXvXSzwKb8yIfK98+7rm8KmlPorERbSfwz4vwD/BPA3Af9v4K96q0f1FaycC7/75Jbf/WTDk9uJpnrB/PLFno9udmilOIQsptVN7TxNkhiUWvx39bU+a8TyWz/2T/nZp5m5vmnNifkczGcmzZd5HZAEbqyIdE4ClswgleLV5P9M7GjeeA7ngDv7N81/f6jJ88wyGop871LLOSgIbXcOJglhk/QNtNqi2shukAI/KwlAmTq9wBzZTLNcTGs4X2p8EqpiKWLWGqpPytJpdiWLmayWpLIDlp0E4HkagypHpg4cjaFTZboUL8H++TZynmDZWmyBj27GO0O6qYBRCWPg0arh+iBMpGGCnBLnvTBuckWlN8NI3xlu9nIQL3ZJup5RWBZddd+bAvSNpreaosF7KWp2k5fOrpGiIytYNobvv7Om05oXu4lEkXGdDTRGsW463r9wfHIz8f5lz8c3I80YmGJCF2HZdLVQLPnYPZgL0M5KpyEVSbjvKMrIprXz0o3Is2GqzgLaZKRbpzTnXWUPpiLjQ5UULy8PgcZqtE7spsiiVTxYNoy+MOaCbTMO0ZNbI6wmnWE7BN45c9xOkd0gpn1QpZSFOxPIeWzpIR/BzoIU1PMzopknnIiMJuaCs4qegjV1xCnwbBv4g+cH/op3Ne+sJeL8Eeosf+NXzoWX+4Gfvdi9Vhb8TVr3i+b764vcMZ+W2J9+3xd5Hi01llU2bMhHD4IpyhjdXY2NTf7VxPEOdE8QK7hPEZD+3TMl3oL1j+bLUHFehgguiKeOtQZCJmVD2yiGkFhUaWlT4826AWcVBZEoLjtDs5W9pG8UjXVcHQJPthO6iJS4c4ZnN3sxJa2sx5sh4ao/hK0y8s0AkcK6ke97DWMSJsLWw4UpTLnUAl+zGRN/4v0zPrwdeLmZCDlxc/DEnNlNIuEeoyLmhDLVQDpJfCx1z7g9TDgDbe9YtJbNLlJyZd8ie+vaZFSW/S0CvS00zvD4rOX5zYFl2zCEyJPK+um1QRvFMCbeXTm2YyJkjTOGZ9uRQ4gsG8eP3ltxGAIvh8hPXm7pnePldmSKwpRSVvPkdmA3FUoWj5LGCtNo2RvOGotWkRCSUP6LxP9FAz6LV9Wyc4ze8+RWAmpnFLqIL9Ki0Ywhk5H9wlCBqXRkNtwVRQW2o68y8cjeyyS3uyaFyrx7bsk3id0gT1Gvj3F94igFWiDXfG54NMh+FKPEe1+OrxuTXKvZL0oX+dshyTVSRnLKTQR0YdUKnUBMgcsb8735+w540MNZZ7lYNjxYOt45e/vFwde4/jAwhreyUinkUtBK83w7ytRUlQgh8uHtSMmFmyGyGyKuMQxTJqbM1WHk0dpxdR0ZQuLZNtAYQ3bS6L7LgZXBxwlnLEnBj5/thFmDPFuxVEsHD9NYUBYaVe7A/Tkmz2uOD3MjnPL5lBBfplC/vz7vRf11QJfTtVTC9le/7oHz5Y/ndYzeU3Pz1635889MyFkxcWe3AGzyq8X7XJ+aKu9WGs7Wmpud+BGOJ687v/H9Y8uIr+38/VZL43S+9jYLUzgDqto1fBrDWdX8wFYCxsJxNw35s5biSJTodG1QqVfruy97WWdSAnz2de0trDtDKgUfM43TtMbgjCGnyON1w3aI7EKm78VMv2sz2hoaK7Yit4PHKofWpsb4SI6RxkoT5d31is2UuN6NdI2hMYbvXPb4BI8NPNlO/NY7Z4QMP3ykaZuWd9YtU0xc7SKrtuHZZsCHhNaa33r3jFSEcXw6IfKr2B8+rwfSvw7cAP974L9bSpmBzz+vlPpGyxLmNYXET57tWTaOzgUohd99suHZZuB6zKyMZkhiVGZUNYdWAgBoLYntbCj3h72+qvecwaNTbfQXXS3C8GlNRfxrgDmrCbY/CYI+C2Byf82BTXNMlO93rqGi7fk4LQHgJh0LqdN11zHwUIi0rqLXUUACbY5dGaPgzMG6N4SQ2BX52SUImydK8Hq379Am8Pw2UqxM/3p30TCkwjgGNqOAY9YINX6MgvaffuRDfpVGvDaSgB6KTHqIIUqCiZhH5wwLLZ3dGAs3o2fRNVjl2VUtedc0WKW4fNDyW48W/N6zgo+e3smEul2UTsIuQtMUdCNHMLMJUi6SvBiYkgQbpWQ8aMwFfCEqxWFKmAamLKM0i5oBEY02BWM0Z51DlcJlbwkpMcbErhry9pXCj66bT2WMqQRByzPnZ+Ct3ltzzEvI5tk28FvvrghReD1D8HROsfeRlIWpNITaJVYCOHmfWfeygcVcuN556fiVzHlniYfM6KsZ8NrwcGF4uO54vg0cfGS/F9Bw3XM3kWF/kOPqkI1uvlfPncSL/XQEQB0CHjVac4iZGBLBJ4xRmAxOZYaSefdsweXC8aAXDwQoXwnt9Gtc3/gPEnLmw6s9T2+/4ehRXffj3rxmk8u3sWYwdy5KFCI3K0X8ydQJQD7LoG8qZX2l5Hmx5dV4Pv/+7ONUigCxY4aPb9IrndE5SZmLnlkyt3CaMWdKirim4axtCLcTgUyqfH2lNM5qdlPipo7rckYzVOn29Zg56zM/eLik7zTjlOi8xmkIWaM07HNmezgW/ynLPkepI7Dr8esijZRZipuzjJJfTJEPLpf8Fe+tuN6NLFvLDy6XvH/W8vvPd8QYmRIcfEShWXaa3mhiY+haQ4yJ621iyALexST7WGMyD857xrDD1UoxZAHYpiCxdvbEUgqcNXxyK6VEQ2HvRepnFNwME7cfTTzqW967XGJ0whfN7SFiqi/YojF0xnIwmccrK+auObJeNFwsLbeHxBACm1l/rME42btaA4umoe8MY5L30xpslRq3zmJT3VdyYdm2fO9BYbWwXO88L3eezirOFoZygMM+y+RAIWiIpC0eu/ABicOhIGzPWGQKbpLjcsC6b7naBcbKKl46KaBO18xCMqp2lrXkOlSQMtSGR4PIJWOu5sRFrpHT8r3DPJUtyb4++yr5AM98YdnKffV56iujIBbFzRB5tGzoG/dHaY+Ab8E+Ma/ZNHuKiVwKU8x8cjPwMYWfvziAgsvecb5oebBoeLL1hBzZj4FnG88764aXW0HQH65aPny5E/ZygsXCMabEurNoeTDYDRONM9I4S0d2kaJKkTOYFg7DpzeF52fk61JoW97M6nlb+9ahvMq8+nXW26zB5lrn9Cafr8P9htCcQ3qO4Is5+d3eSPzLUQYMmcr2oUCvCwdTlRJ89nk9BWU6jkSDV36nSPwKWUDx8Q0BSyMvoCpSk5XEwM+zZqIAGbwShv7TTXqlIfvrrFMFDnw6K2rRiJw8hEDfWJwx3I5JmroqczsmjM6kmHHO0jea895CkRpq0Wi0sowhy4ZhDFZrdNuybDWtUjy7HXmyGXm4bGWfioGzRcdZV/j9ZwdaXbDKcb6y7KfM988dwxh4th1ZtFb2T2vY+cR3zh2/93THB2PEGM17552A2l/R+rwMpL+9Gt3dLaXUD0spP/22GGinOkHm8brhZpj4+fM92ymycAaN+BMQpLrPSrpbsTJArK5u/X9EVqurtnTibpLOl10z++J6EoaJ1jLGfR/rz06YQyGJHOKVv6fqtHUdh4wkXPeD6Bw4pnsRxHEE+GaUfZYPgWxQLgsd3jaQQmUwpWOwdjUBfXYrk9+crv42Y2aqSWkucHPwWKP44aOWZduwm0Y+2XhyjQ2lvt+YYFnBtHTveGdgZO5AhCjHHQEy6CSa44gg9zFBrLqQZScjp886gzcWoxNKFVJKtK2l0QKK3o6BxioerVp+eTXJ50wVOMsypSMX7uR1UxQZmyrQO0OmsBlk3HVj4dGZwyjNs9uBa6d5tOq4HTzX+0wphaVLFGX58OWI0iJz2E6BIQggmytNeqim16bUPN5KwhOSJP/awKqRDS/W82nqBV21SrTHpbDZB3zOnPUNubbQcoTLheOyd/zkxQFV4NHSMIXE7UQdbasYQqEkYaaddy17H/FZHnSrIaXMTSiAmGA6rehbxTA7FurjNYMT40jEaI8iz1VAQElbJRgpw3bKhMqKu54SZ41jNAWfMrlo1r3lctVxCAk1ia/Ib3+w+tZ0lpVSv1NK+Xc+5Vf+oT+0g/mSa+8Dv7we/9BZpl92vYmB+kVkzZ/W8Z1j5FILqO/r136S/3fIcxtOAvYM/MzM1PnrN61DffNT6fPstTQnejOQZLVMivNJnqtGa24CmOR5sgejjUiliySs1macsZQK+vgA3uY71qNVmd0Q+dPvW3wq/N7LLYepSsySxOPzyi4avbCKDJWFpSVl0HDnR6KLeFUsOieeRWOQZoDWIkfWhuvBc3WY2B4iw5RpXYM1iRILRsNZYymmYJzIuYZJMVXmS/CSuBsjyfmq0awby26IpApagBSXZb4+yGcvOdFaRWss1ijcEPD1uBXQFEUqhd0w8nwbeHjW0jh4b9XhfWaYAr8YPGfLRhoLBVorDFaAZ9sNtzuZNtogsW/ZNhRN3QgTWmkak1gaUEazG0WqOITIqrVcD9LcW7aKWCzLAqvGsDVyl5as5J5Qcu6Lqnu7lvg7D+dokZiLh7FkGi25h6p/a5vK3AiBIVSvrCJAmy3CQs9JzvNZbzj4hA/H6z2DVw7ZC6wS4K6elrv9fW48zrd2qc+Rqz5Ii078oaYge95nLYMcq0+FnBPPtp6/9gfNVzJh56taSqkH920v5nqifvlPvebPvpFLa5GGfHIzMPjE9X4i5cIYMp3R/PTFjrPe8d2LlutDYt0mbsbMxbLHp8RmjCw7y8VCs5siN0NDEyI+iFH9/jAxWc3tIIMFpgjrPsrzX5/1WOT+WxhhjGyHz/aY+aK2F297neZNX9V6S9jRnfHz21j3myJQzaI5EhT6ymhM/OreOT/dMwAYkjB0RmSStcpSR6kivz3dL0A+5xrhV5KC+ZrpUEGk+BnqmCLHMeXPBq9Oz/GENJX7TmKxRmH4cmqb+2sGjyKV/NBK7fq64zNILj/FwNJpzhYOp+oE0JBonWE3RqasWHSW82VHihmNxjaGTiuWncNqxbJVfHwzUGLAaMOfev+MffBsx0Qpid4afnGzx8fCsjX0G9k1tALlDJspMeTMWWt5cetZdoa+cZx1DbfDxOOzjpREwr/qLG1jUMCT25HvP1h8ZfvC5wWQ/mngr3nN9/7at3s4X93qrOHxumU7BB4uG352deCsddzsPTFHNj7hfUbXztJ0rBfvpoa8aX0eCug3aakiyPGsJ/2iSyOsmJSFleGTnK95gs+8VpVy2FVDm/CaiD53to2usiZ7LCjm9aZzezf5KtXOYO0GTryq+TV6/k+TdSbFozm31cexlaoyzzorm/JMzzxrpPNsyLzcFuIisw+ZwUeGulPPdvKz0abSssG/Dt1eNZI0HvKrUr5CNdvsxIdnqp1MkiSX8ZDl3owDpkDbGqxSRBQ+FEYvP6coXu4nkdYlSYZR8rmmIIE/1ER7N2asEhmB0bAZqr9EpcqSxSto3RucNby7bLkZE12jccqzj5EY4MXGk3LhvHd0VuFDZgpSUM0jNSNU3XDtlGkB90KWZHzuonSt4vGiYR8i+ylx1loenXe82EzcjIF9FPO5VSvXq7eG0gmgNKXMohHAJ5QiBqpJDqCpAE+xMIQknYL6GVORYxp8QanCEDUWzSEW9kE648MkY6TnIm3uDs2rs3L9fDwaBRd1ZPgVpKPxvcueq30EVfhg7XCN5ZPrCadkTOuqt3zvcsGqdTRG8y1af1Yp1QD/B2Ri583pD0sp/4ev4Zg+98q58MnNgP5WRfNff82fdqbKz53I2siUhOuEHTF3REP9r02vT9bn/eXL3sFtlRPNCXdbj4MKehx8rM+rxK9xglElLnrom4bNEIip8LK2PnMWfzoFYBStMzw86/Eh8fObgatd5Nku3pmXWluHHThFpvD4zHAIiVALfq2OXm1aiadNUfAb76zY7zwvD57Wav70B2uctfze0y1//PGK1lmmKfFi7+vfGCkerCGRCTlhinjSLVwLy8AQE9dDEWP0UqeDKoVBYZ1hqDK2rhGWb0aaBmednLO+tawaR9KZGGB7CKRcASZb5YKqgE3svIwq1iiMNuwnYaNupszL/USzHWmMIanCeetojWHjk4DsRvbhmKVZ83LrWbQKazU5KvLec7UTH7+2yXdeeiVXtmnOrLuGh+uGX14feHoT+M7FmvMVHKYREG+hxskeWTEirIIHK0M7Jbbjie9cZcltOOn6J5nG6uPEFITRkzOc94oHa8uiFuz7MXEIcL2XxtJFX1nFRZgnyookLvhXx1zP9/5c/J2mM7M8LtQGlq9sWY14MLYFtp9S+SbknrRWmMNDSCKB/naZaP9zSqn/aCllA6CU+pPAPwn8DkAp5R/4Og/ui67OGX7wcMn5wvFv/PyKnz7f0zeG7z5YcDsGXmwnlt0CYyJdY2l8kqm6IdVplYU/9u6SVArvnfVc7TyjibzYeYapkLMUkgXJy2b282nd4SszEV7N6b/JtYlFWOhvw1T7q1qzp5BKb0fGB7VxjEzA1sh1axXCuOEIHr3pb+FVaeI8HXystcKQxB/2oDN9BXqm/NqX+1LrAPTVX6vl9SSETh/VFktT1Sif8przII948nWXpTbb+oiuDNO38TFOyQX+NUhrg+QT6xYpCtEopfAxY6zmt99b83vPB0KJ3B6kSNOqkGKgdZYQC30HD5cd7160PLke2U6RDy47toMMIvrlzUCjICMNLjCkGFAFSoKsEreD53zRsjbisfL0dsQvHP+h3z7nvHW83E+83AUenXXkrHi86hiDMI9mRqqPkZAyrf5qWEifCiAppf4E8KeAc6XUKdPojKMl0LdiWav57ffP+H/9pSf8+OmeOAVB9xTshsgYRcaiVNVbcnxIP+um/QbHv9eusdLvv+yqeR4JuNlXE9fXrJuaJIUg7/m68zghvgPrVqaJDZ/VOjk9BiShMwgiTpJABcfCxyIB1FgIZBpbg1VNBJ0WMM1HARhU1f3mUo22DTSNIhfN1ZAYE7Q+c9Y5bvflFe8DxylYBfk1BiUF6WLPXdLTj9spSYRVrj5N6djlnpPc1kHyEpx3PrFq1V03OCXPqu9IOeEzDOPRk0QhRU/JknyHIgWaTyIzmCUZhxqkZ/PnWGTK2apzXCxasla82I20VoIquTK4SkEVuD4E7hrOCKvg9LrvC8RBGHBKV416zXJyPUGtket1XrWGnVW83Hl2XuhgvdVYrXixG7hYtLx33pFSwyFl2X2VwseCD7KBdo0wCkdf0AacFVPwj68nkRPYY/LVGmicYdVZbkdPCAIqj7VLsa2jvhtho+LTEUQap6O56nknhrFaQYkF20KnDRfLlqI0RmeuD54xKi6Wig8uOozWdM5y1jn+A9+5QGn1bSoKKKX8TUqpPwb8HcBfUEr9/4B/rJTy577mQ/tcKxVhgx3CW8y2vgVr3goWFrIGU71pzqzE1wOvAt33E+kZJLp/1iYkxq1b2ExfzDvQ6WOx3SkBna+GoyTUGdhNhbHG7ekg8VyYRoaiNFrLREvysVsasvz+whWMNsSQeLaZaHaFWMzdYAVb5a/GCkC9dAZnoXWOzhae3U40TjPEjFMKtOFyYRhj4ZNrj1EFYwwPl5Yfv5gweuJmCIwx12OUwtE4S+sU+60wSUOBED1Kax6tWkKdyLRqDcGL1G1KtTkRI91+4tGiZbMLjCmzaDSNySItVHDROYZciCHzInrWraG1BmcdU0xsowA9Y71WOQpoMhlYTV6MW0Pig8ueyQdiqIB4SmilWJyJZ8PVIQCKviJq21H2JGfhwcJxPUQuF5YntxO7CvyYqlUOdcrp1T7iAySdKAfPEDJhggfLwHvLho1R0mgoQBEfJGOgSXK9xphkSMa9eykhhcmcsEbkXolBWNKNk6/3U+F8qYRBGpVIOKpMqG+gaS27GFFFwGZXO//nS7jdv1ogfVahOXfzZ5NckBxkbY9jst/Ut/RZCtr9lPn9Jxu2k+e8775NMrZ/AAGR/hbgjwP/R+C/8PUe0q+3tFZc9A3vrFt+/HRHyYWfvNjRN5aLPpF85Ho38XjdoUvmyWZinxLOZzY+EpJ4jJ13mikYGpu52RcBmhDQ+L5vTuHVJnBCnmF488TMb9KKfD4D769zNTXvtvrYCH1bSyGf3xfZb+f1WbHj/s/vW5BoxP9PWylmjXr7QOKs9pgl5XM9NpMuGlNlvEVy5M9zD96XuG88rIvE6IWT+PjrXoLTc+A4Nqc0x2N0Fi4XhoerhrOuZeEssWRiKtzsPYmCs4XdIZNzQmnNEBNqykwp8sOHK94762idIcZCYzVNVLx/vuInz7c4rblYWpTWXO28+BemxObgsc7ROWgbhfaaZWt4fpiqTUDhsW745fMB91ijleFqv+O8byjAO8ahoubRosEnkdKGJB6rH1z0X4mU7bMYSH8cmbp2AfytJ9/fAn/mrR/NV7hyLgw+8XDd8Hhw+OC4GSKpFDqn2QyZxKsP8h/F9TYCyZyQzV3oz/rdz+owrJx4ZnzWZqKR5GpOvuYOn6l09ouF4eUu3V3DWRde6i6qnQBCbfWpCVkO0FcwLCX5r9S/7Tsx0Tx4oYuXLIasucDH15OYuXLc2D3cRdEOuFhAPPwqnXhmSM068Dn47wt0SV7zrFO0ztHqzNNNZNGIJENr2XCsnhNQAUVKguuhsJkGAWbqCVraKgnjOEnjbtR83VhyEapm3538DjJpLFcwbQpRxiqHhJ63DK2EqaVlSoKp/NCmbrYx/er90SCAzRQEiHGV8bWr0pCQ4PmucJgmHq4M7y57tFXcHALjVER7bTKL3mELrBeWd896+lbx//2958QQIWfOe5HPpAJ9Y4g5ka1sajmLsWCujLMQj/IB0ZErlFKkqNjXQkzpKsMMcswTcuEMxylAiaOBYSwQgmigu9bW+7VwmCJFKRaNxkdN38rvnV1afFT8znfPyAWuhoAaIx+c97hvEQuplPJjpdR/H/gLwP8K+KuVUgr475VS/pmv9+g+fakCn9wO3Oy+LQK2t7PuYpE+gkg6Vw+xN1Sxc6k6syZftzJ1wME9Zupn7UHivXZ8rmztos5x0hiJLfvK3AjpyIrSCJAQdomiYGUF9FVKnv1U471RYExhCpnWakKC2yHcTcvstADr7545YtaEmNBJJqusOwdF2EJpN0ojShdaq1m0QnHf7AONK1wdIolIZwwlF15uB4wyKJ0xyuJTYgiQS2aKBaMytnEsGkVr5CyHrDnrWqZpy2EQKX5roG8sWms2Q+ByJdL8QiYVxXqpWWjNunMMu5HIbNCdaZ1i6SwbAw+WijEWplFi2tWhSsALfHI70VnDkBK3h4ntmOtUuzppzBYscL5wbIdUu8WJpdFMUcCg3QRaeWKC20PgMB33hJmFM/sVtUqu1bSXwQs+CuPi+e3A7ehRKGE+ZQF3li1Yq0hJ5NY+cCdBn81f71jI9b6Z6v465wa5wMJZtJE9rjcWmsIYkxgS179JGSYv4FGpkuySqutBZTHN0uzPWjNzNZ98DUffkEUj/3/1Br9Ii/xOawwpF57cTPyxd86/FfI1gFLK/10p5YB/HlgD/4lSyo+/5sP6tVfOBaUU563lZ9cHPrk5yPj1pXgaXo+R6/2G64PnevB0zlCyomssuwD7MHG1G1k6g1aG1ii8L3fWCK9b9++3+ff+MCRif9TX3BQZi+QGb7s09PGLNVVO1539Br+aY2cqOzOJ79t9RcfbWHPTfJbdtfVYspL4e7l0bIfAPhwbQV90ZaROSFpAndOJxr/OmvOd08/gOMquOwsPlg1903C2sFzvIw9WLa1RhFz46Hpic4gMPuFjwumCyrBoLOcLx9nCEnPhycs9D1cty9ax95kxRNadY9loXu4iq17hjGKKma4xrHpLSNAaxegLuyHwUS48XDYcQmTRWPY+8eT2wM+v9vzm4xWP1y2NMdweJpRS/OY7C0IufPLyQGMV33+4wGr1lUnZPhVAKqX8s8A/q5T6G0sp/8pbfec/5JVKYTsGfnk1MAUYYmYIkavNgFHlFYr+H+X1toLgfK7exuvtfGVFfcZS1K62OoJNCulGKwUvd+lXPIfmY+0b8YtoGosucHXwTHUM+91GwTGZcwBFAKehFkDOQGMVIRa28Rh8XrcKR1nc3D26//PM8fx19TN1Rjarxhp+40HH7RBxNsv4Y5vY11H2faU0Ry3Sq1I7JalC6qn6N8zAhqaOJC4CrESkixmQjawFcjgG11CPv7fw/oOe886ilSGViT/93TVPthMvtiOxJtezz4Yt8r6tkeLRp2OH5G6cqJL3fzEcN4MW6QSPlRobEviUeHHwvLtu8CHeTTnbT2BUQBvDw0XDb76z5F/58Qt8BB8LQy0s+0azsHJzrJrCy52AxM5IR8MYuYNKlsk3jYHJwzBF8iZyuYB1pzGmcHso5FrE7rx0vFM5nttVK8XSEI/dl5Qh5szCFRatY9kYtlNG5cSysSwag/eKVSeToKwp/PzFnu88WNI5w4Plt87b4q9EJnX+LcCfA/7WUsq/oZT6APhXgG80gJRKNRb+y4uAJL4LjdzTUy3E1wsNGazOr83YZpD9TWtOLCISSz7v3euQWLgrx69TPCbBljrlMx9j22kRNccYay0xRmyjsTGLAXcWgKF3isvecrHu0CWSD4quyQzhyMCcslS2j9cNTmm2vjD6wOATYwqsm4YXO48w2AsmJcLtRNdoTCkcYqZxlt0YmCJ0NmGsYgwCEhklUt14EHlUiOKDYE3D3ntCspx1hfcv1rjNgWfbiUxh6SR+WStsxaVV+KIZfMRgyKpw3sODZYdSisMUMEbTWlW92GQa2X7KMhbZGJSKd16Ec/PAR0naQ0k0Gl7celKWvSdQmTMR4pMD7w6e3jkUipwyt1G83hp3nGpZClwd5Psge7ite1ajIRcBguZreV2BrFZDyIpxLxvJjx41pKKIKXA7yAQsWwH+rpHNs1BIY7nbYzNScA3pKJlvtdxDqcD1EIX1qmHVO26uR1qjMEYTx3zH4k2lAkUVAbUOGqXx9UN93nt8Zit76r5nqx9TruyyKj28sLKfzIDr3N0/6+Gsczw4kwlsF0uLs9/8JoNS6h/m1ZTxDPgD4O9WSlFK+Xu+niP79dcYEh9eH3ix81hnuOgtWvX84tmOJ9eRqSSGKeFD4mYfiGRCTIQMXQg8WLYMPrEZE9MkErfr4ZvP0PmjvO7AI75cnfM6Vu7p+nXaVHOcfFP9cZi765+yvsg4+9et0892B9ZXoC0X6FrD/nW+JRzZP+UzjsOo434cOBqIz+DPF702M/B2v/EVEUPydQerruHBsmXpDPshcPCJ77kenwqdM0Rd6BrDIUSU0igUi86xbi2TTzy9mfAxYZ3msjS8c9bSN5qPbg68s24ZfMRaaKzmOxcyJe12H1h3lsOU8QnWvWbRWZwTdhO13njvvOPlTmjV+ynyaL3kxXbifNGwbh0hFpzOvLNqOFs2Yr4PTDF+JWqGz5Kw/bdLKf8g8J9XSv3n7v/82xTwVYGrvccozeXS8q/9wcjPX+7xqeC/IL3+L4f1WQ/m29jXDNLpBdH+J4QR8jrEuuXEiLIcpQxN9Z0Yw68WKqcAzeTFwDn4QC5w3hk0iaYCQbsT6RsI8JOyIOCu6nl1hikU/KfsCubkNXbh1WO4v+bQapH3aI0kkwoZ6/7RzcSiM6x6g1MFnxU+lzreVQqJfYCLFla9ZjtmhkkKpVJRm0M9Jmuqn4c6gh4zKykh526MR3aZQpD41opR7YNlh7OK68PEk9uxTgfTLKoZqZ+OBug6gK5d1GUd93n6uvNo6dPzEhAphUIKClunR+wGT8mRq12+A6JMkdf4wYWDAn/wbMfVwfP+WcePn06EUCeqLTRjTAwx4728Zoz1fqmdY6XFx4J6XDMgqbXcZ9ZkhspQaiycW9iO0hmfqbsRyEpxtii8rIVPzPVcJyi6kEpGoXiwsNwOkXWjyaohpUzrDLlkdFGEUvjR4yXvnvVordhPX03g/4rW/xr43yFsozvPw1LKx5WV9I1frVV0jTqOj/zLZA1eAN8WQMnkwkP49AT4087QzLKAY7w5/bs5ub6fZGcquwORNqtyHGAxM5JifnOxXlVRLBrFpMAazVmnmVIkhCoXCIWxKQSfKMCq1TzbRsYgr98gQH7XKjb7xLI3PFgYXsTE4CM3+8AnyYvJ9jz1BvAhc4iZwyR707IVn6Ep1yl0UyEV2UsMgI48XjYYY4k6cusjoRR8LPQq8XyX+c2H8O55T6ijeJ/vPCFnDlPm8dqw6B3hEOmcwhiZ9pKLQhvF5DOhFDH1TVl8BkOhTInOZJrGUrIMimgqU3UuSBwigR6VmDZPXuLm/WsXM+yDXI1lazFG4SfPojUYCj4USsykDKWCIXfeB0XAJWMgU+6KZcexwFAKHq4tB595sU/sfcIZjXUNapxQ5cgaXzYy1v56N1Hw7MZXWT653lNoub4WOFTKhlbw6Kzj955uBczKcJgy+wo6tfXmklgvBZLSoFXhEKpvYj15873+eZ6diaOMbaFF2j0GkVwrLSBTbwTsUmb2bNQsu4aLRcP3Hq6YAtU09xu//sK9r//1r+Uo3vLKufDkdqQ1mt4ZSmUTrruGjY/cDBGFIuXM881ABpZOsZmkOTnpzBgGiT9FmoKzNcNfZr2Mb+T6so/W6bX7vGCNOvn3i3rUfhZgdf9YFNKsmd4Cu2r+bBrxLtqO4c5yw1TP1ene7897ScObz81UBJTqtOTkQz5+zo4vbqx96vN4mn80VD/VpmHZNWyHKEBTUZwvLIcQOWsdsTjImsbK03mzjzijeO+ix1rFZog4q4hF/APXveOveG/FX/zZDSnDJ7cjL3cTY8gMU+Lx2YLGaopRPOhaznqRfG99Ru88Z21Lawof3wyipnCG715aXu4m3jvreLdOcTzvW9adI5fC1c7z6KwlxkzjDDHlr2ya82dJ2P69+u/9wP+5l1Lqb0am7xjgHyml/E/f8Ht/PfCvAv+ZUso//WXf702rKHi8bnm5n/jxky1aZxqtUWQO3zoXo69+nZ6RzxuYvsiaJw3kIg/usppxv2nsZuJoWEpl9RSq51E6BqTT4z79/whc76tJeoHeyRvF8nqDuakIeASSvHVV8qY1LJg9F36VUqmpHdrPcQ46qr4d+ewkkWosWilCJj8xJcv7Zy37KbHGsh9Hlm0d06xF/meN/J1VcLlShAwxFSYvYAscvRx0Bd/m0zz/23D0InKIb4mtaFguiZQTBosp8GI/iLzAJ84Wjush3LGWMhWMqyydXGSEfZyObAQ4aqfhCLLNsoKY64jQKJKxF9t8JzPU9XcPEV7sA1qP3B48qWRe7BKNtWAiOcJmiCydpnMGZxQ+RrSWv53ZC/PFm03hqZ3xkOB6D8u+al+gmqcKaDmmIwiXgP0onhiz/AaO8sBQxHOLtrDoWx4sHGfLjnXwPN0E1q3h4bJl3Tuc1vz+8y1nnaN15isL/F/R+mdKKf/46TeUUv+NUso/dP/799c3YZ9wRvObj1Y87Bo+uT/P+4/wOqWGB4ByZAJ+3uWopsCnr3Oy7r+W4jik4HR/qaFDAJYTVvAMSM0/e1P3USFMQOsijxYdZ4uWVheebic+vJ6EmdhprNH87OWexioWjUMTsBouDCgtQwkGX5iM5+Gq5fkucvBFZFi+SomsgEepgtKqcAdGJyortAjbxiiZEDabhYKAMjuXUXgerFqcVTzdTMQMi9bxx99fUZTh8VLzbDOyHcRbKSF70WFK/M1/6j1+/HTLi11gM4yMWbNqDINP4n+AUOuvthNJifTPOUALI2mKMuygs8Js2Q2VlVqPUxWRgCekUbGdBGCPSUCneUKmU/DOumfZav7tD68hKrIqKKPYjfL71sq5Cgig9mANq64lZLgePCXV5ggnzLUkDKRSYNkqMhmtDP9/9v481rZtz+/CPqObzep2d7p7bvOaeq+qsMsdLpMQHClALEH+MEFJkAMSMgkYEpL8geSQRgKBUKJ0CEEaMBGkE0KxgoJJHBFQZCPLYLtSjrGre1Wv3rvvdqfb3epmM7r88RvzrH3PO/fec9673XGdn3S179l7rTnHnHOt8Rvj9/s2tlhQOaewReD0fDMQUuK69+z6w8ZAc3CtqxU4Z1i2htpYtv3AEBWtldwImrG4JOxuNJUmSpBC1h6Vldy0asE1JSf553/WnxfP2xj2CY6dfKa6kt8HikspcFoLHcppjY+Rx9c9f+AbxxzNHPkVSBE55//js79TSp0Ab+ec/9PPev/XIUc8L2IWJFxbWe4sa37lwzVjSCxq+ff5ztNWiu3Os+4O0gO5oCj3CXwvz9iVImFGipouf3oT8nW8GvGiSJ9846fh5RzgXjRfm/J0hxVfAAEAAElEQVS5AlnT1urHGSA/6Z7PITlvXdb7My37ipvXf1O2wyH7jFl8vpauQpCwY5TjLqzoEpqyLI/9i2t8Teuc6byTnEZlCzK5kkYRGmaV47St+WjdMfaeHBOLylIbzdZ71nuPwvDOWcWidTij2fWe23PHzBkaa+hDwIfIX/vRNdtR1vkhJt4+nrErKKRZJRq2t2Y1pwvH403PZefZ9OKCahRUlaWyltooLnaemTMMMfHuxZ6rvWcIiVvLChTse8+DTc/xzPHubs/ZoqJ1lntHzRfCYvgsCtu/V34+nfiVUhpYTA4KnxZKKQP8b4A/ArwP/BWl1J/JOf/qc173PwP+/Ze+ghcMoxTz2vG731ixD4FHmzn7IXC9D+x7z+8w3dSXipe5NTVl4ZN+fNK8ydtVCDqldQJ1HELGj+m5Tm2U1xsjiymfD1a6KUvn9LMS7FTNV0ncVABSoV897/puTnI9BdWDWDnXpbgxweNvxs3JfuqYT9DLZy9tQkyN3LhXCVInlfumNZzNLNflZItacW9liSlR6UxImdbB0axm3QfRZFKKmdNom3kyRpwrC33guvtxV6RWF4HALEgiQ0HfIPfmZF5htSGj2HeBPiYSYksRgF25+c8mue3Ni42HzkoxhHtaeNHAolDt0g26GwXO/1Srio9TViqgNeL29nDjqXXk4TrirFBUTptMQnPnqOJ6nzmaOVJKPFjvGXaHQtQUT7vrSjjIKmX2GRSZZWtIMQo1RsnnzkdYzTQ+JIayC66coK826YCsayuhBFUpknWFU5mdT1RD4Gjecv+oZYiKo7njtG1AwYPrjr/oz/lb3z7m23eWrwR9rcQ/DPxLz/zujyOL/k+Mr0ue0FrxM3dWfPv+kr/x5HdOAel5i9sXmfMnOPmEYLxZ7Jn+9rxjT9/xaYp49lwT3XUqRhWH9UPXFPm+WitzhiraZJTXHc/gpLXsfCTuBu4sa1CK0jTEh8R2HGXuaRyVVlx3GqtTQWiK1loc4YlK6HVPSIl1H9iNxcqY4sZ4Q9hzWpAua0oDQOauZQ1t0Uaa8ltdaNfdGEjAUTR0IeO0oa7g1qJCofjoaoc7nVFXhnWfsE5hNazmllmlsEaBNtw7MigSl11P5z1t7ahLvmydxjqKK5vCWEM/Bnb7JA0cZP53RuNcwiSZ+2NpNvRBELI+CxoplkKZdUI92/YZpQP3NTijuLVs2XYjF/vIdkikCG0t96OuoM2Sy28t57IJCJF3jhsutgM5C1qpMVJEMRq6zmN0hgCPLz3Hy0hOGq1EA8l7eV6dh9R5chLnUVUomYtaEHbOwr6DlsiaxLLR9KUrZI3ici+U7MrJNd2M6XOckc/dlCP7ApcLpTM+0eunz/bLbMQS8rnRhWo+mW04JZpHTVtx1LakJKjVo1nFo6uRR+ue3/3G0Que5asPpdSfA/4o8tH7/wGPlVJ/Puf8T33Ke74WOeJ5YZRCK0WICWs0d5aOzTDSjSNKKU4XFZfrjscbz0BB9/nDOqhFkBSzG8LDGflOvmZG/M6IiT58EzF5s9H7eUbIcNKA04o+Z0YPTTg04af8Cy8nwD4xHUI8FO8nZ2sVD5qvRpe9RslPQ/nbhESacv7UkI7xhmacEu05ZRTrPr8QLv9Ii57jpJ2IlmNUWq61j6VYpzSVc2w7T2MtPzzfohV0PguSyhjun1T8xkeeurJ8+7hh23ta5zibV7yf4Wo78Hjj0UpzPYyQFP2RUFW9j1x0gcoIw+S0dmy6wHfvLTiZN1RWcbao6YPnNx/uqI1mDImZNdxdNtw7FuzuxbbnbNHy83eXBBK7PrIbPA8uex5ue27Na1azitOFYvCJt45b7BdEcf4sBBIASql/C/gnkPv9/0Vc2f7FnPP/4jPe+rcBv5Vz/u1ynH8b+PuAX33mdf9d4P8G/KGXGPtLhdaKe0cNH15l3lrNeHTcc74ZePf88icW+fqdEi/DMx0ocP3n/C0iybJ1Qu8ySSazlBTdEAVi/8yMOdGEpoJGVSYdV7q6x3PLbh9oM1z7549zmmQcMokcz6ri6vXJnQHFj3fGoSyq1fPhpfPyhp5DMrh57mUli8KpcDIljWddjAZABbjaRXovtvRHdcsQIiFpdj5Sa6GzWWO57hLz2tJWlpyDiJ2mxPHKEkIkKU3wkcaKFebTcyATuTZwNBPhtphLwcPI5qetLKdzx8W+5/G2w3uhYfXe4cfIvssMn/C8b8aEGNDl3NO/pwl81SrmlWYfIuNYrKcrQVrVTjYCNwXuGy16HA1Qa3E8IkdCAKcz1laMoxfdopwZQqDzkKNCI4lnom2AdJ9t2ST5UqFc1BCzwhlHImKVUAua0iXOKXE8dwzWi8uP0XQqYfoDeisji0JnNY1RbPrAqrVcDp51Lzbf/7mfu8PlZuT9iytykq79zDkerQe+eWvxGXf2q49Cb/4HgW8ppf7MjT8tgfMXOMTXIk+klHm87sm/00SQfsJ4dnE7LfqmOfuTOqcvsui7OZ9MUHcoLpWIbbr18h01RmNI1O5AgXu0CSwbEaX80ZM12zEzrwRZ1QWhsirgo+uRVaulu1kptj6LGytF5N/Ah+uBW61iN4hW2oTWmuaweVkQd8i8XVspRJsCy2wq87EurKHo6VBoTwZ2PmEydDEyN4bHm47VzOJj5slm4MOLTtxZnGIIsNkn/DjyN967ZoiZ7z9ai1mCyqUolhkjbIeATxmLwlWGRmsu+xFfOrptrUhJXusMrBrNpkuEfCgCKgXzRpOzaBjNjcxnY4bK6AL910+7rDlnrnuPypnWQjQ81b6j/Fw0FmsNmUwaR/pg0drhzIDRYJ1hbiOuCIpmL5sAH6C/SqxmCaXgaiuo4ohsCEDQVMpYrIrsxsxmL/e+D7L2WMwsKUWudgMpZ4ZRBLs3fdnkOEFC1fy48xWUzY+W66isUPP6sgHTWcYxrSkTh+bR85pI0/dhOsfOCzp7+r1TUrzTBsY+MbiBunJUVjNzhp0PjGMk5vxii/mvRxzlnNdKqX8Ucen8Z5VSn4VA+lrkiOfFtLf4wZMtP3i85Zd+cIFWilurmjtHFQ+uOqpKy5qFg/DwFE/XQvFA0XW8GIr9dfzNEYai78dhnawolNuCHP28iomVlvykteJ2ZXgQAgMfz0+Kn+zzN8YDNayeDHzKpDdR53KhoAslq+TTG/qrUxFpKqJVCrIt+qRlj6d8flqA/aSY5tFFq9mNctIYpen0dG9WcspMw515w3Hr+OBiz6YfCWhaZ1Fk5pU0Xa73oifYWlkzHM2qIlmR+datOX91N9LHSGsyZzNHVWucMSwr+OUnO3JK7DLcXTZkFHVhSNxa1lxuR0afOJnV/JG/Zcl2CPzg8Zar/cjP319y96gVZ+nK8ge+ccx+zNRkNn3HB5cdzhqsVtw9arjYjdw/bvExf6Ho1BfNOb+rTPj/EPBngX8aKSR9VgHpTeC9G/9+H/jP3HyBUupN4O8H/i4+ZdJXSv0J4E8AvPPOOy847I9H4wzvnMxQZL738Fp4hfHgGvV6wn5+vCx8dvcJb7AInWkoX+BtgnoAnwJjkE23U0K7mp7FtJUzCAR9H0sBRsu/ow+iFTB++jhvVvZ9jOSCYpoXDYu1PyTyCSFVGTnfszHGSdzzIIgZKQUuLSgnkGtRWgpedXWwkp7uxYROujk+yu/HXODLPnPpM/MqMnOK9T4wM4rbRzOuu5F17yHmAvGvSFljiDgnNA1yZluqckoX+kGSY1ugqaE2GqMMi1bglLWLkDPOGowSx5txzAx9Yh/E1nneWtrWMsZAlXghBN+EIrA3/q0QGsC3by94eL0nBOm2dkG+kzGVMd94uBXS/VYps/UBqxWt08xbGIZC7xhHKqPZDj2bDvwIxhqM1TQ2sg9STDOFsjarobKWmALOWMaYGEOCnDnf9OQMy4UhhUxCcdxmtFZ4n6gqx9urGq0NV7sBheDRc5aEV1VwtqjoQ5auJNBUms5n9mPgNz685qP1yOgDM2dpKsNvK3jrtOXD645v31p83VFIfxH4CLgF/K9u/H4DfCY1ga9Jnog582Cz5/uPngemfh2fFTfnsk/rnL5IV7Xm0IH8GGIpHxCIlS1IzUqha8eYYRgiSiWCz+w6j9IeV4rN/U5yDkg+WRQ0zXqfUEX3rOvlvPMKZlbTh4SOsO6zoJ04dEpz+W+10NxZNHzvwR6Vpeh9NtdopdGNdAiNFQ29pRFqlEqwqmDRGJyFrk8MBeXorGijvP+ko6odswzLtiLGyIPtSKshI84vv/TeJXcXFY0zWCuaDFf7hFUivH97VdN7EZqOSdzFyIfNagyZ2ikymXWfcEYJ3aygiF1BVp7OLXufmSvpXBttCMNI4xwxJ2rrWG9HKqO42AW00iST8UGMLepi7KCUGDOkGHmw3nE2qxliJsaekA33l5Zt1Fgyuz6z6xLD1C0uVLohQ9wVqnGWDYkFbCkQBgWNS+xjRhUKkCtafGdLS0wZg6YfI0lJntcolm1m18nzHaJc93CjCjpRJ0OSY9mi/+dvoK0neuEUU+HTIWuGbToUkqam0ZTaJkFtgzS6xih/7GNBQKdAiJYwRk7qCp8yVU4o+7XODc8Lq5R6A/gHgP/xC77nc8sR5bU/9X5iipQyg488uu756GrHk92AM5qP1h39EHm43rPeBTbDjyM6pk1w5tDUq5C5yDwHxf86/uaMab+jEF2imEuxMd1A3/yUUSNNWZ9g3YNVidNFhVHhKb1rkqLIHHRnP4tCN31ml5UUwMcy5/qiuTrmwzxoOGivGqQw7sePF84chwJPRiieajx8V17kXjjgaAZkxRATO3+QnJga97EsLmaVIIR9Trx73nPnuGbbRx5vevox8gtvHeGBD6/2PNr0DIXO9u7ljkVl+fbZgm/fXhDJrFoHShFCpHZWNJTmjhxFv8gHuNgM1E5zuljws3eP6EPgybZn23lmleF4VrGoHfsx0laWvY8czWruLhtOZhXmg2sudiNHTcUQE90YOJpXfPfWgke7ke0QpMHj4xcugfGiBSRXbDf/y8D/OufslXoh2b7njfzZ9/1LwD+dc47qUy405/yngD8F8Iu/+IsvW9MAxCnhg8s9f+WHF+SsWLWG0Rue7OJrqOiXEApZkN1ccPVZaGEALhwU8p+NyEGTQCMUKR9hy0FrR/NxZJDm42LRIBPadRelcFhBoxW7MT+lRsxdEVoNUql+NkbkvM92kCbqV1WBH6TgMZaFeoXQISbY+3ScTwMVOuBsJq490QtnfoipiDkbBh/FxjeOdCOEHjb9yJ2lYdZUtDbxcBdYOXE0CvEw7oxsEAwwc4pVa7l/vOD20vEff/+CkDOL2mGt4clGdDfOt2NBi8lmLOwDtqCxUC+GUrvZMZioc1rBzGnO956UNVlF9lITozLgyiZmVslGIWXpMPcR1BgxMTKEg5Cts3Kd3QC5SuxGqK3hdC4uQV0Qwdm6C1z3FI0nOFk03DtqeLAeSBkYPQlFyokYM1bDdoisKkvIsGoMShmsSiQ0jbXCR/aZk2VDP4bifJd4Y9lQ1xV773m88ThtOGpnjMqzGT3vn+/YxciuS/RV5O16iY+Zq86TY/7ai2jnnN8F3gX+9p/wEF+LPKEyPLjuebR7nQ2ejZvoic/6rr8MYvV5MW2sp4Xis4vGgAgLz2tNJrNwFUYrdj5xvfciBp0kn0xF+mlhSvlpkfkklAJErSUXVaYUJDQoo0khoazMEZXj6UJ0yjUa6IbE2CbuH1csasPFbqQbRXx7Zi17P7Leg6ugNZrsEynBqtXsQiJE6WCOQYr8uyFRGY1SmbnVXO892yGQlWgBjVF0jJq6Yt153n2yJyswWjGMGa2grSK3ly2LymF0QpEYfZJiUmnzmnIhmy4zb+C4dYSUuNpHGie6FMrKXDcEGWPOmbrS7IeRwUecGmkqizIJgmZZV8Tco41CB3F6G7x0kWe1fDACcDVIcsyx53jW0HlPipGLDhqXOd9FRn8wXxjTIYeD5M9pYzIVLP14KDbKNUPbwEnrUErzZDewGwJjKQTOWul8DwmsyugMq1oebOflWU+f5QldN23mQgLjoW1BK4UymW3/8c1WayT/T4g1ZWRzaJI02Z7dCA2IVl50xVSjuLBFJJ+tWpg1hqsu8GQ/UPvE4vYClV8pnTyAfx6hmP2FnPNfUUp9G/jNz3jP55Yj4PPZTwDsh8D7l3vevxSnxCcbT1NZfEh8cLljP2QutkG+B59wATeLRBMqO6Qvhr70Or6a+DQto5vsg4wUxW+KUn8e+VQhyHmt4KjRrDtx+3r3cS8FcQTVP6uh68ocqiQvpvjpn8UK2YM1Flxl6AdZw/dIo9qV44YRYpmgVS6F+P6wD5pQmhNVXSONg326gUTKB2r7p0Vr4XhWk7LmctsdWCxIY7/VBRlVGtRdH3lv2OET3F1W1Coxq4Tzvu5GrnaRykmxuLKGJ1tPpUDPxaV6O0YebnpCymyHwFlrURpO5xUGRRcjpwvZxBijOJ7V3Jo3jDFwvhnYD5FVa7l7MmPbeXqf6ENi2Thqp7m7qAp1XPHmWcsvv3vFh6ojJUg588FFT2sN949bHlz1dE4aN/ePvxjtoyletID0rwE/BP4a8B8ppb4BrF/gfe8Db9/491vAh8+85heBf7tM+LeA/5JSKuSc/+8vOLYXiskp4Xo/8P2Haz662vPgWkQXJ/2T1/HFhufTkSovKxY3UFT/J0Gb8ocWSGXGGG+89rhoLkUN89ZgreVyJ/bEjrLAVTD0hw7s8ybvZ/89aRwtnTjBbMcg4qMcFpy7GwOfjjl112+io57a+1awah0hefDSyV21ltlRTYqRy13PphfKWU7l3gbQ28iqyewGWO8SqS7Io3KPJs2nqdN9Mp/x1nHL0aISK2OjaJQDpbFaEXPEU4FWgogqm46xiOzOKp5277efQCGcYrrWpYFsJEFpraicJaRIbQKbLOOaWytFmPK6uYHdIB3aptLYmDmZW/oxUxtBRqUkSdEqQbOlUjhbNJpZo/FRUSfN9SCTq7NwewZVVXHSOmprOJs7hpCg0ez6iFaRi33AKhiDYgiJMSVuzWdYaxhCYl7BbvSElEAlnLIsFhXztuLWXBwdtj7RGMvd45bdPvLe1Y59L+ip833GGYUxiozm4aajci2NMyjz9d8cKKX+Qs75DyulNnz8I6CAnHNefcYhvhZ5ImYRNm3NZ7/2d1rcXEDWyHd5ovfcmHrhxv/X/GSo3qkgf5Mu9uw8vIngiynCvBowumLdjaR4wziAw6J0mnsMMheaUijS6dCNVMicP6+gcZqUIyEKyimXC5tQKBZYtGCUxsfEdj/wjVsrGqMJWahuOWfWg+gdbY0smlFwOtNshoTNGZMy+1GuJwF1FGevEOXK+yD05NoZxtGzrC0mB5JxXO9H9qMU8XWGMWVUoVVZZ/lo3bPzCes0+73nug9YI4WmeQ3dkBkKlS8m6IMUj+ZWKGpRJ7RWLGvDdpD7Na8tPsPWB1SEqyFSj7AeIm+sWj5aj8QY2MdE0djGaZ46WSpgUcnGYBcE/XW+2zOvwTnLEANXe9lETflxmv0+aRMzFfOcEkTt6OFsLvQ/o2FWW8aQqA2s9wcR1lXj8DpRJcW8UZxvPVrBrlj7GGTT0uXDuaecro3k3C4qtmPGmUOBa1rHdOVNChF/raxQJbYDtEnux4+teQpC2Hv5jE7n1eVIj64HQYxpcRm9s6qwRr1SFLac858G/vSNf/828F/5jLd9LXLEzdgPgV9694KYElfdSEqJq8GjsxI00mVHX6AV/gU3GDcL56/jb564+T2/mYum/HYzni0ofhYK7eYe4nmRkOa4NCdgO6SnTZWcD833mGTu6zkghF4kErIv2CeY2YLcjGCTrAGclX2NtmLCEJC90jAVmfi4wHVdAAEJaSRP19bnw5g+iQ4MsCr7kYvNwNGqQinFopZcpwuyNOfCNNHlHBpy6RCMY6RZNOg80mhL5xOVk/3YR9fyhV5UmqayxGJe9GQ/8N6TPUZlKqXwSXHUOO4dtzRW8eFlz61Zxd4n3ji2PFr3ZCLdAKeLGmMybWV4/8mWIUoer41l2Vqsrmgay1lbEZI4qr150vBo3ZFRLGpHBNa9J1xk7i0bfv87Jywb94UzF14o5+Sc/2XgX77xq3eVUn/nC7z1rwDfVUp9C/gA+GOIVsbNY39r+n+l1P8B+H98ERN+zJkxRn500TFGcTk5nlW8e7Fn/xon+spGAq5jcbrhBr88Hxb6E0R4E2RiqS34mBnjSO9lsb8odi1dLwvMowq2ozh2VaWY9EkTlkO6ucYoKqdonCwQr/yPd5jg4xuhSSx2+r0zUh1vnOJqOzJGOJ4ZamfofcJoQwyZPmT6cOi4zgrkfe+h8+kph9mMAlvVqjgt6EOHva0My9aymFn6wbOOkcYptFbU1nK9HzHGMDdwrSLngyCs5pUmuARZoXVm2Mu5m/I8pk3jJA55M2pkw5NL5d86xfV+pIuwKhu17QB5CJiCcHK1oq0q+jAQsnT8tQVQItZnDOvBUxnNMCS8lgRkrcLqTIqZHDPrIbDtRmbOsS/PLSnNrHJc7gN7H5hVjl0fUSS2Qyr0OCkqNZXCaQVj4EnnubvQ5JT48EpoMyBFt6ygrh2V0eyHSBci3ZhonWZZ1Vzvdmg0OWf2PrLu4WRuWQ+R01Yzrw33j2aMXpLB15y+Rs75D5efy5/wEF+LPJGSPI+2KV/+1/Hc+KQO4FTkmQrhcHCanOKzFrvw8Tnz5vz9bPTIwT68SLxxHAhJCga7WBasz7w+IrS1xgiipYsFNVqQIqOXc+1HmLlM6wwxBozR1M6yH4MUkKcxRjiaa0I0ZCIPNh2LylIZwzunjkfrnhgTGy/HDxk2MTFamZtG8tNF8vQN9whc32ih6A7ec9kF5tZxMnd8927DDx5f8mTtGbNcS8w8damsy4G8j1iluO4GGi9jb6yicpptH+kLnaYpXV0R9BbUjzGCzNXGEmPkpHUsatiOCas1m77HhyxGFsYU1Gdi2/U0lcNpRZ1AFVvPmEoRLsk5+yQ51RihnI2I9bOOib4s4h2HIpIrlI7nhbvxWTEKGqtwKnM0d5AV+zGhlaYbvRgfNHC6aqRAqTROZUH5BM/g5T5qihNWOlhc3zz9hJLWCozKGCUoas2PF4QU0sW/u3R03mONwaiIVprLLpFvmHHMDMxrQfluCxouZLlXPsN+zGz7wJ2jijNjqJRlO0RiejVKDkqp/37O+X+ulPpXeM5XOuf83/uUt38tcsQUKWV+8GTL+XZAacUPnuykyTRGnmx6PlrvuOrlszLRKF/H67iJRPoshFn1GX+foi703mnFcrPZMtHLjmaKYchPaZITGmeTPl6MaZB1e6awKD4DfQRSQNGqmPHE9JT+O1eKIWW6UbQMpnMqDiLyFnmfLU2GkYOIPBQEE3LP6vL+SctWU4x2biCTaorJQ4JdAtsFxphpnGI/ZNkfjnA8L3k3CyV71din7s9jgBACc2d5c9Vw0XtyUswqg9GW7eDJyqJUwofMr3x4jUJxb+W4tWrZDoFt57lz1PC3f+OUB1sx7LjuIou5IoUsOkq1wynN6dLx199f01hPUmLgs5xV3D+q2PYerzKPrwfmlWHTRVat4+6q4eHVwOV+5N5xiwIebQfGILTE2pkvZd/woiLaNdIh+OYz7/nnP+19OeeglPrvIHBVA/wbOedfUUr9E+Xv/+pPMuifJIxSpJgZY+L+cc1ffW+PVvlpt/J1fPUxcV8TL48Imzo8NyfdkY9PfhFYj7JAn5lEVR0E1bpRaAFDlgJORKFNxgSZVPL448WQKQzSAe58ZjN4cbRRB+g7/LgddeLAxb15HMU0IQqKSBfq1H6IKAXfuNWSrGE/enbl/aFc3M1NyLIW+ldOUpBRFPtOI6KmPgA5ctUN3DuquR4ij64HHu88Y0hUWlM5xb3VjMs+sA2STEyEdZewBqoC2++jjGHiTH8S8sAg3QilIQZIDmLSJBILp2krxc5HcskyIUNTgdGakAJKwZHTDDGz7zPvdqOMo4ha91E2dyaJuK4yMlnnnIkxQ1IsKkdCM5QEtu4SyyZjTEYbgw8Ro0uhSBuCj2Q0R7Vh3lbSGRgNMYiA3qPNgNWJyllqqzjfBSqb2A+JVe3YDp6YMjOnqYwm5MS945oQMqNXhEGci2LMrBpH4xRvnTR842zOz99bUlevBhymuHP+pznnX3jZ936d8sR29HTj647Cp8XNovfNmNA5E0xc249ryMCLb6Re5AlMCJcA7IMgMJQRJ8QJFeXK4lqVRWbwMj+2tSYmEa4eoxQOJiSpVuBzZq40bVWRVWLXBxQi3FzlMt+M8L4PrBqorGLTBVTKBAzzlOnGyEUnLmTOSMEqI1D+M5fZdjLem/v/ulTM6ommW4SfFjaIvlE3kKJoFmlkATwVO5yWYkOIcL3PtHXmzqphXksxy8dELhW+iSagjOj5rLtD3tURrM7y+ph5uPF45DrOFjVZaVQS/aAhFlqcs5zvPW2EcQiiKRkPO4EQDro/Mci9mNXgYtER8pLrtJKHUAHKS9NDZUHuGC1mCjeFVgOH4xojRZamtlhtaK3j7koxby0/eJgJObGqLa0zZKXpRtGKUCrLecoHe9r0Bw7095vriIzQpK2Wn42TfKqe0xbPlAaO0cTR0I2RnITanNMzFJUs1wel4Fa0j3yW3I2S/JmS6O81lWbTyRu+7ijVEr9Wfv7Sy77x65QjQAqmF5sRazRPNgNGKZ5sRo5ay6++17Ht5bk8W3x8Hb+z40X0hKZpZCq2fFYMBTWd448LtDtkfbzZ56eIzknW4+Y5p5jQvsaIRt9+kNyYeH5O1kiz1mkxixjGyHaQa6hnGZtFZuRm3p++E3MHGy/IpSYdrncqMEz5aBIYX7SQCz09Z2EZqNIl0ln+NiLjzeWEdp/YRNiNYozQFBkRq+B01lBbw9VOaHwJxVAaI9ZqaqPZhkQImeOZsB1yilQaVrVlvffMZ47rfaCtjEihqJGQEpedp3Ga//evPeKdWy0ZhdGKrhgeeC/7kpNVxflmFLc6Ywg54yzEHNn0IykrjmdaaMoI0vRqP/DuxZ7N4LnuPIvKMGa4Pa+5vapZ1Y4H1z3vnM6+Hggk4N8FrhHh7JdCpeec/ywivH3zd8+d7HPOf/xljv0yobXirZMZf+P9a666yDdPG663Hd3rvcLXJm4WWV42pgnKmR/XKLoZ0+O+jtB0H6c5xNKBHkbQMZN1gX8WkaVP+qxMi8zkD93ym6ii502ecFg8Vvqg8VAZqCtLjEEWxuqwWfEJPnjSEbJQDOZtYtMdjrtqZexVkgLSdi+bECg6IKVT7coNHhNs95Hf+HCDtomLvee4sWJB24tOR+1g00cWVcXCBroQuNiXznfRijAGmizUwKagnII/FNwmOGxG4PnzCma1OAaQE33WqJIN2joRUn4qOK6RxXkgkSNcJ9EMqSyorEhZNmLGyOL6rWPFdsjSTdDiaHa6qpm1jtlckX3kwWakrURfSgGX+56TWcVRXaE0tBGu+4HWaToUwY/sI8xVzbduL8gZfvPhhm4IOJVEKyllYjRYYNNFvrPUzJzmcieJ7ve8dczVzvP9RxtUTnRj4nRWc86IVZpI5s6yYeY0v+8bp9w9qqmsflU2BuSck1Lqryml3sk5/+gneP9XnidSyuy78KnaZK/jMLc55HvdU1AbBSmikc30hOh5Hg34ReKz0EqTIKZCvnNCiRWUSVYC1/dl8Xs2U4SQ8YW6uh8Tm/Dj49LIMfY9VDqwaCuUNuyGjhRkM9/eKILvk7yWRqi421EEHkxWKK0xSugCk7uoRWD+YyqOcP5w3ulnLNehohTQYxL0T8oHd8rGSU6Y0Ke6FIa6KItro0XfrrKaTR/ox4g20I2JvizwnYMUDgu6mnKMDJddwuaJduCJaIYh0o2BW8uaeavZdgnvM5WFEAM5w34Q4SIfoaqlcDQUWuHkLOWBNhdzCVsQYAEsiVFBbRWNMWQViIPM7XUFrVM4pdmPkX1fmk25CKo70ZS66hO1ztxaNSgUMUrhq3EWqy3XfeCyi6xquH+6IMbA40vP1TagldANtZHC51QLqsqYp/Q/oZ50Lm5+qgh6f0Kr3mR4vB2IQdzaKoTKMaH1pvwY0wGh23meOvmFIka7dLCaN9LcUvKw7h3X3D9qv1Cnnc8rcs7/nlLKAL+Qc/6TP8H7v/IccTPGlBl94AdPtlRGM28MdxY1TXNBMxp2Kn7M/ON1vI7Pipvo2xdtpCdKEf4T/rYpf5ho4dO6esqtN7c1Gp66YW96Wf+nIHPdLv/4eKZi06zS7Pv0VCJDA5f7T6ZkjmVcZbvwdKzTMZ0WBNE0rQXgsitu1jOZE+e1Zl5bxgB9GOm3Pz6+bfz4GPokhSulxDAIH6iqClTgfD2iFSzaipjA1gZLIpM434rA9a15BQrZO2jF7XnN22dz3rvc4Yzm4aan95HaaYYEbx5XWGO5s3T8jfW1GIAo+MbZgrNlzUnr+PCyozWGxilWTY0zmtEHMnDcWFaV463TOT5EhjHw1967pnKKk3nD3Bl+7eGGk8YyqwU+8Xg3Mq/Nl6Kd+qIFpLdyzn/PFzqSLyEWrePv+Nlb/PA/3vKf/GjNbz/cvRaq+xrGTfjls9X0Se7okwgmIX22QPUUN6kV441jjsiiry5IohCy2LKHAyR0cgiaUESTpHylwLjD5uLZTVDFYXzT9YUkxZ+xrOQHH/BlER5uQDRrDVlLt9YPibZSVFp0WypgVRnWKhJGuN4eXOKeFrg4UAMqLY5llYmc7zyVNeyGhI+j2GwaqJxivY84bdBVZlG3vH+xJxFJSdxuRKtJc3vu+N7DAaOku3/UKh6v48fcJTIyJp/gqBar+j4mQo4cNYbRZ1LpAJzOBUoq2hyR2iqCVfheYKg2wvHC0g0eo2TDqBNshyKIXihu88Zw3Fr2g5diYNEoCTGjjbxOKyPUAqO4d9zy8GqgtZb14NkPEasMy8pw3DrurRqc1lxseja9RxnN3aWhC4l+GHFOE8bIekiE7AkxEpJi3Y8sZ477py1jSFw/3HDVeciJ43mNMoqTWc1bpw37IfJoM3LvaMYYE41+NVBIwBvAryil/jJF9gsg5/xHv7ohvXhkJXopIb1e9b9IZA7FB11+kZi04KDXcP5TMAFfBK0UgJkq2m5lNfrWrRq0ohsCj9ahFCAsq1rx7kUxHXjOsaa5eqIGdzGxcoqHFx1DkLmiClLQXrTFGTIV15k+sdSRGCK2MmQSxlhxVCsncxSEECJUevP6ps5vDHC2hN0oc/6EQlVKcoyPssCvrEKTRfzUgi/FO2vAGZntuwApBBpnWbYi/GkKvTcjRZKbj8dzKPQsKinE+x6iy2gT8VHee70f0ErRVIrdkOm93P95I0UxlWXhfoeC6i0uOzcX8iPSZGhboVJHm5nVljvGsE+JofPMHGXBntkPgRQVo1HcO2q5rkbGKN3uxgrCR2nN3CaGkFnve1pX0QfPg3WkG4I0YnyiG+HRDj64uCYBbS3PtK5EO7FxmhAS89KUqDScF2NGU+73GOR++/IZUE6cYJ8XY5SC41jWD5Nltkaci3wUiuOkSaKUbNxAjum0zE1tY5jVhm5IbDtPXCS2faCP8VVqNESl1B/8qsfx04ZRShBzWnHcVmgtuiiVU9TO0jhPzK93F6/jJ4+pwFxzQFw+mxMnfb/FtLFAWBTPe93NVc0n5dasoJuKQAX9WWmR8sgc9i+U8x63kySGxutIYw05Czp1/Rm5f9o/wQH9G8v/jxOCiI87XAL0wzSfJk6XhplLvHfxfGTLhE7NHApsrrAbrnae47njZOHY9XAyQyQ7anHozDlzvk+oDLeWjlml2Y2ZZWvpxsi6H3m07dn7wJON52hmsUb2G3dWDT5kHq57ujFya9mQcubn3lgxqwxWaz646njjuOaN45bGKB5tRz667vjoes+3by14o5mxD4Hz85GLzhNj5jt35pzOK5rKgoLf+/YZV7uBhOLWrKKtHf0YON+OfPf2p9//zyNetID0F5VSvyfn/Ne/0NF8wdH7yEfXe37loysutx3j+Nrp4Oscz27jJsG5aSKb0EM3I+QDReynilJEiVkW88Z8nDt8E0U0ubMoBHIfb0ycN+fQiqL7kwrv15TEkECVjYgpJ/HhhutLWdQ7BbW1kAN9gOtOYJm1gvunFcYoFm3Frvc83AZCko6qShPF63C/5q0SHaggoqqbPkphKsCikWJWVJn9MJAohZ+QGGPEIovtkGRzEGvQWT2lHxitiTmJzTZyEZPotqPYb1vLdT+KNojKXG5GnFX4JEKolavIRMYxMqsMrbPMlKILvXTNI2w6/1TXoxsi+yCFpbaRe5g0DCHxvY92hBSZ1Y6jWjF6ocOdzS0Jjc2ikdY4Q2NMQbEl+jFjlcY5BUqzGz2b3cAuJG4tGyqj2fjI+xd7nFakDG8sa8aU0Uqx7UYqq2lqQwyJD7f7MrDMoq1Ig6fOmu2YuLWouLOquX80Y9lW/K3fOKFx5kuDon5O8c991QP4acKi6MapEvE6PituFmFuigwPQRysXtQU4Wa8iEbSzWi1IEbwBbmT4PFmYNE6NmOQwkyEYYxcDump+PfzYjpvBFolxZD3H3cMXiixi1qx7rLoNHSHJkVAPjK7LmI02JRonCV5qLXCkp/C850TCpvSQssqTJenC92AFHZcaRZsi/DnVLjQVdFoSJkYYNkWcebactkJCiimxLK1goixBltu0LJ0JfccdJyevX7LJFQquUFTCiW+uANFeLgFR+ZkJvdeJXnTGGSjMeXCMRyKX3UWtNEY5TgzW/KohqO2Ytk4tkOgspr785Z1PxJDImLY9yNog06CVrJO40ZY1S3HTeDBxrPuEpVOQmUg8e6TPbeXic0Q2Q4jOWUyUpAby4d1QsjGgsjy5SGplFnNNN84bfmtJ3vGMT+loyuk2NNUQhs5iNEqlJV7dvPzZZEC4rSJsbaYXZS/DUHQZKmsCfa+0MxL8woFRy1ENDFJTrHWcLac8fbZgkVt+f6jPb//zUT1itCdgb+qlPoziJD2zUbDv/PVDenlIiu4d9QwcwYfMp2PGK253PUsaselHlE/0Qz4Ol7HIaYGcGtLfkgyN/Rl8p5pcLX83hqZT56XP6f88lkx5INQdUKMceY3dEFuzm21KnqoMWEJdD3scxRdQf3ZJhrTPqpB5uIpH00/GyRnhEJZm1w3d2XjFxI8vO4ZQ6b/DF7U1LCfGCaLGrIFVGLTjWz7kcFnKhu53mdCyFxuR44XNaOXpoTWiqtdz24YiSmhtWEMkasYCTFD1tyaN7SV4dGm42LjaazlzdOWSit2Q+T+cU3v4fF6wBnNrLLcWmTev9yz6z273rOqK5TWXGxHxpQ4aqzou+aIT5nbRw211cXYI9Nax/Hcshsi191IZTRn8+pLQaW+aAHpDwN/XCn1AzjocOWcf+8XNrLPOSbRu1/+0SWPNwOPN57up64yvI7PMz5r83Dzb89yfaeYJsqftojUIRuI6RyzG7S4mwWkm1S1z2JDTvoatjjFnM5k0a+1FGiMOkDbl046tNM1SLcLoUcogXDm8nuj4Wo/ctQ63rqzABLd+9eMXjQ7Nr0smmtdFvcJYsiy2SDhrAaVqYwUZkZfdIWslU7CIBc/+IhC0FIxCcw+ILSI9y97WgvLWQ1Ksek881rjNKxH0UyaWWitIimN1lFcDFIWB5PSYjmdOXxOVFZz1Boebwdqa4gpEWKiUYV6UdBZ3ma+e7bgfNvzeD2gjaIxiu2QGGOS+5dh1ihSivRes6gtrUtYa/A+c7KoOZpX/J43j+lD4rvVgs5HYsrFctPRhwwRdiHy0XVHWzkSiSFEKgVnC2kZj1mxqA17n0FHFk3N8cISU+L7T3bMKl1EZQ1kaCvLrWXF73/njBgTzhneOG6xRmONZgjhS4Gifh6Rc/7zxaHzuznn/1ApNePFzTy+8ghI9Xn7et3/0nFz/ut+ivrbhOh8Flb/vLl8oQUxMnoplE96dk86eNh5LHDSSpFmVyi5bQ1++GxqwJhF7y1bGUAEnqwP75oWow2yIIoI5L5NsGw1uxF23pOSaBrogiTdlnPXpfCVyoVO15eB617mysZJQyRGGbcpKKNUpoJZVcRHo8KlhFMGn4RC1ziDIqOyog+ei70nBpk7FzWkMg6tZNPw9LqBGUXbpyrUiFIUUcCtBq56ufarXuiC21GQt3t/uDeW0nhBmi+VKroUSv6WszyzRV0zb2R+dcaglGI7JirnqOrMw81IyLHYFcMwJvaXPRaZGzOHgkxIQiXrMuRNYtkEGqPYZ0UfRMx7eA69faJZVlroEcumRgE/vOgxOeO1HLcyRW8qw8wZKpdJPrNqKjZ9xKUgiDhk/WDKc7aF6q3Lgy5gZqFL5oMAd+3kvg9RztcXJMB6hGWV2I+ZHsXRXHPcGN4+rTmZtTza9HQxUr06U+0pcA78XTd+l4FXpoBklKJ1lsWx5day5sPrPT98tBXHRKuYVZpbC8XVVrRn+s884ut4Hc+PgBgAgZj7EKGKIrh/Nnds+8DVUAwZnvPeSYT6RfdDk6THpHXoC4XW5UNTyCD7jnUnPLNrfzAaqsra/EXAGRn5bjw7JzsOmnhj2RtpDiCCpoxh1wsDQ30KTz4hxawJeJAMrPvMrFbkpLgePLshMYygdH6KBPUpozvPvHVcdiO9H+l8oq0qQHE9BHKCZW1YrhxjiGz7wHo/EvK0Z8vsx5F1r/n2nQXnW8/cGXaDZ9E4Prjs6cbAj57sCCmzbB3LIui9HQInc8vdo5b7Jy3vX3SEmPjZOwu+93DLGBPL2vGduwt+4+GGi+2A1pqTmWPVui8FlfqiBaS/9wsdxZcQPiY+vOrY9SISHD6hUvs6vrp4mefxSRsAx2ER+dPGzUP4T/j9BLF8kcmyA+pCy8rA5T7QjTJJt0rg8jnJhmT0skGYO8WYpGg0BrjuI/UkHId0so9nDgzoQq0CgVcbqxhu+Me2TjqwRonTkHPFMriX74NxZRHdyAQ6hECKsKwty9aRUnwKt7/YjdiSVHQZzKKtuLsUUbm9ijRVze2lY7bzXPUDR21FU1f0Q2A3BHKOjDGKyK2GrBXaWuZGSQceWLY191YNH13vWQ+erOGNZYXVmhgDoehcVFZxPKtoKkU3ePpwsI2uHJAy87bGEAkonNF0Q+LWquLuUcPPvrHkaOa44xTnm4HbS8dF4ZFc7sXJ4c1Vxd1lwxgTD64Hlo1ca0ThY2Jeu8J/dnzzzpwfPl6zahU5JUJGeMkpc74diTmxahzL1rIq4twn84q3jlsaq3myHbizrNFKvTL0BKXUPwb8CWSD8DPAm8C/CvzdX+W4XjSiT/zgye7pRvh1fPkxIi4wTRGdnhaMz4ZCNuZWwyYLuvJZDb1JN6E2BfmCGCg0WujFcECG3JzTJyj9kMCNMG+L5XAqZgHqYNow6TBN55aivhIUyZCZW43SimGI7EuSqLUs/vf+UBR6FtF6XfLEohY0F0hDY14JsjLmgvgZQZFxVeaosfLaDNf7kbNFw3UfaKymH0rnOghiyZTFecpCW5vyl0VQMrtBEDZNJc9kCEXDKJecp0oRLcuzOl04Prz0qCznaZ2MVys5hs2aMSdcLAtrI3l633suDZwuGvZjYN8lrEqczWsGY9n3gccb0SVrG4PJsN5H2jrSGsPSWXbdQfewsoKWCsDFxmOMRjvDvXnDbujprtNTZO+z+X1MMHM137o159cfbNh3UZzgkriPNhpWrWHdR9rKcDy3rM/3PLgaaJ3kxelY07GNKY5BxbRh2mRNhhnTs7eFsjav4Xwo1JHyORw9DBaUymLNrBTvXe5543zGpks0laE1r0zxiJzzP/Jpf1dK/Q9zzv/TL2s8P0lorbh31PDgupcGVWUZE+xHWc8END5ljC3fAf+6iPQ6Ph7Pyz2fFg4p1mdKThxgDP5pg2ViZ0xuyFNz+yddzkyf192NBDxJeCRkzt0W6q1BijR7Dg32eWmMf9rn/pOufwIATIgqnT+ukbRoSgGrl3VAY8EGWN/oPNWl6B+SGDb4KI13p2RNcHtRc7EdyFnydXYFNVtMhhYGaqeZWcWD9UCaOU7nNUkpfPSoBPPKspo5KquIUbPpPV2RIKmdJsbMrLIsasu3b82xRvNwPbBorDR4gJASlTFc7Dt2Q+DxVjOvNGPIzBvN2aJCoziZCQbWac3Pv7Hk1kIEsz+47jBFfiFluO48d1fNyz3snzBeqICUc35XKfWHkc7yv6mUug0svtihfQGRMvshcdw4fjv1r90RPqeYED/T4veriGlBWJXiisovPjG/SNy8rmcF6KYNywT/z/BjFIGJxwyyMaiKQ5FV0u2m0ARMOfgImAB7lTmqDX2MTzu7qSxU57WcfDt6amv51mnFjy4HRh/wIWN1xjqFKcgKYxSzOpPKothoWfxfdYWG4WFVg9KGMMbDpikHUobGWlAZnyKNU4whU1s5VlQQg4hD70MkZ8XZomJWWdY7jzUWqxXei51yW1k23cAwFhqdgZwyth+5dzznZ85m+Cwd6FtLRzca9oNh20d2PrGsLRHHpu/ROlA7y3KWuN5FNr0gr56WXcqKfdcPaG24tTRoNDs/sB0EReS05r3zPUYrnmwGlDKctJZdyAQfsCjmteWHF3u2veej645h9MQUsVqc8hazijCI08IQIm1VsRkCvU94H0hZsWoN53tP9rAbA62dsXCGSmsSioudx1pNSnDUON56dehrAP8k8LcBfwkg5/ybSqk7X+2QXjzGnNj242viwVcQk0bbhGQa4qc3FDJSGG4rg1KR6/7QaZ3m3UnsuCvHqpCCx7zQyKao7AFl4zjQlKdj5aJX9NR++cbE/jzU6dU+MFZw3IrxsB8SnZYmAXBwTwPeumXZ7APnOzn+TRfRgGxEmypjyPRBEEwpF+RROtDObIbdGKkMnM0rYo7sBi9uaD5IwakcdyzFoFYXUe6ii6SQXDShcWwl7qTWwiwctPRMIwv3IQviylnNxVYgNjUHWh7ArIHaKNrKcrEVtxmHNCjmtUFpi7WW/RCYN5bej1ysB96/HDiZO8aYsUZc51KKJDR1rbi1kIX8uveif4dsVEIp1DhgNbNoo+m9bK9O5zXrXccu/Pg6RSENm/NuID2ETT+S9eF4+1FyHDkyRAh1ZEiO1cyyJuC0YoxZUL4KNuNhk9VWmtomscQuhaG2ghxl4xM1TwW2j2qYeym6gWyghqK7JXRATWUNRiu2e8+itvzu2yusfRGCyisT/zXga11AAmic4c6y5oPLPY82PY+uO1CZR7uR9x5vxQU4yFzyWej01/E7L14WwPBUw4dDgSjEQ86aPmNTHoOXL1JN8UkN8eftbabilVFCqfOl8bNPn3ycz2KbjMDtSui82ghKc0xSjNX50AhP5eIixXTgxti1guOZYVlbtn1gmyMnC03WokG0HwIxK07nhie7hNFyVTMnznHailNnYzVzZ7i7aKgqi4+JEDSnM01Umn7wPNkmThpLSAlbUECV0TxY7znfDcwaw9lRwzvHc946abi1qPnrH1zz3sUeHyPOGTSKISSchtbVfOduy+1lzRgyIQbuLBvOFhVPtuL6uB0itTP4mGgqy/G8JqVMX5ykvzYi2kqpfxb4ReDngH8T+Xz+X4C/44sb2ucbzmhurWr2o6f341MY8ev46UJz4PP/tB2WhZZJ4ifRXX1KKUtffBHraXeRA2WuQrR7khd+/LMQzgmlNHUfc1lYHJVdTijwUJMO91QX6PwYIWdNU4tDzXbImJTYli5xyuJIMAQwKLQy1DWkmKgt3D9u6X3gfN+zrB1ai5PNGONTTQ+LLKCHCPiEVlJM6oJcy2YfaI8MTit6EjHLQnnSnJLuduZiO+BjpilYfwVoo/Bd5HwXURiWrUUhDkFPdnKXRBfJMQZxwxG7Sk/KiU0f2XtYVAatZSzDGLh73HKnaslZcXtm2fjINUNZsMN+ECHZkATVsGxr2srQ1pZ1FziaWd46afnZu0seXY/cXTk+uB647Ecer0d+/o0Fo49c7D0+ZlLOXOwCIXnmTjjIjVVsBo/Ohn6I3FrUHM0sf+DtYx5e97x3vhX9pMHzwyd7Proe0TmzmjuWlcOHzD4klFbcXdT4lEkx88ZJyzfP5q/axmDIOY+qIKaUUpbPt477hYZSsN39FKrPr+MT46YY5vPi5lzZlsLFZy2wN3sYQ2TmRMB590wCuokKmpZRNzXlpjlZF7h5Th83OJjodB2HLuvTxSmfrDVhPHgthZY3jxf8xsM1tSmoz6JtFAqC6HITqZxmWSfOBzn/lEuMgpwTs2KPfNyKzXCKhdpWzjk1GzSZZSuaa8Fr9jFTucSDy/Bj914BbasYdhmrQNmCRgIWMym67AdY1oqmdth55nzr0Vqx6TONEdSMs4qYElaLmLkqqq6pLPZjgrXPNC7TNoacE/shs6g1p23NvK3xKbLuPGEvJbuuoIk2fUAjIt2qCOjN6kw2mkWjsdYxes9Ja/lwDE9RPRMyV8pOmkySz0lVs5pp/Dbhn3l403t9ggfrgcYIUizdQKv5DOtBnvssKtoQ0VncNklgS1WwMYZ+jEIbSUKFWC6KS1EvuU6rss5RcNY6zvdBNgq5OM5VmtYZHl15WivvaRsn1s/zmp+7O+cXv3XGz76xIqcvZ7PwJcYrcSEpZR5tBlLO7PrIZgz8+odXQkspk8+k9/FZG+bX8TpeNG7ubxI/rjM0UdkcH5fbmEIIWBJWibvap8Wzn91PenmfwcWDE/UnFRem78PNwtaUa6d5WJUXukrjlGUMgcZkRp9xGvZZctbSQWUdIQa2Y+a4OLA6I4hQaxTaao7njsZX7IZB9hg5U1nNotJcdwGFoJCoM2MShFJtYdU0jClxtmo5mTv2Q+LxemRWwS+8dcYQAr/+YMPZzPH26YL9GLjcexqneLjx7EYxZdAZnmwGnFZ889aS2hqs0ay7kbqSfdU7Zwseb3q+eWvG8aziD7x9gtGau0cNzmh8SPzye5dApnGWs7k0u40WF+hUtDsFnf3lODi/KIXt7wf+APDLADnnD5VSyy9sVF9AaK3QwI8uej64HD5V3Ot1vHhM1efPoxg3psPC/WWOd3Nh/yLFo5c9/rMxTXrTpGoQXaCr7jCOmZNJbNPLmG5ukKb/VwiNYd7CRXfoIlhk8zAmOHKaymT6kFl3mVxpfNE2qopLTFaQcqKLkboyzGvDZkhPKWDfuNXwZBfY+0BrDfsYUTkTvLjLTcWsvojFkjJKCXVCq4N43XU3cjJzKG1YuIzKke2Qn1p/qpRQzmAVWGt4sO744fmOlDPLyqCMFne6QVA2q6ripO3wGbTSnLSaGCveWNb87P0VF5uRD6/2vHfZ4UNm6xPeR3ySe9uPAv3UJtH5jCNjtaE2mSFl9j5RGUEcvHFcczavSUoTyNxd1kLzU5rrvedy5+lD4Ml2oNKKmCLbIaKzFNMWtWHdRQbvWXeRe6sWnzMuRjZd5GRecTKrMEbTVobRi7ua1rBsKn7jo2tS3hKjQmtJKM5ojIWjpuLbt+a8f9kzhMBuDPz8/Veyq/znlVL/I6BVSv0R4L8N/Htf8ZhePDLyZXgdn3u8zF3djC8mnOUR5M11L4vFZ5dLN/PC1DmFIlKN0Kx8ElHOyUq9vvG6m84100LJlq7ntNh9lsIckUaKzeJMsw+BPoiTi0YK7WGEDbKQ70Kmi1l058r7lT4sgJ1TzJylGxMmC/W2rRWbIQgypYwhZZm/VzPNvaMWawwfXe54tPZP0VyKA9KrsbBqHTGM+EI7m1A4rbPUBnIamVdOFvLGMneZb95u+NUHW5YVhGTJKXCxLw42StE6cbDx5YEPg2xwHq09pwuDT4aUBCG784moRnJOPNkOrOqKWWOIsaCrvCB6cpb/4giozKrV9EHRkFnVNXePK9B7caPJUrQygFKGN48q3r9OjGNgzJHaWep6ZNfJs57cf3x5NiQRWZ0tFJXR9D5+7LOQleTIcQw8iaHYWGu2XcJHcU3TRAxClVjUMKsMDuiQQtuk11HLreXxTugQVhUUXpac0I+Rdm5YOYtScDUEsooiFm4UjXU8uh44bqtXhub8gvFKNB1izoSUeLwZ+ehyzwcXHU/WPZsufgx19JMgQF7H6/hpYtI+eqqhygGt6kAazKkUW8bn75sMMCsNgZ1/sQKoLu8ZPkUDSZfxVeUcFEr4zeJRZeCotWyHyC6NGKVwWrGNma6Md6HgqG1oKvCj5qxJHC1bFJl158UYx0AfEttB3EizAu9F27TWir1PhJypnZFGvBWa9NmyQitN5z1Nkqa3RmOtuF3fOq7QJOrKcmdV0VYVtTOsGsvl3nPUGjZ9pDqqmVeWkDO/+XAjciC14WLvOZtX3F41pJR4/6rnnZOWN44bjtqK2lrO9yOns5pZJauP33q04WI70laG3TDgY+LesuHOUUNImUdrqWrcWdbcP26/FObCixaQxpxzVkrMypVS8y9wTF9I9H3gz/36Y+CwuHkdX6/QUBywXmzD8ezi/Vko5ydF5mBH+Snaa58Z04JcKbguxSOLFF06LwtBhXBxb3aMp3Hq8t4cnxHWLK+bFxHToDRXnSBzfE5PnY5mNdSV4bQ1XI8RXwi8Wlt636MSeO/pxpphCCxax71ly0dXA1f7HT5LZ9OGw32ZnGj2XgpHVRGnzUCvM0+249Ni7Kw2+BSeCnnHmOnHyGJWk0Ok90KDm9firqbJ1JWlsRqtNfePW5TR7PtASJHKaI6OGr55eynFnpjZj44nm57dKEWvmAuMFdj1gU0e8BlaM4jeBYptlMLP3ClMYziZGc6OZtxfNlzuAz4GtqOIZEPmuDH0IXF+vuW6tA63YyI/3KCtQZHE/SLJ3NFUMKs1ViuGANvBUjnNqnVc7kfIjjePWx7vBlZNRVsZFrXjD37rlB883rEdAts+oLXi0dVAZTT/yW8bvnnWspg3KJX53oMty9oxq190iv5axP8A+G8Cfx34x4E/C/zvv9IRvUQopbi1msHD6696KL+j40XmcMprRi9U3i7zFFXyIt8Yjbxe5QMydBLpvHnuqaERgXlxEZtyRq3lPY2VohfI3L5sobaaPkSePBqYVVAb97SYozkUsCajBg8srCA+VYbaGNrWyrw7RmqrGXxk3jhikAbCVMSaKHdGCYrqyWbguKlIOZNSYuFEGF5x6ExXDrb7gDYaFZIU2zIYY6kxRJPJWbHxnkTGDhprNT+62DGM4Ec4nmee7OV+7QZAZR7v49NNwMxJHkzAPkI1RLQShI0xmotdzzxUfPfOTFzses/1zgtVoVxXSgdUFgiaNSShs9XWcmc5YzuM7MdAP8JiBjOr2frEEAIfrgdqrfFKk4Ji0Vi2/SioaQtVLq4+SLOnsTLeq32mdfKwG0TEfCjX0o2Sm3OhpG2LG0u88Swsgmobg1CVawOmCKP3oyCbVARt5XjOFpOLLDTF68Gzqiw5KsZiIKFTIqLYjYnvPdjy83eOeeOkfUXwOi8Vr8QVGSWd//cudjzcDAU5nZ4i1l7H6/g842ZD5EXiWaTS9KUaEBOFhBStP+nLphCqdMgfLx590jgsgh52BmJ3kPe4ub+atI1AXjeroOsPdPHp2LY4US6bisvdSCSz3mdKPZ8GMRfornvaSlFrWM0aKmuojGHXB7k2rWmcoq4s/RAIYxJtwVYLPVrBwjnOlo6YpCExq0Abi0Fx0YkG6baLLJ0l58zbt1vurWZc7EZ89FTW8a3bMwaf6caD/pA1Iykq7h83HDc1+xA4mVf4kNj0HmsUt1c1RimO5hVns4rzradxhlvLGsXh4fiYON8WtJLRZDKP1j23l1Kg+u6dJe+czKRoZs2X1nx+0d3J/1Up9a8Bx0Uo9b8B/Otf3LA+/1iPngfrjk0XaWrFev+6J/BVxKcVbHpkUWY/YYZqSiFmWuBPaJ1pQvo09NFUMJrGADJZHVVw8ROyVqaKOfkwWRoji0TfF2pZI4v6bhQrzol+MG08xih/W1g5QFfwnykXHSeVUVpoCxHRQpjGnzOEGHmyyxincMbQVJb3n2zwCRaVZjdEfuvRhlltqY3jYj/iTOKkNfQeaiObDMWhc5tV0WKKUlCautYoqIzGWdj2iXmlWNbinONT5mxpebAecRo2MTNzlsooKpu57kRY7nQmndPbi5qzecuqqfjlH15SWdHC+N33V2QN711s+eiq57rzZKWw2uCjuB4YXTSbghR0rIOsBeI5JMgpiQh5A6vaUTtHToofXHRsh4BWirN5xdVuZDt6zree07njcjegs0JpWNYaYxR3jyqebAbGFGnrCqOkMPZwPTKrNI83I6jMZvA82Y5CV2gcWSluLWveO9/jY0ZpzTunS5a14298cC0WzTrzjbM5t5c1q1bz/lXH775/xBvHLYOPfHjd8e1bi1dJA+nvA/5POedXKjdMsawdd49a4HUB6VWJiMyVlQU9HuD7EyXtU2lz8eN06akzCgfL9knbwSgxHYBiK1x07FRJZhVSGIlB5vhtTCiV2IeEz3DpfXG9PBQaNv7juoH7IM2GpoZFo1m2lifbgLOKsbjsXO48sxoao6hNpjaST6wRCt8YIw+uOsZ5JuSE1pZFC1oH9sWuft5C5QzERI5ZuqpNhVaKvfdc9CN3lpajWcV6P6C0lsZFTLSNYVZHzvcQNpGURUNpiELPs0he2wbpWmdkse+c/P26g5OFprEGssIazdu35oSk2Q6eqy6KaGr57+bziYh76D4GjltDiIlH6555o7Facu9TAeOQ2OXIonIsZ5btMPLB1V6QQZV0q3dRGjE1gvqaF6HVeSMfBGelmKOQHJ1Lnm/MJHAuaOB9oUA2RgpGI7Ixs0YaRDGAKiLbqnTbG2BWyzO8HqQ45ctnNgObfSR42If4lGLpAacz2z7yjbM5v/7wml94a4X6kvQuvsT401/1AF4ktFbcXtY83g6kFHFWUVtDTXjNcHgdn3s8uyV62YLStPd6igDSnyz54ShGFsWReW5FgPpZNsUUNwsJ1lqMFdG8Z/d6U16NFNfULI3wZaE9xzKeAJAVQwzsR2FEVBya7Kq8fleo283CcmdRs+s8F2EgpsS8qTFaTHBE+sNLo0eBRir4xhjePJ3hrGLfR/qUuNU01JUhxgydoI5MVMwryxgTv/jtMz68HAraaOCdsxkPrwb6ELm7mvGHvrXCx8Rf+M1HqJyxxjBEaZ6su8Cj7UCKGa0Mbx1LIUrWE4ZfeLPl1rKRYppSdD7iY8JHAQ6czRzXfWD0iZAyd5dSrNqNgSeboTirisB/4754Y4UXFdH+XxZKwhr4WeCfyTn/B1/oyD7nqI3mcjdwse3Z96+LR19VfNadH+BplfnZ8Pn51fIWWbR9lijbpHsxjeGoOlgiPy8mAZdPmqQnmOisLl3FLAvpSbSVKIvOyspicjp/QBaYWouGUT8K2meaUJ9qcBSRUwodbV4L+mY38BQXve7BkKginDaJXedZj/JetMWHyG7vCTkzrxWjD6xmjrNFy37MZBVY5UTvJY30UYRDawdzI5B8ZcSGugKaSvjICehCZNlUnMxqrvcDYxJdo7N5xcwqnnQjKmd8TPRPxQAy88qgElQ68f7VyDdut3z39oqkFJfbkX03MmSIWfHGakZlBtl8hcyQIjFnvA/iemOFrxxjJiYRmz2e14ScUSkxqzRGZS62I9+81RKSiGk/WEcqrYlZ8dGmK04GmqoyhBRxynFnZXnndMm2D8QEMQaqynDvqGaIifNNj9aG2wtLFzL7MfDde0u+c29BbTX3j1rIirdOWu6sGh5ve967kITgrMX7SGxgHxPfbCoSI3dKR6KypjgavVIbgz8K/EtKqf8I+LeBfz/nV4cTprXiZPnluFe8js+OF0GHBkRbyOoDotQDpIOQ6BQ3tRyet8G7eT6PbPIzPBVR2vWSg5729pLM28bCcVsWt+qAnLneh+JmKe+bcs8k9g0fzy0Z6br6CNs+CgKGzKYPOKOZWUMI4lC2aivUkzW7AJWSHGIUDD7jdebxZo9zlqO5ZhgVlVFo7ZnVhlXlMFrRhcTD6wGDuIMtKgVeFV0jzehHUNBWiplzPFx7ul18aqk8NUKEvixaUlkd7uH0xe+Q5o9zBr2P6KSwRlFnoXcNIXPVjQwhsagtikA/fHxjM2liZC33cz8mEkIp1rphUQkW66pL6ByoS3Pmw03Pj656Ri85eMjgcqLR8PayIqtISFAZR1XBB096ElLAiykTi1NOc0Mc1kfRBWxtoi+I3crJ/Q+lwdNnsKWgqZE1ABk2hapuDHRjptcHCl1fPpwGQaapHMVNtHxmlBLdjw+vO87mlr2P/NbDDctZzf2jFmdeDcqzUupngf8dcDfn/AtKqd8L/NGc878AkHP+n3ylA3yJaKzhraOG33q05oMnO9Z9+DG9tNfxOj7vsEh+eppTTFm7f8p7ptyXy/uNBp0Ormo332uQvDZEKW4ftdAp2RvAx3OppRSYSvG7H4Lsecp+KHAwyFDlvG1xnFZAUErWuiozZNEeign6mBm8IFpjlJydKa7KN0wd5rWstS86T44R5zQVlozo9rVOse0DnRc35NrAZvQYhP4x+EhtHM5KkSgluN56Bh843w00TrOoKxaNFaRvUqSY0Fqx7iOrIbBqHSvlaJ0SCnfO3Fk0fP/xljYMJBR/y5tLbi8bzuY1l/uBh2spPp0t6mJ8kdGFiuyMJsSED+Ien5JosPY+sWwswSW+PZ/jjOaH5zs+uOxwRvHGcYvVigfXPe98CQY8L8OP+OvIXj2X/3+lIuRMVVnWQ2D7GmL6tY5PejzT72elsDJyKMi8SEzV96kLvB6lyv5JmkgTwkndeP+zx8tIF/ruSvNgLRMUwFzJyZYVRBRGZdpKMa80j9eRMRfqQpBNSC5uCtNistaw7aGymVFJkWoIh01GVSrwKouLS4jw3uXAqja0VqD+624Uyle5hsvdgEExxJG3Vg3LpeGyS+xUonYwqzSX23ToDqiisZGkeBUUXG9HmnIdMWXGkLnc9Vhn0DEyrx37IRJR9EOUDq8BV8HMKU7nNbPacNl7vqHnLCoNyvBbT3bMasP3Huw4nVvuLmq00YQYOFvUDCGSyTxZR9Z9YF5pGiM0EaMUQYEfM3Ul5RalDRnFsqmICRoSISk0iTFkfPTkuiLGhNeazX4gZvjOnQXzqmWMmVntUCqT0JzN5XhX+56rIfCt45bRJ646z6ZPWK1QBo7mFXdXrWwWBk+IiU5U0DlfD4IKMIoQM0PI7AePj4kfPl7TBXiyHbizbDmZOYz+coTwPq/IOf8jSikH/L3APwj8b5VS/0HO+R/9iof2QrEdPB9c7L/qYbyOEi/a5kmI0PHNwgz8+Jw+5Y+Kj7u1TTG9VyP6NSrfKEghBRJDEa1G0KKtKUiZUlyorWz+nZafTXXQwXv2PFPcpGJPlLTLPlGZwK1lw0c+klTG+8SiqnDO4lMma1lop8RT4elUzu0TLLRowo1KCAzLtqI2YK3i3qqhjwlF4sGVp9uPeK+pTCIGxTolVE40ViD8ISRxbzOHcQ6IVfPk6OmTUL264eM6f4ZJFD1yvNCcLSv2XijQtdU8WA+EGLm/ath6KdQPHlw6HKN2B7r3UQOVUXTF4fIc0VEafSJHQT9Nz9YaGdfkWKSANIoGiKsdy6Zh8InGaR5ddYwZwgBWy8lnE2o4fbzoqBHa4qISKpwPki8nyqPnUDyyqjjfaUVWmUVVrgWhAtpnVGpzubcxHD7DQ/lD9pBJvH+1ZzXCdox847bj0WbgHWdeFbTqvw78SeBfA8g5/6dKqX8L+Be+0lG9ZPQ+8v3HG77/ZMeD646ND/T+k1Ear+NvnvhppC8+j5hpME4Qq1CaqLuDq/Mn7aEqDq6jfSgNAFOK1vGQm3pkHpwKoWPRaAOZ35Y1kGRO9WnSYS00auCo1qyTaJDG8YDm9UizofNSdNJGcbt1XPcZ7z1KwbwSV85hCHReqN5mQndGMRpSDppRKHPWKGKC8+0OjUL1jpN5xcIanBG5iG7w3F02OOMxSjPExKrRjCGx70eGlDluHD6Cs4atT8SsuLtoaGqDUULhFsRhT86Z2lkxulEwhMTJ3HLdRc53A99/vON0XvF73jrmfDvyw/Mt33+042TeiAlD7ThDcWteMa8dKWd8zNyaVzxY96CiFJMUVFZjjeYdNeOjq57j1lFbw91Vw6PNgFFQO01lNI83A28et6ScvlYubP8o8M8A/x/ks/CvKKX++Zzzv/FFDu7zipQyH111LJxi7gwX/evp/VWIm5P0TZX+mH+yyfvmhmLqTvsok/H+E+gOAZghdKjrshFwHOCUVom9bx+y2FhmsZ1ctYqIZllbRh+ZVQqfBFnS1j1DJ2Jwk+aGo0Dwo1AC5q3oe6RcFpKluWiAqhb3m37M1KWzOUTRufAxUhtY9zIebaTwNAZPXcGdVUvXB35wsWNeG85mFTMXebiVzc+sBh1kwa+0JJtFpVnVmnUX6LP8PSvF6ayisnDVB6oMOWVuLyvqyWa4j8T9gDUw04pFZdkNie/cbjidw8nC8asfrckp0kfNbBCEVGsd6zHiVORJSNw/arm3atiMCW0tpzPF2aJm2wdcMviQUCkKlYDMRTcwry23lg1vnzQ82Y8MY2ZeKT64SigtXZU2iy10YxQbrdAxc77zHM0a2hrOZjVDSPy+t46IKbPrBz5ad+gQ+Oiq5/2rPfPacTyzKDRZZf4LP3uLy23g1x6sSQl679mOiVuLCo3iZFbjtGLXB3Y+8dFlx7dutSzahj94d86ui8xPxOHtzrJ+VTYETyPn7JVS/y/kK9oitLZXooA0+MgPH2++6mG8jpeMZxEvz/7+Zkzz9tQNfd5rDFI8ck7m4v0ondo9B/TR1IRIEdqCQMELEiiIFB0xyRz+WauNZ8fdeUG8ZAVXe8/eR0ZfECgE4jYTQmQzymJ8uo6p8JCS/H6XIz8aBfJiDcwaR9u6UuxSXGw9zlTUVRD9hi6xbAVFtR+TOEnFjFGBumhbDIWWZjTUSeh2Kos76KbPUsTiIAg+aRkFZOHfVIbb84rHfcDkjFWZhdVsa8utRU0XMj4Eej9iDSwbQUv1PuGMZoyRmdNc7SOuEl26i31kDMVdz8G2bFimDY+/8ZCnBs2EZn77dMYHF3s6n1jOKrTVPLga2OyFGr0PB9rFs9EFKdalXCykNZwuRN/vupNiQpjOP4Cty8JFKVLOjCX/Wy1NmokGP23+nv1cTIhorURD6ufuzrl/1LAfE7X5cjYMn1PMcs5/WX28OfLKIFVB9hQ/eLzl1z7asB8DBsOqMlzm8Go8gdfxU8XzqFlftPvzFAoxGWiizB21lYKIKd3u+BzB62l8lRFWBMhc2FaSpyoHvvs4Q2NCNoUorAeH7JViLo0EJSijrGBVa5hpQetn0WYNXaIximAOEhxTflg4mDWGyjmGkLAuEwdAw3YMNJVmNySqSpDhQxD9o+OZYVZrQshcqcCyMYwh81sPNqDgZ85mZA3XnWc7DJzMa1ROhGxRKtM6zX4I9D6zqg3fvbdAo+lD4vas4lHn2exGTucVvYWQFLeWFZU1vHnc8o2zObsxcrX3dD4w+EjWcKsVd+tu3BOzI8fMGBKV1cwbw71Vw6Jx7HqhmJ/OK+4ftfIeL8Wi45njyW58ms/P5hXnuxFbkKWLxvHGEbxx0tJYQ8yCSmor2W8BpJwZghzv6+TC9ieBP5BzPgdQSp0BfxF4JQpIsdBofITr18WjrzRexs705iQ9rS5s+W/3Eud8dqMwLdKmItLRwhF2nhAPf795/g4I/UGbSSq+ski/NdPsx8SmE/vHShdrzD7jnNgHJwWbMZOi6AClmBnigQsMMrmfONmkjBFiXzSQJkHRLAWmSRtpbhUG2A65CFgX6HyQSr2f3lNgpTMlyeZyO9DWGp1gCJGPNj2rxjGrHVYlLnccHGQaSFl0gLZdFHegUhHfjpF1L1SsmdPcWjYctY79IJbRtdH8zO05714qNnshGMYsHZN3z3cczxx/4Xs7rNEMSdMPnstd4riVzYExiTGJC09M4q5w/ygSfGA3Kq46T4qZ43lF7TSPtwOtjdTOsBsSKMWdoxZnLSczRe88v32xZz8GFrXj/rLlg3VPaxKDVzilsY1l0Thaq/nm7Tl/6JunOKtZ96JD8hd+4wm/627iw41nOwZU1uQEuz5y99jwc/dOcNpwue+4s2wYY+LJJpP7nnltWO88PzzfYbRM+PdXNXOn+fk3ltw5arl/NOPhpsenhIqKh+ueN47bL4XL/HmEUurvAf4Y8HcCfw4R0P4HvsoxvUwoDefr7qsexut4yZjm0BdpKkw0t+e9fqIqTUWPGKVAFPMh/zybuyIy305UIyii20leu40Hrbxnzzc5v006P1M+qo3oBOWsuNgPVErQn86K82SIid1QFv3phnYdBw2oCln4pyS0L3H5UhhjsDnTDWIMEOLI3BlqHbjqxDzBGXltYzJxolgF0XhKSZouQzo0Ulyl8REUIkq6rGBXLmpyOasQNM/Dtedqd00ETucVbWVJ24HOJy53nm4MxJg4aqT5MmSIKXO2dJy1Nc4ptn2i91u6IYquk5VnsGql2TIvGkwxgyk5p8+Hol9Vns+jTcfdbcX94xkPNiOL2khTwio+uuopMh5P3zehkc+WhqtdFEp6EgRSCLI5M2SyylRGEUIWB7nyXK+KnpLWUCtFDJkqFTfAKHndlLHe/ExO/3RaqJK3VjO+cTrjuK1oKivoXOVeJbTqE6XUz1AuTSn1XwU++mqH9HLhY+LBuidm+T7aIoAf4pdXSHgdX5/wfHmopIaC+IllTs6JSkO2UuB/XiU2IvN1Hw902EUtc2RtYDN8XFN2mvN8POj0TWyEyTwCDfOZJmSFUiLuPwY4XVjmdcWsEtfk2hVduCiOyK2FprHMa8u8rvngYsd2DFir0DnjrMIZS2aUHGM1lYGQI3eWNbdXDb/5cMO9ZUXvE60zOBu5vWhYtRWbMRBTQhuD1YpdyIwh8GA8uAUta8NRa9n7zH4YaZzmwbanrgzKSqNizIpbM0dbOUafSMDJvCLhZa0QNPsxsu08nU80Fdw7bkXXqTGMMRFjYt1H5nVFyJHH2x6t4Fu35nzr9oLKaHxMpJR5sO4LIkwofeelmBRiwhZKmzGiH6i1giR6Ryllbi1qHlx3jCXnvHHcfK1c2N5HnGen2ADvff7D+WJCZXiyHUkp0r+e3b/S+GnYg5Oo5vhMR/GzSoLPKyBNnUinYDd6WiuT5bPUBleOnxDXlKaIYQagsgrrHHOb2YyjdFpTgXsCSmdCjpAtMQV2Q8aEkRgPY75Jn7vqDxsck2XBuEllU6Pl37Nac9RofDagAp0XTQqQ1wVkcQ8C/0hGxq0Q4dXrIaG0ZvQRP5TusdbUVvNw40XE08imYzcWSsIo1fSYFXOn2BeBbMg0Tia0e6uanOHxJkqhS2uyguAzXUjFtj4y9onGgTM13ZBIKnJnZpitGjaj56ituN6N7EPm7qLizlFLJvNrH10TYqZxBmsNm26kK8J0rROS3nJW0xjN2ULTjYHf+8YRAB9uBrZDwKK4vaw4bmrePJ3RVPBwM7LpA/PG4YyhdpZ9sd1+vPW8Vahq1/tE5yP3ThbU9cijdc+m8xzPLGfzit/79gnfvrXkjaOWR5uBbozsNgKdve4Dv/nhNWMSHafFQmGU5qoPLCqLc5oYMz863/L+VU/jtMBak2eMie/eWb4qSKQ/jmgf/eM551dORzTFzPhK9cFfnXiZxsEXHZ+0yHfI4nZMgrK8ITX3Y4vym6ifkQOiafrP6YMmzkRpaTjA+DMi3jwRJh1Ch9tGsUFunaUPUuRpHJxUhjFGYkGHaqShkbJ0ox0fL5Q40agWZE658WtGtIZlbeljZPSRq97jQ0EWZSk0La3GOUPoRyoNrVN4nxkpxSPK+TVcdeB8Qk05oz/cmyl3FpkgdoNoEE3l8KvdSAiiMbQdAvt+5N7xjNoarvqRh9serTRtZTlta4xRnLQ1D67XbPrIfpSmitNCuZgc7bSSYhXIMxhvrPmeIqIy+DFxsR1ZtRVj8CSnChUOhhFiEcGuCkW8rYo+Y5KEakpTRueCRAa0M+zHyBDyU/r4RGebV/K8ks/o2rBoZPzHjaOpAtshkkq18mYRqUI+E9ZJlzqhsFozry3r3uOMKd3sVyJHAPyTwJ8Cfl4p9QHwA+Af+mqH9PIxjpEfPdmTU0aTebweeN1++J0bX0bxSFGKMVkK5z7CfhDEa2Vl3hufU8RMCFI2IfN8o2WenMTlDJmOw95oQizpQuWekEmB0tQe4Fu3K6wxbLqMNQlnFdckVnXNaVvjjGazH7ncBxqTGEKmqTQpZWmiKsXD6z3r4jA9xEwIsFKZhUssa43ThtXM0AWYVy3HjSFlsFpxtmh4tO2ojEJlx9Gs4tFmIEUpXN1pK8YYWdWOk9ZxvR/Z9Z7aGm4fN4IeGkRf0BqNUZrLbeC7d2tuLSp+7aNrfns38rN3FW+eLPnG6ZyzpYhT/9K7l6SUuN6PxJRxVvNoLfITb522fPN0xkfrnvXOY5QUnB9uB/y4JaUjFs1tGmfofeTBdc8YhA7bjaKtZJTinbMZ37694MlmYNN7tFK8dXLQNdJaxLIfXPeknLm9bJ66sn1ZueBFC0gfAH9JKfXvIp+jvw/4y0qpfwog5/wvfkHj+1wi5iwVSa2/NovY1/Hy8bwJ+qbWwidN4M8+86nCDmIjmaJ0d60+WEFPcVMzqVJCTTNKk3KisRWNhSc7/9SVJ4SD1pLJsN5nFk1gjIKZ3w2ySZkKR1PVP3CY9CtkUTo5oIV0gIrmnHmyTxiV+fadJWfzgR+cdyLSbUWs1I7yHldE8Noabi0b5jZz1Q8EH2icpusT3sMHlyPHM0WlRKsIQFeKTZchicDpW8ctjzcjWWkMkVVjCAnmjcWhebTuQWtapzlZ1DxaDzzZ9ORiK+OMIiRQOfPwemTVVFirUWSismzHII49lcZHwxzNO2cLTuYV71/uRTB8jNRaM4aI0Zo7x5azecN2P9CUBbVRAvd0zvIbjzYopTiuLa3TpbiXcTpgtOI79475+fuZX/rhlQhwG8NJU3HV93zvwTW/9WjL73prxaJyWKN453RGTND5yBAjd1Y1x3NHSprfeLDl9719wro4JHxwvef98z0Pr3uue9EaiQm+fXvGm0cz7h3XXG09d05qfuW9DdBzNHPMG0PvE2cLQ0qZR+uBb57NqfXXH4WUc/5jSqlvAP954D9USrWAzTm/ErywkBLDa4DqTx2agw7MFF+XvDsJ3E45wJXfFbkBxiRzpy6onUkA9NmY5vinaCUOBaUpD41JDAiOK6GldeHjRab+xphA5mo9HVwpUhLR0ocDqJKxJu0hi2jk3RxPRjYGCUEn7Qvipbbyt72HuBm53o+cLhoqZ9CdUPRqV/JQgiGKU+2sNjit2Y5etP3S4doSIvo8IXPmJdd0HApGxy1YL2igAZ4WVJKCVQWXHbSVNCdSjjzaR5IemJXq16KquXNUMfrEexc7lFI8uOppG8vxwsI64IsG1KqFXRGonrcwrxxjDnRdZlkQSZN2lS7POmt4uN6zHiKWzG7IaCVWzFZLga42Qs1TSuiJi0poDSeNIlvNzMB+zBitiVG0pozSOB3Zl/M1RrSbYkEpVQ5qpzie1dS15c1VEVt10jDYDwEzSP6f3OUW84rWKt44mjNrLL/vnVPeOWtRSvH73zpmVr+MnOlXF0opA/y3cs7/RaXUHNCvSn64GT4IAunJbmTwkXXnGV43H17HFxwOmcciRXetfObmZX5SfDICzinRTYpFs27rYdXIurmtE2kdxLTnRuQsrpo+HLTv2iKYHRK0lWU5S2x3EbRiXhlhRJBZNQ4fEicornvPsi3NdaMZQ4CsUSh8acyrJIUwn6BPmd5nOjzWKt44XvAzZy2P9yM+ZN44nrEfAiTDACwrzbsXeyqtqJzhznFb3Mo8IWpurxxtJU2Z1bzi23eWrHeBJ/uBRW2pjAalqFLmw6uei93IEBTLyoiIdmWoK1mTO6tZtRZF5rqv6X1kDIl5pVk04gAalebuquU7d5a8+2THX/rBObUxNK0mpMz/869/xH/9F9/hqg84ozDa8MFFh7Wat09mDD7yW4+2fOtsLkWmdY9Wigx842z+lJXQOCNN7pSotOg0fZnxolnn++W/Kf7d8nP5+Q7niwutFZt+pDWweb1J+FrEy3alp8XrtHBvtExIcKjMv0wXoJ26lEYW26l0cm92nCfzsIxMpvPKUjlDZQxjge1r7VjNRjb+0F3WyIJRROUUmfxUP6Iq512Xk0znapDF9aSpsCtIplmhDuw8WJs5XlTUWrP3QTa8ZffiA7StIcSIsTIp69I62I4jq7bhZOY433i2MZH8QVOqC5m6Mhy1js4HxpCpbGTZOLox4WPmjZMZj9d7fIxsveLOvMYqxRATl+vIclbx5nHL73/7iB+d7/hz13sSUXjQOaMz3FrU9CHRh8ztpeW3HnbsfKSxmroSV7S2srTOEFLi/Ys9j3cDp23FEBIK2PjA/dM579yac7Ud+WjMLGbCpW4s7MbEd27PaWrLcev49Q+vqSvDz91b8e7llv0Qud4N/L53TlBK87f/jOP9ix3ff7LlNx71vHXcsB0FcfTgVx/z9ukMpRXvnLbUVrMbAtsucHdVs6gcZLh31NCFyG70nO9G9kPk0XZgV+y77y0rHu4CWiuuO0/MiW0fCTnzzdsLTlrLPgQut4FQIK2vWiil/jHgTwCnwM8AbwH/KvB3f5XjetHwKT1f7OR1vFBMaNBpTq9VcRX7Csf0bChkbp476dTObSkSJdGKs6o4puWPW8g/GxPNFwQROxWSnhbOohQLnJFjVVbmdC3rVPrxYFmsKXQwJwUjn+DB1UBTHazpp9nAP/NzGkvrZFNALPbxFB2mKHnBKGlKpCx5zBlFNwxP7eedkfFVRm5AV3YMA6K/lJQc6ybdbmquhCCFI20/jjpa93K+cjug3J+cBCUbkiCPQs54H0kRttseO6uk2KM157uBq30k5UhjFZe7kWYvpEBtJMcSpUDT1IIWqp2VPJsV2QrCaVWcfTpfqOFZtEI6Mq1L1K1h8IFZZTBaoxB6nEr5qTaR1eBqxXFTUTlDTImrLrL3AZUjs0qLuKrRIvLqIhHNtkuCQirXjYcTEmdLzRurlofrnmVlCRGWbaYxlrbyPNpEKgczZzmdWe4eNfyu+0fUxjBrLI2zHM8q6urr31yYIucclVJ/sPz/yygRfG0ipcyH1x2109xZ1TxeZ3LMvDpP4XW8amE5MDCmmPKsQ+bmm3TZ58V1AjNIjptV8jNlaUa7ytBWgcaJwYtWIvA/IPTsSc9uovFaDWOQYvuqrTBzx+U+CvJFwabztI3l7eMaZQy7MfLuk448jqwWFTNjeLDe82QbyaVZ7uNBX28MmWVj+dbtOU/Wey7Xe347RaIyDNEzhsyu9zhryTkIjS5nvnNngY+ZR9uRO4ua823mUT9yvs7cPW5pK0ttDV1B9Bw3jrtHLUYpdt7T6MxFH1EJTheOfR/58LpnCHBrVXHdjfzqR9e8f9Gx7yO3j2rePG7Zj4H9mLBWc28pzZnei8Pb0cxxb1UDGqMVx7MKHxO/fb5hVjmcdgw+0lSmMKV21M5w3Fjev9xz2Y20VopDl7uRymi+cTZHa/UUwZSKg9u9o+ZLlbx4oQJSzvmfA1BKLeWfefuFjupzDmc0JzPHdR/ZvS4efW3ip6Wz6SLkGbVANy/GT59Aaw4Fnog4CWxL4WiXDpoUbuoYlvdN9IQEPNl4tPG8fTLnzsJBTnRjwKPpfXoKA21M2Twl2HcJ44r4JfJ7q8XBZnKTy8hk3Ra3gYmW0NSy+I9lcm2s2ODsQ2I3BAKZqjG4lAhBKGWtVWSlGcaIrRRaJWZNjUODko7CvkDyxwir1jBvHSet5clmZNMFYhRXtpAy89YyrwzH84pH656jtqIPke0YuLWoOVtYQlY4rbm9cHxw2eF9RJMJSTMkcdWZV4qjyjGGQO8DPhq+ebuhD4Ewwn6INCYyqwzjmLiMA85aFIqP1p3Q7ZyIlG470cpYto7TWc3p3LDuPNd9xKjIfFZjVOaDi71oFaTMWyczlpWlnRnunbTElDnf9dxd1qx7z3duL/jgfCsucZ2nsZbH255N73nzpMUAd44bvnk6Z15pKmfZlUSkjOFq5/nNj7Y01vDNsxmX26FsqBQ+Z24vKrohcL4d+NbZku/cXdD7zON1z63lilY5xiozxkwfxL70zrJ+ZeyZEWrC3wb8JYCc828qpe58tUN68RCr1K96FK9u3EytI3w5mP7nxE006lQPnFBHCckbKJmjq1rxxrxh7z1jhM0+iCVy+PQGR4toSBzPLRdd5HIvZ2wtuCgFnVzoTZEi6Fyc2VwRRVIaMR/Icp4hwKIt9KoiyD2vFGPIYl7AQZz6YwUkJUUprYTWMG9EyWLskhStkEKLraSQZYxhM44MPtGPUmhqnTjZWGU4PRVL4ZkxdDHweDdyvU3MaugK6mnS/CgMCMZQijmF8qAQutr0HKYNUAB0FMpcMatkDEkQYAa00ay9Z+4sRidCEnSSRvT+vBctjNNZzWYIKAONU+Scxc1MCXJqNyYCGZ8Vc6fxXqjVehSUbU6lKJbgshtxpuLxZkQrRRcyedKPKp+lRQWV02SfUC2sasN6VFQ6UxVx8T4kfJK8WdeGmDRVzqQq4fuDCYhWYFTiuBF016IWPZCjWeCH53uszdxuW2Z1YjdGTE7MK8cvvn3MkDWVNeyGyKPNwBgyP3f35b4fX4P4q0qpPwP8aW7IWeac/52vbkgvHpN4bVNblrXlt/uR9RBfLRXw1/FKxSd9tkoqQ+eDyYPlgIi9GVNjPGWoirZqShof4HoQxQGDJhtIMVE3MDeGy50YAky50AdBeWat2Q6J7SDOYKdz2RdYrdEW9r3nwVXi9sISc2Y3jCwqxbKyjD5wtY9Ch1MH2p1B8pmzhsZVGBRjtqSYeLwbWDY1y9piGsVv7gaUitwtAtWXe01lLTlH9mMk2oTOmpnThCxonWXj+OZJQ9s4kfGIib0P+GKfnZRm23Xk2mEroU/nDPPacd17fvPXtxijuLNs+GG/4bcf77i3ali1jiEE+lG4gak0y9893/F4PfD+RY8zijeOZ+xGaVRcbD1P8sh+TBy1lg+ues7mlrfPZgw+sR0C57ue3/hoK2hhpbh/3OKjGCaQ4MG1HNcaQ4iJB9c975zOvl4UNqXULwD/Z6SzjFLqCfAP55x/5Qsc2+cWWituzWvON/3XBkr/OiReRMPo2UjIBqUBlnPNdhRnrakL/En7loGPuyU82X3cdWCC3qd8GNe08ZheY7RMdo93I3sfOJvVzGqL14bzfUdVXquMdDhnVaEFFAe3WXH1MWVjMW9kUTtMukllo6CVbDRSEWOdbKLXXSTlTMyJfpDFcKU1HoXSuTh9OfqI2D1Whs1+JJEJKKxW+CybFY90vTOQU6YbI1fDSG2lozzExGZI3D0SoXA7DHzjpOXOUYMPiR9d7ElkrrrIaXFF+8HjPWhY7wecs8xqTcqZTR9pYiIrWDSahXN8586C7z3aAprOB2orSK1Frfnewx3vnM2pjaIbPe+d7zmZW05Mw8xZTuaOe0cN5+uR+6cNjVEsGkf/eMu9owV9N2KtpguRs3nNph95uOlY1A5nNMezhnnt+K3He666kVlluH8yoxsjQ9F4Ot8OjFE2McZqupA5X49srOE/+zO3+NFFJ93IdcfPvbFiVlli6njvsufecYPWmj5kfOmez13F6dwxhsjvfnOFNZqchU647wM5w91Vw72jBlt42fePXyltiyHnPE7uOkqpyTjolQin9esu8isQn0RXVkhhZ0LAuKJTE5W4qE1oqMZCU2tCgM2YUGpgPyRmlRZzg/J1m+b+58VqAbU17EZxEmucII5mlSPmSEqwbAwKzYfXA6kYEDgr+joTqmWiz03IoDzRvBL/f/b+LNbWNM3zg37v+E1r2PMZY8yhsjK7q6qbwrSaNqattoSRMBJgbsxNY2TLIHFhCcwghEAWIF8goRZq0W0JcYMQjXxhwG4EFjYyYKraPdWYlZGRMZw4057X8E3vxMX7rbN3REVkRGZlRsSJPI90dM7Za+21vrXX2u/zvv/nP9AFXqRs7kyyd5K6isz4SZNZtNyxaoCrNntKEPPgYZiYTnWAplTIlFi32edN5JkCrUukCG8eGd44qPnwekAryWGluO7ys7rx4/16x8Iq9cSaJfeVHfC2e49KcXNtmgy8FQa0VsQo8CEPP0LKccj59TrsNLkepqh7ydSvAvTOI9N02BAJqdUEzGmG0RNjZlMZZXBuYJjkY/OZRMXIMA2MkhSEkHh0OdL5nOIpRQbxdoBjMX24QkpZXuETj65GFoVkr1EUuuDZ9YCWUBqN84FCC+aVZN3FLH/XeU+wi76+bOHds557+xUP9ioeXw0YlYEwazXXXe6HpRLsz2qsEoSUDVc/WGfZhRCJUufD2cshYHtRB8A58E/f+loCXgoASYmcplsqwXvP15yuBnr3deJZvqpvWu163m5t3e0Id1Jsd+v/9hO+RbvaKTcE0xAl5e/oxkhtJFoKWpcDpyD3FClyL9sN35XMa/myNNSTlOKqHVh3I0Uh6cfIauiolMLFSKEl7196ovdsxkTvIaqR83WfBx8WhuFmIFGoPIQJIeK848MLR1QaYyUp5h5ltGQcI421aJXNuzd9x72Dio+uOpwPOB+JIVJay52qQpIxgIO5pSkMtZW0UiJ9ZFHBR5c9nfOkJFg0JePoGMfAstEczwt+840lzieq0lEqjYsRYzXCdcQUeb7qqAuNUYplqVlU2XqjKTRvHzfElPj7H1xwuemZV5Zv35nRFHrqeSPXnePeXkE3BDZ9hgsrI/mHH15nyV6ZtTHvPl/z2kFmTO2AbK3yrlUryeD9l5rG+UX7zt8C/tWU0v8TQAjxnwX+NvCXfzmX9YutGBOPrrY8X710vq7f+PqzEMIU0PlITNm8czfh/Gl1+9fq01p+ICeX3T757g4RI3nSWJhsOhcDPF/3WK25u7T048h5m43a3XgzVd75KmnytHem8yI8jPl2K24WUCWhLsAoRecC6/5G5lCQfTS6TX7ASmVKvpORwUFpmeImC35ylblWmz7TSjddnqxfdYHKSkqdGMaES7AsdX5iIShk1iXrFAhpArBCZD4z9KNDSsFHVwONlYQoOGwshba0o2PTO17bz9GU637EeTAmMSsNzgVmTYG1mkbAvNJ8dN1zep2dvM+3efq7HD3t6HEhG+5dbkeEzLI2ITTXnWNeaurCcFQV2etJSYgJIRLrzlNqwbPNyKob6VzijYOK7eiYK8Wysbx+0DCGiFbwYK+kGwPXnWO/tvzg4ZL/94/OcDGyKPL0YTMENtuRvcMZTalJIUeK/tbDPd672GKVpPeBRxctV52fDPkUi8pwd1mxGRyNVdRlwbfu1jy/Gogk7ixKBr8lAfPKcHdR8tbRjNLkiE4lxMsEHgH8B0KI/wFQCSH+GeC/Cfyfv+Jr+sJljUK8NGSvX936LEQyAYgMuuyAl01/I6urKzAum1BvxpiNrgFZCCqTfe0kk7cENzKt2yCSABYGNh2sRcgyYZmXz51vjh8FEUE/BjrnKPWNnGx02fvoRcy9yMCGC1kK1ztoSklhI8MA6y69AMTgZsPmARXyc/tJfrcbfogJqIoxDyq0gmoKYhhdlscOk+/EsrDUVtJ7T4o5pODHZ1suNiNGK05mhuAjanqNjchJPpEbI21js+lnivGFafhu1ZLkQYibRuJaZGYWQpAQKAWXbUTKzApKEkotKIwlpQEpcurPZkoXUmS2cTsGtIRlZQlEQkgMLtHUkpmxrIYIMXvVbYZJwidgURoGn6h19j5sx5EhZVDHiPx6dj5oO8aXmNC7fkhImfu11LDqPbPacmdZ0Y6Rykxx00IweEdsJUaLLE8eAr1PDDGzngT54KWU4GrVYqzGR7jsPLIPpCQZXJ7Eh+C5dpLff3xJaQyL0qCUZF4Y1oN76eTOKaW//lVfw5+lpBTcXZT84UdXdM7xbNOzHtPXSqr7ql6Ouj2w+mlnoRcDbCYJ2XR/z7TGitw/Ipn5WUyg/Y4lKmX2rCu4Yas6Bw8OKoKL9Al6n2VUQzvSTkflqy69WOsNeVgQyKbQBPBEVp3nzGdZOCL3ok5kVUGSMadATwqMFMENIYP3GkzM/XAnK7cagpAUSlEYyXXnqYrI/f2as83Axo3IbaLziXmVrS7a0VHXhlpLXKXR0lKanndOO3rXc7KoOGwKztqBulDMC02KgmGMXLWOWakIZD+n1w8bVp3j6XVWLdzfL/kLrx/ycFny/mWLcxEtUwaLBGz6gBEjpdHcW5YsS8uz9YAkM4cPG8M7pyP39+rMBBZgELRDYHlk2IyBN44aVv3IHVHiQ+TOvOT5ZiCkyIkvGX3k2arnoLGUNp8rIAPZUoiPpbRJIb7UNM4vCiA1O/AIIKX0708GeC9FuRB55/mazSv86BtVVx6KyRwzkjfJRbxZWOHmELBLQpFk5lL/icfaIfOJGzPtSP4F2flaJLJvUeET695z0CRKY5iXgjEmqtIwCyBEYAwT22lnjEr2s4gBlBbYQhBTZBin6fDkkbHfGLRM9NOGW01mrombqW6jb8AvSb4d8mFhDJEfnbd5IVEKrSJnm5y0swQKlWhdZFYamlLgUqCwkrrQxADzUnPZjowpM6WsyUykIQT6wXPQWBaNJgTB0UzTWMPdvZJ3nwfmZQZ43jpqWA+W9ZSuUGuJnpe8fVLTGMvaOc42I0ZKUgoIJJqES5GzbWA9eJaF5cllTzfmk5HRgtLkGYzVilmhiCTmVnHZOpSUaCXwiTw9F3C+GohC8OhSIEi0KfG9uWUYAx8NLTFGRpeBqiFmU/DgI792ZwYCrM4b9Hb0GK3xIXFQWy43jvcvtpRWclBbntieWakwQnKyLPgH71/RVIJEwbePG56tRt44qrhuPSLBrNR0Q+CqGzmZV/ynv33MXm0xSt4kLLycZjz/PeBfBH4P+JeBfwf4N7/SK/oZSklJ9YqC9FLXvM7x6dsur/GCm4156DIbZtcvYsyeOdddQCro+8mjTua44p4/zUASZIBpl3qzmXx+AiALuO4cSkJlDZXWuJiN77SSdDHQ7qTJEtwkoSqtoCLRjlkKNrhIN06JcLf8JwwZ9LmeFv9d7Lskp3btJNhqYgSNE9CjAjRqSiQLCcPE6BHgJ9nm4HPC5keXfTbMRpBS4NHFyNbl/jTEG1nebAJR8oY/y9CmZOEXfUpP16wm5o3WsLSwGsnTXBOprabU0A+gp4TTKBL9kBlQIUa6W3LywMRykmBL6J3DmszWLK0gxMBVl/Ap/1tOIFVtNbVVWK2YF4IxRNbO4SI0WrCJOYFxHf40+3g2sXR1yrK3qz6QZL7VbUautiPt6PBR0ztPaTQhRpwAmQyVyb4dQ+tesJwPakVRZPbQh6sRo0YSkmWjWXcJISLBR2oET1cj+43FR4gpsT+zXG49755uub9fMYZI9Qv57fnllhDiv5tS+jeEEH+DT8GBU0r/7a/gsn6uUlJkxqNRbHpH614iqu2r+lLKkntJGz/eh3alufHR2zE0P69ug5Rm+juR9/5WZXA/kRmUZrLMkJP/225dW1Z5aLw1iX5ifAYfkCnvk2PKA5gQbkCpRE67HGPuQd0YsHrMCWoxs0K3k0fefApUECKfozSwGjKoJW1mvTalwWiF9w7vA1ufn3N0IGRkf2l4uFdx3TsKJbjYerZ9JMSAri1FEnz7ZEaIcN0KSqtZVIZnK0fnHG0fEEQSktIILrY5Jft7D+b84aM1l5s1Q4zMS8PVtYMYWY+B+3sNd/cqThYFd+Yl3707pyktbnIXt0ZPqWmRy3YgpETnItbAe+ctbx1JfnC04MFejdY5XEgriQueyz7LlWczy35j8l5B5UTsymiWpebpasDHhA+JBwc16z6wrCT7laG0iuvWc905ujFyd1m+SGEbvH/hgfRlDp2/KID0rhDif0SWsQH818jRmy9FxZi4WHU/1RTzVb18lfg4EDTEj9M74eMLbnaG+PSFendQEORFbwcm3QajXjwPTBu2RIies41HIZG7KbS88S0auNH1ipTlBkYrrIaU4otkGiZq6BjzZnzrc5ywjzf+S4kbc1QzTZoLK0khnx58TFy2A1aClJqmiAgpMTJvfC/WI/0ki7gzKxic52wbuIwDqy4ghciSMZevXYpJWz1GNp2jLgy2EBzWBV7AcTNnViq8T/zG60veebbhcjNwts3+QaVW9M6xqApmpeHZylMXie3geLCsQAhaV/D4qqfQCisEw+iptGZWWTrnJ4aXoLKGgGJmFHu1phs8f/R0w0Fj2K8sB3PD6Wag0pIVEasMRZElJCF5fICD2qCUYVEpLreO3uX37uFewdU251jHmEgInE/8+p2a/Znl2WpgCJHrrUOQUxhiDDy66Pjz9+f8+t05P3q2pnORwQcOakvwcHdRshkcDw9KKmPwZU5w+9bxDCkF80Lz63eX2JfIBPWnVUopkpmpf1sIcQA8TCm9NPtq7wPXr3KYX9pSQD9mduDubbwNAHlgM30ad3R+JmPj6G6YSineeEnsfGt2U99x+redvi4nipJImZ3qY2aCnjSKPibiZPbcukDb3zy3Iw8TMqCQGUFWZSZMO96wUWfVZPY8SbCINzK9psg+SWm6Fk2+uBTydex+8QSZdaVkBnEWjeFy60hRsh0d2y6nKSysxcdEN3rE1L8i+SDimZhNMl/3Tg6+sIY+RLY+vGBuMV3L3E4SMAGxgkWZQRDGzE7drxNSCQqjSCmglGQgsh5zelskUtssA09DNjcvRWZUSclkOq1ZFIYkEzEIjEo4F4ljyJR+F5kXmqpUGKl5ctWxqAzfOq6IIeFjnt6W+BcpWrv9QamzT6IAllbSJoFRKk/2RX6fDmuNCzAvFKs+95lt8tnQ3EfW7cDhTLEsNLGB822+dqkTRgQ6l158dl2MrLYjETiqDRdhxPlAU1lKo4hJZAPYIbJXaxal4cGy5Hw7Mi/Ny8BW/deAf4McyHP5FV/Ln6m8j7x7vsVPi8Yra9VfvfosKTXk32c7pZftese9mWDjEttJsmVlXtOHkNe2n1a79T1xk8J2+zNXkMGjXYiBJJ81Cp17kROSbZ+TAo3Ia2elFUQwKnHZ+twnXO5/fgciuRspnBC5rxRaMIZEXVhWWfebh/PiRiaeprPYLmkapiFHhMIqCin58KJlXkiqSlGKxLaLGJOHL3OricDrBzXPr/sXg4KmMBw3JfPasKw051uHNYb7yypLSUeXr63UbJxhGB2nK8fe3PLafsXZauRgZnIYg86BNnMriVIws5In1x2IghAFbx9rlMz+yavO8/pBzaYP9KMnWsnMSp6uFS7ms9N2yN6uEkGpFfuN5aPLjpmV/PDZyMxm2d+9ZQlJ4EJiVmaW1WFj0Urx/fsLztcDQgguNiNvHNS8e7rNyc8+8f17c5aV/Zjf0esH9VemWPiiANJ/HfifcKNR/n8BLw0NVUqBNubz7/iqXurabV4/ay2OP+U2uFnob2uHP0sS5ye/BqkE/TYbKO7XBVpppIyMYyJOHhyVyaBS2HlZJM9qcxO7uZMhGAHd6KgmiVuIecMupwV/ILOntM5+Le20OR5DIg4OIQSVlUilCSHkKUGR8CHSuUihslQjJclm9NlMTwvGKNl0IzFN5t5Gso4RPVH7hYB176lKgxaSw0Wm7S8Kwx89XbHtPPPa8u2TGf/eeYsSkuO9iqNG84dP1rx22PB8NVAVUFtFN3i2zjN6WPUjPgaskgglaUqLNYLeOzadY7+xLCrDdesgRN6+N+d4UXLZOl47rEgRPrjY8MNnkd4Hnq2yl8Si1uwNJS44FlVNDBGhBJ0P6FFysqh4tu44mRmSkCgJv//hNd86WXC8KHh+1fE7751zd1nz9nFD3weer1vONh0Hs4LSaC63A//gQ8/pemTdT74j0+doXit+9HzN/szyxqzmzcMZv/9kxf1llScvIbLqPelrv+f/4iWE+PeBf478a/QPgVMhxH+QUvpXv8rr+qK17t3Lyft6VUDeOG/dDa1f8dkJcGm67fbtuwPBjqisuJGalRM7RkTo0uQ95PNz7TbsYgKexgDr0VNpyaJQ9IPDxwzGl9x4AelJDjUMedLrIy9Mr5XKEgM1bcohBx/sfDC0zB4/Y8opYRU3jNkdZGsmqUI3HXDt1GPWvUOq7JmHy4bhKsLZNvsA7TyXnMgMqEplhhAqHwzqQuFjoLI5KbNSkk0KGJMlCULmSfKOxSNkZu9ct46QEmFi1676xF4Vc2+MoHRGvYycIuxVlqbvJNxaQFWCVXKi7geC9wxacFhVKJl4dpWj1aWANw5qwkTnL3WWGRda0hjBZevz8EYICqUZVaQwETG9fkcG7bzPkvI7+xX3Csv16LnaDqQEWgiElAwusFcpogAfsodeP6W9hZhlDluf2C8tl21G/K62kcuUX7u1U3T15Jk4Ky3bMaKVwvmISJFFqTmoLYXRLCrFybzGGsmbx7O8V/gSfS/+DPVMCPEG+ezwV7/qi/mz1FU38vS644+ebTKI9Kp+5eqnnSWyvcbkxUdm8l91eVCw6zk+3oAyO+BnV7e9jnYDgsLm/fh4644FuQe1u8ecvneX9CxU7huIRJKSqsh2CUZLUojZnFlK5i4xeM8w5Im28Bn82p1/BHkty3JtQSUFb+1bNtueqz686FuQGaI7Cbjgxpt2B2rlM1birZMZD/caHl9teXTZY3Rkry7Zqw0RQTtGDqocnGOlnMIoBO9ddbwm4cF+zePLTBs+3/RshkBCMIbArDDMS81BYyi1miTqgnbwVMZwZ1kihOC9sw1CSPYaw9HM4lykKQyNVWyHyA+frvnDJ2teP6hQUjK3kjPIZ5LOcdBYlAIlFd0gEEKwrA2Prjp8jAghOGgs31eCy61DiLy+r/qRo5nlraMZRknSRDB4dJW9lN48anhy1XHVen79/oLl9HzLygIf9zsySn5la//nAkhCCAX8nZTSX/sSrueXUkoIZsU3Y8r/qn72UtxMfStxIzkAmBteJAwUgDKwnlb4inyY+KSMAfLi2I+w7gNNMZlkikQSKW8sTUJIyczmv48ay1UXqE3isveklP0U3DQBtxPFXyoQQnK8sDy97EkiH1SOFjLL4RJ0LoKJWKUotGZeSEojMVJxOMtx96tu5GLbs14F3LSZxyR8DNxdFBRWEIPAJ8mBlKwIbMeIFDKbusZsdKqAslDUWnIyz4vXHz1e0Q+R/cZmtL1QhJCorOY7Rw1JCvYKyaNrz4O9mm8fzwkh0YdsqnfvoMa7wMVmwAjFyUyyrC3n654gElpqrJH0LlEoQVNaaqOZVwapJD96tuF4VpBS4un1wJPrgW3vOFhYQkxYAe+fb7Mp7piNUYVRvLFf0Q6RvT3FybIgpoQScLwo8Slwuu4xWvAHj68nbbXnvL3iH35whZriSTe947WDyHfvzaepQ+Rs1bNsCq46hxKC5+uWZanYrwtmVvHoamA9BEJMmV4cIvHlIeb8LLVMKa2EEP8N4H+bUvofCyH+8Vd9UV+06krTfyPfll+Num1f9XnDgk+77ZNfuz3lXbvcO9J0v/YT9423vqdRWSo2+iytvR4zGJTIfWKcfPESmeWy9jdsJ6OyZCqQE89WQ+41O/nAiw15hMs2+67o6XHG6QKWdWYcuUjuH/Hm51OqCRiJCSNu2LpDAOXBu0kSB8jpAKRlPkiYlA9CRgYSksYautEzkljUEqMV3ehZdQmj8uPsNZrNEJAysdmkbMIa88/Bewgx4EJCSEhRIFT+3lkhMCZT9tXtBhxhTAmtInVpOV5YujFyuu4ZQ2RwkZTygOfRVUtT2jxQKAs2IywqzfXgKLyn93lYEiXURtG7iFWw6m/k7pXNvXC17bBKUijJ8bLmbN2itcJ5x+CzbK4xCq0Um94Tbx0UNwPMVcRHwbLOP/F2TGwnsyibwGrJONGNFQGpJSoKtEzEGDmZF9zdq3jjoKGwklIpXjtqsEriQvpSfS/+DPU3gb8LvA38vVtf352T3/4qLupnLe8j75xuOZ5lOFi+8s17VbfKTn9LbvqHczdsnNvs1mGSzH4y4Gd3n50/XjH1DS1uhtyTlRx6Arw1t9QKEmZWcFgpLrchX4fI++wUAsMQGHxEeRj9gNUqDziKrEK46iIpQBWzVHjMKi8Q0I+Rw6YkCMmdvYqzJxuUziC9GGNO85T5WnzITKudB52cLloLmBeGVTfyZDUwBk9tFPuVpvcBJRNGFswai09grSORQxGEG3i+6kkhUhrJpvd8cD6wGQLHM40UGkTksLasBpfXR584W/U8XwvePsx+RCcLw1VnuNsUzCrLG4cNEWhKwYfnPU2paWwO0/mddy9446jGaIWQOczgjcOad55tGX1k3kgO65Lv35uz6T2lUVTWIPfg8VVPSNl4XGkxqTRGDqrsl3QyLzBafswUWyt447Bh3TveOGgwStKN8TP9jmJMXwkL6XMBpJRSEEK0QohlSun6y7ioX3SFlGisoZE5rv1V/erUDsnfLeTdJ04JUmQpgJtM4La3RtJWQ/Q3E+nb5cnJPkbAwUzTj4lVl3W2dxYVhZQEAZvRk0LWGmuVr8iHbLapJ1+KzSRl8BF0gCFGpIvMLXgkyDyNnBf513WfyLK2rFrH0cygpOQYzePViJKC69az7h0+CmLMRtl6YjlZnSfNuheEkGnzlynTWWOCRaXwSbAvAmNIzKymLCRzayiVIpF1/60PdJdbCqupbPZN+vC9LbVSHM00/QikQFlYhBScLEuuttmYVZH4sB0wRqC15NtHMxaV4Y8BHyNGSS62I6PzmHnNcWPwIbHqHZVVjD7wdD3wwWXL4bxEiERVKPohkWIgakNtFcfzgkL5id2UDca1VMxKO9FAE70LjC6iyTrqJ9cd59uRQomcbCTgfDNwvCxYFIbrNvLu2QolYH9WUChBYKKitjlhbj0kLjrP0/XI2ycL9iuJEoLWBz4434LI/glvHeXG8FUt/r+E0kKIe8B/FfgfftUX87OWTq9S2F7W2vGLb7f3XzQWOKZpcPA59xvGDLKElL0iQrqRvk2WbkBmH00KgBdShtZDY/O63ZQC12WQO07g0e517npSRZambfwNm3VWWjb9iLvFWIrkQ8ZVn0EqKbJcQe30eSmDZLvnKM2N5BqRe6NPsB1hUNCYRGHzydkHyXJm6IPAp4Qc/AsW1GYaR+8kdd30Bo1Tvy2NIgY/JZCmFwl0R/sliixpDuQXoI2aDLYV22FECMmqdYw+0Y4jKQlqaxh8IIbMxFqUWe58th4JEZJIWKHpnEdKKEw2Mr3YONrJ42D3GYrkIVFTweAl/eBYjXDQWLSQKCNpR8/gAs4FVp3AiPQxz6ZqYpBtByAM+TF9PvQ1Oh8OQwQlE3u1Yq+2zCuDlYKrNmAUrAeHlorXD2pOliXr1vFsMxCAh3s1bxw1L0XfSCn9DeBvCCH+ZkrpX/mqr+fnrTHmT8gPHsz5u7+X91Gv6lXdrl2Cskh5rdXpZs1+IQuevrZj6NxWOxjgaCYIwHoyIpISmkJgQsree/CxgdfMTB5C5Aerq8RVFxlTwiiVpdIuQkw5eCAm2tbTOShNwCeYlQprLLM40oVARfYWVSLSjQmjc3pmZRXvnrYYkbJlhsivrFDg1ZTOaQRukyhMftFK5z7gQ+Ri7bLsO5BTTLWkMIJHl1vmVcHbRzP2mgKFYlZp9qqC3nkCkTcPa8pCs+5G2iFwsfVYI1kIhVKSmRb0PnA8L7BaoUQeRvTOTz54kqNZwdNVz5sHDSIJXjus8Qke7pe8f97Su8imn+RoNofakCCEnFL3k7OWHz/fEknslYZladhvLEoqHl/1vH5Yo1X2erq7l3vGVevwMfL4quM3Hi5ZVJZN7/j7H1xm7yIhcOEGJIopYbV64Y36WX5HvQs8ve6JKb34emm+nJ3sF5Ww9cDvCSH+78B298WXyfROKvnK5O5XsD4PL3Rj3twroJ8mSYYM7HyWX1JB3vCPk3b5cutzBOaQAZjCGiSwrAx+007Sh4RW2cNg5nJ0Zgw3CW07AKnroSgg9CNK5wOtMRajFIdzOzGXFJUR9D5vcI8XhtIo+pBpn0olrFTMGs1aO1Kbd+9JTHIFBUZlqqdzuZFVGqzJtnNWSPaXFYPz7DUF69axrPNzBDLoUyjJR5ueuPbEFHA+8XTV8q3jhuEyIKSgGyPzMvGT0w3eB9a9ozCSMQgeHs5YtY7LduQnFx3ElsrAflMipGBeWS5axzAGHl/17Nc6x95HOJ5XKAnvXWy53g4YLRh95GzbI0Qi9GNOQ7ho+c79JSeLmtIKLraORam5v1fyYK/i/rLk0VVH2ztON/BgWfPj0xVWCvoxcjwviUSeXg+crz3eC4SSjH1kCInnq4HRB2KC3/vgGqkUzkWsVGgpMNYgUuJ0PbJX2ywPLDRaSIQSGCVZ947zbT65fNmL/y+h/qfA/w34D1NKvyuEeBv40Vd8TV+4Wu95ZYH0y6lPCy74Rdbtye0n5Ws7AOXnrR09IvLTX8MOi9kdCOIEwCgBxa0DRDkxmbp0w3RxAeZllmz1Q6KoBPeXNemqxY3Z2FT5G0DI7p5HZH+7F2wZoB1dHhikPP11KcsYAvlQ42OWQ5RFvsbM0sx9rzLZS8OKvOGXMkuyo485kEJN02ghCT6wrAuuuuzT0209tdH0NlArCRLO1yH7Hon8/Ds5hicDWM+uHcrkkIQkFH7wuAgXqx6pxIsJfVlkXfeiNBzPLH/8zDH6QEiScQyEJAhJsK8lVSm53kScz5JwoyVWS4zWrHqHF4GUEpW2GCkIIRJCnu6P6QZ4LMkSkBhgJHAwrznwEakFIimMlsxKjdpk8/R1m174Ju4+d3Aj5etcfq/cpHlU02dkO+QJ8nwps8S7C1wlT2UtfQjs1SXLWrMdPf/wwyt+cG/OtxczujGgpcCql4sC8zKDRwBWyomRLFjWkndOv+orelVfp/LcnCFS4lNZzS7dJKTtvHlv360Drts8ZF6UguizkkGKSF1p/OjZ3GpqhgziVAV0QzbufnoN1kSMzX6rx4uCy63DuYicvH3euxgQMUvDSiXoh0gps7nz3dowLzTvXbY4n2gKjVWCrXese0ddaIaQaGpLChHnI9sxUjfZJ7V3Ca2GHHogsvTtbmN4/bDhnbDlsgsIcsDBVTeyarMPXWk8q85zf7/JKZZNSds5rkgYKbg7LxhCwlud2T5asB6y592dRcGyKjhsskzvYjNQF5rCKFrnIQlO5pYn1yNPrjsqoxDA4cLwT7x5xPnW8f27C/7eeMm683TOc39ZUBrJ3WXJ6WaktBIJvHlcoYSi0gIXI28fNlijuO5GHl20PDioSCGDOnuVZa+ymV2FyD87FzjfjighqKY9v/OR0cdsj/IJU+zSqD/ldxRj4ul1j1ECrdTHvJG+jKHCFwWQ/q/Tn5eyjJLsVfpFWtWr+tWrXQLBJ+u2dti7GwmCFFnL68m/JJK80O822T7myW+e5uZf5NLCos6xyBcbhw8RPBw1BUnA44uOdnRIITDiponMBazTzSHnqJaMUXE4M8zLgsNG8Xw9cHdWMITIrLLEAOvOMThPbUsqI/mLbxwgFJxd91xsB842Qz5MqMykSkw0UpFIQtCUhlZE8IHBZ0+LtotUNsdDHs5LJPD68Yy9QqGkYDVGBBEhNLVWfLju2W8MQwwUVtOOibIIvLGoWRfZ+PN8M2CV5HBeoqVEysSyyoi8EQKlBZvBIaTJEocUsVpz2ICoclLNvNCsx4iPkdIoti4ghWRWKoSQOJ9YdQ4pBbWSzMrIZe/56LpjNURSjFRW862TGecbx+i3vHU847dfP+CHz6754LLFhQwa9UXkbNux7QfakNifG7a9x4hED9zfqxAk1u1IFHDYFDmNKMHbRzWF0YQEPzndct07DmrLBxctY8i02kUlMRE+umx5uuqpreLuskJL8aUu/r/oSin9HeDv3Pr/u8B/efd/IcR/P6X0P/8qru2L1NXwCj76RddiYv3+MsGj27Uzvfaf+NoXqc/qEeJTHvPTagfuOGBPZYPnMWRj5du/zVpOIA03oMpAljGXJg8mmgSjTyxKy6kbiLceY5cOlqYTyDCZXccxH1qcznJonSZp24RcSWBegRCCFBOFlowx0+aDz3KIyoBSgnmt6HqPj1lCllJ+/Y1Q2ELgg+fZOmC3nqYyWCE5qAxKGowQFFpw2g03fkwa0i0Zxy6BqCymsAmfKFXETCjOEBKNzEibS+A6z7ySFCr/vGaFJabEZvSMPmRTcwUX255umNKIYl6Tu9YThePPv7bPvNQ8u2jpXE5pu+hy6qdPUKgJRHI3ZrUx5D/zKnGx9QipqFLCas35tidFGHygHdLHvBOZ3qOQbmSAenrziklrEuMkTQkZSOrHxOGdgnXvuL7wzAqBJO8t2jFy1XoeX/e0Q+C7d+bs1yZ7Sr0c/kffmNJa8v17C/5Pf+99Hl+Nn7suvKpfrUrkNRk+Lqu+XbueVMvMyvxkj9LAJuY1bAiJuhQ0RnK+jdQp0lRgPFwPN/5wg88yZwPMpuS1rYOa7CO06TI4XxeSKDQbl3tTANKYmBWCRB5QCx9oh0hMAZEE81JTWMUwOiw5SEBKydgHtJTUFlxQFGpAmQw0rbtAXWSAuzTZf8goxfl2oDKaeSW5al0ODRoitZUYIAnBe+db7u4V3N9vmJeWB4czqnXH01XPj55vOV4UHDWGJ1cdnU9oJXOQweA5bEp+8HCJVIJ3n21YdZ5EIgbonOdP2oHfffeSw3lJNSW0/d0/eMr37y7RUnA9eF7fr3nn2ZpHlz0x5j3/dszAjnORqlCEKNg4R68VRsLWB87akTEk/uCjS3783FIViu/dnTOGfG4ptcKnxPvn22zBsRo4WRRImc9cRkvu71VIKT5VkSCl+Nhaf1v2Bh/3RvoyesIXApBSSv87IYQFvkf+/fhhSumlCTWTUvDaQY3ajRJf1UtTu8nop8nIvmh90qDu08pyM7Hehkw9333Aby/uAqgKyaywbN2AFIqDxiASpCQ5mhuuhkRIkYs28p2TGpBshpEkYOhHopR5gzttLvtJGrE7wFx2Eauh95oFsChzildhFGNItC7wzrPV5KOReO+iZ2YVdaHp2khAsO4DEokUmqpIJO0ZfU4oIsEm+BcGrYWVKCIxJrSWCCHZDiOFLtFGcjy37JWaR5c9l9uBD3rPXm2QQhJjpB8C/RipjcLFRBwif3K6xWjFt49qnLO8cVTz4UWb0xF6j5aSuVUoKZEJ7ixLjJZcbQYu2xEpAzHlie6yNDw4nLHpRn5y3uJi4nhWcFBbtoPn2XXH3UVJf1AzhMSqHWnHnFowuogz2afoW8cz7swzVfSqc9xbZHR/M0R+/d6Cd55v8EHz7lnLybzkovNULtCNWQanlaZKnocHTfYxigk/HaySUJzMDEfzkuerkQf7BfvVklUfuGrHqYEGlBQMIbLqAy5E7i8rCq042wzc36uIPn6TDwT/PPC1BZCeXnxZMMevTq3jl9tyd8ad8db/P8tI+5NVibwWf/JAGMn9YWdq+mm9ZMdyMmQgZtmUdGM2z769UVLcsFcTU9LNlIxTWai15myb1+oPz9sX7KeDuaQdItc9RJljm6XOIIQjJ535lIcaPiashqHL/kq7n8OizJKK3ieSz8MPLUVmHcVJagAsa0k3eIRQqBQpDGyGRG1gjAGN4KrL4FSQASk1PzpbcdiUlFpRl4rNGKiM5e6+52zt0FowuvRiw1mIzGbyPh98CgOtj8iJomRkHiwkkX00lIBuiJxtA9fbLU1Tsu5GiCJLwKxijOBSoCkEwiWch4utQ0uB94l3nm5QihwY4RNXLrCoFI0R9C5lNle8YZzt9h6KDCo9vmi5u6wIQtKOkVLBJmTj1l1CnY8f/3x4MmNZAkoLpMzyiVXbsR0TxkItIAlDSonnq5F5Idmvcz+vjKQPkdEHusFTa4VVgovtQIiJe8vqZfE/+kZVZRSdC/gQXnjSvKpXBTdyNMtNYudtj6LbLEX/KeARfPzz1EXQQ6IfffY9SpHOZdBox4z1CYpbaFWcpHM7ZpJWCSUV9xeKeW35ydMNqzGQuEl3Q0RmhcTFSOsCdSEhBVJMbFzAaklCYI3EWMmyMmwHjxaCWVnRe4+WCZeyf2hI2SVcKcVBU7B1PS4E5sqyWCquW0dlNU+3bU5+C4J7+yU+BJQQaCF4sFfhQmTbe4aQJWHt4LnajoiUuLcs8VFw3Y7s1xqlFG+eNHxw0dP7wOmqZ1YoVn2kH0aebRwQ2YyOYpTUVjKvDMMm8vtPrthvKk7XPfcWFQeLAiFhWWvmpWb0nlmpCCkbWrdDYDsG2jRy2TkKo1lWmn4M1EayqDV3FgUX24F3n69fGGaT8h4BspVFjHmHtPM12knWvkgpIaZAiU/3Rvpl1xcCkIQQ/3ngf0OO3xTAW0KIfzml9O/+Mi/uF1UxJq7a8RV29JKWEBlFb9NPj878tDLcTIU/q3ab/92UWZLNqnd125BVkCeVSUQOq4LjRcmdRY7Sfe+s472zjmVlOFlYnl0NrLpA70e6MdAPgcFDNxlCLCfJQkv+RdxR3QcHWmamj5Jw1vYoFNoojhYF297TLkp8EgjiNJ0c+f1HV4wx8mBZYbVgUVv2ZorNENm2I8/XPb2PSGBWGdZ9IMVIP8Ssfy5gbhSLWnHdBYQQnLeO9qNrfJJ897jOEcZAN3p+7e4MUsSFSGVgCBGLpNI5El1qyRAS23Hg0XnkdO1IJDoXsRIut46QIncXJUIqtqOn1BKjFC7k157IU/l28NSlZV44Bh8RE2K/a2Lz2rLvIh9ctpRGMSsNEYkPiWH0bEePI/Fk1bNfG+S0wK57x4cXW3zMZh8hCU5mhrvLGkTi0XmHj4F5XXA00/zoWctBY7jsRla9Z15oCinpY6BzkbvLgn4MRASr3qO14O5exWv7DSHmicJmYkod1HmK7kPEp8To8rYixkQU6aVkIX1Ofa1fUFW+XFKQl6G+7J67SzjbPe/kU/y516HI8qVPboheRBCTQQ/SDZAUuTE03YFMsyrfdtX1efr8iSc2ZDbOXDFJciPR5o2gUYrTjUeryTMoZbnTcpZBn0gOfUgyJ4MNDkolsWM+gnTj5KXkcrKbmS6u1JmtNMYMhOjpGsZpjV2WBYdN9uG5aj0hCAYPdSWwytIYRWKAlNh0kZQSY4RaZfZQO0a2feC4gcIIrrtI3weskVilOZxLun7gcCbYjgk35utZloIuZGPtMLFwBNPk3Cc6H174iPiUbx+DR2jJdetQBFwKGbCrDGMIrPrArJR0PqDUlCJXAlqiReLRxciizCyqNHoutoH9RjKz2fgcOTGMxzxcKU2W+7Vjfv7zbYdqs3G1kQIx6Qh3iWvuE++1I78nRktmJsd4S5GT6JalwGjDyaLkw/M2e1gQuGw92z4ybxLLyhAn74xyOpSsB89mcJwsCk5uSRxe1ZdXgws8umhxIb0Cj17Vp5Yj95WZydLVFDIzEm7CGD6PhVGQ18RVyP9e1Nk3r3N5+CC56T8l09puMnOpD9N5xmXm6f7M8GA5Qwh4UvZsXaApM8NSiez5WVn7gim07RxrMlP1sCyyH14SHM4MVam57hxykiYjEkKInADd50FpYfJjS5mwRvHt44ZCCbSR3N+r+eGzDZWWiJRY9QOXbeRyOyKF5I39AiEF//H7l5wsLO9fbDjdjFy3nm8d16wHzxiyFvgvf+eY+3slq63j/cst7zzb8HC/wk9eZU+ue147KPnjxy2vHTTsN5Ynlz2XrWOvzME7s9LQu8S8UFy2kpAi75+3/Ln7C3zKDNBV7/juccN+bdh0gR+fbZgZjTGK7y0brtqR7eA534zs1YZnq4HT9cjpuqcykl+/v8fr+xVCCF4/bIgxcWdZ8uiiY905tJIcz4uf6TP207yRvoz6ohK2/yXwV1NK7wAIIb5FlrS9FACSC5EfPlnhXyFIL13l2HtATJ4E8DP5lOwmibtEtd3C/cm6vQkoyJt0O02PJVBOUcNFAUZrfJQUlWXwiT95tqKxlsYKkjDElDK10yiMkfgY6V0giciiUlxdhwwUhZxq0+6mCZNPRgiwbzUhCh5d9rx13PD6cUUI2WSU6HJDihGlFbNS4rvER9c93ifWQ+DuoqQQmrI2KOmIMbEX80a8dyFv3ifWUC8iY0yIJAgxcrmJ+JjYdD1KZU+n5BxPVz0uRg5mluCzoWoUkmUliQiuu5HKSvarAk9ARPjwfMN6CLx7uqUpLZszz2sHFUpJfvDaHh+cb3i+zvyy0moECS0VnY9sW0/rAtetY24MD480Dw8qSisppaYNjtOV53hekGJir9Q8UwKhBOPoM3upMvgYefOwwfnAo7MNj5XitYOKn5zl5151nspISqNIIVA2BcezEhcjZ2bkdOOxLnC2Tlg9yRWV5P5+RUwCHzPYs98YpJSU1vBgWTIvDCFGnq9HwiS9a6xEKs26czxfjzmyOiWUkJRaUlnNR1fdN8EP6dPqa70C71v7+Xd6VV/rivzpTfntD92n+SEZoDY5KaecPCQ+ubkvyIOMmDJQtLttJ8fy5Ah2AhirWbUeF27ut3vengz0PNgvWQ0jXYBKS2aFofeJQkNpFb0LyHTj5+QnyZmpDaN3NFZnlEMJrM5sokUt8S6xHfMrtiIDICSo5JQ2mkBImFVqSitL+OixWiOE4mgmeLIaMlsbQfCBZ10GXYzWDG54IZNwPsshINEYybw2vLVf8+FVT20dd+YlZ1vHZshybqsUJ3PBdT+y3gZan0gRikKyaeOLZLpZkX9Y/TjFYE/AndGZMbVXGToXmdU14+U2s5Mnz8J1D20XXphRxZhTTRdWIKTK5rYpUUtJNJrWe1xI7DWa7eCxMpuW9jazwHxMDNMJbSAfygQ5rS0JwUldsO4c7hNMAklmfLVjvu6QIijDQuf3QBmdk9dS4nTrQEhccFy0HonkahjhErZVwb2F5fn1yGbwHNSWZWNIKQ+AXPjkp/lVfSklYD2MnH8yleVVvaqpdmePmPLau2Md7f7eKSM+6xNkgVk5AedDPisMLoNHI5m5uhtcHFSCea354Nzh/cfDgsoCtNAMY+Sq77naegaXUxf2S4PRCuc9YlrBQsqnJKElyQdcTFQaXBLsNQWlkigkjYX9qmIIntYlQswDCU+cEuQ0QURIgmEMVKXhYF5wsqhYFIpV63lwUHGxrXjndIP3HUIEIBtJdy7y0eWWd09BpEy3kkLwwUXLybyittlL9IPzLavO0U0sqau2g5iy5C5E5oWh0AYlBaebnjePGv7St474v/yjx5xtew4ay28+2MuWGJXh16xBiuxdSoJ155mXmm4MbF1EJsFvvr7kzaOa0ihONznF7sOLlrvzCq0E5+uRzejYrw2Di1glGX3gYmLNzkqNzalKPNyvOGgsF9uR0/XAuRh/pr3/p3kjfVn1RQGk5zvwaKp3gee/hOv5pVSMiefr/pVB6ktWO8Co0Bl138nYCjK6/0W2Tp68AZ+XoP0NpR9gPo2qu3AzVa4FoPP3FBrEmJlC+5WmKDXrPvDmYU1EURrF4BxPr3N0cUz50CBEpFzWzJRkZjV3ZgWjDzy68ozhlnmey/TSkiw9ABAhp8JVUnFnUdAOAango/OWx5uBODrWY54Q+ASlFly2efEXUjCvLaUV9GNgqxxFWfD4omVIiRADpTEMztGGTLcMSJIcCUO+PUlJ1/vJUDuDKtveE5NgmzyFVpxvR+aFZrXp6MbIsqw4aXIaGyQ6N2KlYdUPbHpPHwKV1exVhpjgoC7Ybyy/9cYex/OCVTvywyernBgXMnX2+drhQmB0gas28PdT4t5BzeuHDX/ybM3ZeouUGZA5XpS4ENkThuebnsOm4Gw74LaO9y9a3jiseftkNjGCNHuNodSSi9ZhlODusuC6dyiZGAIcN5ofn26YV7k5pJRNUg8aS3CJu3fydGP7ZMPhzGC1Zq9RaKm5t6zwXmCNZo7koh05bAzr3pNS4vcfr3E+cjizmEkWpwV866jhsnUcznJyxJdthvcl1df6hVwML40q+1X9nPXJzXol8oeyd7kHFGkyOk43rNTdhj/Fm7UbbuRyO0+iYcyysq7zxE8ACrf/vfXw0WVPWWSwyPuEkIlFqXBOTIye3BO0yhKvdoB5DXOtsCTOtyPBwzAEUsjpmodzxWZ01AqGmCVVLuaEto3P19vY7BU0uGz+X5qcuukDFDIzewaX03icC/gUs0ePkKz7SEz5MbXIAJLXER/gNx8uub9f4UJmDs0qg0+SELPs4s7SMisLNr0jbB1lpdAp0fqE9xFroB8mtu/u5ywyE3ivEVx1ic4BXWBZJCqrEFGQkCTpueoc/Rhwk9+WTvnPrBSkJIhCvjAaHX1gK7I8oza7ZKBEbS1H84LT9UBIic2Q+8Ft76nCglYCSUKKbAC76TzWgIk3jADIA6faQqEVUia2rUNMztl7dUFjxDS4Ae8c1y5hdGYeLwuDRPDGfsnzzciiNPgIf/R4xcODGX/lewvuzEr+8PGKv/TWIVq/Yk9+mRVi5Mll//WeiLyqr7R2bNNdpP1tJQPwpzzTCnaBAXnI4NIupSwPAxI3LE1DHmqPMUuflYJujNmsWoOdQKaCDLpUpUIgOdsMbPpERGFUfrAEaKnxMTP1131mdWoxGf7rRB9g8JHRg5rDzBi00hw2hout47rf0g+BujQsrMp+pSFQaom1iiRzWtu9vYoHezWjD/yV7xzSxzzEqLTkL7yxYNV7Prrq6ELk2XUPQvLkYstBU3KxHdBSsA2RRW0QveLuoiCkxAeXLfeXFd8+mbHucgr1YmbpfU7xdDGAkFy1nt9974Ljeck/+4O77M0NtdEUWvP2cZPPEj7y5LKjtprOZTbV5XbkaFawXxdsBkehFFrF7AWFZGYkh02BUtBYzcZ6rrvI48uBMXiSSDxf9SxKw+HMMriImwy27yxKnq8HrJYvZGg/697/k95IX1Z9UQDpD4QQ/w7wfyR/3v554HeFEP8lgJTSv/VLur5fWCX/RZ0QXtXXoRRQWliP2QB6l1YT+eLg0a4CmS3zSRP1tYc9A1XKpqO9g/0GVn1G+5eVZh8ISVKWhkVtQYx0UbDthmz+3DpaF9EqEUKkHXOywF7l0UahFbjg6ceAFgmlBOVkLAswU3BnZjhvHcOYm8qYshfHDvHePN9wPUTGcURJwfEsM5+MTnx05QiT/rUyEu8jQUpaERljZr6kBMELrM6MmNJqRIKDRcnzdcfcWpQY2fTQ945ZoTmal1x3ge31QGkEQkjOt557y3wIGEKk7TyLWnO6HnhwUCNw/PhsixIgy0QfIlsfMUqyXxrO2xGrFM83HSeLEheyEdRsMso+345sBseq86wHjxWCw2XBLERChGfXHdYo7ixL+tFzd1GhJxS/HUeqSvOXv3PCxWZEKcWi8lgpqAqDkYLvnsxRSnBQ5alLIrOx1n1g1Y386NlIYyVGC47nltP1QGMViZy6crYeub9fYY2mSImH+yUHs4JCZ8+PNw5rjFQ83K+oC4XzESESvcveHqaU3H1tj2ebHkGmyb52UDGESFNqzrbjC2ndl22G9yXV3/n8u3x1pT7T8vJVfVOqJDNYd94UO1ZyJKejWTsxK6f77wCinQxOTaCMZZJW25xsmcLEjPWTT5747MlyAFaT4emDPcm8sVxuO7CJqtRcXbvsazEFNfRjjnDWQtD2Oa2m9flQMS9zj1QSai0RjeKiDxQxHzbcBBzVOsveQoBVdwvkSHnTL6XMcfQhIaWkHQJCQqUyM69SgsvNmBlDOr9ereCwtlSlYj0GrroRHyX35iVRCh5fbrlqA3cWlnXneff5GqMkSit0jFz1jol8+iK9TpBlZ/Myvxc+5GvWU/OXwEfXPU2hWFSZmpwC9DGwHbLMUJmbyb8ViUj+YVz3CSUilwPEwbNXwOEsM333ao2WitFHNn3eK2o9mYfHKZU15fTS3BMSkRyWcLAo0UoiRCQEwUU7UllFqQVNYUjk6fy6G7PnU/AsmxKtNdEF+hBRQiGE57rNzNmZldSl5r2LluvWc/xawazQDC7Sh4CIidIqNr1njBH9au36Uuu6HencK/Har2rtziK737pPnkckmUmZyGD+pykfbv+/AVAZdB58Bp68Y6Jg5qFymCYZgdx7hmlI4TxcuQQyUJq8ZlYGgssDAyEza/KyGzFSUFtLoSWdy2D9bz2Y8Ww1cDVKnl62+bwQoK4kRkRUofE+UVlJiGCE5nQzYpRk8IHGKIwSrGKE3nFvvyZuejonuLNXkhCcrTpSElyse37rtT3ePd+yus5eRqfbgUWhub9fU61Hnq2HaXDiEUj6MdJbjzWKQgvGIbKwktJojhcVWx8wWqCkYDME3jhq+OGTa4bR8/iy53Be8PQq8NZhw8XWUVtBivDXfuMuPuVhSohwZ1nxzrMNp5uBmBKvHxY01mQWbed4eFATU8JqRWU0f/5+zdN1z7KyWQ5XCSoreXO/RojE1aYnhDwsKLRiMwTOtgOv7de8cdiQRJYO7oywpZDZukMIYno5vFC/KIBUAs+Af2r6/ylwAPwXyL8HX3sAafWKfvRSlSYvpIGbCfDuV+mLgkc7A8yevAn8tLpyebNfiKwdbj0sa8GmT6x7T6kVVguOZprR5+ng2VXObru+HvN0M8LoIynmxbwyeXqQXOD3P1xxMC8Yfd6Atm3EGJgHmFeCxiiEFHiXN8xLnQ8kF5uBRSEwQrDx0A9jtlyLIJWmJHFnr2RwLbWB0+1A5zydC+xXhoN5ybyQ+ChYNAbdBdoQKZTgZFZxOCu4Ny/4D390xsV2pHeSUgm0lnzrTsPRrGLVe378bMVV5zicWQ5rw36pSRFmlWasDAloe0/XjXQ+ezakBIWWpCQolOSqHXETkDSzkk3veefZmh89vUZIwdU263+VBK0VlU70o6Mwitooks6mfHKKXDZWk5LkevCk3vPwoOLNsqYs8jTfh4QQEh88i9qysJok80ItYvYkerrqEYgpQULyw6cDIkFl8mHqx6dbKpNlabPS4lM2JbEyx4C6ENmOgbdPZmiRkxOqQqOEYAyRx1cdH131GCV587Dio6uWi61jXhkKremdZ3CB1jm0VC8MEmP6uKHey2SQKoT4LvA3gTsppT8nhPgN4J9LKf3rACml/9lXeoGfUwf1KwnbN70Gch9pdN4kWzN5Dbls6uxCnuz6mPtCECDjLS+lNKVopQyghInBqpikzyJ79d2Og/9k7b4+RHh85Wgqj3eJ6z7m6OeYJXUp5cdtYwaQLrchm0lPB4cppAw5PaaLnq1L+IkJJUL237kzF/TJMPQjbZ8n0ztD10JCcJGgAx5YVpbYedo+EifgZM9Kehfp/Q1jNoosLRtiQruEUQIjFEd7lsutp5CJWWEYhpH3zrekELJhbFRsXwxT8s9hZzCrJ5BmSKAHMAXcmRf4FElbxyjIMfchsB4CpU0kKSi05qrz2TTW7gyOI1YlbGEIAbbOMbjAorHsVfnn4D20Y0BrTfCCqpaMziEkSASClIEjAU2ZWWCkxOA8o4f7BwU/eLDgnedbvFWsh8h2GPP7JsEFQesj3eiRIh81myIPqp5vOpbesCgKjAyMcmKyxfzZ61JEisCagXaIWdqwGSm0RAuBUpLHlx3L2mDlK/Doy6wYE0/WHZv+FYD0q1g1mfHTTuzEnW8q3IQsKLL/Tx9yj/g8MdKW/I0GIGXwSJElbIvacrkd8YmckKwTo5+8WmUeIEhARRhFft4U8teGCJpEP2ZriO3oKQtY957RQVRw0UUuBk8MksJahjDSRRAk9mYFe7OCUku60bMasuguxYQTie0QONuOlMqwXwl6H3m+7qm1ptCClKD3gbow3N+ruO49/94fPmUM8O2TGbPactGN+CS42g58cNUz+ESKkfWYGeEHM8PgPUoolqXhB3fnNKXl+Xbg8XXLsi7o+0iMA4vKYKTkjaOGP/dwwffuL3nn2ZqPLnuOjku+c3eOkoKr1nHZZQ+kWWHoXeC951usETzYrzhd9fzxky3LyvD2cY0RgsEFrFbs1wYfE+ftmAdRWvIXXtsjCXi+6nl81bOoLMuqoHUdF9uRe8uSQgvmpeFkWX6cMRqzzc7zVY+U2SJjv7Evxd7/i6aw/fWfdvvXPZ7Zh8jptv38O76qr03tqOy364vQhXeygnG6f/opDqo7eYJSGdE3wGUPmz5l+ucIsYrUVnC5DWid6AaIQtCNjk2XkDpNHhV586enw8foIlIL6lLSWIVYWEyb2NqATnKK0BRcjB4l80YdD+ssAcZoaIdAEjC3il4rYgxsR3h62VIajZFgjaApFForztYD68HTeY8Pgd5L2nHMRs0poQXs1YaDyrJfWda9Z1ZIhqi5t6dBJPoxJyfsVQoXAlpJ7i4KZoXFiUTn8uIWk2C/kmzHgKlz9OVBU1AUmm038uFFRzfmSXppsizj3tJSW8OiUviY2A6RMUQ+vGhZlDo/LnmSUBrJagycb0esUSyrgtpqjpcFz64GDueWyihaFzi/HnhwWGeWjxa4kDft+zPLt09mXGzcBKpZYkx8dJUTGkTKkdYny4Lv350TJzBrUej88xsCZ5uRzRCpjKR1njooHl10uBA5mZfsN3nMdNE6Xi8NUgpKqXiwV+FDZF7maCMpBKerDglsBs9PzrZUVvLRdc+80Cwry7I0XLYjs8J86WZ4v6D628B/hxy4QErpHwsh/vfAv/6VXtUXrMF9Xlbjq3rZK5HX+Rgy+2gcsz9QaSdAocsgiST3hZ33jvdTFPskb95OpsrDxIqpDS/MoJX/YqlMkQwOhW2iULkXWZMf302Hkx1YpCdZV5duAKM2QtdNXw+g28AwDSJCyklvysBVl7AmT1l3somd1GrrYVZmsZ5IkESCGClsHuBIYOMCeI9RWVLWj/lnZxUMY6A0+YXHGHjn6YajmeV6CHx01fJ8NeRQCJWHK0eNoLE6H0a69OJglciPqRXoKVq6iND6PEzoXP5+kQKdy0CMEQkvEkIrllU+FAUPQSe0hEWpWBTwfBuJ00Fu044oJbi7ULiUQAi6wdOODtspogvZ66NSSCG5cD6Dhkoy6IgLoLTk/n7Bmydztr2nVJLN5K4+BliUkr3aIsh+hGJCHqtC4nwkAps+kEKi0dmwPEnFyV7N6XVLmJS0WuXh0rIpWLcOqRSmkWgteXrV0ZSWv/StV/K1L7tciDzZ5ae/ql+5KsvJD1Vkg/84gTW7j0Mgg+FFAQx5KP1ZQ+8dw3XXLxwT43F6vOsehjAyeFgWUNjs8D/47G/nk6DWicrk88dmyM8vgUblnrRfa5rC0HWOCx85u+5IQlBrwWt7M/Znhufbgd6NhJCoCkVtEx7BGCMxCeZFtmEwUrDqHWVhOG4sSEF3uaUpJYumYNN5ztcjRSUojKYwim49cDIvqGxOKHu2HjhZlPzx0w2LKvedxuQzQUyR/dqw2vasWwcCFqXluClQEr5zMqcdI/cPKk43I/PSMC80e6Xh+bpDkDBG8NqsYdXllLnffH2PmK44WWR7iN45vI/88Mma43lJZRXfOmp4suopk2QzeDoXaQpDZRSDh7vLzDLdpZ4N07BeCEFKiZTgO3fmPNyvcSFiO8Hbx3P2ZwXOB/Yay0lTcO+gzv6Fn6y0S2ab/n5JtLFflIH0efW1jmduR89F+8rf4mWqn1dw+LEUlGmqJ1JmId02UDXwIsY+xcz62fibWMydUWrXJ05jz6KxNIVAipxA5n3I0+uYN/vb6exZTFPt0Uecy6PjFDv2ZwU+CcYx0qWYDwkx5inAtFikNB1kRD6IXK4d1kI/JkYf6V1+rkhCCsfWa5alxkcojMSnxHLa+LZjJKVAZWX2/hEJozT7k5Z4NYxcbBy1VZzMS7QSrFuPMZLT1UipszdPoXPUw3XnEFLQxsSJVVgtkSovpiS4bDO75s684In3OO9YNIbjxvDuWcu+Fnz3zgyk5P2zNddbz6w0KCWY2azNnlWaWZHNRWeF4nzT0TsYnac0kg8vM41wMwa+ezJHa0kk8Ww7sDd62lFQG8VvPFxysR3RUiKQfPfOjLt7FTOj+fHZBi0Dy8oQfOK6dVijGCJ4F+hdfBFN+t37c642jiTg/dOWRWXyz0rCR1c9dxY5/eBoVhBT+hjl1CiJ1Wqipuapwl5d4FPi0UXLYWP5cw+W/OFHlzifePO4RibBdev5zvGcwqiXDTwCqFNKvyM+Pjl5aca0l+OrHvFNr8nnmpByr5BkOXHl89fYSZVkBiysYUqYzNI1kUAqQWXyprG22dhUKej63GcEObTB88X62ECeGFc2e1+EeLN/vG3SvetdpcgsndtmrKXI4Q6j8+xVmm4ICJvwMYc0OB9Q+uOSC0E2Ym2HhMZhlGbTOzzQFIZZJdm0A2drh5t64y5ZSJLT3YSQeA/XKRBWI4eV5mLrcN7T9R43IVaC/LNSIpFUQpCwGualpHOR7TC9H9OLclNPXhB4bb/m9x+12Th28qq6HoDNQGMNQnia0jA4T1lrBBJkIiG47hI+RjwTuCfASrjuPUYrmlLQjongcyiFTLm/ppSTVgW5J2+HSHIgNBzPDIe1ZdsOHB/NqIxi0ztan7hvJWetJ8RsrlVoiRCSfhwZfH4/Zjb7H+YBSCKQ6EcgJZSSzKrcxw+biqbS7FeW9883DD6ghOGf/NYRR3MLSbJfvWJNftkVY+LZZZuHba/qV6okN+uImEDxcmKd7hKf5zrL15aV4Tw4ev/ZfUDzp2/byd1G8uBgNqFMfYS+H5lZxfFM8sZhxQ+fbUkx4KJgcOmFT2ylQJjs0aaExqeIQ1JogQ8JRSJJy1uHM4pCUemeYBKLSvB8M+K942heMqstS5O99UBwPK8YQ8j+q0bw5x/s8f8LWYJ1UBm8T7x1MuPOomJRKS7WI8TAfm2xWqCEorKCvcrS9h0Sw2Fj+WjVM45ZwhtFxCVBU1oWhWCvNNmTNYEWEqvhP3rnnOfrnmcrxXfuzGkKzbw0maE6ep5e9+xVlu/dnWOU5Pv3F5CYLDYyE2g5BVbcW5RcdplN5KbAozgF41ij0FKgleSNwwYpBd5HHl12zEv9wrPo2arnwX5FqRVaSmKE+wcV8SJxus5+Rwfzgof7f9rXKKSE0fJFMpuUgm4M3ygJ2+fV1/pVSiUY+1ceSC9bfVpizhcpAxxUU3RxyNHH7Zg35yP5w+rI09RKZMRfi49v2ivyffsE0YEdHM5JtILtmHf4MeWNv5L5cawEoSTdEGnHnOISUoAEp5uBdoBllTesQ8oHhUUpSCRcgMsB0jhNiOU0hdVw1eXp77wQdC5hNMysZllKhBBsu5F17+hdYDYvqa2iHTyeEYGmKRRKSU5qy7p37DUFhRbUOqedaRJtSGxHx7Iq2F8UFErQjp7DmeW6GxhI2JgoC8tBrVkNkQ/Otow+cXdhebhXUplsPt2OgbrQvHXQEICTWaK2ktZHnlxu2A75lKCNohsci7rAxcS80LRjNtSrrWZxtOBwVvLsssUBp+sepQTfu7vgtYMK7xOn1z339ysO6oLHV1veebam0Ae8dtDwcD9rlk/XAxfbkbM48OiyZVkZtJJEkbgaRmZ1xVtHM/7o6RXt4FhpwcGs4GLjqApFqSWbuUVLQRKJDy87lBSse09lFU+vO47n5ccop7fjNUfvEULy228d4H0gxERTaHoXeLQaiTHxB48kv3ZvQUyJJHgZwSOAsymhMwEIIf4rwJOv9pK+eA3DKwbSN708eV3doZq7/tJOU18NMJk3O/I6PE7up4G83q9ceiEBCyHL1WS4CXnYbf4VH09s+6zaMWbFmNPU9CSlm+wvXgA2HTdMnR0QlID9Cu7MLSM5Evmiy2ENKcCslEiRo+OtNMTo8OPNaw8J9o3gcJE3vx+ct8QYCEkiSfiU2Ve7NFJDBtcQsNdYMlgsaIocU7oZPYXIm+K87k2srYmZ2wfP64uax65jiAnn0wv/o2L6e9f4PdC5HKE8L2HTTwwyMfVwByMOoxXzRhLrgu/dm/PwqOEfv3dJHzyPz1t6n0E+IWDrwIX8nNljKffeGDN7dVZoLiaPPyEkdRHz++kyOFjJPOXvXc/oE4VRXI+ey3bMBrQxbwy2g0OJyBgE9/dLCl3xJ89W+BARIgNXSSqUyEBZDJ7BB6wWHM4r5kUOZxhd4CIONDr3e6MVv/P+JX/x9T2+c3eeGdav6ksvF7OM6FV9M+vTzh4F07oToCglKUXQsB1u7iPIoNKgwLkMDCcyyNRNsuZd79jJohudn2yMN2CSmO6nyeuDkFmi1lSK2miQORxgUWhWEYYYmC4ne7DWkKLksDasnGdpLQJPYwvGGKi1RBtBEtlG4+6y5Ewknq5axjGncs6KAolAWo10jtcPa8wkoX102dGNiUcXA8eLIiddF9m+4nBmOZgVXG38BMrAR9cD/ZCHzG8dz5gVkuvBMQZPYy37leKp8xQGlDQIk3uJlNlWw4fIa4c1o488u+6IRGZlQW1gM+QUpKY2tGNg9AkjJYtK83xiP7223yBSQslsMfF8NeBiln1sBs/z9cDrBzXrwbEZPNsxe/ft11lBoJXEKPlCYna7eud5ctXxYWNz0tzM8nTVM7jA3WXJ20c1Riu+fTz/VLbojtUUY3oBSL0s9hW/KADpa024apRGileHg5ehDDeL6M8DHknyBlwKgZBZzlRbnX2C8AifWUNG5cmiIlPyk7hpEAO8SOwLZKDnuk+kFCjEjfZZyixrSMCi1jmqcQh4BTGknMQzjXrXfab8+5AyQBRzU8gGaoLGSIiBdnrxApBasB0Ty0ozLzRDyKynISYC2TBOy8jezLBXaz686Fi3LpucpsS2D5iUKKxmv7REKWiHgNERKRRCKYbOs/aB1eCQSI7mBcjE1dbR9oFlrWmHwBDhshu5qwQXnUJE+NbxDBcTe6Xh8dVAVXhqI9n2ARfgfDNM5qIJrRSNzjGZTaF4vBo4X/cA2Frw6w+W/Gd+7ZiLzci9vRIjNO+erfmDxyvmpUYhWVaGZVXkhiUk27FnjIn9meWyHeldojSKeaVZ9Y73zjZcdjkxwRqJJvFHT1bMrEYowbxUxASvLev8/hvB6mg6DHQj553ntb2SD84HUsoHsXXvaIfA9x8sQSQeX/Xs14bjefGnQJ9dvKabTM6tklid/x5c4Fk7ImKk0AqjFX/06Iq37yxeZk+L/xbwt4DvCSE+An4C/Atf7SV98RLm69+wX9Uvr3Z+e2piInny0MGIGxPldmpKu0FETPn2Md0YbcNNgttt8OizmOkvPJHIvkVCZrBDTAeO3c7lhdfRre+RwHWXr6guDFJMU+2pR1mZ6EIijrCVmUlk1TSkCJk5pRS0fYBCcHducSkHQlz3+ZmbAlTI5taFgVJBM8U/aykJMeJdRMqMLD267rO583Thw5hfmwUGmX86RmsWKrLp8p0Km4c418MkQ58GMnri8yclkCohZO6pVpNDI1LCx8BqDJzslaxdxAjByaJi0418JDq8TzjykEcJ2J8LSmUQQnLdDfm5FAgZue4jcvJ+MlrSFBbvE1fRoUMO9Fi3A0rmKObcdyJu+lwMPmbPkxhZFAYXPZedZ24T1XRQa6zhJ+cbtm1PJwV7dQFKYY3C+8hBrTmeVVz3I3YKe2isBBSHc0tjNYMPXG8c4mu98/4G1ysA6Rtdn2aKbVWWM+81lpNFwdlq4Ol6fMGecNycXdKQQeF2kjjvTLE9GYBvdGaGxpQlboaboABBlqeVJlssWKEYUoAkCAEGmXhzv+H+okQohbjasupAVpHBJaSEtgdrBdcusF8V2RduDAzesSgLCitxLnG+6plXinXn6X1kWZeUJmK0xGhJqWHbZQXDqnWElPiNN/aRUjIrFZVR7FU1nQssa0NhJO3g+fFpy2FdMITEnWXFVeu4uzBctR4FXHaef/K7h7R94vmq5cOrASvBakM75CCf/VoSk+CgNoQEe03J88uWZZ2HuYOPPNn0tOsOV1kKm+MuFrWhHTwkgYsR5wMXm8Sy0fQ+g0iN1XQuoqTAhYBVOSpvZjUHdy1GCa7aTAI4mlmO58WLz4JRkpNFweV2pG9HfvhkzaJWrF3AWsWq8/zWwz0+uNhyuhkZfeJkrrONyKd81m4PmwfvXyr7il86A0kI8Z8D/lfk/dS/mVL6X3zi9n8B+Nem/26AfyWl9I9+QdcFQJRwd1bA6fD5d35VX2ntDDV/3t6cyCkEnc80TSFgPfgs36oUAoULno2LeA9B5ucqNCzr7M3Q9zePZ8kyBu9zPGaYNuZG5rhNRZ5IGkRe1ER8MUVtrMS5iFEZCArTFHtWarZD1gSEAMZISquprOTxtXsBPIUJbEoC9mrLRetI0bNxnv2yQIgs4Vp1edPZFIbL7cCqdRRKs1dapFJZYjc6hjZyZ1FS20y9/NHTa1qf2C8V9xcl28Hz5LrleJbZRIWVPL1oc9pCCAiReLJyrIeARPDtOzMKrWjHxGU7UpkSqzT7TeRsk/2PLlvPw72S42XJ6TojdQ/3G5SU+BghCZpCczSvOF+PXLWOh3sNRzPL++eK7eAZfWRZG+bW4nygVJJ5odn0isOm4NllR0iJfvQs6zwVf3Y95LhNI3n7eE6IkR+fbxmCZ9xGlBKcXUcOZoaPVh1KCJ6vRg5qw7XIyW2zmHjvvOUnp1u+c3fOUWO56jxbF6itwkfY+hEwnzktkFJQSMXdRcnj6w6R4K2jho+uO67OHHVhGEPkTx6vSCLxgwfLz2w0X+cSQijy2v3XhBANIFNK65/h+7/yPlG9MrX4xpZgAjC+wH13ErcpcZ0ufXo/2vkI7YCe23KEHQvpdu38l25zoT/JUOoB4sd7oJi+D258+9Kt23ZS6lXnKHQ2WBYi0gd4vsned2ny6oDMBhLphiW16hPbYeCqG1lUhnmpCSFRyISXksoo0uCIU+9TCmZWEIGTmcUYyZPrTA+6XI8oQh52SIGQ4Pwk96sFpTU83USsUmz7KenNKAqjGPqRQeVrayowWhFSlmPvlxoZHT7kAU5dQVkYSOB8ZL/Q3F+UdC5yueqRIiEULKuC7dBjJ2m5VYJCaha1xmiNAPoQWLeOq00+ONYGpJAMMbNyUxQYDbXIw6beQ2kTy6akNIp+jDSFZL8sOV13DDFy2CgWpSWsIjMtCClSGMngIt04ooRACclmjLSupykFx3VDDIGEYjVGfCAbr9YanyBFwQcXW6xWjCH3zstu5HhefoFP9ctfX4cesashpa/31PxV/Zlql7y5M8guBOzVglm1M5SOaCmyjDfmM8fu87Bb+23M6/uOUQpT2qe58buT08Q6iQwyVSoDVRLJvLJsR48SEh0Ti0IjhMQogfOBZ+ueO3ND1xsg4R1cpsxEKgqJEhGSotIyM6pCYlZYlBTMC8v+nua7d2eURtMdJmZbg4uBZ6vsy+li4rz1GKEoG4ULie3oeffZhoOJZeR9yucJLWis4c0DwY+ebyF6pMzeQaWVrHvPG0dz7vjAXmn56Krj/rLBNZE/fLKisZJCaYz2XCnBG/slP7loaazicF7yW68tudx6LtYd6yGQQmQ9RmIIWJOtM+pSsx09WkqOZwXPVi0Hs4KqNMyt4kfP1lz1+Xw1uEiIkb1acbZxvHVYU2pFSonNEPjtN/aRUtC7wNl64MlVh1GSe3sVpVG8cdjgfOBPnq2JBOZlTUqJy9axLDQIsEbx5mGNNYoYE0+ve14/+NMSNrgZNoeUMiPpJQCP4BcHIH1qPPN0qPhfA/8M8Aj4XSHEv51S+sNbd/sJ8E+llC6FEP8seYL9n/oFXRcAKSZWr/wtXora0f5vb5J/ltot+s5lDXCp8yFepMBmSBgTEUmgp6mxkXA0Uy8mtrXN6Ss+5CnoLka41Jk+KlLkbJMnobMym6wp7bBa4H1CSMn9g4JhzDT4ESgLjQ8u+ysFwCSsgqNFhRWJMWbkW6nEVecZY8L5/BqMgYNaUxhNXSQWZU4U0ypvSjXZl0FridICabIWb1Zq3jiuyeHkiYPGctmNfOt4xh8/XfN8NXCxdTzYr9Ba0vvA1kU2Q96Y3t+vebA/4/Flx9woTtcdMQmsThzOLE8uep5ddXz//h4b5/Axu0f54OnHQF0qvn0yYzskhMyeT3uV4eF+xeV2nBowPNyvCTEgAJEEISQ+vNxy0Y5YI/iLb+yz7TPFtE0ePcCzdc/7Fy13liV/7sGCd043fHC+ZfSRe4XiT56uqaxmZjXGKH5yumHdO35yuuVs0/PafoVUhsoq0kQdzW6uiTEENr1DS8l153PqjRTslRqpJHu1Ya/SvH/RQhIoCcczmymwn+Fb1LvA8ymvOgHfPpnz7cMZl9uRmVFc9Y6nq54UE2NMvH++5Tsn85emiQCklIIQ4j8x/Xv7s3zv16VPfM2V2K/qz1A74OVnKcHHU0A/WYEbqUH6Kff75GOa6f6eG/DotqwBbg4uk3ruBfBldgyjCdSyE1vJaEGlYfQJLfO6pCZZnZv8ORqbgSYh89+FhEJNz5Fg3SWGcaQfA3f3K6yRlC5ysXUIJEbFLP+L2UjaCuhC4Hrya+iHSKElQ1AIPEYLiDAziSjhoDHZ5DVE5sWUuikUKUSCBJcEpcnguU8gY6K2AikSIUneOJrxfN2jtad1UJhEEgKXEhd9JJy1HMwMXZAgJRdbT+siQuafU/AgdGLrAgdYRMxg23GlSSkiVHgRoeRTIoZsvj34lH2pUmYmSQl3ZiX3Fzb7AvaeShku2pEhJMYAV5vA4Aa6cWRRVZw0BasxcrV1uBBA5v6tRDZyx4AVkUHlxLu9MvHaScPFJr/z15uRmLIX4dvHBQ8Paxal4Y+erNiv7DfeSPvr0yOm60k/v0/nq/r6VyArEmY6DxHGkBMglZCsescweoQULxQGlgn8n0qR0xsT+bOiZU75FC4/lpFQWY0UUOhAU0iMzPvHs40jqex+UyiJUbC0lm7I4EJpNb0PDBMFrnMBHxJ9SJRGo5QkkVmky9qyPy/Ybh1y8vEpjKTUmtpKvn9/j+0QshcskdNVwPvE+dhTFhoxMfNDEoiUOJkXQODx+ZZxDLx5Mmev0fzeo44r4yiMJqVMxw0hIkT2Vh1D5Hw9IKXk4VJhRGaUtq3neGYwSlFYxdmqhxgZkuDevGBRF1RW8d75FqLgZFFzh8gfP11DjFRa88ZhQxRQKEGIidJkdtQQSn7ztT1ciPyjRyv+4NEFQ4T7ywIlFaTAug/44Hm+UljriSmD9lIKjJK8d77lcju+kK6NIfKtoxnDtKe3WpLf/cR159Ey0faeQOJ0PfL6YY0UAqkEg/c/1ddISvG19zz6ZH0hAOnPEM/8TwDvpJTenR7n/wD8F4EXi35K6f9z6/7/EfDwZ34Vn1MJMLrg47/ir+rrVrtN9M5v4WfZ8O9+7RR5Y6zEtMnuoSp4AZL0MaFlolYCTOKgthgt6V2mK8qYaEpNDAFtLav1QB/y5tGHyRzZBCoNRin2a4tWipNGY63m+XpkZiWFqfjh0xWFydTTg8Zy3Y3UdaagIwS1lvzGa0tGH3l83dONnoNG8Xzt0dPI/O5cs2xqfvONJZs+cLEdkFoRQ6QpDaMPhBA5Ww8UWvFrx/N8sEnZAHvwOVVNKcEbBzVnm5E7k0/SXil4/6JjUVlICS0le7XkZGk5mhlW25YQEhSJprBse0dlFDOrWDQ5te3RdctRU/Jbry+RKWujL9uRg8YyuIRR8GCv4XhZ8fii5aIdubtf4EPkaGa5s1dzet0RSfQh0hSaxxc9x8uEj4n7eyV/3G4otWRRG2qdU9AEkXYMXFSO+8sSIyVNodgMgeu2ozKKw1mBUoI/fHzFojIkYG4tZxvHvEiMMWZ67PEMjeSgtmxGj1GS55uBUkmqwvDaQYNU+fH3KsPp9YDSmQZ7OLP0IWF9oPeBUqsXzSakRAqJR5cthZFU1uBD5Pl64N6y5Pv3F7x3uuXxVU9TaO7tldRG83w18OZhQyE/L/z1a1f/QAjxb5MHCi9ApJTSv/U53/e16BPr4dWQ4ZtaPw+jNfL5MurbjKJd//oslpMkHxykzAlnn7y+yVroYzK428+jZD7M3N5iDjF7Y/iUCEEiSLQu5tSyW/cTIv9JE84QI+xVIIQmTMOV0uavp5RZQyLB1idijJRKIkUGsA7nBZXROC94fu0wSqAEKBl5vnZIEYkpewVqJRhD7kfrPtCOAQ+oIf9EhAwMLhFFpLCa5D19zIBNWWVWbjtESpU4bCyNVTxZ9eiU6HxEokgxQcrJmz4artoxm2qHyNFMs+3H7CMiICVJP2bT07oyHM0KhgCLUlNoQ6kFF62jHz3bAZa1wqqAmlLp5qVm8IkIPFmNWCORWnK26uhdRGtBNXkQjjEwBnh02ZGS5O5egSTxfBVQKTEvCiSe0xToQ+LJeuRkXtANIz8aRj647IkpEKLgZG7wEURKnK0HJHBnWWbPjxjR33z25NeiR0A20R59+LlA6Vf18pQjr62zIkuLk8hgzbrPyYxaJGKC9ac0F8EEOMs8qC4EzIxgPjP0yRNCYvCeymgO5yVWCpQ2LAtBEorReVyIbIeRkASydSgl2CsLRhc4244IKdiMAakkIuXk4toYkgAlc3iODwkfIk1luK8E+/OCYfQ8uuq4v1fxzrM1z9Y9o488XQ08Ot+yHgONFhQxYZVACIFC0EV4vh7RSpASsB2xl23uDybbhYDncFagpeR03aNVts04nmWA/aA2/KNHK/6Tb+4xs5Yr6bO9g5bEkFj1jgeLCpciZV3zfNNz0Y2stoFfvz/jzeM55+uBu/OSwwclkiwl3vSOBwc1wxA5nBfcmRfc36tJMfH//fEZl5sRpTTfPip573TNXl1yOC9447DiDz5acbrtuW9qQkgIrVEiv57nq+FjZtkfXrSQEk+uey7bLLWjgKvWYbVDJMlfeKOhKQxXrePpdXdjjv2S+Br9LPVFGUg/bzzzA+DDW/9/xE+fCPyLwL/7aTcIIf4l4F8CeP3117/YVU9llMS5V/OCr3vtGvLPyj4SgBUZ5XfTQj/EyZsiAGNCjgFrd1rjLJ+KAc43I4USlDZrYC96ECKbf87xlKWhlhGVJD4BKafHlMbkDX7K8Y1Hc8Ojq54Hy4bOOQoluTO3xGTwUZBiQIiKwgjePm5Y946A5Lp1HC1qHirJ1XbgdDWyVwquekdKcNEnivXA6BL3lhWrzvFrdzIC3g0eMzM83K/5j9+/QAjJ3AjOtj4bYI9Z7vb63pzv318iEPw//ugppZZcbEeEyAwcVDYzXVqNnRhM751uueodDw9qYopo7ehCpEyJR5cdLsCDOw2VNRQG9mvLwdxSFopHl1tGF7ncOk4WmepaasXrBw1aCtoxx19ao+lHj0+JVRsobaIuFHWpaJ2nlIJ/9ME1LgRKqymN5IPzlsXMsGo9y5DN7UIyuBj53p19Wu8RJFzMsol177FKcWdRsFflie2jy555ZfJUx0XONgOLytIPga3zfOskJ+tsXUAhuP9ggZ+mOa/v1RzWBY+uOiSC7RjZ9j2rThFSwmrFQWO5ah3d6DldD4w+sD8rOJoVlEYx+Lzj2KsKfnBP4SZTbS0nk76UcCG+MO17ieoAOAf+6VtfS8DnAUhfiz4h7Tf+EPYrWz/PYS+SN0i3o+ZvQ4yaDAilmO87cpNu9mn9y5CZNeozLmSX/nnb4+hjt6nsm6Gm23evqfd5uHGyyIlmfmLTfuw6EnQOKp3ZtMGAkJLt4F8kj+78l8YQ2fYjWghkCviQv5ZSThvt/UBlB2pbEAWoJNi6yMxqkvAkFFYlehcQJJoqe0kN04WZmL0A96zitA2MHoRIkHyeyseET4nBh0k+7RmC4NF1S20thZGE6TGUECxLjTKSxhpGH6mNoimyCMX5QFMq0hCQCZSK6AQJQWk0LiTO1iOHtZ2GN0NmHk0+SyEmrFU4HzASFqXBKFgPEedGlDD8+df2+Ic+EbcDY8yfCWs1hRKYEGmHkMMUXEQqOJoX2Qg2ONoAD5YFPgp89GwHzzAGXEocziRaCa7bkaoQ/Pq9Be+ebQkh8viqp9Q6syDCr4SY6hfWI+DP1ieSgOj9K/DoG167/T1SEIbE2dqzP5s8LH2g7fNnYbfO7sIOJLBfAwg2Y/at0EYgtWSIkZgklYEQA7XWKKlxBKxM7M9Knm0dwmdmJUhGH7EKSInrdqSf9HJ7TZa4DS6gZV4rBhmRCMoajBSczPIg96zrkTKfMaSQ3F0UPDyoeff5hg+uelwIXGxG2nFgXhiOFwVKKKIULKzibOuYl4reeQqpKAvNw6Xl0fXAphuZVxYJXPaOO4uSq9bx6/cXOJ+Dato+csdAXWpE53AhsVcbYqrYDp515/nwss0qkMry7LqjHQeOZgVGQdevKXS2BCkLSesih8Cbxw0XG5c993zkL769j5WSkOBkVvA7753TjZGy0JQ2ByjMK8uskJzMLKXR7M8KjJwAuEazKDMId7sJx5RwPnC5HXn9IMvYKqMYfcDonG63rC33liXzKRnz3l7FB+ct685htXppfI1+lvqiANLPG8/8aT+tT+12Qoi/Sl70/8qn3Z5S+ltkSiq//du//TN1TOcCP3n+arn/quuzNta72hmT/jT20U4ycBsOTOTJbJxo+XUhcD4xxLxZ9uTpoxaCQmsKI7ncDthCMvSRVUj0MVBoRVNIfAAXIus+8K1jw8lizmXnSDGbXp9vBhKJWaF486ih94mrbUAKwbLSVEFwth5Y1AUyJoLIMiZt4Lod+ZPnLZWBxhqGkLIRd8yL2+HccNGB7B2FERRGIGTknacrnjeG0SfeOp5xd1nxk9M1Wsrst1Ronl/3nK8D89Ky31hmtaUJhrfvNIw+8Xzd4n2kaUoeHjT8ydM1C6v4jfsLRgdbl+mrD/Yqnq46EoHjecHBrKCxCgHMTEESEa1VTpMpNKergfUQAYmRggd7DesxsCwMhZU82K9483DGB+cb/ujpNVLAnUXJXp1n9ovCsBkCSgnawdO7wKLQPNs6Qkh0LqJF4PcetbgQkdM0/fFlh1UCJRoOaouL+T07nudYzkDifDuyqDQpQaEVRzOLD5E3DmqElGiRuNrmtIjeZYO9dggcNJYDAe0YWZQaJSW/8XBJpRW/8/4FR3PLdoi0vePDy44fPFiw6j0hjrx3tuVbxw2tC1RGct05liEDVUczS4z54HN3WfLkqmO/tmwHz2Jm2A4+xwRf9ygls4bcvBxMpJTSX/85v/Vr0Sd0/JU4iP1KViVh8xl0otvg0ifTdyJZxtB7YDK2NtPXC33jK5Rufd9nfYoGoEg30oZPluAGHPrkuGskp4Fqsk+Gj3myXZJ7XG1zcIIQuQ/uDLfhhhlFzGmks1JyUJWTP1HHuk05MppsZt0NibZ3HC3ycUiJDADJSfYdxszudXHIzM9FhZKwrCXXW8nJwnDRBkIIRMAoTdDZcwIBQkGpJHVtWSLZqBFSJCbF4DwhwaJSXHYBJQPrPqIFKET2WNKK2ghqqzBk41WlyL07CVJMfHjRcVgruiCQUuJdh9LZP6R3kRATIYT/P3v/0WtJmuZ5Yr9XmTzyStfuEZGRoiqrK7uquqd70ADJJcEvQBDggsAsZgCCS3LHDzDbBjizIPgduOCQBLgl0KLYpbIqqzIjQ7q88khTr+LitevuGRkZESkq0yPTH8Dh1/2Y2bFj995X/J+/IApBJiOTXHLdDCACk0ITEWyagc4HfIA805xMc7SQrNphlHwIOpdSPr1Pnh+VFGlz2TtMqVFKMS8FUmgsAT9AmQlmVUY3eIbOjelFEU/ySIoyUc3aITAvNDZGLjYDPwwpACLPDa31XDU9//qdA852PVWuf+82J5+r39gcAb/ePCEDPFm1X33g2/rGl42wayNlnozkjJbsuoEhjD554tX4WmVQZ4rBeopcYW1gXiYGpQqRvveITHFYZ9gASZwQWU4Muy75rhUmSdkaBuwQk0G/u2GFQpmlMVUKaK3DB2hsZJKB84FOQHSRRa25NSvIFDzb9ixLw2xUP/zkxY6HxyV/93iNCw7nA5uuZ9cNuBBppeDFduBwUqAIDF5yVGuKTHOxG7juLAsJ//B84MU2hd4MAbQSbFvLvDDEkPZJ141DRJhWCi0Vq/1AbhSfXOyIozXEpk1pa9NccTTNkxzPpvCB/RBQCvLMsO0909KTac3JLKcdPO2QkivvHVQoKThb99xZloQY8URuTwvWC8u2tygheb5t8R4CAhfgfNNzPe4RhEz7PikTU0gpwck052zTcd0NDDZgQ0DLZDA+LRX/9LxlkiuEEPzg/oJmCLgxNEdLwb1lyZ1F+Us3g28UDG+6H9LXBZB+1Xjmx8D91/59D3j6+YNGSdz/Ffhfxhgvv+Y9fe0637VcvU1M+J1XziuQ6PMA0U1k5WgH8IUAUsHYEOAVGGXHfyvSYB+ActTgTjKBIMU2WpcSaUJwWCfJjSTTBqd6gr9JrokUmaI2EpNLdo0lM5rWQW00nQus9z1aq+T1YD1/+3jNo+OSSV7QDfDkuqEuFbveMikyrvtEIx28Z57rZJSnITPpV88owazSDMET9oJb84pAw74LTArJ4CKb1rLrAg9CxbeOE/voctODECyqDOcjt6c5Xe+42kVyrbh/UGJdoDKS+4cF13uHEIp7BzVRCK4by7QwFEYSkeyGxJiZFpqq0JxQ4rzgcjektIN1T5Vp/uhujQ8Jwbna9WgpyI0kV4IYI51NPj73liWTXNMNqYsMcL4dKI1m3VtiDHx00fKt4zotzJVi3Q6sOsvZpmNyPOVbJ1MeX7dJ2lZmsOuwNuCASmucicyrjKNpRggCFyL73jEpNN9bzHiyasiUYF7kfHi+pxs8vQ8cTDImhebWouB8M5CZQGk0kzwN8lUmWZQGrSQxRJSW3FtUVLnG+sBhndFYjxKBUks2vWOam6RNHxyf7VoeHVX4EKlyw7JOyTzrXc927NA8XrXcmhc8PKxTR3rT4XwYddMlkyLJ3b7MeO9NKSHE/zHG+N8LIf49X7CojzH+H77iEm/EPPF0+1bi/KZUztczvP669YvAI/jZuebzhwWSRKFUyQy1BrxIGwdnk8G2ZGQjMcoe+MUNkGxsUw+vIUQ3c19ZgI6JpbQffp6JFICKdL4QKdjBkzYWETAxdaYzBdqAGl6lxpkxea02UGYZR5OMx1cteWZo3QAugVL74ZV0b98FyiLQjvIvKUGPpkwxwL5NyWWLOnAyKzBCcroQyU9IBMr8xg8jMTVLDbnR1FoghOS0NlzvLW0f8B6kdAlcKTVCCKxzeGnRAspcshuSdAQb6AZJZTQyT47gfYAjo+l8ZLCenXUclxlDgFwFuhAR1mO8pDCCXKnR2yikBlDncSEyzzNCHtl2nklpyHxEiIiLgkLB1d6iZWSWG4SINEPk6arFBQnRMxAYnKe3sMORmeQ1EggJOSQxTA+nBZtdRwiBOlNkWvJs0yJCTGuZEGj6gc4PdL1nPjFkSqGkYFEpjicZMcKqdWy7wPE0Z1oYfo/rjZgjAPoYeBvY+c2vG5ZmYFQmiFfecgZeikJtgMpHpJK0nWOSG/YuJVoG+WpMr3JFnZvkAwQYFehi8oVLifEJRLcuoHPFoS6QcpTPygQUXO0SiF1pTe+GNObqV0ENY7+YQku2XQLkZYAq16yanlorhEo+O0KCDyKte43mfDsQJ6CV4vmqx7pIYx3r/YALHiUkXgRc8AxW0lvHnXlBMwSUUhxNcq72HZc7x75zuJj0zoelISK43ls27cCL0Rvoet+zmORURvP4KhlzSymIpOS5j8923D+oOJpkZJlMoI9PwMm+dwyDI2aSymQpiCH4kRCWGPuD8/TOczIp2PaOXe+4agaerVoWdYa1nqfbjpN5xovHHRfbhkjk37x3RD/4tC+MkjKTbFpHtbNIIZiN46iUgvsHFS+2HYvSkE0TKHi27TmZ5Hx22XBQGW4vSo4nOc0QEuC07V+mqd1elOS/ZAO4s4mxGmJ8mcj2pjaRvy6A9KvGM/9n4H0hxDvAE+B/DfxvXj9ACPGAJHH438YYf/x1b/yXKSF+s4vRt/Wr1evbsy/q9L5uIJqP/w7jsZmAeQHXbXr9ZpGuSAP/zUAqgUKC1RoRIoEUaykkbAZwNpJrT2HgeuhTt1YKOhuxIRBioKgLFoWh6z1KwlGdwKPN4DFCoESg61OCjBeRdoh80rcURtEMns45Nq2lc6BkHOOMA6vOET1II6mNxIY0OV3uBlZ7S3SBd05nNINj3VjazmKMpPVgZOSqtfzkbMutRcXJDGZFGlSG4MlNMoU+mAoG6/n4Ys9+8Nye5fzNJxu0SdPhvM5Sd9MmY+sqM2S5wofIxAgWk4JZqbjc9pzOM3atpbWeaaapS00/JIBoWij2g2cRPEImWu/zTcfxJBtjP2UyUC00UqT0mMu2Z9c7lBBMS8NJnmij9xYVQTSs2p4QIk3vWO17cpMAtBjTZ703rxkmjsJojBb4ILncDvz1pxu+d2fK/eUEKRKg5ULgw7MdTe8pMkVnA8Yo/t13j/j4xZ5n644Y4OFxxaZN368qF8wKjVapo6CEICqBka+6B0oIykxT5WlH1jvPi23/6nUpktdGSGymbkj3e1gmecXDw4oi0y/BoXtjqsOjg5ohBBSCfExt0Ep+pfHeG1L/J+C/B34KXP8K578R88TF1eaf47Jv63dQNyyh15lBr9cvI2m7mWd6B6VJ4QbDGLd8E+5705/KSIuq5rX3YbwHRZJUe//zKKsxqct8E1NfG9jaV9e9YSYF0vvfAFU3m5zejcBPeCW1a27uUaaEn6aHTsDVvktmoSr5HB1WBusD51v/UooRgMsedJ+ul43vI0hvuqgkUkhCCJRG8a2TGVpA+2TF+dYihOCwTh50z9YNRBgcaBXAZCxrxdk+mce2TifmkUuSsV0PB5Xg26dT9m2PUDGBTnh8DAiSCayUIj0wISkkdNbio8AGh3CRPiTT1/OtYFqYBD4RKbVC6UQna/shsXy8J9PJ5+mwMjzf9uQiIqSgMIrjuuDBQUUfNnRDet4jHJTmszqjHhIQlVcGGFJi3OCIAQ7qnKo0DDZt/qyLVFlG7wPP1z1KCYbBozLN8UTz2WVL49IzKZUgzwyCmObi3KC1JFOKTWs5nuRcbHvq7PeahfRGzBGQfue2w1e5o72tN7kMaZ8gdDKxvwkSeOmlKpMFRjuO1Y2HuQmsu8B3TiuI8NxaXEhjtPbQSs+8zLg1L+ic53o3YG0gKIlzKVQgzwxDANd5qiyipMaPLMaq0CzKjB/cm3Ox6am2is+uWiASRCR0EYlkVhryXCGkI1cxMSGtRSjobZJUXTaWZQUX7UCRC1yMOOv54Kzn9rykG5n+IkJhJLvOE0RKUosRylyRaYHSkqVW3F5MiHiUVFR5pHeBXClkmcahnfMMPq21q7EJ0jiP2w28d2T4zu0Jn1w0iCiYa82DZcWut2Racjotudh35EqxGQb2vUUrTV0kVYDRnmWVgUwhRtdN4GSakWuNDYF/OttyMsuZlxolBVf7gdxIfny2oxkcH7zYcf+g5FunEyqj6axHKclRZTisM35yBocTwZ15gRCCdZv8p3KpMFpyd16SZwolEhnh08uG1nuWdca9ZZnYn0Kw7x1Gy18rTe0mrc0ogVbqjW8ifyWA9OvEM8cYnRDifw/8v0nrkv9bjPHvhRD/7fj6/wj8n4FD4P8ySuRcjPEvfrWP88U1KbKfAyze1u+mbhbuX9Tpff1rAUx1AlhCBCLshnT+tEiD+r5PNFIfXw3+LsLzPWTacX+Rs+oSSJTr1GFtYkpCMCp1cK2HeRmpppp967Aerncd1geEiHgv6H1kUWdc7wdipiDK8bVEJx1cQEq43ntW+y7FZFYagsAoxbZrmebmZVKCUoJJkeLbd53juMoJUeB85On1njpX1JnGOYcLAq0g15JJNjKSOsvxNEcryXU78PSqwUXIlKIdApvWsulS6lsmYH/gmKoUzwzwYtXio6AqFZkS3JqVHNUlT1d7rpuBVWMZvEc6CTJiXeD2oqLMNc82Ld4H7i0rHiwCF61DxmTGenuepZSyOoEl1geWKmNeGT54tiNTmjpX9C7w5LrhcJJTLDSfXrf8+MUO6z0n8wKtJdvO48dkt0ILFpXh0dGED8+2VIUmk5K4gCLT3J4VtIPnbNcnY8CzLX/9yTX/4cMrciV5cFhhlGBwjp883zEpNKe64HiSMc0N9w4q/r8/vmQ3ssXePa65biwPDysynQbxZ6PpoBmT2H74ZI0fpWgPj0oGF3AhEkLku7emCCmpjOJyP3A4yfACjqc5RZa+B1pJNm3Px1f7lNIgEnj1Ytcj9z2ZViwrg5Lym2C890II8RD43wH/i1/25Ddlnmj6tzLnN6FufIC+rL5qPr9hqip+cXRGCbRf41oAG59SzKwHH17NUTcM2JtOdinTXFQm64u0CYnpMxUZ9MOrBsgig+3wKjU0juBUkaWus3/tIdwATj3punq8to2vIqfD+KGte/XZJwY6C9sRCCpUur9V15OL5JsRhcD78DPvddPAGZV7aP0qqloJQEhyYziZZWiRJNu3FiV/cn/BJ+cNzzYtCigLRb6TZCake1IJCqvyDEVk3ytWDAQBk0pzPC+QMbKocpSSuBApoyWKiJSSwQYKzSgJCBSZpNSSbx1PuNz3XDYW5yWts1yc7XiuBcup4eFhTdM7fEjytSJXGCX5rN8Dgl3rOagVu8FxOq84nZRMC8XzTYeWyUh2VmnuLmuu9x2DSx5PWqVkphA8OxtpOk+UkcbCrVnBECJGQB8kU6HIVWDTO5reMSsNh5OCwaX0u15qikwlcMgolhPDtrUcTtPGZlFmrDtHrhXn646jWcnZpuNbx5OUAvjmNxp+5XpT5ghIIOe2ectW/SaXJe0t5iOz5+a3RosxMOe1MV6SAKchCLSIXHee1of0ugQToTA3LKHI4AL35iUiRtwmEELAibQ+jzEyjCybSmtqI3h8vUNLhXWRs03Hxa7n3ZOaPEtebs4LQnB8et3inWdaKSaF4bjO2XWWg9rw4/M90nsGn8J5lBLkWrHDY9Bs24FN51AI6hPFUZ2z6SyXu57OejJtKHJJlaVm8vG0QAu4N684mOZoqTjftVS5IvjIJEuzzrQwKJmSy2aFprMphMi7QGY0RiVvICEgU4IYBdeNY91suLesuNonAPxP7y34q09XWG+xUXNvIfnkak/jPDSB908nTHLD81WbggNczsODmnvLiqbzHNYZx5OSXT+wrwxPVy33D2qOpwWfXjY0g+dwVvDZ5Z7Prhpuz0eFxLIi+ECuNUanxu3rlaRsaVSVUqCj4O6y5PasoDQduZZIIRicJ4TUkJHqV09T8zESYkSr1Hr6oibymyRv+0oA6deJZx7P+Z+A/+lz//c/vvb1fwP8N7/sdX+Z6rx7Cx69IfVVW7QMyE2SBygNhVJ01tMPib5ZZ8nvJ0UmQjde8KbDC1DniVbah0CpDYeV4qKxDCElZwiZQKfcpGvmWVIx55lioRK67txApjQXm5Zd7zmd5hxNMvZdYN0NCOBgXnJUGM53A96FtFjUkvNtz75LvjqzOuPWrOCozni86th3kRfbll3nOZnnLKtkPK2aZK4ZYtJRX+0HhCzYto5padh1ntZGchUpM8m2dbgAMQZO5iUfne247gbs4Gk6SyBQGoMHPr7aczIr2HeJSbUoFXeXE66ahqutpyvDiNprvnOr5Pm248W14/ZBxr73fPB8x6r3/OtHB7x7VPPZVcOjw4ppoZg2lgBs9pZ1l1IJMq2pM8nxJOP+QcW6seyto+0tn163OOewLvKD+3M8gmmpKI1kWhhyIzkSEh+TpOvWouRi17NqHYOHP743pzYJaGmHwJ1FSa4VzZC03IKUiJDngocHJZfNwIttRzZqkn/4eMXteclikqOk5O+erjmpc05m+Uvd8+V24Giaken0E+XCjXF40jbblx5KyW+jsR4tU4SoUZLbi5JMSXyMvOcjjohG8HSUqWklGZzncj/w8KAiM0k3/w/PNtya5aw7x2ADz9Ydf/Zg+TufJL5G/Q/A/wt4F/jL1/7/Rmn67ldd4E2YJw5nJbD+53yLt/UVJfliE+nP15fN5zeAUCZSQ+GL6iaoYSrT1334cg+jSAJ/bhg/r6emvT6nFaPrtpESIQKFUjQuMHhBodLiMFioDMwqxRA92GTYLETqiG+7BNK8fh83G5kbYCgwRt2P9xIB6RP4VOjUHHFA79O17ciY8aPswhA5Xmg2fWAYmbA3z+Xm873cVJEYTEqlzrzzMDhPpuRLP45d1/P4KnAwyXl4MqHxnscXDS82DY1NPn9SgLOOXVDs2oGr/cDgAz4KlJREIZllBoTg0WHNbkgSiXMZ2baOUgtE1ESZ3t+YNJE3wfPxVUOZKTatS/HOmWDwgnVn2Q6Oh4eao3lBiJGmddya53RD4MNhw0fbJklDZKDKDJf7JHvohoHDaYERkbuLmn7wzAtNJnM+vurIpEAoSV1o1ntP8CmEQY6b0F2fJBFaCya54qA2uJFhq6XCyEjvA7PCMCl08mbynn07IAVkSjOvFYMLDC5wd1Zwa15wPEsef0YmI/Tzbc/9Q/1NaDT8WvUmzBGQ5IWb/m0oz+9D+QCTAnbdCOwLmOWJLdm7V2B/VCBJ6YvrbY8fjbARrxIu51lGphQhBi4by+Xe0btIpiWzQrDvPHWZM59qdo1HaNBS0A6WPIP1zjKMhviLUqcIeKnJZIqhj0IxxMC6sSzKgu+eTnm8btgNlmmmKfKCbWvxIabABCNpnGfdJUZL8IFpafA+kJeS7drzrZMJm87RW0szRI7nOdPcMK8MZ5uB5TSnMJp1M3C57dMHlgJtNE1vmZWGB4fluP8S/ORsz8ksRwi42A7kWvL9+zOsjSyrnHawXGwHdoMnxMhBbQgxWY1853SC0YJn1w3P1x2zMmfwHavO8lcfryizZHydaZXGSxd4umo5nmZoJFf7Pn0W77luBh4dTXAhPf9973DWc77pKYxmXhqklPz4bMu3jmuqLO0zQ4iczPKXthtSJgnZ83X3UpZ2Z1QN3FmUPF93bNr+ZaP4xpriV5WcqbGZfLNPcD78THrbmyZv+7oStl81nvmNqOvN227Bb6s0v3yK2uvnSRLlHp0G9zoXido+IvxSkpJKXJIDZLxKxrmRGhgtKYxOvhV58hmKu0ihJV0fcKNers6hdbBrHZUBhODFLqIVKZaSyG4IBOl5umlx12nAuzMrKAuNFoIgEkPIRzjbDHy67pBCIqTCR8++s5xOSy4bR4zJ30GOJmxGwt1lyXawXO2TMeckk5z3lv3gebgsuTKWs11PCIF3jmdY6wmBcWCETy563j2umVYpQe35qkVrQaYytBT0NnCxaSmk5OQ0sYGeXLc8Xl3wbNUyyzVIkAhcH1gUmnlhaErLRxcNd+Y5xyPD55PLHfMi49FRzbzOKIzkcu84mGhuz0qu9h1FpjidF3RDYGsdL3Y923bgfNMlHyUpWEdBCIFVazmeFRRaM68yGuvYdgObNpkDlpliVpp0jwKWlcF7waPbE8pMc77rUeNgG2McE9ki+8GxazytC+w7n0DCaYYAjEq01BgiH5zvqHNFZpIZ+OBDYjM5/3IQl0Lw5LpBytRZcS7wZNPzrZNJAnYU2JCMx2/M924An8EGnm9eDfaLKkV79i4ZZR9OMrJx8BcjAFVmmrowhJDkCka/+clgMcZ/D/x7IcT/EGP8737X9/OrVl1/3enwbf1z1a/b6DHAJBtNn5MtzS8sT2o0BP/qfSuRWKpfNH/dSKtv5rfXjbeL8dd0WijmE82uCfQ+JXfGGHEuIoxGS5c8lBRse89gR7DLJPlZ04+JbvFnQydu5GovvYgk7O0rplYlEwjUDa+ApkIk8KgfXt2r9Ym5VOaGWV2wnEqeXDVENEUZWa8c29ekHNx81pDeUyvJ6VTTW48QcN04JgaWZcbzVYdAcLbpaYZIlWumheTxdcumSSBUCJFp4ehsjhQ3IrA0VuZ45qXiYJrzdN0xLwzvHE0pM83TVeoiF0Yng2otuGrTWKqERitB6wL9MLAfHDake85G/5DLXY8SkfdvzciPJFd7y8WuZVqWuNjiHVzvLUYpXmwGtBQUWYaJgnU7YINn20eUgqu9Y14aiLDpLRKBkhCEJjMBaz3eR64bz7QAKQ15DOw6z3KScW9R8pOzHVf7ntYGrrQl13BnXpPCgiNReDID+yZirSPPFEfzknuLEhtS4p2SinmpOd8N/OCb0Wj4vSgRoH3rof2NqdfH0c9XIMmRyzwxOCeZRAhJnQWebgKRNO63AwxiHHc9ZFlACZAyyXgJEKOlaTwrJIIeFwLGJGXBunU0A7jYkamKqlTsW8euG3ixccxL6IbUdA5CYm3kbGsJzvG0cxRacH9Z0tmMi93Ax2dreuuYF4aTSUEhVfK408lPtcoVhVHMS8OzlR9TNCWZlvggOJ4V2LHhOSklJ7MEPn3v9px7hyXn255JllGaNNafbRu2vWWSGcxEUWpJrA1//s6S946n3FtUfHK1Jwp4et0xLw3vn05YVhmHVc7FbuDBaHT9d483SNnjY+R4lnNrmrOcZERBYlk2A0pJChXYNJZlZdBaIGLkR8/33F1WnO/X3F+WlMbwX717QGUUT1Yth3XGotBcN5bPLnfcWpQczzKeXHZJ/h0it+YZRikOJwYlBX/24IBt5+i8p1CKu5+TixVGfaEsrTCKe4uSj6/2LxvBvwnJ2eEk42Lb07vwEiSSUryR8ravu2L+VeOZ34jKsjfTgOr3sRRfL57v83VzTge4fqSMApVxDCF1bIchdQpsBBlf+SbdLJgDaaFcGUEMnudNZJ7n+JhMqHntuC4kk9HDiWTwkat9cu3X4+/h1kd8SF5JzgX2nWNe5tSZASlY7SzvndZMi5xV2/P4umXd9iAitVEjRVVyWBfcX1Z8cL7matdR5ppCJjp+jOCJbJpEra9zTWYUn141uBDZDJ7lNEcowUGVoaQkL5KRppRwsbMoCZf7AYmkMpJcD8zqjLb3dNZjAygrqMzAZ5d7FnVGa12KKZYKrRXr/cC6s3gXiD6ktBqpyKSjsYFFaciNYpIbTmc5t+ZpIqiKjLvLgklhaAdHawMxwEdnO07nJd7DPz1ZMUTBvDA43+FieDlZPb1u2XQeLfZMCsPptODDiz2ns5xd55mXOZf7gVuzHIlgWY9StW3P3WVFAM42PTEmMObWrEALwaZLbKhb8xIj4em6QwR4//YUYnpel7tkIvhnj5ajIe1ocOgDmVIc1RnPNx37wfJ01b3sQhzUyQ2kd55y9DKSQvxcysIXDfarxnJvUabo1wiPV+3LTsONZ1KIES0kgYj+ZsjXXtY3GTwCuLx+65T3TazXNwiOxLIxJgFJ2x727os3EIcVRCGxTWAy/poJDca+YkHdeBwNjEEN/Py1Rn9UJHC19wgl2HaJ9VzmikWpkSKQK+i1oBRp8nIxMXrEmLDTuyRRi69d9yZx1JHkaFubQLE6vmIaZTp9Xu3S6zdznBDQ2p8F5QaSV6DwgUme0sZOZkWKjI6Ro9LyyUX30kz7Zl4OAepKkQuFUoqJUEwnBklqoiAEnXM8Xbf041yQZ5I6T+k2gfQZlUwg1nYYUEKyrA0hwvVoLv3jsz2ng2fXWIwW3M7y5DlnDNM8Q2vJxbaj6R2TXKO1pB8Czzc9mQQRAps2pdFpA94JpBFMcsGsNrS95WoXuW4Gtp1jWki0LDjbdMyqFD7Ru8imdSwKg5eSR2XFECLrfY8Xgn3XsekimYLOBqZZMmIdNp5SC5ouomRiMRgpKTPFo8MJeabxMXC176m1ZKcku8GDDWnj5zyzUnOapw3cprMYEZnUGSezgs46MiOphKDKNPcOquTP0vs31mT197GEFlQVb41VvwGlgFol0OeLegmNh9wnb7tpkWwjpE7rwUKP6chhtN2IiX2pgOAS8NQTyEkA1MU+4qOnyD0KjXWe0KfABKUgG5sMV7uOeWVonUcQKYxk2zsGN8qO88izfc92sEgludr2rEfWZKZTvuYQI8akRMamD2yHQNM7DqY5y0xzOi243A+UueR0kdMPjkhECMmkkExGD89JYZhLya7tCUDvHS/WCfz69q3ETtp1jkWZc1CX7HpLb5O53qI0lEbzYFkzKQ3vKUk7JI9TEeFoknNnUZJphZbJJLuUaZySCOpMsd47gu/IdPJRfXhU01rHf/jwkjrTnMwLjIKn1w1CKJSWZFqgvWTfWH7w3QV3FxW982RacTLLudoPPDqs+ZvPVkglKYzie3emTEvNg2WJVAIfI70N3J4XVJlmN3hMlIhfAMRI+cWytChACvGyEayVpBssnfMUWv1SwM7r7CJIlhev+9p9HXnbb7u+FoD0a8QzvxGViTe/i//7Ur/qnPr5TcCNPGDVjMkIbvRhCEmnXGbpzdr4s/I1CbxYebSBRal4eFDyeBXIjKMdGZi5gYkEI5N/0Y1/UuSVLEAIRokYZEqmGF4fQAo2raPOFe/fntENqctw2VhiCFgXKTTkSpBnGinhsk0+TJnW1Maw6wemheB4mtP2HiEEk0JzUCf0vcwks6LivZMpl/ue3Cj+xb0F227gfGcxSlDmiuutpSVp8hGRaaHpziPRR6yLKBHJMsPDw5KTacHj65aLvWVZGya5QQpBiCm20gBDjLzYdiAkMgauWsfCZnz/3gznE/BSZIrWWtohUXVjhHmpaXrPtDD0LjD4yI+erlMH2KTvgRDQuqRVPqjN2NUYuHtQ0dt0/4VR/MWjBd4Jnm0aRAzURuJ8Sl0IIZKZBK4g4L2jCSfTnGfrFiMlZ9uew0nGe8cTrnaW1jomRca/PZywrDNmpWbVOGwUFN7R9Z51l+QCH53vqQqN85FHxzXnuwRMXe8tRxPDJE9D5dmm42hMwNn37mc6BK/Xlw72Yxfj89TY79+ds2rsl173bf3zVftWlvCNqhug5HVAJ44v3PjkEMIXgkeaBNgYFch18sjLjeDFSL+Jo2+RI20uMqA2knWbxrz+tfe72ZhMinRD+z7BLrlKC+fORkII+CCYGU2LowkJ5ChGSlPrEuvo9XsNvAJ/bsyzXzflHnEojIFcJsbsjcStGpGvbf+zDR1D+qyTUhGixAXHpresdwNFYTgqNHWhEdLR2xQ1rXSaK9eNZ1ZCv0/uIE4KRAyjiWtgOUq06kLT+wGF5GJnCUGQm0gMSXLueihNIEp41gyYTDJ4zyw3BB85WzU0Fs531/zT8y3Hk5xu8Ggl2e8cWkmMigxBkCmJKSWX2w7rAvcPcta9x8a0cSsLzbRM3hYfniWvkUWds2l6LLDZDswLmb7nSPbWM8kyci25fzylHxyfXbdY58myJCe7ajyGiNSKykgeX3csa0OuBTYq8szhfaRQKW311qxiWqbGTQyR830PQnIwLfj2rRm7wSNiYNU4cqPJb3yQpOLWScFBlcy2Y4Bt53AuspwInqw6FqXmdF6+lFy8rX/+kgGatwykN7pemmGTxkLXJpWA42eBpBsfu1xAnkmWdZlCXLqU3FyPc8N+lDlkIsnZXm9K5DrNN1YkphIBbEwsejeO0ZkkGUybxL7PFGzbSOcT2z2ODYjCwLTUXG1brqLg/kFBkSmu9h1PV4FMChwR7yKXu55FbYDIrFDcXZQclBlBRG7NCpRW9Daw7fZ0PiUkz8pIMwQ+PG84qHOkFGzbns+uWh4cVWx7z9Vuj4+RBwcV3z6dUmeK7Rh+c90MXO4sSkYO64zTWcHFfkBKwUcXOz67blnWORDZdo7Wek7nydLhk8uGazvQWZcSOhGsuxSY01vH0bRASUFpNP/q0SHOe/7u6RoJHM5LvE1zc+cD693ArUWBQjL4QK6Tv9RPz3d01nG9d9ya5Tw8qHh0VNMOHi0lizLjw/OGOk8N8T+6M+Nin6R2pVH0zvNs1fLwsP65hvAX+Q59XnK26yzPNh1RgJbySyVmr18T+LmG8+VuoD7Qv/C9Pi9v+13UlwJIv4F45jeitt3w1Qe9rd9Y/TIJNzdVqtFbYfz3jbFdH1+Zk05zQTNEXEigkh7pToY0QEs5JtzE1KWNQnHZ9AQEk0KRy0CIEGRazG77URYnXr1vNm4+1BjPuSwURpFo80ZhnefFZmBRZzy+amj6xFpZ7we0VhiZFuPCSO5nmoNJzuW2R2vFD+5VnDUD6y6y7wc+Og8czZO30q5z/OSsgeApMk1VpUS33kXuzAtuz0tKrWmHHctJztmmp8w000Lz4Kii6T1PrhpuLXJKUzEMnsfrhklm+PMHBzxedZSZYtU6JEnqlRnJtnOsVg2DC+PGQRJDIEbB3YMSicCGyP2Dmj9/Z8lgPX/7ZM2H5y1aBN49nlFpifWOk2mOkoIPznY4H3jnZIL3sB8C9w8K2t7yk33PxxcSrSWzwnB3WTLNMlrrmeWK82YgRs+297xYp4nlwWHFskoU10pLzjY9CkHvPE9XHVWmyDPFUgrOtz3zwvBHdyZoIVLnA1hUGYPzPFn1zHPFoi4JMfJ80/PR+W5MXYPee/7jh1fcWRSczoo0MREZRpPZwUXuHVTUmf5SI7svGuytDzxZpZWnIHle3TCSbq4zK8wbY5D3h1bT6dsu/jepPi930+P/+ZCMo/shsPsFmjhJkkAHkmRaSnixiXjS7+bNT0Ih05xQmsQyCSLgLZQi+fRtw6v3nmeSqy5gh/QGLnr64CkFeCGIRHbWYocxKc0l6VmZK7QO9M3PQ1037NqbkeAGDIohzZlGp7nuRRsZ7ZcoNHQuzac3kdSvN3ZihK53XO469oPHh4BSmugj+yCY5oqmd6lrrhL7aPDp6yKTDIOnGQTF4IkCdr2jHRyFkfgQycqMu9OMvZfj2iuxdfqY0uUi0HmfbhBepp26EFnvO7yAZZUxeGh3PTHCcW0Y9w+E0TepszaFa3QDuz7gPTjX4YHaKGaFxCjBaj8gRGSSmTS3tD394DFGsQ+BwQmOquS9FEPkep/isz+52LHIU+Lnrg0EATGmzV5HpO88uZaAZ17UTAvDp5d7lIjMKsO0zOgGj3WO1gU+u9yjlUq+K6MkvzCKQORim57TsjYMHmqtII8UShBjxLvAvcOK01nJySTjunXMC40UkvvLNzOh5/e1egLfIGLwH2RFEuh/VEtuz0ui37MbY51fbzpExsROB9v9wHSRM68Mm94S7OixOoYHTEdv1Wb4WZaoC6M0WCfG5410unVpH1QKqPLEsGkHR50ZepvSjLsBqkIgZRrcpJRoIYnBorUiIumGAaPTfiDG1JStS8lqP/APj68pjOZoWvDg0FAYybrzZEbxJ3fmPL5qsDZ5g9ZGUCvByTTnnZOaeZEzRMezazjff6V9fQABAABJREFU9lzvLc51KC05rAw/Pd/xfJPG311nWdb5aLBt0FLyL+8tWE6LBM6fb/nbJ2u6ITAtNZWWbDpHjAkoqQvD/cOKZWmIAnobyLTEWs/fPGlpfQAhWNaGy33P0SznqM6oK8NnZ3tebBq2PnJQGspcsSwqTqYlVa642PXMC82ud/z1p9cYLZHAt06mXO4Hqkwz+MjtRcG3Dmb88e3FS19SRxrvhZCcbxP7p7eBo2nOtDDAl/sOvd4I7oYEHt2ZF9SF+VKJ2eeveTjJvpJd9EVN5991k/mrGEi/bjzzG1E7+xZA+m3Wr5JlFF8DjyB1Bcz49U388b5PZpxDTL4V1ZiK08W0yM1Hf4gYEmVUErneO7phwId0bu+hVoK8UrQrRx9eGeXdAF8uwv1liZGKy93Abgh0Q8TiONv0GCW4NTU831pkCMQQ2A2eOstoskCIA4GAMRIboMo0RinqKuOQ5LWQ6RQPX2vFJ+cNUoD3lsJIOue52ncgIkpI3jmecv+gonNbpJR0g2dRam4vKi53A1II7i9KIHV/r/YDIabF7hAiPz7b0tvIrXnBeyeaRWX48GzPvvfEENl1nt55pFIsS8VV47k9y5hNEoLvQ+S7tyZEIfjLD6+wPjCvNCLC03VLZhI7aVrAJFNkRmK9Yts6DuqcSIopXdY5RzIZZl/ue3IluN5bamOQEkymOCDjLz+5RkvBO4cVCJiXhtvzAiEFZ+ue42lKdfjHZ1te7LrUeYmGECOVUamrFOB8P7CsUtTm6bzgctdza5an79+85LOrPU03AIIq1+w6T525dC9K8GLToYTAx5SoE2IkRl7SSr+MNvr5wV4AxJSm50Lk2arl8XXL3WWZ0t3MK9O+39cknTe9rldv28rf5LpJJwtjN3fzJYZKA2nO8R4mE0HTx5cgy8084EnMGz+m8lw1Du+hsWnjkKsEAPlxvtnbgBuviUjzUgQGBXePCoJzbNqU3hPGTUnnIAaPUUkul2CEV+BYLkb59siGNf5njbPrDHqbPreSiVI/kLrikVf+TjcMW0u6525setSVZpKVbIeBEAT3FwUXrcITWXeOvgt4CWEADKgI0zLD+R6pJVoIrvaWOpOEmLyMLvzAf/3eAfPCsO0m/P2zFeebHiFSF7jIJIdVQTMMCDzrLlJpxVUzJK8lTYpGth5lVGIKh0iMEWKgLjNyJbjYtFw2jiwTGJkYZft+ZAwEz7wWySeo0lgvECqxuNZtjzESM2pGcqN4dFzyD8927HrHYZ1kDWfbnlwlBnLnwmh0LhiCT8lMRlBlCusELgZ6HxBCYozBWvB5YtYqCVfbnkxLTmYlq7bn+bqHmGTOp/OcTetZVoaPLlNAxbzOeHBU8/hqz8eXDfshcDDNWRSG5aTAGMutWYEbgzve1m+vpIfN26nijavX0zRrCVkG0iiUhKo07JwlM2m8/Hy5kMILLvY9syJLCcoyJSgqmcakaVlgraNxCcY3JPnw4CD0cJxJqgK8D3T9mNA2yt/W+0CRBbSESak5rnPCdctgO6SI1FViX84Lw2GtKQrD+abjetchlWRZGaa54Kgu6XzycR28p7OBF5cN59uO2ii+c2eOFoGHBxMWtWZRaI5nOb0NSJmekFSSi91AN0Q2veWnL7aIGEfLC0G/s2z2lifXPXfnBd9/sEAK+OB8yyRLzJ3DuWHnAu2q5aDKeLHrR9+4ZM2xHlOUQ4hIOTZSpWReZtyZl/zTsw3EyNl24HiScTwvgGS87QN8e1nRhUitDQ+OJtxZlpytWz66anHBcjKv+LOHS4SUbFrLtrUUmeTOskQIwacXe356uSf4wMk0Z1Jk5EryYt3x6LBGxmRt4UIKq4mE9H0nAfbn2556TEz+Kt+hG4+kzqWGSj0CT79IYuZc4PFVQ24kpU42GBfbtPr4KnbRL/Jj+l3VVwFIv1Y885tSq+6tNOG3Va8P4p//f3jlI/H5annVZRW88jeCtLAWJHTf6FcL/N4mOZpyoLK0yB0CyDGmJuAZrEu0+jzpUV10tD4SukBmoALW487B6ER3VRFOpwX7IbKcSoINaBFobWQYLLeOZ7QuYvqBeWGIQuKd57rpEUJQZinat1ISTcBkikmmWDUDLsCjcQB4vun5xxc7JrliUWYoLbg1q/jJ8y11ZTBG873bE672A//5k2syJTiZFggBZaaJIXWEm85hlOR6b/nsumGSaayPVFkyMZURbAwYJfmzhwdEIvNCc7Hr+atP1yynGfvOE0LgYt+zqAz3Dicc1IZt79n3jmfrnneOKi72PVqmxLTBeh5f7DmYGO4va3a947PrBh/ge6cTDuc5LzYdhVaIGPnzdw55ttqz60JKXMsEq8YyKywn05yDKuO5bZkWmsM6x42Ry1olnw4fIs9WHdet5dm6xXrPth34p9ajFNya5RxNct47mvD+0QS3DHjg0UHN001HYRTvnUx5umr46HzP821Lniu2jU9Jb41lMTHECM/WHS5EFpVBIOiH5G1yZ15+7UH79cE+hMiTVYsUgvNtuhcpkxHj83X3c0ykt/Xbr33/61o4v63fZSlS13kPX+rGfTMX3TB1rvaR8JqM+fUGSAjJ+2JnE/CDGM23x+PKDPYdTPLk0ZfYKaDHFrUhNTmETzK2KNJxgTFpLSbZg9OjHI0kn75h3uZZAqqsTU2U10cGraDODN1gkSaxWjoPfZ/OuUlMu2FUeRJ4pMd72gwumXXHZPTado4nMhl+ez8myJG613kGZaG4ah2ZtGwHyLSnqDVGRnKd4caHKEkM395H/vW7B9w+KPmPH5xzth2ojKLMDZt2YNc7poUmV/Gl8bVRKVDguhlg3NRM8tSAUQJ2Q0TKwC6meOjrxiUZnUjyDylBINASFpXh9qJisx/4bNVTGkWQgW3jKXOPE8nPZt1aNBMOyow615zOCh5fN/QBlFJ89/acXWf5+HKPEJArifeBTCpCFNxalGRaU+qImUuerltMliKxM50hReCqHdj3nv2wBwS5kcgAy4li29pk/jop8N4TguDWImfVDBxOcspc0w+B6/3A+b5jWupX/njydyth+EOsKL94Dfu2frd1M+TfsDCjgEwEzvcDjXVolca+WZbYozeEz5vzPHC2hXU74DxMSkGukgJhURogcGHdS5nwDQtJAvNScFDmbAbPfhjQdZpb7JAa3qWAKhNUmcF5aH2SgBmZmoqnsxLnA62LdCEQYqAwCVxw1uOC4vasTknAUnI6MVzsB4a+Y1pojJR8etXiIvzFoyXLSmOUxGjFnXmexkkiL7aOpnMMLmIHx/nOUmcaPXqquuAZnOfeMqcZImWh+LvPrikyxbaxY9rwQJErbi9KlBA8WbXoKLi9KLnaDWxaSzt47h+UHE5y2sG/ZMtonVKKf/Rsy65zuBBYVAaF4NaiYNsOHNYVdZFRxhR8dLbpkUJgI9xaluz6wPduTRBSclxn1HmSr21bx9Ek55PLhqrQeJtYpsk/quRiP7Dr3MtG8KTQlJkhTAN/+2RDNgbs3JqXWB/onEcJ8bV8h6QUFKPX05eBQJ31PL5ueLJqmRSao0nytbI+cDoruB5DdqRITDEf00Lg9T3Bm9Rk/ioA6deOZ34T6qp5m8L226pftG6XJO8iREqx8KTFsueV10MuYF6AE3DdvDIRvVnQK1J3MQDzTCGUptCR6+1A8LALo/QtpkV/9JEHyzR4RqHYND1SpoX7QaVZdYH9mHwgJSxLxfE0Z/Dw4HDKZ9cdlbc8d4HCZOzdQOvhetdzMM3Zdo5ZkXE0z4hPBX0QyBjxEYSKPF516K3g27dnPDisWTWWTT8wL3JWreXhkeHx5S6Z5UlYVDnNkPKWHx5WLOuC75zM+KfnWw5qw2Gds2oHPjrb4UKgNJqDKuPZpiWXgkfHE374eMX5umfwgTLTIBW3Dkruy2Ty3A6O5+uWs62l7Qe0lky0ZJ4bMiXZjVrkSS4JAQ4qw3tHE25Nc356ngIYr7YDkZSKUGpBYTT3DyvONh1Nb5nXGQezAusDT686JoWis4FJrnAODqoMqZKJ3qTUvH8y4cOLhvPdgHWedvBc0dEMIUVE95bjac66dePPURqUP77csek8pYkMXWKCdS7Q2DRwH00ylnWG45UfkQseH+D5tqMfPGebloM6eUhkSvBi3XE4yXmxbokIDkqTdObjeH227bklxdc2Lb0Z7INIVNXe+dEkT6BkMt9b7Qc+vtonb6Q3IJrzD7Wm5u224E2r173xvqzGROWXEbG/SEZ9c5wDtqMezI6+d59/H0kCkFpgqiFIXqamRZHSzLSQ1HlgWmaELGK9p9+Gl7IzpZM8Ytf17IaY2EnjvdmY2Ay1hCCgKsYUNZH+35DmscGPcu2Yut03jNkwQMg9SqQUtyLTbLeOSJrP5ChhK8Ro4DqOYVGkzrmLESE9F/vAYB1aacIIdoPAR0FhBEJKShXZdh7nwY4SjXU/UGWSLDPMasOu9WRKIUTgatvTXTfEGFlUGd+9PWeaNfzkfE/rUnf6sC7Z9g4bLFFIlpUiUxE7JlA2Q2IN+xjZ9j3NELA+3buWiiLT1EHgBkvnk69IRDItUzjEnXlFqRQ7rTmdRrZ9YPCJSWR0YsL6KInBc9UMTAvNxSjlaAbLtDSsG8tff3bN46uGEG/k8gIrNHeXJZVO43hvHVVpmJUF63Zg8IHeeeo8I5eSOhN45+mswzmPlIr3DgvuHU354ZMVaIkgJKm19dRGs8Fy1Q4QBFHC5W7gYttzMkuSdh/5nUsY/hBr3w+8JSC9uXVcgTGaiZFctZbgElisRJKVKUaLCv+K8TmQ9hpGJPA9BLBDZDIBiAQE+wGi0Cyq5A/nYjq5yKEuDe+cTmgHz6dXzRg+A5eNRdvIvFScziqyTDLYgBSRfvBMCk2tFadjsAy949as5Mmqx9oGGcFkGUYKjFajiiKy7n360/mXY1mZSWojOZrkPN10nG17fAg83Qz0fSAQyLRGCUluJI2NKCU4nSWPORsiaoDBxtEfEBZ1zk/Pd0wLw/GsIlfw4fmeXCk+zVqOpxkhJDuGIlPkOjE+Q4S/eHBAPq5jb0JmQkgBBT+4P+d81/PJZcPlbmBWRl583FLmhluzKnk4SYH1IQEzSqA0VFqz7SxGK3adpc4Vd2clz7cdfgzTudgNGAkxVxyUGb1NvkaTXFPnGi2Tf9ysSkyhaZVxPE1WInVhaHvH83WHGBcEnfMYJci0+lLfoa+SmN0E6+QqhUvEEHmyatJ6xKdndDorMFpiXeBs23+hbO5Nqi8FkH5f4pmd/TpL0Lf1z1maROm/WaXfmNfd+DZAMisVIkWk3gBOUiYavhaJIVQayb4PaCGYFpreW5QS7LskQTDj9bSBxkYaG7ARKh0pMk3bO5oAzieqZIxpQSoBZJIrzauMo9pwtht4uu25bjyHtWYWDVoG1r3lzx4sOJpXTAvFT15sUUpwVKoxZSUZSR9USU513Vg+udhxNCtoNgERB9oBQvSJ7ZMX7AZH23s2jU0LUheYV4Yn65ZN7/Crlr/5dI2USY98Osl5+KDG+4S8hwCzUjOvMtp+oMoLGhu42PTcnubMFzWTQvGjZxu2jSUSuWwHVo0jhMC0NNSZ4t684F9965BPLxt2reNQG07mOdvek2nJn9xZ8MH5huu9Y1ZpHh5NOJ7kGCk5niYA7HRe8HBe8Z8/vaIuFPeWNZtm4EfPNww+sY/uH9SczAumuean53uqLG0IusEx+MD5rmffO5rBcX9ZsW4cWgqCIBl1O083BJZVlmQEPvkSdM6TjckLl7uBEOC9wwlSCAbnOdt0vFg3NJ1l1VjWrUergXdOJhxOk2dFiJHcaOpMseotNkQWp9nL1LXXKay/yFzv83UzuTxbtbSDxyrPrVlJOzgudwMPD39zMaBv61ers92vIr59W/+c9XXBo5v5Ynitq/x58EmQJGk2JFZr4JU30Bc1PsRrr/ceont1XUmam1wM9A42bZINj/g/kpTMAzeG3unEENP89Pr7dqP8WsmRyeTSfR5ONAe14dmqw/tIPzZIblhSA7DqQ/JycsmnL3goVBpvtInMRAK9tAAnE7s2RNL8MAx0fRjBdZnkUVXBvvP4CBGLjgqpki68HQJ1nszBW+lpB4gxsiwMwXm0COx7Tx8C226d0neUILs95/F1x2VrsdFzVBVj+ISm96k5s248RsNuCORSUGcGFQc8gkzCYAXeJm8P5zytjywqxTsHNc82e9ptjwCEkCgpWeSG40nBo+MJH53v+fHZFut6JgZanZ5HpiWDjVgETT+MDGdB7yLTIsP5yBACn75IEnMlFbkR2OjJCew6S1aXaAGzStPawEfXewRwd57k1733ZNpQZXC2TeO5ljr5hBTpWVsvcL3FaklWCZ5dt9w7qtj3lqfXHYsqY1Fl3JsrQoz8+d0lVWXeslV/R/X0ev/VB72tf5b6RQqHm6qASV1ggNIost4SCs3QOkJM4NCi1gyDY/Cw6dJY6wA9NpfLXBFFWgs0NpBpgRBwUGd0NmBkxpNVR9OlsXdmkqx3WWRsu8Qmf7LtEB7KLFBnYvQrEzgbuTsvSdEDkioXPDycMikM755M+OvPVlw3luebFoGgyM1rSV+S4zrnfG+5N8s4/6AnRoFWkmmewG8pk9dSoRX3lwUfnm25tygYbCTXknXnuHNUsmsdk0yy6cEHSefSnuDOtGBeBUwUSC15dtWy2lu0EDSDxSrBJFPkmeTOIsf6yN1Fye1FmUJsqoyDOuOgyrhqLCEOL9k0RktCSM3caZlR5prBB5RM/qN1lnNYpwCDTy735CaNd59dtygBL7Yd68am/dnEJGm5D/zt0zWTQtG75DM6yRTRKB4eVtgY+IfHG15sOx4c1nzv9iw11oFhnE8G60f/Vsl+BI9uzwu0kjxbtewHx+V+4HiSEkG/DLT/MonZTbBOmWmOp0md8fiq5c6i4MFhjZaCs23PvfFZfpls7k2pr5vC9o0FjwBmE/PVB72tf9a6WXjDq0X9DftIkwzqOptkakLARCdfiV2XgCZJSo6RUiN1j1QJbV81gcEm89ObLrIcTVFPpwWH04yw7jjbDGkAAyojMFojRWRwkdZ5MglVppAhkqlkRPfwsObJ1ZbOeq52gSo3THODlo7ZtKQq9LgYN9w7KBlcGhSy0dDz/hize74diDEyL3KKU82n1w1GpcX2nXnFtMr4+HyDljBXisKkxei+80wLzXtHKZJy31syrRls4MVu4H9WG64bS5UnZ9LV6H102TpmVUkePXWhuNoN1EXGddPz5KrhcJqz2jumucF7sIMHH5lkmsNpyXbv6AfP1W5AEXl82VBlmsJo7i4yJqXmuhm4tyi5NSs523Y8WXWsW0udpWtedakLuyhzrpuBi91AYST3jiruL0sKrbk7L2lHwKYYB/Ui04lGOs2ZHNesWkdhkj/GojJc7wdOpgWzwjCrNHWuyLXhoNZ8dtVxUJmXnYsIyatJJfDm8VXDxbbjp+cNWqXku/3gcT513P/odMKL/cC+dZSZpjCKi23PWdvz3dMZ8LMU1sGGX2iu90VVmNRpaocUd/1Xn66YFholxctF0ZsQzfmHWu1boupvtQy/GSnIzdzy+sbi8+DRzW+lECNLdZSPfVn9jJRtlJTd+PS5mLyPBp82HtalY278iG7uRQDLylAowcVuoP2C3Y8nbVxcSOdOclBKsO09103qdms1spFe+1yVGkMjRt+gUoNVSco2KdLi/MImDZslySjaALcmOcezAmsN1/uWw3lOKRTXvWfTWeaFQuuMbQ/DENkNHmcdmUzPrA9pfss1WB8wuUAjmJU55883KJl83iYaPrjYsekcyzrDSIkSihihzBSDD8To0UphtKfMDIMXTApJP0SOZjXXzUAfIm2f0jK9SyETffQYnfPOccVsojlYd/gQsT6QGcN7hyVDiLxYdywnhoO9QcuaMpNI2bMaBrSErfMoKVgNoEJ8KSlY1Ian6278QQkoqWiso85y+qFFKoUU8P7JBBsCn103rPYD57uW3CiKwbIsMz69aJhXOSFCoQNlkSGDpxmSz2GVKW7PM0SULKuMD8931Lkhk5JZleH8jhADSsHdZU2lJcrIt6lrv8O6eBvB9luvG0bpV4nMZxVMlWQ5y3l21bCzkVpHlJT4LtADQ+bYW5jkmlt5WmOtWjsmLo9G+RHqXDEvNCaTeCc4nibgaNWFMXgggfVRSTbNwD9d7FkUGikzKhO4tj1qDHLRIq2JCwFVUbNtHYs643iS8eCgZt9bHh7U/OjJmsveo6RkXihsiGz2PcUk59YsZ9+nfcG7356yd/DTF1vOdz3bfqAwmj+6PWVZZ5zvLLfnOXWegBaBR2mBHCJnq4FlpehDxAhFmUtyXaSUsjpj4gMfnu/IrCKvDX/+zkHy39OKq13HrM5YVDmR9JxOxnXv7dHHSAnB41X7EgDZd5b/8uk1t2cJeLEu4HT6TmYypcfF0R/06bpD0PDZuuNf3pszr3OMFDxdd1zvk+zZxeSHdzor6Gyg0BLn4d2jmsEF5vcW/NOzLQjBau/4k/tzzjYDJ5OMTesoteJokrHpLKuLBqTgZJZzOiuSQiYm39onq3a0mhAc1xkeuLco0V/hOfeLJGavB+sURnFcZ+x7xzuHk5fX7J1jCOFryebehPpaANI3vVbbtwP+77oiCeCZ5tD0rww9BWnhe9OxjQFKLWldMqLTMkneMp26p7mGOivJReBs19MODqHSuaIfF/kBjJDcPUio7lPfkamUcLXtHblRLMoUl6siyZvIR2IMMNL4N73DNpZ/994JB/WGZvC4kORUmz7w0+crfvDwEOc8q8ZipGLnk2a20JpJLTidVdSFZNOsCEiu2oFb84JbNmdeG/7x6YYy1xRGIEWKgFwelIQIk0zwrdMSpTSX+54XI1BxMFXcXlZc7QaeXLXUpWFRaj66aDiaZBzWGXKkwh/WmhebFG3//Xtz/vazNUZJXEik3PO1JarIwSTjaJqTG8Wz1Z6//PiKb9+acjIrkQL+4dmG796acmfsGBxVGYd1zq0xwlPrJP/64ztTFlXO4DzbPrGkPrlqKbK0aZBC0g6eXee5co5llfHwoOZiP9AN7iUDyUhJlJIqMzQ24n3aMgUfRn+LRCc9rHOUkrS9Y9PBvNTcnpdMC0MIKTltkqdOrTGSB8uKjy92zEo9dm4EyxqkDDS948UubQ/rXBERXO16Vk2fOiKrPfeX6edJCoGIX2yu92VeRiFEzrY908IwGzzTXMPIYrqJDg0xps1wiEn29oZ1HH6f6yb6/G39duo3JRi8MbzmNR+j1zcaevwTSYBL4JX/xeulPneuIMm/8iwBRJkA4V55KEkJ3ia2a6ZSMwOSBE3L9LePYyPERuwvILgFoHHJw8cAUUp2XUDI8V4ibG26vxt2kwea8XpzA9pIMi2Ig6excNVbstFYGkZ5eK2IjUeLmLrqSAahmGQ5gwu4aGkbR51XzAtFaz0DA5NMITLBVetouoCSkcHBpJTMJiXLytD0nmmpyaQAATFErItsWkuuDFU2ekrIBJRlWnG5a2gHTzlV1HnGNE8d6ncPS/728Z6J8EgFwibT2MoIIoJd61BaQPQcTgqOZyWzPGfXdHgiQwCtFeu95dasIjew6wNizHa9syjoLwacF8QQmNYltxcF1qcF+qOjir9/uuHJqmdRJM+mSa54/rSlGxzzKud4ktOFyNWuxSISqzQGYgQfAk1vMUoyrXIOpxkfXrS0fWDTdJwsch4dVRidfEcOa8PpvOT2omLdWiaF4ZPrFikiRaY4rDP++M6MTCkmhaHQb56U4Q+plHj7/H9blZHGva/b2xEkJqcQsB4cdSboXKTtAu14vaZPwP/GO2Z1hpGRozpHa4H1kegjqtRMM8PJLCNGweO25XwzYKQmEzaZ/SsSj0imsXTbdiyqKfcOKpSM7HvLu0c1RqfEtG4/UGaKD17sMEolUF3pcW0s+NHzDcfTghfbjkILAoKplpyFSO0jP3mx496i5Hiase08gbQ+PJoappnmoC5Y1jlaSmKM7DqLC5G7i4JmCGzaHiMN3zqtaAbPUkuKLCW3na877h0s2HSOSS5xNlAWhkxG3r8146dnO0JM89y/uDvnu3fmaR5KOQF8eLFDRFBKcjjJ8D4gRUpnvtwn8D/PkiIjyXsTSOJj5HSWs2osz9YdELlqLZtm4B/Ptnz7OBJlRMnI8TTn3dMJu8YSJWiVvPumpaEZHEpJ1KgguXtYEUIAAYVWnMwTU2vfO7ZGIkQK8JEqgUJKCp6uWx4sKpSSP2c1UeSadkwd/VXrdRXCvncoKbizKF8yK27kcZmUP5fg/Itkc7/r+oMAkB5f7H7Xt/B7Va8vYr9uBUYa/Wuxx4G0KFcClFYMzmN9iryMNmCyG+8GiRISoSSLIksL6xiR3qGVYN1EurF7K0jJNEe15uFhyarzaRGu0kQipSQEz+AVObBpk5GoVgopgRi52Pe8f1IzWFBa8M5hzY+erxl8ZJIrTqYFCMWHZ+nnyijBySLn4tOOaZExLTSTwvBi05E34EWa0ESEZ9cdV7ueKpNMi4yjSY42sO0su8HxfN0AkpWEs51lWcKz62T4PNjAo+MaQsAocCJFTs5Lk1LjtOC9kwmtLXhy3dN7z6QwLOqcGEFJwbQ0VEay65Ip3WFmeHRc09jAhxd7Jplm8J51M7yk7VofOdv0/IefXiFkilj+X/3JbS72A0YJlEgo/a73lMZztuvZdpa6SAkYu9ayHyyzwnB7VnJ3UdC7pG2ucs3378754ZM1+6FHScH37815sU6MplKnxIgqkyil+MH9KXL0KnpwWCMQPN92hBD5zp0pWkjWbdo1ncxybi9emV4LlYz+1q3j48t90pUrATHpx2fjRuEfX+w4qiWNFHzn1hQhUyzop5cN95aJrhsFP9cl2HQ9H1/uUwfiCxhJNxRWPXaP6yJj11kOqoyzdXpmESDy0nD7TdU+/z7W9u008Y2vLyIVKRLY044SsNcZQq/XzXxWjjI3RZrnMinIy8SykZ1nJGxCTD5GsYdeBlx8Jcs2cpwnI5xtLYX6xd1zRZoHZ0Uy1J4qSRcDagSAZhWEffJT6tzPsq08cG1hGpPvklKjzM0mo+wwfgYlYG/TXDj4dI8OuDcvuLMo+eDFDu8jRSa5tyzYto53Dys+uhJIIr0PnGjDC79PHlAOINAPnr2Ag0nBpu0ZQmTTRiSwagdyDZ0deLpOTM9NOyR5dxEoc0Wda+4sC9Zd0gceTzXNEMkziQuCeSa5tIHKpM1JZ5PB7NwYLhvLf/nkkqNJwe1lyf2DFEDRtj33DmuWU8enFzu2raUdkpHqph3YtY5tH7i7yBhCxqODkigVjxaKvz9r+OR8y6azHE0MuU7z4aoZWE40IQiOpzllpqilYFZqPrxo6AbHprEcTRLj1rnIxbblzx8dspxktDbSe0M/+CSv3vf84P4cozTLOkPJJKNTUnJQZzzf9BRacljnvHtSYz0cTzP+9P7iKzvgb+uft24SU9/Wr1dfJUeDxLg0vGoA3Bz/RedlwHULyJZVn+Iwdxaciy/fbACCTV5HnmQjMatKjmvDRev4ziLjfO/YdD3b1sPeYQdPmWmEFEwzSaZLdjYwWI8fk46lHQCFJCUz3j+oKYzh27dqHl91LKuco6lj1/U8WXcsCmgHx7wwNINn23s+u9wBkb2N3FtUKAWfXbdkIsmL9zbw2VXDeycTVntLbwO5TkbZ6TMKBhd4tmrY9YFtOzArk0piWmierzveOa44qAvuH0perAcOJxlGCQ7qHAmc79b01tE4z0Ibnq4Gothxe1Fwf1EghGBWpf1EFIJFpfnrxyukSE2BZWV4fNXwdNWy6dI6fPCe+8vqZVPVKMndcV1+Z57kWoXxtNYjRZIeHk9Lnl+3nK06HClMYVHmNIMHITAymVvnWtANyW8ojkmd1gdOJjnnux7rIgLP3UWFFNANHiHT+UWmyFQKPdAqNbeJyc/pej/Q20CMkVvzMqXJ/YZAnJs1ihDiJXj2umeS1vJLvZTepPqDAJD8MHz1QW/ra9fnk2pu6kaSMIagYUhgjn+N2s+4qI03x8XUST3MJbsYKbOIljF1HiMs6oJplbFterSMVLnEqMRoWTeeXEts8C+NuGc5LCeGb9+esmkc57uOTCnuLiuEgKdXDQFJrgQv1gO9c+RaMi01jQsgNXOdIpmt91xt02uRJHE7nRoiiugD7x5PqHKdIhml4t2j5KMjgWmR8bdP16gYee/IIBE837R4HxBSsO7CmPgVeXzZ8nzdJeZOJ1FKU6jIJ5c7PgyR56ueYXA83w78P3/4jPeOJ3z/7pxCKP7o9oxdnzyQ1t3A7XnJk3XD/UXB/eOK1d5xWGfcP6yxNuBCpBpTbSa55tFhzW5wNH3SDh9NMna952o/jMcECiN4umpYVIbTeUEzeP7Tx1f84P4CITQvNh2X+4HBBa73Pb2LRBEpTAJw7s8LhhD48dkOKVMX+f5BjR/9gxZVxr9555DOeawLXI1SPO8ii4nh9rzkaJqnexoXz85H6tzgQuDRQUVAcDhKBd4/mb6cqF4fdJUQ1LnhT+/POZxmPFu3XGx7jmcF3zqZooSgcYF3jysU6T6LzHA8TbKGzX5IX48AkBSCwaYJybvwystI/7xuOYyRpoLUnQe42rWsWo8LgSjheJJz3VpyLV92Ht5U7fPvY721QPpmVsYradkXVQ8/s+N4ffMhSfPUjTTMkNhDN/HMLkCUglwqhuCTcSqpIbAaKVQiJo+kmx+fPqaUn2w0fC5kWmzHX+DoJIG6AKUyjuqIyRJo73ykytJcFEjg0c0VbjZUN5uwjUvz7LJWRCJaBqRMDZjWgnegcsXJRJHnht1gyZXmoNZ8dNnwdN2glaQ0SaqcaU2MkeOJTwayneVs0zOvE+hNkQzBjQatBT4GPOKlQfmNWXlm0kZJCsHgAz7AetdxUEx5cFCihaQykkwqznYdMUo8gWmuqUwkKk2Inn0v2Q2W3jGCUpZcas7WPY3zXLc2jb1KUGWaw8rwYt0zzQ2ZUUyLjJ+ebSl05KJ11JliZxMb68dnDQcTzfk2bXDWfeDhUY1Rik/O98nHSEmO64pmcJxMck4WBevG8sF5w653abOBxHsxNmoy9kMyFY8hjec3iXICgQ2eT64aZlXOyTznem8ZLCwrnSK3BczKjPdvTfg37x7RDZ6HBzVZpl5GY7+t301lbx0xfiP1dTNPb5iqN0xSLUkJiaRx+4Z1Kkk+q35kEnoE7RARIyM0H6+VyVehBFWmOZlmPDiqKa5bolDMcom1gV1s8S5wZ1Fgcs27BzXX++QV1PSB1W7PeggYD/NpxaJQXLeWz672dINnkqskRasMQpCSJj1MsgSQCCm42LccznJuzXMiSXlgw47GO7QNZFLw/u0pk1zjNz3dYDmcFsxLjRTwg/tzfvRsgxAC6yLP1z3X+4F/+94Rs3EMnJUKMUrHplVGaRRtH7g1K/j+3Tnr1vLxRcPFrsM7z5PrjnmV2P/zQrNpBya55i83a94/nlDnGbfnOaVWfHy5R4nUmHY+rd13vUNKKExaw15uLXaaZscbNs3N2twoyT0l6VwC0S93A9PS8PH5jmZwzKqM40Lzk+c7Bu3QhaE2Sf58WOdIIbjcJyDsct/zfN3y0+cbitzw/btzjqY559seHyJRpMTM821PZlSyjgiRi93A6TRjUmhyI1k1lvvL6uW5zgWs4JdKYP7Cn/cbE22dTLSdD6wa+4WqhS/zUnqT6g8CQHrL+P36dQP+/LK24zc/3kuTKKS7PnVDjZZoIFeB00Xx0ri4s8nQrvegAuwGh9GaKtNJq6sdfe8I0dN2yefn4dGEwXpccOwaj1KRFxv/MlZ5WiYn+1IpNo2jkYHVbmBWaTzwYFHiQqQdHIsyw2SO1T4t7GKIZBK2XdIbh5AW8L1zrFfJcNtax4sYWRQZgUAzWCaF4nt3Z3xyvsfFyKdXLaeznLuV5sEyxwWBDcm5tLOBb92qsaN596bxiAhX244ykzjvaPtAoIMi4/HFnk2XPIAyYzhdSHatxTrPrnNEEVm1lncOanrrqVvFtnN8ctFS55JpY3nvZMKm9Qw2cHtZJb8QCbmcvKLcx8jV7gKBYFbn/NtFxT+dbci1YJZnHE3gg/OGMlNpk5El74veeq4bm9hVwOWu45+eD/zJ3QX3D1PHYdMOvNgN4wQveXRYcTwtXqb9hBBxMdCOBtcfX+zZdo6jaYbSCfF/eFgnVo8UnI/JBD5Gaq14ctG+NEC/NS8Sw0B/sUfE6ykJ95YVp5Oc3gesT4O09YGPL/cJcDuoOFGSOkseRfvWcr4fUFqiZeoQLCrDD5+s8SEiIsxqTaZ/Xrf8uleSdYGd92yagZ+c7ziscuQ048604LIZXp77+Wu8adrn38cSb5XO38hSnzc8+ooKn/v6dfCoHDcWKYHGsG0sksAkl6zbiA8JIPr8NTyvNjJ+/FtGED6xlEoTKccOSySBLJA2NVUGSEX0jtbDrBbIKufZqklpP2MKm0gNUvrx/JwEpqTwgHTP1nqGkM5ZFgKpBKWG3icz2ICgziT7LqCzwLa1fHq2Q6gUO386L/ngxZ5/+WDJ8UxjHVztO5rOkmvBto9kWiOsQ+UpQfKgzIghoEnykPyGcQt0XdpwZ1pgA9yapwRSFz2rznFrko+d6gABZrVCSUORB6zz3J0XPNOKZ5sWR2Dwnn58+MZHQpZSg4qJYrV35EbSu8D1Psk34ngft2YFgci661iM3SbnPbsg0Dierh1/entGHyK7LvDpZcvpxBBjIISIMpJJafAysm4H6lzRWc87x1MWleHZ1Z6/+uya3WC5uyy4s5gQQkq6Q0QWpeGoUkiluNwPyURbq+T1l2k+u2hYtQPb1nIyLTia5Nxb5txZ1iiRxHfPtt3bpM43oFabt52G32WFUW2gxcgAHf//5u9NB7uuSyEHwCxLcifZR3oPTYB89I3rbUgN7sEjlKIyiWm6loJ7BxWdC9Slpulj8n6LqQF8/6hCEHH7AaMFD5YVhdF4UhDOECNCCgbn8B6kSvykm2TGW4uC4JPcNpNpTXl/WdI5z61ZxraXLAvJxxct09wwr3M6FzFSvnwGszJ5Il3tLFpKbi8KHh1V/OPTDX2IzMoMoyQfXexZ1objWYEUaT/Su8Cjw4pFmVFnmn1v2XYDt+YlL7YDxIj3gfdPJ7zY9swKw7LOqHLF2bZFCri3qHAhjFKyJLfadgPeByal4XCiCSEyrzJCiGw7S6bVz7BpOutfro2FEC9ZqjHCo6OaXCsOJxkuJibwybwgU5JJrvnW2Ch+P8K2t/zf//oJ55sOqSTTTLMfLP/zb5/yYFm9BGgALsVAGP3uPrtq6KxHKjn63yn2vSMKmBbJ/uLpKi0Mf9kE5s/XKwXCz+4RouAX7lfe9HX/HwSAZMUfxMf8jdSv+uN684SFgKpUIANCROpMoLSmt57tCHqEkCKLK5VaCc6BVppcC4YQqKNAhNQdSCZwkXlpUrqagl0XcCGwa5PB6A1NP3hwIrCzgRMpEUpQKMm6cVRFAnDuznMer1K6gvMxJd8YxVXbI6VK3kze83zd8t7xlONZzl9/uiaGNCGczApamyLj/+HJmuv9AEJQG813bk1YNSlF7Nm64/F1TxwNOG1wXOwHlrVGaU2uJCezDKNTctCdRcHf75MkTyvF8STHIxl84LLp0UJRSMkmglKKd44nzIqMs03P3UVJrhUnU8mH51sKk8zttq3nJy92/On9BQ9Gxg/A802HB5Z1xvXeUmnJd28vGJxjbwNGSX5wb4kWyWj6aj9gracbtdW9DdS55u5BxQ+fbFi3FqMlf3x3xt8+TklxRkm8D+x6z7dPpikBb+l4vukptcWG1In44GybUH4fyIzkuhmYFYZmCBzWhhfbnttzy7pzL/2BTmcFt6YF/+mjS87WHUYnCu7jq4a7I1X2pl5PSYMk47tB/EWEx6sW5zyfXjf86OkaIQW3pqmz4UJKgHAhcLkf+KNbU6ZF6rQ8W7VE4OFhNR4b+OyqZaj8yzS1L/JKGpTnxUViFVWFJpOSKKDMNU2XIri/Cdrn38fq3Fcf87bevGrj15ND/KK62XhkKgEvHVAMkOnIrMgIwrNpHfshbQRyx8/EeN+8rxyv4cd4aBGhyCA3yXeuNgmwJ6QOeqHTfOYD7DpPK6HOJKumRwvJvMqJMbLtBhqbvJgKk8CfnU+bo1qnhW7vIrvBwejJ5ATkWoEU3D4o2XUDu97T2jQ3GaVZ95ZMwKr1aOWx3rMoM3aDZ5ILPjrvuDXTbJuIVEn6DanZE0NE44kBWue4Vxd8cL5Hj939wUE3SuVyBZ2NOBe5ih4jFUZqgvVc7gbePU1poiF0lJmh1IJVa/ECdjawLA02RKILGCHZ20CuJDZEjJA479n2PdFkzMqcaWH46HLPtkuBC/MyJwTwPhCGgHMR55IUUUmYlwVKCFrnuW6TR2LA82yT2LRVJjiZ56mh1MNiqsiMZn3d0VrP6fyAd+/MUEbyo6dbbs1Sp/rBYcXVvueP78x558ileO8+8uCwpjaa66bno/MdP3y8xhiBEik9dDc4DkWO9Sl19rOrls6lQI1b8xItxVtm6u+wuvA2beG3XTcs04lKTMsbIP/1voFjBK3jmO7sXzGWSiXZR08lRu+6kHztEsDjKTLDo6Oadef58fM1QaRmwcmkQEnFrbmi1or5YU4MluergW+dTJCXDWUm6FygUJaA4mCaUWrNVdMzeKhLCRGmpeKhqJiWGRLB0aLkO6cThIRPz1te7DqCD+wHz71Fzsm8pMwN/+XTVfJYC4Hv3ZlxMs3Z9o6zbU9vHUpCEJGDicEojdIK75PEzijJrVnByciiv24tbe8otORkWvB41TI4z9XesqiyxBqKkU/O9wwueXZOck2IgcuN48W65bqxHE4y7i9qIE2+pdZoJRFIbi/yURWRvjuZkhzOM27PSwqtXkpwbxg5N2vjXEvEnNFDD852PS4ELrYD+9Zy+2TCg4OKECKRVyymECJPrhterDoOphlKJj/Z//LxiruLklmZc2tevJSe3jSRQ4zcnhcsS8Ok1GiZkppv1tw3nqU3jfNfVxHwuon278v6/g8CWbHt29jNX6YUrzqkv2y1FkTjybOUUrLtPaFLA1mdGXbjLi048CJgNFSZYJIrqkwzuMhyYlA7y86mNAIfApmEprcclIaLIGh7h9EyGXCHZFhqA0gPIgqumoHOJZmTVA5rPav9wHfvTlk1nqtmIDOJRmhjJNOSPNM4H7EB9r2jKCQfvNiliMnKUChJqQSlMTRdMjsNUXC5HWgKz/u3ppxME/W/tQ4tBFedp+0H1m2P9wGtaqZFoqkPNrDrI84mcYMeW+llJjmc51SZQsuCzy4aChMoM8lBZchESiyAZNjZWsdPz7c82/T849MNR5MCpRPT6Mmq4b9+7xAlBE82LYWRvHtcE0LE+kg915SF5u6i4mzXs24Hbs8KlJQYKbhoko76ZFaw6xwvNh2Hdc6/e/+IZZVze17gfJJ2rJtE9W97x76z+Bg5qDOqIqXEFZlmUSaz0fPdQIyBy71FApfNwPunNet2YF4ZusHzdO3Z946/ebzi/kHFZARvLncDp9NkoP3H92ZsO48PkRebnn9xb/GF3Q3rkwGK0fJlBzdTkjpX/PXzNX/12YoXm453jydcNRYhW6KHu4clkEzHrzvLrMpemvEB1HkGpG7CYZ0lRlN4lcr2ea8kKRK4V2SarPdp0hone6UkJ9M8LQzecO3z72M1vylX57f1W6mctKmQvDKYfj2l7Jetwb+6VilBSIEQnuudJ1fJUyiTsHrtHMEr6VoggUZKpg73rErxyl0I9KN8QerRGykk+baNr37uipC8lFQfUUqxqDTNkJiN3crRDmkcyjLBzEUGC7lMXgoEixsn7eBSg8ZFuDPNUjKlEDR9Q4iBGDRKw64dkKTPpRRs2sAHL9bJL0ILpIS/fbIl+ASKyxjZtxFiRInUUbVB0HQOFhKFIFMkoE2mZzmvJYcTzafnQ5KdyMDtec6661mUBd8+KfnBvSUfXbesG8vgPVImiUJvI7u2SSk40wy9rAgxcrkbkmmqD4mGEGC1ddhSIqRnWZXMS8O00Hx0njzpHi5zlEhm5imBT9LZnmWZczLJuO4c59uOIsuxIdAPgYkRFIUkRsnFpk+pSVPNundsnl7Re0FsIz99saVKOkV+8GBBCJHb85LzzUDTez4633E6L/nB/UVKURoslTEIFbneZPQuSWW2zvPgoEr+SrnhcGLGwI+Mi/1ApiQXu547i5Lgwltm6u+o6uxt2sJvswTJU24IY+okr1ifN6Ve+zO89vrEpPHt9iJjXgcypTnb9ey7UU5WaJo+oBUUxvDkOiXx3JlXrBpLHP12vn9vQWYkt2cFf/PZCiEHeht5dFTigyRGz27waBm42PYUmRt9zTxSJX+e79xKdhPWeV5sOh4sS+4tK3yAv/zwiq6PdD4BL70jGXqLtOZ/eDihyCRCJAPodw4qrI9Ms4JZrtnZwPNVhxKCu7Oc802LEKCE5N2TmgcHdfL6EYmNOis0f/dkxf1lxbQwQMM/PttitORimxIt7x1WVEax7xyPL/ajuXSkyhWrxlGajk2bnhEx8q/fOeB7t5cAfHS+42I/IIVgXiUfprNt/zNr7855vA+UoyZUK0lmFLdniYFpP71OQJSAd44m9C7y8UWDFCk1bfCBQqqXzJ4UtSoQAjatHQkMGqN+FnD/vDxs09mXSgIlBd+/O09pcf43m4b2ugLi92V9/4cBIL2dZL+ybmIyb/5+vQwJUPpFC/OcRKuXJNq+UTA4T5XBNNNoHXFRYQfHvDIsSCku+8FhlGJWaOrCMFgHUbJvLVZCnSlmlWG1a3m2blFK0TiPEJGqyJCDRc4013tHYPS4yTSzMgEW3TDQD56DaUZhNCEEnl51/MWjJX/9eMW+cxitWJaSxkkmWUZdGHad5boZ2DWeIpN0LiAcTGrD1X6gLgwOyd1ZAUQ6lzyZnm87NnuLUIJcJWDAOo8XAaUkWmk6FylD5NFJjZEklPygoree813Ppum5czBhlmukkBwcZnx4tqO3gW3vmZcGqSSrfU9nU8rY/+fvX/Bi29ENnu3gyDrL/YMyGXvuLX/3eMXRrONsPWBDIBBZFoZZlRhegsSAuS0FB3XG3XnJx1d7ViPrJ9OKv3h08JIKWhtNlqVB9c685O+erEdTOs37p1OudpZ5aci1woVI0zuuG0tnHS82Pd87naAkXOwGrnYD95YlhMD1zjLLk8fG5d5yMsm5vSgwQnLdWKpM/+wgPn6/p3nG4D1N71/SS1/vbkghOdt0CAEPDhN49snFHq0EH57v+NHTNefbHhmTBnuSa3oXOJxkCARPrlt+etbgQ+pe312WGCV/ji1UZvrn9Mw35ns3x4WYJikBHE9znq1arI/4kYVWGMUDo9547fPvY721tvhmlVEpmVOIxBxSMnWoJbD+FcDAm1MyICroessgwRjIjSEKS29fHfM6WHVjSt2E9JokBTBIJaikxOkxedQm9lEgMWbFa95JLkIYIMZIpj2rVrKoMqqsQIuOj897Bgs+RGZFkkF7JNsugUeKlLSmtSQEgR0G1o2k1IreBrohMETPYl4wDMmxqHORModdl+RwrY3UueZi03O2SfHQWigKLfngsmW9D3Q+eRvmuWRiJFEKNm0PMXL/pOZs0yNDBAGn04LLzpEbiGNcXjNYCp3SQn98vmfdJxnJos7YtZbVvmfTOU7qnCdbj7CB822PVhrvI7emOS7kDCGwai0yCp5uW8y+49MrwaMDz6zKeHRQ853bUySCz64bykxz/6Bi2w5c7S2D08zqDBfTZ+57T2UUuyExnieFptCCfecZQqTQisF6rvcdPkBhBJc7y1VjybTk0dGE+8uSOldshsCnqz2Hdc5l43Ch5YdPNvzpvTmfXjbEEDjfWTIpmOWGyzYZqa7HaxkJ0UdkhDLTyBFl9CEyWP+N71x/k2s7vO00/DZLk5rDN5tVBy9tK6R8FcxTjX6rg017kpsEyyEky4WjOicIgdx22JAarEWWmsj/8cMr8vcl01JRtYZpbjid5gwOFhNFoRWb1vH/+OgZRkEkgcTJVqHjYueY5QotJc82PY9XDbNCkwlBXRiIYzLyNOds03G+HTjb9jzb9BxUhl3v+ZN7c+pc83TV8vdP1swKA6NHaKYVP7i/oBkcvYuUeVJsSKV453RGO1j+6pMVT1YNnY3cnRc4Hzmapaf26dWep6uWTy737HuPlEmhcHbS868eHaClTD5BLuBCSijOhOD2tOBM9CBISoEx6rQ2iufrPu0XDkq2reO6tcnWorUURnF7XnA8SZLl7DVfz08u9mRa4mPk+abjtuBlc9j6wLNNh/MBoxV/fFRTGIUUgp+e7bizKKhzQ4jxJSikhKDKDQ8WFc+3PT4kFtef3ltQ5Botfx74uZGHhRBZNZaHBxVCJqBv1aTAn1+VMfS66uHz6/dvirfR160/CACpb99qE76qbhbCrw/Ir79Wjv9vP3c8vJKQFYAYPRkiaeCWQtD2EYFLv4gkqmKmEl1/VpVUWuAEbFtLaSAgKKVnPwgEkSgNKno2naM0ksaGV5IFKVAimZaWeYprX9SGy02fNLmtYxEMuVIoIznfd/ynjx33FgUXUnAgMgYfKIPkbO+YFhlSSe4d1Gy6AS3BBc/DowoXYCthCJ6ud2y6ZM5pZKLTKwTr3nF3XgDQWsezVYdUgnmumZSGQimWpWFRarajgbLWGh8j95YVl0ZyVObkWjEZkf7/6r0jrA88X7cIKXnnoGLXB3o/sCgNu94iheTRSQEisu0S80YgOJoXDD7y//voGhsCDw4qNq3lg+c7qlzyb989IoZXzJx7ywotEpAigF3naAbLi3XPu0cTJuXPbrPzTPGd0wmr1qUdjRC8f5rx6HhCoZNPxH/59Bo1GufNcs0HFw27zvLh+Y51a/n0sqEqFK0N3D8omeaGMtMc1DnHo3l2b33qNPgEyBRacTJLaQk3QM3pvHipJX5db2x9eDlQ3xiQnm17TmcZ286OnXHBYmK4bizPNh33lyXHk4zn65ZN77g9z7nYWy52aTL9i4cHyFFK8PkEhdfri7oO3787Z9VYQoyczgqOpjl1pl/e4zdB+/z7WPHX0UG9rd96+QBlBpMiybr8yETt3GuSatLc1H/FtV7/1keSFK2zsO+gMOBkTFIxazHj8RlpIzPTycSa1843Ck6mhqudH/3b0jk3jdJA2ggFXnknhfF1F2A+dk61lBxPcg4mhmFwXO49vYPLHVQ5zAqN1oKrTU+epcbNrDbs20BVGFoXeXLd0jqPBUIQXO5a+iF92hBBR5gUUBmFVorrZuBia9m2ln0faPoeHwRNH/BAnadubK3+/+z9V5Ol15nni/2We+32acuiYAmaZrM5fc5pmRM6MREKmQh9B30c3epCoRt9Ct3oamIkhY4Uc6bNdDeHBEmAAMqmz+1ev4wu1s6sAlAAiXY0qCcio6pyZ777rZ0713rW//mbOFm2Q+DZqufOXsG67klVlLA/2i+5rCx4R2Y0SjkIcdCw7QYG55n6FK073E5ilhrNellHKcqOeXzZWMogmRaKstT0vaUdPJ2Daab57KJGCU9nJYUWfHLR8GgPcqPZH6ccjlPGdYeSGqMd7xyO+ZvPr3h7f0RiJNNc88l5xV+9u8B6wdPrDdXgOByljFLFz6st4Fm3w+1zp1rSWuiHgX6w7I0M67bnyZXjcJpzZ6yYZgnTImEYHB+9WCMFrJqMT8+3BBfwRD+pbRejszcIqs4xd56mswgpOa96UqNeO2z4Yz98/LHW5ar+fd/CH2zduMP8S7pE5TIC+hDlaL57OdDOdEyuzMzuE+HlIEiICBIdFREQqnfeaJ5AoiTjnT2DkQopAierhlVtOZ5mKB2tBXpvKbKM3jo+u9jS9pbRJCfRin98uuJoYmhdjIrPM8PFuqXtB/rBUwnL81XNscwhSFbNQJYonlzWvH1QYn2U0n500hC85zcXNe8flWRasmkG1M4K4nhW8PllxbSM55hEC9Z1NNP75HQbffCU4O2Dkklu2Lbx1Vcy+oGeLBs2vUUF+PSiQknJ4TRlUig+u6g5GKXYEEiNZDrSrNuezCia3vP5suGz8y0P9gqmhWZfKhDQdo7OOrJE3Q5Fz1YtfxOuGGeG42lOJgWXdU/wAaPlF3rvmz5fAs9XLXdC7HsJUV2RJ3Efutz2PJgXNL1FBCgzE33gELegkFGS+/OC66OO67qndnA0SvjguETLCPwIYu/vxRcDCG7OCXkS/ZqcBNe72+sejtPogSTcrffpN627r6oevs6r7k+pv/9OAEjyzWj5a0vsPnK5o33eoPnqJV1UAIeTCFRcN189Y90kqg1AFmL0sN+BElpB1Uej4qGHVA9M85JpZrioOhZjg3eB41FGqiQH4wxrHUEIusHSDQEpBtJEYUNEpUspIEjqukWFKD3bnyVIEeh6z7Prhruzgr3c8HQVTdISI6g6TyIUm9pyJnuGALNxwjvThMtNz9l2zcmmZZzqaIAqBAejDEKLdTGW+Af3ZlxVA1eh47OLbQRpJil//nDO/WlOPcQDw8myxgNlHkfPXkQwbVkP7E9jgkBpLO8elrxYRWrnONMsijGLUcb+KKF3gbOq5/35hIu6oe4Mzgd+cH/CYONUZdUNGK1orEUhuDMtGCVRnhe85948JzcxgtTbwPmmY9NalILDMqXqLZPMcG+W32qKB+eZF4Zfnm5YNdGgL1GSzy63vH80+UK62WA9y8aybQeeXNcUiSbRkqNJTlLGLOvDSQRIPIHzbUc7WLbdwPmmZdtFME8ESd1ZEq25t1fgXaSfKiWZppqT3tH1L2VeQcCDeUGiJIOLvk13Zi9TEl6dHtzomYWIi3c/xA021QohRJRCJjGiOdOCsVH86N6Ut/ZG/PXnV9T9wDgz/OBujrWBeWkwWqKE4M4OLPxy4tur9bqpwyQzfzJTiD+VUm9+DH8wtfOy/kY8rwtRKoYQlBlcruPXdzuQJjMxrvmqj/82RCAp8NXktlefZwAuq/hnShyE+MGSqPi96c6HI/h4UBr8FwcqDrAStp1nnmuEgM+3Ud7d8jJB7dX0t5t7MERfo3lhSLRBSWjdwOW2IwiJlg5h4rUGB5u2Z3+ckWSGqhpoLFRdS2Zglmua3tIGEFKilUCJaBIdXATfDieKF2uHdZGBdHeccV33PL7ekmpDnkhWTQxMkEpSqkCZxLjqLI2yLSWhHiynS8c0TzgYpQQfGOUJg/NcVHGiLWQ0nvMukBnFvMhwcneosw5NoMwMs8Jwsu4RdUdto7xXAiMPL65a8kxxPM1ZNQOn64YgIFGaoY+HgSyJjfy6tTxcFGgFq8aSGs+6sWzagUwrfvpoQW4k51XHfRuYlimrZmDdejKjWNUdvzyzJDqyhFbNwKpq0cowSg2Xm47ORjbC4OFyO9A7j5aKYpe00w1uN1kPzMcJH51u6fpA7z2jXHHV9ggPUmoe7RUYKThdd9EAV8dU1OerluNp9tphw5v6t6/1av37voU/2BK89CL6p0qJb0oT10OTRKA7uMguevXiQx+HBgQYFQrvHNNC0A0xJTIIMEbgAkxyjZKSSZrz2WVD0w94L0jTQK4Ny9bSDJafPV9TJIq785xH+yUHZUaRKurHS9JU03aW3nuqrscHw15hqHrPqopenaPMkCUS6yMgbIe4Zl7XHcWgaAaLJ1B3A50PFIkkMxm/Pl3zydmGRWnQWlD10RrixarGDYGDMuXBPOe/PF2T7Na0EBx1L5iWCaPUkGlNryMYluoYKGAt7I0NWsYetbEO7z2JUlxXNZ+cb2itZ54nbGvP5abnyXXNw1nBdJcU3fTxXHNdR5bR4STB1Z7OOk5Xnm07EIA7s4JUq1up7Y2yIlGSRCvGaQRT0l3YTJkZjoE7szzabCyb2xCZ42nOr07W/PxkhZEyJnZ39pat9CobKFGS/VHG/+p7B3Hg7ByfnNcoEWVxknjtL4M6N+eEqDoZ6K3Dh3g/bueBdPN2Oxyn32ig/WVPp+9CivJ3AkC6vvp938EfbiXsooY15KmkHTx1t/OUMPHPRIHUEuMU+5mLVP1+N1H1MCqil0PbRxq+8JHiPskS1s2AEgJtJIlwVH2gbAfyRPH2XhGjh3NDqgRHk4xFmWKdJ9WKv3++hBAYp4ZxohmXKYTAfpHQ2h4lU1ItaL2g1JrGDoQc6tbyYJ4hpeIvFzl/9/kV3nsWhUFIwba3uyZXcFW3JEYjJEwzhZSSNJGkRhGEYJRr1l2MzFxWMR1gnBkyLWmt5dFeySgzpFry0YsNVTPwtB443bTMc83xJNvprSPt9P684KBMaXvLRycV3eA5X7U7ICOaQU/zhDI1HBjJr07WnG8arAtoJUmNYJIlXNWWREQZxCgF6wObzmFd4IPjCeNM8Q9P16waG9kuLoImWokIXEhB4wLWB1r3cl40OI8IcUEOPnBvR9Ote8vPX2wwMgJ2Nzrms03H4SjhVydrzM67IjOC//CLMx7Mc/ZGCVf1wN1pBGpSJXhWxanE/XnBshqYlPHA8XCvYF4k5FqxGoZbA2spBD+4O4nTXOs52yWxSRHfMzdgzquL9KvMHx888zKBAE0f/6+HkzR6a0wyLjYtnZYoKRjlKe8fT3j/cBJ/P6SMrADndxMUSLRisJ5nr9zH8TQjk1+/uXx56vCnNIX4U6nlG2XCH0z9tgl2RgR4eh9lbM2wA+klFGEncdARZLkpS2x4BDuPHh/3sJvUtBsfpZvf4pvGUeyQrFUTgSNCTPAREpx9KUmTQLJLBnIW1useMTZYG6iHlyyom+e7AbBuHFWUjPuwShTOR3bRyapiXQeqwVP3NkovRASxpISqgd62aBmn0IUMbDtYd9HHL1HxfkSIKFeewiiJzXwzDJxWDueiQbcWIETg4TzDJDpGJG8aut7hQ2CSm3gA6aKMXHvwLjAaRQlGEzydayMYbwPvJyNclnA4crRDbMx9CGRKkeoYPJBqhffQ42mGwNWmYdt5tk1PoyR152jtQGcdrXNUbc+BK1FEhm1vPdZGaV6SJHjnSaRkkilSAxfbFiTcnxecblpcCCyrnkkWk91SKTFG8eGdKeum58V1DSGwN0pZNj11N2CEwXl4sFcyLRKE95EdZQTjVNH7GKEt8BgR5RX7ZcbRLOfJVcNnFxu89/Q7H6x118cJtwThPKPMIJXgaJKTaYmQMUX088stWsJBmXI8ySjeAEd/EHWyfMNA+rq6IWL+c8EjiOtpD8x2ac19iGDR3YmmGWKvmxrBnXFKNYQdqK/xQhCwnDcWI6JUKwjLsupjcIkyHI4zni0dUkqmefTyfLHqGLxjlhuOpxmLIsUFz7oZmKSKREuawfLpdcs4kaTa8NZeyadXNZPExDVr8NEmwjrGWUKaGg6nOaumZ5wa9scpv3i24f/9y/MItjnPYpzy7kHJokzItMIJ2BPw8fmWQkuq3vG94wmt8ygtccFzXVvsLsXNW8d11ZFogdKwqnpWTQzHGZynSCVCJEgpmOeGX55t+VVvcdbvvFcli0Rz3UTPtsEH9scpB5OUVWuZlSmJkUwyTds3/PsPj1iUGeeblv/p0yvKVLPtLfemOZ+cb/nRnQlSSdqddcXdaXYLPNW7s5ffycms82gpyfRLj9AbydhgHctm4GiUkmeakVG82LGVlPoiG8jtUp2bITDOEooQ2NQVZ+uW1Gjuz3PKVH8F1JFScDhOb1USqYkKkdN1G4dFWpInEbA623Q8NOpr1+CvS1n7U/aq+04ASJdvBgZfW5ZoDJommswoBAPOR58Db2OzOy00mZCsdk1gP8Rmd6+ASZnTdJ56GCiMAMHOcyFQ9ZbBByapohkcWa4gSGajhNZ6vBARrTWabedIjeRk1TAvU9IEPjwcc1X37JUJn1xW4ANawOE04+m159EiYdUO7BnNEAKFE3TeczjJWJQZi3EagafM0A5RO3y6ann/YEzVOzpraV1s5HoneWd/jDGSMt1NXquOs000guuto3OBXzxfcW+WIaXkzrTkz99aMNiAVvDRsxV17znbRh3u+Xbgh3dz6t5jREysebBXMFjPf/7smlVjqbueeWHQWrEYJazqIeq4d0BJmWrONx3zIuFwmuGd5/PLmnuzaChqbLzuJEtQSnA0Tnm0N+LJdc2i7FjVPesupuYAfHy6wQV452BEmSh+fbqNE9AdLfRGyjYpDIEY+amjRx5GCfJMo0SUbt2ZZrsFM5rFlrnmdNUxShOuqhohA431HE1SPruskQJO1z29dSRa38rGxqlCCMkojZMXrSWrxrI/Mqwai/Wej042/OT+jIuq/wLCf7bpvhbhf5X5I0Jc4CGyhXrneb5smGY6elfsBYwQHM4y3t0fkxnF46uae/McIQQv1jVPLhw/vD/leJJxtum+U5OG70J9JzbDP5K6IQ1/HabXsWMpBbiqHBu7YxH5lwyfZheVVhLNqz2RGZvqKBOLgAnYXarajYF2eOX6EkiS6LHELv49ECXTNyWIINDADqwhMp8aD7p31G2k0GevXBvi8EaLGHNvFKRao4VjVCQYCc9WFXVj8SJ6r1VdiBI4ubtOH+9NKoEIAecDuRGUBDSwGeL/U+wAtQEIHeSZRApQSiO9ZVLGxEyjFZvW8v27E9rBsxjtjJaIk18fAtvGIoXkrXnOsu1AQjNEgGjTOca5xNqAFIpfnGwpUwlCUmSSvSLBqBg/nWv41VlN1VkaG0hl4HTVUHeKWZ6SJoqms4QQxSpKBOomSoA9nmpwnK9bxqni3eOCz84b2rZHCEFqJZM85YOjMevW8fHJmsTElJ2784JnVzVV73mxrBklhv1xRsz1iVP/RAs66/AeykRzPE0ZZwmbzrJfpjSDY7NpyIwmN5rBubjHa0i1YL9M0EZyOEnZtJaHewXvHo3428dLTq5qjNEoEfjkYkuioqnr2XXLunHsjxLuzHIyEwM6fv5izftHY7JUczQRrx2WvKl/2+rfOGJ8bf0uzCPBS/YlfL3Hqieu1ZsuSlXnebSzGKWafPAoHVAinifspic1kqttRwhQJIqjsafqPUoEBhsTDbWQaCmoXeD+NEdqzYN5znVryY3iIM8ojEAphQcybTjfRv9MKaAfQgTrERzPIsisRQz6yRPFXq7RSnGxbbjYdrx7OGJvlMTU4nmMvY/yqCj9ut5GmZYknsESLbE+cGcxpth2EaivLY92ab8nqyZ633lYtT0CwWKckih4clFRjVJ+dbrl/iJD7OTP59uO4AK1deyPUn5zWaEF1NZzNMnpXWBRRgDpnf2SWW442/YEEVOXCw2SyAqSUpAozfm2p7OeUaaZ5QkueISIHkKfXVbcmxYMRWCUKjaduw0JmqWG+4uCy23/WiPpm6FvMww8v245GCcsRlFCuO4s++OEO/OY5vbqGqiEiJJD60gyw4vrhizVFOnudW4G8lS/FtQxOoJR+Q4ckkKwquO7s0xjV/i7gEF/iilrv62+Ez3zxW8zQPgOlwP6HnppkRKEiAh3IqEKMYZYEVg2UcZVpBFwis77UddqlCBHR9d6QArJQalx0vH0qmXZDuRaYWScztWdjc77HsZFwruHBVfbgXU9MAhYNT2nK8vRrEQrSZEZHswKTtYt4PnN+ZZFkfK9u2OW1cAnF1smiaIdBDoopkXK01XDqhv4wd0p/4c/v8fHZ1s2XTRiFsRo5c5I0lTFpkxFmv39eUmZRrPMZT1wXbekSrJtBmZ5BJbq3nNVNZSZ4bPzirvzSHfcdhZPZBHlRnK2bnhyVTEpEj44mnIwztl2A8+uW4SQFIniahtoreXONLKaNkIgg+dkHVlaHxxPYqKCVPzFWzMG63l82bAYGQQimlzvDJ2PJhnjnTQqNYp/92jO3z9ZshgnXG17Hu2XOzNSyXXVcVl3TDLN3XnOZdXfmkz31nG16Xj/uGTbOAKBTTNwPM1RCALRrwIiY+np1ZbfnFcECVoKZkU0vRulyY6RpDBCcDRLkUIwOEfbOwYbqAdPN3TcWxSMU83hOMPamH6w3Zlia2XYNANPr2uMkl9Ibfhti3qUrPmv6JJhd/DTincORuyPIj31VRmfDwGlZEzfmOV0g+fuLI967u/YpOG7UG/myr/fugF+bsCOb6odEQgjobZflKB9+Xw3AGYX7iA0TFLJVeORAZCwyKKZ9GChsi+lE454yNF9vP44jYynbfeSsTQ2u6joXUrb9e7GBx9l4Ns2Mjrj3rqTiAfIRfQdgh2YJaOpvpBxP77qLN0w4BwoJUgShbEDnYuAl9FxLy4yibeBVROvE0JgPkoYrEV7T/A7VpaI0nJjIFWS3nouNpYAjFPPvUVxy9B8cd1wOM0YrGecRxmx1BLhBYUJZMZwd5qjleCyslS9JQQRE34GzyjRdM7yYjngheKdvYK390eMM02RGf79B/v8x4/OGSV9BHVSzbPrmqpzrHvLRWPB3fhmgPOCJsSf1zhLMEqRKk2ZJjzay7hqHEdlQnkwYpxKni17Buv41VlFImMSbLvtWFbxUDC4mIh0b14y2MC6brnetiAFF9ue3Aiutx3GKA5Gca8527RIIfjv3l5wtm5QKpAIyfm2Z9MJBtsjiPfbuLgnpDvj2945/j+/uSDXkrJIUERmVN9HtPPTyyZGjbcdkpy9IsZ8V23LKEtidHUI/O3ja47GKUIKjscZaaLegEm/hwpvmKqvrRv25o2f3M1aflOSCLQnJq6DqYc2vGRkvlqaCK47C1kGo1QwzjKmZUy9fbqs2dYuyrR6R54qjBYkRtH7QKkFRZqTd1F50HlP3TqGEBgXhh/NCozRPLmqOJykrJuB2cgwMhot4boemGWarrf4IKgHx91ZweHE8vFpYJIZysywqnvGqWIxTtg0jnvzkmXTkSUa5x3vHk3xITDNNc57TlctjXVM8ujxOUoFn120CCLb3Qdo+p3FxCRyU/dGEIgyPOvhwztjHl9UXFQxLKjuHY0Q3NsreW8/Mpk6B8fjlN5HE5J1N3Awybg7HeGJIQGfXtSRPdRZJlmJEtHL1WjB945HrBtLogLr1nM4VWRGc1AGfvFizb15xqq1VJ3l+VXDh3enNIND6ygX+/69CZPU8D99fkWm43C47SMj6XtHX28kfTP0ba0juMCqs9RdlAZu6oFmcDycl19Z86QU3J3mnKxaVnUMCzoeZxHUAvohKgg84SugjhLRaxBeMqBeF5Lz28CgP8WUtd9W3wkAqf/tX/Kdro6I8m/a2HpnSWxa5Q6537aO6chQJGCDwCmPcwEnQ0y3IlL/Bhc/nyrFuNCcrXseLvKdyRpYK3l0OOLz8yo6/gfPOFc8v2xorWeaa3rv+ey8pu4H8kQzTjVPLreME83DRcHRNOXnzzb0BH7+YsPDRcEP7074X7yzx//302u89zFdTSZoKfj3HxwyLhI2rWVzFg/5HljkUbf3KDFMS8PJsqMbLKmRjBLFSWcZ55pJEhPWJkUSF5UQR7pV73FY/vNnV3zYjDiYZNxbFJyuWnrrqYfA0STHSMEP781ITAR7qtYSAuSJxCjBKNOcrhrmdyckRvLe/hhjwK07jqZ5NNvuLNYG8NGsb3+ccHeSc9UMpLt0g946zjdd9A3aLVjBBw4mKfg4Xd0vM+o+xigfjVNs8IzShPQVWub1tuM3lxXb1rJfJpSZYtM6Bu9pB8tnV1U0pAsRsGp6y6fnNaNM82LdIIEXK8WHx5PoPyTjgowU5EaTJZYP70z428fXvHNQIKTkg4MSqeRu042txMEoYdnE94B1nsTIGIcqvt2i/jpd8otlc0tPLXa01ut64OHCfMFDSQAvlg2ZUSRKYqTjsuqjB8V3bNLwXajl7/sGvuN1I1n4XcsR2QC/7TzXA70D42CaR6+raaHJJJxtbQRIgicT0NiAFBEsanbAESLuiUGA1hrVWdixMrUSMX5YSZpmQMYvR0eyLe4VQEnxEtwSEhCRfWJ99EoKwbOpLQ6JFoGgJcvekgpJ20cvt0UR151MKwbvb9lNk0KzbW00/u4sowSmmaBqA1JBZiR5JmJCWOPYtg4jIxDlA2zqnlFmGCVRQuW8IDjL9XagTDQCQQge6wyzcULvA0IpisTRVQEhA+NME4SgGSxGS8rEoJTAh92kepTyw7sjghB8eHcaPYGer/ivLzZ0w0CaaryLUq9u8NG/RAqCC1h2PovOk0hPpuH+LOe9u1Outx0Xm5639ku2rSXTGotgYjTrrqMbBs7W/S4RFZwLXFQ986rnattxuukZ55q90rA3Tti2jqq30DvK1PDj4xGfXsR94OcnG9puQEkd5S5FQmI0d2cZy2rgrf0R08JQJpqremCvNHx8XmFEfD2mWeC6HVBSkmcRAHJE9tjKC/pVTzMs+V9+sM+kSLg/L0l2ZtrWeS6rnnZw/P2TJR8ejylT81qj1jf1r1fbNweK11Zgp2gg/q7eJDPfeM4lMjImx6lECGh6j20jKxTiupnwchggZGRP5lqSZil6J3NqesesSClMBK6XTYccJD5YlJT03UCiNCkCFzy5FgxW8s5BQj1ENvovzyruz3JSrShSzduHE8pUsq4Hni8brLXRv60e+NGdCctmoHOWdW13fW+8y/1Rzv444d+9NeN//PUlCNgbRyla1Vq+d3dMZyMTx7k42M0TRdt7bO7wXvJov2A2SpBB3ErdMi2ZFwmfX1VM84SjScasMNEfKEBxpLiqepZ1T2YM40yTGI0NcDTN+c35FhfgfN3x1n7O0TTneJRGpUZiyBLN4STjctszWI8P8BcPZqzbgdNN2JlX5xzcn7KqBkZZ9F9NteQXL9ZcNT1H44wf3J3y//v4ksuq484s52GusS7afAgp2BslVF2UrkkR/x3EFy0cvpxaJmUMyTFGMRPwi5MNIQSMkdyb5V+Rkt18f2YUP3045+l1TQhxX7szzWLPv2ojwPUaI+zXAT93ZjnAtwaDvqx6COJlcM+fYn0nAKTt7/sG/giqeWUEIIfobRCIRqTjXCKEIFOeZoDGWrzXpEISRPxN7b2jMBJvNIP3XFQdtYVxocF7pJZ0g+Vq25EYyf1Zwd4oYZYn/Ga94dmyoRp2IJJzdD7w0fM1Wkca5dEs571Dzap29M4zyQ3TPEEEKFLDYpyRaElmoh+D1tFAtLGOatVSpIog4P2DEVJJxqnk88uWw0nGVd2TGYkSmkeLgjIzvLs/4n/85Ir3jhX/5fH1LbDx4/tTPruoebiI3kfNMFANng9HCQ/mBX/trlk1A5uuZ6/MUUpSdZafv6houthYx2h6wcm64WLd44JAICiMYV4mHE9T1q1jnmvynf/TZd+x7QaWdQS2zrYdbhc/3A6Oi23Hto0Hm0WR0PaWZ9c1n1xUTHNDahT1MLA/Suicx/qAkoq9MgJj3ges83x0Xcdo4cxgpOAfnqz43tGY+9OCF6uWRDvuLeKU9Pmq4bLqOdotrEWqWNc9k0wzyQ3t4NkrEwIiTlMEWO95dlWxbSyJkszLhHGZEgLcmWTREFVK2sFx9vkVl5uWLIm6ZC3lrXzsd13UX6dLrrp4jPsmeqqUgv1xytPrBikjEHY8jUyzIPjOTRq+C/Uv4dvwpr59id3HP+Vc1n7Lr+8tXDhPnghsiMltVevYH+dYP7DtLLmBca7J0sCmcejdKaixkOjoK2TUDhSSkSlTJJK6h2IncSsSqAa4yWRMRNxjFZAJQEY/JYUnTRMOxylX1QBSYpCMsrh/ddYj8DgHuVEoKSIoJSWZEKyd3e2BsDfSNL1jPkrorAfrGeUeT1zPpYDCGNqhiUwkBEoK2t6zbSxCBGZlTpFq7s5T/vOnV0wTRask81Jyte1597AkMYp11VE1PUoqJlmCkIJRqnh61aAFjDIdJYJIHuyVHIwSkkTx+LLjE1fx5LolldHPL5VQjlJcUGyanmdtj9m9cEYImhBIFaRGRWPT1YAUmjuLNKa+7cymx5mi7R1GK5brFuHhvGrZNjE5TQnBSEsaBrrecrVt2Q6ecao4GqWcrKJH0iQTTLMR55sWrSTr1u3AKc+4kPz8aUueQtU5PjwecVVZHh2N+M3plrcPCoyOqFzbW7o07iiJUoyyyELYtj1lqiBE36emi6/j0Tjh/jxDS8PlpocQ35vLqmecaQYfX9e+DRgp2bQxAOONfPrftl5c/L7v4A+zFBHUv2EgvRpU0PGSoeSQjBODxTMVu7TfLtDumKRql1gpiF6qB6OM2c4AOzOSprd8/86U56uGq00HQSCFZ117amtJpKDpJEkmGKeavUmKrCzGGJLgEVKxP1bkieZOofnw7pTCSP76s2uerxoSE9eTtw4KPj2rWDY9QkqklCRaMrg4gCgzxbu7pEkf4L95d8Gzq4bPr2qcg/ePJ8yL+Pv5+CoC0LPS8JdvzfkPvzjjYtORGs3B2HA4LTgYpVT9QKoUWguuK0uZGqaZYZRrUqOZFYbTVct1a1mMEp4uWxYjw6ZzfH9e8HzdUWgRlcchUKQSJSXX1UCqFWWqeOeg4LPLGiVBENgfJUghqAfP2wcjvnc8oeoHnAs82htxuu1QEBMhteDeLN+FFShGqeb94zHOe6aZRgnJ/jS5TUPOjWaUxBCf4KNP1auD1ldTywR8ISTgeJrx9LpmnGmyRHE0zihSTdW97NXbwUXAbzfMvTvLee9wzJ1ZzsWmw/mAkpKfPpx/o/z3dUE3wNcypb6pvk718KcI8n8nAKR/yUjJ70K1AaSLU9ijaUI7sDNIllzVLW0HkzKQJJKmiobaGYGgBMYE+iEgQ1w8to2lSCVt60iN4v6iYJQacqOoup7PzrY0vSPVistNT/Ceuos+BEOIBmtt5zhf1gTgYJSS6sj6sM7hE8n9ecbFpsf7wN98dsWiTEi0pDAJv3ix4sFeSSqjz8N052FQpgmShhA8s8Jwte2ZT7LIKLGeT7c9WkLnAsfTnGU1MMpVjEQeLI8ORoxSQzcopCQatS0KjJY8XTV46/nh/SlVb/l//P1J9BjabYCn6569MjDPE4wQ3J3l5Gl8bXrrybTmg6NIIW1tz6xIeLRfsGwsR5OUu/MCKWIkZyIFV80QIy53E9z/+MszDiYJjQ28ezii6T2jVPFi1fHOfknVOQ7GKUZGvXUzOPJE8viq5bPzLUpJ7s5zzjaO3npGeaTKJiZqqo93r9PlpiWEmEDz7LJCiIBDRildovn+UYHW8gueQ1VrWdaORZmQG42RkufXNdPc8HwVQctuiIynwQVO1y0QOJ7lPJjHJvnbLOo3uuTeuuifsYvn/F3oqWWiuTfPUQISo/B+50EiBMbIf9Lm8qbe1Jv6at1E2/9z6ubg8nV1VABK0g0e6x3WxsSzZoB1O5DpQGqgHcDX0bDae9jbJdEsK8uygVxHKZsmMpvSJDC42ACjogTNtjFQIpUxaEKquKdmOsrVlIF0l4zmvOeqtTgEznkskCmwUnBQpizbARscRkVvvDw1lEmUXp9tt2gDeapoh4BUgQeLkvvThE+varyDPggQjmADaaKZhQQpFHkiER5OXPTVCF6RqrjOna562s4ikIxSxaqxrNuei63mLx5GWdYdrXn3aMQnpxsuti2X257MQAjxIJEniuN5zrYd+LtnSw7KlPcOR3x+WfNs2TBKDYMd2HSORMbI7CzVLMqMaSp4se7RSiAHT5EZUiWZZprOejyeZTUgguCv3lvw9KrBOpAi0DvPbJQwyw0XdYf1jjzV7BWKzoNoBTY4nlw3TIqE2ShjMUp5smrYND0LYdj2A9M84d5eyaJI2HYxkjvZSpatJU0Ude94fNVyNE4YeocWcFUNNH1DCIJ784zLumeWG4pUoZXEAe8eThic5R+errG2Zxg8vQysWsV9qZiNogz9R3dn9C6wagbO1h0f3hmjZTSXzdMYpx3TVf0b+fS/YT35fd/AH2jdrL1SRA84RExOuwkvwEf/VK8985FhWPc0HUwyQ+96/A59ypNoLSEFFInBS4HRhnmuKDNDZz2X645cRkA5TxTbfkAoQSo0B2WCBR7OI8Po4V7JrIhgzdWmx4fIHNwbGRZlTtc7TpYtZ+uWMo2JxO3g+OjZhqod0FrzzmGJc55xZhhnhsuq42rTc7pqebAouNj2HE8y3tkrebAoaDqHE4Ffn1YsSh0BfClY1j3X246/em+PXCvKRPHZVU2uJYMLHI/zXWq05KCMQ8nOOoyU3J1kPF+3EZxX0Q/peJpyd5ozKTQfPd8SfEAExd1ZRvA++orK2M8HHzhddRxPUsap5mzTM801D/ZKHswLzjc9Z5uO4OFk3XC26Xix6jieZSghaHrHKNN8/3jML8+2bJqBaWb4/vGYy2pgb5SQavWFNOTDccrzVYOw3CYouxBu3yw36gDrI9v/6XXDvXnO3VlOZhSPFiWEaDmSaPWFXt37wOcXO4BPiHgWsZ73j8aMs8gC/Tb9+euCbf4pYTffpTS27wSA9F2r39ZI/7a6oaIqCbMiY904JJ6y0AQS1rJn8I6rjcOYOFMYLFTCUmAwGpJU8+OjER+fVbS9Y5RrRloRgmBvkrBXJDy+hM51LJKCuR84WTWsGkuRaoQIXNcWkIQgaV3g8cWWZGc2+oM7E45nGVJInI/gyfeOxvzj0yXn6xYlYxTjz59vOLnuOJ5nXNUdSkCWGAYbY4mNUlw1/S2VddtaHIHUSBbjhI/PNzjvCSIwLxKsC9gAVRPDSstUMc4092c5WkoOJxmH4xi5q6TgVycr7sxSpIga7RBimpvzsBgZ6t6RGs26cWzqjiJL8CEwK1J+cDzFEkikxIXA55cV49wgRUTeu8Hxq/Mtq3rg/iyP7JxtFyfSWrMRjhAEB6OUO7OMbohmdvvj9HYx7qxnnhueXTeMsyjnGqeGfvA45+icJ7h48Ag+gIjJbc+XFe0uv7pqojY5M5JxptFScbLpEFKQaHWLvt+b5TSDZZTq20jQTdvz+KphUbpoYicEZ+uGq6rn+/emzMuYgDBKNZmSPL2uebQoMVp+5X3rfWDYeTPdeBlJKZgVhp89W+2mEYIf3ZuSGfVbGURSRnDvZNXGGNMvfd2bJLU39ab++RX47TK036U8cWo9BjZ8kVGWAVZE7zIhIhNJACaVCBUTtEZpQjcEAlFSVvUurvul4Xo70HuY53GIcbLuEAL2R5rUJLS9AwnGx2l7u3vycGPq7SGT0fvDA8aC0IG2juvKMDi00RAkRkM1eIyCqgvxwNBJtAy0waOkZ9t5ci9RYsfeGjxKwKRMuD/PyRONczWr1qEkjFPFZJIwzRPeOSz56MWGy03HqukY54YPDsds+yg1+PyyYpJrtr0jiIFlE2i7gaYfqLuO01XD1XbgaJoxKxLuLwqu656jiWZwESBbN5ZJpul6RyoFm8YyDJ7TdcOqGbiuBvbLhDzRMZVHBLo+UhCOxmkE+b1g2fWkWiIlZEpwUVvuzuNe50OgaQdO1i2H44wQArmRbFsHQpIZzSTVKHIg+tpdrlvuTFLu7RfIELhqHKUR/PL5+pa9NM4MtfUkOiCIYSBPLyvGqSbVkt4m1O3AJNd0dmDTadLE8u7xmGHwrOqBTMep9tOrmo97x8P9cueV6Dmc5Gzbnodzy3MRUAJa78gSGQdd1pMlilm5YwZ0Opp8C0HVWYKAMpFoGZNS38in39QfQt1I1YKIDE3kjlEUIhAvZfQ1mpU7E2QlGWXRry3REq0CsyKJZsciDiJTJUiMpLWBw3nBIk/Aw1Xbc1gm/PJ8Q5FIQjBkieB01eN8YJwnbFrPi6Gn7gf2xjmbasB7qIfAB6OYrHiyqlk1Qxxy2sCiTFg1lsHFvvydgxHzUUrvXFwX+h6jJJkWnA0O6zzOBzIjebaMjPxH+yVCCaZGs0kGEq3IjODj84rHlxUiBP77+/Nb9cAoNdyb52Q7u4bHV3X8niQez+1O/WCJbHopJefbjiLV3DclIXhOVx2D8/zFwxmTPIlDiaZnkRm8EDgf972wYw5Ni4TERJbTNE+4bgakgqdXNVpI6s5SJorOeqpdeMCdaYYQsGosk1xzue4pEkWiFX/xoPyKJ1s7OM423e17Y5LrLyQo742S3d8l55uWzKjI9hfcAi5aS+4vCk5WLVX3xV69212/TNXtcPhs0/FovySV6htlcv+a9V1KY3sDIP0J1Y1J3W3iyiuP3eiLf5ufuCIaiKYJt2i/VuClpOkdnQ0kRtJ3nmEAKR2TbKdbNdH1XgrJJJWcrvroD6ED0zzKqp5cVhyODe8sSv7bt3P+4y9PIQSyLOPRQcknZ1tGiYoTVyFIlUBIRZFEmdX9WcHeOGVSGkSQzEcxnvJmuvf+0YizdRe9c3xcxGo98Pgq6ncfXzd8cKhoesF7hyV7oxR/FZjkCdtu2KXzCNre8eSqwbsQGVFS0NnAe4cl3zseR9PP3tENngfzlMUope4dMkRPg8dXFZdVz4tVy3VtyU1gqgzbbiAAdxcZuTbMioSrqqdIJKebge+PMpyPEimtJGK32EoiGON9AAmPLyuqznE4TllWUbcthOBk0yBkPFUkRtJ0cbFXUqDkjk6vXy5szeB4sWqA6KsxyhOeLRtSLZgUCe8fjhgIDN3ArEyYZIbPLyoSLXm0X9L2louq5529gsRIjic5z64b9icJeRKf52YzMEpSGM1G2Cg7KARVN3BvlsbktXrAukCiJVJFyYRWgtRo2t7xYtPS7UCr+4viC5TQurN8erHlatODjJK5t/ZKEiVZ1gNvLYpbGu1y53f0uzCIvo7aCv+2m9KbelNv6qt1AyPfDEwSAA3CfnH/64DryjMQ98iOCOhUjUcp2NqAFAO182gpMImh3K2Xk0RDGcMTErMDlnbXrVpPa1uazpMKSS38F1rEG/azDFHW1rlopq0k9H0MnShkIPhAPwxkWjPJU7btgJaBq6pDG4VW0YcI4TmvBhIF1iu0gURIyjyypATw0WkFIdD3jq63lFk8LE1yAyIyBD44HLOepnx6so3SMAHzImFdD2gdCA7uL3J+fVojvCUISWoMmz4azBoh6DrHuh24qgeMVsx25s9n2zZG3BcJmYLL2rLuLP3G0vaBPI0ClWXVU+aavSJnUWguq44yURyMYuxzP88533Qg4MV1g9SCjMDBKCUzmmXdsrWO1brBh8Cn5zXH44wi05Sppu8HtBLMi4RpmXByVSPnGf/9+wesO8e6GWiWHZ/1UeJ2NEk5mmZ01rO8apikikBkDTxfN/zk/oRnq+hFdLG1PJwblDE8WGRMsoSfPpoTQuA//OKMwTpO1rH/qYeeIpUkUvG/+fExp9ctdaZZ1QOJlizLgXXd0zrPs1XNW3slM5PQ9I4i0fHwlSX88N6Eq23PrDBc1wNlqnCBN/LpN/V7L0E8NyQaBgtexbU4y2RMHiOuyWhBIMbRjxLFQWHorOOyGuI5I0jsEEhzwfE05eHeiLcWBX/9+JqDMkGryGrcnPSkRvHTBzPWzUA1DHQD3JkKOh+oh4FuCORKcroduDsfAY69WQ4E2iEQXKALAWs9TesI4SZYReC8YFEaJnlCCIHLTY/H81+fbkh19PPcn0RDf6Mkvzrd0g0OHwKLMoa+PF+1OBfYH6dMMhPNvIcEKRXrdmBaJPjBMh8nKCkZdkzCw3HKurXRO5QI+mglSWRMSO4HB+FmcOCoBseyalk1FnZfC5AJxTiPffgNC7/tPd4FTtYtiZRcVj3H4xSlFQlwtooJ0pfVwMP9glUzMM71bUjPPz5b7aSFmoO7CdfbGJB0UfUc6wyz0x6/ysLJE0NvHT9/vuatRXHra3qxA5c6G183dpLqxCia3t0CLt/Ug3fWse2GWwbSjXTu1XpVJieF4HCc/qumWX6X0tjeAEh/ZPU6dpEiUuUTBU7sACB2VHpiUo0AZoXGOst58/XXF0CeQqYjYHE4Ttg2lifXLUPwDC7SzUeJgjQalyEl1sVf9lFuGIYYb1N1sSnKtdrFsTuqNpouK6X4n7+3x4/vzzlbt1xsOwKCRZnwzsGYTAv+8dmaZT0wziS1DTuKeM/+JNtJ2RTHk5gG0FmHdYFRZvjkvGLT2t1Cp2ic526puL/IGWzgwzsTto3l8XXD46sl/RAjfaXYZYwJQZlK2t4iVZSeIWOM/eA8+6OURI24M80oMoMI8PHZlrf2CnJj+MWLJb8+23JnkjPKFLNC8w+fL1FKMs01bx+MWeQZjbUkWjMrEr5/PEYKwb1FQaYV/W4S8aqG9nCc8nzZ0DvH6brjwSJOmotEcbZuuTPzKCTjVMVpkBSsfWCSapwnsmnWLW1vbyVZNyh+nApHE+5H+wVpIsFH0GzoPfuTlKNxxumqobWW3MSEiEmRcG+Ssxgn1L2jHSzN4BBC8GLVoqSgMGoXXRrTzHrnOVvHjWqWpzzYKzlbt3gfUCouvEoIPCFO7IOnt54yiT4SqZFfoITWneWvP7/ichtpynul4brqSXaaaB8C+W6ag+JWQ22U/MaJwKsA0Y1P1LC7t959NzTOb+pN/b7rxog156tJeTe+GhD3QCVg85qY7RtWrSCCRwFoPcgd0JQpQAgKLRBCYV2U76ZK4oJgmim6scFaz+na4n000c4yTecckzyhtZam/qqX1k1iHEQJm5GCIlf0FurG0nqwbQSyCgOrqkdIQWdBa0XVOIxyHEwyhDSI4OgtjAoJSKxzXG97FiNNCBJnHZu2iwc5okfhDdv0wSJnVTuUdNGcdV4gfGDTOS7ajqof+PHRHOeiv16Z1AyDorYOKQVGCAYXUFpwsukxcsOoiLLmznrWnWXwnkQrFqXiH59UlJlglBieVx2tg4nUKA2bZqBqd4yiWcE4NSRGMisStFb88HjM/+vjC5p2iJL23rPqLIMLbLuBi83A4D1PNwNqM9BazzjTTFJDP1ierjoORimrxqKlYFQY/tt7e9yZlnx+UaEQ5HdG9NZzsu4wOvodjRLJg1nG4GFT9eSJokw0g5f86N6Uv/7NJeNMcjDLGGeaqnMQOv7x2Zp5rvn0vEaIaJhbpFFmo4Vk8J7fnNbRRHfw3F3kXFVdPGBIOMhiyuu7hyVHk5zPryr28oRJbpgUmlUTDd8fznK+dxQ9Hd8ML97U77ME8RCZJ/Gc0VvQBqQGKRXGSNrGUyQKjOTePKdqB55e1iRakhvDrEiZlg5CwDrHs2XLkU5YVpafPkp3ycaGwQY6O5Alhh/cm3NVdbTWE4B3DqcMg2PVRla7tYFREhmf88JwsekpMkU3eP7iwRSpIuvlYtuhcxPvLwg+vthyNMm4O8u4P8sZFwm/OtmwagbqwfLnD2Z8frXletOy7S13Z1k8d+QxLj54z//zl+d0ffRqfbRf8OnFlkwr3t4vmRUZh+M4ND5dN6wby+I4phVbH9O/xM5PdFXHjexwnHJ3lqN3cfPPlw2DC2RG8OQqMjTnZcbRRPCr0y0/1Bop4XCacX9ecLbpGELk5+6PEs62HYmSKCk4HKW82HQsigRETHj7/KIGIWhbj8kk11XP/Xkc2M4LE9OmA3x+1TBKNGkS/+8vlg1v7cWEtC+zcOQNC+qGvS/iWepoknFV9TE0IUS7EP8aVuXr2P5KRMCp6WNynN29Jq9+n/eB58sGJSBPFHVn+dvH13FAvzPU/rZ9+28bHH+X0tjeAEh/ZKV3H46XbCJHTH0Z5xIXoOv87eQzl5Ca+DHJFK0NrBv3WiZSSqSfSwFGK+5OUxKlaIaBIjNsmh7nAvUAB9OEMhFse4+1URqUmUhhVEagtUQOkjKNTZR34IJkliZMCoNRgXVrMUoyL2PDd1AmHIwSZmV0zv/Jgxkfn21YFAmr3qKDoOo9iRb8+iz6/3x0suW9w8g0OVm1FInmv3lnwccvNojdovX8uuN6O9D0sQlf1UNM9RJwvuk430RD0L1Jxr1ZTmctP3taIyUoKXjroORy06GU4Lq2lKll3Qy8fTAiT3RMn9stettu4OOzilU1UCSGIhFsa8d7x9EzaVoanl+1cdqaaUojmBVZ3DhETB8AvqKh/fyyil+z+1nNck26YyRpKdgrYzLbg3nJk+uGcaqZ5wn/7q3FLbW0d57BeZ6tI410r4hJCZGGGietvfVIAVpKtFb86N4EoyKl9e+fLVlWPctmoO7itOTBvOBwujMw14rBaTobyFSk4La95bLqeT/EhVdJwbv7Ix7tlXgfeLFuSVSU/p2sWryLE+Y80axqS5FrCAEhQSoZwTutbkEgPJF9BRSJxijJqrFMM30rZ/unTAPawfFi2TDsIj3nZcKyHnaTkpgGNEr1n7zG+U29qd93CV4yaw0RCAqvPBaInht5Buv6ZYT0l68hiQbWdYCJhpWFxoPooTSwqS1aCYo80PYOpQQHk4QP7k5ZVj3b1vHR1RZroxyjSKF3Duc80kiGwd+CU6/WjbTOhTjkKXJNqhR1O1APUGbgbdx3r6oerQCh0CLKQayPXku6GVjkCfv7E7atZTZOqS+qHYAmCA6qYWBepiiZcd300Si6s4wyQ2IUCkFnLamWLIokmtUqSaYDvRIcTgoezgt+cbJh3bV0Ng5UjDKEYKms4/F1w8O9kvf2C+4tCnrrQBj+4ck1286SJZrSKJaVZ5pJ8kTTO48QkjwJJEaRaWh38rr1diD4ioNRxp/fn1GkhpPrhifXNUrBZnDcneY0Q2BmPakSnGw6xpnCeskk1VxXPSIEVtXAJDOcb3u8dzzcK1iUKbV1CAc/uDvmN5dxCNNai0kMnR0QUpCb6GtklcAYzZ2RoTAaZEAoSTc4VrWlcYHcaM5XLd6nbFvLokgZqPnli4F12zNJI2Otbi3TXNNay7b2HExTlBQMeDaNjUOSEJAysp0aC08uG+ZFzr1pzt1pRj14usGjCoGWgstt/2aveVN/EHUD4IsQ16jERHZKYhQTI8lLQ91ElcC9WU41WDZ1z2yU8Gf3ZkDgo5MNMgiyRHK28aRaRx9WEfgvn13zP3x4SJEkrKuOi2rgaCJRO8B/v8xonUcBh/OcH+VTfv5izbrpqTpLYwMeQW8t2goSLTia5fz6dIuSUKQaiWTZdLy1KFEKvn93Qq4Vvz6v0MaRJYpH+yXPltEzTV4JehfwOLbtwGnbsj9OEQL2xhnzXPOss+RGMUoTytRzsuoY5xqjFSfrDus9rfX86N6E+Sjl49MNl9ue451MbJpFs20pBSKA3TGlMqN4tFdyME55cllxuo6MxP1RipSCX59uKBPJKE9ufYQe7ga4Sgiq3nKx7RlnhmXTsxilBBf44O54F6QAyzrKZC82PQfjhEkWU+CUiLYTmZakWuIdXFc9L5KofugGz/44ZZyZr7BwYhJ3VAC0/qa3jmyp40nG/jjlfGd6HX5HVmUQcDzJ2KYW6wJaCUapJrzybVVveXbdkJp4dup3A+DcfFEd8buupV9mM30dAPVNrKk/pXoDIP2RlSP+0CRx4b4h7PUWqs4jlMDv3qtKghXRvHOUGqrOYr0nS6EI8VptH+VuGXBnYdg20eth21pOlj1+GulL41QyTlJWteCq7nHOMTjDIje0Q2BWaoQQrOqBRZmgEIyyGMopdwuX0QIvJRebLkbTu/gLPx8nMcY91WwaR5lJnJNkJm48be9xAu5MimgU7SXPVjU/vDvFBdh2joOR4oOjEa311J1lWvR0zvL0sqFMIr0+CDhfR3lWlig+Od/GVIFpih2nXG46jBaM0pQX1y2zQtN7WNfR72CaGZSUMeEG+IenK37yYPYyRWhwXGziRDECEFueLVsUgrvznAd7JVdVz6ODIjbTRvJs2bE/Dgw2Uld7FxO/vozen607Hi5yklQjhvi5po9Ro89XLZNccdkM7O08MO7O8lsfIHhJKR2lmmQe9dqn2w6zQ+FX7cCsSLDO8/3jyS6ZTjFKDQCfnG+5rgYWZUqRas7WLf2OjfXWfgTwXAjRaFrwlejOxjout/0XFt481bceQyHAB0djQgikOuqXF2VCZhQiwOPr+rVGem7HO84SxbazBAKDdQwhmncbJb/1NMD76Dd1XfVIGTfBzy4r3jsckesIij1bd0wO42vzp6xxflNv6vddCZAlsNkxaiUvGxctYJ7FvWxZf71E+yYhqN3te82OeeSI4NTgIphkbCDRHq0EiU4oU82Tq5hMebJuySU0u3vYtlCkjkQrhJRUw0tA69Uyu/s0WlAmEqN25p5KEnBUfWRAyV2DPfQglSNo0EEyK0AIw16pOZrljLTiaRBkIsp9vVVse09rI0C1aQcCfidpi418oqO3nAuQSoFQkUF0ve04nuUsxilCeK5qy399vkZLqPuBh4uC622HQ+K9INWKzlpUcFzWHdXgGFy4lUmPsoR5kZBpsWNSxf5hVqYsqo5tb+lsz7qJPoPHk5z785IgYTFKGGUJ67bj82UVATQnuDPO0UqQe0dAshglZImkHzybznKx6Vh1A9MkJrhebzusC7yzP+Zk1bFsLcMQeOeg5KqJKXohCA7HCavWc3+eI2Q0MDdCcHeakSeaF6sWPdYY4oCmGQYkggfznGlhOFm2XGx7hIxeWNet5WCcUg0OFeB009Nay9m2ZQiBTCuEhM8vtrggCN5zPMrjQW1kaAZPpiVCSpQKnK47poUmMxolBGeblvvz4o1p9pv6g6gUSJII3u+PNKcby6LIUSpKaZ3U7GUZKZZ139MNMYggSTRH03hoXzeWxnreXpRs+4HBDaQ6QQXYDIHtsqbZBaDsTzO8FIwyxeW2Y5oZOuPZV3C62vVqCP7q3T3+02+uOBin/OaiQgqBVoIPjkY0g+fxZcWzZcO8NFStQ2vHXhEZpKnRgGBaphw1lrNthxaC627AOc/JsqYZAvMywfpAbx1CBu7t5dRdTEz0IkqSpxND7zw++NjLas1V1ZMowZ/dm3FdDbRDoB9clAVreQtGnG973torWbcDv3yxifvFzr9zViSMM8N7B2POth2FiYlybW+5Nyt4/2hC+krM/av1ajDM2wcl1npcgL0ipek9SsLDvYI7NsUfRYBGSXlrSL03Sqg6R2sdCOh9BGS0imnZ55vuCylqr/bdP7o35brqeXrdkGjBw70CLQVnm46Hi4Jy79uZXishyBPNKNO3HkjOv0x58z5wsekwSpDshsdn65b7O8BICvGt+vZva479XfBIfQMg/ZGVI9L4JbExneXQ2V0qjIQ705zzTc2mi9HBSkeQ6LweSFUElZQEO4DWUKa76zrYdjYmxxjFLDfsjRPmuWY+SjlZ1VxXA9YHyiwl04LeWeYm5+2DnMU45+y6Rgl4uDfCB8/pumOUJsxLwy+biLAXaYz93S9T2sGxbS3Wxyjk/TIlUZaLVUcIcHee82h/xOA8n1/WvHdcsmlj+hrE9BqlFFpGR36jJdPMICYZSkHTWuZFihACaz3TzPDp5ZYsiR5JrXXUlcVoxXXVcV33TErDOE0wRlHbwChRDEpwb17cJt+MU0MAnlzW/Op0TZEYJrnmyXVD00ePIykDH582LOuevXFKmSrWzUDXO7wPzEpFkRgoBW/vlRSZuV2g7s/yL6D3nY18Mg88W0a/h7Az8L6sPN87HKGNxLnAi1XLTx/OSb+Eit9QSkFwumkpjMJIweA913XP/UXBNNWcrjuEBLGTE0oZgSoBaBUXwyLRcUNMFA/mr3gR+SiZSLX6QnSn9XFjSbX8ysL7ZaT+5l6/vIl8nZEePrKl9oqEwXnOVh2D97xTjG7TIDL57aYBw05iN850fP0Hy9PrhvcORgBoLXHe0+z8Rf6UNc5v6k39vssRk9JulGmBnRG1iPvX9+5N2DQDq2fNayXe8UjwRbPuV4GmgSh1ELvnWtcBVGDkG07WoEVPkWjqwTI46AO4G+lbiAyhy23HzgP6C/dww3xKNOyVKZmRLJuBd/dLrhuL947Oe2aJovGBfoDJKA5ymjagtGcvT3jnaESqFXfnOVU9MM4d/TBQGInX8R4kkRHs6XEugiRJopEhsGl6QhCMM4dVkgLFYC1aK15ctyRK0dqYnFr1lqNxiqtgr8zQOg5Ptm3P/jjlyVXDuu7ROtANgXGu8M7t1kJH3Q+sGk+u4Sf39kiM4GrbsZnkpE3HZRU5ZHmqaQZ/y/Jd1gNPrrb87Nma3kYPjElueH7VUA2W3nrePSjJlcKawKaJoRue6LE4LQz94HjvaETnPEIInl7WTEvNKFVAoHOOk1WHkvCbi5qDUca6HW4PSKNcMwSBdI5JYQjB8+S65cWqpW7jEOzerGCw0VNxu+2YlSnP1j39YBEIvAvYEKKU3FsuGsv5uuF4VvLxyZraOn7yYE7dezYuSnISrdk0HRd9NN09WXZ4AmfLHql6isTg8ExTTbIDlN7Um/p9lYB4nhBQpJLBCcapItXR7LnuITOei3pgYgRHoxjw0vUWISQnyy1X2x7ro5/P+bbjctPRdPH3XMuMNPEM1vEPT1cUieLurOC9/XFkIC5blAyM0niENTLKrGZZQmMtiyKh6iyz3LAYpRxPcyaF4e3MkGjJnWnGsuqQQnC1aakTx5/dm5InhtxoLrYdUkeZ17xI8AS88zxbNtTdwPEs4+Feya9P1ggRz09N76l7y6O9knVlOd/0SASz3MQU4b2Y0iylYJSZHbPQ7QavHi1fmkF31vLrszUfnWzJjbpNUfvZsxV/9fYeWkuSRPGTB3N+9mxFs+1QUvDDuxP0KwEzrzJmAA7GUW58tumin+juc68CPqNEczl49kY7z6lXeu3c6NvefpxofvZ8FdmlUnA8zXE7mwcZImjz5b47N4rB+dswIOAWxPltlhJfrlfveQj+K8NhF2Kq851Zfstusj4wTfXt+erb9O3fJXPs37XeAEh/gPW6KeaXHxfsGl8hSRNPU8Wkg+vWEqRisA6tI61UiZfGdsFFc+UheHrgeJzQ9p6qjZG9qQ4YJZBC4hFc944fH484WW5JJTw6GiOCAK0IzjLJDVorjIxJaFdtH9Nahgg6zEcJsyzhe3cF26ajsTHyeJQpBhed+YWAo3HG331+TaIlzRBlVL8+3fLhnSl+x2x5ftXywZ0xvzzZUHWWF+uOw1HKVkZq4l6Z8GR5kyYGQciYIDBKOJzH5JnI8FFcrFuutx3PV0308CkSgg+sq55NY1mMEopEMysM7eD44HCEECJOEHYsmDvzbOfhkFGmhnlh+fXZZtfIeu5MA9PcMC0UIkiWdceytnx4Z8JbeyWDdazbGF0shUCqiIgHwRfQewEcjBJOV+0OrIlTmEQr7k4UkzIBIkLeDO61CWVqpzl+vqy52EZ/oFlhuD8reHLdULWWIAT740ix3xvFCUvVWYIPcZMR0AwOH201uD8rboGqVzeqwXkGS9wsRQSiTtftran2Ny28X4fafx0l9NVN5HCcsV+mHE0yxrvY1N923Zt6Vdf8lc/7gAwweI8f4GTV4Dw8X7bsjT250X+yGuc39aZ+3xWI8q8v/Ju4BhkHn1xU6N1+9jp/QEMEmxyR9t75l/urBBIJg49fmwA2RMNX6wStdSwry14pdkakkWIPcWAzyRPqzpEaien9bcrazbVHMgJfg4d6cEgRb8Ij+MmDOR+niseXDc71dIPAyLjXjRNFEB6FQCi43PaUmaa/CrwzywlKUvcaKQe2TY8NlkxK5lnCrNT0g+V6F3NvjMZ3nm3vaPqB1ChOm57caCaJ4rNtxy9PloyylCKNa7QL8GivZHCBQguavkcEqFtL3Q80g2ViEtJEkSiF1vGAMbjAOJVcVQMhRLDs/cmIdW356YMZf/90xbKt2DYO0TisrRF4WuuYlwkvri3z3NB5Tb/bH6eloV45jJJs64FZnnJyVXNnUeB2HOy6s3zvYMTJusV5wbb1nK/qKBdxgfkooek8at0xzQ2TIuei6jlft8xKw4NFwbIe+PR8Q2YsD/ZHLHLFR8/XCOKh42ic8fy6pu0db+8X2HHKyCgcMMo0WyHoB4tR8fXzSMZFipCKzjoeX1Usqw6BYJIZ3jkco0Tg3jxDE/AyZV110VTWe1KjWHUDi9JEqZsLnGw6fvqguJVvv9lz3tTvowIxEMA7IHjyNEpJq8GzXxgWpWKaataNZ1ykjDJN5wJFImkGeLFq6G3LNNO8fzyJdhMukGp4vupZNz1GC+7PCk6XkTVysem5P1cgBbMiYdXEMYBSknGekJroHfrLkw2r1vLeYcG7x2OMgMU4BR+QSkV/Mq1YtY6DUUaiBamW5KlGEFlFvY8L+b15wZ1JxvtHY05XDYdXW359Vsfoeeepe8e9ecHDvZJJ1vOfflNTDZZ7i4zBwbzQjJOE7x2NyU3s88PuPJNpwabxDNYzzROUgtY6Nk3P8+saHzzrpmeSlVHeNsmo+nhverfuzYqEv3p7j95Hc+yLncXEjVn02Y6BY33sW59dN9yf5xxNMlyIDJ3zTceliPK5h4uCwXke7YXoefeKiuHVXrvZhScsynRnHJ6gZUyHfraMJruvk3gZJW/DgKT69iDOl+ubpGI3Mjq9k0921t2eV78yiP6GujkbiPBPs8P4U643ANIfYH0TeATRLFQQp46D9bQOlIpsI7075ENsWnv30jyULlJONTDJYDOACILFKCNRHUooUh3QSuPxWOvBB355viYzhmaAwQe0lGRKMBuXMfZy05Fpxf4koRocWijuTVOu6oGRURxMUn50b8LTZUPV9VxuLalStMOAkZpl1VOYGFtbdZb5KEULeHJV8enFlkcHJUfTnNwI5nnCfpEyzmJkcNM76sHxl2/NKTNDZiSfX9W8uz8i0Yo705Rfvdjy5LpBiMD7RxOazpKnhkd7ms5Zlu1Anip+eHeGJ9AN0YzTC+itZ5QajqY5iZRcbHtWdUwHm2aafgikKqLq0XQ8i+yVXKO1xCjByaqJRquF4Uf3Z3Ga6ANKSopUsty0TEYpcic3UEJgzBfR+6q3nD9expjLHdp/4/HjfdQSe+LP5msXtBA9nW6mHDf/vr+LRX6xbklTebs4djaCcpdVHyODEZhd4t3RpOTtgxFyx/76MrWzt567sziROF23nK47Lrcdh5OMRMnb/+fvqimGbw8ufV192QTvdSkNh+OUs3XLVdPjfWCUG5recVXF/+d7RyOkgG7w3N8ZHL6pN/Wm/uVr+JrPGyITaF07uv714FFpdj4dMh52JJCK+PcApDrK2V59jrC7diID28YSgufFMg5heuL+mUhYjA2TVGEHy6r2tD4+ZnfPrQCTRKmHMRKEoBk8k0xyuem4rnpGWcKjvZzPrjwjKQnCE4LnsnbMS003WJoeettzf55xuh74XEAqJb0PXG168hSmhabrPYMbML1knKXkPqYNFYmkd5o8QOs8XR/YDI7vHyf0HsapwgZBqgWfX1QYFThZNRxMc3Kl2B8ndDaQ3srjBVorUi3isEkJpFCMU0ndDbgQo6eTRLEoDfNRytnO96NqB7reExAM3rLZxP070YYgI3vnwzsTBIJPLyradcfxNGWVSNb1wGfLltYHLuqB79+P7ALrHKerFiegGgLn65rFOOPZVRxECRH7pCdXK/bKlMUo4XLTczhJuVi3UY7tA5NcMS1SZkVCmWheXDcsm47DccbeOCNLIqh13fQ8vm4oE4MN0WcjSxR3pxmfnG+ikblzPJhlrJrh9jA4zgy5MTGRTUuW245NaxllinXnGBmNKSXbduDzq4YPjkZ0znFVwX4pee+oRArJybq9lWC8CW94U//WdQPK36Q9uwDOOwavmY809xcld2cFB+Ocnz294oOjMRdVR5karitPbmKi16a1zIvIxDESJoWmSCVlloKQvL2fIaXiaJLy/eMJy8by8fmGD4/G3JllbDpLCIG39woSpXi+ahEisGkdWsB1ZfngOOOqjklhj68bFgUs24F+cOyNEg4nCUEkbFrL44sKLSWrpqdIDceTjDuznMQoNnXPp5c18yJlWkQvWOc8b+2XTPLIfq96x1t7I35yf4qQAoFgmhvuzQtWTQyXKVPF82XLb84v2LQDD+Y5zqf8+YMZq2bgfNvy0ckmegHJHusDF9uWxShl2/UEAvrL0fQ7lv3jdf2FHvz5KgI5qdFcrFtSrRDCIwQ8XzUEH8gSdTsQj0PYCDp9oR+XL9eXzCjuz3I+u6x4tF/gQwSmnl413J1mENgpDeRrJV7/GgbTX3cuePW5/I6h9PbB6NZu43c5K3z5bDArDMt6+JM3x/5d6w2A9EdWN+wjs6OPChGN68aZIdOKZTuggHtzzWVlad2O7g+0AAMo4RnlisQ5ikzjfKBzgUUpSZTkfBMTSTZdR2k0y7rnx/dnHI1TOhfwLpBJeHe/jAljTdTvLjcDD/YKOut5OC94ixgZ31rHxTaCEJM8oxsanl7V2BBT01Kj+OyiwnoY54of3JlQ9T2fXtQMfWRG3ZnFlK9ECR7sFzH1pre0NhpDCyF4vmzodr/wD2YFiVHsjTI+vBclbN0ujebTc0czOIbBcX9Rsqws0yJKsvbLhD547k5jlPC2HVg1lpNlQ5Ea3jko+fhkS78DWIpE8flVdfvzmeWGH9wd8/FZxTQEnlw37JUpqVHcnxVcbgfu3s0pMsPZquY35xWfnG0xSvLv3przZ/fnX1hsbxbGV7XLNwlqIcjbBf+3LWguRInfo/0RR2PLZd1Td47Oee7PC9Tue24iQLWSNIPjfNuRG0WZRq1x2zvuz4svaKxfT+2Mx7mzTUeiJUfTlJ8/W/PkuuF4mvHj+zPgq2bhX6cp/rrkgy8npf22eh1YdDOlubmHs03HvVnO6aZlsXtf7BWRkXUwTpjmye09DC58wbTvTb2pN/VPq4QI0HxTGeKhJfIwIc9eCsYkL2VoEJsbo0BLgVEK1ds4NNnpyoyMZti5Bm3j9/W7a3fAugdN9IVwLn7fNAG7M4tNtIzAsYpAUd7HgY3YXaMwkBvF/shwUfXU3QAB5uWYVdvS95Zm6BFBkEjFdJyyqjuWjWOwkbGUao3z0WB21Vl659i2gkEphuBQKvDiuieIyEBWCrbNwN4oypxmqeZwlLBpYhJQbgzTicas2pjOZh3OB5xzPD5vscQDRz94Tq8r7s0yhEwZpZrBOZo+3pMPnk3vudxsmRYpDxc5y8bR9oEHi5J7U0EXPJvGke5Shc7XLVJF9pUQkGpF8MRD2SihaaKv0k8eTPFI9keGq63CE1gUCevKMskVm2Zgnmt++XzFD+7P+C+PV2QmyqPfWuT8+nTNVTXwYtkipeTZqmFRpFgbuKp6zjfdLrFV0Q5xei4QBC8QxL3suooef4nS1J1j07UUiSQzmrcLRZklJEqxN0q4rgdmheJ807IoM0a5omktT65qehc9Rpz1nK0H9icJ7xyMqDtH1cZ9R8gYSFKmms46jsYJo1yzN0pgOzAtNMZIPj7b4gL8xYMZZWrehDe8qd9LJSKG8lR9XHPbAfZGmoDDO83lpo+SYB+TCDc7tseiMBgB51VHohQP95JdAI3HoNgbp0zKlM5a6tZxME453wzMi5RJHlOX100PQmC9Z5Ibut6ipGRvZPjH5ysSJcgTyaLMbwNhfnxnilCCPy8TVm1k+P961TItEgKxZ9/UA5vOcW9qGGUluZEcTbIYjNMMPF+17JUJ++OMPFGcrKMaQBH95QCMiqP/X51uSYxGS8EP7mjGqWG6A5meXgfKVDE4w94oJYTAshnIE82dccYnFxvuTDN6F24ZLttuwAdouijPfb5ub4GMmz52b5R8pQcXvSMQvVndLuE4MqDg6VWNC4FZkbA/SslMDEt6vmrIjfrGfjyIeDZJdoE/D/dKNs3A0TRK4149Q7xOafDPHfh+m/pa5cI/0fNoWQ/cn+VvEjB39QZA+iOrQPQ7Ch7mpSAIMEJyMM64M8t4er1hXcvIGHGWRMSEBLNzEfUBcgPjLCGRbpfsFRfaTTvs0qsCqYmysk03YLvAk+t653uj0VrcamovK8u7ByO2/cDxJONi2yOFYN1aFqVhmhm+Px+zrOMirIXge3cn3JnlDDbw5LrCqKjx3Rsl/PzZOsb79i5O5pqBbdfhvWOvzKLnkYrof5EarOtxO4NJKQTXdUzL+bvH19ydF9Fo2Ufzt4mWXNY9ZRoldyLRFJkm1S0BwdNlzVv7OR/OJ3x0sgERJ7h3ZtEYMzWSj89a3torUFrinOcXLza0gwUhohleYri7yHYytsDByJFqxYO9gnGWYDYtz9cthwT+02fX3JmlzPOMqht4fNnw5/fmr/25SyluDafr3SZ4d5pTpPoLKQs3jKAvL5g3dE7vA2VmMFrSDZ5HixKt5W105qv0TMIupnW3ISRaxeQELXkdVfTL1E5gt8FJ1o3lrb2CdvAcT1OW9UBu1O+kKf46ltK3YS/B6zeEmylNnnzREFuq+HrnO6BMCsGmjSaqfnd/byisb+pNfbu6GYB8mS10A7r8NhDJ8dJEW0gI3jMvFBpHO0CeCao2RENps2Pr6pi4OYSXfkgmFZQKKhtQAaTZpaUNLxm79RDvx+zYvYboA+d9wDsYpZJRolgLzdb1mKjiot99fzQZDZzXPRqJ8HFd2VQNZ5sBqcDf+BQB3nsmRYL1HT5AIiXeQ9cPKAmXmxajDVVvwQg+OdtwMEkJwDRTLBuHEIJtbznZ9Iy0IjUKIQVpopgWhkWRkchAbwMIxaZzCCWYJgnrtidVkkxKikJxsmpZdgF7WdHbwCwzGCORIrCsLUYF6iHwIJVM8gQ1WB5fO07XNaPUcG+aU+aGxnqCD/zmbIN3nnmuGOUJy+1AMJpxpsmVZusGEiFY1gOtjemi/7N39/ivz9eMc8VAReIl13WPVJLH1y1XjWO/0Nw7GOGd5798fsUoM4xTQ5YoXixb7sxSNk1MUS2TKJlXAjobuDvLKDLDk4stm3Zg8J6DScpVZakGy8P9EiXhVy/WPL8eeP94xP4oZ9NbVnXH/jjhziwmCJ2tOt45HNH3HikFhVYURqJUQdtbvAdtFJlRFIlmmhukgHEeJd5GSere8XC/RBCTnvJE4Xf+VkII5rlm1UbvvTceHG/qX7NS4nrmiWvzjYdcE6DvX4L4AjjbDowTxQ+Oc5JEkWrJ58uaD4/HXG2HXZpkPGdIISjSGD2/bGLozGKkaAfLsIm+NYkSnC17ykzhnOeq6jBKsj+K6ZKzPOFgnHK2gZN1y/444dFBiR08Rksutz29dQwO9iYp69ZSppo81eyXCftlBI+WtaUdfPQpmmZM8gQponRZK8nhKKVxjt46qsFjnWecJYQQgadFkfDR2Yaqjf17ZhT1EEMZNm3PXmmY5DV3ZjlKitu0ZqPkDrRx0Y7EebrgUUKSGMW27dl0llXd86N7Ex7sFSzylCzV9IPjZ89WvLVXkGuNdZ7zTRdVKa/04ErFAfPJuqUbPN6HCPKsWxIdA2aCD1xsOw7H6Vf6/a9bX76SsOYDiVZkWv3OEq/f1WD62/b4r6t/qpn113keBcHvNKz+LtQbAOmPsNzuo+4Ck1IzKzKsd1jr0UGTKEEzDCQmNs0yKtGQxKjg+SjfdfCC81XLwTjhzqyIRtRKsR8kQwgxiW3dkBrF4ytLpiP1uvHxOk1vKVNDM0SG0TjVnK4bFmXKdT1wf5aBjAkskyyJUY87c8yqc3TWIaWkSHSMCtaao0lO1Q0UqWaUGA7GKW0fSKTnum55voqL11nvmeQKLRU/uDvhoxcbVk2PloIf3h3zi+crhBQ82is5nKRYH+OI50VCYeKm9NHpdpdsMKMbLE8uGzKpWDYDi8JQpBpFg5SCZ9cNXR8Xs3uznGyXOrBuBx7tFfgQ+NnTJb8539K6MeNUo2RMVtv2/pYmOs4Nk1ST6Jj6Yi1cbDvmZULVdzTOkfD6BTIzisNxyvOdkfbzZcPdWb6LIo0L5M2Ca30EgG4ffw119P6iuJVeve7xu7Ocs12q3DdtCF9HSzU7qVpnXVyIpSQxkizRNH3kCfy2Defrkg/u78C0r2MvvQ5Ee92GcDOl+fI9JDKCsF+4R/m7M77e1Jv6rlVC9AVqX/EBupF03VTg9RLtQEw3u5F+udd8zc3XKSBPIgjgQmy+EXGP8y6QqSgxswGkioEQ141DiQgceaJ8+M48Y9N61m3HxcYz8PJAdHPvoyz+X9oetCGmcdmBde2xwXO6akgShWxBqmiwrVwMqLg7T6PMwsdUN6EVSgo2g6W3oAJ47bnedKRGIgM4H/AicHdasKp72iGQJBIPXFcDaQJGxrTT3nnaIbJgtU5AtAzW4VzA9p6r3vPOQcI017x7MEKLaDq7bjsmmSEzigMZ94y+t7TDzSEvgkqCgB0GagkaQe8dbW1ZtTFuzgWJEpa/e7pm2TimI8M0icOczCh+9mLNg3nBYB3TIkErSTUEhuDZNnG4gI9T3U/O11xuOyaZ5u+fLHm4X/D2/ojOehIlmI8SDkvN3z1eUqaKplMYFVhXHQ/mCf/4ZEkmBas2SuBfbFrmRcKLVUvvAs+XLYtRQgiCP3tgMErFPf+64bOLmjJVBAK99Xx6WUfj2mnGO4cTButuQxrePiw5X/ecvujYNB34wOU2pqhlCTy5rOIhVEoSI7juHH92f0I7BC43Hc+ua6z1TIqUw3GOC7BqevbLlEA05j7Y+Q/+6myL9LA/SZmVGi1jD9XvDoOe8GaA8ab+xSslsjLdLiCg3QHvgZcBATHGJpbRN0lshiLTu549Mvy1krgAZSIpjObevZyzVcums3gfeDAv2LYDnY3gTELs2avekyWSd/ZHNNbxYtVyZ5bx4fGY//TZFW3vSYzke7tktbcXI5SU/OOTFZd1T29j4EEIgYuqI3ggBK6bgX6IKYY/uT/D7Ianz5cN59voqeRDIIRAM1j+5sk1zkfm4jv7JdYH6r6nHTwhC/zidIMhpoG9czDixbpjkhsutz2PDkaMM4MQ3PasN8CD9Z5tG7De4zOFUZJcKYyUdH0EwUZotIqpaOM0IdsZhotXgCh4yfjfH6dcbvsv9KaZUTzaKzkYp1xsOgbr6W3g4V4BwPmmY9tappn5Z/f7Wn818fhwnP6T/dq+berZv3R93WD8zXr7st4ASH9E9eXGunUw8h5J4K15TlGkvHc04h+ebth0inaoEAS0BK1icy/kDp3WilwqXC8428mUzC7d43CSsW57ztYdo8wgQkTkf31eM9/0jHLDtDA8Wzasuy3v7hekWlG1cVF//84IIwXzUcpgY0xllsSN5dl1w8UmLrJKJCyrNY+vKv6bR4uoMS0TJoXm/rRgb5TybNnSD447s5xl1XNV9WRG471nGCR/+e6MItWspgNSBKZ5Sm8d+9OcgzLhaJKRmmiadm+XyqV2TBylJMu6px8cF5shpjiMU6yNC5WWgvNtz9m6xWjJ4SQlUZKzdUuRRuQ/EDeb823PpvcUmSY3muerlkmm+dG9Kb94seHxRcX9RcFeGZvAurMkOianJYng+XVDkSpy9c0MmrNNhxSwaiz94DlZx9S1ItW3C673ntVuo3z18dfROV8FWl73+LEUv5Ne+euoosfTjBfLhm6IsdLH0/yW7WTUVzecL1//66YAvfe3n/c+Tq2ci41BP/jXTi1etyHcTGm+DAq9bjO8uc6XGV9v6k29qZtDBGz6+Pdl88W0s2+qG+Dm64CjmyqAaQmJFlxVAWdho0IcjiioWiiy+LUaYMeSsT425XkqsBZEkDgvGOeS0x149CorKmfnnXNjFEv8+/PrjiAgUXC9sWRGYn2UnHm/Y/uK6Jf0YtXhgLGGoGGWKgKSVRWDEZyDegh0FmTwjBZx77CD52rb0Qw2sj2FIFPRCHbbB3ItaR0kk4x+cExSw+AGMg2XW0+aaoIUBBc433YcTXKOU8Xjqw0n6y1VO3BvUbIoNc3g0MKjEsUo13jn8AK6to/xzuN46AkIUh3IE03VWc7qjlQIOueoWvicLXutprXR9HtepJRJjK2fFIa/e7IkNYoSqHtB0zve3S+5bAf63nG+Y+A0NtD2lp89XfOb0y2r1jIrDJ+db2msZ9M5QhB0oeOdxZjny4p/fLLCelAy0NvI1Eq0puoGRolg03QMzqJlhlaSF9cNRWb43vGYZdVx4hxyCAxDIDeSTEvePijZ1JZhsAwuMB9FGR8Cni9rLjc97eD47HqNHzw/fjBjcIHPLmr2R5Y81dyZpFy1lqtNj9FREnN3mnJ3UbJtLUGCt44QQGuBEJJRZni6bNh2lkRFqtTlNloK/OTBHB9i0mozOLSUbwYYb+pfrG7eRaMEhIKDwrDtHdebCNDLEEH79pUJgCKCSpkR+CD51WkFQtK0PV4IuiGACFxtB8pUMckMd6c5k1zz6fmWv/7sit4FZkXGqh7Y9gOT3JCl8UmeXzf84O4YKRXH0xQb4Id3JlzVfWTK7Iakeap5a1Hy4rqBKmCtZ1Eotr3jYtNR9w5CoEw1qdEcFlFW/HBRII3g3qLAhsDZOu5Ye6XhZB0B7SzRJErym4uKH92ZIHJN01mum4FVM+y8PKMNRtW7nVzWkxuFUpJUR6ZREDERbNMN/Op0w7PrJjIltWJ+NyFJFN+7M+Zk3ZIaSZEqvne0QCv5hSFn8NH36EYFcgNslImmXOjXBs2MM0OZaAbnMUqib7xMxyldYW6VCP/cfv/Vzw/Wf9VP6Vuwh37fqWf/Gn5Nf2r1rw4gCSH+t8D/mbjW/N9CCP+nLz0udo//74kJ9f/HEMLf/mvf1x9bfRk8SonNaiIlDw4K/vKtfc6rjt56yjSmQhVGc75uaKwjNxqjJD4E6s5xr0woM8mzq5bWCVKlyLWkc4F7hUZrOF11IBRaefbTFITH7JICRsFENL6NXgM/vDfjxbomdPDpWcX370zprONwlOECVF3UKv/5gxnzq3qX5hUQIvA3ny15sWrJEslPH8652PScVy3r1jIMjsNJxl5hOF13TEvDnWmOtZ7G+ttYzPvzgrNNR9VZtBbs5QlKRprmzQL75USBe/OCq2qg7eM092gaNc+JUcxLw8mqo0iiY/k001xuez68O+Z83bNpBpwPzHPDk6uGi6qNyWuzjERLIuFJkieaHz+Y8dlFxTjTSCkpU8XT64aHi5KfPV9TJgKE5N9//5Ak+foF1oV4ELrZtMa5Yd30PF81vLM/+q2PSym+QOf8OnroP1Wv/DqqaGYUb+2V7I/T2yjNELhdiDP5zdf/uilAIuPBatsOXNcDvY3pcEeTjIuq/9qpxbcBhb4p+e2NZOBftt7sE3/8VQWo1pGJdOMj9LvW1zGTvvIcQFWBJmCJz9U1UarWe5ikcWqeyAhgbVqPoIuHdAGJMtTtANLh1hYpoxzjy5K6BshC9HtwYZcC5+PzB8AMMOBIcDHOWr9MTw0ufr/pIUmjFGnobDRd9g6loveSCLAj4dBATE5F0gw9lbUEL+gGkDg6B5KBzgkyrTicZEzzlMeXFVp4sIrJxFB1lkJLrrcdBztZAsLzD0/XAHSDo+oH/ubzC8ZZEmXEAD5ghEQYQe8DQoAdYFlHNvA80zy9rFmMDM3gd/svtDvvqFA5+t0h6a39AonHecn5ukXg+c3ZlnmhaVpH8AGtBVlhWAjBk7bBqEBjPbYbuNp0OB8HDpPSoHeSgW07cG+axaAL6/n0YkU/BDrrQCjKVHJYptSd43TdMskMZZLQbHsSY2B38Djf9rybG1ZVz0cnW55eNThgXpgo5egdXe8QAla7RKPe+egpVWjO1z3LpmN/lDJ4Ry3g+bqiNJpCwzzTFEk0NT8oE66rnm1vcR4+PJ5EA3QtOb1uaJ3jz+/O8BKmmaGznqobSJXi0UFJCJGhPEn1bVDHTx/OMVp+5wYYb/aIf926YXci4WicopWis4E89VRdVB0oAbmI4QOdg2JHGb03KyjzJMoyCaw7y7sHY/xObVA1A3emE1ITbSQuqp5VExOPD6YZkyL6f11VluumY5KmEcE3nlXnOBjrW+b6g72S/BUw5M5uMGy05K29kjvznP/6dMl2cPTtwMEkYdNYWusYZ4b9MiFPIxB+A0ZkRvH+4ZhHeyUQWa3n254s0fgd8DQrDMfzGKbz159fM0o1TerxznO6thyMExZlQmsdgw+MUsXRJLvtr5UQUUZrNO8elHz/zjhaIYTIcJpkhr0y5ScPZ4gQIuMoRJ/NLw85f3RvyrIeXpsm9nW9qZSCVCru7Nj7t0qE+Uslwj+337/5PB6efclb9Nuyh/4QGEDf1q/pu1b/qgCSEEIB/xfgfw08Bf6zEOL/HkL4+Stf9r8D3t99/HfA/3X353euFklsfrc2ovo3DbJRsdEcdl2u1jBOiJKvWc5enrE/SdFa8mLVsj9K+Oy6xnligtg8p9Cxwy2zhOeXWxZlwvE0I9Ga8+3AT+5NUEqyaTqmRYL1kGtNNzgum56qcUwSjQ1gtGJWGPJEY7Tl/aMR7x+NGJxjXmRoCdY5Lreev3y4R5G+RMUhGn7PcnPLGvmzB1PuTjOMVnFSgEALyf4o5Xrb0Q4eH2CUaryHi22Pc55m8LSDIzWKItX89OGc58sm0uvTKOhtBvda5Nj7wLIeeLQfqZxPr2uuqp5xZvAhJqvdmWakiWKcGpQSWBfItbpNLTtZt7x7OOZi2+HxONczyeMm551nUUafAikCb+2V3JvlKCF4fF2TaME4y9kbJ6zrgfuzgnuz4hvfH0oICNAPUQpndw2lCLx8fb/h8VcX+29DD/3nAiavTkBetxB/0/W/iS57OE7528fXKCFIjWKeG042LfBVT6NXG4VvAwq9AYv+9evNPvGnVb/NCPtfom5kcTfPtfPs35mGQuMjgCXCS9nFEGDdDtR9PAyt2shc+jrWkwVcHx//MsB0k9rWEwEj4eI1jY5SN9VDmsL+KKG1nm3rmJYJ3gWqTrKqI5PJ+Xgok8DFusO6NrKTAkwyQ927mKbaOWwfPQvPvCdNJJJhJ3aWHC8SUm1oned02SJ3/lCDk3xyUrPuBhIpWLWOqhtoetDaoZVilEiWbY8Tnm1r///s/Xm0bEl+14d+ImKPOZ08wz13Hmrorq5udaslFZKQALcQBjQYARYGCxskez0sM8sLg957BmRYYGFYPJBlEEJLFrIxwmIwQi2EhDUi0ZK6eqiuHqq6hjsPZ8pxz7Ej3h+R59apW/ece6vqzjc+a+U6mTv3jh2x82T8Mr77N4Ar0EknksyKGt22TPKatm0ZF4p+ItmYO/Fo93Mw1l2neQkXxjmbU82x5YTlbszrGxmXxznaJAy7AaPMuuIXtQtnb9qGcdHSiwLyxjAtKrIakgAqA5EUNMZVNH3q8IDPXJ6QFwZLAyogDBT9JCRQgvOTghODEFREErhqd2kkieKQYTek0QZjDFml2ZzVdKOAOFJMsoqtzHJ4EBMqyazSdKKQOFAkkcsX+IUrE85uZ5hFeH+jDVtZxXIvojGSUa4pWtiY13QTg8BybLlL3cKpXsI0rzi/kzHohnzg2BInhikvXZ3SYpkVLWVj6YaSOAyczWpd4ts4kBxf7XB6tfumm2CPE95G3F12xe/OIrHR9rwibyCNXIqJRmu0hSQGgUAby3ovYqUfEknJseUOSah4ar2/KDYS040Cpk3LWjdmuRPy5KEer2zMGaYRS52QtW6fz1+eMS0a4iAgDuTid6sgiRWBkC6stDGsdqLrnuvdKKC7+tbfkrvPx7OaOFLktUEpePXanLVBglIuef9WVnNYireIEbsCy25bSorFXGQoqpbGGBRvnE8IwUo3YmNW0QklIHnmcJ9ASZZSN3ffeMO0WXjJx6ETmQHyWqMX20MlObHccb93G3PgTc5BEr4jYeNWosid+M17J7yHHhQPIL8G2J+77YH0lcAr1trXAIQQPwZ8C7B30v8W4EettRb4mBBiKIQ4aq29cpf79kAxDGCtH2OsQeWN+1Eq3B3QbhSwlEryBiqt0a2ln0T005CvOL3C17z3EKtd57c/fWmDjQkMo4ATR3oYo7k6rVjpJcSh5NRqhwu9ECkkVWuwwDNHOnzg5JBACbKy5en1DttZgzGWf//K9qKHNV96apnNWU2lDUkgWUoCjg+X6SahU/fTiGhRTv5IP2GQhsSRessXcHdScF4jgg8eHzItNcZaysawPojdtTCW48spF7ZzlrsRZWvYnjnXVSEE64PouugjpaATuzjkvWLVfpPk7gSXBu4rcGzY4fx2zqxsiAJ1PR5YScGRYcqVcUHTWtqFy6ySAgv0kpBOFLDWi3ltc349RO7k6gpp4MSk3XxCcahcvg7gyFLK1rzCWkEUBBy7DWX+eiLtacm0qIkCxXInRMk37kYe9P7Nxn8v3UPf6US8n8ELF2FmexNdz4vmpjmNbvyh4A3CA4W3E553jQKaxolJFvfjJg3dtnbxWmvoJlCWLim2VC5nUbFoQ/DGj6JAuX3q1olR+3lIhcqFuUUBDDsBjTZYDL1IsT5ImRQNSdBweiVFG0lW1tSmpak0WioUhllt0a1FSIkUBmtwlTGl62snkSQBRCrALCqFZZXm9FqXYScCIdiaVzx9qE9eWQJhCZSknwYun1slyGtLVTcEShEGhkEckipXRShSCmkFpbSUTUsYwLHl1AlKQjDsBoQqJata8tqJTJI3QlgMLmyvl8Agcp4021nN8eWUuhU8vd4jCCV5oYlDRZoEzCuDMS2dOEYpjdYW20JeQxJCHAR0Quk8yxJJXhuSUHJymLATVYSEWOmuBxba1hIIQTeOENoySAKMgHC36psUqFDxwVPLDJKQn/v8NTphwCCJUEpSVA2hlPSTkH4ScGa5QxopvrAx59hSykrPeVPszEv6SUBjDJ0ooNWGWVPTSxRrvYS1fszWtOCJRQ6UTiwZ55r15ZTNSY1pYSdrWO9FBIEiUhIpW9rWoJKA1U5E21rypoUaltKIU8td4reZPPYRw9uIu0AqFt6QQNZCGrsbiq1tAUsvDbEtDDuWJFSs9BOwllmpOT7scHiYsN6PiANFGCqODlJaY8nrCCEtQwvdKGSQBpxa7hCGkk6oWOrEAHzwxBKvbeXOM1NKPvLMYZ5Y7zKIQqJIMS8ars0qN7+09kBPGykFa/2Yi6OCYRKxOa3oxCF507LaCbEIlJRklabqhJxY3v83dxBI3n90wM+/tAHWEoWKZ9f7bGU1J4Yp6/2YcVEjhGCYBpxaXuY9h/oIJW5ZzCZcJJ7Wi7WAtW6u3v2Ners3Od/N79i7/Rv4TnkPeQ+gB5u7LSAdBy7seX2Rt94RuNk+x4E3TfpCiD8G/DGAU6dO3fGO3mt2cz50lUswd2Q5ZdgJuTQqWR9IOkFI3TYUjeDkcko3DqitRVlDHCpWuxHDbsx//OwR0th588SB5CPPrNNPdwik5Phyh8P9mJeuzUgCl7wYC88eGZAqRWGcq/ZO1rhSm1rwzNE+Tx/qc2GUM8pqvu5961zczqh0SxIHHFlKkQKXEDmQrPYSPnhsiZ2iRlmJCgSHBy6My91d3T9+tllMLnHgfrRVuqXtRterhQVKkuDKRB4fphxf7vDpC+OF14xkfZC4EsR7RI+3TLL7TJI3TnCBFBxfTjm+SHS3N/+PsZbDA/fDsBsF143D3uN3774cHTgDt5ssb79qaMFC7KmbdpFk8Pa+itc9rSYFwoK6IQ/Crd7fb/wPeoK4mxk8JcRbEl3vl9PIG54HGm8nHgNi3E2R1uXUJMT9jST0E+dtslPuf7zkDc/cXXbtqGFRXjqCyLr8gIGAMBSEylLVrvQ0i4TQlbDEsfMASkMBtaVehL6FAfRD0NYlJ40VmNqd90ZPpFRAP3H5hmSgSKOQOLD0E0MrJGnkEqQOOgN6kaTUluXUhUlszSvGVUNgFa2tGXRiYiloWicQKaHoJdCamvVefD2PXWeRK2NWaJ46PKBqNAh3J7sTKT5wfIluGNCalnGpUQieTgNeuDyhag2JUgySwM33oQSh6IdgIkscBYznJZ0kJIkD1OIGw6m1DnnZugWQMGwo6ERgEZjWUrXQjQQrvYQ0VggrSWLJyeU+47xgKY1Y7UZszErSQGBxvx/CUDIvai6NSgIJo6JBW00ShoTK3aQxreHokhNzlBQoqTg26HBkkDCuWi6NC5aSgKzUHB/GNC0cH4aMy4blJMZYy4nlhCQKOTpM+IozK1ydFHQiRScMOLEi2J5LVC/k9FoKSFa7CU8d7nNhlNG2hiiQWAudJEC3McNu7NpIoBs6yxSpgDCUDNOQUEmePTbg8qikapw4uJSEVLVBSFeAZF4JDvcTnjzcp6xbdvKavGpZ68esLyUIuB5i0okf+3Sld8xGwKNtJxRuXTG9iWvlIHKefdKAigKshSSQzOuGuLUsd2OiIGCcVSRdeGLFCdRXxgXPHu1zfLXLzrymNYZhJyaNFKv9BLWoTpvVLcNuyJm1LkoIrs0qklBybNhBCuiEIYF0HvAATxzqc3K1y1LqcgGdWaRa2PXAicOA5053bztksxsFHF9OUQKOL6dcGue4VEHueyQFb6o+fBD9NORDx5cIFxXLAuXEJxem2yUcy+u/n48NU6IbBN6b/WaVUnB0mFK35nq+pfV+zLFFGN5Bxz5M3EnvoYf9WjzK3G2rdLNP/cYbebezD9baHwR+EOC55567nXQJ95QQF24mJHRC6HQCilIjpEJi0MYy6ER0I4mULinaai9hrRsz7EQkkWJp4Yb9haszpLTUleHIcoJEMexFdENJ0RoGiat89syRPp3EhaIBi8TPkhPLXY70Y/oLt8+n1/su6dpClDk2TImUvC5uGGMpdXs9FEhKwenVLpGSNK3h1HKHtb5LIF23hq15RbPICXB88eNmpRdzdClla1a50DTDgRPGrrvobml6Y52AcXw5vT6WvdXA4tD9ED+50nF3EwO1qJZwc5HqVuxXdWzvXb6D1O/9jr8xSdzNDMjucUabxXFvb2LtxMH1nEc3M6q3en+//j9sQsvbzWnkeWB5bOzEw0bIG+FaAU6kyRdXVfKGeLPfhVaL45IAVgcRnUiwOdMYWoZJynKquDqvscaSBoI0bBlnLcWikpsElgIXOjGvwAiINKhFUQjEG3mE1gYhzxzukdcWbdxd8o1piVGWtCdYigPmtav+OUgFSIE20AsFSQS90AkaUiqO9ROuZBUbkwIBpIGlaS3T6o1/xFhCr+NCjuJAstKNWO1EaOs8U5850ncLA+FCPs5tZ+R1y0rX5fNYH1RONGharo0lUsD6UoeycZXUVrqhs7ehIk2cJ2kaKU6tdDm92mOU16x0QiwRG9PChYGHihPLHTZnFWEQkcaa06sdLuwUPFE2dIKAULm8TKGEo4OE9x8bMMk1F8cledW4eDQBSkiOrUbMi5alOKRtnZdvGnYIA8WkaAhDRVk1tMbZ5FNrXQ4PYrZmNUIKurGgbCKWuiGRgqKJefpQh6cP9/j42RHGGAZJl+MrHV7byEhDSdvCWi8gayzdUHFkmPBNX3qM81slSx3FqeWSaa0JpGKgNabV9JOIlWMDTi93+PyVKQZc8vB+wriueWKlSxg4e95PIoSFZ44OeO3aHAMMkoBD/YRDvQ5PHe7SiUIQgkO9hCudirxyIt2RfkzVGJbSgMODhBPLHUZlxeakJokURwYxQggujwuWOzFPrfX51MURr1UZdWP48Mmh++0CHBukTpBc/L9EgQuVO7PaRUrh7debuWM2Ah5cO7EcwehtxAAL3Bwb4ubEEysxp5YTwjBka14wKxoq3TIpWpaSkCPDhF4c0Y8ClvsxRaWpteb8TomUgihQrPYjro4CN5/1Y8rG8vThPr/zQ8cYJBEsck3u/tbd9bpvrXU3VvfcQD25qt/IfSkEHzyxxLVpuUc8STi50nmLQPROvU6ue+FPShBwYrnL+44uMS/19T7srT58EEoIwkBdv2G99yZrGErOrHbfcQjZ3nxLj2pYqvceevQR1t69uVMI8ZuB77HW/q7F6/83gLX2f9qzzz8AfsFa+08Wr18CPnKQ2+lzzz1nP/7xj7+tvpz57o++/QHg7ppKYKkD60sRX3bqEEkkubpTEASueko3SYhDQS+NObpYhBsrGM8r0jikG0u6qVrc+XNJ1gQQCMm40qx1Y9JAsTqIGcQh86rh7NZ8oXwrDvVjksAJO8KCxhIg3uQuCVx3mbxZ9vu9gtHtfpFv5oJ50PZbvfd2zrNfO/slfn6nvJP+3onj3+157xQPSj/eDY/CGO4kQojnrbXP3e9+3C6Pgp24EwS8eQXU3PB+BKx2XS68SrtwLCkgCmGtn7Cc7pb5dfnxjvYDqsawlTfMc8O8aWhaQ61dQt+yWAgyyoV69dOA1grSOKBuDUWjrxcKWF/qIWyLUop+BPPScn5ccG1a0LYuqaoUgJTU2hAql+g+jV1Izpn1Ad1IEofK5bSx0DSa1roQgG4nJA4kL1+e8amLY7bmBYFQnFnr8v5jA7RuGecNQeBy48WB4mOvbrKTN0grOLPe49ljfU6udFnrOQ/EL16dsT0vOTJIeP/xJfKm5fMXJ3z64ggjFGXdsNqLWEkjVrshTxxeYlrWtK3L0VM2LXnZcG1eUyxCuboxlI0BIzBAJ1acGLqKZkq569aJ3B3306su7OjYkrsp8urmjIujgmnZkASScd5Qty151dKNAq5NcsrWOEEjCnnPkQFKwbxuuLRdMCk0y52Q9x4euJxyieLCjvO+EVKwnIaEgWSUNQzTACucsDYtNUXdUGtL0TRcGlf0Y8H6oMuXnx6ynMa8ujnj46/vcGGRn2+1F/HssSWWkois1pzdytwCSgqeOdwnbwy//uomW3lDq1s+cHyIkpKzW3NaIxASnj06YKUTOk9k5ebmYRLQiUPiUFE0Gt0YZCAYZQ2xgu3MVTb64sacUFiSOOSrn1rh6KDLIA3YmddUur1ebTRSijSRhEIShJJJrlESXt2YA5CEAU8f7vLUoT5KiDf9LhqkAee25lyZumSvRwYJp1a69BOXP2/XpozzmhcvTii1Zla1HF9OmOctVliSMGCtH9GLA16+OmM7q5FCcGYtpR9HhIHEWksSSmalXuREFNdzxNTtzSuG3gseJjtxt2wE3D87oXAVG/sJvPfokEO9kEgFlLpBSNicFFzeKUiigE6sWEoilBRcHueoQNHolk4Uspq65M5fcWaZr3pynShQnNuec36Uc24zRyqBtQYlpLtRLCWnVpzXz6F+DDjvuMuTklc25hgsSaAoG33dU/23vXedY8vvTAy48feZMfZ6Koe7JZ7c7JzvpO93er3h8TxsHGQn7raAFAAvA18PXAJ+A/g2a+1n9+zzTcCfxFVO+Crg+6y1X3lQu+9kwoebT/rPRvD0CTh2bJ33nxjyxOoSwkChWwadiE4Quhh7BEtx5DLj43KsaCypVFjB9YoAcejKitfGECCwi7nqxpCm3ediUenl7Yg0t8OjvKh+lMfm8bxbHqaFATwcdgIgAZaB9SU4vAxJ5BIz9wLF0aPLpEFMEIUs9yKENpQtNFrT64QMohgLFI1mGMd0U0VVu3wyoVIcG3ZQUjKZVyRJwFInZjaveGk0ocpbTq71OLbcRbQCFQjqpiVvNZGVqFASLW5OYCDTmkhJunGIsDCrG9rWJQYqaaG2iFDQNoaqbQl290VgsSgpCRDMmwatDf00Ig0CGmtoW0snChAWRmVFVtU02tBJQzoqYF436NaQRgFiYefS0JWnB64nClVCUGpXiTMOnHdpa1355axumBWu9PlSGhMFzqY2xt0BTgJnc/OiYVLXRFLSTyK3OJdv5JjIa40xljhU1+1yqVuqRlM0LbGUsNg/UQqzCG9ziZ3NdTtd6ZbGGpQRBItwpbo1LkG3cmG0SaCuHxcqF/Jwo13fXTjt3qUXFmrj2gkCiW0tWatR1o3RSFdlFVx4mrGWUEqCxd16K8C2Fo11VSkXXit7f1MA1xdru14CWhusgCRQ1+/EG2OpGuedtXuNd29Qgave1lp3nt3tdd0ybRpi6cLjlRAUtabQLb0gcOFxe84Lt/4dtFvwoa5btHC/r1Qo37IQ3N3vxjZ327Gt+w2216t6d5zvZDGrtbn+m04o8ZbzSynQ2rzJk3vvOA9axN6v3zMPk524WzYC7pydOAR89dNw7Ogaw34C2pAmKU+udVhJUrQxbh5B0E0jQiGpm5YoDjjUTVEI5lqTBopQSrJGu5ynxtIPQ4JAorGI1jKvNcFi7rFAJwxI4+Atc83udz2S8k3z2t45ZO//5+73PFnMuUXbkip1YHXgRx2/3vA8ztw3AWlx8m8E/g5OcP9ha+1fE0J8J4C19gcWpTe/H/jduNKb32GtPXA2f6cTvsfj8TzqPEwLg128nfB4PJ57x8NmJ+6GjQBvJzwej2c/DrITdz0zn7X2p4CfumHbD+x5boE/cbf74fF4PJ4HE28nPB6Px7Mf3kZ4PB7Pg8OtM4l5PB6Px+PxeDwej8fj8Xgea7yA5PF4PB6Px+PxeDwej8fjORAvIHk8Ho/H4/F4PB6Px+PxeA7EC0gej8fj8Xg8Ho/H4/F4PJ4D8QKSx+PxeDwej8fj8Xg8Ho/nQIQrXPBwIYTYBM69w8PXgK072J0HncdpvI/TWMGP91Hm3Yz1tLX20J3szMOItxNvi8dpvI/TWMGP91HG24l3ibcTt83jNFbw433UeZzGe1fsxEMpIL0bhBAft9Y+d7/7ca94nMb7OI0V/HgfZR6nsT6IPG7X/3Ea7+M0VvDjfZR5nMb6IPI4Xf/Haazgx/uo8ziN926N1YeweTwej8fj8Xg8Ho/H4/F4DsQLSB6Px+PxeDwej8fj8Xg8ngN5HAWkH7zfHbjHPE7jfZzGCn68jzKP01gfRB636/84jfdxGiv48T7KPE5jfRB5nK7/4zRW8ON91HmcxntXxvrY5UDyeDwej8fj8Xg8Ho/H4/G8PR5HDySPx+PxeDwej8fj8Xg8Hs/bwAtIHo/H4/F4PB6Px+PxeDyeA3lkBSQhxO8WQrwkhHhFCPHdN3lfCCG+b/H+C0KIL78f/bwT3MZY//BijC8IIX5VCPGl96Ofd4pbjXfPfr9JCNEKIb71XvbvTnM74xVCfEQI8SkhxGeFEL94r/t4p7iN/+UlIcS/FkJ8ejHW77gf/bxTCCF+WAixIYR4cZ/3H5l56kHE24k3ve/txEOMtxNvet/bCc8d4XGyEeDtxAH7eTvxkPE42Yn7YiOstY/cA1DAq8CTQAR8Gnj/Dft8I/BvAAF8NfBr97vfd3GsXwMsL55/w8M61tsd7579fg74KeBb73e/7/LnOwQ+B5xavF6/3/2+i2P9/wB/Y/H8ELADRPe77+9izL8N+HLgxX3efyTmqQfx4e2EtxPeTtz/vt+lsXo78QD0+2F/PE424m2M19uJB6Dvd/Hz9XbiAej/OxjvPbcRj6oH0lcCr1hrX7PW1sCPAd9ywz7fAvyodXwMGAohjt7rjt4BbjlWa+2vWmtHi5cfA07c4z7eSW7nswX4U8A/BzbuZefuArcz3m8D/oW19jyAtfZhHfPtjNUCfSGEAHq4CV/f227eOay1v4Qbw348KvPUg4i3E3vwduKhxtuJN+PtxMM5Tz1oPE42Aryd8HbC24mH0k7cDxvxqApIx4ELe15fXGx7u/s8DLzdcfzXOBXyYeWW4xVCHAd+H/AD97Bfd4vb+XzfCywLIX5BCPG8EOKP3LPe3VluZ6zfDzwLXAY+A/wZa625N927Lzwq89SDiLcT++PtxMOFtxNvxtuJh3OeetB4nGwEeDvh7YS3E4+qnbjj81Twrrrz4CJuss2+g30eBm57HEKIr8NN+L/lrvbo7nI74/07wF+w1rZOWH6ouZ3xBsBXAF8PpMB/EEJ8zFr78t3u3B3mdsb6u4BPAb8deAr4WSHEL1trp3e5b/eLR2WeehDxduJmO3o78TDi7cSb8Xbi4ZynHjQeJxsB3k6AtxPeTjyaduKOz1OPqoB0ETi55/UJnML4dvd5GLitcQghPgT8EPAN1trte9S3u8HtjPc54McWk/0a8I1CCG2t/b/vSQ/vLLf7v7xlrc2ATAjxS8CXAg/bhH87Y/0O4HutC+p9RQjxOvA+4NfvTRfvOY/KPPUg4u3EDXg74e3EQ4C3E2/lUZmnHjQeJxsB3k54O+HtxKNqJ+74PPWohrD9BvAeIcQTQogI+EPAT9ywz08Af2SRmfyrgYm19sq97ugd4JZjFUKcAv4F8F8+hCryjdxyvNbaJ6y1Z6y1Z4B/Bvzxh3Syh9v7X/5XwG8VQgRCiA7wVcDn73E/7wS3M9bzuDsjCCEOA88Ar93TXt5bHpV56kHE24k9eDvh7cRDgrcTb+VRmaceNB4nGwHeTng74e3Eo2on7vg89Uh6IFlrtRDiTwL/FpeJ/YettZ8VQnzn4v0fwGXT/0bgFSDHKZEPHbc51r8ErAJ/b6Gia2vtc/erz++G2xzvI8PtjNda+3khxE8DLwAG+CFr7U1LOT7I3OZn+1eBHxFCfAbnkvkXrLVb963T7xIhxD8BPgKsCSEuAn8ZCOHRmqceRLyd8HbiUcHbCW8neATmqQeNx8lGgLcTeDvh7cRDaifuh40QznPL4/F4PB6Px+PxeDwej8fjuTmPagibx+PxeDwej8fj8Xg8Ho/nDuEFJI/H4/F4PB6Px+PxeDwez4F4Acnj8Xg8Ho/H4/F4PB6Px3MgXkDyeDwej8fj8Xg8Ho/H4/EciBeQPB6Px+PxeDwej8fj8Xg8B+IFJI/H4/F4PB6Px+PxeDwez4F4AcmzL0KIPy2E+LwQYiSE+O773Z+7jRDi9+yOUwjxe4UQ779D7f4VIcTvOOD9HxFCfOudONeDhhDi24UQx+53Pzwez73nYbchQohfXfw9I4T4tjvU5nNCiO874P2PCCF+8k6c60FDCPFhIcQ33u9+eDyeR5+7bX/2rhn2ef/bhRDff6fP+yCwsFNfc7/74bl/BPe7A54Hmj8OfIO19vWbvSmECKy1+k6e8G60ebtYa38C+InFy98L/CTwuXfTphBCWWv/0rvs2l1BCCEAYa01d/E03w68CFy+i+fweDwPJvfchtwJFvN2a63d/YF8Bvg24P98l+0G1tqPAx9/l128K9yDz+PDwHPAT93Fc3g8Hg/cRfuzOHbvmuGBYteG3cVTfASYA796F8/heYDxHkiemyKE+AHgSeAnhBDftauiL7xl/rYQ4ueBvyGEeEoI8dNCiOeFEL8shHjfAW3+iBDiBxb7vSyE+ObF9m8XQvy4EOJfAz8jhFgRQvzfQogXhBAfE0J8aLHf9wgh/nchxM8JIb4ohPh/7Wn7vxdC/MbimP9xse3M4u7DPxRCfFYI8TNCiHTx3p8WQnxusf+P7enH9y9U9d8D/E0hxKcWY/zEnnO9Rwjx/AHjPCuE+EtCiH8P/IG9HkZCiO/dc96/dZNj/+pi/5t+N292vBDisBDiXwohPr14fM1i+38nhHhx8fizN1yTvwd8Ajh5s2t3wNj2a/PFPfv8ucVn9a24xcI/XlzH9KC2PR7Po8NdsiF/YDH3fFoI8UuLbUoI8Tf3zGH/zWL7PxV7vF0W5/1PD9j/I0KInxdC/J/AZxbb5ovDvxf4rYt57LsW/fzwnrZ/ZddO3aTP3yOE+EEhxM8APyr2eBgJIf6jRZufEkJ8UgjRv+HY37TY/uQ+bd/0eCHEnxdCfGZxnb53se3DwtnTFxb2Ynmx/ReEEH9dCPGLwJ8RQnyFEOIXF5/HvxVCHD3g8ziozecWz9eEs4kR8FeAP7jo7x/cr12Px+N5N9wl+3Pjsd++p9232KYbjv0mIcR/EEKs7dP2frbtby3m8heEEH9qsf3rF/P9Z4QQPyyEiBfbb1x7/M7FOT8h3Bqrd8DYDmpzbfH8ucXcfgb4TuC7FnP5b73V5+F5BLHW+od/3PQBnAXWcF4k37/Y9iM4zxy1eP3/AO9ZPP8q4OcOaO9HgJ/GCZfvAS4CyaL9i8DKYr//BfjLi+e/HfjU4vn3AJ8G0kW/LgDHgN8J/CAgFm3/JPDbcHeNNfDhxfH/F/BfLJ5fBuLF8+Hi743j/NY9ff/5Pe38deBP3eK6/fkbxv2twArwEs7rZ+95d9//n4F/sPv+Tdrd7/h/CvzZxXMFLAFfgVsEdYEe8FngyxbXxABfvdj/ptdun/Mf1OaLe/b7c8D3LJ7/AvDc/f5f9g//8I97/+DO25DPAMcXz4eLv38M+B8Wz2Ocd88TwO8D/tFie4SzF+kB+38EyIAn9pxvvvj7EeAn92z/o8DfWTx/L/DxA/r8PcDzQHpjW8C/Br528byH8wr/yOL6fM3iuFMHtH2z478Bd1e4s9i+a1dfAP6jxfO/sqf/vwD8vcXzcHHsocXrPwj88AHnP6jN5xbP14Czi+fX/w/8wz/8wz/u5uMu2J8bj93b7s1s07cD34+zRb8MLB/Q9s2O/2+Bfw4Ei9cruDXTBeC9i20/yhu//8+yWHssxv1LQHfx+i8Af2mfc9+qzbXF8+eAX1g8/x7gz93vz9g/7t/DeyB53gk/bq1tF2r21wA/LoT4FE782Pdu5YL/y1prrLVfBF4DdtX+n7XW7iye/xbgfwew1v4csCqEWFq896+stYW1dgsn6nwlTgT5ncAncV4178MJVACvW2s/tXj+PE7sAPfD9x8LIf4LnMh0K34I+A4hhML9qL5VKMM/vcm2KVACPySE+P1Avue9v4gzGv+NtW52fhvH/3bg7wNYF3YxwV3Df2mtzay1c+BfALt3Cc5Zaz+2eH7QtbuRg9r0eDye2+Wd2pBfAX5EOO9Ttdj2O4E/sjj+14BV3Bz2b4DfvriT+g3AL1lriwP2B/h1u0+4w439B75ZCBEC/xVuYXEQP7E4983G87eFEH8aN//v2qJnccL+f2KtPX9Auzc7/ncA/5u1Ngew1u4s7OfQWvuLi+P+Ee4myy679uoZ4EuAn11cn/8BOHGzE99Gmx6Px/Mg8m7WMD9ubx4adjPbBPB1OPHmm6y1owPavdnxvwP4gV27sFgjPYNb17y82Ge/ufyrgfcDv7IY2x8FTu9z7lu16fG8BZ8DyfNOyBZ/JTC21n74bRx7oziy+zrbs00ccNzNjhfA/2St/Qd731i4WVZ7NrW4O9AA34SbIH8P8BeFEB+4Rb//OfCXgZ8DnrfWbt9i/+zGDdZaLYT4SuDrgT8E/Emc+APwG8BXCCFW9ghpb+f4G7nZNbxZ32567d5mm5o3h8Mmt9GWx+N5fHlHNsRa+51CiK/Czd+fEi6MTOA8Qv/tjfsLIX4B+F040f+f7G6+2f5CiI9wk3l7n37kQoifBb4F+M9wd2YP4qbtWmu/VwjxUeAbgY+JN4otXMHNo1/GAfnj9jle8FY7eSt2+yeAz1prf/PbPP5G9toEbw88Hs+DxLtZw+w3l9/MNoG7Uf4kC0/V/Ro9wLbdOJcf9Nt+b/8E7sb8f36L/W/Vpp/LPTfFeyB53jHW2inwuhDiD4BLyiyE+NJbHPYHhBBSCPEUblJ96Sb7/BLwhxdtfgTYWpwL4FuEEIkQYhXn6v8bwL8F/qvd+F4hxHEhxPp+HRAuv9BJa+3PA38eGOLc//cyA67no7DWlovz/H3gf7vFGPc7bw9Ystb+FPBncQlFd/lpXJ6Nj4ob8mDcxvH/D87VdTdmeoC7hr9XCNERQnR5w4X2Rt7OtduvzWvAuhBidXG3/5v3HPOm6+jxeDy7vF0bIoR4ylr7a9YVJtgCTuLmsP924Q2EEOK9i/kJ4MeA78B5Su4KRgftvx83m8d+CPg+4Df2E/1vxWI8n7HW/g3c4mLXI3eMW0j89YUNfDvH/wxuTu8s9llZeKWO9uSq+C+BX7xJky8Bh4QQv3lxbLjfzZVbtHkWF/IMLjx7F28PPB7PA8E7XMPclH1sE8A54Pfj8t/te6N6n+N/BvhOIUSw2GcF+AJwRgjx9OLQ/ebyjwFfu7vf4nf7e/c5/UFtnuWNufw/3XOMn8sfc7yA5Hm3/GHgvxZCfBqXE+dbbrH/S7iJ6d8A37kQZm7ke4DnhBAv4ESVP7rnvV8HPoqbHP+qtfaytfZncCFl/0EI8Rngn3HwxKaA/2Ox7yeB/5+1dnzDPj8G/PeLpHJPLbb9Y9zdgJ+5xRj3ow/85GJcvwh81943rbU/DvxDXNK/myWc3u/4PwN83WI8zwMfsNZ+AhdW8eu4MI0fstZ+8sYG3861269Na22Dy3/xa7j48C/sOexHgB8QPom2x+O5OW/HhvxN4ZJ8vogTtD+NE3I+B3xisf0f8IZ39c/gPE3/nbW2Xmw7aP/9eAHQwiU4/S4Aa+3zuLDid3RDYcGfFYvEqUCBs4ss2r8G/CfA/7q4M31bx1trfxpXGejji9CFP7fY94/irt8LuJsPf+XGxhbX6FtxCWI/DXwKF+KxH/u1+bdwIt2v4nJx7PLzwPuFT6Lt8XgeDN7uGmY/bmabALDWvrQ4z4/vWU/czvE/BJwHXlj079sWa6bvWLT1GVxO0x+4sTFr7SYuB9M/WczPH+ONGxQ37ntQm/8j8HeFEL+Mi+LY5V8Dv0/4JNqPLbvJeD2eu44Q4kdwyUP/2Ts8/ntwSU3fUr3sXiCE+HM4D6C/eD/O7/F4PJ4HAyHEMVyy6PdZa8197o7H4/F4PB7PPcHnQPJ4bgMhxL8EnmL/nEMej8fjeQwQQvwR4K8B/50Xjzwej8fj8TxOeA8kzx1HCPH/Bf7ADZt/3Fr71+5Hf+4WC1HpiRs2/4WbJXN9kNq+jXOv4vIq3cjX30bycI/H43lXPIw2RAjxHbhw4r38irX2TzzIbd/m+f9X4Gtv2Px3rbXvJnzP4/F4Hjjupv2537btfq4tPI8WXkDyeDwej8fj8Xg8Ho/H4/EciE+i7fF4PB6Px+PxeDwej8fjORAvIHk8Ho/H4/F4PB6Px+PxeA7EC0gej8fj8Xg8Ho/H4/F4PJ4D8QKSx+PxeDwej8fj8Xg8Ho/nQLyA5PF4PB6Px+PxeDwej8fjORAvIHk8Ho/H4/F4PB6Px+PxeA7EC0gej8fj8Xg8Ho/H4/F4PJ4D8QKSx+PxeDwej8fj8Xg8Ho/nQLyA5PF4PB6Px+PxeDwej8fjORAvIHk8Ho/H4/F4PB6Px+PxeA7EC0gej8fj8Xg8Ho/H4/F4PJ4D8QKSx+PxeDwej8fj8Xg8Ho/nQLyA5PF4PB6Px+PxeDwej8fjORAvIHk8Ho/H4/F4PB6Px+PxeA7EC0gej8fj8Xg8Ho/H4/F4PJ4DCe53B94Ja2tr9syZM/e7Gx6Px/PA8fzzz29Zaw/d737cb7yd8Hg8npvj7YTD2wmPx+O5OQfZiYdSQDpz5gwf//jH73c3PB6P54FDCHHufvfhQcDbCY/H47k53k44vJ3weDyem3OQnfAhbB6Px+PxeDwej8fj8Xg8ngPxApLH4/F4PB6Px+PxeDwej+dAvIDk8Xg8Ho/H4/F4PB6Px+M5EC8geTwej8fj8Xg8Ho/H4/F4DsQLSB6Px+PxeDwej+eBRAjxw0KIDSHEi/u8L4QQ3yeEeEUI8YIQ4svvdR89Ho/nccELSB6Px+PxeDwej+dB5UeA333A+98AvGfx+GPA378HffJ4PJ7HkuBuNi6E+GHgm4ENa+2X3OR9Afxd4BuBHPh2a+0n7maf7hTGWFprUUIgpbjf3bnr3I3xvtM2b/e4m+33ds55p8a8tx1g3zYflv+pW43nxnEYY2lag9aG1lpCJYlDdcc+k7fzOe/2BUAJQWstAKGS+55ba0NtDJF0+zStwRiLlAIlBFaAsGAFbxpzUWnyWhMGkl4corVhWjfEShIFyu1Ta2Z1jTWWSCkaYfh3L73Oq+cqfsuHlvnmD7z3nX5MDw2Psp3weDyeu8HXfvdHuQQcB37le7/pfnfnrmOt/SUhxJkDdvkW4EettRb4mBBiKIQ4aq29cm966PF4HkYelrXXg8ZdFZBwdwy+H/jRfd7fe8fgq3B3DL7qLvfpXZNXmsuTAmFBKcmRpYRISVpr37KQ3MuNC9G7/Q97pwSasmm5Oikx1iKF4MhSQhKqmx63uzjfuyC/WT9ubHO9HxMG8pZ9vVlfdq/9Qe0fWUoAuDIuaFpDqCRHh+mbxrG3n3VruDopaVuDFXBsKaUTB2/a76DPenefRhs2ZhXaGKqmRQrhxJMbruN+1/h2xaebfQ67IkeonKPh3s9mt62bCR8HnSOvNJfHBQhojXXnABpjWOlEhKFke15fH0c3UVzZzrkwKbm0nVMby2o/4gNHBzxzZIlQSTZmFcZa2tYw6IQsJxFBIN8k9DStIWs0O1kNFqQUHB4kKCG4Ni1pWoMQ0I0VZaWZ1JqOClCB5NhSSqQk47Lm4k7GTtZQN5qyMUShIg4Va92IU6tdAgS1NSRKESrJZlbyuStT6ralqAzdSNBa2JhVCCvop5KVfkJVG4bdgAjJsBfx+lbO869vcW1aEQaStTRgXGoq3VI0hpU0YGdWc3aUMSo1VdmS11DsudY/9ukt/uHRS/yrP/N1+37Wjwg/wiNoJzwej+dO89Off4Xv/EcvXX99CTjz3R/l7GMgIt2C48CFPa8vLra9RUASQvwxnJcSp06duied83g8Dx63u769E9xNoerdOky8E+6qgPQg3zF4p14seaX5xPkRUkAUKIZJwGsbM6JQ0bSG7XnNcickDhTHhm+IDuO85sWLE6q2BQurvYhOFBAoybFh+hYR5EaR4u0u9N/pl+Jmws7GrCJUgkAp9EJYObXSedM/6axsuLCdOfFAwJFBwhOHegDX2xPAWj8mlpKL45x44Ykyy2s+fi7j6CBBCPGm67b3MxDWtbW3L+e2MqJAYuFNgtKVcYEQkIYKYy1XxgWlbhllNQIwWLKq4YnVHlI6wWgnq7GLczatIZCCUdFQ65ar45IPnnhD8Miqhs1pxXI3JAkUw17EchIRRYqyabk0yilqzXbWsNYNmVSaa+MSIQQfOrFE2xpe25jx9KE+Ugoujtz1SKPg+jXevfbGWqqmxVhLEiiUkqx1I6QSBAiEEtcFplnZcH4n4+q0ZGtesxQHHF6KkUIwzTVGwEonJAkDatOyOalYHyR044BeEjArNSyu5Xo/RuCEpkhKCt3ymYsTwNIuPvNRXpHXLS9fnVG3BgScWOrQSUOyvObljRlYyOuWJFB0k4Bz24LPXxzzwZNDjix1Ob2SUrQtv/7KNoU2LHVCTg5TEIKmtRSNJitbNuYVEsOZtS7WCl6PQ6SAQLr2P3F2m5c2MqZFzVIa8t7Dfd5/YokXLoyxGF7byNiY5vSiiEujObkxdKTk9KE+rbEIYchrEAJ6UUAvVVwdl0zLmu1Zzca8RhtDJxBURpBVDVq3DJKQXhpQNYZeophkGqUk2lhCIdicl4wqEEAvgFJDfctvouPTV3J+8rMvP9KeSA+ynfB4PJ4HhTPf/dF93/va7/7oY+GJdAA3+yFvb7INa+0PAj8I8Nxzz910H4/nYcF70NycW10XY+xb1pQ3rm9vt61bcSeFqhsdC2Zlw7VpiRLiulMLcNeFsbvtgXQr7ssdg7JpuTwu0K25LuDc7MLe6Gm03o+5PC5QQtBPQ/Kq4fNXZ2S15vgwQUqJAF7fzljpRFydlnz5qWUiJfnk+RHzUqOU4NxWhrli+dLTQ0IpmZcN/SS8LoIMOyHjvCGrGrZnNb1UkdfGCVOhYqUTMS31vl448IbQIqWkXoz3zGoXODiE6sYv0+WJ84lIoxCAQEkqrWlag7SCRhte35rzwsUJO1lBrBRL3YidrKZpWzpxSBoqtHHeP69tzVEIGmNJI0XbGkZFQ9W0COvavzot+fCJIXGkrnvwGGsxC4+euBuhF2LF1WnJ8WFCNwmv93+5E3JxVBAGTmhb78WUuuXcTgFYjHHXZ1rWrPVjlBRIBCdWUo4vd6grzYVpwVIcEYcKlOT18ZzqrCYMFKudkM9fmzGa18yqhrxs6aYBJ5Y7fO3Ta2xMS17ZmKFb2JyVCAknlrvMq5Y4Evzqq1tMy4ZaG15bn3NkKWFSaPpJyHovdkJl3XBx1NKNAxpteenqDIvl+HKHUMLz53bohJJJrnnySIc0CJiUFZ+7OGFWtiAE1sLrbcvsFc1KJ+LQIKWfSF7ZmHOkH7GR1ejG8NkrE55a7ZJry/HlhGPDDm1r+OWXN5iWmlobrLD0ooBJ3lA0LRvTkpeuTmlpqbXA6pYwUAhpyKuWo72Ac+Oa7VmJtoataUVrYLkXcmSYspJGXJ1UTMuGSV7xxWszokCRFRWfPr9N1bS858iAXhKyNa1Z6YWc38kpK8MLFyZ82ellhklIYy3zvOYLV8Z84dqceakZdEI2Jjnntud84uwmQijCQNG2LfPasDXPKWuwBlQAX9yccXTYZWdeo6QgwFJojTEtGkHTwKho6YSQ15CbN88T22UD48bNU7hfrGrxXO/ZzwJTzdvm//h3X3ykBaTbwN9Z9ng8jzUHiUfgPJEecy4CJ/e8PgFcvk998XjuCffSg+Zh4nauS7tYVwbKbd9d37bWIvfo0e/0Gh/k/LBXqHo73kM3RoFkdcMXrsxQUnB0kHB4kHBpJ0dIQagECuHW8gsN4E4KjPdbQLqndwx2Q3vObs6ZlA1CCOzCu+PJQ73r+UyUcGFbez2NljshlycF2hqkhLLRTEqNNi1JIIkDxeVJSRIqBIJOFJDXToBa78VszirWejFV07I5q6haw8lpzaGlmJevzfnyU0PSKKBoNC9cGLPWDXllMwMLr25XnF5OeWWzYilSfDJv+LKTQ/ppdFMvnNVehDaG1sBOXmMtVI2hGymmRUNrLXGg3hLC1VqLNgYlJbVuCZTEtpYWS920iy9XS9W0XBjl6NZwfidnZ14xKxqujmuUtExKjTWWSVFzernDqdUuo6IhVIJx3rDWCxhnDee2KgwSaBEIulHAqbUuO1nJ8+d2ODSI2Zk3HFsIRHXTcm4rYysrCZViVtRcHhUEUpCUmrVeTN22XBo3WGO4NtXszEo+UTV0k4BpoVnuxAgJWd2wnVUMU4WRIW3rvpSfvzzFAhvTkpMrXZ5a6/LqVoa1zuumFwec38m4MipIwoAvXJ1xtB8TyIhISf7tZ6+wM3f+JUoKNicV2hqeWu8zyVtevpKznVXEUhEowTirWOvHnFjuMc0bXt+cuzw72rLSDXhqvc/WrEJJMFZQ6YYXLs+JI8nZ7Zqyann+3BYIy+cuzmisxRgnjD5zeMCwE2Faw+s7GWv9iKqRWGt44dKEXhqQlS3XRgWXdnKeOd5H2ITLk5y6aXn52pRTax2y2nJllJNVNeOyQQpJpATjoqZqNJV2/x8W6EaSUaHZHMPVrKSqwRioW9AWylHDPGvo9yImRcWZQwNiJbk6KdjKal7bmFI1hlLD5bHzFtIY4lBhW+gnAbWxPH9uh34s0a1ge15Q1C3bWU2jodQVugVZGaqqIQgDhLDMa0tVGrI9AlDYwrzSjLIJRQ3xTTyEwsWkVLT7TE5756nd79I7maD2YWfzDjb2cOLvLHs8nseSX33tAt/2gy/c7248DPwE8CeFED+GC3GeeC9Vz6PCfiLDvfKgeZi43euihEAKcd2ZRLcGKd6I6Hg7bd3IXkcVcOvrNIqBNwtVdWNumm7lZoLVvGj4xPkRgRSEgWSc1Xzh6pRZ2aAEnN2Y8eT6YBHhJMkb426MK0EvCjjUj+kn4R27zvdbQLpndwx2FcSy0bx4ecrJlZROFJBVDZ+97HKczMqW1V5EEijyWl/3NNKtYZQ3JEqwkzVYYFzUFHVLJw5Y6UaESmKNJa80/TSkNe4f0Rq3hpFCULcto7zGYgkVICxXJy4nT2stl8YF87LhxcsTVjoRlW45utShmRu+uJkTKBC9hJ15xeVpwXuSECkFG7Pq+nh0a7i0k7Mxq9jJKuJQMeyE1Frzs5+/SqwkgXKCWN0anlrrXU8k3GgnRo3zGqUk/SgAIVjrh5zfztCtIYoUVW3pRBKL5aUrU6QSdOOAWV1TacOs0vTiiDBs2M5rRkWNsQJjWs7vFEyLmO15RdNahBDMipo0ConCgOUsYGvmQoW0MYwLjZDwZBygjeXazH2Rm9bw6oYT2Azw5KEes7zGWEDA1rzm2rSgbgyjec360AKSpm25NirJqoZawyjXKGlompZXNucsJSGnVjuYfszLV6dc3J6jpGCpE3J1XDDOC8rW0o0jDvUFAkGlDbo1KCV47eqMSanpxIpuHJLXLUXbsjUr2c4qPnVhxE5W0wkCDvViMt3yPgMfPDbk9Z2ci9sZR4cpaRTwqQtjNqYVFrgyLbHGYq1lsvgfCpSiqFs+c3HE5sx5+AQSlIJagzWWtX4MCPJa82oacXw5pTWW7WnJ9kwghEADs6rh46+NCIUL0dualozyhknesDOvmZQVW3mNQjjvJt2yMckR1gkuugUrYZobLNp54ghoFp/PLi0gGwiqmktjGBUjPn95zOY0Z15Zag1N6wScSyONlJpu4kI4w1BxadLSjSOkECQB5LVhc9IgFMz1npMs/ioLttW0zULAukFSaBZ/xwvFqLqJh1Dz1k33lCe8I42/s+zxeB47buV1tJe//W1P3sWe3H+EEP8E+AiwJoS4CPxl3P0drLU/APwUrtDCK7hiC99xf3rq8dxZ9vOAudseNHeKey1e3e51kdJdi6uTkkrr69dmbx9vt629GGPdWrqoEULQGkNRG3pRQBSq66KS1oZLkwIl3shNe3lcIIAokNcFqyvjgkEa8MnzI7azmn4c0kskL21MeW1rTl5pSm2IAkkUSgLV5VdeHi+WQpIjSzHbQnJ8mPK+o0t37DO43wLSPbljsFdBFEJhreHatODEULKT1QgBWeU8ibKqJVYuEXAaq+vK5LyqyCs4NkwYlxqhLNXY8MyRHkkYcGVc0EsDxrnzfrkwKkgl5I3mUDfmyUMdXt/MmJUNkZTUreGVaxmlNqwPQs5tZww7EVmtnYDVtHRCxaVxxrRo2JpWHB12ONwTxGHA1rTmiVWXKHl3UthNmrw5r1ntRYyLhqoxfO7ylDRUvLYx59hSShIZpkVNVrU0umU7a9DGkJUN21mDWYhf56uMI0sJrTV84vyYUEInDchyTd1awHJlUqKN4b2HBsyLlqzWhAPJsBO6UKZ+zGbesDkuyCrNas8JGjtZzVIaEASSp9Z7vLqZMS9rzo/g6kI0KRpD21p0azgxTLk0LogDxYlhwqcvjunFitV+Qt0YPvbaDr1I8p7DfZrWcHmU8/rWnF4coqQlkIqtaUnTBpzdytwXNpCc29H04pClJGJc1MzKmih0SnMcSpqmZWosr29nrPYT8gZGmaYxYFqDblu25i2rg4TzW3OwlsZYpoVmVja0rSFUgs1JySvXZujdimSB5eo8p2wswrY8e3yJJHQhh4NuwLVJjdaWFy6O0IsKXVIKplnF2Z2MSErSJGRcVBStQbegjRNANM4949xWSdZoji6lFHXL2c0Zl0Y5Hzo+AOmEu0negIQ4CDg+jPnU+R1GWUNr3MT5sdc32ZqVxIGibC1Z1tIYCAMnGtXWncsCsn3jucCJN3vFo13du7awk0FS15SLKmWT3L7F86cCMNDk7lhRtQgBwtbMGwgEGOvaa/YJDZtr0O8gbOxB4svee/x+d+F+4+8sezyex4q3Ix49ux7z+z/07F3szf3HWvuf3+J9C/yJe9Qdj+eecJAHzN30oLlTvFvx6p2IT7dzXXZJQsWplc6+53g7be3StIZr05JOpIhChTGSvKoodEtjXCoWBLyyOeczF8dO9JGS1W7EIAmIQ0UUyOtpWz53aczGrGRSaloLS0mDtZZL2xmjaclKP6FuajamBbOicdsLjRWQBAGtsXzpySU2ZhVPrRtieWfEw7sqID0odwx2FURt4PxOznZeszNvyMoWqQRHlxLn0bAIOwuURAhBP1JMSk1WabSxHOrF9DsR3SSktQmrnRglJK2xHB4kfKC/hDWWX35lk4vbGVndEgaC89s5Hzq5xHIvIg4kvSQkKxuklPSMCw37wpUpR5ZSLPDs0T6fuzJDYtme1xzqx4yzhl6kGBcNT6x1FomcNdaCsZaLo5woUPRj948xTCMODzQb04rVbkTROKEIC0eGKUrAa1szosAJD6Os4lde2aIbBZxc7XKoF3FlUsIALo0KkkAwKTTdNOD8KENKyXovYb0f8+rmnCvTnGE3ZLUXsZQEDNKASLkEz8NuQCfs8OpmjtYtm9OK7VmFkoK2aNGNoWkNnVBxZVIwLVuePtQjiRXTvGFjVjHKK8q6RQKXJiXTUjvvI2NIY0W3cdXNLo4KLo9yLo8L5pUmkJJp1XBtXiEtxJkkbzSrvYhQKa5NCiZ5w8rxkOU0ZJTXbM8a+qmrMJYkAYmFUrs8PkEAUSCwrWWU1zyx2mWU10yyisulppsERIFgY1oxL2qsFZxe7VBp5602qBVVI5kXGiss/Vix1I2ZZDWlNpRNw2vXMuZFw7wxRFKAdB5sWdXQTUMO9WOuTit0XjDOGlfdbyHe7NVKBDDNNUpUrPRCqtbSjQXnRwXvO9rnV17eptQtjRHUsuTFrCKNBLsZfLKqYXteMcosodKECgrjHHzaxYn2CkR7n0e8Ncao3bNPC+gGysYgMGj2D/vSi/ZqswglK1w7AojEwR5CD7l2BMCZlaX73YW7yoNiJzwej+d+80uvnOOP/NCLt73/3/62Jx958cjjeVw5yAMmXCRMvtMeNHeKdytevVPx6XY8i27cf79rIaUrKHR5UiDq9nqS6oOKWZVNy7VZSScMiEJJP3IOAMcHKUEguTx2qVd25hVZ1VLWmjgK2J6VxKHiUC8mDiUCwasbM75wZYYUhqKBQSzZmArKqubsVs64rLk8LcjKFiEF3UizOclIk5BhEnO4FzCvGoRw68g7yd2uwvZA3DHYVQovj3NmheZIPyFWEiFBIjjST5jV7kOUQiCApU7A5tx55igEX3JsiXndXlchTWtJo4Cjg+R6qXQpBUWlyQpNHLrXW1nN1nTCidWU96z1GRc1arsgrxqkBCkUaRhQNgZjDbOqZbUTstwJr4sqp9e6nFhOyarWJeQS8OyRPieHHTbmFadXOq5aWGO4VmsO9WKMtQw7EZdGBRKYFQ1HBhHWSvK6pdYty52ASdbQ7QRsZzVRoDBArRs+f6UkrzXbWUhrLbPShWFZLFnVAi2r3ZhuHHJsmLLaiwikIgmhqC15qckbw69+cYtjKx3ySjMraoJAUhqLklA0Lev9hGnZ8J5DXTpx4HJTYdmcV/R1yDgvGXYTBAJhYbUXMik1ZW3Iiopeori0k9MYS0hDrxMSRZJuopjVDZqWQAiuTAuO9xO0dV5a1yY17znU5dhShygULHcThp2QX365YCebYoD3HR5weCnltc0MgLxuOJKm9CNJEgjyRnNircMZ1XW5qjbnREI5kXKeEaiA1W7ISi9mc1aSVy07maasodJ6Ef4Yc2zYIQgEO5OKvNK8vDGl0hApwdOHB9i6pdLuf3Fr2rBdtHRDSYtEiYbCQCeEyR4lJcRVE2sNZEWNEhJra4pS8+yxHpU29BLJTm7IipqLmUFI6CWCQ72EogEwLKUh07KiXXg4tTjhxlWycxPIzUSahjcLSpK3CkqGNzyObjWt5TfZZoHqMchyE0SPdkLEB8VOeDwez/3k7XgdAZx9vKuueTyPPLfygLkbHjR3incjXr1b8elW1+V22U1abXB9Xu/HJKHaV9wyxrKd1dd1hXlVc3ar4cxqh2vzikP9GAvUCy8lYw3nRwWnV7qEgaKoNV+4WhEHkqvjgoujnNV+zLjUXBlV7OQV3ViRSkllWnRrqeqGojHEgSAOIsaFptACrQ3BIsVMJwo5vJRcD5W7E9zvELZ7gpSCQ/2Yl69OOLedE4eK1U7EIA0ZpC7PTydUbGcu9KsxllBKjg8Tl0jaWHbyhSdQ3lBpQ70oq355XCClYK0f040Cl4jaGorGEkioa0OhDS9dnnB8kBKHijCWrPbcP+HmrOLSuOT0akI3jtCm5AvX5jx7pE8SKg51Y4SFWCk264qmNSwlEUIILoxyWixrvYQ0dvmPskqz3I344rU5TWswFs4c6jDsRryyOWdrWtK2LRLLJNNktWG5iSjrlqU0ZGdacmlkKZuWJ9e6DDshnzo/AWsoW8M01yRK0osVtW45uZISKYGU8OzxAdNcc2VRCa1qDXVtqOrWfRmmFUeHKaESnFztsT2vWOuGjGYVpTZcujRlqRO6EMNJzutbLmb02LDDtVnFpXFGNwqZFDVpJDEmREnBpGxZ74W01uWZOr+dkxUarQ3XRiVSQl21DA/HlK0mbiWzonICooFQSkbziklZs9SJOBIqBqliVmqujUtODFOKJiQvG65NC9b6KetpShwG6MagtZsKx/OGi6MJs1IjbEA/DrC4Mu5NYyi1JqtqGm2IQkUaKGpr0brl7FZOGsLm3DCaa4pK00sDLm5lNMZQNprWuEnV0jKpnddW2Vi6oUCoACEa5vVC2JEgJVgL0wpkUIKQgOAz58ecHWVc3C4p6pZiUbq+bUFYS9EULmQOgVCWSEG2SIINTrh5u3mB9opJ+4lOnpvTuUPuph6Px+N5MPHikcfjuZHb8aa5lQfNrY6/sSz8ncpX9G7EqzvhOXXQdTmI3YJb87Lh05fGxEqRRIrlNGRjVnFCyX3FraZ1OXFPrHbYmJRcHmvWehFPHeqhJFzYzlBCsJO72+fzugVrmZaaQ92A17cy1voJcSCprYt0sRYmZcXmrAbbYiPFvG7YmNd0lKCxLqWIFBYrnGdaVjdU2jkRfPWTaxxbSjj9iFVhu2cICztZwzRvSKKWtnUZ0t9/dIl+CoeXEp5a6yGUYF40fGo7I42cmpjXmquTksNLCUeWEvpxwLVpSRhIoEG3houjguPLKeu9mLVewsVRSa0NTevKn+e14TOXJywlEa0xWOuSZVXaEAWuzHsoJb04YL2vOTZMmZSaKFL8xutbSClJQ0nTWla1Jm9aGm24Min50uOSMFRcnRRUjWFzVnN0KXZV3ZY1l8clrbWcWUnpRpLWWq7slKwtRVwelSBwiZ2jgJNrXawFoeBDJ4YoIVBygjGCYRIShYqjw5jDg5Sr04JpoUkCyazWXJvUCGtZ78Uo6bLIa2tdEutBjMByYjlme+5CAstFRTptLa9vZlyaFHRDSdFYpLRM8obfdGYVBJzfzrg2LTkygNVehAGW0pCsbjk9TAkjyU6mmZaatTQiKzVZrWlay0onopeGzJqG1ghC4SaVjWlJNwzoJ4pRUVPrlpVuRKQUVliODDtEi2TnF7cz5lXDuNCsdmOWuiGhgvNbOevDlHFWM680ZdOAtczqGinhqUOJK/PeWqJA0ksipkXDIFUMOzHdSLGdNRS1y5mklKCfBEyKiu2ZZpRX9KOANFJIKTEWRmW7EOWgEwcspwH9bkhWRJzbzsgrJyDp9o0k1uMcFIYyrAkkzJuGqrHM60WImHV/awOhhSQyxMoFomVVy66EYXDeROC8kfZzALoxnG1vbqObiUePgSPRO0IAw158v7vh8Xg8nrvA5y5v8o3f9+u3vf///IfO8J99+AN3sUcej+dB4t160xx0/F5PmqZ1eSLCQN5WyNit8hO93VCyve2aRQGq2xGfdvshLNeLQu1GBR3U15ttKxfVvi/s5Lx0bYq1hjOH+hxSMaOiYSkNqY15i7hV1g3jomZ7WnFpUpAEkrV+TNW2xKGiaDRfvJwxKzRLaQAWam3oRRKtQ6q64cqiqntrDK9cm/OFqxO2s4a8bmhaVzwqDiRl02BbQ1mBii2dJCAUmkkB48wVk7KtcyIotEEI+NzVKSdXunc0efpjISAZY7k8LVDS5f8ZlzXndzLWeilL3YDNWcnlUcGxYcpKJ+JzV6dM8oaibtnJKl6+MnUCRFHz+UsTEIIkUHzJiSXGuYstXO4qlICtrObLTy+zMS04u1Ww0lXU2tKNQ6QQBNKFeJ1Z7XJypcMkbxgXDbq1BAqODGKuTmB7IeiUjUugvdZP6fVCyqbl81emrHVjBmlErVvOj1yATxIqji+nXJu6ZFvdJCQM3D9LNwo4t+2Sds9KV9lslGmatmWSW44ME2a55vBSSt1onljv0QkD8rrh1GqHU6tdrowKJmVDGgUcX0k4PIg5udxlI6t4bWPO5XHOxqRgY1pTmZZESZY7Mcu9GNMapBRc2Ck5NEi4uO3c8kZ5gxQwbVq6UcCVcY5Fcqgf0E0iCt3ymcsTBlGElK6K2qSUTHLN6ZWUSdFQGwut4f3Hunzy7IhJ3dCNFNomzIoaKwT9jmSca5YSRd629BP3uYzzAo3gqfWUq6OK8cLTbDmNiCPJha2cWVkzLjTDboQ1llFR8eLlMU+u9si15bWNORdGOVdGBUop1roxSioa07qQPG0IQknTGpJQkZUNeW0QtuLIYMiRQcxnL08Y5w1KSfJaY4E0CsjrlqoVKG0xtiVrNN1A0LYKgaUFdoqGUdmykgas9hO6iSavFjmiWpfRaDdXUCxdhbZSWowFJZxnkcZNBrUBW0MlLL2hJC8bkgBCIai1pdDQiSCSoCRMSggFzNs3i0Z7qffZ7rk16yksJcn97obH4/F47jBf+t0fZfI29vdeRx7Pw807rUj2Tr1pbtWXXU8aKSQb0xIh4NRq9/p7+4WM3RjCtd6PCQN5fVy744yUvG3xyxhLVmu2Zq6QUtMaGm3eJGjdKP402rAxqyhqzdVpSWsscaBY78ecXuvuG24GvGVbpFx+op28olisScdFw+a0QgCDJGQpCQkQGGupm5YgkIwzJxq9umXJK0MvUVwcVYzymkBJ2tbyyXMjxvOKuoVO7Cq6n1hOSJOI9SDg3PacsnSVry+NMtI4YGNSkMaKqmnR2mKsoRtFbM5rysqtrWwFtdaEIcQhNLVb0ykFFkkSKBprGec1z5/b4eueOUwQ3JkwtsdCQGqtxbaWJApY6wWs1CFF1WKF5ddfHzFMQ2aVE1M+fV6zOgg5udrhwnbGZy+OkEpxZBhzbjOnagwnVxOiUPD5K1MO9SKEcF/rKHRl1Zc6Eb/nwyf4969ucW2aszGukMJiWksgJYOOK6seSIlUgq9+csUlE5aCQEqeOdrnC1dmi0RcFUudiDRUCGBWufxFUjq3wDBQlJWmxRKqECUEUaCoG+dGd3mUI6RFAGdWOry6Nef1acGr2wW9WIGFo4OYQ4OI9x/r01pIgg6jrGZjVrPaiXjmyBJFrRFSoFtY7iy8dKylGwdMtzLWehGfuTTBGENlLaEMmJYNlpoolNSt5On1HpuzmlAKjg5Tnl7v8uLlCXmhSSLF5qwEC3EgUFIwCAIujXN6oSIcSHqJQgrnQXRkKSbXBm2c0jwvWj59bkIcKnoWop5idnVGFLpQrJU0xhrL6jDh8xfH7OQNh3oJCMFOXtFcaXlirUc1q9jJ3ISx3AvRxrKRNVwe54RC0o0UpoJIujxQW9OCjWlBrV3oYqIkQlmWuiFNI3ju9AqttXz+0oS8Mk6NjtznU1o4u5UjFUxKDQgiZcgXk2LbGoSUxCH0OzGjeUlWakoFSkjiSDEvNUoKklASBlDlLaGS9NKQHdOAcdXKdhNQ60WJtLJ2XkrCvpHPyODEpl7ovF66YUAkDaIU1LrB4qqa5TUgodOBNHShbwFvFYqCPe163hmDbkQ3fCymaY/H43ls8CFrHs/jxbutSHanz7s3TKxZ3OQHJ84cFDJ2Y36iednwifMjjiwlBNJV4R7nzdsaZ9m4qKBLo4JQuTViHATU2nBsmL7Jo2h3PG1ruDItOTKImVeaeakJlGDYCdmaVyglODXscHGUE4eSNHCpXq6MCywQB5JAKeqm5eIo5/hSim7N9eJUhW4pm5btWcUkrzi23OWp9R6XpyWNNpzfzilqzfmdnG6omDea9V7M+Z0Ki+XyWHNqOUWFkvM7GWe3C5qmZl62GNvyyrWYpw/3sEagJMyKmqrRVNpiTU2t3eopDARBqFCmYXNeUzcuusTi1l1d5dZyUoIJXGoWa6GsDW3sUqCUteHapKTULT0vIN0+SgjCULGSRkwrzWZWIYQgCSShklybVix1QpoWjDDsZA39yOVHqo2lG8DmrGGUNxgLk9LwZCfk1a05RdWQhAHvOdxDayfaaG3oRAGnVzrkdYNdkkRKYgV89vIEKSUr3ZCqMQuvJMl6P+bEMKUbuY/k+LLGGEPTtmyMS67OchqbOI+QMKDSLQhB07QIBX0VInAeUMMk4OqsYieruDAqWO2GbFcNx5dTjLFszRvSQCAQzMqas7pl2IkYRhHnRgXPHO5zYqVDP1JszGuODRI25hXzqmWlG/OBYwM6ccBrG5nrB66cehIIWqsYJpaVbsSVsWG1F9GLAw4PY1Y7CYe6Ccs9J4i1xtCLFa9vzLkyqbGtwWAIpAIjUCHkecuZlR5nDnWptOGL16ZEkaQXhhwaRDy11mVS1kyymkAJ1gcJ21nDxiR3peQlTMsGsCz3YjqBdKXuW8NmVhCHIU3ZsNaN2Jk3hAIGvZBJ3nB+a85aLyXLKqwBFQmEhHFWYmzIK1cEWd3SGkEnVhgrqCrNyNQ8ud4l6oasDxIK3dLthGzlFVjBsWFKoiTzsmFat1wdFQRKcngpoahrkhC0tsSJJC8aRrmmE2q0taSRYDkNyWrLaN4QBNBLQ2wrKepFwrRI0lhLUixC2BZhbBYoKueJJAG7p4LZ7nQS4BJTl9oyDKCpJEno1PJau/0kkBnI5pBKp3TfDJ/n6N2z3E0pWy/BeTwez6PAi5c2+Ob/5Tdue/8//40r/PHf9pvvYo88Hs/d5naTQr9TD6X9ztksBJNoIZbsPe/eHEVKOK8hIbjuoLBfyNhe4ckYyyhvUEKQhgpjLS9emnB6pUMaBW8Z536hZFcnJUpAHLr18uas4vjQVSaX8q377l5HKVzEjm4tYSBptGFzVlFpw6xsmBQ1k7yhGwesDxI6UUBWudVJN3aV169NSoqmxRpLayytNWzOSyIpqHRLPwnoxAHPHO7x6kbGmbUOg07Ixrxge14RBZKqbfn85SmXkoBAuXVeVjZ85rKmGwvObmYIC/PKsDEtKFsYTWquTQv6cUC/k5AEknHeUreG7XlFo2FStPQT6MQSrS1l7dZ1e/PQTmroSAiCxTrcWIxx0SZSGLphyLATMqs14g7mC3ksBCQp3YdZ1pp51RAJyZedHDIuGvJaUzUtK90uWdUwyxukEjw/K5lXGmldguydec20qDmylPL0WofXtnKGacB7jw6QQnBxVCw0WsG1acVKN8QYy4nlLnIZNucV57Yyqqbl+ErEvNTsZA1PrXfpJ85bZ3NW0V0Nrvf37Oacy+OSujV0Q0WoJIcHMR84MWQ5jdjJKz5/dcZaLwYalrshSkoGScAHjg44uz1HSktWt0yLhqxsmBaaWElmZYPEIiWEEqoWLk8LANTi/IGUtBYaa1ntROjWcqTvcitpbVhOA7SxdELJuNB0QsXmvKYbBSjl8v3EgaJsDHXj4j0HaUhRGyZFzeevzMmqhmmpOdyPyKoGI0KaxhKFAoXkPYe6PHukT7cT8uLFMaU2CCG4nBW8dHXGb3pyiLWKOJQkoWJrViMkdBOXdX5S1KQrbtJsjWVrVjNIAsrWUFQN1moGSUQgJFYYljsxhwcJW7MdrkxqprUlbw1aa0prCEXIci9hKQ1IYkU5LaiMQRqIA8s411TGUFQtw+WIjVlJEChOLXcQWC7tFGzNKt5zZEA/CZhtZDSLSb6xFmMlgwQ6gZuIRSqpas2saKgaTScOKbXz0LK4BGll3TKIAyZVQ141BCLASoVSAiFcqNruZLNwQAIgioGahdr+hsgkDOhWMy8ViJadeU1TQYXLe7QrDO2GvO16N91Nbsyj9DgggLp24qfH4/F4Hm4+9N0fZfo29vdeRx7Po8HtJIW+kx5Ku23V2v09vpzSEeJN5w0XJendOQ3L3QgsFHW7b8iYWohKu8KTBWrt8vxIKcBAayxicdze89WNOdATKo0Uavd81lLp9i0iVmstbWsIlEJYXMSNbpEC6qZlXDSsDxKwlvM7GeN5TaYNS2nA5rzifYf7hEpigcm84nPXZm4hpSTHlxKqtmV7VnNhK6dqDWmoOLHcIQwl07LhyqRiteuiljamFZfGBYNOwHiuEcI6b6RYurzCcUgoBdYIjNFMy5Zx1lBq3HUGyplGt4Y4VMxK56DQGkPVgDVu3VNryEqDFbxpPbeLAeYGohq0sSSBIIlAKEsnColDRWvhzEr3joWvwWMiIIH7Mm1lNVIJgkBydJjQTwK2ZhVXJwWXdjLGRcPhQcKVSUWtW2YLr51x3tBPAz7QGXKon2ARRAF81ZOrHB52MNbyhUsTpIRhJ8Ja2JnXaGtJQkkLzMqajVlFEkgXxpZIhBRESrpcNQaqWlPqlki66cRYy3IvYlI0DNKIbqz4ijMr6EW41Bc35iBcgqy80mxnFU+suizwZ3fm/Oqr26z2IspaEwWSVzfmHB8mpLHieJAwKjTDWDEpNcNUEQSK1V7ITlZjWktWN+xkDau9ECklTx/u8dpGxnRrzs68YqnrPIl6SUC/E1A3LRvZNttZybiQPLnW431HeygpUCrg2qRkJ6/ZmVUcGaZ88OQS18YlAsEgDejFfT55fpsNXZOEAUudiF4Scm1eMWwtW7OKadFQ1i3zsmUry9n8dMHp1a6rahYGLteUtSylEUXdEFRu4lFKUreavHZ5ngyws5jM339kwImVlPPb+SKcyzAtNcNOiF5Ukisaw5nVDt0kIpSCotFcHGlqbQmlYJTX6MYw7EQcW00ZRiH9KMIimGYVVyY1aaQ41Eu5NssZZS5m1wKTsiEUikpr4lCR1YYoEKRBQK8D18aWaV2DFbTGYFqII0UvDtCtZla25FXJbrDYVqZpao02IAUgnShkcQJQuPhOZKULb7PCiRWxglxD3cK8NthZ5SZrAzKGtnrzd0ov2lPc/VC1x008Ajc5r/Zjwv1cvDwej8fzUOBD1jyex5dbVSR7t2Xrd9vYTSa925bFiRnbWc3x5ZTVboSS8vp5b0ywDW+twnYzYWtXeGoX1b6XU5fnV1vjbnAbC4rr49zbp93xXR4XHB+m16+NMZa1XszlUU7euBvjp/ZUDjPGkleaS5OCQLp0LZ1IUjYty52QWdlAAXnligStdCOKxnKoFzAt3S3yi+OCrzyzSt5ofvbVLa5OC7SxHBl0+NTFCbXWCARHlxKWeyHzUpM3mqPdlDQMCGTNy9dmnFjpIIFp7hxPqrYlCRXzKiernHAWRw2DULHUjRBSAZq2bWkWd+EFi2JEhcHaijR2Hl3TzF6vep0AlXY38LEcmAWrBrQGgyWysNKN+LLTQ549NkBKwZm1LqHyAtLbQmvDi5cmdELFSjemF9V88vwYYQ3nRyW9OCCNAurW0FpY6YVUjcICy92Ess0RCNaXIp5Z7zIqGxqTUjSGWhvKWrOV1YSBJKvdMlobSxIpYiX49MUx47wmiRSrnZB5ZWh0Q4tTbi9PS7Ky4aIUFLolrw39WPHyxpyTw5RTq12sMVTGIoErExd/eXE7J68bXrw05dSwQycNEEqyOSvZnFbMCo2xcGatQ9vCydWU9xzqMypqNmc1kpqjwy7LCxW5NS2dOGF7XjMpay6NCloLUloEgte35kgJF0c5G9MSs5Wz0gtptGVaVDxxqM/p1S6jrCEKXOLu1sjLcawAAQAASURBVLiJ49de26QbBy6Xk4Sr45zDSwmlbsm1ZrpTc3iQYK3gUDfGWIvWhu1pCULQtg1RoJiVDVXrFLdpZUgVjIqGo5FiY1ry/mMhrRGs9xI+fi5jWjX04oCnDg2YZiWzsuXIICKvNL0oIFCSQ0sxeWM4sZqS1wYlFYGUpKFi3rYs92KUFPQSV5VsK9MsJSHdyNBPFHnVEisotXO/lFYxbSx2XnJYRJzbyhACOlFMLwkomoBpXlE2GlAEArJG0w8FUgnKqmSUC9IopLUGrVtaDRbLuNDEShEay9ogZpQJTNPQNgYloTIgFip1DbSWtziwNHC9qtoghqKBwrj+C5wwJC2kERS1oFi4J0neKhJZfKja3cICHSVIvYDk8Xg8DyVvt8qaD1nzeB49blWR7N2Wrd8r8phFHtW4E7E9rzk6TLg2raibliuTki8/tbyvKHVjsu6DhK1d4enoMGVjVpFVblxfctwVmNp9fWQpWXjPvDG+WhvOb2fUuiUJg+t5k4pGk9ct2liuzSqEFBxfSqmNYXtacXVWgbHUxo2xrCUfPjnEClc9zhoYlRUIwax07Rxf7mNtzUo35shSQtM6TaDQmtc2MwSCjUlJGiriMCAOnYfS1SslJ5ZTiqolCZwm8L4jfV68PKVqWsrGkkSSjZlLi9PUNf04IFQCY2B7XjMVgjQJ6YYB221Ju1iQ7UZ8gMtHa61mPNeEAcQxNKVbqwW82ePoVvEIBlc0aaUTcmiQ8sThJQ73EwzCiV7vMixyL4+FgFQbF76ULPILdRchY+870melnyAQZE1DGqcoKRhlNQ2CpTRiY5YzLxpUGvLatYyXr8w5Okz4ilPLGARntzKstRzqReSNYWdeoY1lrRvTjSTzuuXJ9S617iCFYGNWMS8rKm3px4pzOznr/Zg4CljrBFwclRwdxGRNi5QwKjVrvYjNWU3duMpwjXHeUfNGUzYtk1xzkYLDbUyjNa/tFAgknURR1i1bs4o4cFPC65tzjHGJsxMlmFWuYldetggleOnynGePDbg8KvgPr2yRhgFxJHnveo8vbs45sdwBi8szNC1Y7yU01pAGiqp1fUkCyYmF6HV5UtBPArS25Gi2ZiVl40LCBp2QlW7CvNCc3c54dWvOvGpZSyPObud0IsWRpZQzqx2mpUbrhu1ZTdFoOknoRBAhaHTL5rymbQ0vXZ1ydJDy/LkRZWWotGWU5VyblHzw+DIfONlnJ6s5uZoAikGsmJQN7zs24ORyh7ObGS9tzIgCQdlYjq50mWUNxljnlVY7YXB9kLA1dyLQWj+msQZtWxrj3C4LbYhlyNkdl9htO2u4NClQKsC0LY22zCqDEAa1EHx0Y6lMg7WKQLToVlOUhmzhfhOHOLdH3WKNIUkCl0C8glntxB8hnNCj7cEeQdI15dxPW3dshDumAQoNW1NDtsh7VO3flOcukUhACGpr6Nzvzng8Ho/nbeFD1jwezy43evvsXczfykNpL1obamOIpCQI5JtyCAVK0mrD1awmDiXGuqpkR4cJRwYJ1aKq2S63Cps7SNgKlUQiCJXkhJLUxhAgEErQCRQa+6Y+ApS1y+f6mQsTd5M0duuYcd5wbJBwdiejE7uIEoDzOxmfPjeisYY4UHTjYFF5rWS5G9NPAlprGWWNi4jphFTGsDGt6ESS6bTilWtTlJQMOxHaWK5MC1rTury3UoKAxhg2t0vCSHCk3+H4chclXf7X9X4EwmCsy7N0bCmlE7k8tmv9mFq7HFKXx67qdxQGdBRcmeRoY3h9Q9CPAzqRJFYJ10TJrIDSuogQ3UIhXMhaYN1nv/up7+as3V2ztbf6H8OtFcMwQElXXW+tH5OEwfUcy3eKx0JAiqRESUFeOS+WaVEhBax2YjazmkAKqqalmzpvkl4UsjXPiQOY5ppuEpI3msP9lEvjklBKPnN5ym997yGmec121rj8O6Ocz16ZoRBMBzVPyh6zsiUNXVxnJ1GsdiOKQLLajYhixeVRgTFuQpgUhiuT3IWMITjUTdjJarS2LKcBp1dSjgwSPnl+zNmtORvjgnHeYBGsdCLiSPH862PCwIlfaeCSboVSEEjFs4e7PH9uzCANuLBVECm4PC5Z6wbUWjOIYoSAJJT82qub7OQNx4YB47zh51/eIlLOc+XKrOLKJHeeN7Imq1s6sWQwDplXDUkQUDWGqtHs5A1Xx4ULh5s0HO7HqECgRMAnz434wLElTq11OLmS8G8+c4WOEmxnFViXN2mYSL5wZUqtDZ1Y0U8U2/OaWVERhtDFUNQBja4J5GKSkjXCOtFQCTix1GErr9nJKo4sRZxYTokCxbntOfPaJVwTV2Z8/PVtrHVf2w+fGvLCxQnTouHS1GXnbyx0AkGtWxCGJFbkjRONYiWppXOvLJSmG7nJc160aGOIAkmtW3Thsv/ndetifZWi0Q15sxAMZIBSAq2hbgx57Tx84sDFwbaLCSeILJuTkjBwoWxCaGalm4DyW3wfJK7NCIiUQGJpePPEVBj38Nw/+l3YzDVFoxkS3+/ueDwej+c28SFrHo/nxqTRN3r47HIrD6VdxnnNZy5OqNuWQAjee6TPMI0oGk1WtdeFoH4S0LaWqjFYazmylF4v2nRj2Nyu8GQXr/eGzd2OsLUrQhW1Zjur6SWKedmy2otIw4AjSwkATWu4OCm5MikRwvLUeh8lBKO8YTkN0Qv/GiWlO5cxvHptjsUShwFNq3n52owjg5g0DEhCybzUXBhlBFLSXYhRR4cp00IzLdy6b2gjPnB8iSiUTIuaSeHWpnnVoKS78Q6KpW5A3liEEHz2yhhjLKY1tKbnQtLChnmpeeZwn194eYNXN2eoQDJMXYqWeWOpa1dR+1pVk9WWXiyJJMx1w/a8ojWGvHLFh6xeVL8WkCjBZuXyRIUSAgW07ub920kRYnApnbRuEYC1zsHiudO9O+p9BI+JgBQEroT8r7yyRdO6nEGnlp0KvNqLuDwqqFvDqW7KSg+2Zw1HtPPcCQPBej9hlFeMioZAQRKGFE3Dqxtz5oVeJO8ylNpwqBuz3FFMq5bPXZ5xqBtzdBAzKjTjvKZuLavdiE4akijFsGM4uzkjq11Fsgs7Bdq0nFzp88RqijaGXiRJ4oD1fsLGtCQMhMu9owL6KQzigG7sstanShDHEQbLpUnNMFWA4Kn1Lqv9hLVuhJSCncwJLkvdiH4aMl2UP1ztRC4Gs2wZJCGTvGZSOM+fLzkx4NJ25ryWioasMdRNS6k1wzbm8jhjmrfoFizO5S+rWqrG0FhD3WimpQsNO7yUcHY749woZ7kfsT2riIOAQmu2i5KmtigFX9zIMK0giRVJEBDHIb24IG8gDQAkk7ImUZJD/djlQMISBwHTVqO14WyWI7FkacilUclLVzOX5Cxv6IcKKSWvb82ZlS6sLVSKsppj2pa2NSgMpXbZkZJQYi2McjdZL6cRVdsQBQHdWBAGILBEocJoS7VwBcrrBt1aqsbS7wQIDY1tKfMGYSEMQSrFSjekbC2bpSav34h3rfeElwUCeouqftPcTYBhqOiFLcVuYqID6EdQ1K7k47y0t1S0PfeHtnXJ0m/Hfdnj8Xg895+L21N+y9/85dve/898fZfv+o8/cvc65PE8oNzJimMPIjfz7omU3HfMkZIcXYgtSggX9mXs9f20Nnzy3Iis1lSN4fWtjE9dGPOhE0uUul04EgRUtaao4dnDA44MUzZnFVobGgHHltI3hc3dKDx1Y/WmsLmbCVvr/ZjWvhHmcHVSoiTkTUukBBd2Co70Y7KqpRcFXBm7G+edUHFiOaW1rYvAwAlXeV1jRei8lZSkNS41TK01O3nNqZUOgZLUjWV7XoOBKNRUrSZSAZ86P2a1FzPshLQt7GROqFnpRUzKhn4aMi7cIuqlqzNXdU4KskozLxuW0pA0EsxLCBfCWFW3tMaQ1S3BKGOU13z56WU25iXDTkheN4zLhtm8Ia9rpIQ0CgmV4PzWDK0NaeTS5lyd1GzNSuoGSpwnUYQTYDQu4kMEFoVLPVIZ957ds8+tkDjnAqWc5hEHkidWUkLpUueEdzB59i6PhYBkjKVsDM+dWnYJgy1Mq4ZR3mCtU/p6ccAkd6rke9Y7PL3e5fXtjGuTgjRyIW9b05K1fsS1eYHWBiUlJ1dSlrsxF7YzJlnDci/EGIGixUjBidWUrDYsd0KOLCUcHaRsziu25/VCDXZeTnEsuDgu6ISSK+OKw4OU58+PWIoD5qXzcCqblu15zUon5tRKgsFwbWboJiHdUNHvBPSTkGE34rWtjEO9kMNLCV9ybImtWcM0r6lbw+a0ZHtakcSKbigYlw3zokZi6IQh00JTNC2BEvTTkO28pp8q1gYxX8wqvriZUdQtS52QotYEMsBYQ1a2DJKAw4MUJMzLljR0XkFVZUmjEAn0kgBjYdiJ6UWKy6OSpmlJQkGoAuKgx7nNjDgUVI2hGwdUbUsaK7Q2dJMIITTdWCElWCMIQ4k2cHVaMEgDTg1jJoWbAJaSkDhSrHVcVbR+FLI1qxjlDa+XLU8d6vDylRlxJBlnFb3ECU39WNEaQxpGhIHl9HKHi6OCqrEkgaQ1lqeO9Hjt2hSJZVI25JVlZ14QqpJuGhEKl9eo0oY0lHSTgEhKNqcVpnWhZrGC5rogZjHaTaz92M3Pk+qNuFenKENlLHVrmTXOK+xYYpFWUmnDQEJu9p90ksAluLPudHct+bXA1w97N+jWcmQQ0bnDbqcej8fjufN8/Xd/lFffxv7e68jzuHInK449iGhtuLiTE4eSNHDl7M9tZUSBy69z45j3Xo9GGxC4ELE9+5W6ZXNeMUxDzu/k9BJFXrfUuuWVjTnrg4R5pRmmEcM0ojKGfhIuwqtcle2NWcURKUhCV8Vse16TBJJOFFDWmu15zXsOvXksu6F3TWsom5Zr0/L6GFZ7kQvtEm5NFAWK1ljCQFEv8uvmjbuZ3xhoW8O0cFXTioUQZqwTtoJAstKNOLuVcWFe0LSGJFIMOxGhknzuyoRQClb7zhHCGMFGVjBIQ/LaRfvU2jBa5F/azl2YnRCCnazi6rhgXrlUMJO8QSmBlJJZWTMqBJ1YcWaty9lN59wwiAOCQDKrnDbwxGrKaj/li9em/PLLW2R1S6MN07JhVmpCUTDoRi5puHLV6K5NSnaymmnzRhgavLkwUA3I6o1wtd2q07e7NouB5Y77PCzQS93af1YbXtmcc6gfc3q1R5jeWRHpsViZ7MZwduPguuLdMQFPn+7TtIZPXhjTjRSBkuzkNZ+4MOb0apcLOzmBdDGep1dTNqcu4XYnCVjrRowLTRooJHB6pcuVacFKJ0IIwdmtxiUzNtCLFUeGLoF1EEjiUHF2a84Ll3JMa8gbTRRGPL3eIw0VV6YFL16esjMraYE0VKx0Ir7yzCpprLg2rZFScnyY0g0USaKwVhBHAb04Ymdekxc1vaUOh/spUki2s4qPn91CA5OsYpSXXL1Ssz6IFxXMFNNSc3TZMOymfOD4Eq9uzl1icd1ycqXDxZ2CSEqOLjnPqKJpqbVgtRtyarlLGDrB5egwASG40M6dx00SEQeSQFoujJ1wYgJc/2OFxTLJNUHW0GIoy5owgqUkwmJRQtKJBPNKMypqIgzDboxpNdPSEimBUOZ6UrLNaY3AuRWCAWsJJBxeStiYVZSBIa8127OaUrdszaWbGHNNIGGU1WS1RomISLm7ANuTkklWsTGtObqUsDGvOTJIePHChGlRUWvNvLII6ZKHp7FiKY1cOJ62SCHpxSHzSrPUC+h3JOO5oWmhG4NdJHwb5S1J5JKqDZKASanfJMJYNyK2Mnt9vC1wfmLoKKhaJ0Qps8juvzhOArFw7S51I3Rb0bSQtXdPQPLi0btDWzg2dHdePB6Px/Pg4kPWPJ7b405UHHuQKZuWi6OcS+OCXhKw1ouJApds+eRKSicK3jRmeKNCmZSuEJK1cHq1i7FvhJXthpOVTUvdtHTjACEsVWsJpCRUgqNLKdZa0kiyNatIA8XGrCJdrHF1a7gyLjgySGitZaUTUmi3JlJSsNqNWGTyeJOHWL2omnZpVLjzDFMCKdiauQypxlqUdCk+lBSLquKG17dmGANbWc2xYYIQgmvTgo1pxem1Ds8c6fP+w0tESlI1LTtZzXvWezx9uEdTt7y8MaPUhkobOqHitz2zThJKXrk2Y2NestqJOL3Wo25a4kCy0gsxWGaFpNQG3Vpe2ZgSKUVeNQw6bj1qgVYb4kCQhiGz2oX7ffFahrEaay1SuIiPq+MCi+DTFyc890TAlZ2crNYIoKgbZrmmBYxwgpySAmtBC0OtLZParYckNw8QsUCxWDC1e/ZR++x/s+MPLyVOOCtbhLGM8oZJ2RJIgTaWT10c8+WnlunEd072eSwEpN0v3bxs2M5qqkYDLk4yWLh1JYsvtEvwbMmrlpU0ZisrGQwTtLX83i8/Tla1jIuGvG7ZySqWu6ELhUoVT631aC28sjGjG4UcWoqodEtWt/ymM6vXE4m5ZMeS5W7ArGxRwPntOWm0hDGWojIUZUPTWvpJwPa8xhrLb5zb4Rs/eJSq0cxr19dBN+L4codACZaSkLwxjIuKIAj44NEBaRTw669tcXEnxwLzWrMzrUmjiEMD54miJDy1PqAXCAa9hKODhPVeTF63tNZycrWDMIJRXqGAfhqQhC4XURIqVjoxq0sJ06JhXhmOLqWA4NWNOca2hGFIL43Zmlc8uZZStU7IQAiSQNEC6z3JKGvoWEOsxP+fvT+NlSxL8Puw31nuGttbc63MWrp6meFwNJwZkiYpfSBliaYF0YBhwYa+SIYBwoAtAvICWxYMUF5lmIIhW4QEwYsEeANs+AOBkUxSFCmRosUZsoczXb1V157rW2O921n94cTLzKqursrqqerO6oo/8PLli7hx34374p6I8z//hRgD+3XOjVnB+xct8z6iTMs40/TWY33ABcGkVox0RhCJ6S60pJCCOpO8cm0MUaBE4LJzbAbLZWPY9JYgBUUhUZlg3hn264zLxjDfGJoB6hKUkix6T2kHMi0xQ1JDHYxzWhf4YN5S6zTSXjSOSGSvLhjlGa21rHrLtNKsO8+sFkwqnfKGnCcXguNactGGbaVjRMbUiiakYN1GHhtH/zHszsdV2mek5rQ6AxcSKaUctD4NQrWCaZXsd5vOsBl2wdgvMgQQfapA3WGHHXbY4cXEZ7Ws/Ut/uuK//2f/zBd4RDvs8GLjD9o49iLhoza8K3KsUCmTJ4bI+WbgoM4AKPSPP2d42lDmfEAIgRA8Caq+2q7IFK8cVfzue3NO1gN5a/nG9THOeQ5GOSEmh4LxIbVak0qkrvYdYqS3nrfPNrx30SCFIMTI7VlJnqmtayDlGz2riBKk1rQykxSZJFcpMuX2XkUEjicFZ+uBXAkWQ+R4kvPmyYbLzUCda149GjErM87WhvNVImOOxyUSwbffX2xJscisSk1sdw9rcimRheDuYQqzdj5wPC64vV+BgJN1R+9SmdBgPblOLp1mcCkLdzvnX/WOcZFRZZJNZwkusOwdvYsoEVg1gb1xQZ0J2gjd4Lg+yxnnls1gGcWMzkemhUIJmG8GTtY9k1yz7NM8r7WpCEkK0BoqIRAiYAK05ukivf3oi+cn4Mq+9mnk0VXxkRLw7mmPF5BrMD6SucCo1ByOUsg3MfJw0fHa8eeXhfSVIJCkTJ7N/9/b5yxag1KS/Trj3fMNXzsco6SgNw6tJGUmGQz0zlNqzbjMktVMCOpCbxVFenvx1LgAB6OM4OHX7+5x0QxY7+mGREQJLdirNVEkVvrhomPTGS7WPVIJtJAcz0oeLjvmm4HpKEMJUEpR5elijkIgtozmg0WLVJLfuDOmKBSDTVWI40Kz6BzjUnE8Lnnt2hiVKRpjeee84XBcIIGzjWFhLC/VFVJmLJtk41t2lo2A8aigyBQPly0CUKTcnhA8s1ITQ2qx612gKjTjQrFfaV7aq+hGBRdNaqEz3vG14zGPFi2EQNd7oo8cH444qHMeLHpEjGwGx41ZRZ0rvnV7xnfvL3j7bM3JSiCVZHCRcaEZF5Lb+xPePW85XfUpuV/A3ijjbD2w7KDUiTyRWlHmEiUky97S9GkgeOgjk1ywGXyqUoyCG5MSGwKCmKSghaJznhDhbNWlQOsgmQpJQDIpNfPOoUUi1NZaMioUozxj8J55a6gzifOCIDzGBUaF4tbeiPuXDeetQ0VPpgWdi7iQlCaSZKWsFEgpkdozmOdXBw2ADHA4gnkL3QBRwF6egrd1gLNNINNJFbdTB73YiKS/26qzT9ordthhhx12eHHw5/613+L73fNvv1Md7bDDZ2sce5HxcTY8JRMpU+X6CbGy6R2TQnNtWqRtET/2nKXYFvQAPgTElsj56HaTIueXX5px+6DmnfMN52tDlknu7Fcp0ycYSq2JMaKkTESMEKw7w9l64P6iZdVafvn2jCrTnK97vvNgxcE42cR+5fYMgEeLDiGSA2ZwntP1wGvXEpkDyYrWDBa1DeUWJHJsVkUezDukTHPlm3s1gw/4AJkSrI1n2VmIsOczMiF4/6Lj7n6VolMkfHDekGUS6zwxCr55Y4yQgpdmNfPecn/ecWNakQlFiIGTZcfLBzUna5uyl2wqNnrpoObd8w25VEQCnsD3T1Yc1Slsu84UvQl0xnDeOoIQFEoyeHjluOaD8xYhBTcnBUpJ8JHeOwSCaaU43bT0Q5pQjQoYHNgA0gQyBY15vvyij+Kq5OjTCCQDVKTWNSGgzlJB16Z3tDZwY08xqjQ/Ot0AsD/OP1eS9itBIEFKf79oTKqzl4JF5zhZJWXJ69fGvHW6wQ4OIQR/7LUD1sbzaN7S28Cm97gQmZUZxsf0h43w8tEI6wM3pyXGBS5bQ4yRiGA9OKKIfGM6RiK4d9EQgVWfwpRP1i0P5gM39woeLQemVUYUgrv7I967bLk2zfnh4zUn6wFCZLAO6xXff7gksM262TKv686RZ4pcRhSCa9M0iN3Zq3m8agkxscc2RFadZd1Z3g+BSktO1oaJzZiUGbmQvHO6YdkZvnNvyUGd4aJgXGgmleZ4XPDu2YbWpWyjrx3voWRydU6qjMOx5MasoB08Z+uBVZ8ayspM8PZFy7TOGRUZ0y1JdX1WogUse8e7Zxv+wbsDRSZYblIzXp0JqiLZwTadJ9OKo3EJMZ1HqSQRQZ1pBhvZdAbjYTrOWQ+Rd09XDD4yytJ2PgTuzXuMc5RKojNFCKkloDUWLdOqwLhItE1rIoWAo4lmVmZcNANReKILPG4sa2M5ntSEIKgKiWkT8z2Y1Lo2qTW9S6Hii9Zw2VkmuaT3SWG1aAJKJoVQphJT3Q4g8GQSvEr1joFEMF2RST8pVM0ByxZmVQrJbgwYD5WEqMF7cNvU/y/X2/RXE9MSopTYsFMh7bDDDju8SNhZ1nbY4afD8zaOvcj4STa8l/aqJ+RYmSmuTwqGOuOVgxFua0f7uOe8V2e88WCJD5EQIoeTnM76D21nfSDTkteOJzgf2B/ltINlr8z4z9+bc9kYMpnmgO+eN/yp14/RWjKtNH/rB5e4EFi1llmdp4bwXNPawNEk55XDEVIKFq1FAPfnHUWWHDr7dUaIEecCR+OCD84bHq97Bhc4nhTcm7eMCw0Cfu/+mvuXLVWuyTPJojPs1Tm1hpP1QDck69fxpORs3TOuMmIIqK2F7WBU8DvvXT5xqayagf/4+yccjHOOJgV//NUDppWid4LBRd4/36CVwIbApNTsjQomdc69i4Z3TpOAAQ3rzhGjRErJaghUOVgP9+cNK2OZ5Klwan9U8FpRYaNkmktMjHifRBZaQNunIq5V78m1RKtEHDVbS8coh1zBvEuKo+dd/hXbrwBPwrSfB4bkMNFCkuucvVGOEBItUyh7CGleu1dnzJtU2vR54StBIIUQOVn1KCkoteSiNQQfGVUaFWEzOH7zzj6OiPWBRWsJ0XC2MVyfJmnfcaXZDJ4bk4JMS9S28lAJgY+R3qWA69VgcS7iYmCxtvzdxTmHo4KqkPiQAscAlq3nwaKldw4lJK8c1oyqnFmV8Rt39/nB4zXORy5XA5M65/qk5NZBTWd9CuaaN3x72bPpPV+/PuGbN2f01vNo1fPN62PKXLPoDW+fNMwqTWc8J6sO6z11lhjjeWNQAupMoARctoYxmkVr2HQO41L493uXAy8fltw5qLm1X9HZwCtHNYXW7Nc5nfMM1tMZx6p3/O77lzSd4+ZeySjXfHDZsBkcmdacLpNCaVwoOpOUOIUWnCw7TjeWwTjevUitaevBURcdtdZcm5UomdL5pUje1LqUzDeWcZXx+vWC9eA4W6ZAuN46TlcDAslklCNjxLjEmCeKDyyCdT/wZ79xm7ceLfnhoxUSQaY1UiTJ3/Esx9jA/XnDYGHZOWol6bxnlGsGG1DK0QyOdWe2eUyC6CSij2yGwLgQXGwGFhvDYptDNCkkSsGoUBzUGTYETlcpyR+SKklIKHwahEYZDFv9YyBZ1j4qh7SQKOsuDYyWRCDJmBrXrvKTJGmgyraPG9gpkl5EuAC1TqtHO+ywww47/Pyx2gz86v/iP3ru7f/in6n57/3Tf/oLPKIddvjy4SqY+cvawvaTbHhR8GPk2Ev7KdtJRXhpryIKPvScQ4gsWsvLB3Vym4SIC5Fbe1UK0t5ud6VCMtYjpcDYSGMil21HZx17dY71nrO1YbCeX72zR5kpLjeGm9OSMlc8WLTMG8vgHINJgdd1rskzlZRKveVk3ZNrQYzJfvf+RcP+Nqg63zZA/2O3Z0zqHGM9H1x2jI80756tuX/Z8d7ZBpBMKs2NWUmhJPW44JdvTTmcFPzg0ZrOXs0xFSHC+xcbpJBsBsvjZce4lFw2hrfPGupMM6409y4aLjcD+3VOmUkWnWMzeMpckOeKk4Xh1iwSQ+SiTcVQkzrnvbM1j5cDR+OSX7ox5bIdWDaGUoMgoEkii0wK7p83T0LBq0KRS8FACirfGInzJEGHc7SdezJ5ynX6r5BbOxuJCHpeBVLkw/Ow580/8kBvYFpFgh+4XCcH1d6o5KVZwbjUTKuMUZExLvSTfKvPA18JAsnHRAwJAfcWLevOMSoybuxpzlvDZnD0xpFpRaYkMUauzUq+eX3CpMyeSCwFcGOvYt5aJqVO0sUArfFYl2oQY4CyUCwe90QhqXPJqMzojeHxyiBEpNCKaZ1xZ79mUmhcTIqm40kil9rBcTzJ6Y5G3JyVPFr25JnmR4831LnidNPjQyBTyVJVaskHly1fO6xZ95ZMpXT9dZdS5u8cjvjd9+ZkWvL161OMc/gIIQTWvaMuMg5HJT50rFvDpMyYVBmNsSx6h8RjHZytBk63gWnL1lDmmj/66iEhRC4bw48erzkYFRyMCloTeOusYVwqHq86JmVBO1i++2jB4TLnV+7MiDH5ZJvB8d1Haw5qzcmmp85T+NlemWFjZFQoFPB79y55tOgJPnD3aMTXbsxYdY5CS3ItkcseM4r01lEpSSgymt5yvhoYlylQbt4EyhxqDUWmWA+BHz5Y8IOTTao5jJEYA52N3JwVVLkmeMPgQOu0qhBjYFzmHNcZy97hfcDawCiTKBG5aAMuBJR0zCpBkeecLzusTwMLGZyvA1mWLIpBKBCCSakYFTnzpmNtEqt9BeMgz2BaS1ZNYPUTRiULKP+UxXbAJvChwKMrPYsHJhLGGZzvApFeOIgIREEudyHaO+ywww4/b/yL/8Zv8bfPnn/7nepohx1+MqQUX7rMoyt8kg0vy+ST1jJIbVwfLFusS7myL+3VjKvsyb6uyKjqqnFXgR1cOj/PEGvGB6wPPFilmvrHq55bs4Jln3J137/Y8PVrU0IWySR89+GSP/FqBgKKXG3VTBWrzrHeZgPt1RmH2+Yw55Md68rJ8u335sw7QwyBw3FOjJGDSY4Lqf07xIiUyd3xwaLh7799zttnDUpLbkyS4iVXhj/+2gEvH4y57AwT6/nmjRHfub8mU5L7Fz2Hk2Q5m40yLuc9p6uOTNacry3tkOJPzlZpkpIpgfWe1nrmjWFUZJSZYJRpwLDqDCergdNFl6JI1h1vnTTbOBGN1mmBvc41687SukhrAlKDCMkKtuxtsrc5iwmRTCimZc6s0iw7w2VjyZUizzOETEv5VwvzpUp5To7PZl+rIMXWROjs82fUZqTnY1zEeSh04GBScWOa0Vi4tV/w2uGEutDE+PnaRL8SBJKIMG8t16cFlVZ8EFqIKVjswbzDx8hlk6oRb81qFp0h+ETqLFtD4zzBw7TKyNTTgSFTkmwrK3zjwYrGOD64aLAu8HDeUBU5dSGZ1QUhCoKIPF717NUaIeD2Yc0ky9gYQ6E1o0Izby1nq473L1sWreFgXDC4wDvnDS/tVfiQ/IuDi9yclnTWsxw87cWKdWd49XhEZz2tsXz34Zqbs5Iq17x+bczjZcfXboxYd5554xiVgvsXHRvjGXxgVGRUhaLMNUokYk0KKLKcW7Oc+8uOm7OSXEruzxveO9+QSXj12oTzzcBq8NSF5/68ox0Ml43hbB1oTGCvzIlSIAjUueJXbk/57Xfn5FJibcC4wINFR+c8KibCpPcxqXq0pNIS6yO3piUmRIpMc742vHRQsthYtJRoJWiNo7Me5wLGBwiCddfT9QLnI2WeLvLV4GHoOByXvD/vaLZsTSYFfRCIYBnnGTYGNoMnxkgIEh9hYyIj6WmcxnmQIlJlUGY5D5Z9UvcoyCU4r/DG0LpALqH36fVoA4wEOO/QUafsJglKOEBAiOQyqS/FtgngqIQhpLDwT2Kn++33T6MdciDLUnPbDi8eMq24fVgSdvzRDjvssMPPFTvL2g477HCFT7Phma2lzYX0fVRI7s97jPV89+GKP/3NaxyMC4AnGUKdcRRaPclUenayf2WZGxea6bWMZrBbS5vCuKSmUULggicieGk2QpAcMlpKZoXm0bLnbN2jpeDr10a8ejShyFJLWzOk53Brr9r+bDhf92RaIrXCucAbD5YMzvPOecu0UAwhUkjJo3XH43nH+WZglGvGVUZvPbcPknNl2Tl+//6C88aQSXjzZMNelfGN62N6l7Jjf+2VfYz1/P59w3SU40XEE1gPllFeksnUBNcaz/WZpmkNLkR89HifqIzr05K9OuPd84bBBy5WPcvesekMNgreOd8wyiWjIme/Urxz2uF9CuD23rMeYFLAXp2z3AysOkuda6yOICIhwv0LQ6GgNQ7rPEIkhwgk4qd38Yka6XkhgCpLzhPnn87hnvexjiROyBVURcas0CzagLE9v/PWJedLw53DMb/+8v7nqvT7ShBIUcDhKKe1HjWSjAvNRTPw3YdrQgiUheJ82dMMnr065/os59WjKbf3St54uOJ4mlNniaU9XQ8fqpqUUnCxNuSZ5LLzHIxz7s1bjiYpAX+ca+atYX+UcWNa4F1k0Tj2igwlJdf3SqpOcfegojWeR6sk/3u87GmMo7OBm9OCDy47RARBJALL1rJXWZAS7xxGwLj0PFykWsMq0yhgsIFV13HRWTyRWVEQQ2KfnYcik2ghuD4rmK97Hq8Co0Jwsh7QSnB9WvD16xMGGzCm4f3zwKI1ScUSYDlYfvhozUsHFeveMVhP01ku28TK2pDCoTsfOSo0QwAlBWcbQ2scMZO8f9Ewq3MeXDZYH1kMjhuzkqY3eB9ZNUPab2+py5zLjWHdGxatplCgpaQ1lhAFR6OcByvDZuipshwvQwp9ixBFZFRIVm0gRlBKMKv11n7nCURUponeECQYb+hsJIokcZQiIoRi4z2h9xTaM9k+XucZnXFJNRRhr1LkmcQYz6qHGCDPoZaw6hPBpLTADJGzTY8PEFUK5XMeCgVZnphs4xIzbaXGGIeUiXW+sqT9JHxaco4CrIOwI5BeOChgXEmUVOgv6QrdDjvssMOXHZ/VsvYX/qTkf/Ln/9wXeEQ77LDDF4mPNqv9JPwkG96z+UiZUhAjv/v+gtv7NdMyY9la3ri/5E++foTWEuPTIvqVw+PatODlbSbRFT5qmasyDTEyeM9+ndMbz1k2oKTk1n7FQZ0TgVIr9uqM37/f8HCZEv+PJwW9i3z30Ypfv7v/Y89haj3/+TvnXDapdCrGyNsnmySIGGVcn+a8edKwX2serFqKTHLRWnKtWHUDh5MCBVyblixbx6uHio0JTAvNurfc2a/YqwuOpjkXa8OqdwwmhVMP1qMQEKBSmqNRTpFJ5r1hWmZ888aEe4ues3mHjZF7l5aDUUldCF4+HDFYx8Vm4OFly2Vj0gq8UpQiYJ3j3AiawbPq0nmv8ozV4DE+kTFFJvHe46JAK0FVKKSUXDSGh4sWH2BUpFIlYxy9AR/g2S4F4Z7PfgZP40Tm9mkO0mfBk6wkkVw1iJAa6oxjf1LztVzS+2TPu2zSOdy1sH0GKCGocs241EmmFwKddSgih5OCZWd5vOjJc8m4UjRD5N3zDa8e1RyPC145GFFohZSCZnBYH540qglg3hmmucbaiARqpZhOMtadox0cp+uBUo+fsM17o5w618zqDOciv3RzwmVj8TFysho4npScrHpaE7jYNCgp2Bvl3NwrmLc2pfV7z7w3DDbyzetjXr8xoTWBprf88GTDpFb0PtAvO24fVlS6ZPCpie3lowrjkof2YJTTW09vA1WRcfcoI8bIN25OOFsMTErNj04arPOcrAZiFKwHiw2Bg1GO8uCl53CUQxT88PGci25gv8q4ezDi0arjh4/XGOs4awK3ZhXHk4JlOzDYwCxX1Jlm0/d868aYSZ3zvQdLYgyp8a5U9C6wXA4M3tG6lOZ/2aTB9O2TDUezgpFWICLXJgXjXPI7TU9vDTFKDiYVbWcIFrwLjAootCZEuFj39B589FgvsN7gHNyeafK8AOnoPMgtE278djzathPM6pxHl20aqAtNpS19Khig0CnIWsUku2yGiJApzHp/JLEuoBSshyRBVBIymaxrHihc2j4GOO+h7B0ennx9lOFWJNLoeZhvASB36qMXFR6wNnB9L0OoHYG0ww477PCzxn/rr/wWf/Pe82+/Ux3tsMOXGx/XrFZm6kPbfJRg+qgN71myJ8QUiGO2rhUfIlWh8ERMCMggkrKoTDk//eCIQpCrD0vPn7XMuRC5f9nweDWQqXS7lII/dHvGqMjJtMCHyC/dmgKwaBNpk9qjDcYFjiclm97ywUXD69cmKcIDcC5wsu65OSvIleT37s+RQiIVHGzDqf/I3QP26oyjac7jRU8E6kKzV2YIBIt2QApJDIEqTwRMbyyd9Vy2yeGz7j02ei7Whugj33+4oveB+4uO147G9NZTF5KDcckfe/UA69OS+QfnG04bx7iU3LvsOd/0XGwcq87wxv01N6cFjiREaJzFmjTPMg60lk8CwS8ag3WRcSmJUbIwnjwDZwPDEPAuhWQfjzIuGkvbO5RIc7WLTYoyifHDVjNBmn99FgVRJAkKov/xXNvnhQKMBSkCft0TXJqkjgvP+doghSQQcT7sWtg+K56VGtoY6Iyjt4FVH7hsNxgXkBLqLCN4kCoyyjV26229GiScD1gXuH/Z8nDZp4wSCd5HTtYD+3XG/XnHO2cbbuxVaCXZH2uu65Jfv7uP0pL3L1puzAruHo6QCN45a6hzzar3XLQ9p8setZda1A7qDF9r7h6MyJSgHQJKShyeP3Rrn81gKZSgyjRHdclZ7Hh4aZi3Br0U9CZdrC4EpJKUSvIwRvaMR0vBqNC4kELDj8Y5pU72tXk7PJEy3r/sUBIue8e0znhw2bIZPJmWZFKS5ZpFM/DG/RVFrpiVJXf2R3TG8Z2HSxatpTUWJStihA8WPRDZaysmpeK8dZgYWA2eV45H3DkccTDKeOvxGmsDQxTsC/jgsiWPChEiWgiKXJIryVlrWDnPSKdAtf26wDiHUgKEJAbBemO2g7nA+vS8CymwEYbBo7QEoVAqsj/KWbQOoTJyJVBocjwyizQDFBLGdUEutt5fl5oMilyRKUEMgpN1B0SMj2n7Kqfwjt45jAGdkYijLgWvDX6rJgrp62pAChEy//TnK+LoWWWRJrHX/fa+jCRn/DQSKQLdrtzrhYQARhJULll38XNtTdhhhx122OHTsbOs7bDDVws/qVntWdfJswQTJDXPKNdIKZ4QSyLyoXyka6MCIWDTW6pCM8olYZtveUU2uQCn6x7rAtZHrk9TCdGzRNWNWcmjRcfbp2tO1x2ByNnGse4sR9OSwXpePtRcH1U0ved8PbBs04L/Xp0jlQAhEEKw7g3z1jK4gFSCm7MKJQQPFx2PtwVN40IyLpLfQUnN7YMRj5Y9jbHEAGeLgXnnKG3g1rSkc45RmXGsC/7E64dcn1Z8+96ch4uOzXaiMy4zog/88GSDDZ5la+mc5+5+EmyMc8Xp2vDKYY1WI7SKrFrP9f2Cdee4t5hzturpjaW1jhgFkzKpipatYdkOWB94vGjphrToroVg8IFCpmiaQESQ2rAHE7hoLJ6UjTur0/z7+qxicJ6NhdPNgIuJPHIBTPx4h8dP+1G9yJJ17bMg58NNbdaD9pFCCkQG41xRFpIP5i1SSkKIT/iMzwtfCQIJktTwpb2K3nkeXHh8hJf2S9a9497lhs1gublXMaoUziWblRCCb96YsO4dZmsBCzGilKTIEoFhfeCXb035zgdLprXiR2eOvVGB8YE61xgHf/j2BKEkvQmcrwemZWojm20VUYVWzFtDnWXcmJUsG4O1gcNJTqY0N/dLlJB868aYziZ22LrIurcMLrLqBpb9JZNCoZVisenJcwVC4lzgdNlRVxn7h2NcCLw3b3ABjkY5NgTePVnjfI0PMKtzfIgcjnPOl4azVZ/Y8EySS8i0ZiokVa7IleTRok1yRRlZd5ZxofjmzQn/6ZvnlEpSZFDqkmawTAtNVShePR7z7lnDjx4NfP3mBCUEdS55cNmyX+fEoDDO03sw3oNWjEuJJON4ks6tC55HqwFFhJBCt1vjKHX6W+ci0jjL2gSMS/lVIUZGhWa/1CglmbeO2wclmVaEELm/6CFGeh9YdYbBBmIIDCFwe7/EC03XOwopmFY5i87S9JZRpekGxyAEq8FxfVJyPC4REn7v3hzj+lTBuQ3sz2Rimx0gtylrkUQAPRu6dpV9nZMUT/12dBJAsX3MpIQgoHDJqimA1jx/BaTk061uO/xsEQETQMbky/YxfnUG6h122GGHnzM+C3m0s6ztsMMvBj5qE5NCYFxynWSk+d7DRUehJS7A42XHg3nHS/vVdvHZPlEu7dUZiza1neWZ5p/51Vu8+WhNlBCi4Fduz9A6TewBPrhIbdUhRKyPvHO6ZlolG9qVEipXkiqTvHu2Yd4Zlq3lwbxjVmvqUrNokv1hv84otGRjHNcmBY8vDeNcczwuuHfR4kKgHSTXJiVCCi7WA48XPUIIbs4KplWGIPL26QbjPJlS/OHbU1oTqDJFCIJRoWiN55WjJDSwPnJ7r6I+VOSF5sas5rwx7Nc53324QouIFJI7hxWPlgO/emeGkILbs5LvPlojtkIBIlw2hjpTFLmiGSyDSd6K37+/IDjPsrM8WrR0FkoNPgryXBAD6RxImG7PRy6hrhW0gd6C855JVTBve9aDR4bIYJNjRCvNpNK01iNkCiy3PjWft2m3P7VK6JOw6NO+Nc8fvP3sHO9K+eQc6FIgtWZ/VIKQyRoo4WCSc2uv2mUg/TS4spz1xvFo1TOr9DbNPckBx3nGsnNEUsbRb76yn/J4NoZhO4lTQnDRpKrFq2rtSGI3j2clt6YFy95hD2FwjuvTkvcuNondnZa8dbpmVmU0xtOajstCcm1cPPGwPl52xJjCuqSS3DkY8ZsvH2yPEw7HJd4F3j7dbL2ainEuudgM7NeaKksh3LNRkQaTNvlX8yyFPa97x/VJwcN5T6YUi87y4LLh0apHKkGhFJ0J3J4VfP/BknGlGRVpIBFScrJoyZVCK5FqDH1k0Tlu7NVUeUamIkWuuF5KSi3RAkwDh+OcwQWqMqeznjcfrzlZDwzO8+5py/4o55duTHn/suXdi4ZZlTGuSpp5iw2BfnCgoMiS8igMqabSuECh0kA+WMs418yqnHnj6FwEmZPJnsbCOlpshMNKcNY6RpmkMw5TStohsBw8i9ZiLRRS0Q6eznkqrai0oh8i16YFxUGFD0k1NPYBKRWTMmfVWYx3xOARQiNV5LJxDCa1oHniE0+stkAMaLENyeaTmWsD5PHpNpFELEUg9rBXQlZIOhNYm882wO3IoxcTSsC0zGgH/+QDxg477LDDDl8c/tL/+7f49/7B82+/Ux3tsMMvDj5qE3u0SMSID8lxIICT1cBLBxWXjaHQCiECkcgbD5a8fFBT5Rrnk7Pjpb2KKMBu841u71WYEHj5YMS0Tq3bUgoORzn/8L1LCi0pMsXBWPOj04Zfv5sxKjOcD7x/0eB84NvvX/Lte3NuTlLO0fcer7Ex8DUBs1HOvDU8mHdbIYPnoM45HOWsesvj5UBjDJcbl9wzMeUDT8uMED0hBpa9Y6/OeLTsmNY5tw8qzteGH5027Nc5r18f8cr+iEVvmRQZF02PGTzvXXZYH3jtaMSNOufxqk+L+VpQKLh30XFjVrDoHMF7TteefnBoLXh42WCcpywyCIF3ztaIGNkfF5wuW3of0ToJFk5XPfPWkGmFDZ4InG96jLGMCo1QkqbzCBUQElAKHySzcUHskiJr3Tl6Gwkk5c42JhfnHPcuG65PSqyNKKmocoX3gU1vn3th/nmgSfMvwdO8pMC2Ve0z7uuqWOnaRHFtVtH2nkpLZqOcaq/iT71+xDeOpz9mxfyD4itBIIUQef+8YdGZFEDdWIwPvHqtZnCO40nJrf2ao1HGYANZJnn3vEFKWHeJ7Rys42vXJ8wbgw+euwcjHq96nI9MS83ROEcoQaE1uUwsdjt4QhRYF/m9ewveOd/w8kFNnadY3LdONwQfeeesJdeSRTPwq3f2yZXg8bqn6R02RmSU/OqdGWWmuD9vU2B15ylyxajIKLKM/ZFm3TnKQrJpLOvO0Pk06NW5pMwzxkUifxBQ5oJppXjHRm7MKq5PEzO56QaEKqkLzWAjB5OMt083aJkCxW7WOefNwGFdM1iP3Mohj8YFb51tcCFwazbmYJyzbh23ZhXN4Ol7y0pG9uocEORaESPMm55MRSotuDEtOBrlRJGY5PuXgU1n8REmueZwlnP3aISxARcF1yI8Xg8Y5+gGz41ZTq4krXEYnx5rfLo4pQYsLHpHmUnyUYYcHO+dp+izUQ4EaAeY1il/yQcgeAqlt1WOgk3vyaREicgr18aczDsuG0Mg0BlLJiWXTY/3jrPG4LdNas+qE7sA0iffa+eSisgHWJmnJNGnkUpX9xlSPpIgtbx9Eez4Dj97xAhSQfwcVwt22GGHHXb4eOwsazvs8PwB0r+IeNYmdn/ekWvBSwcVp6ueGOHOfk2mDA/nHUoJlFZIIchkyjYS2/OllWRwjigSKfVgPeBDYG08xnl+/8GSX7+7T108nYJHAJHOvfEeF5L9DZIC6dGio3WeZnBoJTnbDDgy9quMItOMc82qS0HUOkvHkUnJ6brneFLifUCJyOG44voYHq0HnPe8c77hxqQikpRLxga0EBzUOXIkuL1X8bDqWPSWQgoeLDrePWs5GuccjDL+0b0lZ+uBQgkOR5rGOu5ftmglCDHyn719wXJjECrZwk6XHT94tGJcaiKCw1E6/nXnUFLgAul4Y+Sdsw3zdmCvyvnhyfrJXDxGGKyn0DK5M4ZAg6cPkSrLcCIQjcc6GJwnk5EmQq4yApZlF39sktW6lE+rZEQfCLz1+JiiYEKMn/vcyrF1l5DmbVeL+Z/19+Tb7ynXVvPK4YizxuIcxBh5/fqY147GKWD7c8ZXgkCyPrG/k3LrJ1WCs0WPCZ7oU+7NtUmBVpKTdct6brgxLRkXGUJEzjcp32jZWgTwnftLHi46RnlGlUs647fSxXTBLo3haJKxbj1/8muHbHrHDx+vuH/ZMi0zdKb40eM1kzLj+qzC+8CjdU+WKQKB03VijUut+Nb1Ccejkrgdx1+aVjgfCD7w5lmDd46TVUvTK1a952zd8mhluT7JsS6wP8qpi5xZpels4No0tQbMqpzeWIJIAc/rrRVrMwRCiLgQWbYG30ZCiBjn8QFa4ZAI7uzXzHvHOE/haMZ59mqNROBd5LDOGYwDoXAhUmUV1llO1gPRD4zrjLpUGCOwVhAizJuBVWeIQvJg3nG6HpiVWWodU8nqNy4UusxZdYamd1SdYGVSuJuSksFHlIDBR3q79YUqCEFQZ4lxLzNFZ2MK6A4BBTQmEiU0FkQTGcJW4bNtb9sMlpMl7I0zxrnk4Xrg4eUlrQ3kWSIJXYgoEehsYDCpqa6UEDNYPjMqBFI7XZlBpmFcSKSQ4B3LLdN0Na49T9uaZJdp9IuGPIORVhyN8q/ch7gddthhh58lPgt59C/+Jvyl/9qOPNrhFw/PEyD9i44yU9zaq7A+MKkyQogIIRAixUTc3Kt477zB+DRJuLlXgUixJzFEUGBsIh1E3LoPfGDeWbQUlFXOurM8XHS8djwG4KIx3JgUnDeGi02Hsel3G+spMsWqMzxadlunQ+BwVND2Du/hzn5FpiXjMkNKmeIwPDyYt9zZrzEuUmrJD843LFpLZwM3ZmVqrF60OB8J48jxOGdtPbmMDD4QIhxP8kSe+EBvPF2MWBfpTSpV+t7DFYUW27lc4M3HG0aFwvhIlUs2XVLCrLefYX90tmKvyDmYFByMSoiRs1WLlCkaRmuJDpGTZU8UkUoqlk1q2J4UEiFgPaS6tKTeCQwuZQhN65w8E3R9YNgWDo0zSecCqy5Q5ltb2wBCJZW/8ylr1m0dHn0E7eFiZXCBpHCKkRigFNB9zmaAK0XTVQHSZ4UCyjwROT5CIQPrwfP68RilJb3x9C69fo0PlHKnQPqpEWPkYmOoMsWdoxFfP6p5sOzRCPoQeThv8SFwY1ZR5oqzxnBrr8SFgNim11+bFED6/3vnGw5HBecbw6tHNVorro1rbIgcjwtOlz3LwfFg0XGxMbQ28HsfLHj1eETTW149rNHbC77pHN5H3ny84dqkYN17ykyy6CyrLjW5ddaTKcF+nfHuecuk0qz7gIjw5smGcaEJUbJXaK5NSmIM1FsS7Nq45PZRxUuzmg/mDRcbQ+cst2Y5rfFMtgRZlSnuLzq0lCgp+OHjFZvOslcX23NBsrA5x6zMOF13rHtLbwJKSX7t7gyhYFJlHPiSWZXx8KKh9Z4yG9EPjkfLnuADK+Moc40Jjs0gOd0MWOcZFXlS/mSKznoKrbdM+Zpl71JY+WXPqk/NBQd1xteOJkghCCFw2fSIDupCseo8IUIuJYUWZLlikmtaE3Ah4FySMSrBk4yiTXgqJYwBOudREVz0aFlwf9mlwdQ5IoJu8AwuEVVSCSaVounSbTF8PKMcYiKnsgw2Q6DUCqUh9x/2thY6HVv7CbT083pmd/jywHtACq5NCrKPtHHssMMOO+zwB8f/6q/+h/y7f+/5P7rvVEc7/KLieQKkvyrIlCTfZqNKKRKJEJOaSEi4e1BzMMq5bAw+RKJImUaL1nLZDFysDbNac2/ecn2aBADGecoqx/lAnkkQKXMJoBksNgbONj2ZlByMc75+fczDZc+xC5xsBo7HBYOLjIqM3sVtQLfgN+7u89LBiExJLtYDrxyO0BLOlWHRGqaV5o2HC5rOs+wGbIRH85DsXgKOJgXL1vD+RUMEvnVjyn6dczQq+N6jFdan7N4qlyxaT64Fo1Ijt06bg0nJB+cNj9c9q95xjZIbeyXOexZ9l+ZQ1pEpyfli4P3YcnNaUkrFqFQ4F3BIZIgYGzlZtAzOoYA+kyQjiOfx0tHZlDGcK8F8M9DbiItwNMoodMbgHV2IT1rXCh2YyKc2NReTaim6gLHQbgkhTSpI6kJakD9bOw7GEhnT394GEIkb5DNmXT8XPss+BTBRpAPdOlnGRWpPby1J/ZUJjuuCusi5PivJpPhCruWvBIGUKcm1acHpqmPVDeRaMS00rUt1dgGBJJBpxWvHY5QSiAjn64FNZ1I4tRRsBk/vHPOmRwrBRWM4W1o67+jtIXt1zkGVBGWJEJAsLga+c3/BojEIKQjR8/bJisNJSYiRwXseL3qqXHMwzrjYGC5by6yCG9OSh4sO5yONsZyvUzvaN25MOZ7kKAR3r1U8mrfc2K8YZZp177hsDVLB8bjCB8FBrZmOMwoh+fvvXHLZDFy2Bhsir1+bcroZKLSkyiW3pzVvnawxPtAYRyZTWLiWAuNhcIbjcUVA0nRmm5lUURY5RQZvnTaMy6R2ci4y3xgGG1Fa80s3p7z5eIPe9LgQybXGDJ619VSZxAdwPjIYD0qQKUVnLaJInuR1F8lET12k6OfWBDLtmdUlJ+shNZrZwNm6p3cBJaCuIDoY1xkheEop0YpttlLylm3twCgJtUzqoIyt9U2B8JHWB3qb2uvWvUOI5IvOtMRFcBYGC5mMKOmxEfR2QPo4gseQSKFxKYhEWmOx2/yiK0VRTmLI6wzWP5MrZYcXBUrCqMieSJh32GGHHXb4/LCzrO2ww1N8NED6yob1k2q/f5Gtbs82dwcX2KtyENBtYztu7lWUmWJSZh86B+Nc88OTFVJCZwPN0GN8miM9XvasO0ueSfarpBZSQnC5Gfh7b58TQtr/nf0cIQSDjfTWcW/hQUQqrcmlSJm5leYP35xwNC34Q9f3UFkK+C60ZPCB337nkkBkMI5Nn2GDZ1rlPF4NzBtLIPDNG1MO6pK9WvN3fnSGDymvNorIdx8uubNX8/JB/STo+nc/WLDuDZMyZ79ODd4AF8ueGAXzjcF6D+OCaZmxaD3d4OiNZTF4ut7houCg0oQQeOd8zeADg/W8cjhicIFrM8kHzlMqhUcgY7KfDdZRZpoQFL1P6rjZqIC2xzpY20DrDevWIiUoBIpI50CLNA8rBUjj6WxymlQZlDblyVbqwyHWOkIzBOpSYW1qXotyG2vyc8JYJtFBt22Am5RJFWdMxDnHwbgCUtvc6dKQC80fulNT5TnLwbGv5E+8ln9aPBeBJIRQwF+LMf4XP7ff/DOElILr05L3z9a8f9GiJRxOKl7Rgr1RwfEop3Oel0MKgRYITtc9dw5rYoAi12x6R50pcpnsT/uVRgiBj4HGeHwMLJqB7zxYcDgu02CSKR6tO1a9ZX+UwrJPV5Yyk/zhl/bwIfKDRytylX5ed5av35hwumw5rDPuXTZcNAPzznK27Mm0osgEwQdu7KUMokerjsFGNp1DI1IzV6FZNTal+TvYr6c8mHd8996C09XASwc1t/dL3nrccrrpmVUZMkrGhWbRGO4vGowNCCG5Pil4z3hWg8N4j5SKSjluzEpWMXJ9WuBCpNZwth7oTcC6jMvGoIRgUmqCD1x2lkeLnkXT431EyIDSgovBYhzMu8RQr31ASs+tWUnXd9SVZpJrrBeo6MlyjXeRy6ZHbcmcgGHVWmalRotAbwOjTKKVohs8RgTqXDHKMso843CUY8KaTW+pCzA+XZhha1sTPE3btw5WISSpI+DjgE2FAIwyWHbpjrj10ybZYxqEPk0ZFAI4m+xy3TPWtcjTgcxHUD79fEUufREM+A4vFkYFaBlZNjZ9MPicpac77LDDDl9VfBby6F/4DfjX/rkdebTDLzaeDZDWSuJ8QArxsbXfXwWrW5mluI8rggj4McJMSvGhCbmPkcvGMik1WkmMS+VNd/drfv3uPg8XXZpgiOQk6QbHGw+XHI5znId+2fP+RcOt/RobPCZEjkcZ9+YdjXQoDbXSlJliVObkWvPtBwsOR4ngejjvkjhgq07aGEdvHOM6572LDSHCjWlBkUsyJfnlmxP+7ltniCgY5SlK43sPVhxPCiaF5nhSElygzDWvHNdsHjhO1x0PLhuuzQqqTDK4wKTUHI0LOudYdZb3ztecrQemdcYHly1CCEIU3JxlbHrPZvAEH2idZ1TmTOuMk2XHm49WGB+YVJpFl8qQegtVnhRAs0pj1obeWk5WnkyleBMlIs1gEQJmdQrinjeezsG0SIv5JkDTP227Hrb7VQ5an9RFV+4PD0QDg/F4kruk/zmSRzlJzECEMWl+ICLkWlFUkWbwPFy2XJ9W3JiVQESqyKK13DkY47YevY+7lv8geC4CKcbohRCtEGIWY1x+rkfwM0AK0d7w1lnDprecrw3vnjds+hl/+hvXKAtN65LV6cG8B+BglPG1a2Pma0OWSTIp2QyW9843lFpiQ2Rcai7WA1rAfGPxIVJmim/cyLjYDNwznoOq4HBUQIwYL9grc24eVByPCy5aQ5VLqlyjRfLKdsayGTw2dtw7a9mfZJwuWjKVWtUmheK335vz5/9IxcY4xkVigo/HOZvBUejUpCalwPjIYAJvna45qAsG57lsB2aTjIePOvbqnMvNwKZ3hCC4c1BhQ+D2/oiTVcd8YzA+kCmBJEkFx7lEqkg3OG7uVSx7y5uP1nz/4RLrA4gU2m1dJFeCg5dm/PLdKX/99085Wbb0NmkGT1YDe7XGukCdazpjGaRCxFRx2Q2e3gbu7GfMu63iRwiazrAeLBsTyLTE+0Azb0HApJTYIKl0RmstYkgrJHkmKTQIqSiVZN4NNL3hxqzAeIGnY9WkULUYn5I4V3ZX57cp9yINQtlWEtmY1MZ2UKaw48FFnE+Md++hEGC3O/pYGxswqhS29T/mf3UksgjS77h6a/4k8uizVEDu8GKjd/Boabhohp/3oeywww47/ELgf/Nbf51/++88f0zpTnW0wy8Cnkct9KzqZnDuCTH00e2/Sla3jxJEH1VvfNJ5HZzndNWz7h335i13D0e8djymMSlk+vfvLxms42TZp7asSlFnmt+/N+dk2VNninGREYDTZY/WaUbw6lENCO7sVVx0llJLVr1lcH57zLAZ7FYAUHG2GThdpkzZTCnq/Yprk4ofPFpxfVISidSlxjjHqFSsWosP8MNHK948WdP2HqkEi9ZwUGvazhGJXDaGTCqkSkqYX3t5j7cerXAB1r2lkJJSa751fcy95YDEcLKy9MZz2Vmid6gso8w0b9xbsegGhgClFNzeKygUaCmQQlOowKpzjEtJmQnWQ1pKF4BzkUgkWphUoGNkIMWEBFI4dvQ/vqhvgGAgl2nu9NFP2s9GiWQBJnkqOvpZ4Nl8b0HKy5UyCRoyDZdtiuTxOI6qpIwaAsxbS6k1N/YrJkVOqTW9cQghubVXfe7X52exsPXAd4QQfwNorm6MMf7Fz/WIvgAM1vP9R2t64ylzzc2Z4mTV0VnHyaon15KLjeHlw5qDScG6NTxeD2ghON0Y7h7WSCUYlxl3D0b0r0ROVx3zNrWd3dmf8vqNMW893tAYx1snG65NC8pMEoJif5SnAO7oGJcZrx2PWfaWeWPYH+XEAP/wgwWzUvGj04aDUZ5ePRJWneOyteQ6YHzkoM5Y94b3zjuuz3IKrXnlaEyuBQ8XPUpEQgjkuSR4AcHycN7SmMSC5JlGI9M5ebiizhWH44xZpRmsJwpot4HZ++MC76EzAxsD12vFwahAbdnkUa5493RN8J7BOXobMN6z6SSRgEBzsBi4aByH44zGeEaZojEp7PqiMSgpCcZuCSpLXeTcPajofWRWZyyHyLBtHrg2q/Eh0LSWTECuBOvBM++25I7vKTPB4CPBw6RWRJ8a287WllGRiDVNpLNX6fyAj0RgpJMayW7ZnFKkcLVkmINcJB+tdaBU8p5mEaIC6yO5gjpLljQ/pMeET2B0IjDfeDY/gdm++r2OLSP+Ka/zHXn0iwFBys5atB2bwSE+5+C+HXbYYYevGnaWtR2+ingetdAVEZIr+SHVzcdNOD+r1e0XFVfn1ftAFHBrlmxt1yYFl+3AyWpARLg1K6kyxeNlz0t7FefrgWWXVEpVJnnvvKG0HikFZ+uOo2nJN26M0RJ+dNLQGcvJyvDq0QgApSUiCsS25UxJwcOLlhBTkPdelfHywYjVYFNRVEyZtCfLAScil5uBi8Zgjef+csOjZb8VOETeP92AgBuz1ILWdY7N4LhoBqwLjIoJmZZsjKddDxzWOcILLoaeNx5YQgh87fqYG1mFsSn/d2MCWkCmNb0zNNZSoCh1TvCBR/MNeZYxrXNEhN465p1lUhXkIgVkrzrLEDyreVIzZdv2NWPTor62ya2hHSy6bUvbdl7VfcKquwNkSEokzIfb0J6Fj0mRdEXs1ED7zP3yJzzup8WzH/kVkGtouq2Nbkt6rbfP67xLc9ciA0JEysgs1xxNcpQUHI9L7h6OPtT493nhs+zxt7ZfXzr4GOmdY9VbWuMZXOCyNfSPPM4GNmafW3tlCk2LkbVJWTdVqZGN4c3HS8Z5BkLgY+SPvnrAj042zJsBJeH6tGLeOI4nBVWuOW8M89YyqRSVVigpOBznKCG4OSs5qHPeOd2QZymbad46Ci155WjEu5dtyhxSgjJTXDSGm5OSy8FyXKcXxJ3Dmrv7JY7Im4/XHM9ymiFVMF42hsYE7q96ppni/qJnlMsk8wPyKFm2AyerntY47hzuYR0sWsuibZgUmnnvuDWt2FjH7b2S+UazbD2Hk5IsE6xayweXDUUuUFIwrjIer3o662l6i1SaXAtqFbk3b3hpryLXktONRcsUbj2rNJcbQ5klgqhUkjzPuXtY40Kk6SxISSYCRkqqXOGs5fZelS7iqDhf9xgP+Vba1w4QSRKiGEEgQAjGeYaPIKTkdNVxNMp5ab+k6T1nm5bNlnqWOl2Y/ZAImzymCzfGFGrsSQPWEKH0IDLYqxWDD6gYGRzUI8lm8IzzxIAP25ElAo1L+8hIA9dVG9vVzx/lCZ4lhHYcwlcHkuTRDlGSa4kjPqnq3GGHHXbY4bPhs5BH/+R1+D/9yzvyaIcXE58le+h51EKf1Y72WaxuPw/8LLKZrs6rD6ldzbh0Dn/97j4vH40wjz3vmpY6T+fxqrGtd57OOBCJeJMiOT/ON5Yqj4zLjF+7s0+hJd95sCRTgkedY1pqmsHz2rURi43lYJQ/WVh8tOjIlXwyR8iVQinHrErt2yd5T9NbXr8+5nxjWHYWYuRoXPDG/RW5FERSy3VdaP7E64esOsfDRYckcjAu6K3npB9453TD2WZAIgkxkVPzzYBSkmmdMS4K3j9v6Gwg36qWYhRsrEeGZIWb+kiVpxToXCraIQWWT3PN3qTgg7MNg0tB452xXKwtmYZJmbFsBtIsz6MkrGwiWGzcZh3Z5BjxfDKh86zCJ5NJGCBkIpOu3CcZT5vXPqpOGp7Zx+dNHn30ODMBfZoOk2XQDcnhcnW/IBFLEhgVir265HCv5PXrE65NSl49HlN8QfbS5yaQYoz/vhCiAu7GGH/4hRzNF4TUwJV8oyergY2xuJiq36OAzWC42EgOxwUAm96SKUnTWe4vWn7wcMXxuOSXb0+5c1Az2MCv3J7yeN4xrbInr6Qyk3z/0RrnPJe9A1HwDx8vePmg5qWDGnUd3j1rMc7ROs9enXG2Gjhdd0yrAucC1nkeXLYIAVWWoYRkMtacbgxZLcgzxZ96/ZiIwBpLjJ5CKdbGcroecD6w6QYeLgYe+ZBCygrNwbjAItASjmcV1gXONgPWQVVIHly0uBAoteRyOeBc4PZeye29ERLBot9wsu6J23Doo0nJ2cZy/3zDsrOUWtBKgQtAdGgkIlecrXqMDdyalcQQQEnWnWVUaDrjqXLNYBylhv1SUinJuht4MO+ZVpIsy4hAqSQmgCFyY1py3vRsTHiiGPIxDRrFVh1UForDUU4zeNadpS40Kno2vWOvVFRFzmIz4MPTXKFllwajjPS9LtPAYmy6UKSAqgDRpQt5XCoyrbBBUuSBQkAgIsSWsQZ6kx5XZGm/V29nzxICehvO9nEkUcbH298+8fXOh+WXO3y5UEg4nGZMS8352iB/jt7rHXbYYYcvK/53f+Nv82/+zebTN9zijf/pP8V4tKPrd3gx8VnJnk9TC/00drTntbr9PPBp5+ezkm8/aVsfI94nIYIQqQVr3Vs+uGh47WhMXWjuHtRoAZet5ez+kmmp6Z1PRUmN4XAcuGgsZ6uWusg4Gue8vF8zLnVyRBSSwSoOak2RaSICHwI+Rn7p5pTOpvnaZnDcnlUoJVJcRoipxl0KMikJPlm89kYlnUstZJ3zDD5SKc2o1BjrEBJmVYbzgdZ4Hi1azjepZc64yLiQrLzHhUCIMalijCUIKKTgYj1wsUnzslyCMYJrs4pcwKHVnGwM0TsWm0jTe/bGmoNKU+SWcV6kVvHOYiMcjgvu7ld8775h0XQcjQsa5ym0YvAe62FIPFyyoCWtwJPbno0g+Tg8e1+IKTKi1DCYpwv68PEL+/DhKJEv4uP51RwuklwwhUxzSBOfZvTC02zc4KEJoKWjt4ZVazhdGbRU+PDFyQ+em0ASQvyzwF8mPbdXhRC/BvzPYox//gs6ts8NQgl+6eYEIZI3VLYRHwU3ZjWzOqfQChsji9Zwshz40dmavTLj261BS8GkyqgLxflm4KX9incu0geSKlNcmxacbwZO14br05ybs5IPLhqkEJytDdZ5lBbbGr2Ba5Ocb9yYcrkxvHXaICQ8WvbMyo6LdceqdeRSUBYZIgb2KsXNWc3N/QrvwYXAwbjg2qTg/YsGqVI0+0VnMc6SaUWeJyVVmQFCpUrFEPnVl/Z4/6Jl3Tp6B790c0bvAufrnrN1x8GkwPrIpNI0xuF85M2TFTFClWesO8OyNRyOCg4mBfuVhhCwFw2rzrA2Fq0FvYk0IdC7PuUPZZJXrk15+3SVzudRzYPLniKTjHJJXZSAxwjFurfcXwzkmcBHgetcIrZyTQiRdeu5c1QwbwSEVK2ZqzRwRAAB16clPgoUguNxgQ2Rm7OSh8uOIpMsB0ddaBadwViQGUgP+HQxalJImSIFXU8LGDRIJYkhMhuB1BnCe0KIKc0/y2hNIqs6C5MSrE1klveJULrKNVJX70Uypf1nOWgD6+1IpHg6KP00g9PP/218h58WlYA8g0LBtUnJ3cOKsCti22GHHXb4TNhZ1nb4RcJPQ/Z8mlrop7WjfTRg+kUgjz7t/HwW8u3TtlVCMDjP/XlHlSt6GwgxYLZ2NiLc3qt44+ESSSI3pEilPy/tV1jv+f37C3Ip2J8UZELw/mXHQZkjlUzxKSuTVCc6Y9ka6lwxKTWv1KnlrMoC7WA5muS44Lk2G1EqiY2Ru3s1UaRzsjaWe/OWLhoUgiJXlLng3kWHcZ7VYLizX3LZpobxd06hMQ5PpDWOwQeMC4zLEmu3JI71aCl5f96RAyc+UuaKRWuoMoXdNp/3NnAwKzlrLJ3xSA9aS9aNQRAJXnNtWlNnktNlR+uSQ+hwMqa3gc462gFO3YCXEiUCg0nOELMtF3IBvHgqIqhUUiE9+VvxtBTp49BFwKfHjDMIAsYK2i4RNj+P0iLB00xbS3pueaaIHkLuabcKActWZOChLuD6rMR7gXMR4zyCyMmq5+XD0RdyjX4WC9tfAv4Y8LcBYoz/SAjx6ud+RF8AlBBUmeb2fkkUM86XPReNRQrBqjOEGLmdK5QQFFomddGy5/3zDTf3avZHGWWW7E+/834glxIfk7Lke48sR6MCLaAZPG+fbeiN57VrE05XHQuluFgaBNAPkdeOZoQIG+NZD4ZcCu7sV8w3AxdrQ5FppnXBqnOYAL0POAI3pxVaS6JLOUhEWHaO27OSKkvM7e+8u8b6mPyig+XoYEShBbVWmG2A9teORygNVaGIW7Z6cIHjccFBVXJv0TGtNVkmqUvFyaqn1oqoUnB4M3jK3DM1gQWO8/XAuMzwziNHJZdNTx8SKYJITXSd9czbHhcSy9sMkcNRxrjMEEAIAR8VQkSqImNWO1wAQeC0s+Ad00Lx8o0xZ+uB9843rNZ9Cg57Jj1fkOrPbfRcH1f88u0JSimGdx3nqw7nPFWRsekd3282NB1onQZ3T2pSU1vbWpa4MYSAaZXTuYgSKa2/1unNKBBY9pFZlVjeRWOxPjHa3ZC8uXUBziUiSD9jZ3MRxtvf0fRPBzfBhwesn2bw2sUuf/kgt19h2waopOLuQcmsKsjljkHaYYcddnhefBby6E/swf/jf7wjj150CCH+S8C/SfrI93+MMf7rH7l/Bvxfgbukuc1fjjH+X37mB/oF4achez5NLfQHsaN9NGD6541POj8EeLzsUVvrWNySTR9Hvn0Woi7EVDG/bC2TMmNcaGqtuLfouLVXcjwp0EJgQwDSvOEqd7cuNDdnRaqhHxy9dRjrOZxk3D6eMK405+uBSMRtn9tgI6frgUfLU+at5XCUypjOVj3fe7Tmm9cnfOvmlPvLDgDnA/PW8spxzTtnLVpL3jld4aJIzeJa44XjH7w3Z5RryuMJy87yaNnR2YgUICMM1nK+Crx2bYKWisvWcu+yQxDQWuEinC17GuvxZWRc5ZyvBxCKkZY8WjRcNJabk4zjSU6pFENwvHw04vok5ULtjTO+OZ7wg5MN9+c9g7E0NjAqJTIGBhswIc3PpEqflx3pQr9aoIenjWpX5EZOalFT/hnbmobNR0Jjr9RGSiRLWJ4nB4niZ08ifXQO51ziG8pMcjiSrAfPYhOwPrlhpIDr44xrezUiQl1qZnWWxDE+fGH5ZJ+FQHIxxqX48MDy5YlmEaCE5NakJgY43zhak3KLZmWGQGBc4LxNwWfL1uBC5LIZUtvapmXeGPZGGS8djvnewxXL1nA0Lsm04NHc8LXRiK9fm/DGgyVv3L/ksnNMcwUyUiiF047jac7jRc+yc2RSkWUp52RaZ0DERU9nBAejjFGR8aOTNU3nOJUDSghGmUIIweGk4Fs3JjTGs+otj1cDZaYJwaag5wDgCVHxeNWBEFTzjkxKhBSpQt4FgvMY41BS8fblmsYEZpXil27N8N7TWE/TO2bjDO89rfNsTldE7wkIRoVGSlg2khgDCMWkjOQ6mUq1ktyeFrSD46X9mteOKhZ9oOsMG+NpjKEzgYM6I880cct6E0GIQG8D5xuLk4KLjaEZHCerlhBT8r8kkUdXawNCQakVmRZ879GG69OSUZlz1lgGF9kMPeNSsbIerRPDLH2ykF2l9g/bgUWrrVpISPZrSWMCZjDEKLfJ+JrjqUIA9y57rEtsuAO6rXTIdOkYr7yqatvMlslkjQvPMNw/jV3t45Dx6R7gHV4sBJLXmQiHY8U4V/QmcjDKXojVvR122GGHFx3/xl/7j/k//K3uubf/B//Kn+ZoVn+BR7TD5wEhhAL+CvBPAfeB3xFC/NUY4/ee2ey/A3wvxvjPCiGOgR8KIf5vMcZfCEf/T0v2fJJa6EW2o31WfNL58THSWUcz+CeqolGhPnZi/Ty2v0VnONsYjicFZ+uBMldoJTkY5ZSFZn+UMRjPYAMik+zXOT94tOJkPXB9WkAUWOd553QDIjWLPZh3FJli1Vv2Rzm9CRzUORvj0ULw4LLlpUOPD5JHy46zteGi7TEuPU8tJCerjrPGcGev4vZBjZLw3lnLokvxJvfmHd0QGBcZxShj0RjmrUFnmtv7IzIF7100DMNA7yVSkhreTMTaQLXqku2t0JQZGCt4uOrRMq2OT8qMTAlEiAxRkCvHyaZjlGe0JmIcNDYgCAQkbe/5znJBZxx7k5LXjwuORpbvP1oyLnWaN0mFdREdIybCpBSYIBiXgcFBpWHZf/i1cDWnKklzqnZ7gySRFvYj5NGV7W1tt7a44WlO7YtActgIAY8UglwX+K6nyOFWrXFBsuxNmm9HWAyOk2WX8pZHOZmSX1g+2WchkN4QQvzzgBJCfB34i8Df+7QHvQirBlcDgpICK5KdqdSSw0mBEpIiU1Racv+y42KVWFSiQJCkYO+drbcXqSSSBqj9KuNyPSRmOcJslKOV5NGixcfA+drSGMe6tbx2JHm47Phjrx4QAjxY9uzXGZkUdNZz0QzkUpIphRJxG3Cd8/q1jGvT5Ftte4ePgtlhTqUVizYpqLwPeB/oBocLnhvTiiglSkpWrWNcC4pc8/rRmIvWsB4c40Kx6iybwXG26dj0nlJHFGl/p5uBm8ZSKcX1cc7bZy3vvtcwyjWVVjghON0MeB8pMo1WgmvTisG6VGOvJXkGmUi2vcVgmQrJa8c1Xzse8+5Zy6n3/OHrE+5ftjyYtyw7yyuTEu8je2XGg9VA23UEUpWl95FFm1L+EYpxITHePGGNI6klLXo43wzcnFVcmxaJoAkRuc2o2gyBofE4l/KMcgFuSESSJg0wV4x2LhKxtGgHkIrDWjLJBKNcsBwCMcCyDWgZ6W0i7T76SWXrjIPtvq9GIx/S/oNIId2Bp77WPyg+DxJqh58DtqrGZvDc3MuSHfQLXD14kfAivE/ssMMOX17sLGu/0PhjwFsxxncAhBD/T+C/AjxLIEVgItIq9xi45BeonPYPQvZ8klroZ2FH+1kEW3/S+QkucrExlFpS56na/GJj+Prxj+/nk4io3noeLTo+uGxZtIYbs5KXD2vev2g4HGfUuWbdGS5WhuvTgsNRho+R09XAtM6wPrBoLUIIXr8+5Y37C949W+KBl/dH3NyvWPeWNx4sGRWpPVoJQa4Vkzrj4Xzg9l5JZwONsdy7bHj9+oRMKlrrsM4TREQSebBoORgXvH+xprcBHwMX64HBe0Z5Kvupck2hFQjBg0VHmSnONj298ax6k4QVPrBf5YwKSWsia9dSdpr5JrW89dYzyqAxgUnpqbOSvVHGYD1CCo5HJV3h6Kyn6w2tTdm8RaZ466JhlEuMi+Sd4/ceLHE+gIhURbLxiau/iY50PXRDBCVTWHZI4deZZOta+fF8IveRn+HHSaH4zHfPizdoKNjOWSWlUJRKYC0YB8ZbvId5a/jRWUNdaOrME6MgBsH16RdHCH8WAulfAv5Vkrrq/w78NeB//kkPeFFWDUSER4uei03PqncE7+l95Bs3JsyqFJy9aA0XzYALcLkxjIqMaZVxfZpxshiQmcT6yPtnDSEkdcqozPj68Ygy0zxYdLgQWHSGXCoOasUQAqUSfO36jNZYHs07vnY8ghg42BJOenC4TaDQikmt0VuFUC4Fe+PUuvZo2bLsLUWuCTHJGYlJPillSg9rjWXdeirt0cCk1AiRJJU+Rg6nBY7IpFAMzjMbaWyEaVWw6RouOkOmBNcnOUJIzleGr98YY5eR/SpjsI5Rrlm2JrUHoNibKDa94d5Fx/GkZJQrRqXAOE8/RM66bTBboTDO8ebjNafrgVVrWfeWxWZra8s1s1pzvhpQSiBEZL/WLDcwGUlUVdD0DuthXCkqrxEiEHma93Ol8nEBaiUYFxotYTWkAa4qFKshMTUmptpGGVOyvS5AGNgbS5ZtSKFkDjqSnWhUKQqlaExg1Xuc93ROUOq0wuC21rafxFRfpfQ/qwgy29clEUZZahN40QatHX62GIAiJj+zkil37MF5x2+8FJ9K7H4B8aK8T+ywww5fTnwW8uhlAf/J/3pHHn3JcBu498zP94E//pFt/i3grwIPgQnwX48xfqwQWwjxF4C/AHD37t3P/WC/KHxRZM8XaUf7rMHfn4ZPIqN+0vmJAg5HOa31tMalZuxRjo+R6MOHtv1JRBQkG1wkkinBtWnBybrnYJQzLXP2q5zLZuAHj9ccjjMuWoPzAe8jjsidWYUQEbm2ZJlk01vuHtaMC8X9RYdUcnueAm+fee4cVORKMil1isBQgrNVz0UzIAXsbVvJLtY9pZa0xnKyNmx6x639inXv+NrxGClTeVJvU26vVpIoBPPGkSvHbFRwY5zz7XsLSidpekudK6aVxrlANwSWXc+ykxSZRuAI0RJjxMfAYFJI936pcTHN/8qsYlJqrI/cXzQYlwQcmVb0vWOcKWbjgsu1ZWEcB+McpcE4R9MZiIJNk4K+vQdEZJRL8jzQOyik5yobetldKXR+HFfulOe1oL2oro2BlKUrEKyGLlkePZjWEVM3FXtVxtFE8xuvHGGspy4l1/cKMv3FRWB8FgLpn4kx/qskEgkAIcQ/B/y/PuExL8SqgY+RZWd44+ECgSTEQKE1/+jekjv7I65NCohQ55prs5JRqbHO05pkL7vsLYd1QZGnlPt3Tzf82st77Fc5vQ244Hj5sGawjvONZVSklq99l373qulZDgElLP/R987Y9JYql2ituDbK+S98bZ9V4xl8INeS23s1D+YN756ueftkw6KzrI3jpVnNXl1w76LhaFIgpeDWfsVbJ2v2qjxJGjcGGyO1ElSVRkqB9fDeeUOMkVqrlKUUYdUOVHnKKLI2IAvJtb2aQkmUFGxaR2cCLkampeZoVNA5z6jQ9ENg0VsuG4v1kc3gCERcgEXrGOWKKATOeb79wYq60PgoOV31nK4HCi1xIZBrxUGVczgtuDEreO+8RYrI5Xqgc4F+Zbi+V6KUREt45XDMojO8e7phsCmBfwhpkOgjZA6aPnDvskVKSWccqyGQiYCOEaVAOshUeuXtVTl1rpOsMgSUNFi3DSeLKQMpEwIRPevWPZE/9i6y6uMT9dMnyRwz0sBkSQNZtrWxue3PficZ2gGYyPRBJwKb1nJ9VrI3znBEfsF7gV6I94kddtjhy4W//P/9m/xbf7v/9A23+E//B/84d49mX+AR7fAF4ePYjY9+7PqzwD8C/gzwNeBvCCH+Toxx9WMPjPHfBf5dgN/8zd98EVwqz40XLXvok/DTBH9/Ep6HjPq486OEoMo141IjhSDESGs8DxbJ7iqF4NokTbaVEB9LRFkf6IzbOjcGiDC4gCsCZaZ4aa/m4arj5rRkXGbcn2/btHPF5WLgzcdrBJHzjaHUgjLXvLRfU+ea2bbFrcole2WOkIJxntPbgbpQZFJRKsnDecd75w2FTtEZe6MS4xzvnXese8O8dRxOcj6Yd2REfvh4yauHI0BQaYHLBMJ6lm1AShgVOV8/HvPW2Qai2BYmSVyAwUZCTJ9JXRCEGEB4pqXEOsHmGceJjIIoJPt1xsEoY1xIplVOmUn6wXOxaVDbyJG7+yVVqQke+lwSgTuHNefrgSqTnJvApNRcbAzRQeOgELCJgcHCuIJRrrDOk2dpn90AH30XuCKOfh4h2D8tCn5cAXUljlgNYMOABzYmkTe5hLIAJdP5P19b3j1ryLRicCv2y4JXDsZk6oshkT4LgfSv8ONk0cfd9iw+t1WDP8iKgXOB+4uO/bqg0oq3zzbMu45XjisORhpIRMDRuGBtPHWu+NG843Cc8f7phn7wmCJSa0FnAofjjG8eTwgCHi96rk0LlBA0xjKtFMbBxlgeLzv26pzLjQOV2uCMd0zrDCEE01LR2sDrR1Me5z1vnqzJlEQIeP3ahL//zgXERFbkUjJvDb01/N59y9evT2mNZ3+k+eCixfjI/qgghpRNdGtaUpYK5yLnzcA7pxukAI3g5kFFMzjmG8MH1qKFoI2RbgicLnpePR5ztu45nIg0aysyDo8qcqlYDY7WWC46S9tbImkgageHVoLjSYHxgU2fWJEy17jesuocq6bFISl0pLORUaGYbyzEwEVr+Ma1EY11ZEIwrXPqQnF/3tG3lixT1LVCaUldavZrTWdSkLV2qX4xkl7QhyNJawLdMDCtc17aL9gMnqY3lIVkXAdiEFgfWZvAncOCQyG4d9GkYO6tvSxu6yFP1+m59B5KAU18alXTPN8AdcURxe0/z0otd7PgHSBZIGcjxWGdcW1WohWUWn8VQrRfiPeJHXbY4cuDnWXtK4X7wJ1nfn6J9F7wLP6bwL8eY4zAW0KId4FvAb/9sznEHT6Kn7bl7ePwByGjnlUV2RjSb45Q6JTTuukt3/5gzo1ZiZbyCTH17DGKCBdNssHd2qv4zr0lPgTuHtYcjwtOmwEpU8uZcf4J6bRoDJmWGBsYlQopIo+XA9n2nGRKYkLg0bIlV4Jl6bg+K7loDZNCYWzAiEidK3759oTffueSECLfuj2lGzzvnGzw48DRNGd1f41xkcF7gpL4wbM/Lrh30eNjoNQS4xWFght7FZNC4wJo4akLgRTJGrbsDWUuUAEGneJcIgKlBc4KhAxIoCoyrLP4KJASfvnmFCEUJgT264z3LzomleZOHBGi52xtcB7OV5bWeHyIeCLnq56L1tD0DuM8iw6MTxlHHmgjTyZR6w6c8U8KlCJpof+jdPKXiTiCRBSNM2i3z9ORAsBlKhwnEymfV6s0PyXCEGGqFHkmGVxA4JGkwicfU8D2z7WFTQjx54D/MnBbCPG/f+auKZ8+9/3cVg3+ICsGUZAyixrDWWNSoHaETed548EK4wMa0FpzNMppYuQb1yZ88+aYf6gllg25Ausj55uOg3HO907W+JBCkffGGW+fbvjBow2zSmOcodaaw3FGkUnO2xSc9trxmHuXHaNCUGWSGNKL5qI1HI8L7l22hBjYq3JiDJysByaVZuoCSgo6Y1k2lmldcDTJiRHeOdvwvQdLRqXmGzcmrDrDWydrHq4a7FxSF4rWeG7MSqZVxitHI947bzia5BS5ZNEJ9qocKSV7dcat/ZqNsYDk5aOavSrnwbxBCsXXr0/41vUpf/17DzlfGwbrCT4wEBAx2cVypdirctreMrhAbz0mgLPweG2os4x6WqIICCRaCzItaYeYXvAKJIJcJIWSlGCCZ6ILXpqVtINHxsjhuMRGeLjsUTJ+KGW/94LeJe+sVJJcafZKQV0I4nLAeYWXnrHSzMaaOwcVD+YDpZbsTxWjwaOFpLMBY1Ob2lWYWvcRqeSnvRAVPE1oIw1qzx/xucNXATnbNwsFRE/rkirwfGX5x79eo79ACeoLghfifWKHHXb4cuCzkEevKvhb/8sdefQlx+8AX982Pz8A/hvAP/+RbT4A/kng7wghrgPfBN75mR7lDh/CVXhvbxx5pgghPnfL20fxByWjkkqowoQ0X3m06tFKEkJk3tptW3fa96NFx41tdowSgihSZMjhOGfTO/rBsT/K2K9zbs8q8kyx6SwSwX6VcdEYuiE5FvbrnNVg2JvkZFJS547yIGOcKz6YdxyMcvaqLC2+W3j9+ojT5cAP1h2/cmuPUal5vBwIQbMeAofjgnVvWTVuW8CkaZ2nVEk5RQz0JhClp5eKZWOYVIo7hxNiiPzw4QpkCvb2ITBYhw+KW9OctbGE4FFKcDApma97RkVOlUusi5yve5wUZHlaUM9jYFLlFFoQYiKepkWOcx63ZXCElAgZWawdQQRKnXHR9lgft03dkpP1gPeOLjpiBDN4evO0XfujH+Q6/7TC/sp98mXEs/a6ACxt4gTybfsdpHmBEuAERJfIskqnJm88bAbPtUJvA7Yzlp3lTpVze69GS/lzb2G7BP4B8OeBf/jM7WvgX/6Ux74QqwalVtzeq8mVYDM4OuOYVjm3Dyq+c2+FFIKvXRuxaA2tMdya1bx+Y0IuJbO64FdfUqw6w3wzMClzbkxLCiV5tOk5nOR8+70516YlmU5/rM4G9uuclw8nFLnkdDnQe4eWgjpPAdaPFo7DOmdvVLDpLL/99jmnm4FN77k+K5CAioFmAGKkHTwIgSeSKciVQgrB0aRgr8qIAt48WXG2HiAKfvn2lEXjuGi22UazknXn+f6jNTFEDm6W3JwaMiUZaw17Bb3xOBeYjTJW/cB7ZxsmZc61vZJX9sf8Yy/v8ztvX3KxMRSZ4niccdFa2jYgBIwKifGeAoENnsYl1nSUQROgHUBITwieIUQ2a0ueJWY+IHi0aKmrguA9m86glIQQMUGQ5Qof4GIzYKzjeFKxX+W8f9rhIsTUkomP0A7JHysiZGogV4JVb5nVilGesTYW7yR5JpFCM28GbHC0zqOjpo+ejQ+4kFRIKj5taLuCIF3on8Ry6+2X4OdTBbnDlwOZSq+T3oMzUOcegeDOUYnzMX3o+hK2onwGvBDvEzvssMOLjb/yn/w9/rf/4fy5t/+7/8N/gpcOp1/gEe3ws0CM0Qkh/ruk7FUF/J9jjN8VQvy3t/f/O6RM1n9PCPEd0seu/1GM8fzndtA7YHzA+sCDVSomvzYpePnow2qIj2Ya/aSMo6twa+P8ExvaZyGjnrW/AVgfcD5lqRrnKbbkUW89755teO8i5d1KCTdmJYVOqqfeOQbnMc5DjEQBxibF0cEo53wzMCk1r19L+UOXa4MPsFdolr1HSYkSUGjNpFAIEvlS5RkhWH7vgwX3Fz3Oe0ZFzo1pCtb+u2+ecTDKWfSOUoF1ERuSEmivyniwaJ40ZysJXkiO6pzeweE045X9EQ+WHTcO6nS8Cs4Whtv7NRBZDwEGwcsHFXcPS2Z5TrtX891HC6yLCCmoS4V1glxGcukpdGAwgbYHEyJVLplVHq0Erx6lLN6TVYeQYGIk0woXHZOiRCnQBC6apEYaVwIRJMYm8snz48TRVclR3P4/009bsz8OL+q8S/B04Rie5uQ6EikmBeiYso+sh6KAWak5WTo6C4VK+bxSJBtbXWgOJwWTTFLnGQeTglzD5cZyZ++nI2yfB89DIP3bMcZfF0L82Rjjv/8Z9/9CrBpoLfkjL+/zn73l6G1ASsEoU1yuBzaD5e5BjfVpknbvomVvVPBo0XNzVjLONGfLnukox4TIH3ppj94FzpoUul1oybp3XJ9GlORJYJW1HiuhHSKXjWHwnmVzxjduThgXmlmdcTQumZSK331/zlljuLtf48aR9y7WzArFy9cmvHmy5rwx5Epy96DmaFyCgHk70NnIxabl8abHWo9WV/5dyarzHE5y5s1AlWnO1gP7dcHlZY8XcLZoub5XsTfKWbWGRWc5bwYOJyX9EKiUYL4xjAtNpjTXJjk/eLSmLiV1leERzDcDg/NkSlLkKWDtorXMKs3LByMeLg3tYHFBcjxRxCg5GCuWXQoXR4mtRzjjj78044PLlnZwlLlkcB4RAlWZEYHBWL7/qGPRWMoMHBHvAmWerD+ZShdaFCkAO5AIrd5H7l22jAvFtKzYdAOZlFvfKJxveoJzXLaOslCY6EFK+jZQZEl95D+G3b5K64enF/9HEUgMeviSsuM7/Gzg/fZ1QnrTkDLjZG14+6Th9ePZV6GF7YV4n9hhhx1eXOwsa19txBj/A+A/+Mht/84z/38I/NM/6+Pa4eNxZTkbF5rptYzBeWKE/Jk8lo9mGu3VWWpb/piMIynT/W88WOJDCmX+lduz51pc+zj7m3UB4wIhpKyfSkseLjrev2i4aAZ++eYs5fyYyCq3HI0E75w13J+3bHpHZy33LjsG55FScjwp6J3nfG3YqzWjMuPGtOTuYXzSNv1oNZApOJ6kQO0fnXiOJorbBxWrB4aLzcBelXFjr+RyY3i4aPk7bzo2xkEMlLnCrHo6YFRolp1BI1ESjA1Ma80xisetQwtASqTwLDaGjbG8f9HSGYcSqbnsojHMSs3gBJmAcamIMSZllog4UtHSshsSgYemGCnGZU6he86WPTGmXKIYNM6BloKbs5J5Y/najTG9dTyYd8QQybSgzDIetB2VUMwHS9OHlFXkwAZPEIJxEYk9yI80WwuSLcv5RKDURWreDvHHiaJ6mzX7IhJIkmRFCz4RRo6nc0hLem6RlIk0raHMc4x1TAvB2kach1EJ16clB+OSutAcjfNUroXgYmMwznN9VnPtOZsafxo8D4GUCyH+BeCPCyH+qx+9M8b4//lJD3yRVg3GuaZQkm/emPBoqSHCvHUcTVIQ9t4IehPQWtIbx8mq5+GiY1IqXr+eQqgqpZNnNFoOKkWuBe+frnnvvGVjHLf3KqS4SvKPnK2S3/NwnJrNpAgcjQq+cW1C4zy5TDat1WCJIXLZGVad5Xw1sJCSX3tlj19/eZ/3TteA4J/45jXqTPH+ZcMbD5bcmJVEBJXWnK8NVRZYdwZfaNadY6/OOZqUFJnk/rwnhp7GeL5+bcRFZxk5cD4wrTRFphkVGuM8yzaFse2Pc84bwx99ZcxlZ3i8HCgzybVxwfl6YD0YrI1UuWBapoC6VQvBR2ShuL1fse4Swz6tMqSW5AIGZzgY5fzKzTFvPN6gEamOUYBUUBaab1zP2QyWZvC8f9nRDw4fAqiIi4rLjcX6wKgsaI0FBLNKopTAWM/GeAQBEQQ2eqTI2PQ+VXIi6V3KZcq1Quq0mtEbx7Jz+JCIqHGlCcHzeBN/jAl/ltkuRPKiCp5a3SANDMPn/ULe4RcOz4b/eQ/tYLheVSw7y6NVx7du/GKvoL9I7xM77LDDi4fPQh6NgO/uyKMddvi54qOWsyrXNMNTy9lHSR3jPG88WHJnryLXkri9/yrjKITIorW8fFATSXOXeWOYltmnTpCfPZYrBZJSglt7FVKmqvN/dH9Bbx2XzQAI3j5rmNYKESUP5i2tcXzn/oIb04LDoxEX64FFZ5h3FiUFy95yNEqlPMZH9pTgdD1wa1py56Dm7n7Nb7xywIN5m8qHQuCPvrpP7wKPFgMxipQLFFNgdaUkm86z2mywMTIbaVa9TbEkg+N8M9AZR0zVULQmUGrF6bIj04ppqZERfnjS8NpxzaNFz8myZWNS1kchBS5ENsZjHTxet+xVBZNJyvHtXWSUq9SepiSZkhyOct497wixp+kdvSMpiZRKAdARWuNZd44zN+CCx/nIjb2Ck6Vh3VpW0TKEyGo1ICQInQqLWhvRGmKI5FqzPwqsu4D0SWljQiJaWvt0/nXZpNskT/OQroiYPqbbX0RoYJRD7NIxfrRH6WpuOZAynzatoSiSgu8ISTuY/z97fx5r+bbg90GfNfymPZ65pnvr3vvmHtztbjuOJxKM/wiJRGSDFQhGQg4WiUgco4CgkWI7cQggARYxg4wSy0ogAkPAxsIh6uDYSdrYeenXr/u1+83vDnVrOPPZ029aI3+svavq1q17b9V9VX2Ht79S6Zw9nlXn/H5r/9Z3fQfyXPHK3pDbB2POli1N7xFK8uXDIa/sDTA2Msw0lX55Fc7PQiD9c8AfB3aA/8oTj0XgAwkk+PTsGnTOc9lYbkwrDkYFZ8uey7rj9u6A41lP0zla6zgY5lS55uZOxaJNf9YvHozxRG5MK965bKi0oneBs2VPUWi+fH3Cad3xrXd7vnZjwh/88iEqRn75Oye0znM4KikyzazuWRnHWd1zfVJysTLcuVoxry2r3mN9oMyS6WnV25SpVGYMywJBZN5YFtKxNygwLlJlknevGowP7FaaIsuoMs2ic0gZOF10vH44YF5bXt0pWPSBg1HO/WWP9IEbr1a8sjfgZGGQfc+gLFi2npNFjxKBGCMZgrdPGw4mBXfOax7MOw5HGeNCU+iMcSVBgJaKWeOYFAoXU3i2D6CkZdUFpLQMKLAhTS6vTEpklpEphbce52yy6UlB23tqPHfOavbHOcNc4b3gvEn1l54UFK4kDCtJoXOWrcWFNBFaHwhrj6wPHiQYH+mtZ2k9lRa0nWfZQZV7LmYNtYHWQJWnCShTJIJJPmKCLY8mqHx9u9SJAZc8msQ2UsSXWQn5NF/wFp9NDHnUvOCBRRcY9p7aOPbX9tTPOz4tnxNbbLHFpwd/8T/6T/kLv/y+Eq0PxN/4F343P/fKtZc4oi222OJZsLGcOR/QSqbN28csZ08STFIIOuN4sOyQ69cOC/WQcNo8XwjB2bInxEhvAwfjgnGZPdNY6s5y1VqMDfgQORyl1xa54tq44GQVOZoU1H2gMY4fHLcQYX9cUOlEYtXGszMUCCEwLiAFZFJxUXecL3ve2B8xXLe9XTQddy5qIjxUTH3t+pTOeUSE40XH8bJFAKeLnEBktuoxUaJi5KKxuBhYGY8UkWVjOV105OtYlkxprrqOt85WjCvFa3tDhqXi/qxjXkekSu1tbV/w5tmSB7OWTAs6D5VWeO+YrwQ6k2RCsGxbrNUMq4ydquCyNRgX0FLQucDFsqezHutTIZQLSf0zq5MlLsbA0aQEKRnkkV+/O6O3nsvaokRASYXEEzzr56eiIhvT94MsVRGXucBYiSYQ1HpdFR+5OSSJVOriI+LocaVRziNV/6cRkdQcB2mcH6SSCoBfE2emg8727I0UIULXOM6WPaVSBAHeB3ZzxaDQnC979oYFh5Pipa4fPpJAijH+CvArQohfjTH+5Zc3lJeLh5NZSJWLB+McKeB3v77Hmyc1gUiVJxLkfNlzvjKMCoVzgQBMi2SlujYu0mQYPMfzlvGo5Kru+ZnJlNNlx629itNFjxSwM8g4ftChRMosGpcZo1JzNMr53smcH503SGBYZtTG8dbZisNpybSQGCfwziPQ5AqKTHN9WnC2tNy9auic5/6s5mxhCCEghORk1VBIxe4w42du7hJEoOkCUgkaC6u2x0VB3VtChJNFiw0ps+l41nEwzBM7vjLsjArmraWznsvWkGWwM9T8gwctdW+IEb58NCIgGFeS3njGuSJKlX53pWbZWoQQHE5yXIg4H/BE9gYZLkTuntdoEQlC8NZFi/GBo0nBvHXcn6XbrYuUWpCVGa21eCKNiXjvySW0nSUEyaL3OJdOzFGRTjwlk5yPmJromjYFqJ+tImFzUho4MWvZIJBH6NbGVEEKLttMUJDCzbRKhNJGXeTje72shQQVXq50cksefX4QZArFW5l0zFgPk0pxczJkUGYvzb+8xRZbbPFpxday9vmDEEIB/3aM8b/1SY9li5eLx5vPeuceWtI2aqH3EUwhMO8c0yqjyjWdcVysDF8+5OHzBSngOtnaBDFGzpY9w1x/qApJSsHRuODX7lyxeVqIgW/dnXNrt+L6pMT6wNnCoKWisWZdK68IMXCx6rhYdEQRWbSWnYGnc55Ca8o8xZxorVAy0lpL7wM3dgp+dFZze7eiKjI64/jmnSte3Rs8JMgmg2xdBARIwc/dnPL/e/Ocd88bRAzkWbLBPVi0tNYzby3ORby3PFj2ZCqRcqvekSvF8aLnnfOG1gRyCXkeWUWYLjtqG8mkoLeQacFV3dLbpOLyUTIuNUII+hBYmZYo4K2zFZeLnlGhGVcZEYEPgUUT6UJaG0kJKws6QKEF10YFJnjOlj3eJdKvs57WgJIOAQiVCCARk1Mjkjbv94c58zYwyCQiBq6AlXuUObshhALpRU8SRxs8qej5tCECYR2Oq0KKrvigKKfNOlMCxsOi9QwLze5I0VtP4wJlJsmU4u5Vz42dnsPxgC8fDsm1QrzExeKzKJAAiDH+ZSHEzwI/DZSP3f/vvIyBvWgUmeJL14b86GTFIho6FwgR3jxr8MDuMCeEyOWq52JtbXLW0/rAyjgORyUHowJZZVyblNy/anAhsmyTlep43vHuRcPBqGDZOm7tlIzLnGmV8dZpalf7qRsTBpni629f8vd/eMYg14wGGeM8T6n3o5ydgWZeW6pMYSP0NvDuVc/veHXKu1cNFyvLoNBMtOLerOOyMVjvafsUvLszzdgbFnTWsew9h6OCQVR43/P9s4a9gSJEQabgN+8t+cXbCusCSkTevqhx3pFrQakFkyJn1hjOl5aLleFwnFPpDOMs53WyyI1zxWv7Yy5WhsZ4jmctzkda45i1llwJlJQYZ2msR0bPoCyQmcSH9MExzAQXdY+xgTtXHd57nHOMq5xMQpll66wlhTMOQnx4Mh3P04RUlQKVQW0j41KjTGpw603KSVIOGhdp1pPRRsHT814yRqzVRBvf7cMJTsCkSBaj4KEXyXJn13lL1ZpF39SDlhrmH9VR+PjPZUsK/aQiBFia9GE8ymE8zBhqze5Yc2Nafd4DtLfYYost3oPnIY/GwG9uyaPPBGKMXghxKITIY4zmo1+xxSeBDwqyfl6UmeL23uCp7/UkwRRC5ItHQ3yAxjiUFOwP84cKCilTadDdqxYpUzP19WmVquCfIScy05JrowKlBGernkGeY3xAiVR1DmuiQsC1UckwU9zYKfnRyYoiy9AyhVR858ESHxz7wwyTR1atw4SA6TzGg7WBQZFxueipMomSkhAjuVYcny7ZH2imgwIpYdk5bu6U1J3he03LnbMOH+D23oDjeU0mA71L3odxIekd7E0rHsxbFnVSYfmYSJwgIp3x9CZgPTgHJgaGGayMw3iQWtMay35e0JqIFBHnAl54LlapWQ6vCELw3XtzVq3BImisx/jAsrWUpaTwEduvw6xlIo/GheDGJGfZWVZ9z4/OWpSEKNIYIymvNl9n//iQ1l+b9VilJcsulSy1VjNrzcPN/MeJosBHR4Pkz/CcTxqZSmtIYz66zh7S/3+koco0w0yBAElkVKRyqMkgZ9SaRAIax/Gy59pEcHfWvidL7EXimQkkIcSfA/6LJALp3wf+ceBXgM8EgWR8QACdC1iXyI2fvbXD/qjArJndm9MKrSVvntaUueLuVcsgU+RaESMcL1oWvaUxSQmzP8r43vGKedMzayzXJxUns47WJgXNtWnB7YMhWgrOlyno+t68493LGk/KzannHWGcqusPRwUny566t3gPr+xVeCJVprhcGaZFxsWyZ1wI6j5QKMGNnYpVa3mrrdkfZtzcGaCkwPjItUnBzemAy8bwg9Mlwzy1ytW9w/s0ecway+my42duTjkYes5WSbJogkcLTW08rXEsO8+s7Sm0YNl4hlok9lkIrpqecamQMrJvMy7qnrfPa3yESam5bAzEiJCKKgMfIm1rOOk9O1VONSlZmsiisewMMgot6aTi1d2SWeOJMWKcRwtojafpU5BaocC4JH0stEILgYmWet1OoEnySHw6SYd5OlHb9TGxsZvJx74uwqNO8QGPmgD6CKpbP08l1VHw6blawSCDej2hKp0Y9meaFdbYkkc/uehJx6IQUGSSa+OKvUHGV66NPlKavcUWW2zxecG/+fd+lX/9/3XyzM//9//F38NP3zx8iSPa4iXgbeDvCiH+BlBv7owx/oVPbERbPMSTwdY/7uJTSvGB5M7jBJOIcHeWSIdNy5oPvEeBPcw1t3ar5OrIFCFEYuRDVdobMqw3npNVT4yBq8ZxbZLcJHmmWLYWrSQ/f3uHk3lHINJfBfaqnLNBgfOBZWdRAqZrAmiQKVyMNMZRZYoHVy07g4JruyWFFJzUPW+d1dy7armxWyFj5PvHS2ZNT6YUbxyOOBoVZFrw1755nzvr8O7XDsb44KmyLK1NveP+rEkklNI0WYrkuGotMiRLX65h1hjwAS9gWgqUFizbwMqCWFlu7Q6YFJI7vaXpLTYGtJS0zqIQmBDI+gwXDNZa+jXrU2jBtNIYF5PtzAtcfETQRAtlBlJKrlqPCTWjQmGsJ1NpDeXtOgBbJuKImFRCm9xYgNYGBnlk2UUWnWFpPr6L49NOHnlSc3jjk0hhY7n7MIT1vxgDxksQEq1TSdT1aYWUMCoU06rAry2CrQ2UWXhPltiLxDMTSMAfA34e+GaM8U+sm3D+rRc6mpeEECJvna1466xhUmqWbWTeNNyfJbZ3b5TjQ8QRKbRKAVTOcTTOOV70WB9QQvAb9+YE79kbFczrJJJbdQbjPfM2cH0n8mDRkmtFZzyXK8Gi9cya5EcMUrBqDJ317I8qgg+cdJZZbZkOM17ZG3C+6rm9N0oe3wCny45hrmmt4wdnK46XHXeuVoAkl4JRlTHKFdcmBV88HHE0rrhsDM4H3rlsuHfVoyRoKbk2KdmvUjZRGx29Daxak5LbY2RpHK8fjJjXKajtrYuaSiedXe8ip/M0+RZaoquM1ji0EnQmMsgEq9Zx1TkezFtWvWdnkNFZR2cjxgWq3COCRuDIZUbTO4pM0RhHJGJj4LLu0VLiQ5KmKilApKynMtMgH01IOhW5YQMY45GFwlpwzjPKFRFPG5PdLM9TTfp7AovXXyUwFDycFDdkTkc6YTfqoPqxF2akk8eSMpDauCaZgOjAfNo1lFt8alACuxVECaNCEoJHKMVV4+isZ1A8zzS9xRZbbPHZw9ay9hOD++t/kiQg2+Il4XmVRE9rK3tZi88NpBQQwBM5GhecLntsDO+zvG2ee3On4nje0Rr/vuc8+f9t+rSZH2PkZNmzP8hYGIdxHfdngd/56i4hRDIliaSGuFf3BtS9ZZgpijz9Dpo+pZrOWsdkkJPLtCay3qOF5J3zBZ1dt7GZjLkP1J3ncFhyvGj50cmSq8agiFgv6Kzj62+ec32nZLa0iBB5dT+Fh1/WPYfDDJUJjhcdWkamVcF87TZ5+2wJBJyLTAeaVe+QUVBI0JlE+zU5YQI+JGtYrgSKwP25ZZQpRoVg1St8hN1BkWxpM4OI7cNMIu/BBehdoDEdhYLOQhN9Kj1irSoCijURgoic14bWJMvbrLGE9bqrVOsN9/U668l8oqUD3UaEgNZ9OtvTXhQisHCP1pofdmZtfs8FQIDep35vpUve2B3SuVTEFULgy9cnvHNR8+rugL1BSQiRq8ayW2Uvpc35eVYmbYwxCCGcEGICnAJfeKGjeUmwPnC86IgxUpvAybLnorZcmzh6F/iNdy6pyozDYUFrAoUWGCfJlST4wO6k4GzZMVu2DHKN95GVdSwax+FYMRQ5xvXMlsl61naWB8uUTTTINb3xLKVlWmb4kMKpZYyYEIk+eWZzI/j1O1f0PrI3ymmNozOWeWcIwWF8RoyRpvfsDDO0lCzbngdXlkmZEUJk0TpWZsXBsELLCJ3luO05GOYYF/j527tEH1jYJV0Pt6YFnUvkzvG8Y1joVG8ZAkjBZdNzVXdUWc5upZi3MFsFWh1YdI6dSrM/yhB4fuveMoVxS1i0ls7C8dyyMwSxPmidgZg7dnXOoNDMGotxHrveHfAukmUKJaF3kQdXPeNKowVkQpBLgchTw5wlZcVomRRAELmqHUKACOn+PCsYD+FqZei65NmVvF/t40kqpsdZ68eZ8aepgzzv9dma9ZMlj6xsm5+1VRdt8WFwAEJQaEGmNUIoplXG22cr3txf8tM3d7Y2ti222OJziy159JODGOO/CiCEGMYY6496/hYfDx9HSfRksLVWkt65j734fBYC68lxHo0LMi3f85rH3+eDbHGd9dyftQ8zlXaqjG8/WKTsJLlubetSY9rBuOR00bPqLWORc2OnAuCd85q7Vy1XjWFnmHFdFtzaK7l32XJReyKCnUGOXNsWjlcGKVK4c64k88ZwvlKcLQ1lrnnjcMTOKON43rHoDIXOqDvDybJj1aUVxN3LhqvGMq70mqxxzGVk1jqM88hcczDOkAKWrSXXIeW9RuiNTySOi1gimUwWPKU0mQjoDXkkJJeNhRiJSiKlYlAkZ4fzkeBhWKTOss6neBdiilfwMcWFaJW+CtI16+Prmj7AvE25UI2By5DWgmLdnpYB41JQZpK69djHFluCR0SEj1BmgpGIdJ9jBmnzuyuBTMDqQxaJESjlo7+FijDKNNfGOdYFvI801lMKSW8D41LTOo+xnjLXNMYQxcvJUn0eAulXhRA7wL8JfANYAV9/4SN6SZARZp2FEGmMZ5BLfng653iR2Ok3Dsec1z0Swd4w52AkafocT6TMFHdOaxa9Z9ZaOudYdoFV5xiXFcZaPJKTZUOZa6aDnJ+5MUYiuT+rEUqwMhYpJbM2fT1b9UgiP3VzwqDMyKTgwVWDloHfuHPJ/ijjwbxPftEgOFu15ErhgmB/kHy8dWuIQiCk4Nq0wrqIjAGtkm7mYFIxHhSJCV71XC47pFSUWnFtWqC1Zk9LlADjPKNSsew9Ugq+e1wTQ2TVRySOs84hQkBrqBQsOjixjkW/4NbukItVi7WO2vAwzFoAsxoUkWEBXkDTgaQFGTkcZ9QmcLnsiTEiCBAVzkOlBY1z5DrnYmXoQ6RpDIejglI5ok+5RDITDBRkSvPKrmJUan54XHPVenKbmHLnklIp570hbPKx75v19xu296NIn6el+29a2B4P1N6SR1t8FBxw2UTyPH067AwktfHMTmte3Vvx5WsTCvnyqji32GKLLT4J/Ft//xv8T//68TM//9/5kz/LP/Kl117iiLZ42RBC/D7gLwMj4LYQ4ueBfzbG+N/7ZEf2+cHHVRKJmF5rnE85sE80pz0POut5MGuxPpApyY2d6n0ElnOBO5c1mRBUhca5wP15y+2dAX6dMWHWY3chQISbOxWDQr+H0Aoh8s55zWydAeN94M3TFWUuGZYZXe+4ag2xTvlCO1VOrmRynOyk6JIQIloJikzyhYMhxnt+/d0rzpZ9UoHHyLTSOO85bkza/PYp+HvVe8alom4dx/OeQiv2hxnHs6S1eftsxbtXDUeDDITknYuarg9Mq4xln4JZQwjM6p7TWUMzqhgVilGu6WNqlTbW0TtHlStWEarMY0Kk0IIQIBBpLWQaok+b6ZmWDAuFIOUilZlmd5jTWEdv12HMpeSdqw4pAoNMc9kEvEvqo00zcEZyaBjSGudJbseSFEv12p0RALleJGUqrYVyCZmQKOnZH8B586jZGtLPcgEIEfcB5JFcj+XTblF7FhTAoFyvObv3P56TfieClBuFSva/LEJeSB7MespCMtKa69OSW5OS/VGB1iK5oLzHtpEQ4eZLylJ9nhDtzeT+l4QQ/wEwiTF+a/O4EOJnYoy/9aIH+CKQKcl4oKkfGE7nhlXv2RtoQlS0NtBZz8msZd4YvnA0opul2kIlBQfDgou6p/GOQkm6GHgw7zAuMC4zRIgPKxmliDQmYFxH13tuTAsOd0pe2xuyaA3nS8NOmfHawRBB5HjR8/O3dzA2sevfenfG8axjZSx3LiWTQjPKMoaZZuU8VaapjcOGQO8i02HB68MMhCBXilVreP1oSCYUb1/WnCxqdgY5k1JztuywPvDFozG5yvn+Sc2+1miVvMar3nNzt+LOqkVJgfeenVFJ3Tt6Z2mNobPpYGwta28yYAPHl0u69YTDWn2TyzThaAnOJ+bUehhl0NrI+aJnmQVKJSgLRaYlk6pASsm8N0QfmdWBztRoKRlmkgcLz6rvCcAkT6FrQYHKUkbVqvcsu+QB7hw0LjWiVUXKK+p8CreOLk2EmkRC2fhetdHTJshnQRIWvvf2Fls8EwR4B7NVTwbsVJo817x1UeNcoHgJAXhbbLHFFp8Utqqjn1j8b4B/DPgbADHG3xBC/COf6Ig+Z3hcSRRiWqK7ED5USbRRAtkQOL7o2B/mVLl+n43sWRBC5J2LmqvaIKVIpJQPfPlo/HB81gXeOl/xW/cXFJlkWmZoJVl1ljuXNTemFYVWiYCSgnlrMTa5SX7x9u57rP3WB06XPeNSo5VMDW51w5EuuHeVtodXrSMQcTHinGd/VCAiD0O6fYxYH5ACbAx8/2TF8axl1jm+UuVUA03TWb53vGR/mKOUIhBYNo6vXh/Tr9U8mRL8wms7NCbw/eM5rQ1kIrI/LnjztGZlLJHIuMpxIZE/zjreWVgyqZhWOUpGLpY9Va4JMXKvq1n1Fg9MtUwZQlqyagyDXHOxTLm5XsJQJqXQQAuESk1dnY1MSoUPjtb5dTaHwAW4uzAsW4+NYDtHa9I6RpLWQYIUF2Lto831p0W8Pk4EpVDslFEr1i8wPtI6m1rgJOT6kdjAr39e9HDZfnh87Ochef+h/c+nOJanYSNyGOikKosiWROjhtpEvAsEAqVWKJGUY8veklnJ7kByOCxQUj4kXF8GPta7xhjffsrd/yfgF3+s0bxEVJnm+mRAJjTOO965aAnRc1Fbro8LskwRgV+/c8XhqODGzoBcyyRPDJEq17y+P+T+rGPepIDoo1GOC6CEZJhLLtrIqMjYrTRSCL5zUnM0zMik5Gs3pjT9gqvOsOot89bSuzRJKK349rtX1L2jLAW9FyxqQ5VpMi04qw3eB2IReX1/mCoalWBQKCZlahKYrQxBJOnmuxcNmZRYF2mN5xvvXOJiZH9UYH3kwbxn2VqUiCiRU5tAkUnOl5ZApO4cZa7TJJBpeutRUpFJ91BGF2UijFYO8ghVIZNX2KbJoNQwzdIJ0ol0wowrCE6klrY+sOx6Mi34YjmgKHOWTceyNaw6SxSJde0deBW4qNdBw0BRrCsgpUgHsAssjKfrk5RUikcSyz5A5UFIGKw9uEElUkuLJAcUJI9uzppJ/zGOs63iaIvnhQYGeZKyxnXG1+mq52vXcyBd2GyxxRZbfF6wJY9+shFjfFe8V9XyOTas/PZDrWvi685ytSZefIzcnFZkSr7v+Y8rlqq8SMoXHx6qc54X1gdOF48IHbe+fX1SctVYXAgpmyhExlWGjJEfnKyQIhCF4GhUcqkNNyeppW2QqyQEqDIWreH+vOULB6MPJLaUFAghCD7Su8hV3WFsYFgovPecryz3rlKdzv6kYG9YYF3gbGk4W7RcrHpqZ4lRsDfIWFnPSAp2RgU6U/z0jTGDIuNq2XGxPKEzltYlNVCVafaGOb3rqI2j7h3DXEOAKlNkGnarnPN6rb8RgJSECFoKPND0AesDRQg0NrDsDfvDtN5cdg7jItNKEQqNkIpRFVl0jkKCiZIgAvM+Mh4kd4YzhnnrMBGGRU6mNK/uVXQucn1Y8s07Cy6XnoV7RN5sTshIWlfF+IhUetoRsblKzUgkz2LzRuv059ama10BsG4g2+TIBmCsEkniPoQ9+rxEgmzWmk/Lys1Ia9NMgZJJqKElLPq0Ji60TiIHAfsDzcGoYJBLjuep5OtoVPHFoxHXpxXjMnup8Rcvkpb61IZ0+BgpMsVP35zwK98/46K2LI1jkAlCFMx6h64Ne6M0iUgpmVRZUua0jv1xwaKzdNbTGIegIgjBF44mXCw7osqRCIpcY2OSDS47z/4g42u3dpBC8Obpiqu6Y9E7Zk2PRqG14M3zmoNhzoNFhwsRKRU3djSXmSbGyP2rFh/SyXt9IpFS8Hve2OFgnPOj85qzRc/FsuNkaTkY5cwbz82disuV4ZW9ip1Bxg+OPUIICik5X/XcuWrorefqvOfeVU+uBdemBcQ0CdVdysd/MOvwwVNkkv1hTu8U56ue3qcGNCQUep0H5AI2pKazVZtazzoPNyaKYRRcrhzLJQgiSiQWFUDE5PW9Mc1oTSQSGJUZxkUUntpFFMl/mwmQGoaFYtV5bIhkCmofkQK6uJ70YjqwNwHYNqQTUkiYVCnXyreJXNqohAoeNa5tscVvJwJpp2Y8zGisRRHRIuI97JX5Uy/4tthiiy0+a/i/fvMf8Et/9Z1nfv7Wsva5xLtCiN8PRCFEDvyLwHc+4TF9riBlyhL6tTtXSAG5VhwNMk4WHTd3Eon0eL5Q5zwuBKo8tb7mmcKG+FCd8zhCSEod4D3v85EIkZNFylrNlEIAV11qvz5ddlzUPXuDnKNJybDUXKwMt3YrQox01lNkis44tJKIyHvUVJmSHE0KLlaPzE1fOhoxby0ipuKjnSrj7lXN3/nOGUfTkhu7FbtVzrfvL/g9r+1xsug4GGWcLBq+/s4l89pSZoIvHI2ZVjm7VcZkLQ4oM40PkVmXcpHeOa8pMk1tLMeh58GsIc9TlqULKbdp1fdMB4rz2qOUxIbA3YsGG1KLm1aS2nq888w7t85TjZRaoCVMypxl7zGmx/mIlhnZ+jGVCVZdUqgoFQghKZCGWjJv+zU5laJczleWw1HKqO1dRIQ8rW/9B7O4jkR66HXe0wd1BGk++D08SQRgSGvDnEREVZvH1s6RD8PnZX3Wk/KPLFCIJMrYHLmBRwTSsEyGwN6BxKMzKDJNoQV7WiG1xIVAYwI7g4I3joa8upssmmfL/qW3OL9IAulT+7fd+HcvVoadYc6bZ0us9xRVweFU0bWWGAIHo4y6d+wPM3rjU+NXCLy+M2LZWv4/37qP94JhJbk2qThb9RAlXzwYsWod5/WSSaH46vUJb56v2B0WvLY/5LLu0+Q0qXCzhjuznlEe2SsznE+Eye96bZfvHq/onKPuPNY6jBTcmBb4KNCkrKO+99ybNdyZdSwbg42BcVlwbTJgOsxpjeX+1Yq699zeH3L/suWqNrgA3TDw7nlN2zvKIpFk89bho+RkYXj9MKPtPRLBZWuIAoKQKAXzzpPJwDCXSBFQUtC7mBrRYmqPygP0NiBlsrAZDxe153HzjSFJGodyLWNUGcYFzhaGZdeTa4WQMckbg2CUAwhqG9ayTGh7j/NQ6kDbJ2YbEnO7mbwcabKSpMW5D3A0UWRKswqeXDm0SBPZJq/pI+auLbZ4YdDAWEO9bptQCrJMMZQCrQVVnlHlkoNJsSWQtthii888tqqjLdb454B/A7gF3AV+GdjmH71gZFpyY1JS5AolBMYH7lw0WB/IteL6tATgeN7h10VDkrRo3WQficjDFmopBZ31vHNRc7pIy92jccFrB8P3ZRtlSnI0Lpi1BuNTcdDeOEdKgVaSECNlrgiriAAOhjmTKuPaToGWAusCkVQydH1S8mDW8aPTJVIK9qocV8b35DJJKbg2KTlb9PTeUyjF6/tDzhbdw6DoH52tsM4zqjS39gZIIRhXGVe14aoz/OhsxaIx/Orbl1RacXCU01nPj45XrDrLjZ1rXJ8O2B8F6t5xvOy4XPUcjArue8/3T5c459ipcqpxSds7JmXOqrX01nG26tmpMiSC+7MGGWFvUuC8xkbBuIK3z5t1phJMCiBGvI10BurO0DuYd8kxUhQ5UVgGuUKrks4vWHSBKlcUQZArsMHTO9LzFagA3jtsSOVOrYscz1Y0faSPj6xVT8KztlSt26o/jGgq1v8a0prsPWVDT3y/yUsKwNx9ikmEl4BN47eL71V0+fV940IxKhV7wwH3Zy2FTiVgCkfwgpBJ3tir1q3xkVlt2asKYhRIlWw/L6N57XH8RPRDSynYH+b82jtXFEqyN6rYGxa0NnBjpLl7Jbi9P2Cvyrn9pQHvXrV87+QKHyKv7FYcTAqmVzlfuT7GRYEWkjKTHIzgYFQwKQvCNBKIrDpLax3DIuOnb0zItGLgHFKkk7g2HklkZTxhFjnBUmrFf+FrR/Q+8vd+eEmuBa8fDSHKVFVJ5GBccFr3VAPBt+8vuLlb4QNY5wgSylxyteq4O+9oe4cWgstVz2XTY3xAS8nFsqMxjkwJBIFFZ8m0ZKdUOCRni47JQCGFIAoYVhC843JlaLueOq6ZYy0olGKn0rTGoqTEx5ByjzwMCygzyawJGJNkeJHEMKs1e92Ydaq/s+wOC7SCyaBgqDW1s3Q+0PWBYZmyqA4nGSez1O7mffLP1hZGeaqW9E9MapsAayUTKy8jnK48pfZYn5RTzkO5Zr23eUVb/HZho45rU9khwwK+fDCgtp42RogpPDHTkuuT8qm7gFtsscUWnxVsyaMtHsNXY4x//PE7hBB/APi7n9B4PpdQQqDUo+Xjg1lLrhNpEkLk/qxNeaVaUuUZNwTcn3dcB7SU7Awy7s7ah+1oB8Oc+/Nk7xqXaek4aw3ZTPL6/vBh1tGmHe3VvQFiBtGnduXrk5LjRUdnHHmm2B/kLBvHorPI9fPb3mOF46p1vLJbEoXg1d0BPgQynca1yXd6HCFEZo3ltf0BQgpiiJytekwIvHVe4wO0xjEtNWcrw+ubhqrOIgTMakPdO4SCTCqKLDLvLONcMao0X9wfcGNS8uWjMS5G7lzWzDpLWUhWfdo4N85jvOC8NkREsuJNIrd2St46W3G5bJnVHRGBc47beyOqXHK+dCxaw+EoEVZRSqZlIALzJuBDWu/cvzK4mFwet/dGjArFxaqnNZYyU2RSMMxTMHljYlrTROhtCiKvSVmwSe3TkmUZ40JwPPfUz7gAGhSwaJ9yrJEIr3otoxEyhWh/lC/VktZqH6Zc+qxB8yjX6cOwOYI3pJokEXilgjJLTWtCCN4+q1EyWVIDUPcRrSRVCcNMIYVkd6gRUtBYR+c9X7s+Su7Il8zIvUgC6VOdbVVmiqNxQZ4JfIQfni7orEfJkq8c6YekyQ9PV1w1dn07Mm8t33xnxrJz/NSNHZZd8rTOGsvhpOJ3vrpL4wKd8fzeLxzwU9fH6EzSd55fefOCzhoyqdgbFvTGMygy5o3hcmUZ7JaMC42SkouV4Q999ZBCCToX0Spy76rjld2Kk3nLu7OW82UK+TldGhASQeSs7ul7z42dkmmVE31EC8F4kPHmeY2IgTLPKLTg+KShNZaYaXwUNMYxrXJmjWVYZaw6TyZyrjpDbyNCJBrGBPDrvKGdQq1JmciytZSFotQZiECVZTR2Qd2mCQsSI70uT2BYQm8gCykbKSdZ0qYDjSJye1zxYNbSmSRZjRFKrWgtCFzyf2bQ+xTQFiIUSlLogPfQbFL/ecSkt2EtFRRg18HakvSg8cmHm60Dyn4cFunjBm8/DRvW/oN2A7b47KLgkec7BBhXgjJXzLrA3iCF2u8ONWWhGRQ5y8699A+BLbbYYouXgf/v997kT/6VZ3cn/aX/9lf5L//Ul17iiLb4FOB/y/vzUp923xY/BqQUXJ+mDCHjHNZHbu8n5Y1UgrpPmvtNwO6ozLgR4cZORS4ld2ftwxa3urP86p3LlHNqArd2FYVWGB9wPuUrGZva0sI6IBuRsoiihN1BhvWB3nrOV2mpOK4Uh+MctS7yqTKBWQdp35hGdoYZB8Ocu7OG85VBS4FxAa0EZ8ueV/Yc4zJ7aMHzPlBVybITROT0ouHmtOCr18f86GRJHaEqNF8+GnFv3jEuNUKUfOlwyKpzqRGtTblExjlEFPQ+2cgWvee7Jyu+cDRmVGZcH5d85/6cHxyvePNslRqrW0eWCQICrQSdC/jgWfWBWdcREAwzRW08y95zVhv0+rbznkVvKTJJIEAUtH2kTb9GhEtrjCCSQqx3gcyl1xEjSoIPglkNMUayLG2ab/KyjX+0vFFAYyLCGLq0lKQCnsILvQc90D/2pMfXJx5o+3Vuj0ib/M+6nHqyfOizjsgjAcPzLCk3TXWDQmJ9oHOBKtcY78mEInrPuMgJ3nE0yRkVmmGV4UNMrp5cMS4zhoXidGE4nBbcnbVcn5bvUwi+KDwzgSRS4t0fB74QY/zzQojbwPUY49cBYoy/96WM8AUhU5KdYcabpzWtcZwvDbmWKCLzzpNrSVj0/OB0wap1/O4v7NPbQGM89Ua1I+FoWtJYy8Go4B/96iGXjUERORjlvLY/ejgZL6Vlf5QjRGLkL5eC47lllCuqQjHykUGu2R/mIAXvXNQsWktAsj9aB1eLnqumx8fAvO6ZForeOWrj+P79K4ZVzs4gQ0aBkilEa1xqohAYG1j1hkGRMSkkJ8uexngyKfAhUrc2Pc+F9P69pTeBO7GmKjLGZUZnHd55gnNoBJmSmBCRHjQRpRTjPMOJpMpSSpBLSZsF4jpfaGMP80BnUvD2Jll+WAnmTWS56okC5o3nsumptESKyM5I44KkyqGzkUx7fIAqS77rpvV0JqBlIoA2Oy2WNCFqnSZeC+jw6PF1AQFmncgmSJPtj4MXRR5tQuVgSx59HvF4/ei4JF2gCbX2wGteGeeMqwzrSRc1Q71VIG2xxRafOWxVR1s8DiHE7wN+P3AohPiXHntoArycFc5nAB+VKfS4qud5A3HLTHF7b4D1qWBHr1/v1rfFY987H1BKUurU3NX0lukwJ8TIVWvRUpArTWsMp4uOa5OSGOPDTKJNCLeUkrNlt85tLbmzaPjGnStihBvTgtf3R7TG8VsPltzcKTEucLxouVgZXtkd8OWjEdNBzsWq5xt3rsiUYNE52t7SubgOk47cvWp4bW/I6bLHhWTBuyESEdave+CDSNElPsKgUNSdS4SF9ZBLvn1vzrfvL/DBkynF0bRgf1wyawz3Zg2llnzhKDlJ7l02/Gc/OuO1vRFvX674zoMFi8ZyuTLMmx7jI1OtCRHqzqMySdMaTleG43lPZwJK5HR92iB/cLVCxID1kTzPKBRMqozOOHxIeU/wiIhQJCXStBA01qNFQClFhmfeGQgp+0irlJlrfMp/fVpe0cXjF6L+4518T65POmC8/r75CV68eD7eetCTCDgpBJ0BLSzDQjMqkhJJioIgBJ6MUZVzc1piPFzWHcMjzfVxyXCQkQvJa/sDykJjrOfuVcPre8OPFYb/UXgeBdL/gXQc/5eAPw8sgf8H8A+98FG9JBQ6Md4ueL54fcS1UcmkUnz9R1eEmOxQg0xzvrTMaotSEoRACPip62O+c7wiV4JRXvGloxHvXjX8529fYZxnb5AxyDW31AAfI6eLDiUEV43lwbzhN96dIYTk5k7BTpFCt29MSyaDAong+jQn+JhURcued85X3Ju3XB8V1MbjY6ANkq71aJlsV1IKlJAcDMGTJqJFY7Ao5vUK5wPOeawJXHY9be8pckmpBVJJJqWgyCTL1rFqLdOqIIhIJmHVO8alxgJRSGrT4WPEhUguBU5AqSR5oelbQ1SSAYFxKVn0AetTE5vS6xDrwNqTmya0bB0MXmQw713yBqtIpiStDwQHZYjUvSHXgkUbKfTaM+oDzqTvGw+5BymThHK5nhg7oHCPmO0NkRVJB31rHyl9Pu4JDy9eJbTNYfrJgGRjvQxI+rUETiEFlJmmypIyr8r0e7z+W2yxxRafdmzJoy2eggwYsY4AfOz+BfDHPpERfcLorOed85rT9YXr0STlpm4UA531D1U9UoiPpSaQUlBIxc2diuN5R+8cUghu7lQA77nv+rRk1hq+9e6M40VHlSm+fDTC2ECZpQ3vCNy7aqkyy41pxc2dKuWlxogUkn7tHhDAg3nL5cpSd5YQ4R3nkTIRWWId6/GD0xWCRPxIAd87WXIwzrl31ZErwWsHI3ZC5Dv35uyNM5QqOJwUnC56lBAMC02VZ0iSBe+aT+Hfw0LyzbevuFj13Ju1OBd442jI4bBg1hhOl4ZMy5QP5aA1hlXvOBjl/O43djkaZcz7wKRU3LlsuFj1zDvLO3sNb50u+cHpijLT65YsBVhEjBxMSl4/GPDgquMb787xwLJ3tD3M246wXjDkGZwtelCCgXd0RiGEYFTmzJv2PWsBu/4nLbxzZdASsnFBpeC8tlzVj7KEeg/iQxRAT1vrvKgN8OXnxYf2CSCS1gRSeaSA/XHBawcDlq3l7qzj1WnBZW1xWdpczg8kWqRm9mujgsvW8e6s5UtHI1yMtL3jfG3NJMIre4MXrkR6HgLpH44x/qIQ4psAMcardYPCZwI+JnLi1b0h0UeqPLWcKSU5XbY4n9Q4tQsgImd1R4yCca6QoqLIFL/z9g5HowIlBHfnDd96d8YgVzgf+P6DFW+e1fziG7u8sjNgtq6qPF8ZWhPYrUoGZVogHu6UXBMljU0BZmWe8cbRgDvzFb95d0GRSU6XPZNCM+8dLgZCFHTOYa0HBNMqWdisczRSk4tI5wL3L1eUWUaZCXZLjUdQW0uOoMglw0LRu4B3jqtOM4mOKFPOUB8iZSawPlKoiPfrxrTgyLUihERwgaDQiq9eG3KyTBWhTWPpMslV53BrcqhxpOrKPEkajX3EpvsAF6tIVaTHehvQUZEJWJrEni/mngBMsjTj9g5an65CIOXHaCDTayJHJBLQ+vSve+zv//hk+iRJ83FJoE0l5Qc1EmyxxQchALWHMiQJsY2SxgQ619G7wO39AaNSc2NavdQazi222GKLF4W//9Zd/hv/x9945udvLWs/UfhzMcY/LIT4mRjjv/pJD+aTxiaHaNaah5lCV7UhV5LX9ofAI1WPVmmdcTzvuL03+MBrgg9TK23USE8+/vh9Te/42989RUvBqNT0JvAP7i+4Nik5mhQMCs3tvQFHo4JXdgcUmXqYfWR94HTRgUjjnlapWeyqNRTrPBfnA6eLlv1hQa4kxnpCjCghmZQpf/Xdy5phrjiaFLTGc/eqTbao4BEU7A9zcq1oTHqtXpeMVLlmXGqM80QBb5+v+O79OcNBzqTQNMpjQyAAO8OCy8YxkBIXIq31FEqSa8XuIKezjs7ByaLj3asWKSJaShaN4e9e1iwaw0VtKIuAIKIl7IwGSCKF0ty/7Div7XqTX6Q1znoRsll0ywBXnWdSCi4MFDIgpGBQKHx4OgGkSBk5ATie9yzM0zedf7sFQNu4jfdC8vz2NQkcjEBrjSgCQmiMTU6fm9OKNw5GHE0d88aliJgA563j9cMRQiYiNFeJ3F11nmGh2R9ljEpNkcmPnDs+Dp6HQLJCCMX6OBFCHPIZyh5WIoVQGeu56hy9c8xbx1VjGFUZwQUWreGtsxrhA20f+NqNMW8cjNmpMu5cNPzsq1MuG4txnjfP6ySrtI5V7+i952xmiCHynWrF/lBzujCMS0VjHFJGMi0ZFxofAyeLDu88J8ueSnu+/e4c6zyDXNFYR2McrY0MlcLG1KjQGY9xgioTCKHJpKZ3ntZZrPNIJJNBRtN5rmyks4E8k+yPSnIt6VzDRd1DTFWA3gWWXWTZekIA1RtWGiSCXAsGRSBX6dDWMlLkikBAa8GoyFK4du9Y9pYQInOXmE6xbmETJKtYa1KFJDxqSgusrWUuBV131hOcJ7jEoCeaLKGxj4LJYN3kBowlCJ3a3HqXwuLimrx6ngnt4058W7XQFj8uZISBlsybjj7LmFSS1iiqUlMotVUfbbHFFp8JbFVHW3wEbggh/lHgdwghfoFHl3gAxBh/7ZMZ1icDHyPOB4QQD0kQ6QN2nSkErAmSpBrQStI794HNSs+iVpJSvO+1m/tCiLw7awDYGeQY71PAsRL8zM0Jq96noGng+k71kDyCRFw5F/AhECJUucT4iI+BpnOMq4wYAle1QYiCg5Hgi0dDzleG03mPFJFRMWLZW6wLLHoHHWgpOF50HI2TtWx3oLk/7zgY5ByNCwqdiDUXIveuGt46WxGICAQ/eLDgoum5XWhsiLQmEFxkWmW0xqVMpeBZNBYfICsEvfe8fdkQY2TeGMpcom1k1hqEiGgFF0uD8Z5SSax1hBio8oxBJpkOcqwPZEriF57OpmwmGxL5owVUxdpeZtMaqLVpoz6IyFCDsx7/AUoez7r0R8Biba+QpPd+1o3snBeTOSRI6znDljx6Eo8TI08jk552XxJWpObDcZFzMM6ZDDTWeqY7A37utR1OFx0XK4s1nv1Jjlw5TuY9mbZMqpwqz9gfFZzOWxAR0cDP3ByQa0Xdf/Dc8XHxPATSXwT+GnAkhPjXSZLTf/mFjeQlQ0rB0bjg1+5cMSk1SwODTPHDs5ovH41ZWcdvvjNnUmquTwqqIkMLyaRSzFtL2zvOVoafuzVhZ1QgReT7xwvyNTNyvuwJQqAzQSYFp7OOWWt459Jxud5VKBcd41xy0Vg652lthBhYiLX4MMKr+yNOFoG9QUGIgdam4LlJlVL2ywympaDuPS54vnJtyLwLnC8azhuHiJHGB0qVEtu9j5wvO17ZqziYZIRZUjONCkEjQSrJqk8TVreWPg5UpMojzgt6G7HBUUmJi4LDcZHCuzLFeW3YHWpcDGgil42DGCmVYL/KueoNIkTamIikQCJdctaZRTEphWJIgdjOg41rr+86hayN6yBuHp1wm7R6J9ICPK7ZJu/fmzHzMrBRP21VR1u8CHjgfBnQCnLdE0WOcR0Zkus7BcfLji8U+jOhQhIpdf+PxRj/b5/0WLbYYovfPmzJoy2eAX8W+CXgFeAvPPFYJMVj/MRArYmjuCaSIBExmZIPN47kWrWzySgS6+cEEd9zTRBC5HjeJTuVksT17edRHPgY0QhyJVl1hsYGZrVlOsgodSoCqo3jbNlztuy5EIajcYGPkQfzlgeLlvOV4WLVk6nkdvg9b+xxuuxpTSDXklf2KnaqnF+8vct5bRDB8PO3d1i1lvtXHXVvqQpF3XlGpaJ1jrr37N/I+ZkbU07qjjvnLcNCcagku8Ocq9pw96rFOsd503O1NMQYueosiOTm2KkyYoxEBPfnLZmS3N4f8PbFisu6Z1RonJNpneIiWqc1iukdLgpc8NyYFiyNIxLIpWRvp2DRGAQRIQSt8Xgcs1WHFIGzOhWgGB/oXFpsl3kqT3E2rWsEqdzHK/B9yjBa9olgehopE0jt00/e9zzpNi8qsDq+wPf6PGPz91lH7gKPCCTBIxJmVMDBpGTRpnyrWdNTZZJCS27sVJxc9UQh1k3vgfmJ50tHI3aqjIvaMMglSmpGRYYbRw5HOVJI8vXcIYV44RvSz0QgrRcGbwH/I+APr//ffyTG+Oz1Gp8CZFpyfVpSZYpA5O5lww0bKLVi6DRvlysGRcHeqKDpPRerjr/3puHmTvIOdp3lOydLfi6TzBrHpMw4XrTMO0NrPEfDktNZx+tHmqvOUuWaRWshRq5qw2sHg/UuQkBLwTCD1gpaY2lMYvOvVj0hwt4gozaOnTLn/rJj1VkaGxnmCqUydkaaTEomZc6sbenX7WugqHQKadMqkmmND5GuD5RFzq09xcmiJyAY5IpFa4jA3jBJhhoT6A2cL0HhqUpPoRRXnafKPBciomRJpSWZElin8EFSmzSrZVLiCTQxkmlFjKCMI6xJJBnXJ09MRJJQKSspRKgkrEyynpkn6NnNzYxHZFLtYCxSztKwFIgSzhYRx8sjeBxbtn2LF4eHbXvrRsDgIuSpnrVUChF54bsGLwsxxiCE+BeALYG0xRY/Afj62/f4p/7Srz/z8/9n/9Rt/pu/+Dte3oC2+NQixvjvAf+eEOLPxBj/tU96PJ80pEw5RNaF92Qg3dh5ZFvftKj1zqWg7Qj3Zu37FEY+RlqbyJaNAmlYKKwPqWTnGQK4RQQhBa/vD/j625dYF8i04KdvjDmvDa9kiouVodASrSR1Z/nGO1cpCkQILmrD/VlHoQWTMqMxnrsXLT97Y8Ky87gQKDPFpMqoCs2tLKmHxmUKjv7VO5dkoiRKwbJ1/IO7czIp6Zzl3fOWSZVxuTQUmWBSZGRScLZMbWrTgWLeBoyNFFla1srOEUNAi0iRCQZec32nIpOS/UnGTpnz+kHFN96e8fbZkgfzhpOV4RdemdLa1MDdGE+uFbPGAj2FFkzLDB9FKkwKkeujnJPGUihBiNBkggdXBuPW0R0BxhkM1vEay/5RU1cKMQcRoI6g7UeTMptrxsexdUN8urBxwGyIIrW+bxN5ssnk3S8gzxXOe3wU1J0HEcnznCLLybRmZ5ijpKC1jnuXLbPakOeacZnaEXeGmkkp6bynayzeR46mBQfDnLOVobUeLRP38aI3op+JQFovDP7XMcbfB3z3hY7gtxFKCLSUuBBwLklFr40LYowczy3GB4akoGhFZGU988YipeIXXt1l1TsezBoGmWTZWA6nJVUueTBXnC97+pDaBM4bQ9M5Cq2QMu0ITAeSYZax6npq41EkVjqsO+4ba9kfZph1VlPvAn/op69x76JhkCtWnWXRG3oPdWeZVBnew7xzhBjZGeQMC5itEruuNXzxcIoPnmVjyFRkoCHTOcaBdY48V9gQaKxPrWbW07s0Gem1YmjZQciSlLW3YL3FuEA3Sr5f7yOFDBglKDJNLhXISNNZtJAUuWCYF5zMe2JIigudQb5+/9akLBgLFPLRyfUkNiekJZFIOal2so3gHEgXk3VNJBXTB0Hz4022khcXOLfFFpkAv7ZcZgqEkgwyxemqo9AS9dhu5GcE/6EQ4n8I/FWg3twZY7z85Ia0xRZbvGhsVUdbfBzEGP81IcQu8GWgfOz+/+STG9UngzJTfPnamNcPUubRky1sj7eo3Zu1D8mbJ/OQRExtY6WWDHJNZxwPZh25lAgpPjKAe2N/s+s2s0wJJlXB9XHJuMrxIWJCeGip2zSzQbJrZUrifSQSCCiiIBUWkQKthVxvLm+seSGRTkoI6t6u12YKpcTDZrjeB65NC9pecm/W8Ob5ijcOh/zUjSlaSX54uuRHZyvGRca8t9yYlExKzfGygwiDTFIMMiZVhhAgRGqw3h8WDPOk2rDOc7HqsQGuWsuqs3znwZJxpbiqezoXqbIU5TEqJV+7NqG3Hqklq9Zw7XDEq3sV7t4SiJyvejobaSyUWhBFJPdJzaS1xri0+hgWaa3iAw/zOqx79rXJdhP70wvNI8XRRvjgeWQ1LIDxIK19IzCuNHULUkomlSZTkqazeJeUiQfDjNNFRyYVRSa5vTfgwapjXhua3nK67Hh1f8SkUuzuFMxrS2c8Z8GwN8w4HBWMy+yluBiex8L2y0KI/xrw/4wxfiaPXykFZSb5uz88p+kt92YtX7k+IcZI4zx7g5yTVc87Fy1lrvnZmxPuXrYE7/neyYJhJjiZ97TGMi5T0v5v3nXkWvKFwyHLznK+Sna32npmrWVYKaZVDgHeuagZ5IJxqZiv1jREjGRKJRJEKIaFZqcquFi2fOfeknGhUVohlUcpjWsNJgYmUfDaUcXZ3LBsLeMyI5NQ7AzoekfvA5KIj4LDScnxvGdYSO7OU72mUopb04p5Y9AKWuvpTZrQBnrtx1wPcWUToVTmyXvbWc/Jok3KCCnIJYzyjEKLhwfrrHUMCs3pvOOyNQiZPkQKAdGCzRIhVUjoQjoQ1xssT//b8Yi42WQrFRHGBbgIq/a9odk89tzH3/PjhnZtfMPP8vptoNwWj0OQjp+n2SvNWnkHUGYwLh7JTS9qwxevTT4T9rXH8M+sv/7zj90XgS98AmPZYostXgK25NEWHxdCiD8J/GmSle3Xgd8L/D1+wixsG2xa0j7scRnTNcDDrCQhMGtVUiETYbM/zGmspzEOIViXBAmqXH9oAPfG/pYpQaFzLvOeYaF5fX+IkpLjecvhuCSX8qGlDsDYkMKxASUFZa6YFJpca/aGGU3vEFGh1iU9Qgh643kw78i0pDGOB1cd8y75BZSCzoAPkXfOVtSd4cFcsj/K2S0z7l41zFrLg0XL4ajgm+/MOJyU3NobkC1avv7WBQejgrqxGB9REqaDnFwJzleGWeOxboXdD2iVyCtjPavOo5VAhMi40MzqjkoPyJTm9n5F7zy983TWpaY4pbg1zfnhaeSLRyOGpSYw54fHSxCB5ZoZiDHifbKsRQHGenoPSiSLmlxveIv19d8mYPgzEyy8xVOxiWp58r69PK1hY4SdUcnQBpQS7A0yhpnGxciq9QwrgVQZN3YHtNZhQ8rgemO3ojaeTnqij8nRg2RU5uwPC6pCMS01pZJcmxTUNrDoHL95b84v3t5NirkXjOd5x38JGAJeCLFZq8cY4+SFj+olwRjPdx8sUj1jJhkWmh8cLxjmis54bu4NuLU/ZNUbBIJhnnEwjnz3eM4Pz1Y4H3n9YEA3j+RSE0LGIBM0SjEuNfPW4gn4SArDjqCRWJf8iO9eNuRFjpKSMpeYEHh1b8igzGisxzkgCiKRm/sjNIk0EiKF0bkYyXcrrHGYEDheGLxPRJUQEZ1p9gY5VzHypemAB/OeIOBsmbyTjXXcnKQqwCqTjKuMLxwMeedScLEy+Czg+pRJlGtYPnYWhJgIH0iLXqU94xy830hoYVhkNMaBkCgRcQGct3S9QUaYDhR172ngocesD89mN/O8N4DbxDTZzvtHE+9HYbhWe3R8NMmT8d5xbWSlz/JztuTRFo9Dky4UnnZgRNIFhfWJBN0dBMaF5rWDMV88GjFrLJOXtHvwMhBjfOOTHsMWW2zxcvC8LWv/q3/6Df7Yz//0SxzRFp9B/GngHwL+fozxDwkhvgZ87lvZPqwh7aMgYgrUNjY1Ez+YtVifGshu7lTkSlLlmlGp1+SSpzOBQn90ALePcW17k/Qu2V2uTSrsOgTbuMj+MCcKOBoXnC57XEhB30fDAq0kD2Yt0yqj0orTZcd37y+REt7YV5zMDV84GqKF4MGiQ/tIJgU/PFmhpOBL10Z0xvH2ecOr+xXGBr6rBL0NLJueTMKD1qaNdAGns46LZY91nlt7FZDUG9cnFaNCc1kbtIZX9iu0FCwaz629ks42tNYxay1HNjCqNNcGFXV/wluXDU3niAIqJSgLyahUKAnL3rJbZYxzjVaSwzKjyhSr3vHtBwtemRY8mLdc1galJK2JGA/FuqZZAiqCEpFRIVBELuu100PDKIPePMp63eKzjaf9DQUpuypbZ2CZtdunEoln2B2m4ylXHuM9kYiLDh89pRZcG+Z4AV86GnNZd5wuTLLA7hXc3h+ilVznbaUsjNom1dwg1yxby/1ZyxcOR5+MhQ0gxjh+oT/5txmd9XzveM4/uD9nmGtiDIyrjMvaYLymN57JMGdUZIwrzcWy56LuOVsadkrNsnFMCsGwyBkWih+crQgkyenBOON0ZZl3jhgirXGMiowql+RaUii4Oc5obMH+KEcrxbvnHpxHqZR9dDgq6VzEeo/1iq/sDjhbdfjguagd54ueVe84GGXkVUZvI4NMcWUMu8MCfGSca04WJjHurefBokcpxbjQ2ABvXTXst5q690glOFv2uAjWpd/FyAdqZblqUhaRBKZlamGou+Sz2djQgoM6ANojhKRre/CeZe84HHuWJjDMOhatY95FrAMhPIpE+GwYyPUc+0ykyyZ/aBNKtlF/fhgB9fj7CgFSpqDwj/p524l8ixcFywfbKgUgFeyWKcS+tYHcRQotUEo+vOj8LGQgAQghBqTNhtsxxv+uEOLLwFdjjP/vT3hoW2yxxY+BrepoixeELsbYCSEQQhQxxu8KIb76SQ/qZeJZGtI+6rXWBY5nHZ3zjEvN7f1BailbK4s2eUk2pnjeo0mRfh7iQ0N0lRBYHziet8QYOV0aDoY5rx4MsT7QGs9FnWrrpUhlRJmW3JxWnC57fIgcjgq+MhozUIo3L1ecLFpGRfYws+nBTPLK7gDnA0WWmqkv655MK/J5x94wR0rBtXHJvVnH9UlFqdX6tQ3OBX7n63vUJgWKr1rPtZ0CYzxkkbpzDAvFqNJ85doEpSSFhG/cuWK26hlWKQg8SkFrXFIN+UCMkCtB13mKTOLWycbzxnFrWrK0iYSLEXQmuXO+REpNJgLvXnU0veGbAWZNhyfluWYqNUs7lxwXvUjqqtpAJBJDWv9EQHtYdDxcF23XHZ8NbNasKXX4o62HkRS3UgSQAq5WlioHEXNa5zld9UyrnBAEwQtGpaRUiugEq97zxuGQzkYuVz1N77g2LhhWGdfHA2IQWALGBwZodgea2ngGa+VhnqV845exjnguTZMQ4p8E/pH1zb/zWVkUhBC5P2tZ9o5hoVP42srxo9MVuVZMy4wzG/it+3NuTCoOpwWv7A35wfGCQqeU5lxLrIh47/E+HT7duu3M+pRltFNm9ErSm0DnInvDnEym3KUWSW8ix/Me78HGiHdgnad1kdf3MyaDjKb37I8LruqOujW8edYwrpKU0tiIJ1BqycnCsOosXSo+47LtKUrJou25OSloe4eLkbo1WCuYtyaRQi7QOp/CrIcZRaGZt4FJpVn2kXkHWsI0T7LL5E0GUQhWJlJl0NpkN/MR8LDqA15AbSyFgtY4grPcWUCRwSBLZNOyf9Q8sMGzen437WcbEunjnAZ9eG8S/odhm3O0xY+DxytON3gyf2vzIZTFdE4NMkWVK3YKzfcfrPjRrSWv7Aw/axlIfwX4BvD717fvAv934DPxWbHFFlu8H1vyaIsXiLtCiB3gr5My866A+5/oiF4iHreIaaU+1E72Ya+tRgVFJnnnouGVvQFaJu/TRlm0yUvaqJzM+uf0zj0krT7o5/XWJ6cC4EOgMZ7OpGxUKQSZSl9DjJwue27vDcgKze1MURvH6aLjfB0E7kMkk4pZ6/AhZcouO0ezLtOZlnpNRsl1E53gwazFOM+9WcPl0qxdFXBrp+TeVctl3fGtd+ccjEsmhWZ3mKGB/+zt87VjQvGHvnrEybLDhqTiOO0dCkGeabQQ3Js17FQZVkvuXqwwHkalYVxqDicZIQpKLciUpsgkbxyN6YzjzkXNsnNMCsX9eceDxYJcCbxbB5e3jt6nNZF1PrVJh7TuGZYS6QJNl9ZLj8cYFKQ8WGshKqgUBLtde3zaoUnX9u36q5aQhXT7o2AjDPPkMpqUOQejMgXFm8Ab+xnjSrBqe2oTyRWsiPgQmTeWznoa43ntcITxMTUh1h2DQvO162OOJiVVpgkx8uZ5g/cwqjS7VYaULydL9ZkJJCHE/4IkO/1313f9aSHEH4wx/tILH9ULho+RurOc14ZRpnjzsma2NJwtO3761pRMCYSMXCwNSiQWepJnvLo/4N7sAus8WsH50vLtesagyhnlCucCw2HBeZ2aCaaDnHlrUTLS+8hXDsf0MfD6/pDv319QKEBKgvfUjSHTikxL6tbxjXcumVYZ1ycVwQeklByOS27sRFwInC5bXITZqmN3kBRIfYgMM4VUimVtuH+xwgbJrPMIERkXinnrcCFSG2g9XNaeQZHUDg8WlkFu8RHaDpx16YTQ6zDqALWLVHn6PeYKylyiZGDeQRtArkkZHVM1ZXCw6Cx6HWad6UekzUYp9LTDeJMx9EF4UmX0cSbZ56273KicfrvxSf3cLV4cFJDJdA5tGhg+aKdiZlP+UZFLYhTYCGUuUuDkZ4o7AuCLMcb/uhDinwaIMbZCfLYYsC222CLhW3dP+Cf/d7/6zM//M3/0Bv+df/gXX+KItvisI8b4R9ff/itCiL8NTIH/YPO4EGI3xnj1iQzuJWBjEdPqo+1kH/XaKtOpCMgFdP7+em4pxcP3LOV7CaUPIo+sD8xbx6t7AyAFWNfGc21aooTgh2dLFnObNm4FlFpifUmGxPrA3auGeWNBsLbOeVa9Z1Toda6SoswUr+0Nub035O5Vw6p3vH444HJlOF8aLuqOW9OKWZMyX1pjuVwZplVGaxzjYc4gVwwyzb1ZR5kJ7s9brPUIIbg2KfnO8ZyzZcf3jldoKel94OdujRkUikVnGBSaQa6pe8e33p1xY3dI0zt+dF7jA+S5ZNE5OtdxbTTgfNGSacl57Tid11y2Fi0ly97Rdg4fN6TRo/XNZt0kSZuCMgs4lyI3npaL05j12sbBVH14SU/Fs5EUW7w85KTreLkmjRxA+OjmPICBSNEwkM5HG+GydQycREo4bQwZguNZz6TSlEpze69g2XkWncP5JH24e9Vxc6fkS0djBplgZ1TwB9444Lw25OuQ/Z9Xkvuz1FAoX1IDGzyfAumfAH5njDEACCH+beCbwKeeQBIRTpc9F4sWH+By1dH7yGSgMM5TZILeRL52fcLvfH0HArx5tmJvnDMtMmYRpPB4IjFE5itDtVPSGM+qc5wve17ZGWBj5GBU4kPkKFeMh5pXypzOe5SW7ExK7l3W9NbTB/DW8s4lLFqD8+FhQ9y7M8f+SPPF4Yh7s4bvP1giNOuaSIkSkkDkqu4weWBUQmMdAdgdZkgBjQmE4PHeY9d1kpKUZdT0aUKDNNkRoDMOqQGVJjVYN54JCB4GhaJU0HpPlit2ZETLyOkyPpzwwvr9M1JAnALqHqo83d4QIx/kEX0cj5MoHzVxPqsFzvPsxJN6jue+aGzJo083ntlyGdY1revbGxJ0Qyixfp9Jythn3lqIAikkN6YVXz4YE4X4TFnYACOEqFj/ioQQX+Tp+eFbbLHFpxhf/KW/+VyfgVvV0RbPixjjf/yUu/8W8LlhIZUQD8OnNw1qH2Qn22BjXReR97w2xMjBOKd3ARvsR9ZzP04ofRQ2RJJ1ntYG6t6x7B3fO15RaMneMON02dHasG6NVUQiv3VvwbVJQWsD1nmu6p7xIFlzhBPsj3L2hmkXunM+hXsLgSByNCp4sGi5PirZH5dkSvCD4yXzxqSsJSK5VowKTVVoBqXC1Z4f3F/S+cDhuCTEwHfuL7ioDcNCcTAsQEYuV5bjRccX9kcs1s3Vrx8OaHrP909WKRR7lKO15GrVMW8gRMGw1DTW8/V3rtirNA+WPavWcF5bbu4UtJ3DurQJr0jkweY3HOLDUrWUexkSkfS0jcMnN8WX/sOv/bfk0SePQPp7VzFlXPXuEXn0YeuCAsjzRDY2Hm7vKQZFxqp3zL0jE5JcChadZ5BLAoKL1mJXBqUiN3amCMCLQNsFOutojOdgVPCVUYHSMgk51iH740HOLSG4sZusoC8rQ/V5Y7l3gE0d8/TFDuXlwcfIylguloa3L2uO5y1H44KbOyOa3rPsLFedYXeQMW+Sl3bWWt44GpFnHdcKSds7fsetCVIm5dFV29MYT+9iahggUmWSQgtuTEt+9pUptXHcn/UMteJoUnGyaHE+MCoUvfG4ILioe2JMjQYni548U/Q2EkLgb3/7hCqXXDQdOwNNbwXRR9659NyY5GQKVp3B+kCZa3ItyAScL1ND2jDPybXAhsgoh9olG5eIj8iRUq7bDxyMJeyNcu5eGroIlYDRQOB9RAC39sZc1YbaOgoJtTHka6bHk9jZTbaRA4ZZCg6rTTrxnubx3Zx0gfeegJvnbQKIRfzgk/NlhFZvZaRbfBAeP96etKXlpGOnWKuPnnZBsDm2JLCbw/XdAUi4qi1CCJrOsFNlPFh07I+Kz5qF7V8h7Sa/KoT4d4E/APyJT3REW2yxxXNha1nb4hPEZ+oD76MgpXiYT/QsdrIn85J2BhmzxtI7h3WPyKdICrV+WpbS8wR2pxzXnO89WJJpiRCCg1HG909WvLJbcjQpOFt2/Mffu6LQmioX/ObdBa/sVry6P0DEyA9OlryyN6DKNcaui0D2BmSZQkS4ag3/+duXHC86ciV543DAD45X1MYxyhU3dwecrQyCSGMshVa8slsxLDQni56LxvDFcYYgclH3tNYRleB02dJaz7K1mOCRQvOV60MA9odwb94xLHKWnaPKFbOVpbae80XLonX81rue42WHUoEqU1gXeHBlGVWCVeu4cx5RKimNXIjcuWzpTcqzgfcTQ5uYDIAuQt89+1piu3H86Ydj7ZaJUIW0+bs0iUR62jp0I0TogcLBsEj2Na00o1LhQ0xrfuPpbEALwfX9EX1ImUbOBc6WDsmKV/YGlJnk7mzFa/sDbk4HvLE/pO5DamWD95DUSsmXSh7B8xFI/3Pgm2vJqSBlIf1PXsqoXjCcCzyYdVzbGdB5nyxVITCqJJ2FzsL1UcHxsgcpsdax6B3fvjtP0rEYyLVMMsdMQQh0NnI0FIQYOBwVNC5wWGruX3X8wmu7vLY/pjeOrveUuaZ1ntY4JnlGVWhClDyYd6gocDEyKDRKCFa9pek8VQ7HCwvBM+8NgzL5eBe9o3ORSkvmnaW3gXFMNZqZ0vQuIIl0LnDtQGNcRm8dXgpG2lMG6NaTWqZhVAiEgFxFru2UuACjHKKF3YEgyzOWtcEEOFm2TKqc3kfKLHLZJpUFpMXww2BsmSR+vYdy/dnW+fdPtoLEzEbSCfY01Y8D3DMwRJsQug9rMvg41jDJs+cmbfGTh8eP6RIQKoW0j/LUELhR4m2yuzYoSMeilqzng8jeUJApOBgVlIUm8iGs6acUMcZfFkJ8g1TNLIA/HWM8/4SHtcUWWzwDvn3/jH/iL379mZ//Z/+rN/lnfs8vvMQRbfETiM/Yp95H48l8og9a1G0yj5RIaoIYIle14fqkBEgEzNqm4nxIeUTZexeJzxLY/STB9MrugLNFv85pkuwNc+5etfgQmbWWi5Vh1Xtu7qbg7tY6zpuea5MCDxzPO4QU7A9yjiYF4yojRHA+EmOKBykzwbDQKAnfvDPjeNZiQySTKatlkEvePq1587xmZTxaCi5ry7jU9MFjes+dhWVvqHCx4K2TFct1IZAkohG44Fi0lhDhwawhF5Lrk4KfujHkP/n+Rbq2UhIXIifnC4SUzJoU41FmDhHTxl9joV0TAyWAWLs3eLSGeHzDO+Pp9e3bjejPHzZrzCak9rwPK3F6/O+fZ5t1uqK3jmUj2B+WmBjZKTKihGvjEmLAdDDUILQm05LGWHpnWXaRo1HJzZ1hEry0lmEVuTdvkxDFBzIlH4bd+xgh8MkrkGKM/xchxN8h5SAJ4H8cYzx+KaN6wYgCxmWG94EYJeMipzaOi5VlXhsOJjlZphG9Z7bq6ULA+0BrPTvDnHndgxa4EFm0Pcfzjrq3uOD5uVtT9kaJBsmUREhYtJa6t8QY6VxkkAuOZx1EiBJiDGQScimg0Cy71JxW20C1bliY1YZuPYlWSjNbGopM0RqDC5HjhU8h1zFA9MSoebAwdMai1uF0yx7e2K84Xhoa41FC40PEaMeyDxgLnYoMtUBqSdt7qixjOsyxjaF1kVlrUArK4IEMYqTMBEIkee3eSNK7wGLNHmnWKqd19st0kCZj/xR5ZuQR6QTPvu30JNG0UTZ9FEFU8Gwy0Mfff7srsMWHQfDeXK0MQMGqX1fv8sGWzVKnTLEHswbrU63sXl4wKjNEhNv7Q6z7zLWw/a0Y4x8G/uZT7ttiiy0+pfiFX/qbPE/wzFZ1tMUWz45nsZP5uA5m7j0hRpxPgdbWJ9tY5wIHWQE8PUvpwwK7N+9vXSKeHieYhrnm1b0BQkCh0+uEgLNVz8Ew43TepjVFY/nS9TEnyz6pI1Y918YZy65gUmp652msp/eBV/YGHI4LBPDmWc2iC1zVhhAD374352hcMKoyjPX8rW+fcXNacF73DApFrhXzleF02fEzNyfcHg340vURb53WfO94Sdt7OhfojKHIMl45HKKFQCB4MOvQIm34704LzhYd92eRSGTeW66WPYNccd9HhHeU65xW61P79OaabrMG6HjkgNg8Fngvy+lI6wb48KiOLT77CI99fZxM1DyyL2a8vyF83sFOEdKx4wUmOMrcc2u35NZuxW/eWyJlZNYGBlqwNLBTSR4sHbmSnM0tk0oxrBSH4wwlFK11DHOVCNsQ6V3g1k6FD/F95/iztj4+D54nRPuPAv9RjPFvrG/vCCH+SIzxr7/wUb1glFpxc1oxbw03dksuVx3UsD/KyJVECbA+8rve2OfuxYrOBaQAiaLuLaMqY5AVlJnmW/fmXJsUICpyASeLnqORQCrJYKS4uTdg1hq+8c4lmZRcmxScLzqqXHFetxwMCn50UZPJ1FBWZIoYNTvDgtu5prOei9oiVWRcZfQ2EGJAK8HOMGdcSFa9ZdkHnI8YC431GOfJdaqPLDNJnklOFi3EgqNhQT/wGAvDUrEwnmFtmLU9WkqEkExLhZQSEwMmwv5I05tIjB4l4drukEGuCRFGpeLGNCNGwbKzCKAhPDyYIo/a1mZNUhc9jbXnifuetZFtp0iWu9qnA3hjcwsfsW/VffjDD/HkrsFmd2EzOXzutsd+gvHj/j3XRYSMZHqzzqddq5yU/eXN+wP2MpJtdH+sGRcZC2NZtoEyE5zPewqlOFm2LBvDoMg/ExY2IUQJDIADIcQuj/jgCXDzExvYFlts8ZHYWta2+BTh0/+B95IgIlysDKVO9pN31koipQQn8477s47ljuXW7mCdaRqJPmIJqHVe4tMCu9OGucH7wINFx81pybDM3kMw3dipOJ53tNYjgC8fjfj+yYoikxyM0/Nb4+hdoFKCQkvuXrVUueaNwzHWOn7rwYKzZc/RNLVLxQCvTitm63yia9OSt06WLDrH125MWPaWTCuEiNzaL1n2jrp3nK46gk/2njLPkFLw9tmK795fUWUCrxVVIRCi4JWdEqTictVxa7dkUBUcVAU2BOad4wdnK/aHORG4e16TaYH3ye5jPBibrsesXxNEIq3Nonm0FthcI64v895HDj1e0LMljn4y8Hh8hSAdMyJCLkHIRBhtsCmJuuphTOAXXtulcylHeKgVdR/4wsGIXEumReTtyxpF4GLRs+otg0KTe7hsAysbOFyUDDONVpKbOwM2ZoW4XgSfLvuP1fr4cX4Hz4o/F2P8a5sbMcaZEOLPkao4P9XQWvILr+3ym3fnlJlkkCtePxAoKXAuMmssC2NZtZbGBZQUnM5bbu0McD5Z4M46y2sHOrF9Zc7FqmVY5Vw1BqUls8ahJSx7RyZTZtKFccQQOV12dNbjA9TW4n2gyjWvTcacLhtu7A44GmYcTYe8e1VTlIqmsVz2jlwJdocZuVRMKo3zKVxroOGijUiRgrwORtBZQa4EK+vZrzQqRgKRIOFrByPuLyyawLVRST8pePM8hXFbBzfGJYNcs7KOHx7PKAYVeyNFkfUsuoCWSX56tWzoouKt3tAaWHUeJdKJNM5gtaZcPYmR73jvAv3JBfuGuf0wGeCTcB4GOk34m5+1Ca/7MHxcosCS/i9P5t1s8dlH5McPTBck1d2T4ditefqVsCDZO+vOcTAomJQ53kTKHBSKRWd5+3zFN+/O+Md/5uZL9TC/QPyzwH+fRBZ9g0f/9QXwv/+ExrTFFlt8CO5eLPiD/8v/9Jmf/y//kev8yd/7u17iiLb4SYAQ4g8CX44x/hUhxCEwijG+tX74J1atGgXsD3Ma66n7pC6alJqTeccg11yflsQIPzhZUmrFqFR8/Z1L9kc5VaY5GhfvC+wGOF10aCnIMokUcNVaqkK/R8W0sdnVxnG27KmNRwnBbpVxNCp452LFvStPYxy7gxSKPSg0e8OC3nm+e2/JqnHsHxUMc53IoPMVznsGpeR40TMpFPuTgi9dG1FkknkT6YIBIQgetBLIKJhWOdZFBrnkeLaiyjO8F7joePcqjZeoUCrwYN6SZYpKZ1R5hl3XoO2PSt4+v+R03tIZS6Y0884x1BITPINSM585HJD5dJ2vSW3TIj59TZKLR/lHW3w+8HE3kR+/Kg8kIlIKCCFFu9gnHtdApZLIo24t0yqjttC4gA6Or1yfoLXkYtnT9I4sk5zWLb2NdN6SCcG4VOyUOcFHZCH46VsTQojcm7UY5wkRDsbFx259fF48D4H0tAb05w3h/sSwM8j5fV/YZ9Fb7p3X/OrdK6aF5sb+kNosKL0giMDhIOeitrQu8Cs/PKPUmtv7FUJI5k0KuT2Z1Sw7T6VVkpaGwDCDSOR0aRhmihA8rffcu2oRRLTKOBwV1K1lkCuIcH/W0NtAriOjKuPapKDpLYfjEjeN3JvV3DlviAJGI41C4qKHCLM+YE3yVUpAKUkWIa7bzparHusil0tLlbXcu2zYGRT03rE3iHTWUxUaiWAeLLPOMOssuUph24WxQGRvUNKYlijg7lVD21ky7ZhUGZGk1DLresF1k+eH4mk2tuchjwCWLskaNjsBj79e8PQdgh8XWy/z5xc/bjPfRoUkeHQsbr5uzodNRpcU6QOkyFId7vnKkmmJzjUE6H3ay9II9gYFl41hZ5B/JkikGOMbQog/G2P885/0WLbYYosPxx/4pb/Jved4/lZ1tMWLwHrj+XcDXwX+CkmU+38mFS4QY7z84Fd/vqGEoMo1o1LTGc+DectFbciU5MZUUOWKo0nBD09WXN8pmLeOUkvq3jPQivvzluvjkvPaPAzsHpea7z5YkilBiJGwLu0JIW0wP9kId7EyFOucJbkD71w2SCEQQnI0qTia5DQm8GDWIqSg0Ip7s5azVRrnorY45+l9xFqPVDDKM/au54QINycV0yrnP/yt+8zbtPH+6s6QH5zUdM7x/fMlpZZUmeJgOODSBd44GnG16nnzLcdl0zEqNUpA51OO06QouL5ToZXgeN6y6B2tWXJed/Q2oE1gXEYEER8dzkGpUumQW0cNFKwbowUs+6eTCh9GHm03lz+biDyynD3LurEkCSOeXLcqCbtDmNfvrx12rHNPRYq3+MFZnQq3dgYUecXRpEJrkdrVVx2tj+QZVHlBWUDbW4aFJkrJq/sVh+OSL10bcXt3yG/em6OEoMgUu1XGRW0QgLEeIQUxvP8cf1F4HgLoV4UQf4G0mxyBP0Xaaf5M4fvHC37tzhUXK8NbLnBz1TMtcyIZmQSRKea9ZVJm1KUl14pBJhlXObMmBbrdn7UMC81lY3AevvVgyet7FWWmkSKy7LqkSFKCk7mhygWRnpuTkpX1jAc5Ay04bSyDMvmS3zpruHPRcDgu+erBkHlnuaw1N3crxqVK3uZFT55B7wLRAzoFgHtg2QaKXJNLQe9SKFyuBSpC7yPntWHeGbTWXNWOaalwCCqV6judT7sfRgpyDRHBxbIH78mUous6ThcuqSy8INeaTAZe3a3WVjjPon0UJLc5sCSPmMfnJYqeho0KaOGefrJvA6+3eNFQpGO4FLCM771/I12WQCbBPHFQbnzzfv2vjCk4e5inB6USZCrSmkBvPIMiY5BLpBI0xhH9ZyYD6U8A/wbwR4AtgbTFFp9ibC1rW3yC+KPALwC/BhBjvC+EGH+yQ3qxeJ4WtMexaWy7P2s5XvQcjHMUgtOV4Xje8XOv7iT1gRAoRMpOLDJmTc+DRaB3qQbs5k6VGtUivHvVEAlc1qlAqDGWvUFBaz1ayvc0wj1pgatyjRSCV3ZK8kxx56Lh3auOG+OScZXTGU9nHBerFq0lbee5bA13Lluuj3JyrVBaoqXgcFwxLVOhkHGBX3h1lzxXvH2yZGEC54uWPNdMSs21SQlC0FlPqRW51hyMJZNqxf1FwNUO4yyFliAFZZaiSO7NWgaFIgRYtpbeQlUoOhto+5bdYYaSgotVi3XJajRaN+UooDGPrvced0dk6+8N283kzyM2JTfPUpq0eexx5ZImZZr2JhGQ5fr+x2NTDkaCzkdiAOMimYi0vaNpHT9oVhxNclqTzt9XdytWvSNESykFo1HBINccTUt+6saEQicnVK4kB6Oc4VpNKIWg7h2jUvO94yU+pJb4n701fSmb0M9DIP0p4M8Af5X0u/tl4J9/4SN6Seis562TJX/rO6eMC8W41Fyuev7+jy75+dtTCiXRmeaq6VBCcn2SWglCiNyft7yiFFWhub1X4V1g3lkqpZmOcu5cNlys+jWh5Lk36/ABdgaaQic9zMGoYlhqFr2jkNDZACHiiUQEUUFrPffnLe9etuwPNbXxDAuF9QL3sB5SMywkTR+Ij5EoxsIXDnLGVfIpHy97uj5Q5oquToSSijAZZXS9wdiI8ZFimKE11LVDaUHnA4XWzBtLVHBWW4pcMWs8wYPMQRM5W7Z4D0Xm8DF90PQucfAbG5vlkRoo48UQSBuWf+sz3uJF4aMkrJsLieUTT9pcSOQChiUsPiShfRO+2AO4tLMwLDOsh0khMTF98ighUVJwXjsEEaFezs7BS8B3hBBvA4dCiG89dr8AYozx5z6ZYW2xxRYbPK9l7X/wj035U3/oD77EEW3xEwgTY4xCiAgghBh+0gN6kXiWFrQPQ5kpbu1UOB8YlxkA13ccd69arAv4kEieB4surTlc4KqxXJ8UjEpNpgX3Zy2v7w+JIpFZWkiE8EghUjbruODV3QFKiIfPkTJda0ghHqoX+t4RY6TMNVIKtEqPaS2ZVprWOk4Whs4FMiGpsfzodLW2QhRkWnG5Si1yvbO0TrLqDG+eLbEBBpnCC8GqteyOCiaFppASCdyYlrgQKbUkk5F3LxrOVz2v7JSsekvdSzoDN6c5rfW8e9Vwb94xySWt8dTGoFSOVALhIyZG6i5QW8O8S2SQJuXTSJFiBSCtUzzvdUds1jLbHNTPJzZ/z2dZV/Y8Pc6ktzxMUN98m5M2i40HKSUywtG0oFkXZEkpOalTjnCpIJDOsf1RCbHFDwqORhlHOwMEsDcqUEj2hgV7w5zjRcfZ0jBvLdenFXpNEq06x2v7A6RIqsNZk0Qxn1gGUoyxBn4JQAihgOH6vk89Ns0EQSaPV2MDF6uOZe/w0dP3HqciUkiWreFsZSkzxcG44N5Vw/mq5arxTMuMZWsoc40QkqUL5C5yY1px97LFWE/de9rekusMYsrmCVFhXMD6yCBTZFpRFpKV8Swag48ihWQpSWNcYvW9Y6AUMaQDDxHREoy1+HXeCjL5LSHJ53ofmUjJxSpN+q0NKBdo3DqTxYNatmRKsDIRB7g6heHtTUqIkdp4mj4RTlkELcCY5K3McoH3MameHGgFIQaUgsYEtIRFv7bUSRjplAMj1+P8/7P339GWbftdH/iZaYWdTqx808tPT08SPBGEAYMAuTHDYBq3u6GxB6EbLNvYMg7t9hgYbIyHCW2ZIIKIxk3TDqMBA2JIDU00JklCz3p64um+cEPFUyfsuNJM/cdcu86pulV1q+6t+N7+jlHj1N577X3mOWeutebvO7+/71dzqshYn3ySU5Z/c1He4Hng/eade8gxBrARgntw+6YBlEhrKgeM8qQidFXH+fEAFzyllHTesz/JGOUarRTvHNf8kk/nL0v72q8RQlwEfgj4Fc97PBtssMHd+GW/7Qf44mP0WWxURxs8JfyPQojvB7aFEL8J+I3An3jOY3oieFgK2uPcx42SZFr1aiB5x5/o4qTg5jx93kllGZhkZD0pFQEYZ4rDZceySQuSy1slsfd1uLIzoLOeOMoock3nA0fL7j1E1/bA8IVrMxrrOKkso0zz9tGKC5OCnYHhnWOYVy1Fbnh9Z8AXmhmZUtxetWil2So1k8IwyTWRyNuHK65PG6RIpNCruyVKCjIV+dLNOYu2o+kCHy1H3F6k5h8v4N2TBkFkO5f81K0FW7nm4iinLBQ/cd0yyDJyHTi3XXA4a2mDQ0fPrLa0NjCvQakOZ2FY5IQQWbQdWkqGmUf2AScxgNTJVqDqHk4QFX0tc28wygbfWDirQitY18L9CxJ8PPUBznPJx7dKBplkaSPbpeGrtysiyXcsJQlqvvn1LaomMKss24VhuuooM9jbKvn4uTEfPTfkys6AwiiUEFyd1mRa8tregBvTmneOKq7slJwb59xetGT6lLRe+6k9Nw8kIcSfB767/xX9CLAlhPjeGOPve6IjegpYyzJH2qCUoO4ci8ZjnU++QiHgokC2lp1hzqL1EBNhM111BCEZKMne2HBSW751b8AwV0yXlnllUTLF3a+ajnPjgtwYYgisukRElblmd5CBgixTzGtLmWnq1tE4R/ASLSONVfjgiFGQh4ApcqQAH6DqPJXzzGuHtY7anUrtMpWK2GvTmmXTMSkyolME55nHU/WDAG7XMJARqWBcaCa5YVwabAjp9yFTVKgP6aTItCTaQBPAtREhkom1ACYDGBqDjYEbJ55BnsZSZLCoe2d6DaWBWX03Y7u+SK89jO4nC7wfNuz/Bs8DZ2Ndz2KdHnhi7zbkXke5rtvccgW9QI+mAyUtoyJn2bZIqUAIhmWWJLQBruyV7AxypHrxyaM1Yow3gW973uPYYIMN7samZW2DFwFCCEHqYvg0KWDhU8BvjzH+9Ud47y8ltUkr4E/GGH/3fY75hcDvJ+3bHMYYf8GTGvuj4EEpaI9bvK1b2W5Ma1atSx5I24l4icCoMMksOwS2ysBJ3ZFrze1ly+7AMMw1uZIcLFoujgtuzhpWjSMzkt3SgBAcLloyLVP6svVcn9a8tjNgWlle3Sm5MWuYFIbKeg7mDVdPavaHGa/tlqzatPkNcGW7ZKAV1gWuH1dkWpEbxcp6jhYdmRGcG2qWreftwyUHs5q9ScG0arEeqtYiouSt2yvmjWVvmLE9yDhcVJRa4ryi855bS0duUvCRUpLz44yIQIvIrLUUIrUITReBjl4BIkFKRWEkHzm3zY2TFdPaIxSUOYgOun4RNxnQ+0Pd/2+iABk39ccGp0IIReo+CCGpjEJfr490sqoY5JpCCwaFpm48w0xx7bhC9tXC1jBjUVnGueFwltLWjJJMSsXP/fg5RqXiylaJlJKP7o/QOhnCWB/uXGe0gtf3hiway5XtEqMkR6K7y0j/RfBA+kyMcS6E+LXAXwP+YxKR9MITSGtZZhSRb3l1i3/45hFKRMpBxu4g5yuHC0aZpjSa1/YHDHPDa7sFbx1WvLI7oMwVhVJUPfF0uOj4WW/scXvV8PffPMRIWHWOPFMcLDsu75QsGkcMAYFAKYF1HoOEAMPCkCvJ3jgn0xIlJbO6ZV437AxztBQ0NmCXNedGOXXnyY2gNBlN46gcDCQsAhiVIii1SKlkUqTv11QwHknaZSATiRFVChqXLpK57GWbLlD4pLGIIdBahw+piF220HWBOp6eLJDY9wKQCGoXqDuPkTAuJAfzwKI+daVvYyKcHnTRXRNbvaXTXUbE92LAe1PdNtjgWeBB0tY1KXrvnFyr7dbqulXfbioApWHZQRAde6MRo8KwaBzbpUZKSak1SiQp60vSvnYHQohPAP8V8BlOW8GJMX70uQ1qgw2+QVFVls/8zv/vIx//H/2LO/zbv+Cfe4oj2uAbGX3r2l+KMX478L6k0Rp918MfBr4LuAr8EyHEX44xfvHMMdvAHwF+aYzxHSHE+Sc7+vfHutZ43OLtQZ5J8czXEOKdkJjOeY6rDkVKfHp1d8DRwmK95yjAt1wZkBnFsrZIJfhpr2xzc970KTOC7YHheNXhQuRgWuN8xLnApNB0zpNpSehb165PG/ZGJtUFMVK3HqMElU+tc5+9MuH2vAUit5ctk8LQ2MD5Ucas6tgfZdxctKk1v0ohPtsezo8KfvLmnJ1hzis7Q968OQeg1AJB5Oq0ZlpZtBIgJCMt+diFIecGhr3acGtRszssmdUR7wM3G0vdnbagjQ19XaL4xLkh53YKVm3LwbKlblId5OgDTkSqnYxKHRb3s9yw/R9iY5b9ckOSFqYVpxu9HwSRlKo2zBVN41EZ6AAnHUSfVG0SR+sUhRTUSnG06siNYlhIzg0VQggm2xk2Soa5ofWBV3YHGCW5vFsgkIyLjFWXSOg1YXPvdSbESKYVRsk75PPNWXPHSP+sz9mTxOMQSEYIYUgmqd8XY7TrHuaH4UXYNVj/Qq8dV+RS8dlXttgZZNyc13zh6hzRX5X3JgUhwP4wZ6fMuKYalIBFZcknGu8jmRZUTcebhwsmheKzl0fUFpatZ9lYlrUlABcmmqEqGA4Mq7bjZOmRnUcqyV6R9eqjiDaKN3aH3DgRtC4yziW1Ax8Duco4NyqQoqPpPEEEEBFjBCqDZhnxHkSAKFMim9KK1gWkCAQXEDGROJHUdlZIyHPQUuF8xAfL/KhlWGjKzFB1HVrCgnRy1fHUWEyQ+j9N//h4FXEhGfNJATdm4W4n+/5i6+4zS8SZz1wf7zhtaVP9mX3Wzb56YjNigw0eDw8zTjyriosks+1crc1/ErG7RkbaocgUGKnItUJEwZXtnK1Bzo1Zg1Qwax2fMumG8JLhzwC/A/hvgO8kmWu/753rRbhPbLDB1xN+3ff+AH/n4NGP36iONnhG+IdCiJ8ZY/wnj/GenwV8Ocb4VQAhxH8P/MvAF88c838G/kKM8R2AGONjzP4ng8cp3takkXWBg0V7VytZpiQ3Zw25lgxzzbKx/Og7J1zcKvA+smw906pjkCl2BobtQY4WCk9a82stWTaWG/OGKEhm2ZOCLgROlh23Zw3vTiuCjzgEMQSWnWP5lkNGmHUd3oPznneOa7YHhkXjOTfKuDlr2R0a8lwxX1nqzjFvOt49WZFpzaBUiAil0VzaLpEhIIRgnBuWmUcLye1lxTgzCAQxChaNRYtEHE0bh2g9h4uGGGGQZaway7GFvdowLBTnxznztqXzPplbO4/1abN6TfB4Dzsjw3aZc1w7bq2WzCrHqk0dG5qUjOVIC5RZHen8gwmiDXH09YN1XflhvXQjyfOsA3YKg4sgWoswaS42QpJpuLXsKPOMPDfIGFk1HcdSUWjHYFAwkIq6cyglCBFuzdMIP3VhwrsnFdanVtbL2yWZkvgYOT/OOVi0973OrFteP4iR/+PgcQik7wfeAj4P/F0hxOskCeoD8cLtGgjYGWbcnNXcXrRMl5Yyk7yWj7A2tW8VmeDy1oDjumOrzLi8U/LWUcWPv3vCIFN8y5UJozLncNZgXcbtWctJ7dgZ5jTWoTU0raNqJavQolYtJ5UjzyIiSjIlmMrIuDDkbWB7XLBTaq6eCK5sFYwKg2kcQggubxdEIVASDpctznsW1veFqSDXkUWvKBI+eQ1Ncs21eY21KaFNikQgraFjUhchIrHPkBoVCu8j88beacEpZK8MCimdTcRe7URvKiyhc6cpVMRTo7k1HnbBXZ+49yvMHUkSePaz1tGJTwr3M0HbYIP3gyaxF2f9sten1520tixJnWsLTUzHr424Rf96nmUMtUTqlCCSK5Wk43sDzg1yjBKUubpr1+ElQRlj/P8JIUSM8W3gPxNC/D0SqXRfvHD3iQ02eMmxaVnb4AXGdwLf3YcurHi0oIUrwLtnHl8FfvY9x3yStNH9t4Ex8AdijP/dkxr0o+JRire10bb3gRvzhstbBcPC3PFMurRV3GlRCSFyUlmUEJRG0eK5OU/Gu6GP6G661J62VWTcnLfUjePWsr3zufO64x+/fYREYENg0Tiq2vKFG3O+5ZUJuVQcVy03TmpChNqmcJyjZYMWSeVUKPjhd44RITKrDefGBQeLlneOl4zzjGXjybLUyrY/zGmD52Pnhrx9XKGE52jZopWk8Z7oBNtl6grx3vLPbizZLvK+LhDcmlXJKzXArLYYKSmNpLGBrx1UjAtN1QRuzxbICI0/TaRe1yguQuc9PnqUMtjoyIximMGyuXtzuug3rDc1wdc/HoU0Wq/ZJek/Nt6/VpUyrfUnmUAKhe06iizVr5mBrUKQm4xpbWm9oNSSRWsJQrBTKryAZesYjlI6oHORTMHeKMMGz//yUwd885UtPnJ+jJaCtw9XyVaGpJg7P84xWt73OiOleOrpzY9jov0HgT+4fiyEeId0I1g//nUxxj97z9teiF2DECJvH604WXV0zjNtHFVjOVy0IAUiJhnY1ZMV26VBK8mq81zZKbEx8s2ZJoTIa7slO8OCCByuWi7t5GRGUs8cQgQ6FymNZlE5BJKTqsH6wMp6dCvRQuBjYKcLqCgwRlDIyHFt0RKM0bTOcli1ZAIIOcumZVp5tIxYH/EuIuTdHivrCyYRbkxXrFrINLRnUtruRI33Z0auAy5AriXzNiBIvkchwMKm960LXkk6UYRIUs/SQCElRyGgej+kNbnzYdvLwpmvZ6f+kySP1rsOG2zwuHBALmAooAt3y5wVsFuCVBLrA9JD3k/oGHsjbcBauDCSfPzShKrzbA0N40zzlYMVNkRklHzswoB542isJ3+MBJcXAI0QQgJvCiF+C3ANeD+y54W4T2ywwcuOx21Z+55fPOS3ftcvfHoD2mCD9+Jf/ADvuV8ldL/O8W8HfjFQAv9ACPEPY4w/9Z4PE+I3A78Z4LXXXvsAw3kwHtSOdvb1s0bbUsBJbSn7KO51mrEUgs55fIg01lFmGgQcVR1SRC7vDDiuuj4MCPZHGVopPvfaDggQSjAsDFXr+Gc3FzStR8jIrHbkWnF+u6Q4XPL5d6YoKVjUDhcC22VGWRhk9NTWsZ3nFEbQ2Ii3qYtiXjtCaKg7T5kLBplkq8ywPnJ92nB91mFkZJBr9gYZW2XOok6G3deOa7LeI2kr17x9XDOtO9pOIFRSWkgp0euQoBhpnWeQQfCeRRc5XjS0RFqX0q9cv86SnK7tc502yyeDLBXuVWBeOay9mzwCmG8Kgg3uwboGLQzgUqfP2WmiACIUmWE0SH05ndcI6QkhMMoNrQ2Mc6hjZFG3kKu+7hbUNjAsNLPK8+p2aoPqnONg0XF+nLOycFJZbi4a3tgfIbXkYNZwaadgmBtCjBws2sc26H+S+MCb2zHGtX/sGt8D3EsgPbFdgw9zwbc+cDBvGeWKk6qjMJIbJ5YQA9OVp9QpiezWtEWGyIFSGJMIpTf2h7St462jiluLjnePa2wEIyU3phYX4dJOzmzekWnoGtgdGTqbTLqPKouzIKSnzCStDUQSkXR+POD2omVnkOMCuOA5mDWs2o6qi9yuLMPMsDUwZMZgIxQmtY2JcJpsNiklLgZaB6sGtoeGzqXSds2arj1ZXIC9kWbVegojkoS2C6l9LCbF0ZrEWZsChwjbA4FCIoXESI8SAe/feyF+krjXuPhJGWg/zTFv8PTxvI3UmwjZfQaQ63SuSJIpfmGSqabzyXtMSRgY2B3nDIuM29OGIlub6xku75TMmyQJr7rIx/dzjlYd46cQv/kU8e+R7Mr+XeC/IG0y/Lr3ec8LcZ/YYIOXGd/9h3+AH3z3/Y9bY6M62uB5IMb4thDi24Cf3z/192KMn3+ft10FXj3z+BXg+n2OOezToVdCiL9LCnV4D4EUY/zjwB8H+Bk/42c8seXEWll0b7LZWVgf6JwnNympOdOKzgZCiKTqIGFSaL54Y47zgaNVx6cvGBZVx1u3lygl0VJybpwzzjWv7gxQWpJJidaSECJaSprOcW1a40NgMjSsmo6jRcflnYKmtXQ2sGod++Ok/ml9xJEImtp55o3HuYYoIiJG2s6jdCDTCkEgxkiIAhcFPkTePl6RK8GFUQFScPO4ZlwahqVi3nhe2Sm4vF0igM+/e8Ki7midJdcCJGghuDmt8MGDVNQuVQAqAkhmlWXaeRSCTKd2HyGgzLjjfwQwUCBkqneuHldoAdPWcryImwS1b1A8jt+R7Y839PNLQ2XvtmORJONsFwMSwaVJzoVxZFo7nPPcXrTUNuBiJFepk8hoRRDJB3l/XFBZCyJSd4FPXSy4ehywIdD6SCYlk4FhWVuuz2t2C8PNZYPJJNPacW6c432gcZ5Cq+dSIzzJ7oj7jf6J7Ro8iQu+DxEXAos6mc1VLnC4aBjmilGmyXQiLG4uGjrnqbqkKpo3jnGRflXz1vK1gyXbQ8Oy6Vi0nlsnK5adQynwXrI3KjmuOqSWSJlMcwVQ25AmkYI8MxzXHaNMIBtJ6zqmS8+tRUvT9Qa80lNFT2U9k0wyrSzLNqAV7OYpPWDZghMhtatFQCY5ZhMTc2rtqVH1urUmBs/IKByS2bKj6VVEZZHa0qTrvYhEOn5UwCcubBG859aiI/rIcRMeaHb9uHgQIXCvZPBx/ujPm2TY4Onhef9dPXcnB0qSt5EEag/jXpY3yaHyAusiCsgEDAvJVqbobMcqSo7rjmsz2Fs07A7z1EabK4a55MruIH2/pxC/+bRwxtdiSfI/ugtCiD8UY/x37n36fh91z+Nndp/YYIOXDZuWtQ1eFgghvgf4TcBf6J/6c0KIPx5j/EMPeds/AT4hhPgISdX6q0mq1LP4n4HvE0Jo0i35Z5O8+J4J7lUWrdvRXtkuiSIZ33Y+cGNac2veclJ1XNwq2RkYrk1rFo1NrSkI3j2puDlruDjOKXLNuVXL56/OOFq1zCvH7jjD+cBPXJtxaafkcNVxbpRTZvoOabU9MPzYuyfcmDasWsvFLYENcDCvOFg07A4MtXMICaVWnBtlnNQdwQVur1oujHNKrZh1jusnNa3zSATzVYcSqW1mZ6BYdoIYk11GoQXj0iB60/B/drDkwrjgtf2Sj+wP2B5kDIzkcNnytdsV06ph0QaKTLKoq96AO7I70OyUAuc8rYdooXUW0Xu+rrrISkSMTN0WnU1Fvuu7LlqfrDfaLtC2iTJaPcTfaIOvfxgeTzwQSFYVtk2hU5lIBNK6Ll0LLFK3j2faBoJPhu51F7Ah9uSxwEjFZKj4jo/uM8wyfvzqCddnLUUmuTDJ6ZznH3zlhFInY+zbs4YLWyWj3OBDYNk4Ohu4OC4odCKk3z5cIoU89Ti7D1n9tPEkCaT7Ldaf6K7BB4VRkvPjnFuzmhvThlnVcX3aMKstrQsoKciUZ76y+D4l7WRl0SJSZoJlG5FSsjNI/V/bA8PWoOCkarg5ryEKLkwKQhTMq5Zla/E+ySe3S0PrAs4Hmi5SZgofwVlHh+RKUTAoFAeLwK15kxQMKr131sAwg2ER6ILASMEwl+Ra0LhA7NPRmp7J0SpdxA8qm4x7z/xFWqDr0kmk24jA4QIoAzJ5c4NPKgofU3qB6qPHY4TGdlgvKLRk6W0ixni4ufAaDyJz1hHnT6PK21SOGzwNFKRzLMTTXYq1yXwQUOj01fnIsk3yaiEgNzAeGOrW8k5bMcySgfa8tbQu0nWBGAKXt0rwgUt3zPJ46ZLY3gc/9z7PvRD3iQ02eBnxOOTRv/OdJf/B/+4XPcXRbLDB++L/Avzs/lqOEOL3AP8AeCCBFGN0fUv0D5GWjn86xvgTQojv7l//YzHGnxRC/CDwv5GWln8yxviFp/yz3IGP8Y5vEYBWknnT8tbR6o46wPrAwCgubuXcnNe8c3vF/iTn3CgH4HDRcWW7IDcKJQTTxnEp11Q21SkXxjmjTDNtOq6eeMaZpmo950Y5lfWMCn2HtJpWltf3BrRd4GBe8UM/MWVkFHmm0AiigIHRqDy1u3mbOjEmA0MgMs4zLk5yrp5UHFaWcyZjUXtmrSUS2B4WBCKrNnnAepeU1LkUDArFzWnNbmkoNNw6qTmaNQwLTWM97x6vWHUO60IKKloFtIbgO/JMESMcLHqtkACTp3pIxWQdUJhUs/gAbZtChDp/qjCxgL3jpv2sZsAGLxoyuKM4i5x66d5bk2p6RdGZ54reP9iR5lnBac0rSWv9gUk+QxcnOZNBzmzZsmoDXV84DzQ0AQojMFqzNyq5Pm3YLjOGReT1vQGL2iKkQEnBx8+P+fJBMnuHxF2MS8WVrQKtJEZJjqoOHyIHi45vuTJhmGla57kxrXl9b/hMlUhPW4H0QuwaSCl4dXfArUXqH7x+VJHJlKi2O8g4WlqOfaDuHMYoCp+mltGauvNoJVFEdoaGg0XDONNkQnDUROousltqglAs6oZplSRpV3aHLGrFvHEUGVS1I8QO6zxKCxadp9CBEBytA+cFQiWmfZ3apBUYDVpILo5zZsZRtY5V51m1kRhhb5AiwgUwypNJ942FZ2gSERR8YlENafJvF2lCr9p0ImQkX6RCJ7mnjIlRFSTyyPdpBe8eV0gEUglmVcC698ZcPgjrEzUjqa+0SjsE+PQZZ/2OPqwr/gYbvB80aZ6FM4/h7nn4oDVHJO1sSZKX1jAXrGzE+kQWhQCFjuT9HWmdQiiAZW1pehls5zwe30fjglGOd04cs8bxxn7apTw3LPjIudHL1L72QfFC3Cc22OBlwm/773+AP/djj378RnW0wQsCwd23WM8jJHXGGP8a8Nfuee6P3fP49wG/7wmM8bFxb7R2Zz1Hy47X9wZkWtF0jq8eVxRaclxZYozkWrDtDbujHB8i0HBUdSltyUhq66g7x2zVsmgcQkDVObYGGU3n2Z1kp21wPiTfJO9ZWceqtSw7x9eOFhytLJPcsD/KWbaOIhMMM8WkMHztuGLZNAxzSWkySqO4sCUoswxUb+BNZFpZpNCMc0ORSVyIGCkZl6kb4/ayY2AkRuXMK8dJbQk+cmuRfFttF0DB3jC/s6l2uEyt/QFAQGEkWkRurxrWlUPXgVCJIJKsa6JUO/g1aRTYtKZt8B6crVEFpxeZdQJ4vM9ra6zTy9fHnyWcIsljWBApjWBnlFFoxW0ECMnSehoLNngGuea4cRTGMG8dWgneuDjicJZa3CKScaEZ5IatQc7e2LE9DPgQGBWK7TJnf1zw5sESJQRaCyaZ4tw4J9eKa9OaECOtDeyPc8aFebK/xIfgkQkkIUQeY2zveW43xnjcP/z7977nRdo1MFpilODaUcXSdtxaWiSRq7VnnEnKQjMuNJ2NTAqJlIZCSXwUfGx/yFdvL7h6VHHjpObCJKexydga7zlYBqDFB+hioOkC02VHmWl2h4aqtbQqci7P6VxEKYghyUnfmTYoKVl1Fo1AmJgKzpCSzoxQZJnA+sS8O2DVhtTipgClKFXE+4gXiRwyKpFQQSS1xEAmNtWdSWTTMrGqWiWFRPJuSRfzuk0KKGNSG07jBEoIjpeBQOohvjdcXJEu6mcT3+6HGNKNANKq4awc8Glg08q2wb1Yx7aue6LzXgatVJKpzmqo4v3njQW2TSJ9rIcYI1pAtX7dp/mtLQx0UhDOutQ/DaeG9yt7mmAogVUTGBdQtZ7OeX7i6oydwvD63vDp/jJeALxI94kNNngZsGlZ2+Alxp8B/pEQ4i/2j38l8Kee33CeDKRMnkc3Zw2tczgf2Co1Wso7r99eNBRGslXmuBBYtpbD3ufw9jIlNodlx+4gY6Albx22VK3jzVsLJgPDziDnS7cWHB0sMZlir8xYOc+isQxyTdU5bs1aauf40o0lW0OFlordQca8dZzbyji+3iKVwnjB3jDnfOcYGkmWSV7dGrKwjlXjWDWeo6XFKMHVaY0PEetbhkVGDBFC4KRzeJc2wUOMhKj55PmMeecpJMw6x6z2tJ3DetgeGNrMM687bs07WpdqkEhagxVakGtDXaVSc71Oa/3peqxzaWPcyKRE6jwsNzvPG9wHvasLgVOxwtnX1ljXBPe+F07DpAKJpBRn/4nkQbyqPV+ZV1SdZWdY8NrugKsnNW0XMUKQGUlZGuaLliAFq0aitCTXklEhU1tajFgfMFKyP8o4N865OCmICKrOc2mr4KSydM5z2HnOjTJuzps7bXI+pI3ncl+h9b0V+tPB4yiQ/oIQ4lfGGC2AEOIS8FdJvhTEGH/L/d70ouwaeBv44a8ds2wtq9bT2cCsaRlkhsoF9nTOlb2Sd48alr2hXUdk1VoWnWNYGq6UGcvOUmrN9VnDKNfcUopV3dHYFNm3M8jxwTNrOm4tO/aGBusF5yYlzsOk9CzawDdfGfOVwxWzqkMpKHKDCxHrArpIUtfdoaZ1AdvB1HfkmWZReaToE9EUOO9xPnkdhSySyVTctr0qyUYoYm/8m+Zob9jdKzF8Tya5dGz0fQudSJ/ZSJAy0npBy+lJdfZEzEkX8hiTf1LN/dvbOvrCm9OT8mlAc9rrvCGPvnHxoBbLtaH8wKQdLCH6VkoPi+5uf6N7kZHkqEJAbSOZEnQhGV+uZbARqAO4DrLek2xN/ua99Lpxp/NfyBRDWwTIYlI1zuqOL91acHl7wGeubH89qZDu+4O8KPeJDTZ40fE45NG/8XMV/8kv/6VPcTQbbPB4iDF+bx+G8PNI94PfEGP8p893VE8GhVG8tjtg1TluzRumlWPVrtgdZRzMG6yPrNoOpSSF1uyPCpwPXJ1VjDLDhUnOjWnN1w6XZErxqYsjDqYtLsC7RzW3Fy3TZcuNWcPFreR99Pq5IQeLlk8NDFdPapQQzGvHqrPcmK1Y1o7ax+S1dNRQWU+mBTF6Fm1Hax2lybk971LrjJB479kdZezK1JZjXTLrDT6ilcMDlY8QA86Djx4lNDE63j6p+2IAZpXDBk/j01rrYGGpnSWGtN4qs+RfJOlTraQiSMFkkGGE5Oq0Roi0ZtoukhqpC0nF3XoonnKQzwYvPwKpA2f9/wfhQWv+dWfCupZYk0eRXjThBJXzGC1oq0hjfbK5KQNLYdkdZRAjRoAl8pmLE7oAX7oxIxYZ335phDEq2evUlguTDKOSOjAi2B1mHPck8yDT+N7MfmeUcXRtjpQB6wNCwI1Zg5SCV3YGz8QP6XEIpL8E/E9CiH+F5Ffxl4H/8GkM6mlg2nQcLhuqzuNickMXISWLlTpJT0eZ4fU9wXZpuHpcsz0wuABfvjkjBkG3FciE4qTpWHUttxYVuVRMckOpI0ZD2zlW1pErCVIiVMS2jlUT8SEVkNMq8Pl350QBudEgBGWmUCJDhJTQIKWm9gIRA1EkhzqjAp40UYwUIKCxESFAm+SFVMekJjIymWznIpl4hw663hQ7Su5clFtArg3nfLqIN/60zUfadLJUITzwBNMiqZ4Wzd0n2f3gOE1Xe1rkzsYobwO4P3mU0/uGASMDMhdUXaTuTnX0A5kIoPuSTwIiAi2Tz1HUkc4mYskD6owKz5GUhIWBoU7nYQyJoA39eRr7YwV9ikiwxGmFUqld9GDZ8gkfyOWzNcd7ivgDz3sAG2zwMuJ3/oXiIT5pAAEAAElEQVQf4E//40c/fqM62uBFhBDiO4CfiDH+aP94LIT42THGf/Sch/ahEUJSEdxetJRG8dregOvTis+/O+XyVlIm3F60hBDZHRp8SMTO4bxlESwxwu4oZ9VYfIzcnHvePloRiEgJs9qileCbLk04vzWgdZatQnN+v+D8VpFa1UpD6z2Hy47WBt7YH3J92vClazMu7pa8sT/k8lbBT16fM11ZGhdwvuHNgyXnJgUf2x9SuchXDype3Su5vupACrSSZBksm46LWzmfu7jN28cNP/buMT5ECuPJdEZlLUZJRABlFHXlqXtzaw2cVOn/AwNXtnLmtaPpPEJA4z3L1ifrEJk6KHYHKZzE9Ouys4RRzWaTeIMHQ5Lm3Nn2xvt1pbzfHAr3/N+QyM8ooLYOFzKu7BSMcsPxqmNnZLg5a5BEWhvZG2c0NhB9oLaBxjr2hjlvnBuyPy5oXeDbX9vh1Z0BLkYOly1V57g5bWit56SySJI/c/ARpSST3HBlp0QQOVx1xBCROnkl35w1vLY7eOobz49MIMUY/4QQIiMRSW8A/0aM8X99SuN6ogghclx1lFqjpIAIV/2SvUnOq9slR43jS7eWrFrHx86P+OTFLQLJA+grN6bcnncYFTlYNOxPShZNYNEEqtaRDRMB5KNnuQzYkC50AjBEDqaWzgUGWWCUZyyalNaWZ5JMaY6rjq1BhpGKFo9UkugjUgpEcAQEJ3Vi7IeZRCOQmcbIiDGSqr/RiJgIItv7CkV/StK0vRKi64khH6BUiUhqbbooR9KJsZbyrU849xDKVpNafpoIrnmvJPB+WPeSPo1pXZA+uNncUb7hsVYZ3UsCtfReXKQ2slzHO+bzCLAh/fOcKtnOGvFVEVgGijz14hNhUKRrRbVW8fXHrs+pxqWbTQZYKdNNTfbJiTL5JmV9X39Kb0mm2pJEbL/s6BN2fjNAjPG/fc7D2WCDlw6blrUNvo7wR4HPnXm8us9zLx0a67k5SwnOt+Ytr+0lFcArOwOqzrM1MPzUrSWHy4bjlUULyScujBnmii9en+NDYFY7doeGPNOsqo6v3FoxyCWNDZysOt4+WrE/ztgfgVQN3kfeOarZGSQPFikEIUaOV5at0rAQNhEzzvORC2M+dWlCrgR/+0u3aaxjXjsuTApqG7g4zmlsIr+MkkgRWTWWqnZE51l0nlJJnI/M28CPX1/gvceF3qvIBo4WDfNKcW6coZXCOkvVnhbg67pAAqMM5o2n0BJPZEsLjjtPJgU2wqrpW4d6O47j5r2/881Sf4OHYV3TrrG2kHD0vsAi+fw+zM93PXeLM5+X6d5+QkEgEkOqATIFjQ0sKodWkiLX1C6RRjuFpnKBZduxajw//dVdvIjYkMQlV3YHlJnmneOKTEumdaQw8s65eX3WcJHTxDWtJZe3S64eVz0R7NkZZByuOgZGPZP05vclkIQQ//7ZhyT10Y8B3yGE+I4Y4/c+pbE9MfgYybTi01cm/NAXrnMwb7i5aNgaaN6eCgoluLSV87k3dljWgR97+yRdzKskFVUCbBSsOkdzvCQKyShTrPpoPaME0ybgY/I9USrFdUopGBmFEQrrPY3zbA0ylJBcGGdYF8kzSd155k3Hpa2S7Vzx49emWBtYtR58pLZpss/bwE4pyQ3slAVSC1rnqatkzO18vHMiOFIRnAOFShGWZy+21kNpoLA9yXTmtbO9n2vF0P14pLJvdTMuFeBtfLD58FnzsrNfnyQip4qODb6x8TAV2poM8jbJp9fPFX2bp+sn8br/fn38uqu4BXwLOoOqhZ2hQhhoF/7OeSRIhJFWaQHkOqg0ZDIgNWgNQwGDXNJ1gTZAZiBTKe3RaIWWKT3SqGfTz/xhIITYfdBLwC97lmPZYIOvJzwOefTrvh3+8391Qx5t8EJDxHi6Uosxhj4c4aVFCJGbswajkofP8arj5qzmtd7DUEnBl28tGWSaj54bcWFiGWSJaPlbX7qNkoLKRo6WLbUL/JyPDbnmPYumo/Oqb0cJTErFIFMYKXjncMWg0AxyxdWThr1RRiYjR6uWVWvRvSfTqvUQI0omn5S3pg2LxrI7zNAIFGmNMywMWQhkSrJoOpado3Oeca54c7agcVAJ2CkNVeO4dVyh+ijlKNIGWmkEuRYs2kCMFhUFUqRdtbPKD0Xa0HbWYRWUmaYKqc3tsIp3NpolsHSbILUNHg7Ng7ta7ud7lJP8fpPq7dG+x7qVLQMmuUBohYyRQSZTCtqioVCST10cMl11ZFLSWM8wB+8CZWHYLg2lUSwqz1tHS37+p84xzDTWR0qt7iQ5GiHxITLIkq9ZkWsuCcGl7TIRxb2yqDCK13YGXJ/WbJeaMjc0neNo1fGJZ1ALP8pFe3zP47/4gOdfWCghsC5wvGgILjBrHHvD5HhupGDZOj73xi7OCzyBm7MWowRv3l7R+dRr4qJDxtSSdmE8QCjFIDcEEWlcIMtgqBUCkZzWAfo2FSTkUhEi1K2jNJoL2wOmq5btkeHWvGXRWA4XDYcr0MZwNFux6pIaQsn+n5J4AQRJCAEdNZkSqV3NRZRIMZe5TO1pXezNw8LpxXt9kjlAdamQte7+sr5wz9d7sepTEUT/s65b0+4HQ2pzWz3FO0FL30e9wQuNdQ/x8/Y9DKRWtlKAiT3p1Cv4DMlAvuoVeuvjDf0OhExzzQpY1OkmMSlSG6fuPY/WKSEKMFl6Y+2gtum8C4CPEqEhNgEt4KPnhphMsD/IGRaa13afbSznh8Bt4G3uFheuxYbnn8uINtjgJcZ/9Vd+kO//+49+w9yojjZ4SfBVIcS/S1IdAfxbwFef43g+NNaFn1ZpBXppu+StwxUny5bMKD62P+TvHFUsWk+Ike2BpvOedw5XiAj744JhZjledExyldq/omBSJvcW6wO1hY+f3yaGQGUdnQt8y7khk8Lwv71zwg994RqDXJNJxcXtgtf3hiwbR2tbbIDdTPO12xXTZY1UgkluuL3sePNohQFe2yuZd55D31F3llXbMassWkDT9WmxmaaxgcYFVm0qwKNI6mnnAROZ1Y5YO0KAcZa8Ws09qc1SpE6IXMGlSc7Kwaxuabq72402dhQbPApMHwQVgZI0h+5354wk0sPS27nEtKa/nwLJkOZ31xfGSqQ6PMugzBRGJpuaj+6NkFrSWk8gsjPMOFxaskxR+ECmDLXtqBrL5a2S3WFOiBLnA//07SmXd0ouTgreOl5xcVzcUREqKWg6hxSCGGLvm6beUw8IJTg3yVm1nqo/fm+UEZ9B2fC+BFKM8T+/9zkhhARGMcb5UxnVU8Ci6fjSrRVZpplkhjzL6TqHUhLnYdZ4dsq00z8pDVdPmsRq+iQ5Q4IMnmFuEmEkQUvBVqlpbWR/mNrTKutRvcl1ptPNRAuIQiCJqQ9SCN6+vSSKRNt886tbfPHqlHeOarQEIcWdyZ+LPk1NAkSG2uBCYGdcQoDbCLqQ/I860gliw2m6U6ag0HC7l0aszcQ6UpEr++L4fmTloxCYaxJA8nAZYJGlorvyT0d9tMZmp+LFx72RmM8bMSaSJ4i0oClI6rx1zz6cqvAUp9JVBJSatJCSsDfQtMEhBdi2J5j698U2LZrC+ofv29e8TwutKGDRwvVZy97Q8F3ftMs3X9kiz14aSvSrwC+OMb5z7wtCiHefw3g22OClxaZlbYOvY3w38AeB39Y//hvAb35+w/nwUCK1m7u+86DpXAqxCYHjqWVcKladY7s0gOR4aWmsZ2+SoZSgtp7caAojUphODBytOj5+YUzrA1Wbjv/YhZJRkTFftRwtO3YGOV89XPLlowUA24OMSaFprENJmAw0J7Xms1dyOg+t7YgIftqVMT9+bUHXOQol2B8lL6Jla7kwLkEErp9E6i6ljORG4KNglMHR0pNnqbYQAuaWOwE7bZe8Huuut8Nwaa2U9QE9a4sM1W9ySylY2UiMknFuqOqHVREbbPBeSE7FEpLki/UgRE4JyjomsikTp50r6xCcQJrfuU5z2kbIMxgauDAp+cj+iFwpblUtSNgrNflOSdt6lBKUmUQJQZlpFnWHRBBCYLpq+fIB7I9zBrlBxEjrPNOqw8fI1ZOKz17ZYtl4BkZxtOrYG2X4CBe3ivtuJishKI1mlGmETGSTj+n5p41Hlo0KIf486cLvgR8BtoQQ39sn47zQsD4wrR17A0OhBe8cVxyvHONcMily8kxRNR1t5yhzxacvTqi6xOaF2OF88ikxEWyILKqOygYyo5jXLklBtWTZOZxPFMY4M2RZ8kcKzlO3Dus9nYdxCMidATsjw1cOlnzhnRmdA+s9t5cOJQRKSoos4EJSFQUP+1sZw9wAkevTlkVtCTFSGIF1kRh7aZ5O/Zii3xVYnGFVzrL7uUhtOIsHxBjcT5V0L9ZF8v0+Yv3+jEQeZUYxcJ7KvVgEwgbPHo8yt54VooBh1qvzYiI7WwdNAxWnZGzglERyDoJMRFOuYJIlQvnCSHJ9ETC6b+/0UIU+/jP2SW0yqfG6kMinLIPzE40UklGeXjuYN5wbF3zsXHgpWtiA3w/sAO8hkIDf+2yHssEGLy8ehzz61Z+F3/2vbcijDV4exBgPgF/9vMfxJCH7drG3D1cczBpuLhsujHJWnU8+Jl3glZ2SL16fsz3MGWSK/VHGV29WDArFl2/PiT6CkHxkZ8AoN3xkb0SeK1ZNxzvW8/regINZx9AYzo8HlJnh+rTC+0ipUvvLwaIl+oDSqe1tlGukgHnteftwwXTV4KLg7dsV08qyajyCyKQ0yGFGdxQ4rjpWrUtdF0oiIigtKWVkYDQHwWF92jRru7Qp3e+JsQwgu9N1v+g7InwGNOkxJAuNzkPnI851+AirbrMBvMHjYy1iWLeXWR59HtVwVyGSk9b0HtgbGVatJ8rAUMH5ScYoz/AhclQ5tPAMCkNrA62H1bwhCljVjkwqjuqOXKbE5p/22g7745x3TypOln2imlF87bjm6knN9tCQG0WpNTIKPvf6Dmar4I295IdslLyLPAoh4mNMxHV/7bk5Sx1WUogHkk1PGo/Td/yZGONcCPFrSXHL/zGJSHrhCSQAYsSRjLBDDFSNQ0uNj4Gf94nzOOc5aRzew82TulfTBDoXEMBWntrFnAcpA+Nc4ENkd2DwvbN65wWDPCPGyKjQRAE7heart2oOq4ikb+NqPT95c8r+sEBKSdVZREz9bqNMEWOSiJZGsD3IqVrHrHbJXNd7RnmGiy0xgIiRKARCRpRPctFccadfLfBecsekl3B9QTs0sLTvPener8UovM8xA9m3yNnefCxEhlkyFd7cKL6x8aKQR2uZqiCRrd4lX6QYT8+b9Txft2uOi9SXnxLVJMIHVg6mjUWrZKI/zjWVdZhCIKqI96ldzpJUf4p+MaXTObjsIjE4lm3gwraiC4FI4Na84fW9F7+NLcb4hx/y2h9a/18I8V0xxr/+bEa1wQYvD37vX/vr/JG/273/gT02qqMNXiYIIX4T8LdjjG8KIQTwp4B/hdT6/OvXqWwvI0KICEArwaWdApNJtBBcnzW8sT+kWrW0LjLMFOfHGfujjJvzDusD108s04WlLBTf9U377Axz6s6T70hO6o7KRnYGGS7C/jCj8Z6dkWZUyDuGu6vWcVxbOuc5XhlGRvHDXz3m533qHMcLy9VFRQgBpSQ3T2q+VrUIlVY0uZJcn1VkQhGD58a0pgnQ2oCWAq0NkoASiohgq5QImfxXV11ScEhSPbFWb0DvFdmbqGbyVHnu7vq9Qd2+OOvBDV5erFvRHqW2VPc5LgcmQyik5PxWyVZpmNaOGycrtkcpcs2GSJlJPnp+xNHSMswkkxxyLXnzYMXWIOeTl7YQIjJddcxax7jQlJmmzBT7wxwpFbkW3Jy3BO/JMgNRsKg9eiBBRd45XmG0xLpAbhRXdgYUfRLz2qw/xHiHLCqM4rXdwV2k0rPA4xBIRghhgF8JfF+M0QohXorzXglB4wK2C5xUFojsjTSv749ZtY4vXp2RacmNWcOk0PgYWTUdrYsYnRxbGuto2tTm0ljYHpcUOrI1KljWFuFjit4GrI9IIrlRHK0sXUzm1pJUpNpAMr/uVoyLjMY5nA8QwKi0a1Bkkqp13Jp3TErNqzsDskwyqxxN51g2gc66O+1tri9KdW8uI/q4y/v1EFtOU6pW7d0X/SeJ2Psi2ZjUHIVMyowNebTB/VCQdrWkeLpeWWdhSFLVLqY0Bn8mxe/eS7Ak7XA0LrWuRQEhBKSEQktiCMSQSNyIp+sAYmpzA5Q/JaO6kIhbrZMnUhY9ZaEYGImMgpOlvSMpfxZpCs8QvwfYEEgbbHAGm5a1Db4B8D3Af9v//9cA3wZ8FPjpwB8Afv7zGdYHRwiRVee4vWhxPnBr3vLKTomWEiUAEVk0LUdVx95QM601McLBvKOzni5Ezo0Nq87iAnz59oqfXmapAPTr1prISWWJMSXGfvHagi+Xile2B2yXmtvLjnNbObcWFdZHlnVgXJRUXYr/Hg80J9c7DucVtYfOe5ZdoPWWUWE4XnSEGCiMQIbIwdIlk+sAgsggb9kbZLy+N2TVeXIjOKkstQ1ApIoPVpQ7YN5z4hnJE2nWvb+/6gYbPC7WWy+GU5+jB3lo3VteaNL6XkmBNoadSUHdeNrOEYTESEkQEu9hJ88YFyZZ1rjIpa2CW7OqF3TAybKlC4GPnxux07rUrSQVtY0URjMpFPujgqpdMSkzMiOpWo8xkkEmMULytaMlTZc4BSKsOsdnL28D3DHrT4nNgZuzhtd2B0gpnnmd8DgE0vcDbwGfB/6uEOJ14KXwQLI+JZq9uj/AEjlZttxaNNgQuL2wRCKZTB5Fbx03DAwcLSxbpWS7NHRWMWtabIShEbQB6qaFLKfrPEYrOu8IIZIZSZ5pnPO0XcA7T/SnhI2iZ+oddAJinirXuk7Fs/OeqvVInYpSpZJD+9VpxSu7BZGkQpIC2pBa22xIyqZcp2L4sDpNULsf1jHmnrtb2h6EszHmj4MqQtedGndX4QN+0AbfELDAUCYi52lDk3bFhlmSToc+Ba0wieyE9y6IYv/GUSEY54ZMCm4vWoKAiCTLUoRnYSSESJGBVgZpIg6H7C8AvjcCEBFykyFFh5YSg0RJzd7QMC40EZhVjpeDpn9kfN0wYRts8CSwaVnb4BsELsa4Nrn5l4D/LsZ4BPwNIcRL1+bc2KTWuXpSk2nB+XGBUYKDRcP5ScGtWYMSgrdv13TBI4Xgp7+6Tesjy1XHvOlwLnBtaqnbRODEEHn3eMWlSUmuFR/ZH9G6wJdvLQkE3j2uOFo2HC9Ti1rdBY6WDXvDnE9d2GLaWGRM65ll5/jJGzN+xhs7DHPJFxaORd3RuoDzAa0k3nsan1rITppI26YQkFEpcG3EeVDSoIziYGkpTOS4toQYyHVvnh1Pa5uH7fsFEnm0wQZPG0UO0iZhxcOw9jwSgNFwfjRgXGiOFx1GpFbLSWFoXCTXkOeKj14ccXGrYF5bnAtY57l6XAEwayyWtG5//dyQssioXIuQQEypauMyo9ASrSSjXFLZSGUtyinEpGBUaD5/dcob+0NKo2md56duLvnEuTFaS1wIGKV6035J69xz22R+ZAIpxvgHScZ3a7wthPjOJz+kJw/fO5q/ujukdYEbJxUiCqSAS9s550aGg3nDrPEIHD5qogjYIPmmi1u8eXvOshEILfBCoAUsG8/2QNL5QKlTKpoQguPKUpjA+VGGGUq+cmtJ6FMK2j7pyQCDDIwWrFrLtOrN5XoVkZIwVOB8JApPrgXWwrWThlFhcDEyax0S2JlolpVD9A7xa5nog84bTfoeeQ6z9tTb5WG43zX/7Pse9hmbFIUNHhWe1Bq2bhd7ErtTa/egez9Lkm4YtUuLLU9SAq0e4OGo+n8+JEVdG2AVIl6Ct6BVZOUDsU8mHOaG/dKwO8iYrTq+0jqMgVEmU4qJh62hYpBJnDf4AFd2SzoH2iiEEJwb5eyNn02awjPE1xcdtsEGHxD/9Q/9Tf7Q33qY5efd2KiONnjJEYQQl4AT4BcD/+WZ18rnM6QPhhAiN2cNQkBuJJmSHFcdF7YKrh7XWBeYFJpl4zg/lrx1tKKznmuzhk+eH7FdGoKAt44qOhdQWnJUdYyWLT7Cpy5MWLaOVWPprOe4SsloKdTHYVzgJ67OWLYOJSIXtwqGuearRxWlEXQelG6puo5RJplVlrazrJoOqSQIsM5x2IXkV2QkhYip7SzAvEpGvELCKJdo4Np0gQiw6jfAvDsNIPG8f2fBphbY4FlBCji3ZcgbS1WnbgHRG22v08jXdcb6n9JQGMnuMCfGgNGSXEtWnadqLUUm2M4Ubx9VvHNSIwKc3yo4nNUcrSyI5IW6aD2DTFK3nkvbGUpmfOL8CIHkizfmNM5xWHk+9/o2XzusWCxqYhSUuSTTEgmMC0PWJzpqKQkxeR5FlxRHSggyI9kpDVLKZ2KYfT+8L4EkhPjXYox/Tgjx7z/gkO99wmN64ii04tw45/a84da8Ydk6BCkpoeoiTWtZdT5FcQaBiIG9YU7nPNdnDZmS7E8Kbi/bPkkgMiwkrXW8sV/QWiiywLzxdDYQXeREgA8RH1xiOEVS8hAT0VNoaH3yRlkTNJo08WNIjKgWkSKTLFoLEpYthGAxKvUtF7kiCtgbG27OLLFLKU8PuphLkqGdkqkNb20I/EFSsdYF+YMiEDfY4INgPa8eZUfrUaAf8BmS5HXkI2iVjqsf8M0UMFDQ+uRvNMkNXYgE51ERhjnMWk9jeym3AJMpdjJNmRmCD+yPciBSdRGpAgMliVFQu0gmVDKxFGkhulsafsk3nWd/XBARz+3msMEGGzwdbFrWNvgGxG8Hfph0S/3LMcafABBC/AJSiudLAx8jIUZKo5D9/dmH5HP6Sh/L/e60SlYUXeDidsm0siA8N6ct3/baNrX1HCxa3ry1oOkcF7ZKPnZ+RJEprp6sOFlZbs4bvnKwYLtUhBC4ter42uGSUiu0luRGcX6c07SO46rFh8CiFeRacP24pvGB69MGGQNKKZTSlFky9R4PVCKkukDbebSUdITTLgnSpva8s8ybyLJJxtdG9EE9fTiIofeQfG5/jQ02OIUHlg0o4bi8VVIXltsLR9VvTguS3xGAMqAEDHPJpMj49JURwUmmrWXZeuZd6vhpPVzMdUpDG2VobZjWLW8frmisY6vUOA+lUSw7y95wwKXtkkwpLuwWlJnhrcMVRsL5Uc7Vac3XjiqWteMje0PmjWV7YFh2nv1RzvlxzrK1ZDq1qZ0b5WRScn3ecGmr4KSytNZzvfN87rWd5+aR+igKpGH/dfw0B/I0obXkUxfH/Pi7U6arjv1xTmYkb9+uiDEic40UgtnKcm5oqFxAS0+uJAHPuDQIIRDR4UUk+oiXCo9AC0kVHI31jLSgVZLgPcvOY62jcYJMgsygc2nylhkURjOt0hPrQtmRGP01kTStQXX2TsRg6FObtIigIrIMuKBRJtL1J8fDyJxS9lHlABLykIx9Pww2N40NngbWuwQfBIZ0Lnh6D677HNMAsj/XwvrA/j2Knuwlze+xSYq9wsMgU8kXzYEzGicSC+XODLbuUq+mEYKdcca1xmGUoFCSED3BKyZlxtYgGfMh4eJWzm6ZEWJgZSPvnlTULvLZK1svvIH2Y+Kt5z2ADTZ4nngc8uhfegO+77s35NEGLz9ijH+1t74YxxhPzrz0w8D/8TkN6wNBCYEUghAj58Y5N6Y11ifVzuXtEiUFCoGWEuss48IgIkxKzd4ow/nAVw5WLGrH/ijneBFZtY53Tla8uj3gx95ZsjfM0udIyXSVEpdtCAQfWcVAAQxzzbS2XD2pubVYe7gmL8bjqmWUKZa1ZWUdUghe2S2JBI6XjnGhaKxnaT2dg5bwHpNrBZwsUpBQpnuiKEJ7JnRns4G8wYsEBeQGGhu5Oa3JVRJWCNIGMOtUZAAHk5HktZ0hxkjevt2SSRAKlm1ItXuU6CJ1BBkpcUisc3QOTlapJbTIBYWQGANZlGwVkrp1nNvLkUpSZqn17FNXJlRtYJAZqtoSBVyb1pwb50zKjKNlx0/eXLA7zPjywRItBVtlxre8soVQ6XozKgyDLHk1t53H6OeX0vy+BFKM8fuFEAqYxxj/m2cwpieOJDetQUaKTIGV5EqwM8hZNC3nRobaBaSIHPbxfJWXvLKtmLewP8oYaMlJ5agbx85OSQgBH6G2jtp6ZpWlsQ7fSyj2c83S90ojqxioQIiR3VJSZIZ549AajAFt+1QnTtvPXIC9AdyuUm3bBBhl0HSphSY6OFqCiI6lfH/yaKSgzGFRgSxAxeQBYz9kdObDlEsvUlT7Bl9fSHqeNOfPhA4mfy+VepcFp15g60XR2da4NS3Tkp6MJPJJkXwA8nz9f4PWHqMEPgqOlx1SxqQ4iknNZ/sblJC92baWXNzKuXrSIoHSmGSy38GwNGRGEmNk0Xm2S81J5Qmh42uHNWUmGWQZv/SbB0wry6QwLw2JJIQYAP8B8FqM8TcJIT4BfCrG+FcBYoy/6rkOcIMNnhN+/9/4O/z+v7F85ON/6nf+UrJMPcURbbDBs0WM0Qkh/mvgN555WgD/M6mt7aXAXdHZMXJhUrA/zhlmGikFIUSUkuwODDdmNYfLmohgGBWHy46DRUtpJI0PZFpgI+AcP/LVY07Od5xUloNZjejVTSe146RuOZ7XGJPUy1LA8apjmGnetRWRSNV5RsawtI5MKaJIZrs6RqyNtK1ja5xzactghOT8GJatZyUClX2vdcC6m2FdbK8L74eVrJt1/wbPExYQNs1V6VKtUPaSI6NS54HoO4EubCm2BwOUkqwaz85IsDMsmVctSkq2C4nWOYs28MZewdHCcrxsOGksA52SlkujiF5wbpKx6AJv7BR89MKET5wfk2cqpbfbZHFzsuzwAXaHhqudI9eSw0XHa3sDWusxWhBjxPrI5e0C6yPf9soWk0FGCOmsajpHZlT6GdTza1+DR/RAijF6IcSvAF5KAqm1ni8frNguc2IUvHtYcWtaMa0dWgjmrafrIq2L7JSazipq29J4IAamVUfnPONMUXUWJaBycHlSMCwyrHCMWosNER8dTRtpvGecK6wHrQPWwSSXjMsST0SLwLiASIAQyVwqcjMBV3YyZJ8cV2hL0/e4Nd3pBV7R924qaPz77wJYD22VvJjW7XTTNhXMD1JpfBgUpBvPwz73SfncbPBy4sP8/QdZMo/H9XMaqHuPMXlmt6ELdy9mzn6/9bxfv742ul8TUyWwNcwZGEkIiuOqpWojVXcqhc1E2t1YE79lX++JIFh0Dh8CSsGscexqjRABKQSddQiSEbcPgqOTBbekojCSV3dGdM7zI++c8As/aV62FLY/A/wI8HP6x1eB/wn4q89tRBts8JyxaVnbYIM7uCaE+KMxxn9TCLED/ADwJ573oB4X90ZnQ2ptIySCaXtg+NG3lyxbx6yyjArFhVHBlZ2S6yc1lXWMMkHrJaNcsWwFUqUgnaNFwyAznB8XeOE5mNdY68m0IrrQp7MqjBDEEOhICudF3ZErgbcOLUWyq3CB2aJNm115JLOacSbprKOuBYHUeidI6/bqzM+43oA7qwh/P3X4hjza4HljXXcG0gZx3de6ZZ7aMKWH7RLGZQFAZx02RKoWdsvIce1pOs8wyzk3LlB0nKw8SgqundSEGJkHj1aCTCus87Q2cHkr55uu7PCpCyNGRcbhvOGry4Yr2yVKCK6dNMwbx1Zh2BpodoaGqvMMC80409TWsew8W4OMUWFY1JaDRcuoMHQ+YH3g2rwF4Pw45/X94XPdXH6cFLb/VQjxfcD/QEqlBiDG+KNPfFRPGL7vATs/TilmXw2eeePZGhjmtWPReFxI9lqdh2GpiNJgXSonCy3YH+R0wTOtWuouMMmTB1FjE1E014rzQ8nB0uN0ZFZZtJI4FzBKQIwIIbHB4SJIpRhpyeGiZdmli+4kT72YRkmsD9SdpXGwttlcX7TXzvFEiI8hH7Ik5rX14GxPWMm+EH8ACj58m9uDEEnscMsHT3rb4OXFh7nstR62CsGJT2yRkDBRULWJNBpIMFk6P+YPYDHXZNF6N830RvejHHKTFmRN5xBCcbzsmNVpjmqgNGBdknNnOikClUzKwUEGxgiaTrDqIFMB6yLvnDSMcoWUihADVeu4tFdgu4hH0LWenWHBrLGMS5Jfm3UvmwfSx2KM/ychxK8BiDHWQrxcP8AGGzxJPA559C0D+Cu/fUMebfD1ixjjfyqE+D1CiD8GfDvwu2OM/5/nPa4PgnV09jqRzfqAUZILk4LjVUeZSb7p4gQXA1ePG7QW2BA4ri2dDVRdZFa1SZUwULRBIVDkRqWN686jjMCIiDCaQEArTds5vA+0JJ/UZe05sZ42pATnXCm28oxF27Go2rTprCXTJrBoVmyXmnnjMRoEii44Ot67Bl8rtxWnxeLGtmKDFwn3U7zdu2ksSPVv1QdHDQYwKHIkEesDRZk2fLcGmpuLlhACLkRihNuLGikVn708JtMao+Dd45pCQxeT/c25ScHrOwUXd0e8tlMQIkyrltvLlr1hxjDT5CZtEI+LgmXjkEKyNyx4dXvA0cqyO8i4tYiMc3nH+ygzveG9T+bZo1wzOW9onSdGyNTza1+DxyOQ/rn+6+8881wEftGTG87TQaEV50Y5q86xXRq2ckMzzMj69AQXIqXWHKxaJlpxuOhofMBZizEKIzu0Ksik5NL2gGEmmTaequ7QWmFcko4WJjVPDjOBixEhIg6BkoooAo2NeG+hL0y9h6pvIdspocwUUkhWdYcnsmiguQ+dvz4hHoXpXxuGtf1jTzIN63qVRv0Q8mikwPcE1eMaGj8K6RT7cSl6ueGZMXtOdz82+PrEWhr9uDtWmkSEZgr2xrCsEoE0LhQD7TlZJZWdjH1iCPdXOzlOlXyqj6MNJGJooGFee+YdaDzhzPsdKa1N0e9qGEGuIcTI1kBjlCRXCqMlOwrmdSQGB9EzyDIGucQ5gckle0XOO3WNlJIYPbOqpuoMO4OMvE+BeMnQCSFK+j+rEOJjnF5+NtjgGwbf97f/Pv+PH5w+8vE//J98J/tbg6c3oA02eI4QQpxtX/7HwH/af41CiF8VY/wLz2dkHw4hRN4+WnGy6u60r9WdQ/b+RUWmcS7gvecrtxdcO9J0IbDqHLsjw9GqZVgoqsYxGmRIAdZHtgtFlmk6lzxVRwV0XoBI/fl5n8J0c1ZxvEqpsjsDg4iS0khyA4vaEUWkNCK1K3jHrI0466nc2pfV0b7PImytUJrkcLy5m2/wHHBvrbB+fPY5Sap375dtOpCwPQStMoyQRAGdDQQp0dIwyQXzuuNo2bE3zpFSUhjFrLLsDzXXpg07w5ydYYESktqldPe6c4wyhQuSz72yTeMjjQ2cG2XkSnJ1VrNoLCcry8Ao9iYZb+wNUVJwYVKQG0WeaS5OCs5vFXzh2pxFbe9KWYNUX+g+ma3MNKvWYX1AxhS08zyUSI9MIMUYv/Nhrwshfl2M8c9++CE9eWgt+emv7/DjV2csmxap4fVzQxofuDXrsLZjMigYtJ5bi5rpylPmgqgEzgdWnUcsW24vLYNMMsoLBpniaNmShciqdizbjpMqUujkV6JdoHPJJFvEgBeKTEVa51AhsGxSEbxWNMxraDtPbjxDndjS8ICL+ljDoi+M1/Hijvu3A0USmbMulCNJvbH2jnkY2j6S/GkTOWtiaj3+dcm8/p4bIun5Y51mFjntgf+wCWlw98X/7N/5Yel+RgABbs7jnZuIkrBsfLoY556mTWogJUH791e3aQm5SIbaPqZFoQ+nrWn3tnmud+SKXKC0ZKfIEAQmhaHMFIMiwznP2yeWUgkGuWZISmo4PynTXA+BeetQAi6MC+oicrLqECKwO8j4rs9eZJC9dC1svwP4QeBVIcT/C/i5wK9/riPaYINnjE3L2gYbvAe//J7H/5R0q//lpFvtS0kgWR84mLeMcoUQgigjt5cd50cZnQsE33FjXvOTtxZUrWWUacpM89r+kI+fG+E93F5UxBg4XrbsDDSvbJccLFp8iBiVktZqF6m7Dsm6ZU7w7nFD2/s9ZjLVDI3rKHyBrS2ti3fWMm202C5tSreuT3yOaV2jubud/yzWCWsWsD15tFEjbfCscXZuliL5GdXudF0+lKkbYH7PYl8CpYZxDgrFyCgu7RQs6oBWAakM50YZN6cNq7altYns3SlzKhs4N87Z6oO0bh2vyIzCh7RZLBBIIpULbBE5XHW8cW6E95G9Ycbf+skDVtZxc1ZzMG9pnednfmSPQaa4sFVglMT5gA+Rg0U6ufbHGcFH8kwhpeRif5wUiY/Q/XusD1ybJqpMiuTJVphn65n4OAqk98P3AC8kgQSwPcj4ma/tcFg13Jy3gOCkallVluvHFgHMqo55Zal8IAuaTAk6H6m6BkXJpJAUueHmouVw2WGUYCIl41KhVE6MgboD6zydjyzb1G/pdKDIBJX3eJ9UPSGeehmtT4DOg/PQymSu/aCid3nmqr02uYPTHuaO9xb3a6bWk/ybBry/AsS+z+tPC/dTimzwfOFIF+0unrZ9Pcg7617y51G8jtaG13Bqiv0gtPF0Pq/T0uoAXQvWeoSAYZHOJSFIxvYP+MC18bb1MCxBlbCoYd6A1jDU6SZ176abIB1/bmhAKKrO0bkIMZLpgnGmaAngW7K8ZJxlZDLF317eLvABdgaaw2XHO7d98kwY5pQaRoXhW1/dZneY4wMvVQtbjPGvCyF+FPgO0q/pe2KMh895WBts8MzwOOTRp3P4wf98Qx5t8PWPGONveN5jeFrovOfGPLkFeR+RCnajoW09P357QWMdmZS8fnkrGelGqBrP8arha0dLZlXL8cpipOBgFrkwyVAikmvD0aJhZ1gyDp7gA6vWIpVCCChMUhEhemuKyiIk+NAghSLGQOtJyVOOO0ojR9rAPrsBR7i7nlin2a430dbvO/t1gw2eNSQgZfIzMgZESKlptk1zvABMnjaDWwd5BplMm7iERJrO68S6LprA3hjmtSXLFLMGfPQsasvuqGBVOxhkzBvL0crhvGd/nDHODNYHZrUjxsik0Bijeee4ZtE4PnFhzFtHK24sGg7mDYumI5OSy1s5jQvkRmJdZNknscUQyXOJVqnroHOBy9tlIo56ZdHatL91Lm0nR8i1vEMo3Zw1vLY7eKZKpCdJIL3QVc606vjC1RmLpmNaWXaGhkIplBSMcsXJquGkcrQxICKsGkfTO5xvjwrKXGO0xPqI85EQAllmaDtLFSBGz/ZkQKRjWQdWbcBIyDNB00XmlU/qjb6g7a/57yF6GqAIsHqITPRBxbXiNL78XgSS4a/sVU9t//0zHt5fcu/3epbG14/bNrfB04WPSaUDUMX3JnFknKqTzhJIjzJf1sbV615l85Bjz6ao9WKkO+RoBEalREiJ6BwupIS0h35vkX42lGCn0DhncSa1tVnPe1ZLGTDMYWgEx42n1IEQBTsjTQSWXeBH35khRWDlI3takCmF9Q7hVTK3FPBtV3aZNi3zyvLW8YpdkjR1d1Rwe9Hxkc7z6t7zNcn7gLjCqUjrnxdC8LK2J2ywwaPij/69f8jv+YGjRz7+f/mPfj6v7E2e4og22ODFgxDi9wK/i9Rp8oPAtwH/Xozxzz3XgX0AhLBW+ERWdUftQjKndp6PbA/42KURXXR85XZFiNC5wCBXvHuc2lrena5492jFrPEMjeDmvGFWOU6qtOHkevbmjfMZISRVdZkpRoXipO5Y2kjofRjXax0dU50xqy3DTIIH1ys11mu2s2syAyiV3n92vb3eKNwE3WzwomBtG9F5WDSwnaXwnKyva13fNTDRgqwwWG+JMSIFlFoipcbHNKN3hzk3XI0Wgs4HKusJQTApDALBrOpYtp5RY9kfZewNBS4aLm+XCCFYVB3nhgKtFZmWhCjonKPpJHXnePP2kq1CQ8xRAt49qSgyxbzuGOWK3EDtHFpJjpaWMtdoBVpJWheSv9qZtf9Z0/4QItemNbr3QErvcc+8W+FJEkgvrPm+c4F/+s4JJ6uOw0XDu8crfuJqy4WtAS4EfAzcnDfEmCamD+AFFCKijUT1KQtaCqxzuBhpXYCmo7LhTiE7LDyNDbQ2JS+NsuSHYmTHUZ/eK2OSjqp4WjCviZI1AdTxaIqN9S+8IMn5Wv9gwkWQiuT1DWR93OPuJDzLm8mGPHr+ODvPPGnXaj1nwj3HrS9bNR9MubZuj1snJzwMa5VT179Pk1o7kTCvApkOtO70nHoQBOnc0YCMgjwzDHLwwRMRLBt/Zx5u66RK0jL9tBe2B8yqBucFRSbJpOb2qsUoz8BoogRtJT4EOtcxqz0fO1cwzDQHi5a/+5UDVo2l9QHnIrPWU6rAqrHUnWV/nD9zSeqHhRDiTwPfCvwEp7/6l7Y9YYMNHgWblrUNNnhk/Asxxv+bEOJ/T0rp/FeBvwW8VARSYz03Zw2LxnJ73jBvOzJlGA8M9SzwE7cWXN4qqLqIkYJioFk0nqNFx7lxRkQkI2zr8c7jpcb5QOsD07pjZ5Azqy0RMMcLtFZ03lFkmhAjMsI4l+hC9p0SjmGmyJXi5qKjc7Cy4S4F0Tp1+ey6P5dgbXq+6FNlOzYqow2eHdZWKd2Zx+s5e6+1xTCHtk119Krv5mmbRLZGYKsEh8DbRB6dHxm0zhj1xvGrKtC6BmPgyiTDaMFybuksaAW1TeelVoGLWwWt9XQ24IErWyVCwMBIlhIuTUquTzsWtaW2jmvHkU9cGDEoNdZF9icpFGfeWqrWMykMRinePlzxtdsV33RpzIXtEmLkxrTm9b1hOreFuG/nwdq0P4j4npa2B73naeIbQoHUOM+tecOitnz19ooY4fq05riySCLL1iFQtNafiThLsrLLWwWjQYaRkluzGiUEFyclKkZuVx1DnSaua+HmvGGkYZgbfG3pnKfzDtdXoEZCE9IvPZBagmKEUQGLNu0erA2yH4azJ9eagKr9wy/4a4WHJpmMrQvvD4Ln0da2wfPBmtQ5q/AJpAt5r4y+c5wlRWOuHeweRAI9SFmW95+3Vuc9bI6tFU6R012JohBkWjCvAo1LxtqlBuFOPcPu+1kupaopJWjagECwPyroXGRa1xQhkUyodK7LGBmVBh/AekVrO6TOGRSCkdd0NqCUJM8Mq7rlZGXRUhIiLFvHu8cVJ1XHwbJloCRlYSiztDNiMoOLcDBvuDat2Cqzl02B9B0xxs8870FssMGzwuOQR3vAj2zIow2+sbEWGP8y4P8dYzx+2YI6Q4jcnDUokYikYa5pvOf8yHB9VtM4z9GyhRiZN44IrFrPwazBek9nFVIKjpYth4uWLkSmtUWqgIiRReMwUhJCalMTQpApwbgs2ClTiE/mUtRMWWichUmhkUISYsC707Xbeq21XnetFdsDmZRK641nDwxiag/yYbOBu8GzgyIp/sckRdG6i2FtVbFup8x1mq+xV9wREoHk+1CdTEGZG+rGYrTkI/tDXt8Z8k+vzzmct5S5wqhkfH0wbVnkHc5FCqPprKPzMC40mc7YKhMZ+y2XxuxMchZVx/HKMW9s6kDSKgXqOMvtRUumJVd2h9gAdWsJMdB0jt1hxlsHMCo006qjyDQI2B0axqVhUVvGpaZzgUVjybTi4lbxnnV/CBHfi1mkFHe1tK09kJ51rfBIBJIQQgL/hxjj//iQw/7+kxnSk4cSguAD7xxXiBhpraNzgVndsFUaFpXFuYBQiY1feRgVgktbJVJIZsuWS9slr+yUGKMptaS2jnkbyLViaOBYWZwPHNcBIXySg4qYJnlMrGmIoLrUhzwQKS58OMhY1B2jHE766LL7Fc6S1DrTcLeiIgKrx/hdONIf/f1a1x6GjJT4sNxsUXxD4Ox8XM+9e72P1oRPsKck6IOMsHNAZ9B2fepZf/w6OWG9unygiXb/WiFg2PfNZRoaF4kxJi+x/uayCIm4fRAhtTaZtxaiTK5gmYZpnVLTjASTQRfAdukG5UgtrgKJFNB6geo8dSvIpcDGwLhULGqH946FD+wNc3KtUTLwlYMlmZYQBDWeo6MWIQUiRs5Ncj56bkimFTenDZ84H8jlS6VC+gdCiM/EGL/4vAeywQZPE3/yH/4Iv+sv3Xzk4//Gb/05fPzC7lMc0QYbvBT4K0KIf0a65f9bQohzPFpw7wsDHyMhRkSEpnPsjDLevLWgtZGvHa44P864elIxW7YcVJZf8ulzhCi4MMr50bennFQdi8Zya95iTOof65yl60CJiDFpw8lGT10F2taxvzXgI/sj5nWHs54ykwwzhQsgjWeQ5XTWcXtp+/Ce0804SOEj7oyCvAppLX/Wa7UCVNjYR2zw7JCT1uhS9QE5MbVcEk/tLCIwLtKcliK9HnsF0jpESnnQmeTCOKcZGM6VOToTvHm4YtFYms6T1ZJl5xEx8QKVjXSd5/xW6iLo6oCSknGhuLw7YLvM2B5laCl5bW/IIG/xPue4tkwKza1Zg7OBvUFGkWv2hoaqC4QI49xwbVrTWs/eOOczVybEKLm1qNFSkhlF6JOyvI+cG+W8ujMg77sOWpvOQKMkXe9xtFYnrQ2z1y1tL3QKW4wxCCF+C/BAAinG+Fue2KieMHKj+Oj5ET/81jHXFw2Hs4aVhbpL7WiVCyhglMm+ZcQxLjOKPCd4j4/pYq4ELOuOYAwXxzkni4Y8AyUFIQZqG4ghTexM9iy/SIxqYZKv0brdxihQRiF6Ay5vHa53BJ53740rlKTdAuKp6khx6mW0VoQ8ykX/w96pHeA35NEGPdaivUhS+qwl0md9jAww6EkjpVKfftDQ9Mev5/N610xJsGeY0rWMdW06vzaRS7sFkmltwUdm7WmyCCQiKYT0/XMDrb2/Ob0nJbGNM03lAj6mVDfdk08+pF2O0ggmA8Wyi1hnOb9VUuQKLSWjXDHKNV8+iBwtO6rW4gUQBZnRSATzJtBYR5HlaAGFMRzNLXXX0QZ44zz40LfMqntdpl4K/FkSiXST08tTjDF+6/Md1gYbPDlsWtY22OCDIcb4fxdC/B5gHmP0QogV8C8/73E9DpQQrFrLVw5W3F40zCrLle0ST2C6bDlZtryyMyBKQaEFs8pijKL2gWGelAvLtmHZevZHGZNMsrKOd48bilxz0nqsT4bcMUScUpwsWxatJYTI7jBHCkVmJIt5xyBXzOoOkNQ+1RsnZxY6irRxfbbEXG/e3YtHrSM22OBJoANiSD5GOusVRvG0VhZAmcEwUwilUARuzR2hJ4907+3bAKoLXDtesT3IWSjPlWFBJS2DTNNYByL5ISEgyoiKCovnpLKMC00UcG6c88lLY+o2UnWB3UHOhe2CUkmMTrK97caxahyZkWgt2RlkTApDayMiBLQWiAifuThOiYxbGT91Y4lWHgnkRmCt593jitZ7dgc5+6OcW4uW7YHh1rzhYN6nso1SF8Io12il3mOY/TwTmh+nhe2vCyH+Q+B/4IzoJcZ4/MRH9YQhpeDTFydMSs2sFcy15HjV4B1keSTPFfPao6WkyBSDTFMYxVBGpjaQyRTVOcg1R5XlcGkptKDMM1obuDqvUuR3P+m7vkgtDZhCMl8GZv1WgAKQfRpa6ylUMuGS0SG70884i3Vx7s68IDhVEJ31n+k//ql6Fa0Z3w2+sbGeZ5JT8+u1l9e9Rtq63xEzOu0e1D6ZugOUADolKNx5zz0TeL2TtqZU1rsSN2aOQZ7koVpFXOOpz3zjSDoXDeDus1pap8lFUjoiGnIhMFLgnUiG9zESRSKYTK7YmZTERWJ5h0bz6m5B5wPWOkaF5pMXSq6fVLR9slrdegqt8DH1XJ80gte3S949rvja8YraeTKjyIFrxw0Do9m5lHF+nGNePhLpTwP/OvDjbPw3N/g6xOOQR/vAD2/Iow02QAjxi2KMf1MI8avOPHf2kJfGJy+EyO1Fh5KCc+Oc48pya9mSyZSiuuocNkSu314iEBwsGz56fsI4BHKjmC1qMiMYFSnteX+SU594doY5+yNDOF4yWznwnnGR4WOkDRHbWnaGBV1IvkmD3FAaOD/JmVeKVWcZSMky+rtU15K0NjOkjWitYWU3RNEGTx/rdfuD5tp6jd5F8G0Sarj+PVonRVwASqNxIWIjFAq8BuPTBvE6sSXTkBnDpa2ScZlxvOqwpI3m1mbUdZdS0EV6XyQRSlLAsDBkUrJdaka5Yneo+MzlCdYLnI+UA82y8dxe1L1/WWRee7bKDBcirXPcmHXsDA03j1uCgKNKc7hokH1Qz3aRM8wyDhcth6uO/aEBBPvjnN1hjguBL1ydIWUaM8Bx1eI8fPLCGHh+htn3w+MQSL+x//pvn3kuAh99csN5esiM4ltf2aa1AYLg9qKhEYFZHRhkUOSCIs+ASOMjgsA12+Ksw0XBtHbUXcAoeGWnQBvFpZ2CrnW03jGtOlZNz5r2k2VpSSbbMk1W38tHs5DkowJQwjEoIosaqu7BFdfag2aNs/3MmmT+1fYHPO2q7X4Kjg2eLwqevQY8J5GYZw3u1h5JgiRHzQREmW4GtT0lPjORPIoGEdqQlHrItBPxIHJyrVISpNjOgemlrAGazjMyMA/3n/+eU4Pus1gTYJKkVjpZWIwSWJWS05oQ0AJ0DsRI0zmuHlaMkjEBy85zRQtGmeY4Bma15WTlOao8UkkyKcmHCqUkQwU6y/hZl7aYVR1Hvay2MBotBcZItIiMCo1RIt1YfaB4uVrY3okx/uXnPYgNNnjS2LSsbbDBh8IvAP4m8Mvv89pLFbTQhYCSgtf3h6way0ltefdoxd4w4+Kk5Pqs5p2jFYNMsjXIAbg1rTFaoLWgMCnxIyJZrixXZy3Xpw2furiVIsW1RmlPrhTbZYbJBFXjqK1HqdTysuw8s4OOTCpsqFg2PllLdA4Z7t7oXSewSdImdfMgf4ANNnjCuLd2fRjq9RtI7ZXWpbpGdnCyatmblGQoFAIXPPP61CR+f6LYGxSc28rBRy6MDfO2Y7vIeXfaULUdQsL2SLJoArbz5FlS+g8yQwQKo6l94KeuL9BGM6s9FyY5l7dKDpYt58c5N+YVx8uOqvVc3in46P6ILiT/om+6vMWy8ywbx7Jx1G3yNFo0jnntKLTk05cnLFvH5cLwmUsjjlYdjQ1Yn64prfcMpLrTgaCkxDpP6zxlpp+bYfb98MgEUozxI09zIE8bwUcaF1ASGhfIlaAlXUwXNUgZIdQMMoPWkqOqI8aAC6BEIAqFbTyVACUjQiiq1lF37o7iQpHIlTaeqoYgMahr9n9dCq4n/ayFznlKA8I8eFfgXt8je+a5sH5yg29YPA9Sz5Iu8pFECp2NiZWk84AIJsIinho3Zj15KgQYkwzo3y9FECAXpy1uA5OIqTU564icNFD5+xNIsR+TUSD93b8vIxIhNTQCoxXOO3yQbBWKgMCHiNES7zyV93QhUAnHpy9NGOSa3UnOrLLcmjUUmUpJbSoZeRdGYgPsDzNe2Sm4sjNEKEHnPK9s5SwqBzISSYRR7SPOeXbHOQOj7pKqviT4Z0KIPw/8Fc7YrMUYX5riYIMN7sWmZW2DDT4cYoy/o//6G573WD4sMilTsdc5lp1nUipyrcgzybxx7A4N86qjzDRKwKy2HC4sn7kyZpRrui5QmkAkspspvAgcGs3tZYt1gRgiMkqCDNxaduwNNaXRaC3pXMSHgA/QtJZOBVwQKJkK5nkV7/hJnsVaBbLhjjZ4Vlir4B7mqbVe2d5bwp5NZJOkDoauc1zeLnnttQlfPljR2SVeJYsJLSU2BEJIysZhYciU5Lj2VJ27E1IV24hRkoFRjApNZT1KC8ZGsWgsK2u5MC65PDLMK0vbOSSCy9sF08bzys6AS5PI9WnD5e0ieTG1juNlx6VJSfAe6wJCRlZN6BVNmkvbJV2IWB+QCvYGhtxolHTY3q8jxEiuVOo48uHO7+fCpCDG9H2el2H2/fDIBJIQwgD/JvDP90/9beD7Y4wv/PUohMhXD5e0zvPmrSVvH69orSfr22ZE8rPFxkhHYNUEgndkZu3YDkZ6XK+QOKktMVoWTYdK/ne0fQpa3wWD5lQRsj5x1r4wmtM+Yw8sfRqDiKceL++He0/GdtMs8g2NZ/XnX5u5n91VWKf7wan0dL3z1ZLM46HfEVune8T+Pb3yqPXJO+xhPGgbT9MY6rZPRCPJT7WGQoIXsIp3pxRmpGQRrVKKgwmCiYxUbfJamuQSR+pLvjAxhJDR+kimBbtbmpuzGuv6i7uWWB+prOP2suWTwxwCGCmorONo1bFsLDGCMQIbIjIKCqPYGeUYLTlatbQuEqJif1JwsmoISJwL7I8Llh185eaCzkZe2yu5EsvnLlV9DJSkP/u/cOa5l2p3eYMNzuJxyCMDvLkhjzbY4L4QQihgJ8Z42D/OgF8P/NYY4zc9z7E9DrSWfPbKFp9/54SDecMo1/zMN/YQItB2M24vPINCsz8wFEXGzVlNqVMLjPOR1/YGHK46vnxzQRcCAyMojGS6amlsoLGeUaZ7Qir0CgTH0aJj2cLOILX0DDNNZR1K5PgQUDGZEct7NtLWPqkb64kNnhQexWh9rYK733Hr9ORH6ZwwKm0YIyX7WwN2RwXx5ortUc5QwbSBVduhpWTWJFXe1eMKKQR7A8XAFBzMm1S/ZBIhYNFYruwVXDIDrk1rTmpHphVKSE4qy6RwaCWYlBlGCd45qli2nnOTHOcjdee4Nm3YHmhO+vP2eNlyvLK8fbggRhAi4nxqTxtmih2juLxdIhCcrCydC4xyTaEj1qX05s++snWXB9L5cc7r+0MyJZ+rYfb98DgtbH+U9Pf+I/3jf71/7v/6pAf1pNFaz5duLmhdZFQqdkrFDecptSSIkAyoYzLiWq0cxiTnc0MkIDAiYj00be/xYntTbBcYFYK6jTh7enF23P9CHfvn7yfpW9j3jy5/ELSApief1hGdG2zwMHyQlI31/Dw7v896E62Jo/U8PIv1nF/7JiWGHSYZbE0U85Wn86dm2feDUZCrpBpse6XempStOvAKygH4Kp0P0BvW63SOGAOZEgyURAlBZgKlUuRGcbRqWbWRk1VKN1FKUmYKIyWfvjjmcN5yfeqJBHKjCQGsjxxXHYJIbsC6SKYhzzTTpSUQ6axFoLhxvGRUGI4WHV87XHBSOQolKIwgRsEwgzfOjQkBzk8M28McESNfOVjxmQtbp9LFFxxfD7vLG2wA8Kf+0Y/yX/zFG498/A9+z8/m05f2n+KINtjg5YUQ4lcD3w+shBBvAv8Z8P8E/gnwa5/j0D4QCqO4uF1QW0+ZS/bLjC8dLLmwVXJpZ4BA8MXrcw7nDcHBp14ZESIsmxQFPlu2SCXxPnBjZvFEcgJKS6T1LDrLovFEIemagI0CF9OG3NEKJA4tk+9LRUuep3LOKLD9hvbaTuBs0MkGGzwJPEr9sN5Qvt8G96QP1XkYBFAq2BlqrA/kSqKBg3mD1pKxyBgXirL0XJ8mg/r9Uc6FrZKDac3BvENrQesDOqYOhTJP7V9FJhllOd/y6hgbIjEEJgPNsg0su0BhkgfqxXHBzjDnkxdyfur2guNlh5KSz72xw5s3V0xryygzXN7OePtwSedC/0NLjEqeRSFGXITzZZY+c1JyflLcCcs5P8qRSpDJZMo9KQxv7A2BxEWsCaMXbSP5cQiknxlj/LYzj/+mEOLzT3pATwM+RjofWLaOgcn4yDnFSXXM0oYU+d0npikBNkIuBUpFXNR01lJ1p+01dy7IvWKo8ynaIJCUDg9KNoD0yz6rzrgX917cH5VQ6uLp8foh33+DDdb4IOaJkVMF0FnCCO42cr/X9vleg/f1zkNm4KMXRtyaWy5tK66fdKCh6VI8J5ymMFjSOShI5G0uIHbJ2JqYJKxVSIoipWDY3yxyDSYTXBqX5ErQOEdrkyfa1kBSZhLbWo6IvVF9pGo9QniMgGhgV2e8sqc4WLQ4H3FBsF2qlNAWIrWNTCuHUYqjZd2ri9JC7/bCsjuElY185daMqosIFWltZJAZhBScH2dIIXBd4LBKFLPzgs++ssVWpnBEsg/w93oeEEJ8krSxcCHG+FkhxLcCvyLG+Lue89A22OCRsWlZ22CDJ47fBnx7jPHLQojPAf8A+NUxxr/4nMf12Agh8vbRipNV8jh588aCd0xFrhSfuTIhN4rjZcfJqqXzjr1RxnHV0bnAsrEYKZjXFikEq9YRZGBZWaxWWG8pjWLRJQVE6yJVDQ3xTmDJnbo7wDZwXIGoHFKmtZCSIMJpD7nk2XtkbvD1jYGAUQHLGqqHHLf2Sg2cBuxI0iawVskI+6453b9nTXoSoe0cUcDeOCPLJIfLjp1BxsnK8u5RQ+sdpU4tYbkQvH1UcThr0EowNoZl3WEjZAommSHPoWkD26Vib2vAMFtRd/9/9v482PIswevDPmf7bXd9W+6VtXT3dM8MszAMgwRYMpsEyEIWIIFkS4zAGmwQxpas0DDhsCQUUmDZIEHYDmJAwtiSQUiEJeEZhVksFrEO0zDTPTM9091VXZX78pa7/O5vOZv/OPfme1WVlZVZndn5svt+I1687S7nvve7v9853/NdHGWWE4Klsx3LznNpUvDmhQGjMmN3kJMZyRduzZARcq347OURt2ct1gWa3qdMYqXYrXJyrZASruyUXByVHIxy3twfIuVpfpGPSXl0f9ERYnxkTyuMIn8Fsk+fhUDyQohPxRi/CiCEeItXJMS/0IqDQcZ7RzVCCO4vLVJIqiyQh2SHkRKGuaL3nlwJlNK4EAgC2vWrrEhvhAgEn5j+uoUyh0ymBeymevBxJJFe33egoXEfLyd92t2CDbu7laduscEnVbN9HM6Sk5vj7mzT2eY2ZxVOG8JJA0am499oiB5unzR0FjoBbQDVwagEV7/fA62AoUlW00yvc8vWzWgupgY1S2pak+uk7SJAbpLXWODxQXB5XFDkipMmMM4VX7m/JIpECxdaoEWkMBKpFbulYTjIkQiiEFyeltw6WqXsAxsYjQoQgSgiISSf9aKNuHWQt+sgBkeVa5QUPFj2jEtNqQ112+F9pDKKywcjDucrskxRuYBA4EPAes+0zMjkK9XE9ieAf5O000yM8afXmUhbAmmLVwJb8miLLV4I+hjjVwBijJ8XQrzzKpJHkFqZ7887Brli3jqu7Q1YdpZJafjK/ZpL0wIXAwfjgirXzBvL1x4saWxSNtyYdTysO2KMnNQdPgoqo5lUmgfzFkSk9x5r0/pjM7ffKMA3yElzKgw0fdoE1zrNgzbrEM2ZMMIttngOKIBBIQghkucguvcX6mywaUaz7pRAysy6DEcmN8FIpfgK2b0/9iUz6djeKRSt90QUUkr8OjJif5jjgudwJRhIiVZwuGiwPhB8JBLpfeTdB0vmvUOK5A5onKf1gqvTEqkU795dUmaK0ihKJdC54ntfv8j1vYpL45LPHoy5OW/oracymoNhBlHw+u6Arx0uWTY9F8cFq94TPBw3LZ86GOIC2BBYtJ7LY0Gm1fvURAAEuLXoMEqglcL58KHc0xDiubOubfAsBNK/Cfz3Qoi3SevT1zltZjvX0Fry/W/ucXfe8N7DmkhgVGkIChsiNqRqv0IpxlWGd57GxUdNUpvgXmUg84koMgqMMUhvESIx/mG9otbr+/l4GnidAXkGrk85MNMMZv03Xi30UXLC84AXRXp8q8EAhYbafeP+1/EDX5993kykC4HSSbLa2qQmyjQc1x4hUwCeiFCHZEHT67DtQLodGnRMTW5erl9fd/oaNzsbQaSKz8aC1Gk3zoeIkIrew5cfNJRGUmSGO8cNi64nhEiVJYls3TnmTcBohfeBt/K0q3G0aAhELuwUzNbe5UXrQCgWXUfd9SjhH73BNOmi2HuIBC7t5HzpTo1WnklVUGaKw2VL5wzHi5aT1rE/9FyclNRd4Cv3F5RG8kvf2EPrV4pAqmKMf+8D9cxbbnuLc4//1+e/wI/8ufee/vY/9N388rdee4Ej2mKLbypcEEL862e+H579Psb4R17CmL4uhBDx6/YkjcBISYg2hegClTF85+UJX32w5MZJQ7eyKKXJjGTZuZRzEtOG2igXLFc9IoZ1WzTYkBbZG3xogb7Oj/Tr3Tojoe5PyaNSQfNKbPNv8aogAy6MYNFFlv1pLMtmlno2wsKRjt9cwWZ6LGJSHmUmbSIrLbm/CB9aC2sB40IhpMA7CARuHa9obOCN3YJVbzmuLS6kTVdnPQ6JiBEp4eFJg1QKoyLT0mB9YJBpylxRGckbuxVvHAwpMsWbF0Y8rFvunjTkuea1nQHTMkMguLNo6a3naw+WQAroFgKOVj2dDeRacbjqGGSG77o24e58xSDPOFn1qYVZCaaV4cq0/BABZH2gd57cpO13rSSdc/gYkQha67k7az+kTjoveBYC6X8APgN8lrTW/9ILGdELQpVrvu3ikC/dXXBtr+C9hw29tdw8adkpMwIpxG7eOtrG4tfV4zacLo47e2oTy4wg055pIam7gPVp4S5IbxbrE4kkZXqTQLLm6LX1TWtQT0EgbWxxX+8KTAClgNU5ZmjO8dBeKUTSMfdRXPXzJBEfR/ptvt+ojpRKuw2dS6SqXiuEnE9kaq4hyIg2aSejjqDWgdkbCetUK8pM0M0cy/b0OTynhFVJesxu/cKNTCH5D5eW3DgmRYaWnkUfiAKs9xgtEVGwXyneOXL0/tQiN1855nUHwrLsUy3npWlONlTsVorWRpSAO4uO49rioySXHmUSwSxEungqKakbT6ElV3cGOBfQUtDaQK4DnY+0zvO1w6Ru+rZLI+rWcGVS0LtACPHc7Tw8AQ+FEJ9i/S8SQvxW4OmDZLbY4iVgqzraYosXjj8BjJ7w/SsDoyQXRjl3Zw23ZytAMCkMK5takjxhTSaliAspoe/SfKPpHSe1pe0dozJlqIYIR7Xj8rRgXOXcmXcIYZMVTSTHg+LDm3NdgEJsmmhh3q/nZOvCn49rtt1ii2eFA95bnH6/cQhs1qh+/f1QpxiHPAPbn2anRpfWwdNBiXWRxtpHERgjndYJUiRStdCK2nq01mgpEMCD+QoRA0bC8apnXBq0UhzOO5yzrLQgk4ooJK31SCRVbtipFD4ELg4LpoOMz1weMSo1EcnhsqPuPJ2NDIaKRWP59MUhd046ci1Z9p5Z6yDC974+RQvBO4c1n7owZFxlNJ3leGUZlpqRzfnOSyOq0uBtwAt4a2/4oY3gVee4ebzi7qzleNVzaVKipUCKZHELIXJ31j5RnfSy8SwE0t+OMX4f8NObHwghPg9833Mf1XNGCJEv35vz3nFLCJGjhce5wOHK0buAFhEfJIedpfXpILGpXZvlGRXHJudodyDItGTReUJMB3ypYZJLxrnm4arH2WRryxQEB9YCIp3wBYlg2hvC7eVHEyfPKxR7Y52TCoYxtb69DGwIga0c4cViE564afv7IJ5EHm3Uc3I96Vk85p911qK52XkIvN/DDOussLXNrOlPQ7RXZ/KNCp0mR4s+UmSnpJc/8zvnoek9izYRUcQ0OdpY5TYybdTaW+0gy9LFy6wPfiEErQvEAL1znHhHphSlVqxs4MHKJ3mt2oxb44LlwbKjzDWZUhRGUveBXGn6ACetp8wELqRaXecDRQazVSKvykziY7LGjUtFYQpC8GRKcmFkWPY9Lkau7BQc15J784abRy3DIuP6bsXBtMKv5avnLTzvCfi9wI8CnxNC3ALeAf7nL3dIW2zx0diSR1ts8eIRY/x3X/YYnhekFLy2W3Fv0fLG3pDaejIR+Yc3Tnh9d0B95Cl0yi8al5JbRw2jyiBbwXuHS+4uWlZ9mgiVEqRRtJ1n1lje2NPsloqH3mNDoNCa3Djm9Yfnbo5T8mgTFWAE9OHDZNMWWzwPfPCYCh/42Sa7qHZpvdytbZiZgt0cZmufmnOeT18c8d7hilXX0K7dOYKk3h8WKXPouHEEIkEr5qseIeDKGPZGBZ1LBGvfB5SEQZaxU2XcPumYFpomBCa5SpEZRBobCBFe3x/QOs/NOy3fd32H9zrPqksZRlenBbUL3Dxa4ULk/iKQackg1zjvuXPScHVS4kNEK8nBKOeL8xYfIVOK77wy5mhpkUqSa8XVaflY8ujz7x2v10eCznneO1xxdad8pFSyPhBiRKukOPqgOuk84GMJJCHEJeAqUAohfjGna7wxKRbo3KOzni/dXVDqlND++feOeTBvyI1CS8GytTTd6YFbFGCbJP0MJOLDstlST57Mo5VPi1iXMli6AJVMi2Pnk21nf6jRUtLNe1aAiaeL7XkHi48xJm8Il82FAT6Z5a2USUnl3MtV+Xxw7FvL2otBUsglxdtZZJy2InwUiedJCjrJqSUzI/2vNofrB09dm4uHIpGmxET0aJGUejHGpDry77/YbP73LqbxtB9Q5K0c5DIRUG2fHrPIkz1t89I2RNlmF0RKUD4RT2IdqO0jNH2ALCJEuki1DRSFx63loz6srXRCUOWGcSl5sBTMm55haXA+sFtldMGTa3C9J4RA7wS9TX7rzkOZGwpjmVSGwmhyI5lWOQOjMQpkjFyaVjysO0qtuXXSpouFCwgkmYaLo5w3D4bMVxa1dxq49yogxvg28GuFEANAxhgXH3efLbZ4Gfivfupn+d/9mXee+vZ//Hd8ll//7Z9+gSPaYotvXggh/tiTfh9j/F9/o8byPGC05Mq0pDSKQOS9w5qruyWdD0gEcxcQIvIzt+bcnTX0fcAFjw0RQbK4dWsVtgoe68AEePcwVYpbmzbRogqP5k6PRTyN0AikIqAtebTFy8JmfbGZ68t13q+Oaa5vTCI4j5Y9jT0hN/I0LDumNUgZIVeCMlMgIlpK2t7i/JowcoG379dEAaVRZFqSZZqR1mRGUZeO/WHO/XlP3VmyCJ/aK2gHER8DNw4bLk8LBkZxtEoZRKNCc22nJESBdY6TumfeOlbWM8iTAqr3kWXnuTtv6B1UmeLCqGCvypBK8Nq0wsXIg0WKxnjc+jaEyO2TBiUEo/XaoveBcaG5Oi3J1xY1JZIayfmAVhLnwyN10nnB0yiQ/kngB4FrwFmP8hz4kRcwpucOHyM+RBbecTAuORjVHNbd+neC1qXsFLEO41016X5aJBUDnLZoxwi3F+5UXbGW6TkPD+YBQZ+8xxkcNqkVoeuTfazMEpGzsulNlpuU8+J9WhCfVYsMxNrqExORpde2uGeBACqVxnYeGxi25NGLgSMpdD74P9+QLoaUE/Q4JdomIL6N7z8en9S2qXl/aLZS6yY0I9BasepcImI1eJdu59fjtC6RRpt2tw1ZuxmLC1DlsPBpguSbDxORnnSsm3UegNbpa7tmyw5GGUd1T9dFLkxyiBZrA7YHnaf3pjKGMgtJKRUiDxaWKjMURjDKNTdnHYs+hegZCYFIkUlOlj3WeZZdakjpOsuVaU5hDPuDHC9gr8qxPtBYx7xxSCN4MO/RSlIaQd07go/sDTOu71R0PvDOg5rXphXj0pwbuerTQAiRA78FeAPQmyykGOMffInD2mKL92GrOtpii284fnL9+VcA3wH8F+vv/7kzv3tloIRArwsuJAKiYJRniAiDQvOV+wtmK8uq6/naYYPzASEEVaZQOoX+Nn1aVCNgf5BaYOvG411aj9QWGhtQ4sPtthv0pHnSBluF/xYvE2eP02I9ddUxHc/zdt2ULFOR1LzzXBilrK5Ogg7p6yqDWedwwTEqM4IP9NYjxNrSiUBL6EOk7nucg4NxzqW9EW3bkxvFYd0hpSDLJHtDw7BUfPvukBtHK/ZHBS5EWhc4nHfsjnJuHtbcs4GLk4wq19S95839inePWnrnub1oeX1vQN1ZDoYFexMDEW4eN0ghuDjMkVJw53BFphM5BHzIdubXttbMyEfk0Kp3aCUx6vSvJ2XKPLo7a+mce5SBdJ7WAx9LIMUY/zTwp4UQvyXG+Oe/AWN67ii0YneQ8d7hCimgdR4fIkYL2j75L31MljUf0wI6cGq5MYBfh2KrdXJ851JWSmUkIQTasCaF1rKaVZ/aprQ8JUpWXTrZR9J9Bxks+5RX49fPo8/kJtmQiABPIo+elXCJpBDf83O4bfGNwuwJs4gO3scOCdKxuyFimg8caI+zpm2Inpx0jIeQCFVxxjZmfVIeKSkwKhJjUvhtDuRN6PVAw7QUPFxE6g88dyAp58yaCO14/PsgUzAuJPM+sDfQZFryzv2ergMZe4pCYSX0PhCjYFRC6zY2v8Brk5JZ4xF4jBIYLRBCpswjqSlljw2e13YzSmNYdo7OOe64QOts8nqbFLDfedgZagalpuk8SsG7xw0Do9ipNHUbGOYapSRVJlm0lohgp8y4NCmZjnJ2B4bLk5Jl69gbvFIZSP8NMCMtCLblL1ucO2zJoy22+MZjvZZACPGDwK+KMdr1938c+Isfd38hxK8H/ihpv+pPxhj/0Efc7pcCfwf4bTHG/+r5jP7D2Czwbp809M7jQuSNvZL3jlpmTc/JoqMNnnvzjjwThE7gvCPXhqFRHLkUK2HEen4vBaUQLORpQ5VYT3bcmQ29s5tssCWMtjhf2KwXFGkzV5LKbBbrA1j61LxW5JJVF4jeEzkj0ljPoYUM9FIzqRSdFXxqP+PuosWFpPAxGoalpjI5O1XGuMqptOTLJx3fdXnMu8ctzjlar/n2y0MaKxAxghAIEVl0Dong7qLn+v4AH8H7ZHHbKQ3Hq1R489nccPekYdFZLkxyJCXTKqPpHVcmSXF4cVxwvLIsWkvdOcpccWfWoqSgMup9trMN8bxTGo4bS9Ok9cOVyYdDtgujuL5bfVO0sP0SIcRfiTGeAAghdoB/I8b4v3/Snc7DSV9ryfe/scu9ecPbD1ZkQmKk4Hje0diAX/su+3C6kM5EYkFXHaxIDOrmjUCEgUkk0nEfkhKJU0vWRrq3cKf5Q7lILVS9Xb+xSEoka6EyqXYzki4Ucl3bKUOSsA4UnHTPdqHYKEK+0S1vW7waOEsKRU4nJzkfr1YLJKJTkRrStEpKt6MVjCqBCJG5hdrDqIhMRzmHdceyiekkvX4cRaqdzRU0NjKswNWn6qTNczV+rXJav8HOjl2SLHbDQjCqCqoyUGWG2apFq3VY3zDDOo/USfp6XKcRTCoQUrBsPX2IiThSmkXbE4UmM3CxKrm97LGk3cH3Tjq8a9BSsltplEjBfhcGBiEEy84iCBgtKIzGeXjvuCVXkguTChcDy8ZSZRqjJdm6fU5KyaVxwax1LDuPFkO+52qZ/jfnyPP8FLgWY/z1z3qn83Cd2OKbGz/+s1/m9/w/fuGpb/+jP/g5/onPfeoFjmiLLb4lcYUUnn20/n64/tlHQgihgP8r8OuAm8BPCCH+2xjjzz7mdv9H4P/7vAf9kWMjbZZ5HzhcRkqjiCEQgLcfLLA2gpSsOpuMa8Jy42iV7D3rvEkboG0irXI07drmE0/n75sYgU2QNpyqtrch2VucF2zWtpY0ry9N2qj1ISn9XVxnCSsYZppMe5adR7gUA+NJQg7hwRKYFrBXGW4c9zyse45XnlJC1I7cGLrOc3FUMCwMg0xxZbfk7rxJljklaK1kUimk0FQ6Mh7mfGeVcVhbhplBSMGoVNSt43NXxxgpORjmRAGzdsWy6xmXOfuDjEVbcGlccLR03DhapbIiYG+YMyoMo8LQWc/deUsmJUWmaXvHYd3zmTO73meVRZPSQAFXpiVV/ng6Rkpxbuf/z0Ig/YYY4yPLWozxWAjxG4GPJJDO00m/0IqDYcHhomXVaV7brXjHR5bWJ+Jn3fqkzfqCEJISaJhDs1YObRaulYBBIXFNIMYU2Ou79Xb7B+QRZ1UaRoDJkyooAIs+LYA3xNUGer1Q1usWqZV7tovEpv1qe2HZ4qPwSe2Dm6yhTCalUVyHeq361LZASD5muSZcT2pP2weilBRZ6vFUfXovleuga0ciUgWnofHFusEsW1tEM/3hTCdY2/HydJH5zqsjHs477swbHtYWpRK5ZbTCxcgw1wTnOVolyV/TgdGRIjfsDTR3j3scnoHRXN6tWDSWWddRt5ZcCZyT3DuuQSgmhaLN5CM5rlAgEOxNCnaLjDd2R+RKsjvMMLOWXCsujgs661EIXtstWXaO9w5XKCW5vFNy5yTtWFwZV7x1MOB41XNxXJwrz/NT4G8JIb4rxviFp73DebpObPHNia3qaIstzg3+EPAPhBD//fr7fxz4dz7mPj8AfGWdsYcQ4s8C/wzwsx+43e8D/jzwS5/baD8Cm5akFIIbGJeGKGC3NPz8/QVlriiM4c5JjXU9IaaclUUj0FLhvMeHtHCOpM8hpHWEsx9WGZn115tN7rOxAVts8aKQ8eQICzgVT2hgUJwWRY1yiYtJ1TMqFNZ5jpskzMizgEDg17nBcMbxE6AJ4FA0Lm0QHy0DuYKlTTdY2o79UUbbBxbKoYTgF27PaW2g7z3TQUZtG1a9Z9X0vH4w4uqkxPpIZwNZpviFO3O0gNvHLdd2KoaFYphrjpY9pZbcPmo5yS3zzlFlkp+6MaNzgWGmuTApiDGdByARPVqnUO2686z6ZDvbG2bJeXEG511Z9LR4FgJJCSHyGGMHIIQoSdzIk3AuTvohRG7PmpSknmlmK4tRiQUttQQVaC0sQ0qM3zCLvklvhBYe1QxuTvSrNlCY9UleJDXD4eqjT+j92o7Gus5ci6RKcjG90TaKC0my+RiZCKxV+GSL/a2sdYunxWZnCz5+YhKBIku7B9Yn324g4CW0HbQi4vxpM1rrYd5HFJ4qg9xInA3JD90noqi2ycYWIuQ6EUfBJ1KmVMkrHGPAx1QHukEOjEpBLiV9iLQukkxogkxJhkXGbqVSc5qEodaY0nDceET09CFlNeVKsuojs8bifGR/ktREe4MC6z1aCUxUaBcJUdA7j5KC5XFLIWFQZAyMou094zLjMwdD9ocZPsJbBxVvHYy4e9JQGAUxsjvIqIzmaGk5GOfEkMK1J6VhmCkmQ82ssRgh2R/lr8TFRQjxBU7nEP+KEOJt0lw48fMxfvcT7n4urhNbfHNiSx5tscX5QYzxTwkh/jvgl61/9MMxxrsfc7erwI0z3988c38AhBBXgX8W+NV8zDVCCPFDwA8BXL9+/ekHfwY+xnVLkiTESGEU86bH5orjuudgWPA1syLTgftzj3m0GSYIpEW1UWmOZIBhtt5c9h92Dmxabs3680aRncXzmW+6xauJjfDg7Jrzo1ws+fq2mnX+6FoI0a/jXYpMpqY03+BcJIaAMZppcASR3DXWRga5JC8jiy7S9ykuJpPJedB6y7wNSCTOp+wgo5JqL0YQITIsNb1z3Jp5RoUiM4rD1hEjVEYjReSkC+y0lv1Bxs4gxzrP33/3CBciC+uJIXJ/0bLsND9za0Gm4Fd+9gK7uaZuHfujjN5GBKkp8cq0wCiBEIKHy55rvWNUGJQQlEYzzDRCCmJIrovHbQKfZ2XR0+JZCKT/DPgrQog/RTq+fifwpz/mPs/tpP/1nPB9jMQQebDouHXScmfRMVt2QEApyaoPuLhe8J6539k3TiQxsZDeJK1NDVFRQtvCko9W/VgSedTAo2oEH0/r0M+SPZJEGinSheRZyKPNwn8ood5WMLyy2BwX3yhE0nEnSMfPkw4dTbpBZ1OQvDYwGZbMG0fvLbjTGk9PyvLK155+G6Fp0qNvXl8ToSA9eRRJiTTKkoqpMDAdZGgluTNvcWv754bMNQqij0QVORjmHNU9zkUqI7lydcLxsqPzkUEmuTqdcGfRc1j3XJpWtNYyW1m09OwMMpZNR2MtRisGuWRWp7rQ3YFmWhmMFLx71DAoNGVIF7LOOkyes1NpBJK9keRgXFIWihvHDeNc8TO3HJemFUYJpgPDIJcIJVjU6S/dtJaHdc/Jyq7bJBSjSuN8ZGdoGGTPcop+qfjNfPxG1UfhXFwntvjmwl/++bf5X/ypn3vq2/+Hv/0N/vnv/c4XOKIttthCpGaFXwu8FWP8g0KI60KIH4gx/r0n3e0xP/vg9Pg/Bv6tGKMXH6PajTH+KPCjAN///d//iQTZm5Yk7wJN5/jKvRNmTWBYSO7NO4iR3lpmdcCFFE3ho2PmkkLb+qSszkkbZ41PhTofFRy4ztpGkS60dttCs8VzxlkhQzjz+XHI9TqjS8Agh/LM2rbpQOvAg4XFrdvIWhdxnSPPYL/KGBeS4+jZLxWdj4SuS88fE4k0KUFEwaz29L6n0hKtNU3n6AMMM8Ww0MQAu2VGFJJcSx4sWiAyXzm+9/oUHwWDXFFoxd1Fx8/cXXC86rg9b7k8Kok+Mh5k3JnVXLo2fRSefbS07JSGw2VHnin2BgVlpjise756v+aXvL5DphVEz8NFxyDT77OnBReeS/B1CPHcKpWeenUSY/wPhRA/TTrxC+DfizF+nJXguZ30v54TvhKCECL35g3zxlJqyUMfWPaOSqcFro2nleDxAx8bbGSkHZDHZItbNv4R6fRRf8zHvQE3TVTw/sW7O/P7Z8VGPbJ542/lrecXGzXbmUzpR3gZ6rFNExo8mbS0pGwv4zbHWEAqi/Ue55Pn2Yckwd4Ew4+KlPfVrmXZm+N98zzd+oE3uxlNn9R3ISSl3rzzdH2yo0kSsepjIqXKXJIZw0nTs7IWSaCxkRBIOwQx4oLgwrgkN5ov33MpvNrkVMZw3HT063rDS5MBvffcPekQUjDIFN92acysdQgiMUYmVUbXBbyI5EZxcVSwP8q5cVSzO6jYHWX8/a8d0XWeSZWxN8iZd45hrvgHN45Z9Y5Bplm2DqUEBLi/6PDrhpadgeErd2uGRhP88Dn/l18o/osY4/d9wvuei+vEFt882KqOttji3OL/Rpqm/mrgDwILPl5ZehN47cz314DbH7jN9wN/dn192Ad+oxDCxRj/6+cz7PdDSsG0Mvzk1474ibcP+bm7M3aqLLWsKclX78/p+0gfAmUu6LrIzKbikKGGUSYIIqLylI3audOIgCcpwD9uYb/FFl8vNImk3KyJH7cmaVwikTxgQnIX5FJy2DhcSC3MjfXJ1ROgKpNKvzIa6+F45Vm2jmWToi3KTGJEYNUndZ1WguAiNrq0uew8yz6pnapMMRkopEypYC5GLoxz7s0aLoyTtazpV9w4ari6W7FTGRaN4+Zxg/eR+dJRSIWSEZMpHiwbYoT9oaHzMC4zZo3lzrzleGVRrWOYGzItmQ4Mt44b6i6RY5enJTGeZpU+T3taa30io2J8REYVRn38Hb9BeNbt7Z8DXIzxLwshKiHEKMa4eMLtz8VJX0rB3jjHReh98koOC4UNgdYF6u79Feebxe0HPwJpsZuR8l8a62mfQ8vZ87wQeJIVb4vzjc3K9nEE0vPC0yqZNpMRx6mV7UmIpHwuIWDZQesdwaXvO5vayDaZXh2w6FKg3tnXevY15yKRQ507JZiKmC5Qi97jg6fM1zt2Ir2wrlvbPEkXnlndk+eG3gt8sHz5nmNSCqosQ+rIF24vORhrpoNE+JQKbs17ikxSGsXxsqe1LrUzKoGRklxJGucptUSKyLdfGlNbi5GSm8cNdeewIXC4aHi4sAyyNpHUS0uVa3YrgxJw73hFX+W0vccFWLSWm0crpEjdE5KAQ6A6y8OFoLGOaWWw4ZDdUc613cFT/FdeOr6e0+C5uE5s8c2BLXm0xRbnGr8sxvh9Qoh/AI/yVLOPuc9PAJ8RQrwJ3AJ+O/Avnr1BjPHNzddCiP878P95kdeHECKHy47WeWZtz/6oYGUDovMsuo62T42uPgS0SBtreh1NMR4YehvT4lt47vdJpdHx8YuyTVbkFlu8KJyVkn9wDbGZx1vgQiHYH5U8mLdIIbkwMiw6T0ukt6lGcNmlebrznhBgtnIMS02RJcW9EoHjOrAzUFipyXM4Wjg6GdEyWT2VlFyYFOSt43DZo2Mkl5qDcY6Rqe341lHNvUXPtNTkWvH6bokgUGaKdr1JrKUg04KskwxzzfHKMciTg+BglLFsA6/vlswby3HdcTDI+M6rUx4sGm4crbgwLhhnhrr0PFh2ZNrjfeTCB7JKn4c9bZOxZpRAK4Xzgbuzluu71blRIj01gSSE+FdJ1oBd4FMk28EfB37NE+52bk760yJjf2j4619qOVy0nKwc1qUT8aiAk/a0tWyo0mK1I9lrPthm1pN8ntqdvrk0afG9zR7a4lnwIicCT3sshjOfn2Y8hUi7aIN1up6SEDSMSni4ANeli0y59vfbdUjeZlftg7trNkJ0p6SSIj1+DPBg4bkw1uRKsOgsbZ/Ct4scxqUhBM+i6Vj1gUFhWNmIXT/XMM+oCsWs8czbjis7BfsDzcNlz8HQMCwU40rT94GVFqxsUjZlUiAkXJoU3DlqyDOBkYZf8taUr92vsT5weVLwxdtzFkc1Qkp6H7i76Lg4zHARlp3lpFFIKTlueoRWdC5ifeDhokNoxapxuGAJIe3ktDZy87hhb1oSSFWjf/vtQ/6ZYUGWnZ9dh4/AgRDiX/+oX8YY/8gT7nturhNbvLr4W2/f4F/80Z9+6ttvLWtbbPFSYNeFCBFACHHAx0w9YoxOCPGvkQoUFPCfxhh/Rgjxv1z//o+/4DF/CHXv+NphzdsPljQ2kGlJ3fTUEtrWURjJycqSScmqT7MeoWCYK8a55nbb4EMKBc7k2g4Unjxv+6Qe8S22eF7YuFsE0Fio+4BQAi0kt05aGhtTMY5PpOkjFZNfb1aH9P4QCAaFYdk6MhOonef1vRGt9TStw0iYFJLagQsCFyLGaK5MBMNcc3FaoKRmVBmWq0DjPMNMIVBkWtI40EJwYZSz6CzWBazzKKWIMdIHz7TQXJqW7F3NeevSkK/erxlkmt4HPndpzMVJycVxwZsHA95+sORgmHG0slyeFMm15COHdc/+6P1x0GdtZ8AnUiOdZqylub9Wks65c9XK/CwKpN9LCjv9uwAxxi8LIS486Q7n6aS/6h0PFh0Kz2zl6NypqmjVw9CkA7teL3g3i9zNovpxktGzJ/rN7sEWW7xI5CQy80mzrRepagJoI5h1k6AIoLIkORUolPD06wY2oxMx0rmkMFpn4NGs7WqbrCQj0u82yPTp+60PELynRyAEmAzKTCClxrpAH0AQCRHuHbVElXb5RhqMUQgESiZTdW89UiTp+MVRwc/fX3LzuKEPkXrV0tqAUaBlzsJ5/v7iiGGheX1/yKhU/PR7J8QQeVh3jHOVHk+KRz7sWdNjBDjrKXJFDLBsLYvaEWPDvLZ44KjuGOWKQguUMpwsW1YdKJ1yoHIJ9xct33ZhhPWBxnuyp9KGvVQoUh3zM1/ZztN1YotXE1vV0RZbvDL4Y8D/G7gghPj3gd/KE9qcN4gx/jjw4x/42WOvDTHGH/z6h/nRCOtMVYi0fQrsvXG44qSxZEqSa8G40BwuLGW+rnYWaRFZZJqTxtGs7ThSgFQpN+ZJ5NG2dW2LbwQ2NsrNsfhRawkDGBlZ9j2SmHKElWJaAbXD+uRG0CGtD/p1xlcf1s1ujaV1qSymyhWrLjBvPJmE6TCHGJiOS1h1zGrPyiY3QF5mCAHWBa5eKFFEbhw66rZnXBqKTGCUYNlZrl+a8G0XR4QY+fm7S6SI1J3H+ci0zKgKzVsXR3zbwQglBQOjuTItyaTk5rwhV5LMJPXPW/tDDkY5+dGKWecojCKESLsu1dkQO2dtZ9anFiyjE+WzP8ofZSV9HDYZa84HtJI4nzKVzlMr87MQSF2Msd/kTwghNnFBT8R5OOmHEHnvqCYEkNKQZy0uxtR4ABBAZymnRZOUFMsmvYGelvHfnti3+EZgkxO0aUp4HJF0Nlsp5/kRmxt7pxQp4FoCysAkN3QusOo8Np4SQ906E0nKdbNaSOSQ1ilDbKBhUEqOV4GuP319vTvNOyoUFEbiolzX2wYQmtZ6XAg4l0iXrl83v61tbpOxwfkAQbDqHEUpaHpHZSSDImNSGXrrqRsHMtD7QK4Fu8OMurMsukCmBEWW8e7DJTcPBUYBQtNYy9FSYoOn1Ia6dRiVGlaKXFFkGiUENgR2RxpjFF2fPH7OeQotUVqxNy7preVYCqSIFMZQmghCUGpBY3vKvKJU5548ArgTY/yDn/TO5+E6scWriS15tMUWrw5ijP+5EOInSe4FAfxPY4xPn3Z/DrBRB2RasTPIOW4sZSOISHKl2RsaXBAcTAy9g2lR0vvInZMVuZK0MTDMBV2f1iHeffwaYrvG2OJFY20qQPH+HN2CNL9eJ0ikGAsDfYRSCHJlCN6TFwZjPVSK46VHyHXTYJ8iLnIJebYWZnioG9gdSUa5wYiA8z25ysiU4KSJzFc9Sgj2Rpqu96AUB6OcSZlxVLe8d7Sk0IoqU+SqQCqJkin7tNSKVdtzZ9ZipMKHSIiBECN7w5zPXR7Ru4CSkrp3HNWWaaV5WPdcmZZc26m4O2upO4cUgsvTkkxJjFHE1hLCmv6IYJRECYFzgZvH6T2ea8X9eYsQcGFccG/WcvO44epOyZVp+bFZRmcDuTvnnksg9/PGsxBIf00I8SNAKYT4dcDvAf7CixnW84WPEQHcPKo5qhsypehF4lcD6U1y1J42rdXNs1djFmzrNLd4sVCkE3CZpZPvyUf1a5KO5alJ8uhPqkiS6w9HOlEMNTgBO6WizDWF1txeNBRZ6tVctJ5MpAsLAVYOnIOdCjIl6PsIal2/KcBLmHUBH2F/Imn7yKJJ8tdxAUZppqUh15KTzjM2ikEeqIzi1omlblOQttHpfZwBe+MUwt10lr63SKUYFJqrewMGRcbxsmc6FCyapB7aHSULWwgRHwQCgfWgQnqtxwuH1NB1DmE0uwVUWcZJ3UAUyAhCCTobgMhyZdkf5Xzu8oSDccm9k5altdyet+yNchZdz4Vhzi/cXXC0XGGkpDKSLiSiLDeaVee4N2s5GJX8E79o51Wwr8FTKo+EEDsxxuMXPZgtvvnx17/yLv/yn/ziU9/+//Cbr/A7f+AXv8ARbbHFFk+JLwNz1msQIcT1GON7L3dITw8lBETQQvIdVya4mLJTll0gxMDDRU/XWQpt0CJSFBnae8aDjFXvaPpIF2JaSMf3b1QbPro6fYstXhRykno/fsBGqUnH48a2pkW6Xa5glBv64NgpFUdNpG56GhcxImUXjU2S14ngYH2/TGsQAkXguPHkCsK6QOb+MjAwik4risyQpr6CKlN0feDNSwMypXA+Msw0eaYotYZBej8eNx33Fx2jTFHlmlvHHcOy5o29IYWWnDQeIwWDXHO4tFzdKRnnaUNaK2hsYNW3WBf4zMXRY8Owr0xLrAvcX6St+QvjnMvTkt4Hbh6tuHXSMMg1O5VBynWB16ylMAopA0rA7ZOGq9MSo+QTCaHnGcj9IvAsBNIPA78L+ALwu4EfjzH+iRcyqueMjeRLKwlS4+lo/Wlr2UYxAZ/cY7zNPtriRcMDqwC2fbrjtHMwWjd8rMKHSaSPUidJTlsYUszzWm2kQGrofaQCpIoUSpLpJKtcSHDrcO0+ngnbC+sKzwjRwnQgCD6SFRk6wCz2SKHJTGAsPK2PXNsfMlKKNsC1nYKHdU/nAg/nHQK4OMq45ftE9oiUwwTQtODWDW1VLtBKcmmYM64yDoYFIgZOasfdoxV3Zy2DMkNmjkUvWPUWLSKdDQQBpVRY7+mdJxOScS4Z5hl98Cgl2R1I6i5yXHd4D1d2S66MK8pccX/ZcWGnJAiYFJo7x5HDlaXpHaMipygyZG+RSiCVooyBgdGs+si4ULx1MOLXf/clpJCEEM/dheMxeFIW3ln8FeCTtrVtsQWwVR1tscWrCiHE7wP+beAep+vSCHz3yxzXs0BKwaVxwTuHS05WFi0Uk0rz+oHmH757ws4g5439AXdOGr5yf0GhJTuTnLsnK07qHkGaly0fs3A4Sx5tbWtbfKMQSfPmsYHV2k65cTqcbQc0GiaVYtVHZq0lRAhjySDT3Jv1CCRZrriyq0AIJrlGCqhyxWFtU76pDwijmJSKwigyKThqHZ86GDApM3ItWTloOsd0oHl9b0DTORobQQRypdjZHbDqHT4Kxrnmwrhg1mi61nJ9b8ju0HDjsOHOUcNOpXEhOQw6G3ABDpctn7owwMfIg7pjXBgKreid58ZxzbVpyaA0SBIJZH1IFlSj+MzFEW/sDx7NzZUQ3DxpyI1cR1qkbCTv0wa5VukxQoy4ELl90uJ8INPqY5vVnkcg94vCsxBIvy/G+EeBR6SREOL3r392riGlYJBp6s7x2iTjztzjbM+sTfK6+jmcoTeZLtt2hC1eJCJPT3J2EbII4xL6Ok1MzvpON6qdnlN72qa6c/McGVAV6U6DXJBnGdY5XIgsWk+hFXUXOFn1rAVGtC7Z1Vg/5qpNBI8L6fvORoSEXaPZqTTiRNJ0PWWhyJRm10i+69Ik2dn6sLbAJdJpd5BTty1Fbih0j5LrHCUFzvJoR08FyJQhEHlv1jJbOW4UNVJKru8PENIwbB0nTU/XOawPqfrTBbSWGJISKjeKicnYHWbMW0sfPE3nyUQkRsGwkCBzbO9YdZF3j2ouTUqmpSG6yN7QpMY1KVJrm4+sGouMUGRJ/TStFEcLS9Nb8ixjpzLsj3NuHXdUxpyr0LyPQozx6Clver5fyBbnHlvyaIstXmn8fuCzMcbDlz2QT4rWphamGCIxRq7vVTS9J3jBwaigs47bJy3eBV7bKbmyV/DTX5vxYOmYN0mdYf2pyjvyeKLIrD9vSaQtnhdKoHnMz3tAupQxmpuI8CDDOjZDQmkEVSboXICwIVMktYsczRuClIxLwzA35EbQhbTeKHPNnvAc145JrlFKIiQ0raMoDPvDjNbDSEKZZexWhqPWE0gbuUYqyszw2UsTbs9q/s5XD1FCseMNn744pOk9mZbMG4uRhv1xycVxzsoFLoxzjuuee7Oet+/X7A4Nn7s0QSuYt55bxw29j7zzcMGoyCiNZNlaeh/RUvK913cojHqUaXQ2xygC9xYdYW1ntS6wO8zZH+Y8XHY0reNgmCGF4OasYdk4docZX7g5Y3doGBWGEOO5a1Z7FjwLgfQ7gA+SRT/4mJ+dO4QQaX3grf0B7z5YUeWOk9oxLQJSCZo6Lam/npO04OsnkLYE1BbPC5vdgt6l4DpBIoO0TGokSG9+IUDGpOKJZ1RDitS2tj9JAdFaS8aFwSjJe0c9bZ0kn5Mio8qTSiZbZx1tbG9ZUqpiHTQhTYaUStlIKkDnHBGN1uC6gJY5ksCFccnRyjIpM5QWyBgZZYroPas+cNJ4ZONS4LRJ4d1SSJZY7NoehxIs256ARIvIoXWctIIrkwGlljifWs4KCVVleLhoKRSMK8PFccHRsicCF0Y5RiuUEigpqFsHRAZlhguRxnlijLQegu8ZF4pMwHRgOFp1PFz0jHLJ5UnJtDJ87bAhiMitkxVGCqosI3aBk5XlwthwbVKwP8xZ2UjwaZL62ReZiP6NxzfXq9niG4afvf2A3/jH/t5T3/4P/NMH/O5f8QMvcERbbLHFJ8ANYPayB/FJsanX7p2ndZEy0zS959uvjFh1jqO6pe5S3krd9Txc9dxddHS9w4eIUuDWO3Rnm28fpwhPMd3btcEWzweax5NHG5QZWJvcAnBKbFYSxqWiyg2HS0vrHSGkOfSoyslEIlUzKcgzQ+8ch4sOoySm9ZS5ZneoGBSGQa5YtI57LmKkoO5TBqlRklVveffEU2mFIJCJtIk7yhS3T1q+cq+GKDgY5+yPch4se3Ij+WXXd9BC0MfATmVY2YDvHMvGcW/R0DmT3BAu8HN35gxyxfdcnzIZGO7POjKlOK57/uFhzbQ0fM/1HQaZ4gs3Z1wa5xgtkcDdecoxujTJsS4wKgxlpunXwdnDQlMYxYVRzqQwvLE3AMCHyDyzxJj+qloky8R5bFZ7FnwsgSSE+BdIlcpvCiH+2zO/GgGvxA6Cj5FlZ6ltYNH3tL2nMIJJUfKwbpF82HP8uBO2WH887kT+tBXoT4JZP++T3uBbbPFxUKQgaR9T4LU/c2C6M1938Gg5H2M6fss1kZStG8FCgKZ3+A763pKtmXfrobPQ+Z68S+8LF2GcSyKBvk8nFylTw4h1ibwaFpIYA42F3gXuzzvq1uIDzJsOoyV3Zi0r64lEThpHbx135i1yLf+MMbK0gVwJpJDslBotBUbDqMhSIN6i47iFQRYYjzMUkkh6TT99a0bvHLNlS5ZllFoipGRokgy36SzzzpJJRes8F6cVvXOMTM5DYKfKMEZyZ9ZwvLSUxkAMLNvAqvWEsGLuAuNCYV3Ax4LgA/PeoUVMdj2p6LxjIAOF1hyMDaMyZ972ibDqHY0rORjlxFfvurLFFs8V3/nDP0b9DLffqo622OLc4m3grwohfowznEmM8Y+8vCE9PXyMeB+Ytw4tBZmWnKx6vnBjRplp7s9W/N13jjlpeqyLFEZyuKwpc4UQaZu6i6frhU3m0ePiBM6qxbfY4uuB4MlRK+O1it8ryBSMhzneu7RJGiBESZEZLo0EfdDUvUUjKYxiVEi8V/TO4UNypeYmzbrLTGE0HC0c9+ctu6MC6wMuBGZNZFoEApLXDkoyrSAEMqMZForgk03usOl4OLdoCVVuWHWOmRKses9nL47ZGxaEGLlx1PBdr035wo0ZtzvHyapjXGY0LuBCZN46Lo5lIn6MxvtIpuWjj8NaszPIMFKQZ5oHiyXL3jItDA+XPRfHOULArZMVd2cd13crLk9Lqkyzt7bHWR+RQnBtt0JrifUhEWijHOcDRsv1uiAS1rc9T81qz4KnUSD9LeAOsA/84TM/XwA//SIG9bwRfeQr92uc9wQkQgjaPtC6huXqlDzakEaCVAM+O/NuMyQmNhNg44uRlHbAQIHw2236LZ4dglPJc1hPUDJ1qjh6kvWtY61QUjAqJFpFZk1k2TmMTn791kU6bwnr21kB1iYiqVApFPtwlSxnmnSxKgQIDZkDkwFEfIRSw06peTBvH5FanQ/EGBBRcOg9to9EPHXv0THQB2ht2sFL1bcKLSNVYRARxkLiA5RaMigMvbcYDSLCwThn0Tpa66gyzXHjcEHgnUOgWdlI3Xt6F8mMYmdgqDKN85FVZ7k8zrhx1DLvXGpfEIIHs5YQIqu+o/URJWAyMJQZPJx17JclVip6F2h6x6r3KZ/JOfbGBcE7pNYoAXmWsTfMmTU9h3XPKFP0PqB4dS8uH4FvqhezxYvH1rK2xRbfVHhv/ZGtP14pKCGIAqxPaocv3VvwYN5SGoVR8BPvnnD7pKFxjhgidadoOk/Te0qTNtMUaX62CSjeBmdv8aLxpDXlQKQN4AgMFSijsb1Fac23HVR40rz4wiCncem4f/vhkpNlh3WBy6OCuYscz0MqvjGKEAu+er9maT2yFzTWU3eeXFt8hINhTkAgVYqq6F3KJhrmKr1XMoX1KS/p828fcW23oMgyEIG6dxChMJrX9yoAjJTEGJECru2VTCrNL9xb8PN3F/TeczDMsT7QOrg0LdAqhVJ3NiCl5NIo47i27A4ytJYcLxvePW44GGQ4F3E+8HDZ40Jkb5hRd477s4bDuufbL47IteLyOLWknQ3HVkIgRcpAyrRir8q4PWvp+pSlet6a1Z4FH0sgxRjfBd4F/lEhxOvAZ2KMf1kIUZLslIsXPMavG46IC44v3l7gnaPtIzZEQkiSvb47taBtMmDOkkeK9MaKrNUZpMa1F0Hy9D5dTD5pmPcWry42p5CnOa7kmdsPVTpucgnKCFoXWfl03G5+3vp03NonPL5j48tPCiEtUyg1IRFSrOs467V3PxeJSGp8uvgMFQSdmslGQ0PvPFJFciW5OJbsVTlHq56j2jIsNMPCcPO4feSbczE1qA0zy0hpGu9xPnJSW3IjCc7jI8yWUGUQcAwyzfHScX23YN51IAJGCpSEIhNcGOV0PjJrPNNC42PKNopSYrJI0wea6Mg0ZEqjlWTVObSUDE2Szy4ah4qRW7MVx7XDB3DeQYjkRlJlGt86hAajkl972fXcOG7RSlE3MMo0B6N00XEOZAhIpakKhYyC0khuLxoWrUcCpSn42oMV333t1YjnF0LsPun3ZzKSnjZse4tvcXzl3hG/9j/62099+3/rn9rjf/U/+kde4Ii22GKLrxcxxn/3ZY/h64GUgiuTkjsnLYfLlr0yo8oUi7rjS3cXNH26hq/6tNNslGdYahatw6b4GAYZ1P0pabQlj7Z4magjDGRyDAgtUTIQhCTPBFWR8W0XhxiVSmUeLjpmjWOcZ2RK0/aWpvfMV54YBcvesz8qOFn2KCydFxRKUhqFBIpMoYXAGENhBDJEbq06iJFpZdgpcm7NaiJwd9ESfWTWOtSsZzpIVrkYoZqUvLE/AJGsZW3vqHvH1w49R3XPtZ2Sb788xsfIvVnHg2WDEIKr04pr0wIfJdPCsOo8K+toXeQXXR1zvOqYrywL4FMHA/aGBfdmLfcXHYNcszvIOFn1HIxycqNYto53Dmuu7VbcPmmIAq5MSqo80StSCi5NCu7OWjrnkFLyfdd3MFqey2a1Z8FTZyAJIf5V4IeAXeBTwDXgj/MKLAhkgJuHLcF6opDUfce8Sy9ey1Np31mZ6EZBsfkDmTVDGzhVazwNyfOsFerbC8m3FgpOfe6b7KHIx0uWN2HYhYFxoei8Z5wbIGKU5uZxi9KpTWGjlssVBP/RMtZKgtJwtEqTnDIHk4PzKaS69YmQCpux6hSOPZBQZJBpRdN68sJQFppLRcmyteRaEoRAa00Ilkmp2R+VBBGIgrU8NrW1sVb31W0gj6lyU4o14XvGl1336T2ocFRDxaoP9M6zbB3DSkOE13cHVIWm0pJZa7k4LZitWlqbLgzvHa4I0iKEYJhrlBAoGel9Cvo7rB1SwbJzvLVTEEJqkqjbFCLuQ7LhFZlMiqgQKU26WDbW4b0lMzlEOJI93zscE2MywboQIQYulyXOR8al4ca8ZaAlg1IzrXJOVpa7Jw32SiCXH93ScE7wk6yLPB7zuwi8Bc8Utr3FtzB++Q//GLef4fZb1dEWW5xvCCH+4xjj/0YI8Rd4zLQ4xvibXsKwPhGqXPPd1yZ8/r1AbiT35x02Nyw6h/OeSamZtZa5TVECEwWVEYQYKTPYHWYMesutxdZrsMXLhwCyDFQUTEpJ00dMjIgoGBaKW8ctB+OMu/OWuvHMmo7dQc4gkzyYW5adJSCRIrKse5wLuBjJjEFHSZUrjlc9lVK4KFAI2s5RKU3nA7ujnDzTWBe5Pa95WPcsOodRiiKX3F9GWueRQnJxnJFpyW/7/tc4aR3z1uJD5PasAQTXdkqWncD5wOt7A776YMmkMry+V4IQhAirPvC9r00YFoZvuzim7h03jmoOa5ssebnCaEXvI2ptR4PIyarn7qyj7R3fdW1KYRTjXNO5gASOG0vvUh7S913feUQiFUZxfbfCx/jKk0Zn8Swh2r8X+AHg7wLEGL8shLjwQkb1nOGIDHNBFyNt27PqHI614ih8WJWxqS1P94WKVF1o1i1Tx+7U6vZxp//t5WGLj8KGEjgooW4SIflBAnFDZH4QG/JSWIhlXFdfKjrnEVIwqjTOexqRdKmRFF79pOPRR5A+kTmRRDYFmSTXkLKUBEl2qNZM16Z9sneggifPNdZ56kY+CuaOAbJM4CLkuWbZdNyatRAChU6ZSLVN1s3cQK7Tuy9T4HxESkUffArpDqeErwWWHdiQ2lBshGz9pINMM6pyLo0y5p3n6k7GZ6+MqLsBf/3n76+JH8XFaUHb9gglkSGFYXddy6LpGRWGgVBoJA9XiTTSQmC9Z5ArlBCsese89+yUBh8lfYCT1pMLQeMiAsfOMKPuIrdOLAfDjIvjAXdmDZmRlJlikBt669nJNIdtqiXNlMIIydGqT5a5c44Y45svewxbfHNga1nbYotvSvw/15//zy91FM8Jo3VIrhCwUxj+0s/e5bjumTcpLFfFU2dDaz3DQtP1nqULPJj327XBFucKEoHRgqPao4lMBwWFkRzXPURonWOnyiAE7s565lJxcax5uOywDvbHOcEHjleWwV7OWwdjxrnhneOWXJMUPFlS20spOF5a9sY5l4YFQqTnfuvCmDvHNc7DvOmT9VMLhrlCS0kInk9dmFJlCmUkygp2KsONkxWzlSUzCqMkV6cVN44aLk0iv+T1HX729oJhoQkhUhnFw2XPP7hxzMEo51P7I0aFocg014yiyNPt3j1ccWmUc9I62s4ybxyXJgUg+Or9Je8drXjzYMjuIOP+rGPWOjIlKcqMRWO5fdLw1sHwEVkkpXglg7KfhGchkLoYYy/WeRxCiLON4OcaIkLvBXtVwQMfiMI9qs58nOLHc6raKICgEtE0KkRKUXfxiWFkzwsfRR5s8c2BzXGWBzAGvE3fK06PS89pNpfmw2HtHnA20IrAovW0vUcZqJRk1kTMOrMrbJ6LZJFsHzOedl0tWxiIPoVfO5dazYSEUsGqT0HUWqXPTQujgXxU9xmsp8o0VS5pWocyiuAC0yrj4bKlcZ7WBbQS1K2nKCQqSOreURRwcZRzaVJy3DpOlikf6bXdigezhtY6Gg/DDHItsCGybBPh1biIc5EoYSczDEuDlqkJpVCC77o25vZxx51ZQwyBuQvsFjm7haHTmnvzJfcXnlFpOBiV3J03LFuLDxatMiKCQSaoO4+SqY0iBMfUFDgXuDQtIUaCF7xxqeLt+5J7sw4pJc4HJpVhOtC01vHOwyU+Smzw3DtuMVpSaInKNKqz9C7i8OwMCy6Oyldit0II8bPAfwb82Rjj2y97PFu8erh5OOdX/p/+xlPffmtZ22KLVwcxxp9cf/5rQogM+BxpGv7zMcZXLrVBSsHBMOe9o5o785bpMOPitGDR9TxYtEQJYw15Dr2LzL1FxLQZbS3U28n9FucAikR09n0EHRECxsOCw7rn4jCnsY5rk4JfuFfT9J7785ZFG6hdi3WCzqV1w7K1uBDoHCzbSN15pmXBZy9U3HjYUJpkY5sOMkql2BlmfO7SmPnKIWTkcNlzb9bwYNFxeZpai987WnG46LAh8ub+gFFluHWyotAaLY+5N29T5ISWnKwsByPFSW05GOccjHKu7VQUWjGtcrwPHK56Hi56lBTcOGr4yv2aL9+r+aVv7nDnpCU3EtU69oc5e4MMpGCnNHRG0vae3UGBVpIqU3ztcMUwU2RasTvKmDV2nZsayEyyNr2q7WpPi2chkP6aEOJHgFII8euA3wP8hRczrOcLKQXjQiNlQIskOVKcKkCeZBvTCi5MDA/mlnGuOWnsY+s2XwS215dvDcw6qM68Ezc2Nsdp8x9nvt8gJxFDDxsYOMe4kiilOFp6GgI+JovmqIS6SxaxCBQa2sccXJvn9BaKHLRK4Y95BoMiESGZT2ojuZbf2ZgC8AalYZgpep8IJIhYItZH+uA5rFtunTT0Pl2gdoYKoQQDY8jU2hrWB4iRrz5sGJfJJ13mSeVzYVIwb3r8vMcLyIzESI0IHV6Qwim1ZFxktM7z6VGR/mY+2d9Olh0nq47ZqqO1iWxr+hqhAjvDgkmVQ+yRSnK86FiufYW50QxzhRCSvUFGmVnKLEAMFFnJorPEKKm7JI1qe0dx0hGjRCAJpPA8oxVVZliEnsOFJZNwuAwIAtEqMhmZlnli64InuMjnLg55fW+AUfLD/6zzh38B+O3AXxJCPAT+DPDnYozP4kTa4lsUv/ZHfoyvPEPV0FZ1tMUWryaEEP8UKf7iq6QpzZtCiN8dY/zvXu7Ing0nq54v3prRWsetkwbnPdemJd4Hmrbn/iKQKZJyQkXaPtK6NP/q3LZZbYvzgU2eqoggZIpzyI1kXGq8SC3MX72/5Kju6dcbwHXvkdbjrMClOFB6H7B9ciVUmeakthwtjxgVmoujnGt7+5ysLCdtz7J3vHlhyMEwZ1Iafv72nFJrLoyz9H6Jns4HRoWmtZ6r4wJLpG49y1Xg13z7lMYHFo1l5TyXiqQM8sFTW8egV1yaFFSZRkrB1Z2Km8crVr3Hh8DJmuxJTXGBv/3VQ17bLcnWc+27s4aDUcH1nWQ766zn4fKU4y6M5vKk5PregCpLY/z8e8csGktmJDulQUr5zVaA8yE8C4H0w8DvAr4A/G7gx4E/+SIG9bwhpWBvmKOExKgMXVjaNqkwPjZZJKRF6KSU5FrR9HabU7TFc4HiVOnWu/eTQwMJzYbwUcl+BongOSv7kyQy00Y4qQODQkKEzKR2tM6DtOuLA2nS0vuPVrcZkhqqyhUiCi5OFSEIeueZtYmEEqTPzqfnVQFy5zn2cV3hCQiBR9B1jtalUDvrUlaSURoRIlrAJFeYLDUT3Dxq6LylQDAuDdFHPCl/7GBUMjCGKAQnqx4tBUpBMIKqKNgfZRzVPT54Rrmhc4EQI3tVRpkb3j1qefdwxcNVyyjLGBVgY+TerEVLzayLHDWeznVEHxjmoGSS21ofeX034839IS4EWuv5mTtzEAIlFLuV5Ljp2S0NIQYEgnGp2RtoHswtNljq1tJ2mp0yS6SckVjfIaRm0VgGgwwb4Bdfm+I8XN2rqArNa7vVK6FAijH+FPBTwB8QQvwjwG8D/o4Q4ivAn4kx/omXOsAtzi22lrUttviWwh8GflWM8SsAQohPAT8GvDIEknOBL96aUWhJrjO+er/mF+7MWFrPzaOGeReRKu0HzfoADlZ+rdJeT7yeNR91iy0+KT7qWNu0ABakWApJpHWOfu5QWuFc4MKk5HDRkRtFYwNGazLl8B4ikZ2RorceF1Iu6sVxjlCSxnlsgL2R5mHjMVkgMwLRpGayymhuHbcc1R3GKD59YUhpFAvtOV56SqMY5BobAtNRQWM9b+xVqcjKSL52XNM4j0QwKTKmlw2tC4yLRO5c3TmdOxdG8cbugBAiX/MLTu73WBex3nN1WuJDYH9YsGgdIUZ6FzkY5fQ+cHvWEH3EhciiseSZIsbIpfEpQVXlmu+7vsPtkwYEqdXtFW5Xe1o8NYEUYwzAn1h/vFJQQmB0CuOSraTQml44XEwLcMVHB2IvI6jGcXGocbaj9dudgy2eD/yZr8+SOS2nWT+FTpMQHVMmUGtPQ7d7Tkmn4FKDwvEy0AGhX4tZgKU7VdxJAaUGEcD497cJTrNE6HQRhpmizBR1H2l7y7KLj8ijANRrFrXUifyqZcCFQGEkvQ+0Nj3qTqmpckXbe0wl0UZRt5Z5a0HAynlKpbgz74hEpFDUXUeYBQKCGKAjcrxqKTPNJNc8mHXMnCPL4PrekGGZURmJ1pLKSIRUTEuD9REhJW8/rLE+IEVAI2h6hwuB0Tr87njVomUKw3tgPY2Fwkiu7lbsFBkr69gZ5nQ+EGMEIfjOK+PUSmE995Ydw1yRZxo3F9xftIQYmRQZo1IzyDIO654y0xyueoaFxvtA6wUlkUGhcAS63rHsPSFC6wPBJwnsq4YY498hkUf/DfAfAf8XXsHrxhYvFsu65xf9e3/pqW//v/11I37/r/nHXuCItthii28A7m/IozXeBu6/rMF8EvQh4EOqNr83b5kONId1z/15w91Zst5rCd7D4szkbpPfuMUW30h81CxyU9xTZsmGdtLAOIup4t56ci25MDI4n6p9juoO4VO5zTDTeCkYaUnIUvYpSnJhXBAihKAYlppL04Kv3q85XvZUucaLSO8Ci9ZyMMq5vjfFKMWlSc6Dec/+wJAZgffQ9p4390bkRpKbRNzkRvHle0tmq566c1yeFByvM0svj0p+0WsTqkx/SLmvteTaTsWNwxU+QN1bpJDcn7cgBSJGrk5LOpda3kSEz984RopUEHRpkvNw2TMuNJlWXJm+P16iyjVvHQy/6YKyn4SPJZCEEF/gCUR5jPG7n+uIXgCigINBTqEUq96iZAr3hcS+ftwfYdZDmDk6//5F/xZbvAho0jFrI0THo7yufkP+OGg4bW7bZBqJcPpG7QC5DsOWnD7GMCNZvgSsYvrc+/T7Yaa4tj/kzryhMprSSBZdRx88IsIwT/a25RkGVce065ApcBbyIqCQZDqy6sAGsSaGoDQKZERLwdxCpmHe9lgfebhoMUowLDK0gGXnubqT47zAOc/DumN5v0ZIwaDUXBjlFJlmv8qZDDRGKQZdYFQo9kY5s5XlvcOaYVFyeVLSO8ftGBh5WHUOqSS1DYzLjExJpBa0LnBtr0jZTEYhEKy8Y1Ro3jwYcHVacW/WsmwtRyvHhXGGkpI2eFadJxBRWmC7iFKCADTWsegiWikWnWPRJr3vIE8y1xACi9axbBxGSW4crbi6U3F1XLBa+80H612OVwFCiF9KsrP9FuBrwI8C/+XLHNMW5w//0h/+Mf7Gg6e//VZ1tMUWrzaEEL95/eXPCCF+HPhzpGnJPwf8xEsb2CdAJiVKCprOclL3/OQ7x6lKvAss1823j1tXvHrbQVu86nic2+DRhjLAumFcK9AelIBKCxY2ID3Mu8je0PBzdxecLDx57im1xAtBqQVFrjFK4F1kd5wzzA23T1YIIRgVmlIr9gaG3sKy77k0LCkywYVRxf4w4zOXx8ybnsOlxcZAVWR86sKYeWN596imtanp8Dv2hvTec3eWSNpcK3aqRG5lBq7vlby5O2TWOI5XFikElyYFhTn1GRktub5bsTMw/L2vHWMkRCH4nqtj7i97lJQoJbk4zrl5vCLGyLDMcD4wbxwXhzmv7Q0otHrsnPxZgrJDiPgYETGt915F0ulpFEj/k/Xn37v+vGlS+J8Bq+c+ohcAEWHRWUa5RhBpOve+DKOn2RFY+Kewu22xxXOAJHmKDYm06R2pHcynMOuGNcnE6YRkc2yeJTg3PE8EtEiPaSNJahqhyqE0mrbzCBkZFppZ02GkRBmN1oJlF1isUog8XdpB21jvchIZlfLiBFUWWVlYtoHepvBIF0HLyLJ3NDaRJM6lXLEYkud6ZROp2/QRGzqcT2NcrCxSKQotOJlbgkjPs1fl1K3DOtgpDa09ld7+mk8fUDebat2Wwkh8SKF4AsH3vJbxxZvHtNZR95FvvzTi1qwhIMjX9Z3OQucihQ7slCU/8NYul0YVtfXU1jOqcnwU3Jl17FWaYWbIpOaosZRasWwdau0sr4zkxvGK3WGJ9REtJEtnmRQGU0jmbc/FaUGpJGhB03gCcNw4Xtur8OuLzHkP4hNC/AfAPw+cAH8W+BUxxpsvdVBbnEtsLWtbbPEtiX/6zNf3gH98/fUDYOcbP5xPDq0l33FlzOffPeKLt465PW8ojGS26h4VnXScKsQ3RShbbPGisMky2qwBBDBaR1ls1rhm/TnXaQNXkObaPpzmcsX1WiGXae28XHV0WuG9p8yTsm5nkNF7T2EMnYvsDHKuTSsmleFo1XNlUnBcW4QQLPrAsMzRJdxfNtxbtCnmocgJZHS9I1OK/YFAKYGQglxJWhuYFoZQCl6bluwOM24crRiVGVIqnE8qwM465queo0XHokk2t0Fh6J3nvcOa13aqlHUkBV3vuTNriSJwaZSzOzTkRnNtb0DdOS6OC4yStNZzd9Zy0vYc1YlY6qyjdwWv7Q2+bqJn8/iNdRwu+3W+qv4Q4XXe8bEEUozxXQAhxK+IMf6KM7/6YSHE3wT+4Isa3POCj8m/aIyi1BobOzQfbVv7yMd5EYPb4lsOEshVkjc/7hh0pBN5RrKhlYUgNBETEoGkk6UeyfqCIJICaPURTGggqY2K9W1FSISQdpDlgnJgaGxg1jp8jFRGk2vH3eOetvUIme6zyf4yQCZA6/QaRqXEaMHduccHGGTgdLLbiVWHkcmKFoFxIem04LVpxTtHDcEG6j4+qrvVa3WgEekvNas75lIipEAhaTrHreMaPFQDjzyOXJ5IjDYMc81f/bmHvLVf0brAqNQURvH9b+5yuLCcNMccLXoujQfcmTdMK0XrItd3R7zzcE5nLUdrGevBJCeEyIVJwaTMqa2j7h2jQrFoHXVveW234tMXhuyUhr/55YdkRnBcWzQRK6BpHSsLi84xrjyVMaysRwkYFJqdylDppH46GGQIKVlVKThwv8pYrBxqV7wqQXzfC/zOGONfBxBC/MtCiN8CvAv8OzHGo5c5uC1ePp7Vsvb7flXJv/FP/uoXOKItttjiG4UY47/yssfwvNBaz2xl2SkNu6OM2ycrjl2y3Z/NttwsBTfW/y22eFEIvF/kEEnEUK5hoBMZZMMm6wh2hzkiBu4uUpxEmQtGMXLSglWBnbFhUhiWvcO1nkwphrkkhMC89RSZ4NMHQzyCca4REkKA/UHOUYS78553Dmuu71SUSnLiEuG0W6XN6cO6Z3eU07vI7shwXFsOhjl9iHzpzpy785bdQcalcYGUkvvzjohgXKS5/lcfLLlz0jItNZ+9NKL1kWXfMSoTM3bruOHGyYr3jmquTisujgt+9s6cCByvHCvrCcvId1+rHpFR9xcdIUbunLQgIheGOT9/b4lzgf1RzpVJwf1FxzUlP7FqKITI3VmLElB3nkJLVtYzLDR3Zy3XX5HcU3i2EO2BEOJXxhj/BwAhxC8HBi9mWM8fIYa1FE5QaImMAWtfnKR0u+OwxUehJBEwJx/x+81x0wOrDiZlROmkGnJrJdzmYuFJuwW4jz+WPdB1pzsMzqSftc6jFEy04bDpCCJ533xwNO60FW6DSQ7TcUHXWxrrubpbcXPWog0oD0Il650SiWDKVMoKkDEw7wNaKx4seoySHC57ulS+hhIggyDGyKAy1K0lABpBYTTz1tJ5cGuibBxTdeiqtMjlOo/gpCETcDAuGBid8gkOM/ZHOb/4+oSV9dw5bmh6R54p9oeG2cozzTNem5TcW3YcN5bOBYpcMynBE9mpMu7OWg5GBXuVxI6ThW6UGy7tVPzKz+zzteMV7zyoeefBksW8x0fIVKr61SSPtJ+vaK3nuLbMe8/QCGwPS+npomdgJIWW9CEyKTMujF+ZIL5LwBcBhBD/GPCHgN9HIpZ+FPitL21kW7x0/OAf/TH+6p2nv/1WdbTFFt+cEEK8Sbo2vMGZNUiM8Te9rDE9C0KIvHtYc2/WcFj3HC8ss9bj1+G7QkAeeaREEjy56XmLLZ4XPrgGqH0q5BkowcVxRRc8mRLUXWBQZExKhVYdJ03PpNQsW49yjmEh+MxexaKH6DyZFBz3ntbGVCwTIlWUVLnCusistWn+LiEPCi8iUgoGKm24ilxTGcm4zAGBj5HpUPMdl0b8oqs7aC1ZNJYv3Jpx+6RBSfjMwYD9UUHnAxeGOSvruD/vKIzieGUptKJUMKkMrYu0tqc0ipO65+bRivvzlrr35Eowbx03jmqqXDMsNfPOYkPg8KSjXM/jx6VmmKfTkZaCGCUxwqjQiAjfeXnMqMo4qju+dlgnu9oHbHIbW9qTiCUfIyFGpBBY5xkUhtb69H0Mr4TjYINnIZB+F/CfCiEmpON0BvzOFzKq5wwlBEqq9E+WCmJg9QLJI9iSR1t8NHqgfsokxSaCW53KUy1JAbTxLzsSGeWf4mD26/vE9eSGAEYJWhsolUYrkSxfLjDzHSd1GqshWeBiTKoopeU6U0kgBRzXyfZWakEfI0YIyixifRrzsgVj0u5DDA6i5WFtiULi1+MhQpbBbpkBkarUdFpSdxYfInWbWhPUWoU1LOHa3oCHi5b7i5ZhMSASWPSWh4uWw5XlsLGUEiaDjExLHi47Mq0wSvPGxRGzuidEQZkphqXBA40NrDqLC4pBoTmsO+r3LFf3SkKAy5OcVe+5fbJiWgUGhebte0si8NbekEIrRrnk7797TKVzmhAYZIqbhzU3jpbcPllxMKw4GOe4EPn5+3Muj0oiNl1EBhlv7e8yzA3744JB9iyn6JcKeUZl9NuAH40x/nngzwsh/uHLG9YWLxtby9oWW2xxBv818J8Af4FXcKpsfeDurGXVp8bXvYHBu8Cq62n78Ggu5kjztM0VfPNCt06GLV4ENrlGZ4lLCRgFSmsInnGRMSk1TeepSoORcKR6xLo9eFgojErh1ydtinnQQiKVQCpD73qk84zKks9dGiJIljPnelYubZjGIuW09i4wqQxaSFa95XAFQir2hznj0rA3zNgZFuRr8uXOrKG3lkBgYAzzzjMoHPfmHZ11OA+dS1lEiEiVSXbHBaUxxBBRMtkX7i1aYoS6c1wYF1gPRgXuLxzXM8W7D2tWvefhPKmVKpMCsu/MOg7GBZBa3jrruTIp8UQUgkFp6K3ncNnz+l5FppONbqMa6tdfb8ihj7KjKSGwPnBv1vFg2XNY9+wMskf3e0UcB8CztbD9JPA9QogxIGKMs7O/F0L8jhjjn37eA3weiAKu7ZR87tKIL92ZYYxGtw67TbTb4gXiceF18PS7UZpT4iicuV8AKpGO60yctrOZmAifxz3nJkg7nPneeli2PdbCisDK9dStp7dgzOlEx5MIqrj+2vWBWlpyDcbkSCkxMlIEgws9syZSGNgtNSeNownQdxC8RSuBIF1oQhSUVeLaGxsY5BnDMkMQuL/s6XqL0or9keH+wuKDJy8kmoiUmnuzlmFumHeWWycpVC8iOW4tMXoyGREoVAh89f6ccZEzX/VkRnK8suwNcw5GOQ9mLQ+XHSF6BClzynnLOHdY77m+O6Iwmp0ySU2tD5SZ5KTpOWose4Oc6zsVK5t2IQeFWafiKd7arbh5WBOD4PpBxUndg4C7sxVaCbou8NabQwKRr9xb8pUHSy5MS17bHTAdZk95pJwLaCGEjjE64NcAP3T2dy9pTFu8ZDwLebS1rG2xxbcE2hjjH3vZg/h6EGMkRDhadXzx9hytBBeGJXVb03YQdIoI6EkfmUxztX4dW7AlkbZ43vCkzd5N99iGSEKCs544yHhzf0DvAncXPb3zZHnGwSBj3lga64hRUGgIIRCBKlNMc4VUihAaKlMyHRqGRqVM0FnD5XHJ/rBkZT298xwdNXgfUtGNViw7i5aS13dzCqN5MO8xUvDWG7tc20l2rXvzhv/fz92jcYG6s1wYFuRGcm/eIBHECMNCMco1ZijpnacwSTF0d95xb+4YF4bBOGNkUmFNiGlz+v6ipTSKpveMS81X7i9QUhARXN2pmHWWN1QyU/XWU2SandJwu/e4EDkYFhCh6T0hRvYGGZlOxJBWksZaVr3j/qIj1xKt3k8sPVaJFFPg9u4g4+Gio+0D1scPNbuddzzzxD7GOP+IX/1+4FwSSEoIBrnhrQsD9kYFs7qj6RxN9/H33WKLT4qvd5LwQSJIkhRAPYnMCQGqIilsFnVP78C79Lwf5EYj6c3ekS4yDogBmhZQ0Dmf/NEiifRkTOHYKqYg7E2rSKbWRJb1CKl5c6/kzqxBCMG0VOyPhtybtYlJN5IJYL3DrW1qgkhrIYpI7z1YKDNNmWn2RznDTBKjREu4txRYa5k3nlJFugg7hWRpQanIonNcmuRomaxevQ9IGVm2dk3yaEaF5GHtOFn1fOpA89WHNftDQ+8i16YFMcL1/QF177hxXFNlgkFeoERkWGraLjIqdWq704qfujFj0fZoqQghNcpJBJ+5MKR3gS++dwxScDBK4XytddStY29coJQkN4ZF6zBagBdUmcQR6PsICMalodQareC4Tq8jl69EqN6fAf6aEOIhKef9bwAIIT5NUqtu8S2EP/Cf/xh/5gtPf/ut6miLLb5l8EeFEP828BfhtM8mxvj5lzekp4dRkovjgp+5PeOnbpwQgb0qY9b1SJE231xI86gQQIr0fccrKLfa4pWBJM3Tz25Q56R2ZEtgsWp551BT9xaNoHWglGPWurUtTVC3PYsuUmoYV5q9UhGF5MGyYzrICIF0Wx/ZHxq0NlSl4u37DdNSMywyDkaCn7o1RxCxPpAZycBo3jgY8bmLQ5yP7A4zPntpQm4UzgV+9uaM1gZGuWLVWT5/4wgZIp+5NObNi0OkhBtHDZ+5MOLqpERIQd1a7sxaLo4LtJLU1nL/uGc8NuwOMmaN5Ut35+xUGdemJa0JdDYyLQ2ZkYQAWibHRYiRC+Mcv1YuSSn5vus7GC0fKYI2jWk3Txp6lyxnTe+4O+9wPvBg0XN9r0ptdkrSOfdYO5qPMbXB7Q0IIfLmfgrwvjotH6mxXhU8z53hc0ubSSm4MMp55/6CaamZlIajVYvotrWaW7w4JEogfT4brPhJIYF2/ZhFdtqUcLLsWXbpwiF5/DFdCdAGpE/BemLd8maMQErwQTAtJZEIAmJIIz+u/SOlngKMTkHYdRforOOw7lh0lhAiw52CSaEZ5iNun6ywPhFTVZYmUMRTq13XJ5GOVuCDx8JawRNouwBC0DtPjIrgA6PC4EVgNMwZBoGPgULA5y5P0RKk1Nw+qpm3yR4nCIQQaXtHiJFr0xIfI6NMYoTkyo7m8rTi6rRkWmUURnFv3vLQ9jjvMFoyHWgujEW6uIxyeuu5d9Jgnefq3hAtBTeOVoQYcTHwE+8e8vZhTWE0y84yzT2DKmNnlDHQipUL5FpyQqCxnugje6OS42XPrLE8rFuGuebdoyXzzvIdV+Rj/pPnEzHGf18I8VeAy8BfjDFuDkNJyrvY4lsEW8vaFlts8QR8F/AvAb+a95fFvhLyQykFbx4MWXY9X7g5Y1Ia3jtccX+2olvXoBc59H36ul2/QsHpfHCLLZ4HBFCKVLZjA5QZzPrT4yyS5twhwsnK0/oFRmmMEnQu8HBhcRHGeYbSaQkvYkSryLjUFFpRGYkLBkEquZk1KVZiMjB8ajfnpO6YNz3jQhNj4LiF16cFFyYVx6sWpRQXRwU7a0fC3jBjWGSPrFyd8zgiO5XmxvGKo9oikAxKgQ+Rpg3s7RUcznvuzRrePBikNmgpuTDKOWktd2YdIQRsiOxWGSsb+PTBkFXv+NylMVWuEEGgtGBvmNP0jpV1aZ5e5kREsqUp+SjDCBLZA+k9vyGCppXhi7dmWB84qnu+/fKISZlxsrLcnTWPiKGPsqMpkbKTQohoJXE+rKM1Xp35/gbPk0A61+dFoyU7w4xSJRtKsyWPtnjB2JBGGxvak/A0E4uNIilb39YGmLWpUW3T5vbBHa6hTBeQjR86V+AESAc6g0hEG4WJgjJP3mgtAkvnaNcTILN+vrAeaO8iNqRmtlsnDSLxPWRacm/ZMi6Sn7e1HhsiUqZQbbmuBUWDtWlcUoDUmoNJzn6VMcw1X7g1o8okg0zhHfQhkmtBVRQoImWuKJRmPCi4sleyajzHK0tZKMpGsTfIKDJFbwNNn9RPeaH5mVtzlBK0PnL9YIAQAqMlUgpyLSkzxShTKS+tEORGcn2/5PZJx1fvLdLr9oGHdU8fl0zypDDqg+JLt2b8/O0FkzLDhsiFYcm9xYoruwOmlWHROB4eNyxbx+4gY68qmLU9WgTevr9EKUFnA0oEbhy3EOF42ae/1yuCGOPfeczPfuFljGWLl4NnIY9+6JdLfuQ3/YYXOJotttjiHOKfBd6KMT5rEfK5QWEU33V5hy/cnPGzt3uMgtZFcq3wweMtNGs1+GZOlnHakvXKvvAtXjo2cRSQ1gQbgijT6VgbrA+yfr1jHSJoLXAuclIHcp0KXkojaC0UuaLxAVzKLc2MxGjJw6Wl7gKXpxW/+PoOd2YND5c941yzOyjZHWruz3v6PhFKIQSWXVLdXd6tGFeG+4uG0kgeLFuOV+nd8D/+7AHT0nDzpCHESAwR5yKtCxytLJ3zTErD/qjAh0AfPIeLdk02Bb5yf8mVaclrOxV35y2itVyZFAgJNw4bZo3l+t6A3coQQiQzEi0l9xcd04HmtZ2K+8uWymmujAsOJgXj3KC1XP99Ba31j80zCiFysrK8vlvhYyRXklUf2Kng8rTkvcMVi8aSacWlScpTsj68L1RbyvR4d2ctnXOPHv9Vsq5t8C2hQALoes9P3TjhnQc1Sopk03FbSekWnxybycDZytbAuuZewjCHxqcT+Mqe3uYRGUOaVAyyNQnkTnOGnsQbyHWgtXdJdfQkZVMACgOdhbpPFxkjQWRgBMmzKxRCRoyMtAoujoe0hwsEAaGgUrDq08XqpAVDRAC5Sa+nKjVawMO5I8QAwSfvc+tS8LaUiBwKJQlRoGVgET1KwiDTlKVExkhjPZ2PNNbR2IgSiouTnN4FRqWh0JoilzTW40lSWiMUrbMc1z3DQgGCYZkzzTV98EDOpXHBfJk833tF9sh3HGLEKAE03Jt17I1ytBQc1T0P5palDhwMc17fq8iV4HjVU2WSMldEH7g/7yhzxecujnABGuspM4P3gTZ6cqN466Dk1knHhUlODLDyjqHWdC4wzjU+BvZGBa2zgCYzmsIIdoc5Ugj6EMh4tWStW3zr4d/+L3+MP/2TT3/7repoiy2+ZfFTwBS4/5LH8XUhiEQk3T3pmPeeTEsmpaLrYdZ6MgFdPJ3r9WwVSFt8/QikOXmMUOm0iG/X7cx5JpEhMO9hksG8TwU4XR8xKrkPbExKIiUVQjq896gUh00QgegFRaYxQjAqNVokhf0b+wOmVU7vPFpL3jtaMcwkmdb8wFu7hBC5N29ZdD0XXM6to9TS3Lie3YFhWmmMjLx33BCj4MpOybBIwdQ2BnyIeJ9ayIa5ZJILvnbkGBhLZwMHo5ShdGmcY5SkMIqDUc6t49TaJqPgO66OuTfrqDuHEoLdYUbnAkpKRoXm7kmqoVZS8ukLA6xPhNC8ce8jie7OWowSH8oz2jSolZkmxEieKbp19qmWgms7JVemJUoIGue5c9IQ4UOh2oVRjx7vSY1t5x3Pk0D6m8/xsZ4rQoi8c7jky3dnfOXhkr53dP2WPNri60NGsmD1/v3+dkcikew6R6hYEy3WQxPeTx5FErEjOCWG1m4v4P3WN7W5T4RmTeh83GnHJE6FTKaLRowQJZRrZVJhJEKIVGNZGa4YxSjTzJuOYQHOB1rnWPWBSqbH6UO6EI0KyE2G9xEtk5KnyjSDUjNfWfaHOUIKlBIEHzFaMG8tuTYIqREEcqUZakXde45WNZnSKKmIRHzwLOqevXHBWwcj5iuLIzDODcPScH1apQucruhs8nEf5pJ54zhue4KPDEtD3TseLnsaH5i3js41ZEZyuOiQwN1Zx9Gy496i4/vemBJJgXldDDw4aVh2Dms9R21P3QV6FzluLSF6ru5N2R8mGa0AvHOURuNj5MqkQgpF3XoOxjkXJxnHq6RQ8j5lKrk+MikVfuUJWjIpNZfGJbvD/H3+6y22OK/YWta22GKLZ8BF4EtCiJ/g/RlIv+nlDenZEELk7QcLTlaWa3sl92eRoVE8WDQses+qS3EDH8SWPNri64Umzfs3odmTgYbG4QOs2vAosH2n0qyCS2uPkLK5ihyCh92BwgfJ5bLgcNVjtIIouFRKXIi0NmCFIOIIQXLzsOH6XsXtk4ZRbiB6fEwk1Gs7JVmucc6z6BwROG4ss1XPuDQYLVl1gS+v5nz31el6Y9RzZ95waU2gNJ3ne16fcDDJuX204qdvzFj1gVGmGeSKgGBSZkwrQ90HMhVTYU2mubZTIgTkWqW4ih3J7iDj3qJl0XqqXDEtTbpNJrk2rRAR3j1cPbZNbUMSaZXIHikEvXNYHzBKIoXA+YBW8lHYdtd7lJJcnpZE4L3jFbeOG4wSXJ6WaCk+FKp91hb3quKpCSQhxEXgPwCuxBh/gxDiO4B/NMb4nwDEGP+1FzTGrxvWB750d8ZP35zhvKdzgX57Jt/i60QDKH9K4ggSyeNIJIu06YfLLql94gcYyw/KmHPWtZsikU+BU/KoWH/tSaRUJFnIPq7RrVrLWmOeCCMtBZnSdNZS5poiN+zkGrSm0oLXdgfcX3ZMBhmzpeW47Zk16XlKmTKQgktElESDgLp37FSSMsuZlAYpBEMjadeBRyJEIpApSS6TQkfGyKjQ7A4Lci1h0TBrBJ5AnitEAOegzBWXJmUiZUrwLmC04mRlETSMKsNJbZFCUOQZIHi4sowKRaYVuRIoATtlRiRytGzJtGavMjzoHXcXLa/vDXnzYEgfPO89WHHSpscTHv7/7P15sKVpnteHfZ7t3c5+l9wra+mump7uZgaGGYMBS6EQyBIOyWGsQA4r7FAEGOQlsEx4QsZgWWHCDhGSHZYVBoSF5SBkC8kIZOTBgNCAAjSsM0wPM909XV1VXZX7Xc/6bs/mP55zK29lbZndVdNVlecTkZV1M99zznPz3nve9/0+39/3+3Dd0c0bKiNYdJ5xljxks9LQB8nJquNnfukBk9IwyBWTQYYAqkJza1pxd96wN8wojGZSZrx5XDPLJQ+WLZvWIgTMG8uidWgBR0tHpSVumlojP2+hejueL3Yjazt27HhG/rc/7AX8oFgfuHte0/SBw1HJ6bpns2lSLqWRzJvd9vSOT4bLm8gZKffUpYkzcgGrNsU0ZBJKkzaXy0IwGmQcxMiq9gidhJD9UtETGZgMGyU+OIySvDgrkVIiZORsbXEhkGmJUYpMCcrssZhysk6lOblOG8bGSFrnORzkCCFobGpSsy5QKLFtWNYM8hytJGebHuc8d85bZkNDpRWPVh2b3tH0jreON+RacmNWcWOSs2g8h8OMWWWocsOy6YnCvOvcuT4tebhoaWwKtr46LjhadZRaMcg1xMjZpseHSKF1GjONEb/NKYL3hl5fZBQ5H3Ah8mDeYH3KK7oxLd87fvYBYdvvnNUokd4HMiU5XnXcnJaEGD4wVPvzzLM4kP4fwL8P/OHtx98B/iPgT3/Ca/rEcS7wK+8sOG8s686z2A0g7/iEEDzOJrpwDr2beRST6ygATXx/q9plFKnxzGRp3GyUpRNBv30+pUGFNF8sRGpDcxG8ff8ImwCq7SIs0Lm0ljyDVR3JtEUqGIhkb80zzXSYMTCazjpOVi2CyFnT09rHM9eNg87DKIfhwDDKNY11FFpio6KIgnnjKXTambg50pyue85WDQ5F21mikAwzhUSCkKw7R0QipKLUjk0fiTiEVIyrjBf2h1yfVgRAicjdVcPBMMf5kFoWHiwIwMGw4HCcUWSaG+OcL18bpXDq1iKFpMoFqz7ZbQsjQQq8i/QxUveWN44dgzyjEIKzTce0ynCNpQuBdWOZFBW5jngibR/ICkluNGebHqUExsh08agF12YlX7sxZtkEciOpjOZk0/P26YYiU2RKIhDcO68Zl4plExgVirLMGOYSoxU/cXvCq1fHn1tr644vNn/kz/4M/8EvPv3xO9fRjh07AGKM/+V2Q/qntn/092KMn6txthAiy9YzGxhO1ikDyfqAAGZVTvQN9zc/7FXu+CJw4XW4yCK1YTvlIKG1SThqHUQFudHMKtgfFvTeo4SkC57CwKTMePlggFKaum2prUeIjB+5mrPuHaVRyeXvQSBRMk0GCASvXU8NbHXXs+osTeeZDDKKzHC67nj7rOUnX5qxah1fvjLkZNVhlGS5towKQeMCvQ8cL1uMlpy7kOIgtOLeoqbrPQfDjNZGhIBrk5KDQYaPKWx6UmiEFKwaS4hwY/K47v7yOJiI0IeAC4GyMByOco5XHXXnUAiujg1SCpwNKJkKciBNWlyEXl9kFD2YN9w9b8i0SO1ql1xEHzZ+Zn3Yjrgp1PbPQ4x029a2L9pEwbMISAcxxv9YCPGHAGKMTgjxgxZL/ZrQec9Z3UIM+M/Find8XrgsCimS0LI1HrHabkJJPn5cMlw8l0sun4vGAxnSk3mfBCMDuG1IkpRQ6BRQLXjsRpKkEbMqA2M0WgU2bWDTJhdS9Ems6myaiw4xcrqymLFk0zmMEhwtHdNSI4TgfO3QWwFMkcbiDgcZg0KjG4gxMMgNg9zgQ8RGyJXk4bJj3Vm8UAy0oveCxjmkkmRaMi4zSi3SBZgWDIuM1rXM2+Ro0lrSW8fxMllBj1c93gXePms4X7dMBxn4Am0UubIMc8mydax6x715AwF8iGRKEmJkf5BTasXNScHRuiNoOGssmy7Zca/Phjw43xBjZN1biCn0e1RqoggQI5nSDPJIAKwN9M5TSE3bObwIvH605mjVc/e05esvjBkXGfcXLW3vWHWWYa6wPrBqewa5JDOKiRT4IJlVhmGuWXdppvpo1XFNinfnpnfs+CywG1nbsWPH94sQ4ncD/ybwN0iXLv+OEOKnY4x/7oe6sGdAyjT2f2e+5uffPqV321bataW1Kdpgx44flHKbo3XR4BdIM59jkwpuGgdLl5xI4ypdQzZ9uiFoe0eRC66g2fQO5zzjSvMTt/fY9B4p4c3jGuvgeOMQRBofqHLNoFQ4l1xIwzyNMXzvfM18Y9HGMCgUp5ueGCBTAwaZpOkcL8xKTuoehOClgyHHeQsS5mvLj98aExC8c1az6Rxfuz7mvHUQJVJEqlzhQmRSZeRGclb3tH3g2jjn+rRKbvwIN6YlVf5e6UJKQW/TGJr3gYfLFgkMCsPVUc60MlwbFZxsejZdCq7++s0J89q++/HlIOvCKG5MS6xP+asXTqULl5JR8gOdRJcb1g6GOQ8XDb2LxAjXp5/PoOyP4lkEpI0QYp+tICqE+M3A4lNZ1SdMjDAsc6pMcRI+ygeyY8f3z4V4BO+ddf848SgjnQz8tnfTCCgKAW2k0AIbIk1/EZIHbbcdR1OwV2mWrUMIQd3Fdx1PWqaso956vItIDbFNuxaQxumc91S5TPZXA1WuKYzGRkC0aCXR0pOl8WiymBxLQkpKowgBpErVnZs+UOaCTEteGBWcrDsORzlCgPeBzkaEiCgu8pAkm96xNywpbGBWGs5by17MoY5Mq9QId9/1zOueSZEx73uUVLR9T6E1zgaEFJytLZve83Bec7JqyZRMmUrLljJTlPsVb581bHrHywdDkILTjWNaGr58ZcjxqkMSUMDXb874Vb1GisCidqzqjtm4JLpIlUuUDPRtxNmeKtMokRxDnfW8dVoDgq/dNCgpuHfesFcG2t5ysuo523Q0nWN/mNP2Hik1betwQBSREOFkYyEEvndWczgs3zc3vWPHD5NnEY/+pZ+Ef/2f34lHO3bseA9/GPipC9eREOIQ+GvA50ZAUkLQOssbD9cEH1m3lhAEo1wRoqf5uGyBHTuegnw7vyYkTApB52Mq24lpGsCGdBOfinIi91cdORClo+kcA2HQUqG1oLaOVe25c1bT9JEfuz3lt7464FfuLDjftEwrQ5ZJ3jpaM98IIikkepALVCZou4DJNDdnBYtNx7oRDDLJKNc4E7m/aAkiMMozxgNN7wM/9sIU5wLfEWtcFBwOc0aF4TsPVzxc9vTWU/eOGANCCA5H6dq494HKaHINP/bCjB+5OiYKPjRw+nLwdZkZrgu4v2i5sh0ZuxCdqly/xzk0LgzWpzs0o+S7z3VxTKZTqLZU4j0upQ/jcsNaiJHDUcHhKGeQ6S/kNfyzCEh/EPiLwJeEEP8VcAj885/Kqj5hRrlhf5xztupwu+yjHR+DJAlAz/qtclkoknx0O9plekBHGGYw0NAGsDa5XIKIyVIq0vhajDAo0oml0JIyS5F6nfVgIjFL7WytBdtCqSJ9AJsMNRiVXEvWpZymdWOZDTKIgruLGh3h4XlNYz2VVgyM5jQ6BDAp0ggYeNgG9UUlU22lUlgX6GJEix4XIkIKoo8gFLmJ1H2aI1ZSIHUKeZKkUDrrAlWWwu6qTDHKNSexpyoUJytLYTzRCw4GhuA9BMWiaXFBUOYKKeHu6YbWpdlmHyOLxqIzw3cerZlWmquDAUZEzjaWH70+ZJhrikwTA1yf5IwGhkeLnhuTgiAi0NL0joNBxnzTsV/mlEYxMA0hCpQUiFXPsu4IRGSEvWFG0zpOdUdh4K11T23TiSdXktMu0PQ1my6w7lq0EJSFRmvJg/MaL9JJ9s2Haw6qgpcPh1+4uekdnz/+jf/vX+FP/q2n33zZuY527NjxIcgnRtZOedxM/rnA+sCqtkyqDBdg1Vk2LuCCR+9O1Ts+IVq33Zj2qWRnkGliTIHZUkOWLsXJJJhcU7cWjEo39hE2nSdX6bq5s4JJZRBColTgG++c86M3xgwKxbVpgYwSIQX7w5JV3ZPlkpvTioNBRoZgWClKnyIYZoOc001H65NT3khFbuB8bakbz8lasWh6vney4YXZgFFpaHqPEOm6eX+Y8e0HK8pcc3u/Ymg0J6ueF2cl+6OCG9MCI1K+EUIQxWOB54N4Mvh6WBhm1hNCREnxXjd/SMcToN+GZ4eY8pCmlWFe2/d93Ln3u5Q+jC9Kw9rT8CwC0hnwjwM/QnLT/Srw6z+FNX3iSCnYKwxIgZIRH3YNbM8zHzdSpkjiyOaSgnRRv5rx/vDrCy4LRk8+f7593voDHicu1uTAG8k4Vxidwqlbm1xFPsAwT86hzkGIMCkNmVZIqbD09H1AKUGRSzye2sLGp7wkE9NzhJhsr2xfLwCbtifPNfePGrTW6fUiPFq17FUZ1yY5RQ4GSesCk7JkUihypTlvHFWmaX2g7izDwhBFxPrItYGh94blxoKUHFQGlGRWaVobUQJu7BfMKs0bRzVXZgVN5xlXhroPHIwKvA9cGRgEAhsCx5seGyIEC0JwtGqQUvLSfsVkkOHqHoWg6T3TKqNSgiqXtE4wKiJlWVIWgRf2KpaNpTCKUakYlhmLjWXVOqpMMSk1+4OMw0EGQlJ3PrmpoufesuNwVCQxKRPUTlEIEEJgReS8dbgQUgif9xSZ4WCY03tPoQVHq55pldGFQHSBs1XH7b0KGwJSSs43FilqrD/iyjj/ws1N7/h8sRtZ27FjxyfIXxZC/BXgP9x+/C8Af+mHuJ5nxscIQlAYzbj0LOqe43W66rvsRN+x4wfhcpPfoolUhSNsC3b2yrTB6yOcNx3epUDU8UixNyzQWnKybmkD5A4mVbEVogQ3pgXfvr/m2w+WKAECweE453QtuDaJHI4zvnQwpPWBaWGYVhk39ip+8XtzHm5a2s4xLgw3ZhUhpmvdRZ2uuXvneW1WsW4dTet5uG4ZaUUQguvOc1b3lJni5cMBt2Yl0yonxpS5+htfmHG6TrmiF61q1sePvQa+HHytlaS3nvPavq9l7coo52jVvZt9ZH1gmGu0UvTW88v3Fry4X1FqjfMhtSxOy490P30QX4SGtafhWQSk/wT452KMvwIghPjHgP8r8Os+jYV9krTOE0Pk1rTk4aLhZBN3AtJzzMd97QXbETEeC0cXAdm5hoGE848JYr8sJo22rWlaQb8NvctksqD2MYlLHlAKMiUQSnJSd8j4OMuobqHtod2uK1NQW0+I8E/86BVcdPzC9+YoAo/WDrcVh3LYhuIl11LvUpZRodOaFl1P06eqy3njmGSRqsxxwTMpDPsDQ5EZHi0aNiGSZ5IQJA/PG47XlioXxCCRSpAVGS/vldQuMikFi8ZTZoa6DXzl+ojOOmoXMVIxymGQG25MSzaFo/VQKMEsN8zrjhB7hqXkZOloQ2C+6jicFKxqi9YaKQJfulLR2Mgo19SdI1eagYlUmeTRokFERd1Z1lZgpOSl/ZLgImd1y0sHA/aHOZ13DIucH70+5s3jNZvOMSkMe5XB2sB0aPjm/RXzxvKtBymLqfeBW1NF03uklLy8P2BRWzLtaX2g7QPLzvOV6zknG4dRsGgsbR+IUVDmklGhcEGTK82i7ZgNcr57tGJvUDAqUmPb8brH2t071Y4fHs8iHv1TL8Of+v078WjHjh3vRwjxZeBqjPGnhRC/C/htpEuTvw38P3+oi3tGMplG1weZ5Ffu1nTbAG3Bh28w7tjxrCigUuleIUYolaQwknXriIDSgk0bKTLFODOIUdo8Pa9brg4MIma4EMiNwAXPg2XLV64PaftAHx17umSUpxa0u2cNSsOsysiMZFgaqhDZH2ZcGRd0LnJjr2N/nKIpxqUhRvjZbx1vs1RhNgCEIMs0QoIxCu8iIheMM8Xpuic3KevoYFQwrx1Flm5Gbk0rxmUqwnm4aKk7RxRwbVS86xj6MAHn8uhY59w28zQj24aRaSVpe8v9eUOZKbRStL3j3rJjfMUAIKT4wGa2y+6ny+NtX2Rn0dPyLALSvwz8p0KIfxb4CeD/APzOT2VVnzBKCEym2R8VnG06/FMPF+14HulJTqPLAxs52xA7v201+wguO5zy7e9lAdcnJYtNS91GsgLoQDvQJj3ARmisp4BkP+1TNpLzKaPIx7STcGHk7HpHpg2NDZzUHqUMvXPUbYeP6TjHVpy6tKaLMTYXoO/B5MnmqQnYILGuJ0QBAlZ9INOCIjME6+n6iCk8UUgEgWUrGBea3kXmm447C821cc55bZEC5o1DEjive4ZGM81TPedZ3XIwzBlmGcvaUxjJG0drykwTQ+DKuEyNDVKwsBGUJETB/jBHShhXBftVQZZJjhYtPkSujjNuzUruL2vmGwvCMcgVVyclIUS+/XCJkZLOeX7uuycYpbgxKTgYFSzqNGo2LJODajowPFp1aeZZJiFvkKcdESUVPjj2BiVCRH706pg3T9Y8WLRsrOPaWFFoxW/68gF/981zMi24f94xKhSZhkNpmNeBG9OKh8ueKs/ZGxiuzkoIcDjKGBUmOcyM2o2w7fg154/9zF/lT/zNp99H/6U/8tsZD/OPP3DHjh3PK/9n4H8NEGP888CfBxBC/OT27/7ZH9bCnhWhBK9dHfK94yVKCKaFRnhHvVOPdnyCeFJ0hd429FgXMQZyrZBC0LvI3kBzczrivLZp3Mp6GhsZ5oab+0PWXWouM0rS9Z63Tjd4F9mvcq7PKoxKjcJlpult4M58gxaS802PkIJxkeF85GTZcnNvgBSCTAveOFqzqvuUnaQkhMiytlSFpu3TyNco10xKzaxKgdLDiWGQa1rrGWWKQkvGeXrt69PUrFZIxZVRzv15Q+c8v3h3zv4go8w01ybFh5bKPNnG9s55Tds7MpNyjOL2ElpvxaBs+zyd89v7jrj9N/VImYKwL2cetda/Z9zto9byvPDUAlKM8e8LIf4A8FdJzrrfEWM8/tRW9gmSG8Wrh0P+zhuaTed37qPnHEFqMxOkRoMP4snrgAgUWWpDaz9Gf7z4/pKkyvvOwzjXxCC5OhlwonuCC3SdS21eQKGgNNtKzj4lYYsAQaasoosRNCGSayl20EnIdMc7pw02eCSCa0PDutF03r0bym1D+nxDSCck6wGfspR6C0JIbB+2lleHqZNYkmdJpfdVQIhIJNI6y540HDctUiqUc0wGmrNVh5KKznkeLXpCjNvHJ9fN0arnnquT68oHisywbBzj0lJbx4PzJmUjkZoThrlCTQraPrmWro4yOpeyhFa15eakZFIZjlcd0zLjxqzAOli0HSfznkFmqK0lBLh/VvPifsnVScWy7tj0kbpz/IaXhpytHWebjlVnWbeOaWX4yvURfQi8fDDgbN3R9J7jdcMgS9ZYow3vnDXU2zG8H7k+YlwZfAgIVdL1nlGlWbee27OKuresC4eSgoNxwcBI/v5b5ygUe5Xhyihn0VoKIXhU95xmPTYEvnZ9yiDTuxG2Hb+m7EbWduzY8SnwUozxl578wxjjPxBCvPRDWM/3jRKCKtfMBjm5UVSZ4v65e8/I0Y4dnwSbCMancp0+RHSEKtMYLTkY5ZRakknBunf4kCIlOus5X7cUWnBjUnL7YEQk8vbJGrEdgZs3jnLRcDAqMUbx8sEAIeHlqxW3phX3Fw3eRwaFobWOs7rnx2cTVn0ghpAalwMcDpPTR4pI7yKzYcam84wKQ64lL+6PEERWXbpx2nSO65OC3gdujAte3B+kVrOL2vtwkaskOFk7ciWorWdYJGfSR42UXYyOtdZjfeDeMt3hXRnlvLBXcbTq3h1zCyFyZZQTY1qT9YFJpbl73r77mBcPBu+KSRch3Vo9Hol73gtuPlZAEkL8Z7w3T7gita/9aSEEMcZ/7tNa3CdJFDA0Ar9Tj557LgKyBcmZ8zR+NClSg1nTP93xF2Npyy6JUUXrGFcFN2YFTe847fpk+9xag+zW1bTxSeAxEpRJjifFdpRNp/yid9cc4XQTMGdLei+ICNatYNmkGk+j0tjbxfGFAd8nYasBtE2CWPSOjYMslwyLNEustcKGQOsjy9YyLgynq5Z163nHr3Fe4nzKBVrXFoGiLBSzMifTktNNjyIJLC7Corb44BAI3jxZM61yBrlkf5RztugIwKTKIUY8KVz72iTnaFFjRE/j0g/uvHG4GFj0lmGf4SNMh4aXDofcGJX8F996QBc9VamQmaBUigCUmUIA0yrncJrmszd9CtwelUmwujoqaJzneN3T2cCtWcG9eU253SlxHqSQ1J0j04LSSK5NC/7OG2dp10IIbkwK9oYZo9zgY2R/WLBHxqp1bDqLdeC15NZ+xcEo4+5pzXePG7SMCARXJzl5JimkRCi4Ov7iVX/u+OzyLOLRP3YV/sz/Yice7dix46koPuLvyl+zVXwCSCkYGMUbj9YsWsvpuvvQzcgdO35QJCAc1AGM9tycDLk6ylh1jkJL5p3j0bzBuoAxikGu0UrigGXrONukLfHWBqbDnFfGBZvGc7Rq6V3gtWtjrk0Kjlc94yK1MVdZGu26Pi6IApyLWCKZhpNlykDKtEQJSZFJHi06RiW8emXE129M0FqyaCwxbnOIBxmndc+ytrx1umZvkHNjUr7v+tbHSGMdi8bycNkyyDXl1umzanvePPFoJT/UBXQh9gxzzfiKoXOeGJND6WLMre0tUcALexWFUUlsmjcMc83hsHj3MdnWrfRkSPfFeNvzPh3wNA6kf+tTX8WnTGc93zvdMMgN44HBRctql3L3XPOsX34Xwbmnb2azpB8uSRqHWzVw93SNFhaPoNm2oFn/WJBSfco2kiKdKAjpsVWWhKt+e6zZBjMpoAtwsnYIAUZL5j6y6dI4nJbJ2dRuc4/aHjKdWtoCyRmlgeM6fV5XFexXGUoncaizEqk8IQTunNUsW0+mBc6BUh4fYWAUdW8pTEYIEingnfOO4C1S5NSd46TuSG+7gjzT+BDpvWdfGRaN5fq0wBhFaRRvnqyoO0+hJYejjMIociXZOIdEEGLASIW1gdYGBkZRasN8Y6kyhRRQGM0wV6y7yLLtkAhuTgeUuSbEdEKdVIZhJilUzmuHQ4QUaCX43smGUiusj9ybN9w9r9kfZPT7A751f0WmBJNC8trVMWbb6LBuLQfDAiUF6z6wN5LkWRKkhoVBxFTz+3PfPUGrwMk6cmVUcLaylFpzbegxWnHnrObKJOfGrOT2XkVA8hyfm3b8GvJ/+qt/nf/Lz35QxP8HsxtZ27FjxzPy94UQ/6MY4//t8h8KIX4P8PM/pDV9XzgX+N5JzddfmHK87nijffbW3h07ngYDGA2TUhGJ3JwN2BsaxmWG9bDuHUZJxmVG01kaF4khkmWKidH0PnC8aJgNDDGAiHA4zKm7mmGhuDrMuTEtcDHl+1ypDGbr0BECtN66dcYFi43Fx8jhMOeVakCuJN9+tOL1Bys88JVrE4wSvHG04eZ+xc1phdGS6COvH6+Sm14kl1DvPHfOa3Kj3iMGiUjKSlKCKtNYF1i1lkjg0aLn5rTgxqxCS/GBLqAnxZ4y02y6JPYU5vF4HJDa2Sbp2h0ej7ddfoxEvCekW0pBb9Nd2/M+HfCxAlKM8b+8+H8hxFXgp7Yf/r0nqjg/s/gYIQqGuaK3gWYnHu14RiSwdI+dSx90sSAu/fIk0ebC8DbKINOC5cZx0nj6bSD2ZSJpzCzEx21vjpS5lOkkLgm7PYb0+EgSlzKdGgUwUJXpB7tPVh4GCtbdVjRyyZmkt6ngPVCINGO97gJ96BhmCh+g1BojNC5IattTmaRuBSJFJhkgMFIhhOflwwEhRnyEg2F63J3TNSfrDq0FVZ5BiFgfUFJiXUBIyWLT8fUXZiAb3j6p6fqAkoIQAt9+tOHmJOfqpKCzjvvL9GYvEHQ+8ObRiq+9MCMzgm/eX/GNO3O6vmdaKNa9x/sUnv3a1RGvXh/yS/dWuN5x1lgKYygzzdeuj7gyLuhD5Bt3znn90ZrCCMZlxo1pSa7SGF6uBbdmOWWmyZVEa0XTWR4ue9i2zmktOF93XBvnDCZpLvzRsoUQ+dWHK0KIzMYZzgeOVh1VpskzySgYjtctXfA8XLVsOs+itowKw6pNzXY7dnxa7EbWduzY8WvAvwL8BSHEv8hjwegnSZc7/52Pe7AQ4p8G/m3S3tm/F2P8N574+38R+Fe3H66B/3GM8RufzNLfSx8CrXPYGIjSvhuLALsGth2fHBfyRKZgnBuUltyaDbgyKdJ1ZqGJPmK2I23/6M4CoiUAlZFEJVE+UOaaq9OS2TDn4XnNdx6uyLTm+rSit4E3TzbU1vPV6xNcSFmss0GWslg7RwgRoyQvHQ4QUhBDpLYeJQW390rqzrE3zHm46NgbGKT0XHGp8ezKKOf+ouFo1bFsLHuVZlRkvHWy4XjZ8qWrI4B3xaAoYH+QUVtPlSnONp5N5xiXmivjdA1+vOq4OS0JMbzPBfRkI5vz4d0so4vxuBSkLd8dRbs1LT/0MZAcVFdGOW8drznZ9EghuDLOUxyHfH5zkJ46A0kI8buBfxP4G6Tv639HCPHTMcY/9zGP+6G/6Rc6jaD88v0Fdef5mAzkHZ8zJI/H0i4Q2z//qHEzDU/9vaB43Mb2Yc8Zt8fJS8derMX3sImRuvf0Ps01fxB9fPx5qO0acwVSpRYGo2HRPz5Gk0Qg67YecJXe7IKUZDKgFAgjKEzkdJ3Gw/DJ1eRCssU2MYV5Kw2uhWA9ZS6YDg2bxiNiYJClcOyTteWkaVn3nr2RQcRUD3F3UZMrTW87ykKjEWiT8dK+YjTIOVn1KBk5WvRIAUpINl3Pw4Xnazen5Fpyum5xIVLmkt5FjIkMywyjJZvGsWgcjfUcDApe2St462hN01nunHompaF1kt4Flr1FRzgYZ/RWcjDMAcUoV9REfv2VAd6nUPNf/8KM14823JvXzJuOW5OcPkY6GzheNZzXPXXvEUQKnRxMSkl++f6cgKBvLddmFUUm8T6dvJSAYZ7ENusDDxcN9xcN57XlnUXD9XFJoQT7+wV3j2serTqOVi2ZFJzWDjURnNaC166OeeNow+G2kvWLzGfhPPE88izi0SsGfvaP7sSjHTt2PDsxxkfAbxFC/BPA17d//DMxxp/9uMcKIRSp9fl3AHdJbqa/GGP85qXD3gL+8RjjuRDinwH+FPCbPtFPYotGcLLueed4zTffWbHY9fLs+BS4yGqVEvZGOa9eHdHZgAiRR/OG2TDjbGU5X7UoIZhUitJIhIDGOoZeM61SqzAhiUoXo2eDQnLntObqKON07Wn7wNnG8ju/fp0yT9mbrfXcXzTEEDlZ91S5plASVHI+4SOr1jPINV3vyZSktYFxqVm0jkmEd84cpVYoCcerjmXrKHXHyaZHCMjOaq5Py+0GdGo4KzPNsNBIIZhVml++5yi15rzpybVECEG3jY0QMW2ei+QTQYn3NrJduJvk9nr8g0bRouBDHwMpQPvRsk3RHFJwc1qSafnc5yA9SwvbHwZ+6sJ1JIQ4BP4a8KEC0mfpTT8QWG6rD3d8cZA8bhu7LPJEPj6r6LJ4pEhv1h8WgqgVRJ92lz7MgXTxnJL3Th5diFs2PF7v5aa2C5782JMqPKMAa9MY3TCDsU5uqIvXuXguS3IalUVknAm0NKzrHiUEN2dD9keeu2c1vU87GoWCk+3zKJE+P4DcQK5SEN+wMDTe8fKsRJLq6OP2NdvOoyXEKNAigPEcLRrcPDIpNOMqpwmRK1PNzamm0IKB6YhCcm2Us+ocUgp+7vVjci3JteJLVyoWreWs7rg9rJgNDA/mHhsjX7kx5s3jGhcj904bplXGuMowAo7WHUZJbu5VLBtLZ2GSK3oNw1IhRKRuPUFItFD00fP2ac2wWHBjnLNoFN991LNsHW1/8VWM9M6DiBilUUogZDq53Z5VVLkGEVnWnrZ3VJniazcm/JYvHTCqMlrrePNonaywAYwU9IAiIJXmwbxj0VhONx2b1tFrGJUZldHMyozZIMOGQB8Cmi+ugPRZOk88LzzryNrP/sHfwitXZp/iinbs2PE8EGP868Bff8aH/deA78YY3wQQQvxZ4L8NvHuOiDH+3KXj/w5w6wdc6ofSOM+8afmb3zlmvkvO3vEpMACETsU6VaYwUhAibKxj0fb03nPLD7m9N+DBvGbVWmZVzt4gIwR4/WhFawPWB94+q4kRRoXmR6+PKTKNloJvtyt6nzZlJwPDfNNzd17zlWsTII14lUYhc828tTyYN7y4P8D5wOk6jZMNC0NuFN+6v0ArSd8FXtrflsc0KWuoNIrOBYxKo2vWAVGQKUmmJQ/mDVfHxbvB2O+KOcFzvkmh2ynXKY2tTauMGGE2MNydNzTWcbru39PWdtHIdjls+6PcScbID3zMRaaSEFBkikxJzuqeG9OS4N7vgHqeeBYBST4xsnYKH3tX85l402+dZ9lYMi13DWxfMLZRQcDj0bELDO+3E8snjhc8dhVpPlwc6j3kEmL44Oa2i9e67D7Kts9nFASRWtW6AHsV2DY5gC6v//JzXTyHEEncEiIFXl+Mr3Hpc9Wk3KRRCXWfmtWWwTEoDWWZobaf1bBQTCtJ3QUKo8mNZtG0aUwuQi6gzEFIiRARJSVFrqCDGCLz1iOASaWQUrDpI1IKOhtYdxbtI1JD18FZ4xBKcWuv4rx23BgXfP2FCYWWfPP+nCrLGVjPrNJE0s7EVEvWnWfVOo7mPVcHBTHCpMy4Oim4Oi5w4ZjTVY+UghemAxCR3qWT2f4wZ9lYhBBcm5YURtL1ik3rOJY9b5/VTErNamAwSFad5WTdcbrp+MW3zzhd9xilEDJy72yFEDCrSm7vlQwKw/mmo8oU00pzOC5YNZbWBrQMaAm39ip+x9eu43xq0ut8IJOC42XPjVHOd08sRsC8sfzmG1NeP1rT+IgPabxx3Xl8cMTQUWSSTevYq3Iy+cUVj7Z8Js4Tzwu7kbUdO3Z8zrgJ3Ln08V0+egPh9wD/vw/7SyHE7wN+H8Dt27efaSEhRB7OG85WjroPZOzG1nZ88igD2sCs0MSo6KzjfN2ysanYxnvPyfKcR4uOq9Oclw9G/OaJAal4/e6c9aTk+qzkZNnxYNlglOZo1bJsPdcmOYWRvH2yJkQ4GPX4GBgVBhG3OUIhbaDmxmwdOSXvnNYsmhTIPS01SiXppNQqNRH7yMYH7p3XuAA/emPI904aFpuO88bxysGQ87onbsNARqXBhRQBcTDK3xVtCqO4vVfROo+IKYfpeNUhhGBaZfy6WxPGeRKPlIDNNjf1clvb7b0Ko9577fweceoDnEYXLW6XuchUKrdZTUDKcbX+PWNuzyPPIiD9ZSHEXwH+w+3H/wIf8Qa95RN70/9B3vDVVnE8XfW0u3f6LyxPjqNduIUKmYSXjtSOFklOo4wUNO1DOq4ysLaPBaLLYpMjCUB6+4dPHnMhHslLx0MSecQ2/LqQ6fFu+7oiJuFGAkMFK5/WpgUMc1j1STgSOolKXUgtbC48Hr9TQJVDrgXWJ+mr3za34R1VkROD4O75Bu8i4yrnn/zqjFVjeeukZjqQWB/wEVoLXQ9apiwjoxXXxhWCQOs8UliIHmNK+t5Rt31qWBASoSJd73AxoiLsjTIGRuJd4KWDAb/9a9cojWHdpcY2KSPTSjMpc3prKYxkVTvKXGJDyhxqrWO5/YG9WuSEGBgXhuAjEcHhJGNvkLOse87rPoXtOUcfAuMySwKSDnz74ZJXDgJCCDad461Ha/aHOcNMkWnB8aIjRIFWkto66t5hZBKKci3YWE9EkGvBjWkJQjKvLWfrlhhhb2CYDjJuzSo6G7g6Kni4bJFSsOodnfVEKYgi/RpmBklgUfecblqUjKysZ9N7rPOMS8XJsuWbD5f8jq9d+8KPr/EZOU88DzyLePSagr/6v9+JRzt27Pih80F3aR9oBN+OyP0e4Ld92JPFGP8UycXKT/7kTz7TYIKPkXRFEOi9Y/MsD96x4ymoZNowNvKxqLFsA+ftihAE0yonCLAxcLRqyDQczxu+d64YGM3pquOlwwHWBhZNi3WOQabZG5ecbnpCsBRa8cpBxena0faeO2cNP/liTmYU1gUeLVseLdMG69VRgdGS/YEhhIgLkdeP1uwPUsSEdwHnklPq5qwixMiqsbx91uJDZNkF6tZxVvf82AsTjpYtAvGum8lHGGTvlSOkFBRaoZREb8fGLtrRpmV2KSxbEmKkyjR1n0Qh+wHZSBdciFNPOo0+jAvXUoiRw1HOg3mD9eke6cb0+W5JfmoBKcb400KI/y7wW0lv5n8qxvgXPuZhn9ib/g/yhm+UZDbI8d7t8o+eMyJbR49I+UINW3GFlB3Uh3TMUILUoH0SaiAJQ5dFJE9yIF3+5nvSPSR575ib2/4ygFDJxVRoRW99EpdIwhWA8WlNCPAC9oeCdRfBg9Qpx2jRpeeqsm3YtgQhwbqIkgItIl5A48E2kVXfsj/KKIyhwVMYyffOWq6NcrSSXJ0UPFx22N4jJVypICsMWgiUEgwLyd6goLdJZfuld85YtI7zTUtuFEZJcg2rzmEd5EYh8vRJSCm5Pi34+q0JzoPXkTLT/PgLE37+zhznPMfLjquTklwKliK1lRVa8WOvHRIErBuLC5GuDzycNyAF1ycFLx1ULGq3tZYKfturV1h3lrunKQwwhIDWmnXr0FKkUO0YmFU540IxrQzrztG5wNmmQ0tBYRSlVlRG4b2nyAxCQK4lhZFcHw+4OilYdD3zOoUIaiEocs24yNi0nrdPN7TWM60yQHFjWvLW0Zq6d2ixdaJJwaIN+BAQwMZGXAzp65krtJSUmWGUy/dVlH5B+UycJ77I/Im/+Xf4Yz9z+tTH/62f/m9wa3/8Ka5ox44dO56au8ALlz6+Bdx/8iAhxI8B/x7wz8QYn/4N7xm4uKEsc8VskLNqu919xY5PlD483mw+WVmujjWjUrO2MN84Ku9Yt55lazFSsD/Mk/O+KlAy8GgZeLDoKI3keGWpe4+NHZvebwO2MxonuLVfMC4jx+uO/YFmb1RwMEzh15mWXJ3kfPPekjtnqcUt+Mig1JyvUxj2unfMVEYguY32Bnly6UT4r944QcSYJhqIKC0YZIoY4GBQgIDOpRGyDxNiLjuGQkzHXr84NoAUKdBbCkHbu1TAE+PHOoM+yGn0Ucc+XkPk6rjgYJQzyPRzLR7BszmQiDH+J0KI//zicUKIvRjj2Uc85DPxph8FjItkt9vx/LHejn1d3IpfjH5dvrtsAmi7DZa+9HcXIlLBthHt0mMU789Z6re/Z088fyS5mzTgvSeIJAAV22wlL9LrVIDWUGmJcwGzbXK/cBcpYFCAlgLrIjbCQanoLaw6j/WgFHiXdjC6AL0LjPJUJ6+VxPvA2bojhNRUdjjQbDJF3Vn6KCmlYn9UMMw1zkVa69m0nnVvWXeBug9EIbEhjbllAsosQ+EIRGZFxv4wY1oahJC0LvJw2fJTL+9vw6o9s1LzvZOeSQFGCVSRIaVkNsgYFIa2T01kfYzsD3LazmGMZK/KUEIw3+aZff3mmHZbW7rsLF+9NWFvXJArSWMDp6uOWZVzdZQzKXMeLmp8UCwaiwuBuvMcjAqKzNH0jgfzht4Hbk4Leg/r1pEJwddujbkxLjFKMbYGjWCQK5rO0XSeO65mr8oZlZrTdc90kNF0jnXrGBQZSgvmteVglPHK4Rglt/92WuJcpJeS4D0hgCcipaS2yUb8HPCZOE98UdmNrO3YseNzzt8HXhVCvAzcA/57wH//8gFCiNvAnwf+BzHG73xaC5FScH1SMioM40ztxKMdnzgOKC9agCQs2x5jBKUWzGPkfN3hgqAykskg53TRpBgOmYQUFyLndcONcRKWhISm7bE2cDDO0QoeLGq890wrzUFVsD/MeXGvojCKEHukkCwbx4v7FXXv6bxj03qujAsWwmGDYL/KuTEtWDQ9J6uepg/kRjHMVMonOmswCspMU+ZbJ9GkpMyT9PA0LqAPcwxdFnYGuXo3A8kH3jOW9jSEED9yLc/qWnpeeJYWtt8P/O9IJo7A4/vsVz7iYZ+JN31vA9+4s0DG5+JmbMcTXHYQfdiPvQfm2yuBJ7OTIrzHpnzhSrosHuVsxSGSiKRlCs2+wG1fuwdkymWmyCDTsG7SGJ3RyY3UWNj0gYGBQika5zEouuAZ55ApyboLWJ/aGUKIxACVTs/Tu7TmTKV1Nq2j6wN5prh7vqHKdBImItgY8SFgBNgg2Btobk4rWus4W1tePhhsp5XTnPK4NDTOc3Na8mjZg3BsrGBcafbKilxB55N9dG09k4Gg7j2LumGYSx4sespMIYUiN4rz1nPoHZMyZ1hocqPwPtBaj9ESZx3TyvDddUemFa2PVLnkeNHywv6AaZXTu8Dd85p75w0hFBwOc3KtWPeOGAYoJQkRvnu0ZlJmvHptyKK2KJHcTK0NdDbw0vURpdEEIv0226g0immZ8e17K+a1I5OSG3sFea7JOsd3zlus8wzLjIHRhBhpreO7R0tOVj2d83TOMasMm2HO/jCj94Hbk5Ibk4JKC+6HlqYLaAWlSm1vQkZGuXrfDPcXlM/EeeKLyLOIR/vAz+/Eox07dnzGiDE6IcT/DPgrpH20/3uM8VeEEP/y9u//JPCvkd7G/rhI7gMXY/zJT2M9autwEFIyULDZtbDt+ITpHQxU2tSuO0+hHYNpSWU8rfMUmaDMFJmUPFq1lFrw9lm6xg0ucjDQ2AC390r6CPN1nyIaOsd+kXF1UrJqLPfmDqEVLxeD1DK8ddh1zqcRMSlRSlBIzVoGnA9kRlK3lipTNL3j9UcbxlXaPB0ViqZT3BiXZFLSuEDbO+ZNYFZEHixbbm2FqmdxAX3cONqrh49b2J5F4Gmtf9dddJGJ9EHO/2dxLT0vPIsD6X8JfC3GePK0D/isvOlvrONo09IF8ZENWju+mFz+mj/N1/7JHaWLjYALLlrIAukHKJBCrKMEHZKoIy65np50PNm4bYyLoNDkmUNEqIwgSIFyqZISKfAEghMIA20PZZ6qKHOdmuFyLQlRY7THekGRp1cRMmUp7Q1z2rZn7QK+SyNT684Ro0AScTGtw21XOG8c4rzh2rhgVqWRrvNNz2SUs+kDVQFjlwSeQabwQqKEp3cxiUcx4nzAKMV+ZRDAG0drJJG//d2Wuo+Mq4xXDocIJN47jpYW7wUuRP6bX7/Ko2XHrIqcrFsgcrTsmG8DrI0yuBBYNo6jRcPffsMxrTKWtWWSZ+RK0bnIuu14+XDA7WnJ60cbEIErw4wQIuvWse4co9xgfSTTksNxzksHI756Y8rpuuPN05rFpsNomVrrhKDMJN5Fjpcd841FScn+KCOXkiglVa54/dGaTEuUFDxatFjvaaxnb5AxyDVVphhXOXtVxms3RvzsrzQYJdE65/rUk+eGF2YFeWZ47drkecg/+sycJ75I/Om/+wv80b/w4KmP/6v/ym/mtWv7n+KKduzYseP7J8b4l4C/9MSf/clL//97gd/7aa8jhMg7ZxtsgNaFZxvj2PG5QJMuRC7yTX+Q+8bv97EdYGK6zlcSNn3Pozm8tF9hY6BuPdNS00dBprb+/97RaU1lFDemA9ado/eK0iiujXJOFi1Zprg+qZAKTtYd48IwzDWDQvNo2fEj1yLXJgUP5g2dDXgf2BtkPFq1jHKVNp2d496iRWvJ2ycbIpFB0MitgHN1lHNlUrBoHVonMerVqwOqzJAb+W7I9Sfh5PlBhJ2LhjWjBFopnA+f6Nq+6DzLe98bwNP3/m75LLzpC5FakVrnyfjgFq0dX1ye9c37yeOf3FyKl445rNIOwbxNo2iHQ3AeNn0Sk3INtX2vKHXhXppoEDIwNoq295SFobURk6WWtExE1q0nyxSTyjAtDeuuQ0nJuo0gkljTuZ4QYFhKrg8qfIjUvceFwLVJzokQSOtSM5xSrFpL3YYU0A20Pv0+KATDTLPpe9541OCl4u5ZTWE0X7k54fZBxbcfrNAyQghEKRAh0HmBEQ4lM24fVNw7a9BC8Et3ltzcS4F6h8OMtve4CMfHq9RqkEsaC84HkPDCXsXxokNKwXSg+dbDJfNNT+8CIXrqzvPqIOfhsqUykrN1z1tHa4pco6Tk+rRECCBGWuchRG4dDhFCcOdsgyOJewejklmZ8fZZw8m65fqk4sooZ95YZlWGUpJMSqIkjc+5kOpGpeSoa6lIdaKNTXPo2VDSW0/Te1ZNj9aSzkYCgXnjWNSOQd5zfZaxaQMhBDzgXeT6pEBIwahouHvWIEPEIzgYGF46eH+LxBeVz8J54ovCbmRtx44dOz4drA88WqW7iFmpOclIcxk7vjBcZJfC42Kcp7mPuNhYVpc+/kF6m/qQ2pG1UoxLjZaCsF2Ri4HjjaM0klllUFIwLTSdCwwKzbDQBKAIKQJjUBh8lAxziYuBw6LgdN2TaYWLgnntOFr1/ORLM2aDnBf3BwwLzTfuzLlzvqCzaeN5Whnuzmte2a8YFoZl09O5iJKQKc3JxnJ1O+L5E7dnvH22wXuoMsPBMCfTik3nsD4go/ihjoQ9DuJOXzGtJJ1zHxrAveO9PIuA9IeAnxNC/F0uaTAxxj/wia/qE6Y0mpf3B/zd10927qMd3xfF9veLjKPANhhbKKpc0jpLZpJ4JIRgYCJGK3zwZAqW7bvjzGQXttQe9gbbFjMZWdQ9nQPrYDZTaCNZNA1d79FaUGiNj4pcQCYDGxupt9sjwzy9bgD2h5pDaTiad1RGcGWcs6wlffB4Fwgx4MLjk5snnaRKLXi06rAWihxuTTP6CH3nuHdeQ4xcm5QcDA3fOVojZKDICk5XLSfrht5vWPcWIxSZlkgRmdc9mRacbwR7o4zb+wO+9WDF6brj9qzip146oCoUGmhs4JcfLvjylRHndY8Rgr1hxijXPFo2WOcRMXL3rAYi8zrw8n5JlSlmpeHBvOb2tODts4bOeX5uc4qNkVmVc2NacWNa8t2TDZmULKxjWKhUO9o5yiznZNVxvGipCk1mJE3reeAbRmXGKJOc1ZZhrvERFo2jyiRfvz7h/nzDfNOhZOTapOLRquVo2aQwQZHcaW8frblzKrk2SSN2I6OQAial4WjV07qUT1UUOePCYJTCPx/5Rzs+QZ5FPCqBb+3Eox07dux4JgQwGRikUoQnm1R2fKF4mi+v5rHTSJLuDbSG+mMCsi6X9HzoMTJlGGU69TznWqCkhhjZG2SMy5zzTcejVc/SepaNpw2Rae34Xb/xBvfnLSfLniBhv8p4Ya/ku482nG56Ci2xNrA3NORaMSg0J6uOSZkBsGodg1wxKSqOVh0uBHofuDYuUFpjtKDuA9Mqw/lIH5IwtDdIj69yzauHI4yU5EYmscoHrAvcnzfp3+tDxsYu5xLB0+UlPcnHZRtdjOs5H9BK4nz42ADuHY95FgHp3wV+FvhHPN3P1GeG3Ci+emOcajd/2IvZ8X3xSY0ePplv9LS0JBEpkAKyHTDMoOk9IXikgNIIzjcRZCR6uFEJbDCsW8feKJIrk8KPAkgRaV2g6wNSS8aloukE6y7ZgRrnGchIJP2Q5iZDxIgUUBmDwDFvAxEoDIzLDC0ls0Jhg6TUimszRRciWsG697S9Y9V7cgVlBp0HdVEVGqG2gVKCymFg5HaeOCKFZFZljMuM164MuT4p+O7Rml+4c07bWe6cOWaVZt0G1k0K93txr2JU5cQYGBhNFyBXikGm+Mq1Maum47VrQyKSUWFoW0/dWZoujXydrjoerlqujHIGuQFaFq3jdLXgvLbsFQYpAg+XLdZHrk8Lzh/2/K03TplWGaPCoCTcm7eMC8PJpueVKwOudR4hoPeB0miUEgiRZswPBhnfPlpRO8/1SclPvbTPmydrJIE785pV09O7CCJ9na5NslQhKkTKa3IB6xx7pebBXOBipO89V0Y5q95TGsG4yrA+8g/vLlk1lrpzhBAptGRSZdyelcwGGXmmef3Rmi8djphU2Sfwnb/ji8yf+Qff4F/7c3ef+vj/9H/6G/n1L1z7FFe0Y8eOHV88jJJcHRe8ebKi7iz+c3U3tOPTIOWEPo60iKSCnM2HCEgDlZqSP06mKDWMS0NhFNZHZqVgvukpc0VhNK9emzDINd95mKYOJoXhtSsmbWIXmtcf1hyMMiYDGBQahaA0hq/fnPBw2XJtkvNo3nF1WpBrxbgw+BiTO0gmYUVJiVHy3RIqt20o7m0gG2SMCg0xbYZ2zlMYxaK222vkJAzd2qt4uGjZdNt/EJEEsQvR5smxscu5RNan6muj5UdmFD3J02QbXQ7i7px797jd+NrT8SwCkosx/sFPbSWfIiFEnIdZlfGo2UlIPwwuC0AZ6U32WdorPikvxmXx6FlFqfbSWoYZWJ9OArlLodmbJqYqdpFa1U43jlGpOBzn7FWaVQ/O9pzXgenQoBRkZWTeOiotiUEyLgNKKapM4aNgnGukkGgCLkYyJWl9ZFgZqvbxZ1PmScDYuIh3FgmMSs2ydWRGMRvmbFqwMVAYxUSlCe9NF4kEQox4D1mhKJGptaH35EohVfrXmpSaIARCCvoQORjmfK+xDIyk9wIlHTZEvPPYIHjlsGLeerz31Oue7x0ncWh/mAOCMjfc3q84WnSMKs3RqmF/WFB3HqkE5+seLVM20r3zmjKTDAvDpvecNx3jMqexHiUjd88avnJ9SO0io1wzry1fvT5m2VoeLlvun7ecrjvGpWHRWHoXeHF/QCBwtrY476kyiZGS3gWa3tEKQesCP/WlA4pM8f/+B3dwIXB7v+Ro2XG66hEhkgnJsNBsWsed85ZXrw+Z5JqjVYsnCYVNZ9HS0FmPlJKzdc26czxctvQuokQkUwKjUk5baRRaSR4tW0aF2Z3Qdnwou5G1HTt27Pi1QUrBC7OKv947zmv3blPuzi/8xeRpvraeNLZmgYEBtc1EvawtXuShDjTsVZL5JrD6iPD1HMiz5NoZFRm9DVRGc3Wc028bkDed5/qo5CvXhmmEbZAxyBRVprl7uqF1js4bBplGkEK3tRTc3h/y2tUxm97xS+/MQYJAEGJ8N0bi2ijNXfgQCEK86+YxRjEqJPONY2Mdh8OCK5McJQTHq54bewXDwrxHGLoIu7Y+YH3a+NVbQerJsbHLuURSSI6WLULA7f3Bu3/3cRlFz5JttGtY+/55FgHprwshfh/wn/HeEbazT3xVnzB9CDTOsrK7rYIfFpffgD8rEp7h6deSkU4Ocft7BamxgPSHLkJrwag0xlbo1MKmheRgkCOVoHCecwd98NheMCozzuqeee1pOk8Q6cSTabg6LjhZd8zKAh8CZ02gd55BJilzTWc9hdbE6NFKsVj35JmBGFBSsOktUoKRktNNixCKSZXR+4gPIKQgkxqjYVAY2s6y7gI3phmtg/uLhugDIRO8Mit4Yb/ilYMRd842DHPFzVnFw0XHunVorWh6y/4wZ+M8wUpcdDycNxgt6Xzg2qTg/rymajXee37k+pTeRUSMIOCwyvgugkwJjlcdWsCw0ByOk+9LKcnhKLVGSCUInWBcKJSEg0GOUIIXZkPeOasRASZF+jdatZZb0wIhI2frnrNNz97QMC0ML+yVaCWRcc3RumNaZlwZOb79YMm6dUxKgxSw6hxSCkJM4eEnq55xmdF7z9vnNa8cjnn1YMDZuuMfvHVKCIE+BGZVxsNVR/Se/VHBwEjWrePRombTB27tVTS9w3kY5JL5uuft0w0BwdVJzvVJgRJiN4+940N5FvGoAL69E4927Nix4wdjmx+pBLRhJx59kXmWr22uYFSAQBFCoCS+G4/l2U4TaBAEjILMf/A9yCSDQaZ4Ya9iWhlChP39gtON47h2DHPJ7VnFpve03vEbX9zjcFTx1umKRW25e97Qdi4JSsYxHWZsWscwUwiZRBKtJBOd8Rtf3uPeec39RYsEpBbcP2/4R3cXvHIwoOkDm5CE0lxr9ocZ687z8sEApQQvTCuqXNM6j5FpkxfeLwz1WxHHbwUkSbr3eHJs7HIu0YUTCpIodPGcH5ef9KzZRruGte+PZxGQLmqV/xDv/Zl65ZNbzqeDRvBoYSHuBKQvEjnJxfT9Nqg+yyhbrpOI5EMKtmv7pKLmADqNgEVSkHZRpByjxsHDhQU2DMqMQaa5OskwWtN5x73Fhq5PIe8xQu/T6wwzRaZSdtHAKO4vOwSRGAJ1H5hvembDnBuzgrPakclIawV7lWHedIzLjIFJTh0XHM4HcqOwLjIsMjobsCFQZIpJmXNzmrNsAoURnKx7jEozzrdnFQD745xhrnm4bDitLbOh58q44HCkaSNMC8WD8xYfe3It+cr1MUerFiFTg9rLh0MGueZkbZnXPbPDAdenBafrlvvzmsZ67g1zppWhdZFhLmlt5J/86lUyLXmwbFByQ4xQ5oaqdzS9pzSaW7OCl69NuHfaUGXptX/14YpF0yEVXBnldC6yai2DXGN95NqopPMhNUwEmA0yOp+CraeDjEmVoZXgyijHx1Q76kOkMoYY079zFyL7o5xRrtkfGDqbxKXZwNC5QJFJVq2jyiWZ0Xzl+ojjlaW2DVHA126NOFqkr5WS8GjeYoUnNwqtBYvaMb6pUUru5rF3vI8/+w9/mf/Vf/T2Ux//l//nv4mvXD/4FFe0Y8eOHc8HIsLJumdR9zQ/SEryjs89ksexFsGn0pyhAR9hbyA5rQN+e3+QCahbaFrI8pSH6v3jexgJVCJtTkepqG1AdZ4QwPtIlilkhL1BgRCCV68O+Mq1CV++MqIwir/35jH3Fw0+RG7OSmwIfOvBgswopBSUuWQv5O+5pqxy/a67Z9E5tBRsuiQGdS5wa1pwf95yZZKTa8WVcYGI8HDZgoCTTc81LSm0Qm1H0p7ME7rsCCozw3UB9xct1wAt5XvGxi7nEl08VgjeHamzPnBvnmS5DxtN22Ub/drwLALSvwr85RjjUgjxvwF+Avijn86yPlmigEml2HQ7AemLgiC9YUvSN/H306wXeWwr/TisI41yhfQYuX2sUekXETIDwcKiTWvSJMHpdOPofSCWKRx5VCqW5y3rJu1eDTWUuWKWSbwXjAcGhGJ/lNH1nnEROFn1uAjBRYwW+CBpu0AmBaMiQ8meLqQTlY9wuukY54ZRoYlolq1l3gbyTDLIJZlSHIwKvv7ClEIpnIeqUNxf1HRdYNVZXjwYsm4967bjjUcrftPLeyk8T0junNXcP2uptCA4w7VZyarumQ0ylJb8+O0DchX4z795wq8eLZFRMMoNWkuM1PzCW6d4BOvO4oPgrUdrvnxtyPVxyajI6VybdviU4Pas4vSwo+0Ddeu4Ps45rHLGpcZkKlWWTnJ+9WjDONc45xnlGVcGBVFEeuvItMJISSQyb1IY9rVxQW4USghyoxAxcjjKOF/37zbWtdbzaNkwyCQ/dnvC649WzNuUW/SPvXbAWd1v56wd81VL7wKDIqNzgRgFdQ/TPNWsvrAnIaSZ8uNFhxKCcWFoe4cXkCnDtDKMM0PvPUerjlcORjtL7Y73sBtZ27Fjx44fLkJEBOGZohh2fDZRJBGo5XGwdbUtu+k+xoJ0kX+kACWh7+HceTIN2giujRXLJjUQKwlapAIdYdOUwuV7kECKvxgqGOfJxSQEjEvBovacNQ6p0tiVlpJhOUJLwd15zS+8s+DqpGRQGKpMYgNY5/ExMh0YDgY569ZjrSeE+J7rSqMkSktcHciUxjpPmSsikbPGkhvFqDCEEHm0bFFiOw73RIbRh+UJWR/e4wgaFobrEa5Py9R4LHh3TZdziUIMzAYZxBSpIUjHKQ2ZUR860rbLNvq14VkEpD8SY/yPhRC/DfgdwP8R+BPAb/pUVvYJEkKk7jxm973zhUGRBKRcJdX/aYWgy2igkNCEj36sJp1YqpCyjvYHIrVm9aQzhxCUWdo2EDpimzSG1nTpZBSBzgYWIjCrJN55zlaBsH240eCjx1qBEpbVJolCMgTqzrLqLJkSaKXZtBajFOMihT/3fWS+6ZkODKvOkWtF3ToKI1FKMKsMX7s54ZfunvP60QZCwOiMTedRm57WBl69MqbzkS/tV9xYltw933C6tiwby+m636r2kbdO1ozLkrfrNY+WLevGUmpFXkqKXHFqBEYreut5eb/kWw+XKBlTxed2FCwPEqUjv/pggxGQZ4YvH1TMW5eyjyQcjDK0hHljOTne8JVrI167NqF1jm/enXPeWgaZofGRvcywbCxnm44QQEooco33KTNq3TjO6o5Rbri3aBgXhndOe146GHC07tBSMq0MPiS3VIyR3KgUbg0UmeKr10dIIXnxoOJL+0OWncUoye29AX/7jVOcC5w3PfPOIaRgoBXfPtukUEUpKTLFWycbDgYZLx8OGZWKbz5YcbLuEKSWO2c9gzLjhVlFa1Nf38Eww2j5gd+TO55PduLRjh07dvxwiQK0VDv30eeYi9vBuP3lgVKkZuRVm77GRoHtP7w1Sm5/XTyhDY83lXOjaXpHL9LjcwMRgZYS33osHzy+FsJFplJgUQdGRc60yOm9RbnAK4dDTjc9p3WHCIGHy46rowyjBcNt9ua0quhaS2EkhdH82K0JUkgeLFoerlqUlry4N6DKkwQgpeDGpHw36DoKGGQSgcD7QBSCu+c1Qgja3rM/zLiSl8B7x8M+LE/ogxxBSkmIcHfevC/o+snngTSWVneOX7q7IDcSJQUHwzzlt37AaNou2+jT51kEpIt77P8W8CdjjP8fIcS//skv6dNh2fSp8nzHF4IL1b/2SQQS34e5TJHerCsJq/A4LO+i8+pC4Kl0aiwrTBpf612ymI4rSe8iWku8D9gQMSLZUtddGpETAA6GmUAE6HvHo7UFmY6LFjZdsrx2yqeaS6EhSjobqTLN2apP7jkR0VozKbJteDQMckWRaXyI9NsA6ftNi1LggifPJBG4Ohkwbzynm5b5pqf1gUxJ9gY5i/rxeNemc5ysLA+WDWeLhumwYDIwnKx67s47bmvJorZ4H3nlypA3jjfMa4uPnoNhyaTSnK06/t7bZ1gXORyXnK4biOkk8tqVilJKJpVi1aaxuePaMc4lPkbunjcsG8vhsOTqNKfrPUerFikEJ6uWR8sWHyBXhlzBg0XLl/IB0zznvOm4P2+oMgVCpl0aJdOukI+8emVIjHC0bKgyzSDTuBD45bsLbkwLXtqv6Jxn0znOaksuBUIJro9L5m3P6w9WHG96pICvXBtx56xmWGhevjLioO2RQnC+sdyZb1BCMq40V4c5oypj07uUn7TueefUkmnBiwcDovd88+EKCZxsOtzdQOc901Lz9sGALx+OMWonIj3v/MVf/lX+wH/w3ac+/s/+/h/nN79861Nc0Y4dO3Y8p/jInbMNYhd+9LlF814RqSdlWlmX/sIFKM2Hi0cZjzeypUxRFGG7yWy0IJMRdxGwHtN9QyQiZGoCDjGt4UkHWwfkEfYnJTqzjAvJbJhjjOZs0zMu0nXrT728z+2DIffPa07W6fqzyjXOB94+2dD2jlGh0UryrQdrxrlCSknTB87WHafrnp+4PXtXRKpyzU/cnnF/3jCtDOe1ZVJqHi5azuueMtPbtmnJonZMq+39yhPjYR+UJ/RBjqAro5yjVfehQdfve54AZ5seowTZ9pr4/nnN/ih/9+fwIuj7QjDaZRt9ujyLgHRPCPHvAr8d+GNCiJxL4utnmRAiXR8oTLpZ3/H5RvDeZoTuGUMML+ymkFRRF6AElIF+KzJefGNftMUJAZ1LAXm9jzQWYgwoDUYK2j6iZXq+un+crxS3/+lspKgUN6YZD9eWXKcdjmkJiwaGBUiRRqys7XjzxDHONKu2p8gUt/ZLrPecrnpONw2TShOCRAjBurVAGk072/TomE5OmZS8ebwheHj56ogX90qcDxRaYrQiU/Ct+0tuTQuuTUs2rWZYaP7rr+zz+vGSv9c66s7RusDDRUOZKQoj2RtkDHPBSwcD7pzVrLuUBXB1XLA8s0xLxfGipumSvftHr084WXfcP2u4t+jYOMHLB0PunbesO8eqc3if8dLhkINRhrOB86bj9ZMNhUxz34PMMN84MqUYjgwDo9kbGO6fd9TWs64trfPcOa+ptGJYGm5MSqKA2SDn0bJhNsgQCMaVwUhB06ddkzQzHlh2jlmVEUJkXCg2vUeEyPfO1tSdZ9la2t4jpODbj1bsVRnjMoUAhigotWb/MOd43eK2o4aHkwLrAj4EzmtPrpMgZrSm1B2ZlogYU+vcvOE4NFyfFEwHAzat48G84eXD4W735Dlm5zrasWPHjs8ObQwMc02/S8X43BJ4LABdfBltgLoD9DaHiJRz+kG3jUqkCQhFcheFkB5jZHLlrG1IBSmZ4mCk2PQRFxyrJjLM02a07d8rIF3c1/Q99L3lxWnFeWN5uOzwPvDyYcX1WcHB0NBYz9/49hF35w2VkXz1xoTjVcvVcZlaoVtHVWgORyXnm55vn9d85dqIK7OSQW5YNZb784ZXLl1fVrnmlcMhPkZEfBxGvWwsSqY8okwrJmXK/bQ+PvV42JOOoGcNuvYxEkljb8erjtY6Hixahrnm7lb0mtf2fW6mHZ8ezyIg/W7gnwb+rRjjXAhxHfjpT2dZnyxRwN4gNTbt+Pyjee+uwNOIR4bHY252+/hA2kXINEgB/pJDrd3+LtnmH4nUtFbb9Ett55hzBy2OduvPu3jey8QI48IwyCV9TKutckXTe1qfxKneQ+/9ducjoJRn3XQUmUZ4gW0cQcCsNAwKTWuhyGF/UDCve46WHZNCkRvBuMqxNpDlikEUxBiIRIzSTAYZRggkEaU0nXU8WDQcL3u+wTlfvjrmhb2S3qXxrUeLhmGeQqVlhNNVT2c9h+OC843j2qTgfJOMuMvWsmw8y1ZQaIWNsLGOt082rDrPrMr40sGIcWU4XfdcGWYIIm0f0EqQ67Sz8PC85WjdooVgVmVcm1ZA5MvXBvyje55KaxobWLWOcakZl4b5pufN4w2rzrHWlk0fyPWSK6OcCMxry6a33JxWfOv+inndc7zs6LwnRlhs57yXTdp1OVr2rFrLorM4F9h0jkmRsTfKccFzvrZYH3hhVvJo2XG27vEiEoRAG8X1maE0Gq0EvYP5xvLG8YreRXrnmVWGQCD6C9HRsegduZDUNrBuHWebnmVndy1szzE78WjHjh07PltUUtH0jnbnQPrcc/l63QGrmOIq9ioICDoZeTI+NyNNEFSlRinBMBecrCzWps3lZevJMhhmgAh0VlJqmLcRIZNjKVion1jLxbeTj7BuLYejyI9eG3Nrv+L1oxWn645l6wkxUCnNaJBxY1Jysu55OG+YVBk/fmtKiJG//eYZuZFUuebGrCA/kswGGYM8bXpmJtmjnry+vOzaiT5QZppbexUCyLRi3aVr5Zf2BkTBM42HvccRFHimoOuLMTgtBdfHBW+drrk1KzkYFzgf+OV7C17cqygz/T43045Ph6cWkGKMNfDnL338AHjwaSzqkyaTknnjWX9W+uN3fF9chFcL0k33ZZfQx+F4PFJ22TYqFdTu8fNMclh1jx1KmdpaUy8eENNIWwxp7M1IaO0HC0cXWMBZy1oIbPAMiwwZfbKwCpiOFALYdB6pUpObrIQDvAAAd6RJREFUlBEXQQvBwAgGuWbZ9Lx8MKDQkodri0DQO0+VGa6NAkqlDKLWeTrg3mnN1XFJ5jwPzxv2hjmdT+1sA2NYNT2L1jGtDLf3M+7Oe/7h22e8c5qzP8wY5oZ1blk2HX0fcCowKjMkghgELnqmVcaVUUZnPb1N6v+6D3Q2Mi4ycqMojCAieOFgwGxoAEHjPFprXrkyoso0w1xxtOwRAvZGGY9WLTZElq3DhdQid76x3JyW1L1DxICImt/+1Sv8/J05m23u0/XpGB8Cw1JvxwVjaocQgu88XPPGozXjIktNEgJOF5ZxaXi4bCkzRWkUN2cF33m0YlxqXpwNcDHy8987JYQerSX3zxvWreVglLPuHS/tl9w5q7k1K5mWOUpWPJh3hCiQQkL0rDrL4bCgdZ66dXzvrGZkBEdry41ZiRGCXAl664HI/XlDYRTL2u5s8s8hf+mbr/M/+TPfeerj/1+/78f4La+88CmuaMeOHTt2AHQx4P3OfvR55UIAEhKKAMsnQlBrD3ENPREFTHXa5HUx5RuNSgFBoUgt38FLuhDJVbqn8D419SmgcRFwqcHZJndRkLD6iOBVBTxY9di4ftchlEuFjYEqk3RWsOosXsD1Sckrh4PU1Ayc1R1ntUWSpiNyLTleduwPMmQUrBpLZiSz0iDlR7f8KpEym/YHGeeNZdM5QoQbkxL9A+ZzPmvQ9eXje+eJUXBjWiG3wpIPEbF97Me5mXZ8MjyLA+lzS2Mdbx6v6b/fvvcdP1Q0WyupgkmRbKLnNQwMLOxj2+flsbYnMSTRKOO9dtTaPxaUJOkJDgpYWcglVKWh7y3NdkzOebDx8ey0d48b2T5sOlIDGwv7RcA5hZER7wWFhiAklVE0QaCVJwrBME9ZR0psx+KCoHcRhCREyWhQ8Gjt6Hwgk5JBobAutQxGEWish5gq6kOMHK16xoOCG7OSEKFoLVenBY8WCiEbZlWG95FxrnnnrGHRpqyeXAkKLVlLiTEAgmmp2RsWXJ3kzErDunOcbizr3tG7iFERKSVaCqpMoZVmf5zxYN6ilMI6WNYdw+0JTAnBYmO5c7xGSEFn0wlqr0pNZoNM8b3TDV+5PkGKSGc9Xe8pMk1VpJrTGJNbauTTvHcgoiLMW8sgRFatZ1oaCi0pM0WVKV48GOB94NGyozKC2aAk+Mh50/O3Xj/mjaM1Zab5DbdnjArNrMrZdD0///YpMYBSkitS8N2Ha750bcgLeyU+sB3zU4QIpVIpQPt0jQ+RwsCysRytOyqjuD6tWNslZ+sOLZLYVBVJIrUhEIFxpYm7899zxc51tGPHjh2fTUKI/Mr9OXfP248/eMdnCkMaSbOkqQKtktBz0bx2mZZ0nd8D0UG2vQ5TwKqNTEsH0nBtmmO9Z91Krk1LVo3jXPXUbaTpYdXDmkhmkqCjZKS5dC/65H2L2X6cb8WQe/OGbz9aUyhJkaUM1Id9i5Di3SxPH6G3ji9dHZFpRfSWcWXQUnK0ann7ZMOP3hhhQ2SsYLIVjz5u9OyyaDMpDRRwY1q+m5v0g/KsQdcXx9uta0lvjw8xoqQghqTafZybaccnw3MhIK1ay6p1Ox3yc0qVpW9UqcBoTds5ImmU7LJw9FFGjUB6Dv8Bx10IS/l2lM3GZDGVinfPLsMCWgfOpmPY7i5czEnzIc8vt8/LVoxaNp4gJEpFxnkGXjAaaNzaMcg1m97hg6BpHAiIeF7ezxgUkgpNay2dzbg2KXjztObesmHYBUa5ZDYyeB8olODevGc20CDSut853nB9lGO04KWDIYPcYJTgH91dMK8dVa7JlWSSa65Oc5yPHC0bfIxoKaj7FLqdZ4qXDipcgP1hzhvHa169OqR1Di0ER6uWXKUA8GIqeWk2IAiBmoEPaaRNacWL+yWt9bS953TT40Ngv8y5tVfyzftLhoWhd4FxabAhMC4VndX0PjIpM3wMSCFZdw4t4bzuOFn1KNFTGokWOYVUDIuctnfUvadzPuUgSZGqTGPKOtJaMyoMJ+uON4833JgUvHZlyLcfrPgvvvmQVw4G7I9zFnVg01h6H6ly/W7m0tE6vaZRaTb8xqSgs4FbeyX3zhsezpuUeyQl6z7QWs9+ZZg3PZVJo2yZFsw3PSpKYoRZZVLW1zZ8fMfzwU482rFjx47PLp31vP5ohYs7a/DnjYv4ikpBqaENKdv0QkC6LOYIHuckSdJ9gQeKTICAUZ6RacE4L1h1HVpL2t6jlKDtIp1PDcuZgrAVqxSRINJrlKQnduFxZirb19QKEIpRpjlZ9Sy7niujEh0id+YNWkTGuUEQOd20TMuMm7MhrxyOUtyEEFgfuDYp+Pm3z/jy1SFlZmj7wJunNb/9cMSkyp5qvOvTbjN71qDrCzfWjWn5HvfS129OUlRF9/Fuph2fDM+FgFRmiraz7ErYPn8okvovszTOlWvB2TK9uTs+Xji64ELIadzjLKQnyfQ2UFsnR8skN9TeMS4NSwtD7Wl1JPaR6GGcpbY1R9o1uDgJKR4HfQuS4CQFdH3EeY8LESUle0XB6cpiXcBG0FpSiQzrHYNMMcgVWkhsDPQusjfU9C5Q5Yoiy9n0Hltqro4L3jzZIJznS1eGPFy2+POOycBwtnZY5znxnkXjaHuHHUWGpeZ843jpoEIhOK1b3jjb8Nq1MeebHh8i75y3aJXeJGyMeO85WTa8lWmuTUpGhcYFmFQ5P/HSPj/3+gmZlowrg4hgXeDqrGSUa85rs5111rx2dcjpxnL3rGY8yDjdWAqtWLWWR0tJbT1KSF65MqSxgZHWfOv+ihf3KqxPkuH5uuelgwHnm55bexXz2jKrChZ1z6BIA4jlMKfMBKs20lvP1UnBq1dGPFp2vHVaY33Ae89Xro7YH5cMjOCX7wq0kbz1qMbFyKNVx8Ew4/q0pMw1wzKjNMk19vbxmrr3fP3mlEmpCTHynUdLbo4LroxyJHC8bnjnpKa3gfPOYkwk15LWeaKNDArNuoNCSJRQGCPxMXC2sRRG454pHn7H55W/9qtv8nv//W899fF//H/4Gr/zq69+iivasWPHjh1P4mOkdwHndiNsn0c8aXys1DAwikkRaGxk2aRN4+AfX9PDe0O29yoY5ZpIpLGO3kvuLZdoobE2cLdpMaQmtsqAipDlgtbFdM+yLbjxpPE5G5KzycfHr+FJgdw+OLJMcWNWcCWk0Ys+RurGYpRklAm+fHXIzUkKxRbbfCAtJYfDnPuLlrZPo15lpjFSUlSKk5Xn0aplUmU8LR8k8jzZePZrzQcJW+PC/FDX9LzxXAhISkgOpiX6Ufu+ysQdn20iSb1ftpCbSIgWTxJplIA2fryAJIFCp9aDQm13FmJyxASS+q9VqtkcVwop4nZkSrLue9aNhT452Ea5RguHDZHbe0MeLRvW1r/7g9T06QUzmV6PCErBdGCorWfZeKSEUkl6l5o8bu5VHHSe0ya5VEpTIoVgbQOVFtybN0wKQ4yRw20o9LVxzsNFiykNUQgGmUrjb4UmLj2zkaHtAtY6zhpHmUnuL2r2Bjnnm54roxwtBb/11QPePqnpveOhFLx5vMRIjRSB3nkkkrmLEAK9j9ycBg6GGa8eVvzinQVKwPmmRyqw3rM/zDkYFWmsTAt+88szjpcWIQTLznJQ5qxazzBXCAHeeuresek9k9JwOCoptOS0tkgBV0YZkzLjzlkSdGbDDCMFLnhCAKUEmZRcGZfcnBXcPa25Ni14tOzofaDuHF++MmRed7xyMGRUGAqTcqLePNnQWvg73zvjJ1/cY956ZgPD0bLleN2zbnuMFIxyjY8BhaAqNCeLltfrnrZ3DAvDuvcM+tS0NirT1zMAP/f6MX/lGw9xwLVpxaaz+BB55dDw5sMVizYwKCJfvjJg0/Ssraaxjkwrhpnm5rRiUTusD+Ry1ybxRWXnOtqxY8eOzweZlBglHgdl7vhc0logerKtcmNUuicYZEnosT4JPIrkItIKBAJHJIR0vxCi5XQD0yoVqPgeVJ4mGEotCDEyzDSZC/QuoCQsXSQHREhC0+YDdEgfAZ82YV0QzAYZy8Zhmw5BZL8w9CFyvOwYZRlXJiWtDXQu/ZJS8uu3YdpHq45161FS0DmP1pIY4g90Xdlaz8NFS4hJGDsY5Qwy/Wsu2jwpbD2rm2nHD8ZzISAFIio8Dl3e8fkhbP8TSONjK5sU+h7epxx9UAaSBAYaqkyQIzkcZhyvWpo+JquohFJBZpIgVWlBjCq9cTtH4wMqQpFBawVCSvLc4DuH9Q4hJCp6ooBxoQkxCU2FUYykIMRAnhkyJai7jv1K0PnUhtB0nivjnMWmI881IUSESmF9nfP4GFjXnqaPdD4yLTN8gHvnLYeDNK42zAyZFmgliSEFaedacXVY8ubRksZ6YgzcnFRoIRmVhtJIpIgsG8frD1acNY4i01wbFRxvehrnMQJyJWhtIMbIsNCUMeUbndU93z2pmdc9rxwO+cadOfeONszrnuvjilxrhITeet48rZmWGS/sVbx9uubbRytKI/nSlSG39ytOVi2vXRvzjXfOcSFyWnf8xK0pb56sKbRmNsiJIQln41yjtWK+6SmNZlJqbIjcX7TEGHk470AItJAIIdIJ0wauTww/dnPCC/sDMiV552TD26c1hVbMqozSKB4sWqpc8cJexc984x6PVi2F0tzYq1jbQNk5XIx4F6itI0aPkpJcC+Z1x9VxjvURIxUawd1Vg5IwrTKUFiwbS2cDnffoRjCtMqoCtBK8fbpBAlL47Wy6YlhqAqnmdMcXl514tGPHjh2fH4QSvLhf4Xe70Z9vZGpSNjkMqgwpetYdDAqFkJKus7RhG58hgQiZErg+Xe87l8bUnIOT0FNmAmOgUILCaLrg6fqI95ZimxkUoiBTMTnjm4j+EBNbBKYDzdVJyZWRIUTB4ShnVklO145RlSOFoHORf3DnjCKX7FU5N/dLpBRYFzhadYQY2RtmHC1XdN4Rg2BWaU42lmLecH1aPnPVfQgxbV4rgQvwYN5w97zh5qzkxvfxfE/zek/rKvphu6KeN54LAYkAG+/ZlbB9NvmwkbILNtt7aM/jMOwP4vKtdrb9ONNJGHIR9geK2TAD4Tle97gNaJ1cSTZKRqUmNwrr4Y2TBoGnyjNyCcPMQLDEEJARvrRX0fqIwOEB26ewdi2Ti8lIjfUWRJrXrYxkLi0uCjoX2LQ27VIUhnXtuF5mnG8sx8uWEMEFj5IaTUSKyGLVcVZlVJWm1PBo0ZNrwcNFy7J1BAJGSs6XLacbR6UlmZEEoETjguBk3TEdZSiZ8WDR03vPqvVYFxgUGq0lt2cVrQtEH7g337DpPcNMYl0k0/Bw2TGrCq6NCnKjuXtWU2aKK6OC042j94FNZ8mNZJgrnI+crnukgNZGXpgV3JiU3JiVvHlcs1flIKFzYzItMEryxvGGuvcUWpMrQZ5rMiM521imFbywV/LK4YiB0Xz3eMV53WN95GzT01nP/WXLrWmJlpLro5LDcc4r+0OEEogIG+d4uGyYlBnzpmeYG1atJVcCQQrw7l3gYJgzqTTHq55RpplWmjveo4Xk1t4Q69KFhA+Bs03HfpXzyuGA751vuDNvWHSOMlcs6o6m95ysO4ZFaoTbGxUc15ZpITlatCiZ2v+Msijlmdfwwv6Qa6MCo3bS9xeNX3jnAb/rj//CUx//p/6lr/BPfeVLn+KKduzYsWPHxyEirFqP3NWjfqYQpHuJp9H18u3vWqRRMi0iQiSnUVUYRoXhfA2q94wKifWCgKfMSlZ1zXkTyTXE7YRB72CUCZQRKKUQQmCU5vpEMikNJ8uOhXUQIjaCChGtUzFQ171/zRoYljmTQtM7mJSSG7MBLgTm9TkxQhRglMB4SQiB003Pq1dS/tG9VYdRAq0UuZaEa5GTdcfpumfTB148zMm0fKqq+ydFGR/TxqYUkuNVS2EUUgaU4Kme71m47HS6yDX6MIHqWY7d8cnwXAhIgcim3SUgfVaRfLSAdEGEjxUBBY9b1XKZTiiTgcEoyc29gnvzPtk2A0xLQRSwN8w5XnXEkAISq0xjrWdUKjxpRm7eO4iRUaEptMaRAqEv3ihLnRrdSg2VMRgVWHeSvcoQETxc1qyawLCUaBU5XlumpaauOzqfau0zJbk2HdL2lkXjaKyjLA0mRo7XHep0hT5T/PiLe1wZl9w9X/No2TLIFURB0zp++cGK69OCed2TSYmTkcNRQQiCjXU0rWVWaMrMYL3iJ1+c8isP1ry0V/F33zwhRFBSMBnkrK1jUsGyc0QiwzxDC4EQSRR6Ya/iF+9syLVkPMj4kesj3j5ZE2KkNIpxmbFoLC/tlZw1juN1i/OB69OKeePonacPgVworo0K3jheoZTkxqziN1ydpSayCDZECqU4GEhO65blxlFlhlt7FUIKjFZIEbgxK4FI3XkQ6Wt7+2BA3TnemdfIbRh1DCBFGiE0StLaFFiea8W6d8wGOa0L5EZTZoqDQcavuzVBKsHRqkNIxcBINr1kvukZDxTTQca0NHzvJIVwn2963ni05GTTbUP9Ii/tV3z15ojawWLdU5rA0apHG4kWgiwEhPeMMk2hFNNC8/LBcLeT8gVj5zrasWPHjs8nPkYWbc+i3W1Jf5bI+Pj7g4vj8iyJN5FUWIJQTCqNdZ5BphBEtFZMlCBEwaK15CoyLAKTYcai6RAhOZPEtpW53U4EVJlgNizIZLrmXvWBdR/IzLZq3qdimxghuMct05HHOUhVDsMiYzrMU/ubEFwf50gteLRsyaREKsG6c1SZwmjNpDRpQ3Mr8Gj1WDxZNI4X9ypGeUZhJMvGMcoNIYaPrLr/IFEmU3LrfvJbh3xy+2dG0fT+I5/vWbjsdNJK4Xz4UIHqWY7d8cnxXAhINgbafuc3/awSeH+N5pMfF0DH47HzD2pTAzDbObZcppnm7P/f3p/Ha5ZsdZ3wd8WOPT/TmfLkybHmW1V3HuBeEJqrgAJOoPiC2ipoq9iitn4c0FYb7W7F1vf11bdVoPkgatvQ7dSNooITODDD5d5bd6RuTTmf+TzTniPeP+I5WaeyMrMyqzKrsjLj+/mcynOeJ/beEc85FStixVq/FUA/CWg7+MLmnKI2hEooGuiMJVCgZiVJFGLFRXpMq5aDumPWWpIwJAktysJSP2EpjZhUNZOyI9MKGwSghFnZEIqlMtB0LVV3OMlCL3Eq2nEEZWMQhCgQlvsRaaQpyo6mtZR1h1ZuUl7rRZzbb9FK2J93aAXjsqMXCc9eHtMZw6xp2Z831J0hCwOW8piduUvjSkPNrDbkieKgbDk5iljXGaMs5Cef3aWXaEDIF4LYnbX0sohZ2dCPNFopPvLIKo+t9fiFl3a5Mq5IooB+7CTCL49LLu4XTMuGpTxmkGjSMCDUitV+wsnllCRQdMby/Pacz16esDdrGKaa1hiquuOFnTnDNOCF7ZlL72oNZ4YJp5dS5q2rVpaHikESUHeW/bJlKYupWsPurCYIhJ1JTRIqsjSirFuKxnJ6OSMKFFHoDMnOrObsckYUBpR1y7Tq+Mijy3zq4phAnB7W6aWE7UlNFGiWc5fmN6s6QiUs5zFnV3K2ZhVJHLKCcOVgzn7RMkw0gzQkDhRR5FIf94qGaVmzO2/ZGlecGsVYhBOjhGEWI0XLXmep245Z3XK8n5CGwnO7BbW1LOUxp5cz1gcpofbRR/cT3nnk8Xg8b1/a1vDC5pTan0m/5SjcJnaQwHb5ytcP9w8BkCiXjVC2rlBOUUOcChujiF6kuTyek0aapSxmbZAwKWqa2mCVZZSE5J0hDwOSIKBoLEkkWAN9rZhUHVkIeazIY0UaadbykN2ipW1BK2GQBYxLULSUi81LGDito9ZwVdc1xGVE9BNFLw7Zm1YEgWIYWz6/NSWLNB84u8y8atma1ixlIU8cHzCMnRbqYcVeJULbGerO8ML2lAv7JUnkMhJEBGMMVdvdtNT9zZwyx4cJl/YLqoXExfFhijH2pve7Xa51hOlAUbXtdR1Ut9PWc+d4IBxIYqDzCkj3LNdGHx1GEB3SV+7EILEueiTUMCmcQ+mQq5XPFg6k1kAvdpNlFCjyJIRpQVl1zOtFtbTAnR5UHTy5mhBHmgt7M8qyJQnEhYl2LToM0FHAcqxd6VarEJxQ3XheMilbAmAlc7nKFmibFlRAZzsOipr9eYdYGOYBcajJw4DlLCSNA/LOUjQd86ZhWnas9iKqzone1Qas7YgiTdcZAqU4qCqe27KUjcViUCiMhe15hRbn3BDRiFVkkWJmW6rKgGl45mLJrGmJQ4Uxlp95bof3nx6y3I95+viAg7Kmbg2mg3cc77M+SGmwnN+eoTSEormwN8daGPViVnsxu7OSF3bnZKGrXPfwWo9H13IscGF/xotbc9aHMWmksCh+4fldHjqWM0o1/SSk7kHdtry4NeXj5/b5zMUx79wYsj5KyZKQrWnNeN5QtIYoUAzSkCAQ2tYwzDRla5gUDVoLq72I48OUnWnNvGxpjGEpC4kWoaxRGDCtaq6MC7SBViyPr/WJQsWVSY22lrVBwsW9ikfXXaqdMbAzr4mDgA+dWeITF/YZzxQmDXnqxIA0CrEWVtKQ7XnD5f2CSdVijKEXK+JQM8pCytawPa55bntGFgacGqYcFA2zsmW5nxMHJXEccXY14+kTA4q2wxgfJn8/8JPPneO3fe8nbrn9d33TWb75/e+6iz3yeDwez+1StR0X9opXnnB63nQinKPoxCjgxCjj4u6Ml8bmVQfLWbhITYsUUhm0O/NlkMYEAQQaTo5y+llE0xoOZjV5HLI2shwUBiswTCMi5daeRdvx8NqAnXFJhyVoOpaziDxS9JOQIAioDPSSmFApzu/NmZYtSahoRWNMS9stxLlDp6FUG9DWVYELNbQ2YG9WEqiENNK0kSuc89haH1GKU8OUnXnF569M2Zs1jIuWd50cXo22OT5MeH5rysde2mNathgsl/ZKlvIIJe751sLG6Mal7m/mlEnCgLMrOat9l73RGYu17rmvJ+LnetpFgchVR5gOFG1nbuigup22njvHA+FAUkpcrKDnbcHhbyrg5ZzmrnKT62rPhZlOj5iJQ9dgoqCxoEOX4xwAVWc5v1eg1Zy6dTnPgYbUQNuB0s7xFEWaU8s5RWuZNVNipag7S2sNu0XLqaWU/bpla1zTTwKGaUSohXmtGSUKUQqthHnbEinFaJQjxrA9q6iajjx2VR325x1J1HGsPyTUmqqF1X5KHguXdws601HUHb3EVSmzxlA2hsgasjjhWD9ib94wqzryJGSQhexOG8qyZZgGrA/Tq8LL/SSgbZ3ItA4DlFK8tHVAlIT0YsW8tkzK2v27Pae18PBqxslRxrRqMcDlccmsaMnjiL2ywSiXghZqACcOvTV1Bnd5KeLRYz3CIGBjmHB+t6BrYWdaM0wjOiM8sd5zIuZVy7gwXNyfo4OAC/slaag5Fmv2Zg0v7s1Z7sdsDBPmlUsxazuLtR1Vo+iMcRFGrWHauWL3becqQkSBYjWPuDwuUUrYntYkYUAvCambjq1xTdW2C8NoObc3Z5hFrOYxO5OKQR6x1BrefXLIMI9pO8uL2zPmXUcSKp4+MUArRawVUaC4PClJQ4WVlKJqefbKBK2Fed2QxSGX9wtmdUseh7xjPeHTl8YsZZpRP+EpDJ++NKGsW9rOpf4dlA1Va1nJYx9+ex/go448Ho/n/qCxLlpablVwx3NXWI6B0B2eXjyoUDpgvQ/juVkcvLp9gBZQBqrG0EtDyrol1Jq2s8zqlt1Jw8mVBAFa02Ks4smNHs9vz1HUjKsaLULRtsS1c3Ac60UM44Bx3TBIFWt5hmiht6ggnIQBa3nIQQltl7Cva+atpakrp3uk3H6grp1GayDuIF3E7VfzSHHpoGSQagZJyPFBzEu7JU8eH9It9I+q1skiuCQy2J83DJIQpdyhuQChdgVramO5clBQd4b3nR5xcil7zappr+WUUUroJyF5pN+QcPWNtIuUct9fPiip2vbqe9d7xu20vRW8GPet8UA4kDprifVrSTV77iUC3AlDEkHROq9800JVtewVUC7aHKa/tbhThRBoGvd+0rnrTWvZbV6OTsK6v4RRAv0kJMtC1vOQtjWcGcY0bUtRd9B0xDpkXLbUjSXPXFWwQaYxncVal/ub5yH9OKRuO/IuoGoNj6xmXNorGaWWujMkOiC0Qtw5YzStSsSGlB2kkWJ32mGwbAxSRmnEblETBUIv1kQaJqUh1ZaDxvDQWo+y7jBK0Q8VvUhjsTy2lhGHEUkUsDdveHQt5+J+QW0s87JmUjV0KExr2Jk3WCtUnWFclAQ6pDOG83slF/YL+nFE1XYME82xYcKZpYxze3M2D0q0Fi7sV+zPSrrOMsoilvOYtrVMyobOtuzOKzbHFcu9iEQrZkWD1nBQVIyLmiQUlIJ5bSibhqZtGSQxa/2Y5Twm1oq1vqvApkSxMUhpmhkXDgr25zX9WLO8EbE1qRCEIBDKpuXSQUmghCuTihPDhH7idJsuHpRsWJiUNXvzmuVejFZCPw54cSEEbnB6SlsHrnrF3rylaC1LqdNbWskjroxLysawPkgIAgiDABYV5/YKF9M+rw25UiTa6Sw1nWGUaPpZxLObU0It1K1lazznwn7JtGx4brOlaS29WHMwazm/O+edJ4ZeQPttjnceeTwez/1DKIosDrA+Aum2uV6l5NttFx5+syhu01pIQ0XVGiwNIpCGLmNBBLJYMUgidwjZGiTW9OKAnWmLYBElzMuOzfGMfiiUBs7tzGlaQ6CF/b3WVexNNUEYcLYfMcxiwgDUXsHGKKNoDONZw6WyJFLQS0IOSkPZQBIFRE1A3VT005DOdMQY2rnFWKgXA9WLcStxewslMGs6wqrh/F5BoIRxUdNPnQT4rG6YFO5wVStFHgdXU7Y6a6/qeooIWahYySPSKODsck4av/bW/1adMkrJ604Tey3toiQMOLOc3ZIz53ba3gwvxn3rPBAOJCWC8pkg9xSy+LqeDT6MPLLAvHXfBOLazuuX84UF5zw6/L42Ls850hC2EIbOwz817l568TcQKegM7JfQmoZeHlEYGMXCmdU++0XL89XM9SVQrPcSp1cUBsTSUtYdk7rFWuNEu0V4fnvGWh4Rx5pABVzYK1jJIsJQqLqOKBDmlaVTEVmkeWI9Z95Y7Lzl81em7ExrurajJcKKMC5alvOI48OEaW3IwppBGjGvGvZmNXEY8MhKRtUahtbSYXn6xBK1hX4cOOdH7aq6WWMxCBv9nLaznN+dc2FnyijPWMoTklizX7SECwPVGsv+tOLivkIQVnsJnzp/wHo/ZWtS0XSGIFAoBKVfPpGwgA4CzoxSDuYtoYaPv7RPbS0v7c9ItcYiPH1qyKlRyos7BVkUcm5vRhoHVI0lDkM2BgG7swYWueFKQRIqVgcJ/VRjLDx2rMfu1Dnjzq7kNJ3h8rikU5ZQK5TAXtGQxpo8CTkOrA8Sqq4jjxRRIIjA1qzCWAhDoagMIjApK86u5IRaUTUdF6qO95waXj1tQWC9F7FXNLTGkOiUtrMMUs0VSs6u5oyrhjQKeHF7Tj/TzBrLsVBhgYfXejx7ZQIWDuY1cRgybxv6aURRG6Kg4+LejEF68xMiz73LTz9/nm/+no/fcvu/9lsf5hvf+/Rd7JHH4/F43ihppDmxlDFvdt7qrrztONyGXy9w69oqatfqoMIibS0ArVwUThoKk7rj0l5Fa901sXZOo7oFYw1hoFkfhBSt0HUde0XLQWFouo5hrGmAedVStYZBHNHTir1ZSdW5dfNSohmkGhGh6QwdIcNEY4yL2FdKcX6/BCxhICBCUTWoRQbB3qwlDoSxKKIgYGYMbeNSvkINXevWzh3usLxpwVKxlEdo69bXu3NX/GZrWnNmpUdVd3z20gSthDTS5FFA2XQ8umJpMIh1zqNRqpnVHa2xNMbwyLBHfBvOkDvllLkRt6JddDsOqjfizAIvxn27PBgOJAuT2h8X3EtYuK4q1WHkUYsTmZssgsaqeuGh714+nTisWtAB/UUucxo673uDCxG15uWTjEPDZA1kCjqBpVzTtpaibpjMG0IlILAUB3SxJtOCEcXWpCKLQrQSLk1qmqalMwaD5aKpyLWAgrVeRBwGTOuO1TxBTebsKCeuHIcu5NMaqBvD5rhkXhnqtqUsO3QEXdMyxzKpGx455qqMiTXMasPJkaLuXGn7qjNsTko2hglxGDDKYhoj9GLF1qQhDYXnxxWDLKJoOp7bdpEzYRCwNswpq5ozyzF5ErE/b2kNrGaa53YKhknAftFyajmj6qBsWy4c1KSx4sxqRtVa+nHAud0ZO9OacdnRWkMeRfRjTX9xurFnGrQSemHIFz+8RN3C8VGMsZBFmrV+jLGWURaykmp+7oVdpkVF3Wree2rIu06OSMKAzlgO5g1F05FFIVkUEIUBs7qlM5aoMyjlQm3jMCAMFJEOqBuDMRaDRSt19fXTKz2euXiA6SydMTx2rIcYhVYwLxtECUmoWc0jOmu5sFdwYW9OEmmW84iq6fjs5QmdsaxmMe86NeCZS2OuTEq2JhUGw+6kRGvXl/VexqgfISi6riPRQtdZQqUIdcAwDfnc5RpMQxQGrPWdo+xg3nByZL3hepvho448Ho/n/kQsTKvGZ6/dBtc6hw4JF68druevrtF5ed1+eJh8uIMbxopQK0Qsu0XFrLKUrSuGooDGQBoJwyxkXNSIsmzNDNZ0zGrDiWFM0XTsi0UHbl14UDRuPYhL3bp80DDMA7QCI8KstowyTdNY5mXLWj+h7gyBco6a1lj2phUWSwAUjaGsCnppxEovpOksgWpcZJAxIM4RZrtX5sXkAkag7izWWMqmZWgjBknAxrKTp7h0ULA5rugnzqlVt4a9ouPEMLlabViJsJRH1J3h3M6McdGwnMfoQLmMCHXrTqQ36pS5GfeadpEX4749HggH0qxraTofgnSvYXHG4egE6kI4XSWC9hpr0+IMRB44/aJDg5ICeSqIuJDHWd3RGEPVwvUKZXQ4I6NDmDYdl2dzdiYFeRqxOSkp6o5QC8M84sXdmta0hEoxq1rSSDNIYGwFGqFrDU0Lk8bS2pJ2ofPz9Ikh63lMS5+T21Mu7s+5tF+CVcyalnMHc+pWuZzscYcOXbitVQGlMU4Me1yjpHH2xnTszBtODjNUELA/rdiZ1uRRwABhmIacWk6pW0PduspjtrNorQhEsdyL6UyHEsUwURzLM04u51zaK0lCRRoqRBQb/ZjTaxm/fHlKszgh2ZqUbE0a8rhgKY1RwLm9guODjHltKWtD3VmeXE5ZHcR01jmqlvKQ5zdhZ1YhQUSoAgIUw0Qzr1vyWLM1KTHG8szlCRtLGSIwTEI6A7uzmvVBQhpqskEA4v5eVKAo6talyGUhL+7OWcpCjIWlNEQHiqUs5NJBSdF0aKU4PkwIF3nhxhoGcUBr3Gd+YpRx4aAgDhRpEjIwll++MiEMFBf2C8CFIR+UDc9tTolD4ZHVHGuhMYZx1dK2HZf2Si7szbkyKZnUNQ9lPY71YrJEMytbBonm/WdGfPrSAUXTMbOugt6khGGqqTuDEsu0rnn32SFRGHjD9TbDO488Ho/n/mVSN+zPWhKBmd9W3DKpdhE2wsvr8gZuuro5jCjqhzBvnNPl2DChqjvGVc2ssE5LiJf3DliYVB1hFHJ2JaPohLptmdYWLZa9ouXkIObkKGV7UrJfdoS2I4yFomwJUiEOnWZSZSxRFKBQlI2hrDtOjHKKpmGllzFMA/pxiFKKy/sVoVLsFDV0HcYq+oFQ1B1RoDixlDEtamaVUFSuz9f++RQWQgvDRDGtLKHueFcvZmM5Y3O/5KHVnDQM0EqoGsOJpYRAFNOqYVy2rPWSq9WH9+cNDy/nKOCRYz3SUGOsfUVEzVut9XOntYveKPeaQ+te54FwINFZqtbrH70VXC+X+TDy6NqYMAFWc6ha56S/9v1UnEh2a1yUklbQWmdgpLNIYDmYu1OBzrrKC7a7frhsCYSNE142BqatpW4rlHJeZ22EJHJRKVkcYgxgFyGqVjGvaprOMKtcipXSoLCMi5pzuzOW84jxrAacGHesFCv9hADLCjFbk4J51zEuXCRTGgqBUgiWwDpHyXjWsLGSMYo1F8dztic1x4cZwzhgewaDRBMvxLG3pi51ar9oeHZzghbF5qTEAEXT8eTxPi9uz5hWLTpQWKX4/OUpsVZ82WPHGPU0z16ZorQwLTqSKGB7VtK2lqppIRCW04CydeGxTWdQCkZ5yBPrOftFy0ov4vJBCYtqDJFS9BJNOhPqxlC0LXXb8t6TSzSdpRcLozTk+Z0ZGqGfhmyPK+ZVQS/WWGvZnFQc68dsTiqGacjOtGYpVlweV2wME3pJSD8NqRrD+07lbM9qZlVLoBQfOLNEqNVV41g2HXuzil98cZ8oUCz3Ih5b61F1hsfWcqrFqU9RtfSzkKYz7M0b1gcxWaSZlDWfuTxmbRAt9JoiAqWomw4QdxoVOnHGtoZp1fKOjSEi0BpDrF0K24WdOXkcsl/UWKO4NC45Pkhp5xWJ1kRKODFI0Ep5w/U24bOXtvmav/Ezt9z+z33DBr/nwx+4iz3yeDwez90g0NYXYbsNNFytPKbEHQJPWneYa4+0OUzlinlZqkJZiCNN3bWMsnChnxkwrwN6ecfe1LqKurj9gCgYxAHHBwkPLWdcmVZMS8XxviKLQ+ZlSxg5mYPGQD+JGKYx+0XFtOoW1ZwVgyQkSzQH8xZrDMv9mP1ZQ6BcRNLpUJHHEWv9iPN7c1prECVECurOSWWs9mJ2p7U7KBeYtx1VYxikUNRQXBOBZHCHmlVnOZZrVnoxl8YFB2VDY2Fn0nAuLFAK+mlA01oq22I6WBvEV6sNH0bOtFiCQJEvsgIUcjWipm7MPaH1c7fT5G6He82hda/zQDiQLCDB9TJqPXebQ6FrjfO4c+Tna38bCigb5yA6FMY+JMaFdiZqUakgcLpI2rqUtKqFooLKuLDYcFEOc3YTv2GA00IyOJ2krHX3jXFRRWPldHhGaYYVxf6sZHdaspyFZFrYb5zTK40Eay1hGHJiGLIxyvj0pSl55FKUTgwiNhs3OUaBYmOYoRUs9wyTomXTVoRGUTUtkVaIBKz2NAfzmlBZiqZjJY/ZmXVsTwrKusV0HVkaUtYdqQ64sFsQBXtMyhaFuCpq1rA1rukE8khzcinjoGiYlA29yDk+Vgcx47ohbRXjsuXkKGG5l7B5UHB+Z04caVdhLY/ZL1uGdcuplYylPKQxBmPglzdnJFGAmoIgbIxS9ufutx1pIYkDitqlmaVhwLRuSRLFc9szHlnNKOqOK+OKT10+wBrn/JvXTmdppRcT6vSqgXl8DWpjiHbmxIsqbCKCAHEUcCZ+pSE6PGExreXifsGs7q46hCzCrO7Io4A8DlldRPy43HQXxbRXuDS8wxMdwTIrO5qmZHNc8vBKxiBJ0IF73jDXPCY9NscVsRbO783QIpxazhmkmpe2Z0zqFhFhpRehlRDuGU6MIj7w8BKzWcOsafkvz+4wTGPqUXpb4caeN5/3fcePsH8b7X3Ukcfj8bw9GSYRZ0c5xnoNpBtxuNuKeDnSxtrFYatyh7+90K33D/cF7hgOkkUxnE7cXiCMwKJY6secHKaIUgw1nBqkvLAzpygLprV7Xgj0YlgexORxwImlhCuTkrppQUL6CTTWUlUtwyRkbZhQ14ZACdsTQySWNNT045AsCxhEmkdWe2xNCvZmjVv7hyH9OOD8QcGHHl5mVncs5xFPbYzYnBRUjcHSksWaAGhaw3bREkdCL9KoUcK0qCnKDrvo89FMidrCdG4XBXgstmwZJCGPrvZZylxRn17oNkLDWBOEihODlK1pRVG3xDq46hSKlLpuRI1Y3jStn1uJcrqbaXK3y73k0LrXeSAcSCKg5dCV4XmzOfzUj06U1/PrCC7yKAwEpSx9gYNm4QAU5+wJNKwNNEoFTIqW7Vn3qjS1Fug6dwqQCVT25ecd5mLHCwXuYJFs3VjnuGgbd0ISaeWcMAaWjSVQBtNZ6qajIySNNZuzDiVQt5blPGSYBZxZGWCMYWMQc2yUcm57yscvTFjONVhF0xg2Z7V7SAOBWJ5a7xGI8OL+DKy4U4085NNVh1baafsEAY+vO0/4+Z0ZB0WDNZaHVnuMi4adomE5D3ni+IBx2fLTv7zFuGzZLxqiQNieVlR1S9EYYu3CX+dNx7m9grbu2Jwk7E5LWmNoWsOstrxro8+ol1DULWmsEeD0SsYjKz2KtuOF7RlN19F2hiTUHBQtJ4YpeaKZNx374xKtFY8f6zPMY17cmvLS3nyRthVTth3GGIq6Qwu0rWVvVpNGiiwUdqY1toOHlnOChbYRQF0Zrkwr2oM5k7KjnwZoFbA+SIij4BURR4cnLMZa9mcVe/OGQCl2ZjVJGBBr4exKxqmljM1JRd0ZamNYy+KF4yxkd9pQ1C3zxUIhDgPmdUdZd9Sd4dQoo+0Mn78ypWthmEWICPvziqIxPLE+4F2nhnzy/AGfvnTA9rTGWstKHhNoxUOrPUSEedFStoalPHIRSvOKS/sFZ1dyb8TuUXzKmsfj8Tw4aK14/Hgff6zzag6zC3oBVB3EIUizSEULoZ/AfuGihOrareujhXbR4Ro9DSGNNaNU0RrFUqrZmbc8tJpyZrnv1oEK4lCxV7RcnlRk2lAZiBUggiwOIi/slyz1YqrWkCdOD3SYBpQNDNOQqjXsz+bszRunTyowa90h6wdGI957ZoVxWfL89ozWwInljKU0pGgMa3lEHmnWegnWWDqBy+OC1UHE3lwYpZqdacUw0Tx6rM+8afn85QPK2hAqjY46dPXqDIkY5zjrjGGlF9Mad0j69EafykBRtZRi2RimBFoRIBRtR9l0bE+dO+7YIObsSo7W6roRNVZ4U7R+3q4Vze4lh9a9zAPhQAqDgDjwzqO7iebVE6FmEYKKMw7hIgUNXpnWdpjmFi0ii7JQOT0gLaBaWpcJRggM0oBYK3bmDZPC3FDjiMWz+wlkwLhYvCaQRk5gO9JCXVsK6wxPICDaiSQOkoBhkrJbVozLmlQHZLFi1gakGmalYbUXYCz0Ys2samkrQ2s6xvOWUR4RiKKxlrY1lI3hWE8zqSzzouKgbNkYZAyzkCzSHJQ1q2mEDgOSwIlwn1rKGWSarWlFP1aM0pB51RIGitOjhK1Zw/TCmJVBxKNrfdYHCed35wRiObdfkodCPwlQgYvE6ceay2On7ZNFmqru2J5UtG3L04l2JyuJZqWfcumlXV7cL1grW7RS6KIh1AGPrPVorSUOA95/donsSsC86piWDRUuHW97UqGAKNaMkoDL+yWqbLiwX7A7KWm6iDAI2JtW1K3h+DDh2U0XzmXFkoYBL+6UBDogCQPO7c2JdODS4gLF5qTi+CDms1cmGGuZlB2PrMT80vl9jg9d6tdh2ptzRirmZcMXtmekobvP1qRiXrWs9mIeXu2RxZpjwEs7M/c57ZWsDizrg5RjPSeYaPcKlCh6ccj6ICEQYTWPiaOAR9b6XDooeXZrQrwwyr1IE4bCIAv45Pkx87phkEY8oTUv7c/ZnJQspxGPHetxcVJxbmfKrLHUVzoSrRjEAav91Osg3YN8+uIWX/c3f/aW2//Zrz/Of/ORD97FHnk8Ho/nbtN0BrHCqAfz6Vvdm3sPjYv8DwAM5JFL1xKBsoU0CijqDhWAtNAp5zBJtXMeLfUiitpSNTDKhCAQTgxTlvOEIBC2pyUPr/VYHyRcHM1BDJsHFZ21FK0h0YqDsiVPXDraWi+hHyqsKIZZQN0JyrrUroN5w2agaLsWiRNODFP6kaZpW2aNZXdasD9veHQtZ1p3WCPsFQ3TomUpD7kyKTk+TDm5lDGtWgIRsjhEi1A0LfPasNJP2RilfPbSAWXjop0QSz8JCOgwBsaN27ccVplTOFHwNNKcWcmw1umZpkoRBYAR8kSjEC4dFHzs3D4nlxJOLaduv2UhWhy4Xi+ixhh717V+fEWz+58HwoEUKEFdr+SX545x6DxKcME1hXWOoUyD1rBXutBMeFk4O+TlPGcB0kRItGKYueiUZqGUHUUQLnSGOms5KF30zWvpouvFVyfCILZXTyi6zjmLus6yNNAERev0kqx7TmVgtZ+x1ovol5qiNjTG6WjFgWZr0rFXtkSBEGnNMIsoGsNjGwOGuROA3pmVlG3LeFqDWBIdkCcRWWR5YW/OKAnpp5oLByVXxhVLvQgdhBR1w8pKAkrxrhMDkihgVrVc3isYphFNa1nK3alEL4G6bZmUNRd2ZhR1R55oDmY1bdfRBppeHHNQ1qzkmjNrOQdlw0HZsDev0aJYyiKO5Sl7ZcexQULbwfakYLtsGCQhB0VDVRtCDb/ryx/m4dUB9SJyaTUP+cKVqdNVUk4v6tzunJVeRGOcA6VtYWOQsLXIA59ULb04Zl63ZHHA5YOSOBBW8oh51ZKHLj0uDDSX9woeW+3TT8OrxmhjmGCsJdYBS2lEGgaUXcek7gjEpcgBXDxwHkMRxfa4pGo6mtYwiDWzqiGLFOv9jPefWSKLNcZYvrA14QubM1iczuSp5j0nRwA8vz3lnScHfGFrTtW4yKN3HOshgQsHzmLNr3hsjfVBzEt7c17cnHFyOaVqDc9tzrl8MEcpYZBELm2wdPKRjx3rsTZM2ZyWjOuWurZUnaGxlp97YZflfsJTxwd36P9Sz53g/d/xI+zdRnsfdeTxeDz3B8ZYLk9Lrl9o3qPEraW1OE2iXhKQxh1l66Qm8mihX2rcniANXRTSaj+ml2jqpqU1HbPSuAilRsgT4fntKY8f67M3rXjyeB8ETq3k9JKQh9c6nt0c8/yVOSawaBHGZc3Hz3ecXq7oOhdVcmww5IseWuK5zRnPbU/YKxpGqaaoE06vZKz2EsZFTdkZHl3tMchirAiXDkp6UUAYKq7sVyylIe87NWJ3VnP5oOLUUsrDyzkPreZc2Z+z1ciieE3AxjBhXtdcGVdgQamAtX5I21pq0zEpO6JJwX7h0vsiDXEg9BPN+06POL2c8vx2wbndAhEhj52o9+akYmtcsZKH6EAIlWJ3VnNilFLU3SsOHq+NqHkztH58RbP7nwfCgWQtpFpz/cQpz50kUE5/yC4+aqtAAmdmDQstI1zE0WH0UAAMUwhDyLTmeD+kIqIsGlZyzUs7JdMKog6UMtQtdK9RQzUCohDGFWhtiQMhCcAai4qEWCmUFrJQEypNoA1Yoak7UiUMkoDGWmZV56JYRNBKowOD7WBSWwJRDGPhoHCaQsuDiBd3CnYnNVXdMMhipnWNwp24jKua1V5KHLhTCgESJRzULV0XsDyIOZhDgJDHLnopVwoQRMGkbNCB+4x3Zy3GOJHpSBRF0bI5q+jHIYNUM0hDolAxSjXz1gn/gWXUi6lbgzWWuoMgUEzrFmmFSAU8tJbSGTcxlK1hkGjq0JKHirqGi/sF1sKkaHhua8LWuAaBlYHmYNowrxtnxIYpp9b7GCzPb87YnVUkUcCpUUYWB+zPa04tZZxYytCBcOWgpOlc5Ne8NvQTS9Uahpl2ZUkDJ/4H7gTw4n7J1qRGCSxl7rMMjwgIysKAXpzMCZUCLJOqYXdaIUoYphFL+ctpcUXV8szFMUtpSBppirrlc1cmvONYHyNweVwRh4qVLMRYp0t1cVyy3k94aW/OWj8mEKGfRJxZgp1JTd11nNsrKesOHSh6kWZWt6wPIk6tZDydBJxY6rHej/jc5SknhykX9goi7fSZsjBiZ+rE2rX2HvB7AZ+y5vF4PA8uxlg290p8fYvrU1qnYzTqOeFsZV1x+34oTGyLtR1poogEprUh0ZpQC3msmZYt87qlqjsaA/uzmijpqDpXYeygrOmAS+OC48sZoUAvDXl+syILAtJEk0cKi4s4mpcVW2N34NghPHtlxvFhShgKk6KlH2nyQcLJ5ZznNqc07Zz9qmMl07RWOJg3lK3lxCAmCDR123JiKeErn1qn7lxRna5tadqOy5OOlX7E1qQkDRRpHtOLA/Ik4BeeP2BSNkQ6INCuwlvbthgRtydRijQyhIEgYgl1QD9xUhlIwHtODxkkIYEI5w7m7ExqFCFKhN15A9YuZD6czMatRBPdba0fX9Hs/ueBcCAlYUAgvt7m3eLwHEbhonfACVsLh6lhQi+0zJuXI5Us7o/vMH1tXsNAC+vDmJV+wqzqmJc1L26X1J07ydDAvHTP6scuiqgsr9+nXghJHDArOwLlyrvLIvooiwLiULFfujLqogKMUQzikFYb1vsJaRQwqzpaC8NIUxuYzSrSOKS2EOmQsmnYmlnazpLGmo89v89yHgEWG8D2pObUcsq0ailNx8G84d0nR1zed0LY5/bn7E9q4tCJa8/qjrq1GGPYnZSc35+T6YDjw5zlXkIeCV/YmVPWHUXZ0mFItUvpO6haNuctTx4PWM4T5pXTOxqkmrKO6cXCSzsFeRxyZjXnE+cO0AInRwlV07JTtDyxkdJPE87vTrkyrVnNIhojKGBcGS7sTXkqXUIJzOqGWAWcXEmJRXFlVhKIZX2UspyGlI3lykHJ8aWUldw5eOrE5Y7vzWu0Ek4tpwQq4KGVjLMrOS/tzJnVLaeXM4wxXNivmJQdawNL2xmatqOoWuZVw860pjWG8bzGGIOxwlIeXo2ACoOAXqj4+Pl9lMDutCLRikv7JYMkZKsrWe1FXDooWO8nPLczYXviTog6axkXLTuziud3pgRKEWlBK0GFAUXbEumAh1dzQLh8UPDSzgyAU6OUPA6Z1y3n9xrKxqXJrfVjjg9jnt+eEwaa08uh+zuLnXB3qAzndwu2JjVRAGvDhLVBSKwVnfVz11vNc5t7/Kr/z0/ecnufsubxeDz3H40xzOuGzvoYpGs53FAmEVgrRFpoWkOoAyprCEOFQch14BwqgQJleWilj7VwcX9Ga1/WMO0sRF3Hft1hFxXWlvKET1+csjNtGOUhj6wOCAPh8+db8lBTNi29RDMta3fYV7cMkoiVfsxqHvPc9gxrhDAMiLQikIAzK26duj9vOdG5CntKQd12nFxOiQPNsX7ErG453k8YJCHn9gp2pxWb04qVaQXGsFd29GPNvDFkWugMDOOI0ys5URhwUNTsTRvOH8ypm5aVXkocBaRdwF5hqBpLEkEYWE4tpzy6lnN6OWdv3pDHmqYzREHASi92KXtNy96s5uxKzrndgn6iWe3FnBjdWjTR3dT68RXN7n8eCAeSILwNdLvetihcqlrZLgSsjYsAylIIQ00UuGiS1FrKdiGKjdNEylKh6yxaYFYYNscFB0XLch5S1YtJvHLPGdcu7Q1cxTXUy+lvRwOSeoGr4NCYjn4WMMpjokAoaosxHb00Qikhs4qybLAYelHIKAuZty1F2zHMNVEQEigYZiGXDkqMMezPKowxtE3LKInQWphXHXXVcCCKom7QSrHajzgQg9bCchhRN5Yo1AyTkFPLGed2ZwyTiEy7FLXGQNU1HB/EbE1rtmY141mDFTi3N2clS1juuxS29WHKch7x0t6M7UlFHGuSUDOpWjbHNRuDlg53ojNKY959asTerMYiiECoFNOqY1o1iBKUDnhiLeGJ9RFLWUjTGlazGduzmjwOGKURJ0YpB0XHtGrZnzdYK0ybljQMuDIu+eUrU6q25aGVjKox5JGmtYY8DKiikFljsI3w2Hqf8ztzwjBgrR8TBgGBUqSR5l0nBvyXL+wwrzviIOBLH11lf964inB7BQfzGivC7rTmPacHDNOYpuv4wtaMJ9YzLh5U7M+c1tJXPLHGuGxZ78XszhuMNTy7WTLKIk4sZWyOS87tzQF4fmtKHCoirZiVNZcPCkZZyMYgJdUBF8cVa/2IZ7emtJ2lajoePZYT6YCL+y5VbmdWOUHGeU0/0RwbpMShYutA6KxlfRBzrBezlMV88MwSBtid1c5ZNa+wCIM0YL9QtMZyUDTM645RGpFoP3m9lXzZd/wI52+jvY868ng8nvsU66qCibX3pfPo8FD3dq8RXNS/AhItVI2ln2mMMYzLjkgJ/TSirFsOyppREhFHikCFtMZS1Q2hCBgnN3GYCle2rriOIOShpq5dZLzpDNbAZy7tk4WauYHjw4QXdmZUbUcUBMybms4GdNaQhZqDoqaeGJayiKUsYjyv2ZnNKZqG5TRGKaFpOhBhXnZYBScF3nNqSKAEa3HaSwcFl/cKxlXLWi9ib9Zw6WBOGirmVUeohAsHJUtZyLn9OVmkEQvjsqNo3KF2Hgc0XYepDEXdEgjkMeSZW/PNa+OEwueN2+N0hkCcflEYCCeWUspFtNEgdfqlgzTkzFJ2z0Ss+4pm9zcPhAOpbjvG5WvkPHleN7L4j+BS1JZyMMZNdHvzlniRxgZcrVwRBs5AKCxl59LZEg1pqJlUNbOypuqc4bC8HOHU4pxTceRSuVTjcqkPA8yCRV+McXnEmQ5oO8tKGtK0DatLKWmoiUOFlobTJ/tMyoaitliEs72YrWnFxf2SYRZd3cxvHpQUVY0R6MUhURRSGwtWkSxKwpvWMLdwLA8ZF4am6yhqw7FBTB4J68OEQAmjNKQdpogISSic2y3JtHBl4nK+r+wX7BcNTWexGHZnHVVtWeuFhFHI2dWMNAgW1cw6TGPIEk1rA7Ry+dqnRwkPrfU4vZJRt4ZkqBdOiZYoVCjgnRsDsljTGvcMMHxha0Yv0jx9YsgL23OKtiMMFceXEtb6MSKW08spm5OKQMHl/ZKqbtEKVvoJBoVgmZYNS1nI1rRipRdhxVJ1lqo2DE5q1oYxS0nEzqxhUjQEWqgNTtR6OWM5j1EiWGu4uF/wwu6MfhwySjWX9gue357zvtOuDUDVWE4MU5QI07phe1oRIARaEWohDJzOEcDurCJapCVOyxathMcGA54+Dp+5PMECgyzk3SeHZHGIOSjZmVWcGKZ0xjBvWmaVoaxbmtZwZVI4rajG8Nx0Qh5phlnIUh5zeinjF17Y4/xegbXClzy2QhJrAhHySLNf1Dxzbo/dWc0wi3k81FSdQSvFMIs4Poy90X0L8SlrHo/H4zkkDBR5onlNEc63CYeViQOg4tYcSMGRdrl2B71F7TREH1pNGZeGpGmJAk0eaUQ19OOQWd2RJ4p5LfRSjTGKR9cyLh+UqECRpyF1K7S2oqqdfmo/1kShJlDCpGpRgbCaJ+hAyKKAlABjLOu9lN2iIg8VHRaxcHa1T5Zoutby0u6cYRqgRGisJRIoWkushaU8Zm9asDVrWMlTQiUUtKymEe84PkDEucg2Rq6K2OmljHFZ88tXpjy3NQOcc6kzws7cZTbkWnjkWI/lNOK5nSnzxjBKNG3TYWLNvOww9lD3SBGojrU8JIojjg8Tms4V4AkDpw+1M60x1lXpxUJRdWgV8P6zPaJAoZRQ1B32Hlsu+opm9y8PhAOp6jrmzf14VnBvYAEWwtRJCHkUImFAWbZ0dUvbQWhd5TMdQh7JIrTUvZbHghIILFwalyhRRNpSNGZx2vNymHCCc0YJkIaKNITWWHZnlhYnzqcD9++ktFhriFFEccCZPOaxtRwjiq0DF+mEVYzSCLEtjTUksSYqOwaZ5uxSzi+d22d7VtJLQ471I87vzhlmIXlrOZi3lIsonjOjlKJzqV1WhLMrKduzGmsMs7JjmEVEgaI1ZiGmHBLpgDAQZrkhjRRpHHDpoGDetrTWOZOaRRhvJ9AijEKY1R2VdLzzxJC6deXpw0Cx0hNEhH4Y8MSJISeXU06PMr6wNUUJlE1A3Rr2ZjXHhiltB5cParRSBAqe35qzVzacGGSs9BMXFVV3DLKQU0sZq72Y/akL3U7Cw8gpS5JoHo17VK3h3O6csg5YH8YYsbRmcWpihX4ckGnrxPU6IQoDnliP+dyVydWwtH6s+dkX9+hHGqWEJHRpZ7PaCXUzh6U8ZFq27M0qwlCxkkcYC5F2lR4S7Rw0rbUIcHo5Z5CEVJ1hVrWMi4bVXsIo06z1E8ZFS912LPUS3nHcRcs9vtonS0PazrDWi9icVLRtw0HZspxHVJ2LxprXLRd2SyItnNudszkuUEp4cmNIEroqfY8f7/P0xoBACc9tzSgqJ8LdGsO53Rmfvjim7SytsQjCUhIxzCI+dHqZfhp50cG3gJe2D/iv/tp/vuX23/7RhD/+NV95F3vk8Xg8nrcapYTVfviqqsNvBQFuE1e9jusMLqL/cN2OgmSx3qwX2QTCy8qxh/ql4WKN3TRglKua1oudVidiCVRIqjuyQYRGc2wQ8uzmBLHCMFYUTYexFoviqY0BoXKC0U1nWOvD5f0C6+rnoAWQgH4akkQBXdOR64BeFLA2iNmZNaRhwLwyPLHR4+efr3n65BJxqJhVLm3qzFrObN7wuc0Js6rj1GoPvahetjepWR04yYc8iUFp2s5QNJaNYcIXPbLCk+tDlJJXRNCEgWKYRCiEpSwiiRSfvVRTtQ0bwxRj3Dp3XrQkWhNrxUOrKfuThv2yQRpxwtdhQNt1xDoijyuSOKa1sDWuOLPWQ2uFWhw25sv6aiQPOC3QMFBEgfIaQ563hAfCgSQCtfcf3RaHpwsxzoB0i9eu/RhHkausECewGoVE2mKMoqladKAYJgGdFaq2I9OWOBKSSDPMYwKgrlvmdUfRGsrOec+rsnNOE/tyutthn5SGYSIEQcBS5kT3ZtOWKILUHOYtgwlgLdNEsatQ0LXwrrMDTgwyEBglmlGi2Z66lLSdouXEKKEfBcgoIVTOwDTGUFaWJDI0gUaHmqoxVJ0ljQKiTrl870BxrBfx0MoybQfv2OjxwtYMa100SxJqzu3M+dTFCcd6MZfGpZvwFTStYVYqZnVL3UGsQ6ZFiwVs1zFIQgaxJtOK7VkDKAzwjo0+v/qdx/nZ53fYnNR0puPEUsZSFnF6OUUHAdOyYXfWsNwLuTwu0EphrOXEMKE1hpOhYuug4vKkoao7Vy50BCoIOLWcsTupeOx4n0AUJ0YpgQihdqlwaahAYOtgzoX9mkBBUboS9FkY0Qu1C2OOw0U0kWVzWpNFAceHKXpxorQxSIijgEv7BRIoTg4TWgOt6dielmSxYmdqGMSW/bZmJYuoW+ecCk3AO08MeW57xrioiXTAUuaet5qGbE9qZmWLUsJjaz22JiXGwMYo4eHVHlvTahEz5YTBAxXwobNLjMv26gLk+DB1aYWTgjQKXVlSpclCzdMbMZ+5NGa/cH+zp5d7bE/nzKqGrQk8vKZ56viILNFc3C8w1tBaw+cuT6hNx9a4xGLpJZqtScWVccXxfsJXPLnOieUUpZRfELzJfM13/gifvYG22vXwUUcej8fz4BAqTfQWZwnFuKh8BFILJa+OHAoXX6Kdk6iz0DULmQntnEGdheVeRBwFrOQxlw7mdK1hr2wpa7d/Mp2rljZIA6xyEUDjomFaNwySgKU84R3rA5JIECV89uKYvXnFuHbZBFkUMC6cMHaoNWcGEZOi4fndGaeHCWu9hK1pwX4pLqMghIGGLI3oxZooUHStu36556o0n9stONaPWckj2r4rlPT48R51C4gl0s6pMq86RlnIej/lobWUNIyw1vDi3oT1YcqTJwbszxuujAuWs4iV5ZS6NTy6lrPWSwgX0T1HcRXdEoZ5yLhsmFXGHUaWNWkYsDkpKBuDAk4uZWwbyCJNvKzZmpdgBFENy5lmXgcsJSFbM8W0cULbIprTSykiipVedPWZRw8SYxWwMUq9xpDnLeOuO5BE5GuAv4Fzen+ftfa7rnlfFu9/HTAHvsVa+4t3tBMdtM1rN3s7cujoUThDsZAGekO52Yfi1ocRPeFhJMyR9+IQVnoJgXTM6440ijizknBxv6JoagKtybRgrMJiEVFMOxed03TGpZdFmqVjfbYOCnYmFRf3C6rOPTNSTli7ZhF1hPsDGiQBxwYJOgwIrEWLxphqEV3SocRdHwSQZjFZFDDKIrIoYJhGTOuW8zsFm1NXTSzWQtuGrGTCpd2S7XFFFmsXMRRqhlmMNYaiM2AsvVhjFqcAZ5czdACDLGJWtORZyCiN2Rgl9BPN5rimn2o6A7O6pmg6+onmwn6BNZbVfkIWCLtF45wpdUvbGo6PYqJAUdYdk6phrR+znEXslS39OOSp0wP2JhVlY3l0NWa5l3D5oGBpYWyP9WMuH1Ss5BFFLawPYtLIiW1bKzy00iPVwmevTBllEZ/e3GYQhxS15eRyzOcuT3j36SFLWcL7To1QSjiY13zm4oSybdmbNmSxZn2Y8OR6n61JSWcsxliyJGBSt3z+yhgdCKMsZtZ07MwaljKNAMcGLgwYQGqXb26NxRgwncXgSrC2xrA7bXji+IB6aDgoW6qmYzkN+fLHV1nKY4y11J3lfadGXJ6UiHURaVjLXtGw2o9oW8PuvKGfhDy23qdpOi5PKqyFURpBhqtSZ+H4wpk1SEKsO1Dj/H7BxiDmoKzBwua44t0nhxigl4Q8upbz4k7BtKyduLjWpFrTGcPurGFrWtEdlFw6KIlCxe60xlpBizAtO7amNTpQPHm8z8Yg5uxqzmPHeiilHpgFwT1hJ/Apax6Px3Mvcq/YCKWEJFGUd1lE+9pUsoCXo/EjnFD1IFF0naXsLLGBxrq9Trdok6YwjDVKuXZpHJLHTu9RK6hby1IvxBhFPwmZ1C1nwj570wpUxVR19DPNShKRRAF5GmLaDqsClvOIk0sZgzRiZRARiqIzhqYzbIwSytpQdQ1JAGu9lH7UYIEk0gSiiANFHitagV4Mz+8airomCgOOxwGDLGGYOe2gWd2SBBGPH+9xbJgyK1r2i4qH1npc3i8JlHC+nLMzqTDWEAQBvVgxrjp6aYhVwlMn+xzrp2xNXEXg9X7KO0+6KH4LxEo4uZRStU6IIRDF+uDG66880jy+1uf0MGVn3nD5YE4YwHIWs9KL+OS5faxYnrk05r1nRoznDVVr2BhmPH1Cc2lc8eL2FGOh6AynVjNWsphIK471YzaGGdZYtiYVO1JzfPjyuvkQrzHkeSu5qw4kEQmAvwV8NXAe+DkR+WFr7aePNPta4PHF14eBv7P4945hA+7LkpsBEAeuWsFqDnEUUtQN09JVMdC4U4nDENSb5TYfvhfgtIhC7cStQw2hEurWogNXljMMQCvF2iDCIvRaQx4HPLbWQwcB4yLiWD+kMZYrkxrbWdaHIWXTsT2pCMSgJOBYP6GXhszLjvlCM6doXORSawShJTIu5a3uXDpSP9KM0hClFMNUkUYxF/ZmnNt1YsYKiLSlagXbdfSThCzUxGFAFgZ0Fh5b72HFUjctF8YVK7GitkIUCp2Fp04M+OVLU1osp0YJDy3nfOLiPmA4PspIwoD9suHR9QGdsfRihQyFKAq4sl+SRYqiMXzJI8tcOKiomo5Z2dKLAppFxTZrYV51zK37eVYucsTLluN5ihJFTyvCMGB9kDDKI8ZFw5nlnFPLGZd0yKWDOc/tzKg7w+PrA44NUg6Kmmndsj5IePLEgEnZEgaKyweuAtukdCG/eax5eLWHWMOpgdMuIoJIa+LMsN6PWeolIOJSBOcN/VgzyjP6Uc1LewUreYgOFKt5QoAQRwH7s5rdWUUWanQQkITC5y5POD6IWcpjplXH5rjkzEqOMZYgcMby8rik6QxV65yAwSLyZrkfszerWB0kPLEe0YsDBknEqBdf/dudVS1xFPDIao+mM1zYL4i1C+uNtWJetawPFMOFeDqRRgWKjVF6VaC6s5amNWxOKszUXj3NCZRLt+xnERvD1DmorAUBhZDogLMrPaa1KzW7v+mccmHgRMyTUGGtZWtaMS5qnhz12StadqYVxlpWBzEHhXMgdRbefWaZp473Ob2Sk+jggVgQ3Ct24k//w1t3Hv2Rr8z5o1/90Tv5eI/H4/Fch3vFRoBLXzoxSNBBQBZ2FM3La+xb5TCFTPHyOr4zUCyi7iNcpWFwEUJ5rBARJmVHHEAaO51FsUIeKaaVYVY1NFY4KGpM5w5hB0nMSj+kn0YM49A5RxSoQDGIXQp/ohUHRUMWaXZmFSLCShbx3Law1rNsLOWcXkpBNEuZQomiaQ2ihCzUDPOQNFIcH6bUdcenLo2xVvHIeo+DomGUuNI3x0dDXtwuEbE0iwyDXhTw2HGX3r8x64jCAGUMVecqJ+eJ065cyiKWezGjPCJUAXFkWAsTEh3wrlNDplXLpf054ShFcIfUO5OKjz6xxqgXESJcmlTUrWGQaUZxSHcCHlpxxVB25yW/fFk4u5IjIgu9TyG8iRi1UnI1Auh4GLCUhhRtyxc2Z4zLlofXctYGKduTiqruOL2Ucawfs5qHhFoRXTxgGEcIllEe8vxWwaNrPawIj67kXJlWRFo5ndLOcPmg5Mxydt1oKC9x4HkruNsRSF8MPGutfQ5ARH4I+I3A0Un/NwJ/31prgZ8WkZGIbFhrL92pToTKaeVQ36k73j0OK5rNWxdRZBZfHS5kNQphvjBYATBMFQHCidWMrjGYLOLc7oy1XkyWxHStS08SaygaqDooFs4lrRbRPtrlGh86l0Z5glZCUbes5M5JtD2trm7sN4YJp5YSSqNo2pay7tgYJCABWgU8upZwfJQwntc0nWUlj0jDkIvjgsZYzi6l5GlI2xqMha9+5xpfuJLx+StjLu6XWANRJFR1QNVBFAjDNGRn1hDrgFQHPHZiyPogZnNccXwUk0Rjzu/MCALFai9Cq4Ddec0g0aSR5uveu0HVuLL3TrDOOTbEVhglSAf9JKLtINYBp1YylIKHV3psDBI2Rs6ahzpgUjTkiSvVvjOtUUrx8GqP5TyiPmboZwE704aNpZylXsKl/YKiaWmNK0dfdy5aZ6UfsjOuSCPFrBY0TsPoxErC+ijl4WMZCkUWBgyzkGc3Z6z1E6KF02OUR6xkEWXVMWs6sjggUBFhoDi55E4zitqglXBqOaPtLJaEs8s5CGRRwOVJST+N2JzUHOvHlHXHqeWM4UIAWimhajou7BUkkZsu8jRiqW6pGkNnYSmPFuLShkEaUTSGlV5E23WkYcK8blzU2MJp89LOnEnhQnUPT1UeWslZ68e8sDXlM5cnpJFCcCdCW9OKR1ZyhlnM8UHi9Ig686q8b6UEtVAQ1IG6+q8o99mahZZQuxCpfoWDxsCFSeXS04LgqsE+NXLC3MZYjvVdpFfTWqx1aXBaKx5e6wG4hdi0YXWQcHyUItai1OIUS4S1Xny1kkccKJRShAEsZRFnV3KCQPH0Rp80Ch8Y59GCe8JO/OAnb62djzryeDyeN5V7wkaA27A/tTHkzHKPywczkqrjoLQcJjnEuHX1IBXKxh18thbyyB3ABgIoRT9WBEohCvIwopcGjIuGom0pK8soi6gMDNOA5SzikbUeL+7OyWJFUxusKKyFd57o88LWjI9fGKO1MMpDNEIvDlgdJhzrJZwaZTy7PQNrWBm4NaDLBFBY4D1nYl7amZHFAbWxHBu4FP+DoiGNA9bymF/51Dp5qPnYuT22p05304rQtJZ+EvDQslsH7cxqnt+eMUpDlvMYYyCLhUdWe2RhxLn9OeNZzclRysPHegwSd3D8zhNDtmc1a72I83sFk7q9umZa6cXOaSVOR9QinF3JqFpL3RqshWEW0xrLiUFCYwwvbs9ZymNODFP25g2DpEMpYS2PyZOQJ08MeXZzSlU6se8vfXSVYRYR6wBjLU1nX1M+4NoIIGMsaaTZmpbkUcjmuATl7rXaj4nCgIfW+jRtx6W84uFjIU3r5DCsKLIoIA41omA5i66uuXWgqNrW62F67inutgPpJHDuyM/nefWJwPXanAReMemLyO8Dfh/AmTNnbqsTYRDw3rMrnP/0zm1ddzscplhtDJyiStlaVnsxKoDdaUNTGcYNVEeqhXU4h9EogV6sGCaunMFKHnFut6QzBgt0xoB1osMKKDuDFudsOLOcMW0s790YcFB3xKI4uZxyailHa3fK0HWG//C5LS7szljWmlRbKiskWjAWsjji5DCmF2s+e3nMyaWMtV5CIJaX9mq0GM6u9kgCRZ4q2k5YGyRosSRRRGc7NoYJdesEjvfmLUVjWBukPLo+oGk7zu+WBAiPr/f5yCMr5LFmd17x+FqP5TzhoeU+cah5eKXipZ05cRJQlR1hKAiu6sWTgfDUiQFPnxgyqw2b44px0XGsH1E3lkGsWe3HDLOI/XnDRwYhJ0c9HlnNSSPN8zszRLkFQBwGPLTqnCpBAPPSRYz00pDlXkQehRhryRJNbeB9Z5YJA0XddTx7ZcZKPyRWAZOmJVWKMArQSiGxsJwn7M876qYjizSnlzL6iebSfsmLO1M66xx2vSQkDwNC7cSW52XLlzy2wjCJGaSah9d6rA8SUh1gBc6s5Hz64pi9WU0ea86spBzMW/qpK985qVratuP4Wp8zy+73f3yYcPmgdNEuvRgEGuMibB5e7ZFFmpU04udf3KPrLINM8/TxPlEQXM39FutSvMq6JYm0+zfUPLLaQwLhxDDlhe0pn7hwgFbQT3scy2PiOGA1jwh1SXTo0FHCqaWUE6P0FbnlSgn9JOSpjSFx6KrJxTqgMYazi6irw/bHldww7zsQV13tqINJKxfltDmpbpgr3lmLsRYdOOfcocG2wis+w7W+q0aXL0S+wS0i3nF8wEMrOWeWMw6KhiBQbB5UjDJNGmpEaqJQOLWUsZxHXBlXdNaVY33q+ICdeYMxliTUD0za2hHuCTtxK+kI3nnk8Xg8bzp3zEbAG7MTAOv9jN/0wZP8209f5vJ+RT+tyWJNPwooWycyfbh+iQLlnAdBgLWGaVGjtCbTAevDhHN7M0QUa72EXqrBWHZnTvKg6yxWCeu9mCQK+cDZFU4vu/VT03RcOKjJtGJ1mGLBReeEQhpp+pkmCUNOLycMkpiTqymX9iue2ugzKTsnwqwEHThH1PFhxijV7BU146IlW6z1hlnIsV7Cat/pAX3Rwys8vz1le1ojwEovcmvJ2G0nP/zwKlVrOb87o8NirXB6Kefk4uvJqs9nL084uZQyrztW8oitCSythLTWVetd6yV89UMjHlvrEwWKc7tzLh6U7M9rRqnm2CAh1gFXJhU6gPVBwifPH7A3q0GBsuIEqBGyhYbSKAs5M8qQ4OUDx9U8pjaGSClaa7l8UFI03W3pCR2NAFJKeHilx96soW2dI+7MUsp+0YGFprOcXclRFrZnNVkYEASKS/sFy1nM+iBhuReThQHtQhZCBeIFsj33JHfbgXS9v/Zrs6hupQ3W2u8FvhfgQx/60G3Vz+zHIR957BiVsfy7z+7eMI1L83LlgRgYpnB6rU+I4eJBRdl21J11IadaUdQGAzx+LCMKQ44PY546MWSUxuRJQNvCzrxic7/kYy/tcmm/olOG9V5CZ51mz3qu6fcSzoxSys6y2kuYVg2PHrN8YXPCyiAm15pv+MAJ+mnIM+cPmLcdFw8q1nsh1joh48v7JSfSkLI1fPCRDZ46PmTUi1hKXNrO17zrBD/17DYXDgoQIY0ClrOQc7sFs7IhjjTLWcQ7Ty/TjzRJEqCs8BFl+cRL+4yLjkgrTi0lqEDxvpNDsjTEdpZ52zknme5IIs1jvRgdKN65MUCUQgSKouHcwRytA+rGUtSGjX7GO08skYQB3Yrl8fU+5/fmzKuG3aIhDTTn9udUbUuoAp46MaAXh/QSzbFFmO0gdhv5LNIcG7pIjzBQfPiRFU4v50xKVyujs/CeUyOuHJRsTiqiIODYIOXsco8Xd2fEWigayyjT5FHI6rGIM8v51RDWcOEA6azl0dX+Vb2dZWtdnvK0Rug4PkwBODaI6SxXhZgfXx/w6FqfjVHC1sSFCR/rx2yMUnZnNZOi5qBoWVkYj2PD5BVOCoDlPOYjD69cNXhKCbO65fyei8Ra6Qyrw5hHV/tXjfm1JySHYzg0oBujFBHhI4+ssDkuWRvG5IsyoofP1lrxrpNDnrlwwKyuCJTwrpNDoii4+tk8uTHk5FLGlXFJYwx7s4ZBHBKogPecGrE/b65+FhujlPiaXO6r/w9qxZmV3DmIFkbz5PIr298s71spuerwOeosSsKAM2Fww1zx6zmeDg12GKrXzDNXSkhjzRPHh1zaL2g6w3IaIUqoupdLr1atIQ41H3oop7OW7UmFBU5E+lWOqQeIe8JO/NnfdIK/+E8vXve93/elij/zG772dm7n8Xg8njvDHbMR8MbsBLh1yte++yTHBglb45LJorLrpG5YySKOj1I2pxXnduau9LyFtX7CE8ddyXURmBSuGtl7Ti/TSzTzyq1VjbW0HewXFYM05OxyxsYoI9UBrbXszFwqRRqGPLY+dPqNwJc+vMonLuxjrCUNNE+eHBCI8OlLYw6KhlBpvuady/TTELFQtE5SwhiLFTgxTFFKnHNoMqYzLev9mPVhclVSACCLNU9tDGk6d9xyrch0Lw356DuO8dLujLYzxDrg+CglX0TTNJ1hKY8JlWCAzXFJHrlKZV/y6CrBYo14VXIAeGqhX2mMRSm5uh4/udyyNXE16B5d63EpKtmbNYjA+8+M6MchRe0cQqeWMqJr1p1aKzSLw024I3pCWaz5wJklLu4XIE7u49FjMaFWr7jv+04v8cyFA7qmZZhGfPiRFZbSCCtuPVovouC9QLbnXkVctOddurnIlwDfaa39NYuf/zSAtfYvH2nzPcCPW2t/cPHz54CP3izs9EMf+pD9+Z//+dvqy+WDgv/8+S0+d3mXn/vCDp1p6GzIQ8sZD6/nmNYShsKsNKwupSRa0XQLzZsgINFCh3VOpNrSGEPbWdbziDSNGESajaWMUL+cGtN0xun+TCsOyorN/Yqq64iCAIPlybU+eRayPa2ulhtTCI0xbE0rRqlGi+Kh1R6j3KVQta2hNgZlXAlNjVAZw8X9OVXdEUUBJ0fZdTeibWuY185IJYuolnnVcmlc0HaGSAecWc6JAvUKJ8VBUXNhdw7iSqWv9mLGZetSghYTmzGWiwcFZd2yO21Y6UfkccjxYeIqKCw0Zq6My4XOjZvQDx0dhxyWvxQLVsB2lnpRCj4Og6uT6uGzj/XjqwZULK9oq5Rcvd/hxG2MvWr4ApGrz2ixaNzP8GqjeC1H7wtO5O/QkB1+JofjPmo0jj7/8BnXjvl2jdf17nk73OrzD//2IqXQN8gNv9G9rv093GqfXq8hfz3Xl033ir+t64kW3u6zgRs6715vP18LEfkFa+2H7sjN3gTuJTvxpX/pR7g4fuVrPurI4/Hcb7yd7MTdshHw+uzEIYdrosO1Y9l07M7qq9WDl/MILbKINlavWMO2xoCFE6OUJAxesS7trH2Fs+To2uBma4brrdFutm673r2MsUzKhivjkkCEIFCvay10s34eXWsBrPXjq5H2r2f9ezSFrGy7q3sAePWa683iVtZ2r7WmvhvrQ4/ndriZnbjbDiQNfB74SuAC8HPAb7PWfupIm18LfDuucsKHgb9prf3im9339U74dd1RdB3SWaZNC1iyKKQXhxhjKTqXAibByw6JFnvVkXJ0kjrqYHmt/8GvneCunTCut+G8XWfCG5lobuXa6zlibrQZvlnf78SEeK9Oqvdqvzy3zv3wO3w7bQzg3rMT3/+zH+Nnnpny4Xf1+N1f/P7bvt7j8Xjudd5OduJu2Qh4Yw6k6/F61tP3Ine7j2+Hz8DjedC5mZ24qyls1tpWRL4d+FGc7M/3W2s/JSLftnj/u4F/iZvwn8WV3vzWu9WfKAqIcF7pAfGr3+fVHvboyPdH81wPwx6Pvn4jrs2RPXrtte/fyv1e6xl349pX9fE617ye+7we7tWqA/dqvzy3jv8dvvnca3bid3/x+/ndr7nt8Hg8Hs+bwb1mI27Gm7UOvtvc7T6+HT4Dj8dzY+62BhLW2n+Jm9iPvvbdR763wB+82/3weDwez72JtxMej8fjuRHeRng8Hs+9w/WFTDwej8fj8Xg8Ho/H4/F4PJ4F3oHk8Xg8Ho/H4/F4PB6Px+O5Kd6B5PF4PB6Px+PxeDwej8fjuSnegeTxeDwej8fj8Xg8Ho/H47kp3oHk8Xg8Ho/H4/F4PB6Px+O5KeIKF7y9EJEt4MXXefkqsH0Hu3Ov8yCN90EaK/jx3s+8kbGetdau3cnOvB3xduK2eJDG+yCNFfx472e8nXiDvAE78SD9nYEf7/2OH+/9zesd7w3txNvSgfRGEJGft9Z+6K3ux5vFgzTeB2ms4Md7P/MgjfVe5EH7/B+k8T5IYwU/3vuZB2ms9xoP2mfvx3t/48d7f3M3xutT2Dwej8fj8Xg8Ho/H4/F4PDfFO5A8Ho/H4/F4PB6Px+PxeDw35UF0IH3vW92BN5kHabwP0ljBj/d+5kEa673Ig/b5P0jjfZDGCn689zMP0ljvNR60z96P9/7Gj/f+5o6P94HTQPJ4PB6Px+PxeDwej8fj8dweD2IEksfj8Xg8Ho/H4/F4PB6P5zbwDiSPx+PxeDwej8fj8Xg8Hs9NuS8dSCLyNSLyORF5VkS+4zrvi4j8zcX7nxCRD7wV/bxT3MJ4f/tinJ8QkZ8Ukfe+Ff28U7zWeI+0+yIR6UTkG9/M/t1pbmW8IvJREfklEfmUiPzEm93HO8Ut/C0PReSfi8jHF2P91rein3cKEfl+EdkUkWdu8P59NVfdazxItsLbiRu283bibcaDZCe8jXhreZBsBHg7cZN23k68zXiQ7AS8BbbCWntffQEB8AXgESACPg48fU2brwP+FSDAR4Cfeav7fZfH+6XA0uL7r73fx3uk3b8H/iXwjW91v+/y73cEfBo4s/j52Fvd77s41j8D/JXF92vALhC91X1/A2P+r4APAM/c4P37Zq66174eJFvh7YS3E95OvD3thLcRb+ln/8DYiNsYr7cT90Df7+Lv19uJe6D/r3PMb6qtuB8jkL4YeNZa+5y1tgZ+CPiN17T5jcDft46fBkYisvFmd/QO8Zrjtdb+pLV2b/HjTwOn3uQ+3klu5fcL8IeAfwJsvpmduwvcynh/G/BPrbUvAVhr365jvpWxWqAvIgL0cBN+++Z2885hrf2PuDHciPtprrrXeJBshbcT3k54O/E2xNuIt5QHyUaAtxPeTng78ba0E/Dm24r70YF0Ejh35Ofzi9dut83bhdsdy+/BeSDfrrzmeEXkJPANwHe/if26W9zK7/cJYElEflxEfkFEfueb1rs7y62M9X8FngIuAp8E/oi11rw53XtLuJ/mqnuNB8lWeDvh7YS3E/cn98scdS/yINkI8HbC2wlvJ+5XOwF3eK7Sb7g79x5yndfs62jzduGWxyIivxI34X/ZXe3R3eVWxvv/Bf6UtbZzjuW3NbcyXg18EPhKIAV+SkR+2lr7+bvduTvMrYz11wC/BPwq4FHg34jIf7LWju9y394q7qe56l7jQbIV3k54O+HtxP1pJ+6XOepe5EGyEeDtBHg74e3E/Wkn4A7PVfejA+k8cPrIz6dw3sXbbfN24ZbGIiLvAb4P+Fpr7c6b1Le7wa2M90PADy0m+1Xg60Sktdb+329KD+8st/r3vG2tnQEzEfmPwHuBt9uEfytj/Vbgu6xL6H1WRJ4HngR+9s3p4pvO/TRX3Ws8SLbC2wlvJ7yduD/txP0yR92LPEg2Aryd8HbC24n71U7AHZ6r7scUtp8DHheRh0UkAr4Z+OFr2vww8DsXiuQfAQ6stZfe7I7eIV5zvCJyBvinwO94G3qRr+U1x2utfdha+5C19iHgHwP/7dt0sodb+3v+f4AvFxEtIhnwYeAzb3I/7wS3MtaXcCcjiMg68A7guTe1l28u99Ncda/xINkKbye8nfB24v7kfpmj7kUeJBsB3k54O+HtxP1qJ+AOz1X3XQSStbYVkW8HfhSnwv791tpPici3Ld7/bpyS/tcBzwJznBfybcktjvfPAyvA31540Vtr7Yfeqj6/EW5xvPcNtzJea+1nRORfA58ADPB91trrlnG8l7nF3+3/CPyAiHwSF475p6y1229Zp98gIvKDwEeBVRE5D/wPQAj331x1r/Eg2QpvJ7yd8Hbi7WknvI1463iQbAR4O4G3E95OvE3tBLz5tkJc5JbH4/F4PB6Px+PxeDwej8dzfe7HFDaPx+PxeDwej8fj8Xg8Hs8dxDuQPB6Px+PxeDwej8fj8Xg8N8U7kDwej8fj8Xg8Ho/H4/F4PDfFO5A8Ho/H4/F4PB6Px+PxeDw3xTuQPB6Px+PxeDwej8fj8Xg8N8U7kDwej8fj8Xg8Ho/H4/F4PDfFO5A8dxUR+aiI/Is7eL+HROSZW2jz297AM75FRE683utf497fJiK/8ybvf6eI/PG78ey3GhH5ehF5+q3uh8fjuX8Qkf9eRD4lIp8QkV8SkX8lIn/5mjbvE5HPLL5/QURWr3OflcX1vyQil0XkwpGfn3gtu/NmICLfLiLPioi93hje4L1HIvLf3sl7ejwezxtFRI6LyA+JyBdE5NMi8i9F5Ik3eM8fEJFvvM7rHxKRv/lG7n3kXt8iIv/r4vvvPGJTPi0iv/VIu78oIl/1Ovr660TkYyLy8cU9f/+d6Pfd5G7urzxvLt6B5LkfeQh43Q4k4FuA25rgRCS4hTbaWvvd1tq//3o7dje5lTG8Qb4e8A4kj8dzRxCRLwF+HfABa+17gK8Cvgv4pmuafjPwf9zsXtbaHWvt+6y17wO+G/jrR36u73TfXyf/BTfGF+/CvUeAdyB5PJ57BhER4J8BP26tfdRa+zTwZ4D1u/E8a+3PW2v/8N24NwubAvxG4HtEJFw8889ba//t7dxoce33Ar/eWvte4P3Aj7+RzonjbvsFvoXb3F957k28A8nzCkQkF5EfWXi0nxGRb1qc2P4lEfkpEfl5EfmAiPzo4jTg2xbXiYj81cU1nxSRaxfwiMgXLbzlj4jIB0XkJ0TkFxb32rhJnz646M9PAX/wyOvB4pk/tzh9PvS+fxfw5QtP/x+9STtE5E8u+vtxEfmuhZf/Q8A/XFyfishXLvr9SRH5fhGJF9e+ICJ/XkT+M/BbbtD3H198dj8B/BE5EmEkIn94cWrwCRH5oetc+3vFnaanN7j3q64XkZ6I/N1FXz8hIr958fpvXbz2jIj8lSP3mC5OP34G+BIR+a9F5GcXY/+emzmVbnbPI99/4+L05EuB3wD81cW9H73RfT0ej+cW2QC2rbUVgLV221r7E8C+iHz4SLv/F/CqOfY2CUTkfxMX7fRjh/OyiDwqIv96Ycv+k4g8uXj9B0Tk74jIfxCR50TkKxb24zMi8gOHNxWRX72wrb8oIv9IRHo36oC19mPW2hdupbMisiwi//fCDvy0iLxn8forolwX8/dDOLv56GJ+/quv4/PxeDyeO82vBBpr7XcfvmCt/SXgP19vzyEu6+EnROT/EpHPL9b1v32xrv3kNWvPr1rM2Z8XkV935Pp/sfj+Oxdz9o8v5vCrjqUbrZVF5FsX9/sJ4Fdcb0DW2l8G5sDS4pqrEUaL/h6u6//atdeKyP+4sB99QAM7i3tW1trPLdqsi8g/E7ev+fhi/Y2I/LHF5/WMiPx3i9ceWtikvw38InBaRP6EvLxf+gs3++Xc5J7PHGnzxxef5av2Vze7t+fexjuQPNfyNcBFa+17rbXvAv714vVz1tovAf4T8APANwIfAf7i4v3fBLwPeC/uhPSvyhGn0GIC+26c5/0c8P8DvtFa+0Hg+4H/+SZ9+rvAH148/yi/Bziw1n4R8EXA7xWRh4HvAP7T4vT4r9+onYh8LS4q5sMLD/7/Yq39x8DPA799cVJgF+P9Jmvtu3ET9h840ofSWvtl1tqbbU5G1tqvsNb+v695/TuA9y9Ozr/t6Bsi8u3Arwe+3lpb3OC+17v+zy3G+u7F6/9eXLjoXwF+Fe539EUi8vWL9jnwjLX2wzhD9E3Ar1iMvQN++/Ue/Br3fBXW2p8Efhj4E4vfyxdu1Nbj8XhukR/DLXg/LyJ/W0S+YvH6D+KijhCRjwA7i0X7G+Fx4G9Za98J7AO/efH69wJ/aGHL/jjwt49cs4SbI/8o8M+Bvw68E3i3uLS6VeDPAl9lrf0Azvb8sTfYz0P+AvCxhR34M8BrRb5+B/CFxfz8J+5QHzwej+eN8C7gF67z+s32HO8F/gjwbuB3AE9Ya78Y+D7gDx25x0PAVwC/FvhuEUmu85wngV8DfDHwP4hIKCJPcZ218uL5fwHnOPpqbhBxLyIfAH7ZWrt5zevLwDcA71zM2//TNe//L8Ax4Futtbu4NfWLIvKDCyfZ4Z7+bwI/sdjXfAD4lIh8EPhW4MO4vdvvFZH3L9q/A/j71tr3L75/fDHe9wEfFJH/6gbjuNk9X8W1+6ub7G08bwO8A8lzLZ/EeeX/ioh8ubX2YPH6Dx95/2estRNr7RZQisgI+DLgB621nbX2CvATOGcNwFO8HGr5Em6Cehfwb0Tkl3AL6FPX64yIDHEOmJ9YvPQPjrz9q4HfubjHzwAruInvWm7U7quAv2utnQMsJuRreQfwvLX284uf/x5wdDL9P6/X72u4UZtP4Dzx/zXQHnn9dwBfC/zmw5P127j+q4C/ddjAWruH+z38uLV2y1rbAv/wyBg64J8svv9K4IPAzy0+q68EHrnBs292T4/H47nrWGunuDnr9wFbwP8pIt+Cizb6xsWC+ptxDqU3yvOLk29wG5qHFtFCXwr8o8Wc+T24qKhD/rm11uLs5hVr7SettQb4FG7z8hHcJuO/LK7/XcDZO9BXcDb5HwBYa/89sLKwpx6Px/N252Z7jp+z1l5arJ+/gDtoADcPP3TkHv+XtdYsDheewzmLruVHFtE928AmLnXuRmvlD/Pyurjm1Wv/Pyoin8PtQ77zOs8aAyXwfSLym3BRSof8Odxe6PcvbArW2v9m8eyfxR1efP+i7a8C/s6iTbfYx30Z8M+stbOF3fynwJcv2r9orf3pxfe/evH1MVxE0pNcf1/Fa9zTc5+j3+oOeO4trLWfX3iVvw74yyJyOPEeOjLMke8Pf9aA3OS2l4AEl6N7cdH2U9eJKLoegosCutF7f8ha+6OveFHko7fY7mtucu+j196M2Wu8f7M2vxbndPkNwJ8TkXcuXn8G5/k/BTx/k/te7/rrfV43G0Npre2OtPt71to/fZP2t3LPo8+/3omOx+Px3BEW89ePAz8uIp8Efpe19gdE5AXc6fJvBm7F1rwWR+1eB6S4Q7j9xSn0za65kd3sgH9jrf2t1154B7jeHG1xhw1HDw/9HO3xeO5VPoXLeLiWm61Br51rj87DR/e9166Vr7cfuHbeP9zvvGqtvIjCv9me4q9ba//awjn090XkUWttefXh1rYi8sU4p9A3A9+OcwYB/BwuGmj56GG3tfaTwCdF5B/g9gvfcoNn3+zzOrpHEeAvW2u/5ybtX+ue3sY8APgIJM8rWKQmza21/zvw13Dhj7fCfwS+SZze0BrOsfGzi/f2cc6Ov7Rw7nwOWBMngMoiJPSdr7ojYK3dBw5E5MsWLx1NqfpR4A/IQohOXKWcHJjg8oNfq92PAb9bRLLF68uL9kev/yzupPmxxc+/A3fS8YZYnIyfttb+B+BP4gRMD7UvPgb8fuCH5QbVCm5y/Y/hjM5huyXcacdXiMiquDzt33qDMfw73Kn9scW1yyJyo9Pwm93ziog8tejjNxy55trfi8fj8bxuROQdInL0dPR9vCww/YO4lLEvWGvP343nW2vHwPMi8lsW/RERee9t3OKngV9xaF9EJJM3WF3oCP+Rhb1c2N3tRX9fYGHXF6kUDy/a+/nZ4/Hca/x7IBaR33v4goh8EbDHjfcct8pvERElThfpEdze5Fa40Vr5Z4CPiqvoGXIDbVRr7T/FpXL9rqOvLyJah9bafwn8dzh7dsi/xunU/YiI9MXpnX70yPvv42Xb9+9YSG0sPp8Bzh58/cLG5Li1+X+6Tvd+FLcv6i2uP3k4zutwo3teAY4tPocYV+jiEG9n7hO8A8lzLe8GfnYRlvnfc00O7k34Z7iUqo/jJvw/aa29fPjmIsT01+PSq96PO1H4KyLyceCXcGkAN+Jbgb8lTkT7aM7s9wGfBn5RnGDb9+BOBz4BtOLE4/7ojdpZa/81LjXv5xfjPRQW/QFcPvQv4Tzs34pLUfgk7gTjqpjfGyAA/vfFPT+GO5nYP3zTWvufF/35Ebl+ueYbXf8/AUviBO0+DvxKa+0l4E8D/wH3+/lFa+3/c+0NrbWfxqUT/piIfAL4N7wyHeNo25vd8zuAf4H7O7h05LIfAv6EOEFyL6Lt8XjeKD3g78lCdBSXDvadi/f+EU5v6I2KZ78Wvx34PYv59lM4nb9bYpEG/i3ADy76/9NcP40CuFo44TwuOvUTIvJ9N7n9dwIfWtz3u3h5s/JPgOWFffsDwOcXfdnBpdI9I15E2+Px3AMs0rW+AfhqcYV7PoWb2/4PbrLnuEU+hzv4/FfAtx2NBnqNPl13rbxYF38n8FPAv8WlgN2Ivwj8MXll1bM+8C8W9/wJnHbe0ef+I+B/w+1bBPiTIvK5xVz+F3g5+uiPAL9ysT/4BZym0i/i9jY/i3N0fZ+19mPXGduP4T7bn1pc/4+5gcPnRve01jaL8f0Mbi/w2SOX/QCL/ZV4Ee23NbJIpfR4PB6Px+PxeDwej8fj8Xiui49A8ng8Ho/H4/F4PB6Px+Px3BQvou25ZxCRv4Urf3mUv2Gt/btvRX9uh7vZ97f6cxGRnwHia17+HQvxPo/H43lbISIrOJ2Ia/nKRSrXW4qI/DNe1iY65E9dWwhi0fZbcSkLR/kv1to/eLf65/F4PJ4Hg3vdXnreGnwKm8fj8Xg8Ho/H4/F4PB6P56b4FDaPx+PxeDwej8fj8Xg8Hs9N8Q4kj8fj8Xg8Ho/H4/F4PB7PTfEOJI/H4/F4PB6Px+PxeDwez03xDiSPx+PxeDwej8fj8Xg8Hs9N+f8DvMfatSDUWtsAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1440x720 with 6 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "tract = out_tract.merge(after_tract, how = 'left', left_on = 'GEOID', right_on = 'GEOID', suffixes = ('_out', '_after'))\n",
+    "fig, ax = plt.subplots(ncols=3, nrows = 2, figsize=(20,10))\n",
+    "axe = ax.ravel()\n",
+    "scores = ['fire_propensity_risk_score', 'fire_severity_risk_score', 'fire_risk_score', \n",
+    "        'smoke_detector_risk_score', 'SVI_Theme_1', 'CombinedRiskScore',]\n",
+    "c = 0\n",
+    "for i in range(len(scores)):\n",
+    "    tract.plot.scatter(x = scores[i]+'_out', y = scores[i]+'_after', ax=axe[c], alpha = 0.1)\n",
+    "    c += 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ed8329d8",
+   "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": "3.10.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Data/geo_levels.csv b/Data/geo_levels.csv
new file mode 100644
index 0000000..8716a44
--- /dev/null
+++ b/Data/geo_levels.csv
@@ -0,0 +1,107 @@
+Column1,Column2,Column3,Column4
+variable_name,operator,argument1,argument2
+tot_population,sum,tot_population,
+in_poverty,sum,in_poverty,
+inc_pct_poverty,pct,tot_population,
+inc_pcincome,div,tot_population,
+race_pct_white,pct,tot_population,
+race_pct_whitenh,pct,tot_population,
+race_pct_nonwhite,pct,tot_population,
+race_pct_nonwhitenh,pct,tot_population,
+race_pct_black,pct,tot_population,
+race_pct_amind,pct,tot_population,
+race_pct_asian,pct,tot_population,
+race_pct_napi,pct,tot_population,
+race_pct_other,pct,tot_population,
+race_pct_two+,pct,tot_population,
+race_pct_hisp,pct,tot_population,
+denom_age,sum,denom_age,B01001_001
+age_under25_ma,sum,age_under25_ma,
+age_25_64_ma,sum,age_25_64_ma,
+age_over65_ma,sum,age_over65_ma,
+age_under25_fe,sum,age_under25_fe,
+age_25_64_fe,sum,age_25_64_fe,
+age_over65_fe,sum,age_over65_fe,
+age_pct_under25,pct,tot_population,
+age_pct_25_64,pct,tot_population,
+age_pct_over65,pct,tot_population,
+educ_tot_pop,sum,educ_tot_pop,B15002_001
+educ_no_school,pct,educ_tot_pop,
+educ_less_12th,pct,educ_tot_pop,
+educ_high_school,pct,educ_tot_pop,
+educ_associates,pct,educ_tot_pop,
+educ_bachelors,pct,educ_tot_pop,
+educ_masters,pct,educ_tot_pop,
+educ_professional,pct,educ_tot_pop,
+educ_docterate,pct,educ_tot_pop,
+total_pop_16_plus,sum,total_pop_16_plus,B23027_001
+worked_past_12_mo_sum,sum,worked_past_12_mo_sum,
+worked_past_12_mo,pct,total_pop_16_plus,
+did_not_work_past_12_mo_sum,sum,did_not_work_past_12_mo_sum,
+did_not_work_past_12_mo,pct,total_pop_16_plus,
+house_tot_occ_cnt,sum,house_tot_occ_cnt,
+house_pct_family,pct,house_tot_occ_cnt,
+house_pct_family_married,pct,house_tot_occ_cnt,
+house_pct_family_male_hh,pct,house_tot_occ_cnt,
+house_pct_family_female_hh,pct,house_tot_occ_cnt,
+house_pct_non_family,pct,house_tot_occ_cnt,
+house_pct_live_alone,pct,house_tot_occ_cnt,
+house_pct_no_live_alone,pct,house_tot_occ_cnt,
+total_housing_units,sum,total_housing_units,B25002_001
+house_pct_occupied,pct,total_housing_units,
+house_pct_vacant,pct,total_housing_units,
+house_pct_ownd_occupied,pct,total_housing_units,
+house_pct_rent_occupied,pct,total_housing_units,
+denom_house_room,sum,denom_house_room,B25017_001
+house_pct_1_room,pct,denom_house_room,
+house_pct_2_room,pct,denom_house_room,
+house_pct_3_room,pct,denom_house_room,
+house_pct_4_room,pct,denom_house_room,
+house_pct_5_room,pct,denom_house_room,
+house_pct_6_room,pct,denom_house_room,
+house_pct_7_room,pct,denom_house_room,
+house_pct_8_room,pct,denom_house_room,
+house_pct_9_plus_room,pct,denom_house_room,
+denom_house_yr,sum,denom_house_year,
+house_yr_pct_before_1960,pct,denom_house_yr,
+house_yr_pct_1960_2000,pct,denom_house_yr,
+house_yr_pct_after_2000,pct,denom_house_yr,
+denom_heat,sum,denom_heat,
+heat_pct_utility_gas,pct,denom_heat,
+heat_pct_bottled_tank_lpgas,pct,denom_heat,
+heat_pct_electricity,pct,denom_heat,
+heat_pct_fueloil_kerosene,pct,denom_heat,
+heat_pct_coal,pct,denom_heat,
+heat_pct_wood,pct,denom_heat,
+heat_pct_solar,pct,denom_heat,
+heat_pct_other,pct,denom_heat,
+heat_pct_no_fuel,pct,denom_heat,
+pct_alt_heat,pct,denom_heat,
+denom_plumb,sum,denom_plumb,B25047_001
+house_pct_complete_plumb,pct,denom_plumb,
+house_pct_incomplete_plumb,pct,denom_plumb,
+denom_kitch,sum,denom_kitch,B25051_001
+house_pct_complete_kitchen,pct,denom_kitch,
+house_pct_incomplete_kitchen,pct,denom_kitch,
+house_tot_owned,sum,house_tot_owned,B25075_001
+house_val_less_50K,pct,house_tot_owned,
+house_val_50_100K,pct,house_tot_owned,
+house_val_100K_300K,pct,house_tot_owned,
+house_val_300K_500K,pct,house_tot_owned,
+house_val_more_500K,pct,house_tot_owned,
+denom_house_mort,sum,denom_house_mort,
+house_tot_w_mort,pct,denom_house_mort,
+house_w_1_mort,pct,denom_house_mort,
+house_w_2_mort,pct,denom_house_mort,
+house_w_home_equity_loan,pct,denom_house_mort,
+house_w_both_2_mort_and_loan,pct,denom_house_mort,
+house_no_mort,pct,denom_house_mort,
+disability_pct,pct,tot_population,
+snap_past_12_mo,pct,tot_population,
+median_year_built,div,tot_population,
+single_unit_home,pct,total_housing_units,
+multi_unit_home,pct,total_housing_units,
+mobile_home,pct,total_housing_units,
+boat_van_rv_home,pct,total_housing_units,
+spanish_speaking,pct,tot_population,
+race_pct_black_or_amind,pct,tot_population,
diff --git a/PostModelingChangingLevel.ipynb b/PostModelingChangingLevel.ipynb
new file mode 100644
index 0000000..e863723
--- /dev/null
+++ b/PostModelingChangingLevel.ipynb
@@ -0,0 +1,1556 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "912ea9ac",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import warnings\n",
+    "\n",
+    "from src import utils\n",
+    "\n",
+    "import pandas as pd\n",
+    "from matplotlib import pyplot as plt\n",
+    "from pathlib import Path\n",
+    "from datetime import date, datetime\n",
+    "import numpy as np\n",
+    "#import geopandas as geo\n",
+    "import subprocess\n",
+    "\n",
+    "from IPython.display import display, Markdown"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "7405fd76",
+   "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>GEOID</th>\n",
+       "      <th>state</th>\n",
+       "      <th>NFIRS_start</th>\n",
+       "      <th>NFIRS_end</th>\n",
+       "      <th>years_fires_reported</th>\n",
+       "      <th>total_fires_reported</th>\n",
+       "      <th>max_fires_1k</th>\n",
+       "      <th>median_fires_1k</th>\n",
+       "      <th>total_fires_reported_sev</th>\n",
+       "      <th>max_fires_1k_sev</th>\n",
+       "      <th>...</th>\n",
+       "      <th>snap_past_12_mo</th>\n",
+       "      <th>single_unit_home</th>\n",
+       "      <th>multi_unit_home</th>\n",
+       "      <th>mobile_home</th>\n",
+       "      <th>boat_van_rv_home</th>\n",
+       "      <th>spanish_speaking</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>state_rank</th>\n",
+       "      <th>county_id</th>\n",
+       "      <th>county_rank</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>#_010010201001</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.342282</td>\n",
+       "      <td>1.342282</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.342282</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.183099</td>\n",
+       "      <td>0.820423</td>\n",
+       "      <td>0.024648</td>\n",
+       "      <td>0.154930</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.102113</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>2806.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>#_010010201002</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>4</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>1.581028</td>\n",
+       "      <td>1.185771</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.790514</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.096491</td>\n",
+       "      <td>0.925054</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.074946</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.046053</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>3159.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>29.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>#_010010202001</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>3.141361</td>\n",
+       "      <td>1.047120</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.047120</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.303109</td>\n",
+       "      <td>0.768844</td>\n",
+       "      <td>0.201005</td>\n",
+       "      <td>0.030151</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>1587.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>12.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>#_010010202002</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>3.777148</td>\n",
+       "      <td>0.944287</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.888574</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.172566</td>\n",
+       "      <td>0.821138</td>\n",
+       "      <td>0.168699</td>\n",
+       "      <td>0.010163</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.011062</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>2357.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>#_010010203001</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>1.269036</td>\n",
+       "      <td>0.634518</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.423012</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.082524</td>\n",
+       "      <td>0.995112</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.004888</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.037621</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>2313.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>18.0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>216022</th>\n",
+       "      <td>#_560459511001</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.372684</td>\n",
+       "      <td>1.372684</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.372684</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.054252</td>\n",
+       "      <td>0.711035</td>\n",
+       "      <td>0.053470</td>\n",
+       "      <td>0.228669</td>\n",
+       "      <td>0.006826</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>216023</th>\n",
+       "      <td>#_560459511002</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.632111</td>\n",
+       "      <td>0.632111</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.010724</td>\n",
+       "      <td>0.706250</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.293750</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.009383</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>216024</th>\n",
+       "      <td>#_560459513001</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>4</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1.737619</td>\n",
+       "      <td>0.868810</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.172084</td>\n",
+       "      <td>0.709910</td>\n",
+       "      <td>0.054054</td>\n",
+       "      <td>0.236036</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>215.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>216025</th>\n",
+       "      <td>#_560459513002</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.970874</td>\n",
+       "      <td>0.970874</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.075404</td>\n",
+       "      <td>0.720325</td>\n",
+       "      <td>0.160976</td>\n",
+       "      <td>0.118699</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>247.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>216026</th>\n",
+       "      <td>#_560459513003</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.625391</td>\n",
+       "      <td>0.625391</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.625391</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.075080</td>\n",
+       "      <td>0.688752</td>\n",
+       "      <td>0.015408</td>\n",
+       "      <td>0.295840</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>286.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>216027 rows × 54 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 GEOID state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
+       "0       #_010010201001    AL         2011       2017                     2   \n",
+       "1       #_010010201002    AL         2011       2017                     4   \n",
+       "2       #_010010202001    AL         2011       2017                     5   \n",
+       "3       #_010010202002    AL         2011       2017                     5   \n",
+       "4       #_010010203001    AL         2011       2017                     6   \n",
+       "...                ...   ...          ...        ...                   ...   \n",
+       "216022  #_560459511001    WY         2011       2017                     1   \n",
+       "216023  #_560459511002    WY         2011       2017                     1   \n",
+       "216024  #_560459513001    WY         2011       2017                     4   \n",
+       "216025  #_560459513002    WY         2011       2017                     2   \n",
+       "216026  #_560459513003    WY         2011       2017                     3   \n",
+       "\n",
+       "        total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
+       "0                        2.0      1.342282         1.342282   \n",
+       "1                        6.0      1.581028         1.185771   \n",
+       "2                        7.0      3.141361         1.047120   \n",
+       "3                       10.0      3.777148         0.944287   \n",
+       "4                       10.0      1.269036         0.634518   \n",
+       "...                      ...           ...              ...   \n",
+       "216022                   2.0      1.372684         1.372684   \n",
+       "216023                   1.0      0.632111         0.632111   \n",
+       "216024                   5.0      1.737619         0.868810   \n",
+       "216025                   2.0      0.970874         0.970874   \n",
+       "216026                   3.0      0.625391         0.625391   \n",
+       "\n",
+       "        total_fires_reported_sev  max_fires_1k_sev  ...  snap_past_12_mo  \\\n",
+       "0                            2.0          1.342282  ...         0.183099   \n",
+       "1                            2.0          0.790514  ...         0.096491   \n",
+       "2                            2.0          1.047120  ...         0.303109   \n",
+       "3                            3.0          1.888574  ...         0.172566   \n",
+       "4                            5.0          0.423012  ...         0.082524   \n",
+       "...                          ...               ...  ...              ...   \n",
+       "216022                       2.0          1.372684  ...         0.054252   \n",
+       "216023                       0.0               NaN  ...         0.010724   \n",
+       "216024                       0.0               NaN  ...         0.172084   \n",
+       "216025                       0.0               NaN  ...         0.075404   \n",
+       "216026                       1.0          0.625391  ...         0.075080   \n",
+       "\n",
+       "        single_unit_home  multi_unit_home  mobile_home  boat_van_rv_home  \\\n",
+       "0               0.820423         0.024648     0.154930          0.000000   \n",
+       "1               0.925054         0.000000     0.074946          0.000000   \n",
+       "2               0.768844         0.201005     0.030151          0.000000   \n",
+       "3               0.821138         0.168699     0.010163          0.000000   \n",
+       "4               0.995112         0.000000     0.004888          0.000000   \n",
+       "...                  ...              ...          ...               ...   \n",
+       "216022          0.711035         0.053470     0.228669          0.006826   \n",
+       "216023          0.706250         0.000000     0.293750          0.000000   \n",
+       "216024          0.709910         0.054054     0.236036          0.000000   \n",
+       "216025          0.720325         0.160976     0.118699          0.000000   \n",
+       "216026          0.688752         0.015408     0.295840          0.000000   \n",
+       "\n",
+       "        spanish_speaking  state_id state_rank  county_id  county_rank  \n",
+       "0               0.102113      #_01     2806.0    #_01001         24.0  \n",
+       "1               0.046053      #_01     3159.0    #_01001         29.0  \n",
+       "2               0.000000      #_01     1587.0    #_01001         12.0  \n",
+       "3               0.011062      #_01     2357.0    #_01001         19.0  \n",
+       "4               0.037621      #_01     2313.0    #_01001         18.0  \n",
+       "...                  ...       ...        ...        ...          ...  \n",
+       "216022          0.000000      #_56        2.0    #_56045          1.0  \n",
+       "216023          0.009383      #_56       23.0    #_56045          2.0  \n",
+       "216024          0.000000      #_56      215.0    #_56045          3.0  \n",
+       "216025          0.000000      #_56      247.0    #_56045          4.0  \n",
+       "216026          0.000000      #_56      286.0    #_56045          5.0  \n",
+       "\n",
+       "[216027 rows x 54 columns]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "in_name = 'CombinedModels-FileStructureColumns-pop50-block_group-2022-09-04.csv'\n",
+    "out_bg = pd.read_csv(utils.DATA['model-outputs'] / in_name)\n",
+    "out_bg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "7c9b3f64",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['GEOID', 'state', 'NFIRS_start', 'NFIRS_end', 'years_fires_reported',\n",
+       "       'total_fires_reported', 'max_fires_1k', 'median_fires_1k',\n",
+       "       'total_fires_reported_sev', 'max_fires_1k_sev', 'median_fires_1k_sev',\n",
+       "       'fire_propensity_risk_score', 'fire_severity_risk_score',\n",
+       "       'fire_risk_score', 'recorded_home_visits', 'smoke_detector_risk_frac',\n",
+       "       'smoke_detector_risk_score', 'geography', 'SVI_Theme_1',\n",
+       "       'CombinedRiskScore', 'did_not_work_past_12_mo', 'house_pct_live_alone',\n",
+       "       'pct_alt_heat', 'house_yr_pct_before_1960', 'inc_pct_poverty',\n",
+       "       'race_pct_black_or_amind', 'tot_population', 'house_tot_occ_cnt',\n",
+       "       'inc_pcincome', 'inc_hhmean', 'race_pct_white', 'race_pct_whitenh',\n",
+       "       'race_pct_whiteh', 'race_pct_nwhitenh', 'race_pct_hisp',\n",
+       "       'race_pct_black', 'race_pct_amind', 'race_pct_asian', 'race_pct_napi',\n",
+       "       'race_pct_other', 'race_pct_two+', 'age_pct_under25', 'age_pct_over65',\n",
+       "       'disability_pct', 'snap_past_12_mo', 'single_unit_home',\n",
+       "       'multi_unit_home', 'mobile_home', 'boat_van_rv_home',\n",
+       "       'spanish_speaking', 'state_id', 'state_rank', 'county_id',\n",
+       "       'county_rank'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "col_mode = ['state', 'NFIRS_start', 'NFIRS_end', 'state_id', 'county_id']\n",
+    "col_sum = [ 'total_fires_reported', 'total_fires_reported_sev','recorded_home_visits', 'tot_population','house_tot_occ_cnt']\n",
+    "col_div = [ 'years_fires_reported', 'max_fires_1k', 'median_fires_1k', 'max_fires_1k_sev', 'median_fires_1k_sev',\n",
+    "           'fire_propensity_risk_score','fire_severity_risk_score', 'fire_risk_score', 'smoke_detector_risk_frac',\n",
+    "       'smoke_detector_risk_score','SVI_Theme_1','CombinedRiskScore', 'did_not_work_past_12_mo', 'house_pct_live_alone',\n",
+    "       'pct_alt_heat', 'house_yr_pct_before_1960', 'inc_pct_poverty','race_pct_black_or_amind','inc_pcincome', 'inc_hhmean', \n",
+    "        'race_pct_white', 'race_pct_whitenh','race_pct_whiteh', 'race_pct_nwhitenh', 'race_pct_hisp', 'race_pct_black', \n",
+    "        'race_pct_amind', 'race_pct_asian', 'race_pct_napi', 'race_pct_other', 'race_pct_two+', 'age_pct_under25', \n",
+    "        'age_pct_over65','disability_pct', 'snap_past_12_mo','single_unit_home','multi_unit_home', 'mobile_home', \n",
+    "        'boat_van_rv_home','spanish_speaking']\n",
+    "#other columns- GEOID, state_rank, an county_rank\n",
+    "out_bg.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "84419a68",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0         #_01001020100\n",
+       "1         #_01001020100\n",
+       "2         #_01001020200\n",
+       "3         #_01001020200\n",
+       "4         #_01001020300\n",
+       "              ...      \n",
+       "216022    #_56045951100\n",
+       "216023    #_56045951100\n",
+       "216024    #_56045951300\n",
+       "216025    #_56045951300\n",
+       "216026    #_56045951300\n",
+       "Name: tract, Length: 216027, dtype: object"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#get tract-level info\n",
+    "out_bg['tract'] = out_bg['GEOID'].str[:-1]\n",
+    "out_bg['tract']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "b48d2992",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(72142, 5)\n",
+      "(72142, 5)\n",
+      "(72142, 40)\n"
+     ]
+    }
+   ],
+   "source": [
+    "out_sum = out_bg.groupby('tract')[col_sum].sum()\n",
+    "print(out_sum.shape)\n",
+    "out_mode = out_bg.groupby('tract')[col_mode].agg(pd.Series.mode)\n",
+    "print(out_mode.shape)\n",
+    "out_bg_div = out_bg[col_div].mul(out_bg['tot_population'], axis = 0)\n",
+    "out_bg_div['tract'] = out_bg['tract']\n",
+    "out_div = out_bg_div.groupby('tract')[col_div].sum()\n",
+    "out_div = out_div.div(out_sum.tot_population, axis=0)\n",
+    "print(out_div.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "60da19ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "out_tract = out_sum.merge(out_mode, how = 'left', right_index = True, left_index = True)\n",
+    "out_tract = out_tract.merge(out_div, how = 'left', right_index = True, left_index = True)\n",
+    "out_tract['GEOID'] = out_tract.index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "4fc07276",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "out_tract['state_rank'] = out_tract.groupby('state_id')['CombinedRiskScore'].rank(ascending=False)\n",
+    "out_tract['county_rank'] = out_tract.groupby('county_id')['CombinedRiskScore'].rank(ascending=False)\n",
+    "out_tract.index.names = ['GEOID']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "0c194b95",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cols = out_bg.copy()\n",
+    "cols = cols.drop(columns=['geography', 'tract', 'GEOID'])\n",
+    "cols = cols.columns\n",
+    "out_tract = out_tract[cols]\n",
+    "out_name = f\"TrainedOnBG-tract-{date.today()}.csv\"\n",
+    "out_tract.to_csv(utils.DATA['model-outputs'] / out_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "74634915",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0         #_01001\n",
+       "1         #_01001\n",
+       "2         #_01001\n",
+       "3         #_01001\n",
+       "4         #_01001\n",
+       "           ...   \n",
+       "216022    #_56045\n",
+       "216023    #_56045\n",
+       "216024    #_56045\n",
+       "216025    #_56045\n",
+       "216026    #_56045\n",
+       "Name: county, Length: 216027, dtype: object"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#get tract-level info\n",
+    "out_bg['county'] = out_bg['GEOID'].str[:-7]\n",
+    "out_bg['county']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "67629fa8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(3142, 5)\n",
+      "(3142, 5)\n",
+      "(3142, 40)\n"
+     ]
+    }
+   ],
+   "source": [
+    "out_sum = out_bg.groupby('county')[col_sum].sum()\n",
+    "print(out_sum.shape)\n",
+    "out_mode = out_bg.groupby('county')[col_mode].agg(pd.Series.mode)\n",
+    "print(out_mode.shape)\n",
+    "out_bg_div = out_bg[col_div].mul(out_bg['tot_population'], axis = 0)\n",
+    "out_bg_div['county'] = out_bg['county']\n",
+    "out_div = out_bg_div.groupby('county')[col_div].sum()\n",
+    "out_div = out_div.div(out_sum.tot_population, axis=0)\n",
+    "print(out_div.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "5aed464c",
+   "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>total_fires_reported</th>\n",
+       "      <th>total_fires_reported_sev</th>\n",
+       "      <th>recorded_home_visits</th>\n",
+       "      <th>tot_population</th>\n",
+       "      <th>house_tot_occ_cnt</th>\n",
+       "      <th>state</th>\n",
+       "      <th>NFIRS_start</th>\n",
+       "      <th>NFIRS_end</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>county_id</th>\n",
+       "      <th>...</th>\n",
+       "      <th>race_pct_two+</th>\n",
+       "      <th>age_pct_under25</th>\n",
+       "      <th>age_pct_over65</th>\n",
+       "      <th>disability_pct</th>\n",
+       "      <th>snap_past_12_mo</th>\n",
+       "      <th>single_unit_home</th>\n",
+       "      <th>multi_unit_home</th>\n",
+       "      <th>mobile_home</th>\n",
+       "      <th>boat_van_rv_home</th>\n",
+       "      <th>spanish_speaking</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>county</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>#_01001</th>\n",
+       "      <td>168.0</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>54598.0</td>\n",
+       "      <td>20800.0</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.019504</td>\n",
+       "      <td>0.337628</td>\n",
+       "      <td>0.139963</td>\n",
+       "      <td>0.347003</td>\n",
+       "      <td>0.127977</td>\n",
+       "      <td>0.736557</td>\n",
+       "      <td>0.085260</td>\n",
+       "      <td>0.176695</td>\n",
+       "      <td>0.001488</td>\n",
+       "      <td>0.022453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_01003</th>\n",
+       "      <td>758.0</td>\n",
+       "      <td>133.0</td>\n",
+       "      <td>95</td>\n",
+       "      <td>196640.0</td>\n",
+       "      <td>75149.0</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>#_01003</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.020327</td>\n",
+       "      <td>0.298873</td>\n",
+       "      <td>0.187231</td>\n",
+       "      <td>0.263131</td>\n",
+       "      <td>0.089366</td>\n",
+       "      <td>0.706353</td>\n",
+       "      <td>0.157369</td>\n",
+       "      <td>0.135164</td>\n",
+       "      <td>0.001114</td>\n",
+       "      <td>0.044759</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_01005</th>\n",
+       "      <td>53.0</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>23641.0</td>\n",
+       "      <td>9122.0</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>#_01005</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.005240</td>\n",
+       "      <td>0.328502</td>\n",
+       "      <td>0.173040</td>\n",
+       "      <td>0.401597</td>\n",
+       "      <td>0.257016</td>\n",
+       "      <td>0.581526</td>\n",
+       "      <td>0.122152</td>\n",
+       "      <td>0.293386</td>\n",
+       "      <td>0.002936</td>\n",
+       "      <td>0.050249</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_01007</th>\n",
+       "      <td>23.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>20603.0</td>\n",
+       "      <td>7048.0</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>#_01007</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.013765</td>\n",
+       "      <td>0.320549</td>\n",
+       "      <td>0.151724</td>\n",
+       "      <td>0.318074</td>\n",
+       "      <td>0.146243</td>\n",
+       "      <td>0.642416</td>\n",
+       "      <td>0.068359</td>\n",
+       "      <td>0.289225</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.014411</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_01009</th>\n",
+       "      <td>208.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>57099.0</td>\n",
+       "      <td>20619.0</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>#_01009</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.016088</td>\n",
+       "      <td>0.315907</td>\n",
+       "      <td>0.172013</td>\n",
+       "      <td>0.300140</td>\n",
+       "      <td>0.116018</td>\n",
+       "      <td>0.733611</td>\n",
+       "      <td>0.039209</td>\n",
+       "      <td>0.226844</td>\n",
+       "      <td>0.000335</td>\n",
+       "      <td>0.057006</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>#_56037</th>\n",
+       "      <td>115.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>31</td>\n",
+       "      <td>44166.0</td>\n",
+       "      <td>16533.0</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>#_56037</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.034314</td>\n",
+       "      <td>0.365076</td>\n",
+       "      <td>0.094774</td>\n",
+       "      <td>0.244424</td>\n",
+       "      <td>0.044100</td>\n",
+       "      <td>0.632603</td>\n",
+       "      <td>0.157313</td>\n",
+       "      <td>0.209544</td>\n",
+       "      <td>0.000540</td>\n",
+       "      <td>0.093154</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_56039</th>\n",
+       "      <td>50.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>22524.0</td>\n",
+       "      <td>8576.0</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>#_56039</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.009976</td>\n",
+       "      <td>0.252004</td>\n",
+       "      <td>0.118485</td>\n",
+       "      <td>0.116231</td>\n",
+       "      <td>0.014235</td>\n",
+       "      <td>0.700322</td>\n",
+       "      <td>0.263987</td>\n",
+       "      <td>0.031158</td>\n",
+       "      <td>0.004533</td>\n",
+       "      <td>0.124490</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_56041</th>\n",
+       "      <td>42.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>20658.0</td>\n",
+       "      <td>7432.0</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>#_56041</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.030348</td>\n",
+       "      <td>0.375898</td>\n",
+       "      <td>0.106618</td>\n",
+       "      <td>0.307708</td>\n",
+       "      <td>0.083410</td>\n",
+       "      <td>0.624190</td>\n",
+       "      <td>0.131420</td>\n",
+       "      <td>0.236145</td>\n",
+       "      <td>0.008245</td>\n",
+       "      <td>0.081690</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_56043</th>\n",
+       "      <td>17.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>8174.0</td>\n",
+       "      <td>3493.0</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.039509</td>\n",
+       "      <td>0.301766</td>\n",
+       "      <td>0.195733</td>\n",
+       "      <td>0.363713</td>\n",
+       "      <td>0.081943</td>\n",
+       "      <td>0.773465</td>\n",
+       "      <td>0.107375</td>\n",
+       "      <td>0.112616</td>\n",
+       "      <td>0.006545</td>\n",
+       "      <td>0.102321</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_56045</th>\n",
+       "      <td>13.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>6819.0</td>\n",
+       "      <td>3134.0</td>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014400</td>\n",
+       "      <td>0.281251</td>\n",
+       "      <td>0.180368</td>\n",
+       "      <td>0.261284</td>\n",
+       "      <td>0.072122</td>\n",
+       "      <td>0.705913</td>\n",
+       "      <td>0.048477</td>\n",
+       "      <td>0.244151</td>\n",
+       "      <td>0.001458</td>\n",
+       "      <td>0.002177</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3142 rows × 50 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         total_fires_reported  total_fires_reported_sev  recorded_home_visits  \\\n",
+       "county                                                                          \n",
+       "#_01001                 168.0                      38.0                    12   \n",
+       "#_01003                 758.0                     133.0                    95   \n",
+       "#_01005                  53.0                      15.0                    15   \n",
+       "#_01007                  23.0                       5.0                    14   \n",
+       "#_01009                 208.0                      51.0                    47   \n",
+       "...                       ...                       ...                   ...   \n",
+       "#_56037                 115.0                      32.0                    31   \n",
+       "#_56039                  50.0                      11.0                     7   \n",
+       "#_56041                  42.0                       3.0                     0   \n",
+       "#_56043                  17.0                       4.0                     5   \n",
+       "#_56045                  13.0                       3.0                    12   \n",
+       "\n",
+       "         tot_population  house_tot_occ_cnt state  NFIRS_start  NFIRS_end  \\\n",
+       "county                                                                     \n",
+       "#_01001         54598.0            20800.0    AL         2011       2017   \n",
+       "#_01003        196640.0            75149.0    AL         2011       2017   \n",
+       "#_01005         23641.0             9122.0    AL         2011       2017   \n",
+       "#_01007         20603.0             7048.0    AL         2011       2017   \n",
+       "#_01009         57099.0            20619.0    AL         2011       2017   \n",
+       "...                 ...                ...   ...          ...        ...   \n",
+       "#_56037         44166.0            16533.0    WY         2011       2017   \n",
+       "#_56039         22524.0             8576.0    WY         2011       2017   \n",
+       "#_56041         20658.0             7432.0    WY         2011       2017   \n",
+       "#_56043          8174.0             3493.0    WY         2011       2017   \n",
+       "#_56045          6819.0             3134.0    WY         2011       2017   \n",
+       "\n",
+       "        state_id county_id  ...  race_pct_two+  age_pct_under25  \\\n",
+       "county                      ...                                   \n",
+       "#_01001     #_01   #_01001  ...       0.019504         0.337628   \n",
+       "#_01003     #_01   #_01003  ...       0.020327         0.298873   \n",
+       "#_01005     #_01   #_01005  ...       0.005240         0.328502   \n",
+       "#_01007     #_01   #_01007  ...       0.013765         0.320549   \n",
+       "#_01009     #_01   #_01009  ...       0.016088         0.315907   \n",
+       "...          ...       ...  ...            ...              ...   \n",
+       "#_56037     #_56   #_56037  ...       0.034314         0.365076   \n",
+       "#_56039     #_56   #_56039  ...       0.009976         0.252004   \n",
+       "#_56041     #_56   #_56041  ...       0.030348         0.375898   \n",
+       "#_56043     #_56   #_56043  ...       0.039509         0.301766   \n",
+       "#_56045     #_56   #_56045  ...       0.014400         0.281251   \n",
+       "\n",
+       "         age_pct_over65  disability_pct  snap_past_12_mo  single_unit_home  \\\n",
+       "county                                                                       \n",
+       "#_01001        0.139963        0.347003         0.127977          0.736557   \n",
+       "#_01003        0.187231        0.263131         0.089366          0.706353   \n",
+       "#_01005        0.173040        0.401597         0.257016          0.581526   \n",
+       "#_01007        0.151724        0.318074         0.146243          0.642416   \n",
+       "#_01009        0.172013        0.300140         0.116018          0.733611   \n",
+       "...                 ...             ...              ...               ...   \n",
+       "#_56037        0.094774        0.244424         0.044100          0.632603   \n",
+       "#_56039        0.118485        0.116231         0.014235          0.700322   \n",
+       "#_56041        0.106618        0.307708         0.083410          0.624190   \n",
+       "#_56043        0.195733        0.363713         0.081943          0.773465   \n",
+       "#_56045        0.180368        0.261284         0.072122          0.705913   \n",
+       "\n",
+       "         multi_unit_home  mobile_home  boat_van_rv_home  spanish_speaking  \n",
+       "county                                                                     \n",
+       "#_01001         0.085260     0.176695          0.001488          0.022453  \n",
+       "#_01003         0.157369     0.135164          0.001114          0.044759  \n",
+       "#_01005         0.122152     0.293386          0.002936          0.050249  \n",
+       "#_01007         0.068359     0.289225          0.000000          0.014411  \n",
+       "#_01009         0.039209     0.226844          0.000335          0.057006  \n",
+       "...                  ...          ...               ...               ...  \n",
+       "#_56037         0.157313     0.209544          0.000540          0.093154  \n",
+       "#_56039         0.263987     0.031158          0.004533          0.124490  \n",
+       "#_56041         0.131420     0.236145          0.008245          0.081690  \n",
+       "#_56043         0.107375     0.112616          0.006545          0.102321  \n",
+       "#_56045         0.048477     0.244151          0.001458          0.002177  \n",
+       "\n",
+       "[3142 rows x 50 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "out_county = out_sum.merge(out_mode, how = 'left', right_index = True, left_index = True)\n",
+    "out_county = out_county.merge(out_div, how = 'left', right_index = True, left_index = True)\n",
+    "out_county"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "0c7f67ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "out_county['state_rank'] = out_county.groupby('state_id')['CombinedRiskScore'].rank(ascending=False)\n",
+    "out_county['county_rank'] = out_county.groupby('county_id')['CombinedRiskScore'].rank(ascending=False)\n",
+    "out_county.index.names = ['GEOID']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "ef9d7976",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cols = out_bg.copy()\n",
+    "cols = cols.drop(columns=['geography', 'tract','county', 'GEOID'])\n",
+    "cols = cols.columns\n",
+    "out_county = out_county[cols]\n",
+    "out_name = f\"TrainedOnBG-county-{date.today()}.csv\"\n",
+    "out_county.to_csv(utils.DATA['model-outputs'] / out_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "9bf3c2a6",
+   "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>state</th>\n",
+       "      <th>NFIRS_start</th>\n",
+       "      <th>NFIRS_end</th>\n",
+       "      <th>years_fires_reported</th>\n",
+       "      <th>total_fires_reported</th>\n",
+       "      <th>max_fires_1k</th>\n",
+       "      <th>median_fires_1k</th>\n",
+       "      <th>total_fires_reported_sev</th>\n",
+       "      <th>max_fires_1k_sev</th>\n",
+       "      <th>median_fires_1k_sev</th>\n",
+       "      <th>...</th>\n",
+       "      <th>snap_past_12_mo</th>\n",
+       "      <th>single_unit_home</th>\n",
+       "      <th>multi_unit_home</th>\n",
+       "      <th>mobile_home</th>\n",
+       "      <th>boat_van_rv_home</th>\n",
+       "      <th>spanish_speaking</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>state_rank</th>\n",
+       "      <th>county_id</th>\n",
+       "      <th>county_rank</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GEOID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>#_01001</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>3.431023</td>\n",
+       "      <td>168.0</td>\n",
+       "      <td>1.172204</td>\n",
+       "      <td>0.750943</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>0.384629</td>\n",
+       "      <td>0.320525</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.127977</td>\n",
+       "      <td>0.736557</td>\n",
+       "      <td>0.085260</td>\n",
+       "      <td>0.176695</td>\n",
+       "      <td>0.001488</td>\n",
+       "      <td>0.022453</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>62.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_01003</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>4.452360</td>\n",
+       "      <td>758.0</td>\n",
+       "      <td>1.418836</td>\n",
+       "      <td>0.762815</td>\n",
+       "      <td>133.0</td>\n",
+       "      <td>0.381408</td>\n",
+       "      <td>0.289870</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.089366</td>\n",
+       "      <td>0.706353</td>\n",
+       "      <td>0.157369</td>\n",
+       "      <td>0.135164</td>\n",
+       "      <td>0.001114</td>\n",
+       "      <td>0.044759</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>#_01003</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_01005</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1.290216</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>1.142084</td>\n",
+       "      <td>0.634491</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0.465293</td>\n",
+       "      <td>0.465293</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.257016</td>\n",
+       "      <td>0.581526</td>\n",
+       "      <td>0.122152</td>\n",
+       "      <td>0.293386</td>\n",
+       "      <td>0.002936</td>\n",
+       "      <td>0.050249</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>#_01005</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_01007</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1.644760</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>0.679513</td>\n",
+       "      <td>0.558171</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.242683</td>\n",
+       "      <td>0.242683</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.146243</td>\n",
+       "      <td>0.642416</td>\n",
+       "      <td>0.068359</td>\n",
+       "      <td>0.289225</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.014411</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>#_01007</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_01009</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.539624</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>1.611237</td>\n",
+       "      <td>0.963239</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.472863</td>\n",
+       "      <td>0.341512</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.116018</td>\n",
+       "      <td>0.733611</td>\n",
+       "      <td>0.039209</td>\n",
+       "      <td>0.226844</td>\n",
+       "      <td>0.000335</td>\n",
+       "      <td>0.057006</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>#_01009</td>\n",
+       "      <td>1.0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>#_56037</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.296880</td>\n",
+       "      <td>115.0</td>\n",
+       "      <td>1.403795</td>\n",
+       "      <td>0.905674</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0.475479</td>\n",
+       "      <td>0.441516</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.044100</td>\n",
+       "      <td>0.632603</td>\n",
+       "      <td>0.157313</td>\n",
+       "      <td>0.209544</td>\n",
+       "      <td>0.000540</td>\n",
+       "      <td>0.093154</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>#_56037</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_56039</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.502575</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>1.243118</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>0.310780</td>\n",
+       "      <td>0.310780</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014235</td>\n",
+       "      <td>0.700322</td>\n",
+       "      <td>0.263987</td>\n",
+       "      <td>0.031158</td>\n",
+       "      <td>0.004533</td>\n",
+       "      <td>0.124490</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>#_56039</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_56041</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.337496</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>1.113370</td>\n",
+       "      <td>0.871333</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.145222</td>\n",
+       "      <td>0.145222</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.083410</td>\n",
+       "      <td>0.624190</td>\n",
+       "      <td>0.131420</td>\n",
+       "      <td>0.236145</td>\n",
+       "      <td>0.008245</td>\n",
+       "      <td>0.081690</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>#_56041</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_56043</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>1.396134</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>1.223391</td>\n",
+       "      <td>0.917543</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>0.305848</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.081943</td>\n",
+       "      <td>0.773465</td>\n",
+       "      <td>0.107375</td>\n",
+       "      <td>0.112616</td>\n",
+       "      <td>0.006545</td>\n",
+       "      <td>0.102321</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>#_56045</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>2.126411</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>1.026543</td>\n",
+       "      <td>0.879894</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.072122</td>\n",
+       "      <td>0.705913</td>\n",
+       "      <td>0.048477</td>\n",
+       "      <td>0.244151</td>\n",
+       "      <td>0.001458</td>\n",
+       "      <td>0.002177</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3142 rows × 52 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
+       "GEOID                                                         \n",
+       "#_01001    AL         2011       2017              3.431023   \n",
+       "#_01003    AL         2011       2017              4.452360   \n",
+       "#_01005    AL         2011       2017              1.290216   \n",
+       "#_01007    AL         2011       2017              1.644760   \n",
+       "#_01009    AL         2011       2017              2.539624   \n",
+       "...       ...          ...        ...                   ...   \n",
+       "#_56037    WY         2011       2017              2.296880   \n",
+       "#_56039    WY         2011       2017              2.502575   \n",
+       "#_56041    WY         2011       2017              2.337496   \n",
+       "#_56043    WY         2011       2017              1.396134   \n",
+       "#_56045    WY         2011       2017              2.126411   \n",
+       "\n",
+       "         total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
+       "GEOID                                                          \n",
+       "#_01001                 168.0      1.172204         0.750943   \n",
+       "#_01003                 758.0      1.418836         0.762815   \n",
+       "#_01005                  53.0      1.142084         0.634491   \n",
+       "#_01007                  23.0      0.679513         0.558171   \n",
+       "#_01009                 208.0      1.611237         0.963239   \n",
+       "...                       ...           ...              ...   \n",
+       "#_56037                 115.0      1.403795         0.905674   \n",
+       "#_56039                  50.0      1.243118         0.887942   \n",
+       "#_56041                  42.0      1.113370         0.871333   \n",
+       "#_56043                  17.0      1.223391         0.917543   \n",
+       "#_56045                  13.0      1.026543         0.879894   \n",
+       "\n",
+       "         total_fires_reported_sev  max_fires_1k_sev  median_fires_1k_sev  ...  \\\n",
+       "GEOID                                                                     ...   \n",
+       "#_01001                      38.0          0.384629             0.320525  ...   \n",
+       "#_01003                     133.0          0.381408             0.289870  ...   \n",
+       "#_01005                      15.0          0.465293             0.465293  ...   \n",
+       "#_01007                       5.0          0.242683             0.242683  ...   \n",
+       "#_01009                      51.0          0.472863             0.341512  ...   \n",
+       "...                           ...               ...                  ...  ...   \n",
+       "#_56037                      32.0          0.475479             0.441516  ...   \n",
+       "#_56039                      11.0          0.310780             0.310780  ...   \n",
+       "#_56041                       3.0          0.145222             0.145222  ...   \n",
+       "#_56043                       4.0          0.367017             0.305848  ...   \n",
+       "#_56045                       3.0          0.439947             0.439947  ...   \n",
+       "\n",
+       "         snap_past_12_mo  single_unit_home  multi_unit_home  mobile_home  \\\n",
+       "GEOID                                                                      \n",
+       "#_01001         0.127977          0.736557         0.085260     0.176695   \n",
+       "#_01003         0.089366          0.706353         0.157369     0.135164   \n",
+       "#_01005         0.257016          0.581526         0.122152     0.293386   \n",
+       "#_01007         0.146243          0.642416         0.068359     0.289225   \n",
+       "#_01009         0.116018          0.733611         0.039209     0.226844   \n",
+       "...                  ...               ...              ...          ...   \n",
+       "#_56037         0.044100          0.632603         0.157313     0.209544   \n",
+       "#_56039         0.014235          0.700322         0.263987     0.031158   \n",
+       "#_56041         0.083410          0.624190         0.131420     0.236145   \n",
+       "#_56043         0.081943          0.773465         0.107375     0.112616   \n",
+       "#_56045         0.072122          0.705913         0.048477     0.244151   \n",
+       "\n",
+       "         boat_van_rv_home  spanish_speaking  state_id  state_rank  county_id  \\\n",
+       "GEOID                                                                          \n",
+       "#_01001          0.001488          0.022453      #_01        62.0    #_01001   \n",
+       "#_01003          0.001114          0.044759      #_01        66.0    #_01003   \n",
+       "#_01005          0.002936          0.050249      #_01        14.0    #_01005   \n",
+       "#_01007          0.000000          0.014411      #_01        59.0    #_01007   \n",
+       "#_01009          0.000335          0.057006      #_01        49.0    #_01009   \n",
+       "...                   ...               ...       ...         ...        ...   \n",
+       "#_56037          0.000540          0.093154      #_56        14.0    #_56037   \n",
+       "#_56039          0.004533          0.124490      #_56         9.0    #_56039   \n",
+       "#_56041          0.008245          0.081690      #_56        10.0    #_56041   \n",
+       "#_56043          0.006545          0.102321      #_56        11.0    #_56043   \n",
+       "#_56045          0.001458          0.002177      #_56         4.0    #_56045   \n",
+       "\n",
+       "         county_rank  \n",
+       "GEOID                 \n",
+       "#_01001          1.0  \n",
+       "#_01003          1.0  \n",
+       "#_01005          1.0  \n",
+       "#_01007          1.0  \n",
+       "#_01009          1.0  \n",
+       "...              ...  \n",
+       "#_56037          1.0  \n",
+       "#_56039          1.0  \n",
+       "#_56041          1.0  \n",
+       "#_56043          1.0  \n",
+       "#_56045          1.0  \n",
+       "\n",
+       "[3142 rows x 52 columns]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "out_county"
+   ]
+  }
+ ],
+ "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": "3.10.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/src/data/DataLoaders.py b/src/data/DataLoaders.py
index 3b4cd4a..2764149 100644
--- a/src/data/DataLoaders.py
+++ b/src/data/DataLoaders.py
@@ -6,17 +6,17 @@
 
 class ARCPData():
     # american red cross preparedness data 
-    def __init__(self, ACS, file_name = 'ARC Preparedness Data.csv'  ):
+    def __init__(self, ACS, file_name = 'ARC Preparedness Data.csv', level = 'block_group'):
         self.data = None
         self.file_name = utils.DATA['master'] / file_name 
         self.Load()
-        self.standardizeColumnNames(ACS)
+        self.standardizeColumnNames(ACS, level)
 
     def Load(self):
 
         self.data = pd.read_csv(self.file_name)
 
-    def standardizeColumnNames(self, ACS):
+    def standardizeColumnNames(self, ACS, level):
         """
         Standardizes column names
         """
@@ -30,8 +30,15 @@ def standardizeColumnNames(self, ACS):
         df.columns = df.columns.str.replace(')', '_')
         df.columns = df.columns.str.replace(' ', '_')
         df.dropna(inplace = True)
-        # trim geoid leading saftey marks 
-        df['geoid'] = df['geoid'].str[2:]
+        # trim geoid leading saftey marks
+        if level == 'block_group':
+            df['geoid'] = df['geoid'].str[2:]
+        elif level == 'tract':
+            df['geoid'] = df['geoid'].str[2:-1]
+        elif level == 'county':
+            df['geoid'] = df['geoid'].str[2:-7]
+        else:
+            print('invalid level')
 
         df = df[df['geoid'].isin(ACS.tot_pop.index)]
 
@@ -47,6 +54,7 @@ def __init__(self,year = 2016,level = 'block_group', pop_thresh = 0):
         self.level = level
         self.data = None
         self.tot_pop = None
+        self.tot_pop_bg = None
         self.pop_thresh = pop_thresh
         self.Load()
         self.Clean(self.data)
@@ -145,22 +153,36 @@ def Munge(self,ACS,tot_pop, pop_thresh,level='block_group'):
 
         
         # munge to appropriate level 
-
+        self.tot_pop_bg = tot_pop
         if  self.level =='block_group':
             #ACS data already at block_group level
             self.tot_pop = tot_pop
         else:
             Data = self.data 
-            Data = Data.multiply(tot_pop['tot_population'],axis= 'index')
-        
-            Data.index , tot_pop.index  = Data.index.str[0:utils.GEOID[level]], \
-                                    tot_pop.index.str[0:utils.GEOID[level]]
-
-            Data, tot_pop = Data.groupby(Data.index).sum(), \
-                    tot_pop.groupby(tot_pop.index).sum()
-
-            self.data = Data.divide(tot_pop['tot_population'],axis = 'index')
-            self.tot_pop = tot_pop
+            operations = pd.read_csv(utils.DATA['data']/'geo_levels.csv', skiprows = 1)
+            Data_level = Data.copy()
+            Data_original = Data.copy()
+            for i in Data_level.columns:
+                a = operations.loc[operations['variable_name'] == i]
+                op = a['operator'].values
+                if (op == 'pct') | (op =='div'):
+                    Data_level[i] = Data_original[i] * Data_original[a['argument1'].item()]
+            Data_level.index = Data_level.index.str[0:utils.GEOID[level]]
+
+            Data_level_num = Data_level.groupby(Data_level.index).sum()
+            Data_level_str = Data_level.groupby(Data_level.index).first()
+            for i in Data_level_num.columns:
+                a = operations.loc[operations['variable_name'] == i]
+                op = a['operator'].values
+                if (op == 'pct') | (op =='div'):
+                    Data_level_num[i] = Data_level_num[i].divide(Data_level_num[a['argument1'].item()],axis = 'index')
+            Data_level = Data_level_num
+            Data_level['state'] = Data_level_str['state']
+            cols = Data_level.columns.tolist()
+            cols = cols[-1:] + cols[:-1]
+            Data_level = Data_level[cols]
+            self.data = Data_level
+            self.tot_pop = Data_level[['tot_population']].groupby('GEOID').sum()
         #only get geoids with population greater than user defined value
         self.tot_pop = self.tot_pop[self.tot_pop['tot_population']>=self.pop_thresh]
         self.data = self.data[self.data.index.isin(self.tot_pop.index)]
@@ -168,25 +190,54 @@ def Munge(self,ACS,tot_pop, pop_thresh,level='block_group'):
 class SVIData():
     # TODO: typechecking
     # level and year are fixe
-    def __init__(self,ACS):
+    def __init__(self,ACS, tot_pop_bg, level = 'block_group'):
 
         self.file_name = utils.DATA['svi'] / "SVI Tract Data.csv"
         self.data = None
+        self.level = level
+        self.tot_pop_bg = tot_pop_bg
         self.Load()
-        self.Clean(ACS)
+        self.Clean(ACS, level)
         
     def Load(self):
-        self.data = pd.read_csv(self.file_name)
+        self.data = pd.read_csv(self.file_name, encoding='ISO-8859-1')
         self.data['Tract'] = self.data['GEOID'].str[2:]
     
-    def Clean(self, ACS):
-        ACS['Tract'] = ACS.index.str[:-1]
-        ACS['geos'] = ACS.index
-        merged = ACS.merge(self.data, how = 'left', left_on = 'Tract' , right_on ='Tract')
-        
-        merged.set_index('geos', inplace=True)
-        cols = ['inc_pct_poverty','RPL_THEME1', 'RPL_THEME2', 'RPL_THEME3','RPL_THEME4']
-        self.data = merged[cols]
+    def Clean(self, ACS, level):
+        if level == 'county':
+            tract_pop = self.tot_pop_bg
+            tract_pop.index = tract_pop.index.str[0:utils.GEOID['tract']]
+            tract_pop = tract_pop.groupby(tract_pop.index).sum()
+            data = self.data
+            data.index = data['Tract']
+            data = data[['RPL_THEME1', 'RPL_THEME2', 'RPL_THEME3','RPL_THEME4']]
+            data = tract_pop.merge(data, how = 'left', left_index = True, right_index = True)
+            print(data)
+            print(data.isnull().values.sum())
+            data[['RPL_THEME1', 'RPL_THEME2', 'RPL_THEME3','RPL_THEME4']] = data[['RPL_THEME1', 'RPL_THEME2', 'RPL_THEME3','RPL_THEME4']].multiply(data['tot_population'], axis='index')
+            data.drop('tot_population',axis = 1, inplace = True)
+            print(data)
+            data.index = data.index.str[0:utils.GEOID['county']]
+            data = data.groupby(data.index).sum()
+            data = ACS[['tot_population']].merge(data, how = 'left', left_index = True, right_index = True)
+            data[['RPL_THEME1', 'RPL_THEME2', 'RPL_THEME3','RPL_THEME4']] = data[['RPL_THEME1', 'RPL_THEME2', 'RPL_THEME3','RPL_THEME4']].divide(data['tot_population'], axis='index')
+            data['inc_pct_poverty'] = ACS['inc_pct_poverty']
+            data.drop('tot_population',axis = 1, inplace = True)
+            self.data = data
+        else:
+            if level == 'block_group':
+                ACS['Tract'] = ACS.index.str[:-1]
+            elif level == 'tract':
+                ACS['Tract'] = ACS.index
+            else:
+                print('invalid level')  
+            ACS['geos'] = ACS.index
+            merged = ACS.merge(self.data, how = 'left', left_on = 'Tract' , right_on ='Tract')
+            merged.set_index('geos', inplace=True)
+            cols = ['inc_pct_poverty','RPL_THEME1', 'RPL_THEME2', 'RPL_THEME3','RPL_THEME4']
+            self.data = merged[cols]
+                    
+
         self.data = self.data.replace(-999,np.nan)
             
   
diff --git a/src/models/ModelClasses.py b/src/models/ModelClasses.py
index 17da249..9399c87 100644
--- a/src/models/ModelClasses.py
+++ b/src/models/ModelClasses.py
@@ -348,7 +348,7 @@ def  __init__(self):
 
         self.models = {}
         
-    def trainModels(self,ARC,ACS,SVI, ACS_variables,svi_use, data_path):
+    def trainModels(self,ARC,ACS_data,ACS_totpop, SVI, ACS_variables,svi_use, data_path, level= 'block_group'):
 
         if not ACS_variables:
                 ACS_variables = ACS.data.columns
@@ -359,29 +359,32 @@ def trainModels(self,ARC,ACS,SVI, ACS_variables,svi_use, data_path):
 
 
         self.arc = ARC.data
-        self.acs = ACS.data[ACS_variables]
-        self.acs_pop = ACS.tot_pop
+        self.acs = ACS_data[ACS_variables]
+        self.acs_pop = ACS_totpop
         self.svi = SVI.data
         self.svi_use = svi_use
         
         self.trainStatisticalModel()
-        return  self.trainDLModel(data_path)
+        return  self.trainDLModel(data_path, level)
 
 
     def trainStatisticalModel(self):
 
 
-
+        
         # single level models 
         for geo in ['State','County','Tract','Block_Group'] :
-            print(f'Training {geo} smoke alarm stats model')
-            df = self.createSingleLevelSmokeAlarmModel(geo) 
-            name = 'SmokeAlarmModel' + geo + '.csv'
-            df.index.name = 'geoid'
-            self.models[geo] = df
-            df.index =  '#_' + df.index 
-            out_path =  utils.DATA['model-outputs'] /'Smoke_Alarm_Single_Level' / name
-            df.to_csv(out_path)
+            if geo in self.models.keys():
+                print(f'{geo} smoke alarm stats model already trained')
+            else:
+                print(f'Training {geo} smoke alarm stats model')
+                df = self.createSingleLevelSmokeAlarmModel(geo) 
+                name = 'SmokeAlarmModel' + geo + '.csv'
+                df.index.name = 'geoid'
+                self.models[geo] = df
+                df.index =  '#_' + df.index 
+                out_path =  utils.DATA['model-outputs'] /'Smoke_Alarm_Single_Level' / name
+                df.to_csv(out_path)
             
         print(f'Training MultiLevel smoke alarm stats model')
         self.createMultiLevelSmokeAlarmModel()
@@ -392,45 +395,68 @@ def trainStatisticalModel(self):
 
 
 
-    def trainDLModel(self, data_path):
-        print('Training DL model')
-        sm = self.models['MultiLevel'].copy()
-        
+    def trainDLModel(self, data_path, level = 'block_group'):
+        if level == 'block_group':
+            sm = self.models['MultiLevel'].copy()
+            sm = sm.reset_index()
+            sm['geoid'] = sm['geoid'].str[2:]
+            sm['tract'] = sm['geoid'].str[:-1]
+            sm.set_index('geoid', inplace =  True)
+            sm_all = sm.copy()
+            sm = sm[ sm['geography'].isin(['tract','block_group']) ].copy()
+        elif level == 'tract':
+            sm = self.models['Tract'].copy()
+            sm = sm.reset_index()
+            sm['geoid'] = sm['geoid'].str[2:]
+            sm.set_index('geoid', inplace =  True)
+            sm_all = sm.copy()
+            sm = sm[sm['num_surveys']>=30].copy()
+        elif level == 'county':
+            sm = self.models['County'].copy()
+            sm = sm.reset_index()
+            sm['geoid'] = sm['geoid'].str[2:]
+            sm.set_index('geoid', inplace =  True)
+            sm_all = sm.copy()
+            sm = sm[sm['num_surveys']>=30].copy()
         df = self.acs.copy()        
         if self.svi_use:
             df =  df.merge(self.svi.copy(), how = 'left' , left_index = True, right_index =True)
+        print('sm')
+        print(sm.shape)
+        print(sm_all.shape)
         
+
         
-        sm = sm.reset_index()
-        sm['geoid'] = sm['geoid'].str[2:]
-        sm['tract'] = sm['geoid'].str[:-1]
-        sm.set_index('geoid', inplace =  True)
-        sm_all = sm.copy()
-        sm = sm[ sm['geography'].isin(['tract','block_group']) ].copy()
-        
-        rd = self.create_rurality_data(sm,data_path, True)
-        rd_all = self.create_rurality_data(sm_all, data_path)
+        rd = self.create_rurality_data(sm,data_path, level, True)
+        rd_all = self.create_rurality_data(sm_all, data_path, level)
         
         if self.svi_use:
             rd = rd['Population Density (per square mile), 2010'].to_frame()
             rd_all = rd_all['Population Density (per square mile), 2010'].to_frame()
-            
 
-        acs_pop = self.acs_pop#[self.acs_pop['tot_population'] >= 50 ] 
-        rd = rd.filter(acs_pop.index, axis= 0)
-        
+        acs = self.acs#[self.acs_pop['tot_population'] >= 50 ] 
+        rd = rd.filter(acs.index, axis= 0)
+
         mdl,X_test,y_test = self.trainXGB(X = rd, df = df, y = sm, predict = 'Presence', modeltype= 'XGBoost')
-        
+
         predictions = mdl.predict(rd_all.merge(df,how = 'left', left_index = True, right_index = True) )
 
         sm_all['Predictions'] =np.clip(predictions,0,100)  
         
-        sm_all.loc[:,['num_surveys','geography',
+        if level == 'block_group':
+            sm_all.loc[:,['num_surveys','geography',
               'detectors_found_prc',
               'detectors_working_prc',
               'Predictions'] ]
+        else:
+            sm_all.loc[:,['num_surveys',
+              'detectors_found_prc',
+              'detectors_working_prc',
+              'Predictions'] ]            
         sm_all = sm_all.merge(rd_all['Population Density (per square mile), 2010'],how = 'left',left_index = True,right_index = True)
-         
+        self.rd = rd
+        self.rd_all = rd_all
+        self.sm_all = sm_all
         return sm_all
     
     def trainXGB(self, X, df, y, predict, modeltype):
@@ -449,7 +475,8 @@ def trainXGB(self, X, df, y, predict, modeltype):
        if not df.empty:
            X = X.merge(df, how ='left',left_index = True, right_index = True)
            y = y.filter(X.index)
-   
+
+    
        # Create 80/20 training/testing set split
        X_train, X_test, y_train, y_test = train_test_split(X, y,test_size = .2, random_state = 0 )
        model = model.fit(X_train,y_train)
@@ -485,18 +512,43 @@ def trainXGB(self, X, df, y, predict, modeltype):
 
         
         
-    def create_rurality_data(self, sm, data_path, subset_county = False): 
+    def create_rurality_data(self, sm, data_path, level = 'block_group', subset_county = False): 
         #Rurality Data Munging 
         rd = pd.read_csv( data_path/'Master Project Data'/'Tract Rurality Data.csv', dtype = {'Tract':'object'},encoding = 'latin-1' )
         rd['Population Density (per square mile), 2010'] =  rd['Population Density (per square mile), 2010'].str.replace(',','').astype('float')
         rd['Tract'] = rd['Tract'].str[2:]
-        rd = rd.iloc[:,[0,2,4,6,8]]
-        block_tract = sm['tract'].to_frame()
-        block_tract = block_tract.reset_index()
-        rd = block_tract.merge(rd, how = 'left', left_on = 'tract' , right_on ='Tract')
-        rd.set_index('geoid',inplace= True)
-        rd = rd.iloc[:,2:]
-        rd['Select State'] = rd['Select State'].astype('category')
+        if level == 'block_group' or level == 'tract':
+            rd = rd.iloc[:,[0,2,4,6,8]]
+            if level == 'tract':
+                sm['tract'] = sm.index
+            block_tract = sm['tract'].to_frame()
+            block_tract = block_tract.reset_index()
+            rd = block_tract.merge(rd, how = 'left', left_on = 'tract' , right_on ='Tract')
+            rd.set_index('geoid',inplace= True)
+            rd = rd.iloc[:,2:]
+            rd['Select State'] = rd['Select State'].astype('category')
+            self.rd_bg = rd
+        else:
+            rd['county_id'] = rd['Tract'].str[:-6]
+            rd['Tract Population, 2010'] = rd['Tract Population, 2010'].str.replace(',', '')
+            rd['Tract Population, 2010'] = rd['Tract Population, 2010'].astype(float)
+            rd['Land Area (square miles), 2010'] = rd['Land Area (square miles), 2010'].str.replace(',', '')
+            rd['Land Area (square miles), 2010'] = rd['Land Area (square miles), 2010'].astype(float)
+            rd_stats = rd.groupby('county_id')[['Tract Population, 2010', 'Land Area (square miles), 2010']].sum()
+            #rd_state = rd.groupby('county_id')['Select State'].count()
+            rd_stats['Population Density (per square mile), 2010'] = rd_stats['Tract Population, 2010']/rd_stats['Land Area (square miles), 2010']
+            self.rd_stats = rd_stats
+            
+            rd_state = rd.groupby('county_id')['Select State'].agg(pd.Series.mode).to_frame()
+            self.rd_sate =rd_state
+            rd = rd_stats.merge(rd_state, how = 'left', left_index = True, right_index = True)
+            rd = rd.rename(index  = {'county_id': 'geoid'})
+            rd['geoid'] = rd.index
+            rd['Select State'] = rd['Select State'].astype('category')
+            rd = rd.filter(sm.index, axis= 0)
+            rd = rd.reindex(sm.index)
+            rd = rd.drop(columns = ['geoid'])
+            self.rd = rd
 
         # add state level model estimates 
         sms = pd.rd = pd.read_csv( data_path /'Model Outputs'/'Smoke_Alarm_Single_Level'/ 'SmokeAlarmModelState.csv')
@@ -504,7 +556,7 @@ def create_rurality_data(self, sm, data_path, subset_county = False):
         sms =  sms.loc[:,['geoid','detectors_found_prc']]
         sms = sms.rename(columns= {'geoid':'state_geoid'}  )
 
-        rd['state_geoid'] = rd.index.str[:2]
+        rd['state_geoid'] = rd.index.astype('string').str[:2]
         rd = rd.reset_index()
         rd = rd.merge(sms,how = 'left', on = 'state_geoid' )
         rd.drop('state_geoid',axis = 1,inplace = True)
@@ -528,9 +580,8 @@ def create_rurality_data(self, sm, data_path, subset_county = False):
         rd = rd.set_index('geoid')
   #  rd['RUCA_rurality_index'] = rd['Primary RUCA Code 2010']
   #  rd[rd['RUCA_rurality_index'] > 10 ] = np.NaN
-        rd = rd.iloc[:,3:]
+        rd = rd[['Population Density (per square mile), 2010', 'state_detectors_found_prc', 'county_detectors_found_prc']]
         self.rd = rd
-
         return rd 
         
         
@@ -571,11 +622,11 @@ def createSingleLevelSmokeAlarmModel(self,geo_level):
 #        _prc  - indicates percentage: (_total / num_surveys * 100)
 #
         df = self.arc.copy()
-        acs = self.acs.copy()
+        acs_totpop = self.acs_pop.copy()
         # dict with relevant length of GEOID for tract geography
         geo_level_dict = {'State':2,'County':5,'Tract':11,'Block_Group':12}
         df['geoid'] = df['geoid'].str[: geo_level_dict[geo_level]]
-        acs.index =  acs.index.str[:geo_level_dict[geo_level]]
+        acs_totpop.index =  acs_totpop.index.str[:geo_level_dict[geo_level]]
         #acs.drop_duplicates(inplace = True) #why drop duplicates?
         ## binarize pre_existing_alarms and _tested_and_working
         #  values will now be: 0 if no detectors present and 1 if any number were present
@@ -633,7 +684,7 @@ def createSingleLevelSmokeAlarmModel(self,geo_level):
         detectors = detectors[column_order]
         detectors = detectors[~pd.isna(detectors.index)]
     # fix block model to ensure blocks that weren't visited are added to the model 
-        detectors = detectors.reindex(detectors.index.union(acs.index.unique()),fill_value = 0)
+        detectors = detectors.reindex(detectors.index.union(acs_totpop.index.unique()),fill_value = 0)
         detectors = detectors[~pd.isna(detectors.index)]
 
     
@@ -647,6 +698,10 @@ def createMultiLevelSmokeAlarmModel(self):
 
         if 'Block_Group' not in self.models.keys():
             self.createSingleLevelSmokeAlarmModel(self,'Block_Group') 
+            
+        if 'MultiLevel' in self.models.keys():
+            print('already trained')
+            return
 
         block_data = self.models['Block_Group'].copy()
         all_IDS = block_data.index
diff --git a/src/utils.py b/src/utils.py
index b901ed0..4f9029b 100644
--- a/src/utils.py
+++ b/src/utils.py
@@ -35,6 +35,7 @@
     "raw": ROOT / "Data" / "raw",
     "interim": ROOT / "Data" / 'interim',
     "master": ROOT / "Data" / "Master Project Data",
+    "logging": ROOT / 'Data' / 'Logs',
     "model-outputs": ROOT / "Data" / "Model Outputs",
     "processed": ROOT / "Data" / "processed",
     "shapefiles": ROOT / "Data" / "03_Shapefiles",
@@ -43,7 +44,7 @@
     'acs' : ROOT /'Data' / 'Model Outputs' / 'ACS_Extraction' ,
     'svi' : ROOT/'Data' / 'Master Project Data',
     'map-outputs' : ROOT/"Data"/"Map Outputs"
-}
+    }
 
 
 GEOID = { 
diff --git a/testScript.ipynb b/testScript.ipynb
index 74db353..21a32f0 100644
--- a/testScript.ipynb
+++ b/testScript.ipynb
@@ -85,7 +85,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -167,7 +167,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-08-02 21:30:25.202058\n"
+      "2022-08-15 21:07:52.118509\n"
      ]
     }
    ],
@@ -206,295 +206,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "ACS =  DataLoaders.ACSData(2016,'block_group')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "NFIRS = DataLoaders.NFIRSData('block_group',ACS.tot_pop)\n",
-    "NFIRS_Sev = DataLoaders.NFIRSData('block_group',ACS.tot_pop,sev=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "FSM =  FireRiskModels('severity')\n",
-    "FPM =  FireRiskModels('propensity')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "## Fire Propensity Model"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Predicting 2017:\n"
-     ]
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "**Confusion Matrix**"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[[159423  46995]\n",
-      " [  2319   9002]]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "**ROC AUC Score** = 0.8671176533418194"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "**Classication Report**"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "              precision    recall  f1-score   support\n",
-      "\n",
-      "       False       0.99      0.77      0.87    206418\n",
-      "        True       0.16      0.80      0.27     11321\n",
-      "\n",
-      "    accuracy                           0.77    217739\n",
-      "   macro avg       0.57      0.78      0.57    217739\n",
-      "weighted avg       0.94      0.77      0.83    217739\n",
-      "\n"
-     ]
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "**Feature Ranking**"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "1. Max (0.427508)\n",
-      "2. Median (0.136157)\n",
-      "3. pct_alt_heat (0.082652)\n",
-      "4. house_pct_live_alone (0.077553)\n",
-      "5. inc_pct_poverty (0.072500)\n",
-      "6. race_pct_black_or_amind (0.069879)\n",
-      "7. house_yr_pct_before_1960 (0.068611)\n",
-      "8. did_not_work_past_12_mo (0.065140)\n"
-     ]
-    }
-   ],
-   "source": [
-    "display(Markdown('## Fire Propensity Model'))\n",
-    "\n",
-    "FPM.train(NFIRS,ACS,ACS_cols_to_use)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "## Fire Severity Model"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Predicting 2017:\n"
-     ]
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "**Confusion Matrix**"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[[163538  50467]\n",
-      " [  1023   2711]]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "**ROC AUC Score** = 0.8247673226252403"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "**Classication Report**"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "              precision    recall  f1-score   support\n",
-      "\n",
-      "       False       0.99      0.76      0.86    214005\n",
-      "        True       0.05      0.73      0.10      3734\n",
-      "\n",
-      "    accuracy                           0.76    217739\n",
-      "   macro avg       0.52      0.75      0.48    217739\n",
-      "weighted avg       0.98      0.76      0.85    217739\n",
-      "\n"
-     ]
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "**Feature Ranking**"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "1. Median (0.355454)\n",
-      "2. Max (0.195376)\n",
-      "3. pct_alt_heat (0.077562)\n",
-      "4. race_pct_black_or_amind (0.077486)\n",
-      "5. house_pct_live_alone (0.076930)\n",
-      "6. did_not_work_past_12_mo (0.074547)\n",
-      "7. house_yr_pct_before_1960 (0.072959)\n",
-      "8. inc_pct_poverty (0.069686)\n"
-     ]
-    }
-   ],
-   "source": [
-    "display(Markdown('## Fire Severity Model'))\n",
-    "\n",
-    "FSM.train(NFIRS_Sev,ACS,ACS_cols_to_use)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "ARC =  DataLoaders.ARCPData(ACS)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 3,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -522,149 +234,173 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>geoid</th>\n",
-       "      <th>census_block_group_y</th>\n",
-       "      <th>census_block_group_x</th>\n",
-       "      <th>city</th>\n",
        "      <th>state</th>\n",
-       "      <th>zip</th>\n",
-       "      <th>county</th>\n",
-       "      <th>in_home_visit_date</th>\n",
-       "      <th>smoke_alarms_installed__9_volt_10_year_dhh_</th>\n",
-       "      <th>10_year_and_9_volt_alarms_installed</th>\n",
+       "      <th>tot_population</th>\n",
+       "      <th>in_poverty</th>\n",
+       "      <th>inc_pct_poverty</th>\n",
+       "      <th>inc_pcincome</th>\n",
+       "      <th>race_pct_white</th>\n",
+       "      <th>race_pct_whitenh</th>\n",
+       "      <th>race_pct_nonwhite</th>\n",
+       "      <th>race_pct_nonwhitenh</th>\n",
+       "      <th>race_pct_black</th>\n",
        "      <th>...</th>\n",
-       "      <th>batteries_replaced</th>\n",
-       "      <th>fire_escape_plans_made</th>\n",
-       "      <th>fire_safety_checklists_completed</th>\n",
-       "      <th>additional_hazard_education_conducted</th>\n",
-       "      <th>additional_hazard_type</th>\n",
-       "      <th>people_served</th>\n",
-       "      <th>youth_served</th>\n",
-       "      <th>seniors_served</th>\n",
-       "      <th>veterans_military_members_and_military_family_members_served</th>\n",
-       "      <th>individuals_with_disabilities_access_or_functional_needs_served</th>\n",
+       "      <th>house_yr_pct_before_1960</th>\n",
+       "      <th>house_yr_pct_after_2000</th>\n",
+       "      <th>house_yr_pct_1960_2000</th>\n",
+       "      <th>house_val_less_50K</th>\n",
+       "      <th>house_val_50_100K</th>\n",
+       "      <th>house_val_100K_300K</th>\n",
+       "      <th>house_val_300K_500K</th>\n",
+       "      <th>house_val_more_500K</th>\n",
+       "      <th>race_pct_black_or_amind</th>\n",
+       "      <th>pct_alt_heat</th>\n",
        "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
        "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>010010205002</td>\n",
-       "      <td>32.470418</td>\n",
-       "      <td>-86.424166</td>\n",
-       "      <td>PRATTVILLE</td>\n",
+       "      <th>GEOID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>010010201001</th>\n",
        "      <td>AL</td>\n",
-       "      <td>36066</td>\n",
-       "      <td>Autauga</td>\n",
-       "      <td>9/9/2016</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>None</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>745.0</td>\n",
+       "      <td>143.0</td>\n",
+       "      <td>0.191946</td>\n",
+       "      <td>20365.0</td>\n",
+       "      <td>0.785235</td>\n",
+       "      <td>0.763758</td>\n",
+       "      <td>0.214765</td>\n",
+       "      <td>0.236242</td>\n",
+       "      <td>0.214765</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.221831</td>\n",
+       "      <td>0.193662</td>\n",
+       "      <td>0.584507</td>\n",
+       "      <td>0.152047</td>\n",
+       "      <td>0.274854</td>\n",
+       "      <td>0.508772</td>\n",
+       "      <td>0.064327</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.214765</td>\n",
+       "      <td>0.017606</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>010010208012</td>\n",
-       "      <td>32.455173</td>\n",
-       "      <td>-86.534590</td>\n",
-       "      <td>PRATTVILLE</td>\n",
+       "      <th>010010201002</th>\n",
        "      <td>AL</td>\n",
-       "      <td>36067</td>\n",
-       "      <td>Autauga</td>\n",
-       "      <td>9/30/2019</td>\n",
-       "      <td>2</td>\n",
-       "      <td>2</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Tornadoes</td>\n",
-       "      <td>5</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
+       "      <td>1265.0</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>0.044269</td>\n",
+       "      <td>33336.0</td>\n",
+       "      <td>0.856126</td>\n",
+       "      <td>0.826877</td>\n",
+       "      <td>0.143874</td>\n",
+       "      <td>0.173123</td>\n",
+       "      <td>0.082213</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.079229</td>\n",
+       "      <td>0.085653</td>\n",
+       "      <td>0.835118</td>\n",
+       "      <td>0.100264</td>\n",
+       "      <td>0.153034</td>\n",
+       "      <td>0.538259</td>\n",
+       "      <td>0.174142</td>\n",
+       "      <td>0.034301</td>\n",
+       "      <td>0.082213</td>\n",
+       "      <td>0.032895</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>010010208021</td>\n",
-       "      <td>32.524822</td>\n",
-       "      <td>-86.573009</td>\n",
-       "      <td>PRATTVILLE</td>\n",
+       "      <th>010010202001</th>\n",
        "      <td>AL</td>\n",
-       "      <td>36067</td>\n",
-       "      <td>Autauga</td>\n",
-       "      <td>5/4/2019</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Other</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>955.0</td>\n",
+       "      <td>365.0</td>\n",
+       "      <td>0.382199</td>\n",
+       "      <td>17047.0</td>\n",
+       "      <td>0.376042</td>\n",
+       "      <td>0.376042</td>\n",
+       "      <td>0.623958</td>\n",
+       "      <td>0.623958</td>\n",
+       "      <td>0.591667</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.135678</td>\n",
+       "      <td>0.211055</td>\n",
+       "      <td>0.653266</td>\n",
+       "      <td>0.171053</td>\n",
+       "      <td>0.337719</td>\n",
+       "      <td>0.394737</td>\n",
+       "      <td>0.065789</td>\n",
+       "      <td>0.030702</td>\n",
+       "      <td>0.591667</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>010010208021</td>\n",
-       "      <td>32.524822</td>\n",
-       "      <td>-86.573009</td>\n",
-       "      <td>PRATTVILLE</td>\n",
+       "      <th>010010202002</th>\n",
        "      <td>AL</td>\n",
-       "      <td>36067</td>\n",
-       "      <td>Autauga</td>\n",
-       "      <td>9/27/2019</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Tornadoes</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>1059.0</td>\n",
+       "      <td>118.0</td>\n",
+       "      <td>0.111426</td>\n",
+       "      <td>21400.0</td>\n",
+       "      <td>0.497573</td>\n",
+       "      <td>0.488673</td>\n",
+       "      <td>0.502427</td>\n",
+       "      <td>0.511327</td>\n",
+       "      <td>0.461974</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.235772</td>\n",
+       "      <td>0.075203</td>\n",
+       "      <td>0.689024</td>\n",
+       "      <td>0.053691</td>\n",
+       "      <td>0.513423</td>\n",
+       "      <td>0.412752</td>\n",
+       "      <td>0.020134</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.461974</td>\n",
+       "      <td>0.019912</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>010010208023</td>\n",
-       "      <td>32.543983</td>\n",
-       "      <td>-86.492100</td>\n",
-       "      <td>PRATTVILLE</td>\n",
+       "      <th>010010203001</th>\n",
        "      <td>AL</td>\n",
-       "      <td>36067</td>\n",
-       "      <td>Autauga</td>\n",
-       "      <td>12/2/2017</td>\n",
-       "      <td>3</td>\n",
-       "      <td>3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>None</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>2364.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.042301</td>\n",
+       "      <td>23106.0</td>\n",
+       "      <td>0.626481</td>\n",
+       "      <td>0.626481</td>\n",
+       "      <td>0.373519</td>\n",
+       "      <td>0.373519</td>\n",
+       "      <td>0.217851</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.030303</td>\n",
+       "      <td>0.091887</td>\n",
+       "      <td>0.877810</td>\n",
+       "      <td>0.057522</td>\n",
+       "      <td>0.349558</td>\n",
+       "      <td>0.592920</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.227157</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -691,270 +427,246 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>862041</th>\n",
-       "      <td>560459513003</td>\n",
-       "      <td>43.843551</td>\n",
-       "      <td>-104.260073</td>\n",
-       "      <td>NEWCASTLE</td>\n",
+       "      <th>560459511001</th>\n",
        "      <td>WY</td>\n",
-       "      <td>82701</td>\n",
-       "      <td>Weston</td>\n",
-       "      <td>3/4/2017</td>\n",
-       "      <td>2</td>\n",
-       "      <td>2</td>\n",
+       "      <td>1457.0</td>\n",
+       "      <td>137.0</td>\n",
+       "      <td>0.094029</td>\n",
+       "      <td>33781.0</td>\n",
+       "      <td>0.950583</td>\n",
+       "      <td>0.929307</td>\n",
+       "      <td>0.049417</td>\n",
+       "      <td>0.070693</td>\n",
+       "      <td>0.000000</td>\n",
        "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Wildfires</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.308305</td>\n",
+       "      <td>0.121729</td>\n",
+       "      <td>0.569966</td>\n",
+       "      <td>0.089320</td>\n",
+       "      <td>0.114563</td>\n",
+       "      <td>0.666019</td>\n",
+       "      <td>0.091262</td>\n",
+       "      <td>0.038835</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.366569</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>862042</th>\n",
-       "      <td>560459513003</td>\n",
-       "      <td>43.843551</td>\n",
-       "      <td>-104.260073</td>\n",
-       "      <td>NEWCASTLE</td>\n",
+       "      <th>560459511002</th>\n",
        "      <td>WY</td>\n",
-       "      <td>82701</td>\n",
-       "      <td>Weston</td>\n",
-       "      <td>3/4/2017</td>\n",
-       "      <td>3</td>\n",
-       "      <td>3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Wildfires</td>\n",
-       "      <td>4</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>1582.0</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>0.062579</td>\n",
+       "      <td>34002.0</td>\n",
+       "      <td>0.935884</td>\n",
+       "      <td>0.918642</td>\n",
+       "      <td>0.064116</td>\n",
+       "      <td>0.081358</td>\n",
+       "      <td>0.009698</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.197500</td>\n",
+       "      <td>0.337500</td>\n",
+       "      <td>0.465000</td>\n",
+       "      <td>0.123438</td>\n",
+       "      <td>0.079687</td>\n",
+       "      <td>0.525000</td>\n",
+       "      <td>0.232812</td>\n",
+       "      <td>0.039062</td>\n",
+       "      <td>0.014547</td>\n",
+       "      <td>0.825737</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>862043</th>\n",
-       "      <td>560459513003</td>\n",
-       "      <td>43.843551</td>\n",
-       "      <td>-104.260073</td>\n",
-       "      <td>NEWCASTLE</td>\n",
+       "      <th>560459513001</th>\n",
        "      <td>WY</td>\n",
-       "      <td>82701</td>\n",
-       "      <td>Weston</td>\n",
-       "      <td>3/4/2017</td>\n",
-       "      <td>3</td>\n",
-       "      <td>3</td>\n",
+       "      <td>1151.0</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>0.261512</td>\n",
+       "      <td>23326.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Wildfires</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
+       "      <td>0.556757</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.443243</td>\n",
+       "      <td>0.229282</td>\n",
+       "      <td>0.303867</td>\n",
+       "      <td>0.466851</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.105163</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>862044</th>\n",
-       "      <td>560459513003</td>\n",
-       "      <td>43.843551</td>\n",
-       "      <td>-104.260073</td>\n",
-       "      <td>NEWCASTLE</td>\n",
+       "      <th>560459513002</th>\n",
        "      <td>WY</td>\n",
-       "      <td>82701</td>\n",
-       "      <td>Weston</td>\n",
-       "      <td>3/4/2017</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
+       "      <td>1030.0</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>0.098058</td>\n",
+       "      <td>31463.0</td>\n",
+       "      <td>0.982014</td>\n",
+       "      <td>0.976619</td>\n",
+       "      <td>0.017986</td>\n",
+       "      <td>0.023381</td>\n",
+       "      <td>0.000000</td>\n",
        "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Wildfires</td>\n",
-       "      <td>3</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.595122</td>\n",
+       "      <td>0.136585</td>\n",
+       "      <td>0.268293</td>\n",
+       "      <td>0.164773</td>\n",
+       "      <td>0.127841</td>\n",
+       "      <td>0.508523</td>\n",
+       "      <td>0.198864</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.244165</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>862056</th>\n",
-       "      <td>560459513003</td>\n",
-       "      <td>43.843551</td>\n",
-       "      <td>-104.260073</td>\n",
-       "      <td>NEWCASTLE</td>\n",
+       "      <th>560459513003</th>\n",
        "      <td>WY</td>\n",
-       "      <td>82701</td>\n",
-       "      <td>Weston</td>\n",
-       "      <td>6/28/2019</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
+       "      <td>1599.0</td>\n",
+       "      <td>364.0</td>\n",
+       "      <td>0.227642</td>\n",
+       "      <td>23422.0</td>\n",
+       "      <td>0.826141</td>\n",
+       "      <td>0.826141</td>\n",
+       "      <td>0.173859</td>\n",
+       "      <td>0.173859</td>\n",
+       "      <td>0.000000</td>\n",
        "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Tornadoes</td>\n",
-       "      <td>5</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2</td>\n",
+       "      <td>0.292758</td>\n",
+       "      <td>0.107858</td>\n",
+       "      <td>0.599384</td>\n",
+       "      <td>0.162011</td>\n",
+       "      <td>0.108007</td>\n",
+       "      <td>0.649907</td>\n",
+       "      <td>0.080074</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.119808</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>537981 rows × 23 columns</p>\n",
+       "<p>216027 rows × 106 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "               geoid  census_block_group_y  census_block_group_x        city  \\\n",
-       "12      010010205002             32.470418            -86.424166  PRATTVILLE   \n",
-       "18      010010208012             32.455173            -86.534590  PRATTVILLE   \n",
-       "23      010010208021             32.524822            -86.573009  PRATTVILLE   \n",
-       "24      010010208021             32.524822            -86.573009  PRATTVILLE   \n",
-       "27      010010208023             32.543983            -86.492100  PRATTVILLE   \n",
-       "...              ...                   ...                   ...         ...   \n",
-       "862041  560459513003             43.843551           -104.260073   NEWCASTLE   \n",
-       "862042  560459513003             43.843551           -104.260073   NEWCASTLE   \n",
-       "862043  560459513003             43.843551           -104.260073   NEWCASTLE   \n",
-       "862044  560459513003             43.843551           -104.260073   NEWCASTLE   \n",
-       "862056  560459513003             43.843551           -104.260073   NEWCASTLE   \n",
-       "\n",
-       "       state    zip   county in_home_visit_date  \\\n",
-       "12        AL  36066  Autauga           9/9/2016   \n",
-       "18        AL  36067  Autauga          9/30/2019   \n",
-       "23        AL  36067  Autauga           5/4/2019   \n",
-       "24        AL  36067  Autauga          9/27/2019   \n",
-       "27        AL  36067  Autauga          12/2/2017   \n",
-       "...      ...    ...      ...                ...   \n",
-       "862041    WY  82701   Weston           3/4/2017   \n",
-       "862042    WY  82701   Weston           3/4/2017   \n",
-       "862043    WY  82701   Weston           3/4/2017   \n",
-       "862044    WY  82701   Weston           3/4/2017   \n",
-       "862056    WY  82701   Weston          6/28/2019   \n",
-       "\n",
-       "        smoke_alarms_installed__9_volt_10_year_dhh_  \\\n",
-       "12                                                1   \n",
-       "18                                                2   \n",
-       "23                                                3   \n",
-       "24                                                1   \n",
-       "27                                                3   \n",
-       "...                                             ...   \n",
-       "862041                                            2   \n",
-       "862042                                            3   \n",
-       "862043                                            3   \n",
-       "862044                                            4   \n",
-       "862056                                            4   \n",
+       "             state  tot_population  in_poverty  inc_pct_poverty  inc_pcincome  \\\n",
+       "GEOID                                                                           \n",
+       "010010201001    AL           745.0       143.0         0.191946       20365.0   \n",
+       "010010201002    AL          1265.0        56.0         0.044269       33336.0   \n",
+       "010010202001    AL           955.0       365.0         0.382199       17047.0   \n",
+       "010010202002    AL          1059.0       118.0         0.111426       21400.0   \n",
+       "010010203001    AL          2364.0       100.0         0.042301       23106.0   \n",
+       "...            ...             ...         ...              ...           ...   \n",
+       "560459511001    WY          1457.0       137.0         0.094029       33781.0   \n",
+       "560459511002    WY          1582.0        99.0         0.062579       34002.0   \n",
+       "560459513001    WY          1151.0       301.0         0.261512       23326.0   \n",
+       "560459513002    WY          1030.0       101.0         0.098058       31463.0   \n",
+       "560459513003    WY          1599.0       364.0         0.227642       23422.0   \n",
        "\n",
-       "        10_year_and_9_volt_alarms_installed  ...  batteries_replaced  \\\n",
-       "12                                        1  ...                   0   \n",
-       "18                                        2  ...                   0   \n",
-       "23                                        2  ...                   0   \n",
-       "24                                        1  ...                   0   \n",
-       "27                                        3  ...                   0   \n",
-       "...                                     ...  ...                 ...   \n",
-       "862041                                    2  ...                   0   \n",
-       "862042                                    3  ...                   0   \n",
-       "862043                                    3  ...                   0   \n",
-       "862044                                    4  ...                   0   \n",
-       "862056                                    4  ...                   0   \n",
+       "              race_pct_white  race_pct_whitenh  race_pct_nonwhite  \\\n",
+       "GEOID                                                               \n",
+       "010010201001        0.785235          0.763758           0.214765   \n",
+       "010010201002        0.856126          0.826877           0.143874   \n",
+       "010010202001        0.376042          0.376042           0.623958   \n",
+       "010010202002        0.497573          0.488673           0.502427   \n",
+       "010010203001        0.626481          0.626481           0.373519   \n",
+       "...                      ...               ...                ...   \n",
+       "560459511001        0.950583          0.929307           0.049417   \n",
+       "560459511002        0.935884          0.918642           0.064116   \n",
+       "560459513001        1.000000          1.000000           0.000000   \n",
+       "560459513002        0.982014          0.976619           0.017986   \n",
+       "560459513003        0.826141          0.826141           0.173859   \n",
        "\n",
-       "        fire_escape_plans_made  fire_safety_checklists_completed  \\\n",
-       "12                           1                                 1   \n",
-       "18                           1                                 1   \n",
-       "23                           1                                 1   \n",
-       "24                           1                                 1   \n",
-       "27                           1                                 1   \n",
-       "...                        ...                               ...   \n",
-       "862041                       1                                 1   \n",
-       "862042                       1                                 1   \n",
-       "862043                       1                                 1   \n",
-       "862044                       1                                 1   \n",
-       "862056                       1                                 1   \n",
+       "              race_pct_nonwhitenh  race_pct_black  ...  \\\n",
+       "GEOID                                              ...   \n",
+       "010010201001             0.236242        0.214765  ...   \n",
+       "010010201002             0.173123        0.082213  ...   \n",
+       "010010202001             0.623958        0.591667  ...   \n",
+       "010010202002             0.511327        0.461974  ...   \n",
+       "010010203001             0.373519        0.217851  ...   \n",
+       "...                           ...             ...  ...   \n",
+       "560459511001             0.070693        0.000000  ...   \n",
+       "560459511002             0.081358        0.009698  ...   \n",
+       "560459513001             0.000000        0.000000  ...   \n",
+       "560459513002             0.023381        0.000000  ...   \n",
+       "560459513003             0.173859        0.000000  ...   \n",
        "\n",
-       "        additional_hazard_education_conducted  additional_hazard_type  \\\n",
-       "12                                          0                    None   \n",
-       "18                                          1               Tornadoes   \n",
-       "23                                          1                   Other   \n",
-       "24                                          1               Tornadoes   \n",
-       "27                                          0                    None   \n",
-       "...                                       ...                     ...   \n",
-       "862041                                      1               Wildfires   \n",
-       "862042                                      1               Wildfires   \n",
-       "862043                                      1               Wildfires   \n",
-       "862044                                      1               Wildfires   \n",
-       "862056                                      1               Tornadoes   \n",
+       "              house_yr_pct_before_1960  house_yr_pct_after_2000  \\\n",
+       "GEOID                                                             \n",
+       "010010201001                  0.221831                 0.193662   \n",
+       "010010201002                  0.079229                 0.085653   \n",
+       "010010202001                  0.135678                 0.211055   \n",
+       "010010202002                  0.235772                 0.075203   \n",
+       "010010203001                  0.030303                 0.091887   \n",
+       "...                                ...                      ...   \n",
+       "560459511001                  0.308305                 0.121729   \n",
+       "560459511002                  0.197500                 0.337500   \n",
+       "560459513001                  0.556757                 0.000000   \n",
+       "560459513002                  0.595122                 0.136585   \n",
+       "560459513003                  0.292758                 0.107858   \n",
        "\n",
-       "        people_served  youth_served seniors_served  \\\n",
-       "12                  2             0              0   \n",
-       "18                  5             0              0   \n",
-       "23                  1             0              0   \n",
-       "24                  1             0              0   \n",
-       "27                  1             0              0   \n",
-       "...               ...           ...            ...   \n",
-       "862041              1             0              0   \n",
-       "862042              4             2              0   \n",
-       "862043              2             0              1   \n",
-       "862044              3             0              0   \n",
-       "862056              5             1              0   \n",
+       "              house_yr_pct_1960_2000  house_val_less_50K  house_val_50_100K  \\\n",
+       "GEOID                                                                         \n",
+       "010010201001                0.584507            0.152047           0.274854   \n",
+       "010010201002                0.835118            0.100264           0.153034   \n",
+       "010010202001                0.653266            0.171053           0.337719   \n",
+       "010010202002                0.689024            0.053691           0.513423   \n",
+       "010010203001                0.877810            0.057522           0.349558   \n",
+       "...                              ...                 ...                ...   \n",
+       "560459511001                0.569966            0.089320           0.114563   \n",
+       "560459511002                0.465000            0.123438           0.079687   \n",
+       "560459513001                0.443243            0.229282           0.303867   \n",
+       "560459513002                0.268293            0.164773           0.127841   \n",
+       "560459513003                0.599384            0.162011           0.108007   \n",
        "\n",
-       "        veterans_military_members_and_military_family_members_served  \\\n",
-       "12                                                      0              \n",
-       "18                                                      1              \n",
-       "23                                                      0              \n",
-       "24                                                      0              \n",
-       "27                                                      0              \n",
-       "...                                                   ...              \n",
-       "862041                                                  0              \n",
-       "862042                                                  0              \n",
-       "862043                                                  0              \n",
-       "862044                                                  0              \n",
-       "862056                                                  0              \n",
+       "              house_val_100K_300K  house_val_300K_500K  house_val_more_500K  \\\n",
+       "GEOID                                                                         \n",
+       "010010201001             0.508772             0.064327             0.000000   \n",
+       "010010201002             0.538259             0.174142             0.034301   \n",
+       "010010202001             0.394737             0.065789             0.030702   \n",
+       "010010202002             0.412752             0.020134             0.000000   \n",
+       "010010203001             0.592920             0.000000             0.000000   \n",
+       "...                           ...                  ...                  ...   \n",
+       "560459511001             0.666019             0.091262             0.038835   \n",
+       "560459511002             0.525000             0.232812             0.039062   \n",
+       "560459513001             0.466851             0.000000             0.000000   \n",
+       "560459513002             0.508523             0.198864             0.000000   \n",
+       "560459513003             0.649907             0.080074             0.000000   \n",
        "\n",
-       "        individuals_with_disabilities_access_or_functional_needs_served  \n",
-       "12                                                      0                \n",
-       "18                                                      0                \n",
-       "23                                                      0                \n",
-       "24                                                      0                \n",
-       "27                                                      0                \n",
-       "...                                                   ...                \n",
-       "862041                                                  0                \n",
-       "862042                                                  0                \n",
-       "862043                                                  1                \n",
-       "862044                                                  0                \n",
-       "862056                                                  2                \n",
+       "              race_pct_black_or_amind  pct_alt_heat  \n",
+       "GEOID                                                \n",
+       "010010201001                 0.214765      0.017606  \n",
+       "010010201002                 0.082213      0.032895  \n",
+       "010010202001                 0.591667      0.000000  \n",
+       "010010202002                 0.461974      0.019912  \n",
+       "010010203001                 0.227157      0.000000  \n",
+       "...                               ...           ...  \n",
+       "560459511001                 0.000000      0.366569  \n",
+       "560459511002                 0.014547      0.825737  \n",
+       "560459513001                 0.000000      0.105163  \n",
+       "560459513002                 0.000000      0.244165  \n",
+       "560459513003                 0.000000      0.119808  \n",
        "\n",
-       "[537981 rows x 23 columns]"
+       "[216027 rows x 106 columns]"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "ARC.data"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Smoke Alarm Models"
+    "#DataLoaders.ACSData(2016,'block_group')- second parameter is level\n",
+    "ACS =  DataLoaders.ACSData(2016,'block_group', pop_thresh = 50)\n",
+    "ACS.data"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 4,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -982,14 +694,46 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>state</th>\n",
+       "      <th>tot_population</th>\n",
+       "      <th>in_poverty</th>\n",
        "      <th>inc_pct_poverty</th>\n",
-       "      <th>RPL_THEME1</th>\n",
-       "      <th>RPL_THEME2</th>\n",
-       "      <th>RPL_THEME3</th>\n",
-       "      <th>RPL_THEME4</th>\n",
+       "      <th>inc_pcincome</th>\n",
+       "      <th>race_pct_white</th>\n",
+       "      <th>race_pct_whitenh</th>\n",
+       "      <th>race_pct_nonwhite</th>\n",
+       "      <th>race_pct_nonwhitenh</th>\n",
+       "      <th>race_pct_black</th>\n",
+       "      <th>...</th>\n",
+       "      <th>house_yr_pct_before_1960</th>\n",
+       "      <th>house_yr_pct_after_2000</th>\n",
+       "      <th>house_yr_pct_1960_2000</th>\n",
+       "      <th>house_val_less_50K</th>\n",
+       "      <th>house_val_50_100K</th>\n",
+       "      <th>house_val_100K_300K</th>\n",
+       "      <th>house_val_300K_500K</th>\n",
+       "      <th>house_val_more_500K</th>\n",
+       "      <th>race_pct_black_or_amind</th>\n",
+       "      <th>pct_alt_heat</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>geos</th>\n",
+       "      <th>GEOID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -999,44 +743,124 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>010010201001</th>\n",
-       "      <td>0.191946</td>\n",
-       "      <td>0.3913</td>\n",
-       "      <td>0.5597</td>\n",
-       "      <td>0.3735</td>\n",
-       "      <td>0.0993</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010201002</th>\n",
-       "      <td>0.044269</td>\n",
-       "      <td>0.3913</td>\n",
-       "      <td>0.5597</td>\n",
-       "      <td>0.3735</td>\n",
-       "      <td>0.0993</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010202001</th>\n",
-       "      <td>0.382199</td>\n",
-       "      <td>0.7065</td>\n",
-       "      <td>0.3585</td>\n",
-       "      <td>0.5821</td>\n",
-       "      <td>0.7299</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010202002</th>\n",
-       "      <td>0.111426</td>\n",
-       "      <td>0.7065</td>\n",
-       "      <td>0.3585</td>\n",
-       "      <td>0.5821</td>\n",
-       "      <td>0.7299</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010203001</th>\n",
-       "      <td>0.042301</td>\n",
-       "      <td>0.5659</td>\n",
-       "      <td>0.8729</td>\n",
-       "      <td>0.6429</td>\n",
-       "      <td>0.3882</td>\n",
+       "      <th>01001</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>54598.0</td>\n",
+       "      <td>6697.0</td>\n",
+       "      <td>0.122660</td>\n",
+       "      <td>26178.948423</td>\n",
+       "      <td>0.769551</td>\n",
+       "      <td>0.757760</td>\n",
+       "      <td>0.230449</td>\n",
+       "      <td>0.242240</td>\n",
+       "      <td>0.184333</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.075636</td>\n",
+       "      <td>0.294664</td>\n",
+       "      <td>0.629700</td>\n",
+       "      <td>0.144171</td>\n",
+       "      <td>0.192272</td>\n",
+       "      <td>0.564726</td>\n",
+       "      <td>0.085557</td>\n",
+       "      <td>0.013274</td>\n",
+       "      <td>0.188468</td>\n",
+       "      <td>0.117837</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01003</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>196640.0</td>\n",
+       "      <td>25551.0</td>\n",
+       "      <td>0.129938</td>\n",
+       "      <td>28156.409662</td>\n",
+       "      <td>0.864939</td>\n",
+       "      <td>0.832096</td>\n",
+       "      <td>0.135061</td>\n",
+       "      <td>0.167904</td>\n",
+       "      <td>0.092353</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.075916</td>\n",
+       "      <td>0.339992</td>\n",
+       "      <td>0.584092</td>\n",
+       "      <td>0.084371</td>\n",
+       "      <td>0.118950</td>\n",
+       "      <td>0.596030</td>\n",
+       "      <td>0.137575</td>\n",
+       "      <td>0.063074</td>\n",
+       "      <td>0.099022</td>\n",
+       "      <td>0.032655</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01005</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>23641.0</td>\n",
+       "      <td>6235.0</td>\n",
+       "      <td>0.263737</td>\n",
+       "      <td>18156.073939</td>\n",
+       "      <td>0.467411</td>\n",
+       "      <td>0.459066</td>\n",
+       "      <td>0.532589</td>\n",
+       "      <td>0.540934</td>\n",
+       "      <td>0.474980</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.192086</td>\n",
+       "      <td>0.106423</td>\n",
+       "      <td>0.701491</td>\n",
+       "      <td>0.245668</td>\n",
+       "      <td>0.287528</td>\n",
+       "      <td>0.396123</td>\n",
+       "      <td>0.044605</td>\n",
+       "      <td>0.026077</td>\n",
+       "      <td>0.476302</td>\n",
+       "      <td>0.134071</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01007</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>20603.0</td>\n",
+       "      <td>3390.0</td>\n",
+       "      <td>0.164539</td>\n",
+       "      <td>19864.397466</td>\n",
+       "      <td>0.800467</td>\n",
+       "      <td>0.780001</td>\n",
+       "      <td>0.199533</td>\n",
+       "      <td>0.219999</td>\n",
+       "      <td>0.181294</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.182902</td>\n",
+       "      <td>0.163843</td>\n",
+       "      <td>0.653255</td>\n",
+       "      <td>0.247900</td>\n",
+       "      <td>0.261379</td>\n",
+       "      <td>0.436218</td>\n",
+       "      <td>0.051768</td>\n",
+       "      <td>0.002735</td>\n",
+       "      <td>0.184966</td>\n",
+       "      <td>0.172957</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01009</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>57099.0</td>\n",
+       "      <td>9441.0</td>\n",
+       "      <td>0.165344</td>\n",
+       "      <td>21044.373614</td>\n",
+       "      <td>0.955075</td>\n",
+       "      <td>0.878016</td>\n",
+       "      <td>0.044925</td>\n",
+       "      <td>0.121984</td>\n",
+       "      <td>0.015184</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.159539</td>\n",
+       "      <td>0.215849</td>\n",
+       "      <td>0.624612</td>\n",
+       "      <td>0.162052</td>\n",
+       "      <td>0.214839</td>\n",
+       "      <td>0.540544</td>\n",
+       "      <td>0.062508</td>\n",
+       "      <td>0.020057</td>\n",
+       "      <td>0.018690</td>\n",
+       "      <td>0.145933</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -1045,83 +869,249 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>560459511001</th>\n",
-       "      <td>0.094029</td>\n",
-       "      <td>0.3925</td>\n",
-       "      <td>0.6370</td>\n",
-       "      <td>0.2331</td>\n",
-       "      <td>0.8555</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>560459511002</th>\n",
-       "      <td>0.062579</td>\n",
-       "      <td>0.3925</td>\n",
-       "      <td>0.6370</td>\n",
-       "      <td>0.2331</td>\n",
-       "      <td>0.8555</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>560459513001</th>\n",
-       "      <td>0.261512</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.6043</td>\n",
-       "      <td>0.2862</td>\n",
-       "      <td>0.6949</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>560459513002</th>\n",
-       "      <td>0.098058</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.6043</td>\n",
-       "      <td>0.2862</td>\n",
-       "      <td>0.6949</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>560459513003</th>\n",
-       "      <td>0.227642</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.6043</td>\n",
-       "      <td>0.2862</td>\n",
-       "      <td>0.6949</td>\n",
+       "      <th>56037</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>44166.0</td>\n",
+       "      <td>4868.0</td>\n",
+       "      <td>0.110221</td>\n",
+       "      <td>30960.831884</td>\n",
+       "      <td>0.922428</td>\n",
+       "      <td>0.799483</td>\n",
+       "      <td>0.077572</td>\n",
+       "      <td>0.200517</td>\n",
+       "      <td>0.008978</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.208355</td>\n",
+       "      <td>0.194901</td>\n",
+       "      <td>0.596744</td>\n",
+       "      <td>0.185093</td>\n",
+       "      <td>0.065700</td>\n",
+       "      <td>0.587961</td>\n",
+       "      <td>0.138653</td>\n",
+       "      <td>0.022595</td>\n",
+       "      <td>0.017486</td>\n",
+       "      <td>0.036412</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56039</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>22524.0</td>\n",
+       "      <td>1650.0</td>\n",
+       "      <td>0.073255</td>\n",
+       "      <td>46535.314731</td>\n",
+       "      <td>0.926700</td>\n",
+       "      <td>0.811996</td>\n",
+       "      <td>0.073300</td>\n",
+       "      <td>0.188004</td>\n",
+       "      <td>0.007442</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.090506</td>\n",
+       "      <td>0.211481</td>\n",
+       "      <td>0.698014</td>\n",
+       "      <td>0.041309</td>\n",
+       "      <td>0.015394</td>\n",
+       "      <td>0.183359</td>\n",
+       "      <td>0.081645</td>\n",
+       "      <td>0.678293</td>\n",
+       "      <td>0.011651</td>\n",
+       "      <td>0.164296</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56041</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>20658.0</td>\n",
+       "      <td>3462.0</td>\n",
+       "      <td>0.167586</td>\n",
+       "      <td>25676.949269</td>\n",
+       "      <td>0.943053</td>\n",
+       "      <td>0.877808</td>\n",
+       "      <td>0.056947</td>\n",
+       "      <td>0.122192</td>\n",
+       "      <td>0.001865</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.157961</td>\n",
+       "      <td>0.136405</td>\n",
+       "      <td>0.705634</td>\n",
+       "      <td>0.152286</td>\n",
+       "      <td>0.063708</td>\n",
+       "      <td>0.619667</td>\n",
+       "      <td>0.138129</td>\n",
+       "      <td>0.026210</td>\n",
+       "      <td>0.011556</td>\n",
+       "      <td>0.161868</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56043</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>8174.0</td>\n",
+       "      <td>1198.0</td>\n",
+       "      <td>0.146562</td>\n",
+       "      <td>26347.252997</td>\n",
+       "      <td>0.906094</td>\n",
+       "      <td>0.822409</td>\n",
+       "      <td>0.093906</td>\n",
+       "      <td>0.177591</td>\n",
+       "      <td>0.008074</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.357649</td>\n",
+       "      <td>0.106534</td>\n",
+       "      <td>0.535817</td>\n",
+       "      <td>0.081029</td>\n",
+       "      <td>0.205453</td>\n",
+       "      <td>0.579877</td>\n",
+       "      <td>0.077573</td>\n",
+       "      <td>0.056068</td>\n",
+       "      <td>0.013690</td>\n",
+       "      <td>0.163470</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56045</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>6819.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>0.146942</td>\n",
+       "      <td>29288.308403</td>\n",
+       "      <td>0.931081</td>\n",
+       "      <td>0.921720</td>\n",
+       "      <td>0.068919</td>\n",
+       "      <td>0.078280</td>\n",
+       "      <td>0.002250</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.369926</td>\n",
+       "      <td>0.151801</td>\n",
+       "      <td>0.478273</td>\n",
+       "      <td>0.146717</td>\n",
+       "      <td>0.134248</td>\n",
+       "      <td>0.571904</td>\n",
+       "      <td>0.128429</td>\n",
+       "      <td>0.018703</td>\n",
+       "      <td>0.003375</td>\n",
+       "      <td>0.361200</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>217739 rows × 5 columns</p>\n",
+       "<p>3142 rows × 106 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "              inc_pct_poverty  RPL_THEME1  RPL_THEME2  RPL_THEME3  RPL_THEME4\n",
-       "geos                                                                         \n",
-       "010010201001         0.191946      0.3913      0.5597      0.3735      0.0993\n",
-       "010010201002         0.044269      0.3913      0.5597      0.3735      0.0993\n",
-       "010010202001         0.382199      0.7065      0.3585      0.5821      0.7299\n",
-       "010010202002         0.111426      0.7065      0.3585      0.5821      0.7299\n",
-       "010010203001         0.042301      0.5659      0.8729      0.6429      0.3882\n",
-       "...                       ...         ...         ...         ...         ...\n",
-       "560459511001         0.094029      0.3925      0.6370      0.2331      0.8555\n",
-       "560459511002         0.062579      0.3925      0.6370      0.2331      0.8555\n",
-       "560459513001         0.261512      0.5093      0.6043      0.2862      0.6949\n",
-       "560459513002         0.098058      0.5093      0.6043      0.2862      0.6949\n",
-       "560459513003         0.227642      0.5093      0.6043      0.2862      0.6949\n",
+       "      state  tot_population  in_poverty  inc_pct_poverty  inc_pcincome  \\\n",
+       "GEOID                                                                    \n",
+       "01001    AL         54598.0      6697.0         0.122660  26178.948423   \n",
+       "01003    AL        196640.0     25551.0         0.129938  28156.409662   \n",
+       "01005    AL         23641.0      6235.0         0.263737  18156.073939   \n",
+       "01007    AL         20603.0      3390.0         0.164539  19864.397466   \n",
+       "01009    AL         57099.0      9441.0         0.165344  21044.373614   \n",
+       "...     ...             ...         ...              ...           ...   \n",
+       "56037    WY         44166.0      4868.0         0.110221  30960.831884   \n",
+       "56039    WY         22524.0      1650.0         0.073255  46535.314731   \n",
+       "56041    WY         20658.0      3462.0         0.167586  25676.949269   \n",
+       "56043    WY          8174.0      1198.0         0.146562  26347.252997   \n",
+       "56045    WY          6819.0      1002.0         0.146942  29288.308403   \n",
+       "\n",
+       "       race_pct_white  race_pct_whitenh  race_pct_nonwhite  \\\n",
+       "GEOID                                                        \n",
+       "01001        0.769551          0.757760           0.230449   \n",
+       "01003        0.864939          0.832096           0.135061   \n",
+       "01005        0.467411          0.459066           0.532589   \n",
+       "01007        0.800467          0.780001           0.199533   \n",
+       "01009        0.955075          0.878016           0.044925   \n",
+       "...               ...               ...                ...   \n",
+       "56037        0.922428          0.799483           0.077572   \n",
+       "56039        0.926700          0.811996           0.073300   \n",
+       "56041        0.943053          0.877808           0.056947   \n",
+       "56043        0.906094          0.822409           0.093906   \n",
+       "56045        0.931081          0.921720           0.068919   \n",
+       "\n",
+       "       race_pct_nonwhitenh  race_pct_black  ...  house_yr_pct_before_1960  \\\n",
+       "GEOID                                       ...                             \n",
+       "01001             0.242240        0.184333  ...                  0.075636   \n",
+       "01003             0.167904        0.092353  ...                  0.075916   \n",
+       "01005             0.540934        0.474980  ...                  0.192086   \n",
+       "01007             0.219999        0.181294  ...                  0.182902   \n",
+       "01009             0.121984        0.015184  ...                  0.159539   \n",
+       "...                    ...             ...  ...                       ...   \n",
+       "56037             0.200517        0.008978  ...                  0.208355   \n",
+       "56039             0.188004        0.007442  ...                  0.090506   \n",
+       "56041             0.122192        0.001865  ...                  0.157961   \n",
+       "56043             0.177591        0.008074  ...                  0.357649   \n",
+       "56045             0.078280        0.002250  ...                  0.369926   \n",
+       "\n",
+       "       house_yr_pct_after_2000  house_yr_pct_1960_2000  house_val_less_50K  \\\n",
+       "GEOID                                                                        \n",
+       "01001                 0.294664                0.629700            0.144171   \n",
+       "01003                 0.339992                0.584092            0.084371   \n",
+       "01005                 0.106423                0.701491            0.245668   \n",
+       "01007                 0.163843                0.653255            0.247900   \n",
+       "01009                 0.215849                0.624612            0.162052   \n",
+       "...                        ...                     ...                 ...   \n",
+       "56037                 0.194901                0.596744            0.185093   \n",
+       "56039                 0.211481                0.698014            0.041309   \n",
+       "56041                 0.136405                0.705634            0.152286   \n",
+       "56043                 0.106534                0.535817            0.081029   \n",
+       "56045                 0.151801                0.478273            0.146717   \n",
        "\n",
-       "[217739 rows x 5 columns]"
+       "       house_val_50_100K  house_val_100K_300K  house_val_300K_500K  \\\n",
+       "GEOID                                                                \n",
+       "01001           0.192272             0.564726             0.085557   \n",
+       "01003           0.118950             0.596030             0.137575   \n",
+       "01005           0.287528             0.396123             0.044605   \n",
+       "01007           0.261379             0.436218             0.051768   \n",
+       "01009           0.214839             0.540544             0.062508   \n",
+       "...                  ...                  ...                  ...   \n",
+       "56037           0.065700             0.587961             0.138653   \n",
+       "56039           0.015394             0.183359             0.081645   \n",
+       "56041           0.063708             0.619667             0.138129   \n",
+       "56043           0.205453             0.579877             0.077573   \n",
+       "56045           0.134248             0.571904             0.128429   \n",
+       "\n",
+       "       house_val_more_500K  race_pct_black_or_amind  pct_alt_heat  \n",
+       "GEOID                                                              \n",
+       "01001             0.013274                 0.188468      0.117837  \n",
+       "01003             0.063074                 0.099022      0.032655  \n",
+       "01005             0.026077                 0.476302      0.134071  \n",
+       "01007             0.002735                 0.184966      0.172957  \n",
+       "01009             0.020057                 0.018690      0.145933  \n",
+       "...                    ...                      ...           ...  \n",
+       "56037             0.022595                 0.017486      0.036412  \n",
+       "56039             0.678293                 0.011651      0.164296  \n",
+       "56041             0.026210                 0.011556      0.161868  \n",
+       "56043             0.056068                 0.013690      0.163470  \n",
+       "56045             0.018703                 0.003375      0.361200  \n",
+       "\n",
+       "[3142 rows x 106 columns]"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "SVI =  DataLoaders.SVIData(ACS.data)\n",
-    "SVI.data"
+    "ACS_county = DataLoaders.ACSData(2016, 'county', pop_thresh = 50)\n",
+    "ACS_county.data"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 6,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -1129,30 +1119,68 @@
    },
    "outputs": [],
    "source": [
-    "Smoke = SmokeAlarmModels()"
+    "#include level \n",
+    "NFIRS_county = DataLoaders.NFIRSData('county',ACS_county.tot_pop, pop_thresh = 50)\n",
+    "NFIRS_Sev_county = DataLoaders.NFIRSData('county',ACS_county.tot_pop,pop_thresh = 50, sev=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 5,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "#include level \n",
+    "NFIRS = DataLoaders.NFIRSData('block_group',ACS.tot_pop, pop_thresh = 50)\n",
+    "NFIRS_Sev = DataLoaders.NFIRSData('block_group',ACS.tot_pop,pop_thresh = 50, sev=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "FSM =  FireRiskModels('severity')\n",
+    "FPM =  FireRiskModels('propensity')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "## Fire Propensity Model"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Training State smoke alarm stats model\n",
-      "Training County smoke alarm stats model\n",
-      "Training Tract smoke alarm stats model\n",
-      "Training Block_Group smoke alarm stats model\n",
-      "Training MultiLevel smoke alarm stats model\n",
-      "Training DL model\n"
+      "Predicting 2017:\n"
      ]
     },
     {
      "data": {
       "text/markdown": [
-       "**Training Performance**"
+       "**Confusion Matrix**"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1165,27 +1193,94 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "105.79741754085418\n",
-      "Test RMSE: 10.28578716194605\n",
-      "Test MAE: 7.729334610078945\n"
+      "[[2190  669]\n",
+      " [  73  210]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "text/markdown": [
+       "**ROC AUC Score** = 0.8460147547203857"
+      ],
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<IPython.core.display.Markdown object>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**Classication Report**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
      },
+     "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "       False       0.97      0.77      0.86      2859\n",
+      "        True       0.24      0.74      0.36       283\n",
+      "\n",
+      "    accuracy                           0.76      3142\n",
+      "   macro avg       0.60      0.75      0.61      3142\n",
+      "weighted avg       0.90      0.76      0.81      3142\n",
+      "\n"
+     ]
+    },
     {
      "data": {
       "text/markdown": [
-       "**Testing Performance**"
+       "**Feature Ranking**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1. Max (0.343237)\n",
+      "2. Median (0.117647)\n",
+      "3. pct_alt_heat (0.110819)\n",
+      "4. race_pct_black_or_amind (0.108699)\n",
+      "5. inc_pct_poverty (0.085652)\n",
+      "6. did_not_work_past_12_mo (0.084807)\n",
+      "7. house_pct_live_alone (0.075486)\n",
+      "8. house_yr_pct_before_1960 (0.073654)\n"
+     ]
+    }
+   ],
+   "source": [
+    "display(Markdown('## Fire Propensity Model'))\n",
+    "\n",
+    "FPM.train(NFIRS_county,ACS_county,ACS_cols_to_use)\n",
+    "#FPM.train(NFIRS,ACS,ACS_cols_to_use)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "## Fire Severity Model"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1198,28 +1293,66 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Test RMSE: 14.931982928962187\n",
-      "Test MAE: 11.36208258614248\n"
+      "Predicting 2017:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "text/markdown": [
+       "**Confusion Matrix**"
+      ],
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<IPython.core.display.Markdown object>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[2236  660]\n",
+      " [  64  182]]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**ROC AUC Score** = 0.8541512262498315"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**Classication Report**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
      },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Test Correlation: (0.7416691505778157, 0.0)\n",
-      "Test R-squared: 0.536587472781177\n"
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "       False       0.97      0.77      0.86      2896\n",
+      "        True       0.22      0.74      0.33       246\n",
+      "\n",
+      "    accuracy                           0.77      3142\n",
+      "   macro avg       0.59      0.76      0.60      3142\n",
+      "weighted avg       0.91      0.77      0.82      3142\n",
+      "\n"
      ]
     },
     {
@@ -1238,29 +1371,47 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1. RPL_THEME1 (0.214602)\n",
-      "2. RPL_THEME2 (0.116916)\n",
-      "3. RPL_THEME4 (0.112707)\n",
-      "4. RPL_THEME3 (0.109658)\n",
-      "5. Population Density (per square mile), 2010 (0.107959)\n",
-      "6. race_pct_black_or_amind (0.086700)\n",
-      "7. pct_alt_heat (0.069408)\n",
-      "8. house_yr_pct_before_1960 (0.063759)\n",
-      "9. inc_pct_poverty_x (0.048886)\n",
-      "10. did_not_work_past_12_mo (0.036041)\n",
-      "11. house_pct_live_alone (0.033364)\n",
-      "12. inc_pct_poverty_y (0.000000)\n"
+      "1. Max (0.406339)\n",
+      "2. race_pct_black_or_amind (0.115707)\n",
+      "3. inc_pct_poverty (0.084286)\n",
+      "4. Median (0.082109)\n",
+      "5. did_not_work_past_12_mo (0.082056)\n",
+      "6. house_yr_pct_before_1960 (0.081612)\n",
+      "7. house_pct_live_alone (0.077125)\n",
+      "8. pct_alt_heat (0.070767)\n"
      ]
     }
    ],
    "source": [
-    "svi_use = True\n",
-    "smoke_prediction = Smoke.trainModels(ARC,ACS,SVI, ACS_cols_to_use,svi_use, utils.DATA['data'])"
+    "display(Markdown('## Fire Severity Model'))\n",
+    "\n",
+    "FSM.train(NFIRS_Sev_county,ACS_county,ACS_cols_to_use)\n",
+    "#FSM.train(NFIRS_Sev,ACS,ACS_cols_to_use)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 10,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "ARC =  DataLoaders.ARCPData(ACS, 'ARC Preparedness Data.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Smoke Alarm Models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -1288,26 +1439,14 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>num_surveys</th>\n",
-       "      <th>detectors_found_total</th>\n",
-       "      <th>detectors_found_prc</th>\n",
-       "      <th>detectors_found_CI</th>\n",
-       "      <th>detectors_working_total</th>\n",
-       "      <th>detectors_working_prc</th>\n",
-       "      <th>detectors_working_CI</th>\n",
-       "      <th>geography</th>\n",
-       "      <th>tract</th>\n",
-       "      <th>Predictions</th>\n",
-       "      <th>Population Density (per square mile), 2010</th>\n",
+       "      <th>inc_pct_poverty</th>\n",
+       "      <th>RPL_THEME1</th>\n",
+       "      <th>RPL_THEME2</th>\n",
+       "      <th>RPL_THEME3</th>\n",
+       "      <th>RPL_THEME4</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>geoid</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
+       "      <th>geos</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -1317,326 +1456,172 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>010139534001</th>\n",
-       "      <td>39</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>46.15</td>\n",
-       "      <td>15.645969</td>\n",
-       "      <td>12.0</td>\n",
-       "      <td>30.77</td>\n",
-       "      <td>14.485540</td>\n",
-       "      <td>block_group</td>\n",
-       "      <td>01013953400</td>\n",
-       "      <td>48.474262</td>\n",
-       "      <td>30.6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010139534002</th>\n",
-       "      <td>48</td>\n",
-       "      <td>19.0</td>\n",
-       "      <td>39.58</td>\n",
-       "      <td>13.834508</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>16.67</td>\n",
-       "      <td>10.543965</td>\n",
-       "      <td>block_group</td>\n",
-       "      <td>01013953400</td>\n",
-       "      <td>48.174011</td>\n",
-       "      <td>30.6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010730023034</th>\n",
-       "      <td>44</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>77.27</td>\n",
-       "      <td>12.383258</td>\n",
-       "      <td>19.0</td>\n",
-       "      <td>43.18</td>\n",
-       "      <td>14.635975</td>\n",
-       "      <td>block_group</td>\n",
-       "      <td>01073002303</td>\n",
-       "      <td>67.423523</td>\n",
-       "      <td>2370.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010730035002</th>\n",
-       "      <td>32</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>56.25</td>\n",
-       "      <td>17.188239</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>25.00</td>\n",
-       "      <td>15.003125</td>\n",
-       "      <td>block_group</td>\n",
-       "      <td>01073003500</td>\n",
-       "      <td>59.589863</td>\n",
-       "      <td>978.9</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010730035003</th>\n",
-       "      <td>34</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>67.65</td>\n",
-       "      <td>15.724891</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>32.35</td>\n",
-       "      <td>15.724891</td>\n",
-       "      <td>block_group</td>\n",
-       "      <td>01073003500</td>\n",
-       "      <td>63.964989</td>\n",
-       "      <td>978.9</td>\n",
+       "      <th>010010201001</th>\n",
+       "      <td>0.191946</td>\n",
+       "      <td>0.3913</td>\n",
+       "      <td>0.5597</td>\n",
+       "      <td>0.3735</td>\n",
+       "      <td>0.0993</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",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
+       "      <th>010010201002</th>\n",
+       "      <td>0.044269</td>\n",
+       "      <td>0.3913</td>\n",
+       "      <td>0.5597</td>\n",
+       "      <td>0.3735</td>\n",
+       "      <td>0.0993</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>010010202001</th>\n",
+       "      <td>0.382199</td>\n",
+       "      <td>0.7065</td>\n",
+       "      <td>0.3585</td>\n",
+       "      <td>0.5821</td>\n",
+       "      <td>0.7299</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>010010202002</th>\n",
+       "      <td>0.111426</td>\n",
+       "      <td>0.7065</td>\n",
+       "      <td>0.3585</td>\n",
+       "      <td>0.5821</td>\n",
+       "      <td>0.7299</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>010010203001</th>\n",
+       "      <td>0.042301</td>\n",
+       "      <td>0.5659</td>\n",
+       "      <td>0.8729</td>\n",
+       "      <td>0.6429</td>\n",
+       "      <td>0.3882</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>560459511001</th>\n",
-       "      <td>892</td>\n",
-       "      <td>562.0</td>\n",
-       "      <td>63.00</td>\n",
-       "      <td>3.168435</td>\n",
-       "      <td>347.0</td>\n",
-       "      <td>38.90</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>56045951100</td>\n",
-       "      <td>70.296913</td>\n",
-       "      <td>1.4</td>\n",
+       "      <td>0.094029</td>\n",
+       "      <td>0.3925</td>\n",
+       "      <td>0.6370</td>\n",
+       "      <td>0.2331</td>\n",
+       "      <td>0.8555</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>560459511002</th>\n",
-       "      <td>892</td>\n",
-       "      <td>562.0</td>\n",
-       "      <td>63.00</td>\n",
-       "      <td>3.168435</td>\n",
-       "      <td>347.0</td>\n",
-       "      <td>38.90</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>56045951100</td>\n",
-       "      <td>75.093887</td>\n",
-       "      <td>1.4</td>\n",
+       "      <td>0.062579</td>\n",
+       "      <td>0.3925</td>\n",
+       "      <td>0.6370</td>\n",
+       "      <td>0.2331</td>\n",
+       "      <td>0.8555</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>560459513001</th>\n",
-       "      <td>892</td>\n",
-       "      <td>562.0</td>\n",
-       "      <td>63.00</td>\n",
-       "      <td>3.168435</td>\n",
-       "      <td>347.0</td>\n",
-       "      <td>38.90</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>56045951300</td>\n",
-       "      <td>72.075195</td>\n",
-       "      <td>91.0</td>\n",
+       "      <td>0.261512</td>\n",
+       "      <td>0.5093</td>\n",
+       "      <td>0.6043</td>\n",
+       "      <td>0.2862</td>\n",
+       "      <td>0.6949</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>560459513002</th>\n",
-       "      <td>892</td>\n",
-       "      <td>562.0</td>\n",
-       "      <td>63.00</td>\n",
-       "      <td>3.168435</td>\n",
-       "      <td>347.0</td>\n",
-       "      <td>38.90</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>56045951300</td>\n",
-       "      <td>79.269608</td>\n",
-       "      <td>91.0</td>\n",
+       "      <td>0.098058</td>\n",
+       "      <td>0.5093</td>\n",
+       "      <td>0.6043</td>\n",
+       "      <td>0.2862</td>\n",
+       "      <td>0.6949</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>560459513003</th>\n",
-       "      <td>892</td>\n",
-       "      <td>562.0</td>\n",
-       "      <td>63.00</td>\n",
-       "      <td>3.168435</td>\n",
-       "      <td>347.0</td>\n",
-       "      <td>38.90</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>56045951300</td>\n",
-       "      <td>79.014572</td>\n",
-       "      <td>91.0</td>\n",
+       "      <td>0.227642</td>\n",
+       "      <td>0.5093</td>\n",
+       "      <td>0.6043</td>\n",
+       "      <td>0.2862</td>\n",
+       "      <td>0.6949</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>217739 rows × 11 columns</p>\n",
+       "<p>216027 rows × 5 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "              num_surveys  detectors_found_total  detectors_found_prc  \\\n",
-       "geoid                                                                   \n",
-       "010139534001           39                   18.0                46.15   \n",
-       "010139534002           48                   19.0                39.58   \n",
-       "010730023034           44                   34.0                77.27   \n",
-       "010730035002           32                   18.0                56.25   \n",
-       "010730035003           34                   23.0                67.65   \n",
-       "...                   ...                    ...                  ...   \n",
-       "560459511001          892                  562.0                63.00   \n",
-       "560459511002          892                  562.0                63.00   \n",
-       "560459513001          892                  562.0                63.00   \n",
-       "560459513002          892                  562.0                63.00   \n",
-       "560459513003          892                  562.0                63.00   \n",
-       "\n",
-       "              detectors_found_CI  detectors_working_total  \\\n",
-       "geoid                                                       \n",
-       "010139534001           15.645969                     12.0   \n",
-       "010139534002           13.834508                      8.0   \n",
-       "010730023034           12.383258                     19.0   \n",
-       "010730035002           17.188239                      8.0   \n",
-       "010730035003           15.724891                     11.0   \n",
-       "...                          ...                      ...   \n",
-       "560459511001            3.168435                    347.0   \n",
-       "560459511002            3.168435                    347.0   \n",
-       "560459513001            3.168435                    347.0   \n",
-       "560459513002            3.168435                    347.0   \n",
-       "560459513003            3.168435                    347.0   \n",
-       "\n",
-       "              detectors_working_prc  detectors_working_CI    geography  \\\n",
-       "geoid                                                                    \n",
-       "010139534001                  30.77             14.485540  block_group   \n",
-       "010139534002                  16.67             10.543965  block_group   \n",
-       "010730023034                  43.18             14.635975  block_group   \n",
-       "010730035002                  25.00             15.003125  block_group   \n",
-       "010730035003                  32.35             15.724891  block_group   \n",
-       "...                             ...                   ...          ...   \n",
-       "560459511001                  38.90              3.199404        state   \n",
-       "560459511002                  38.90              3.199404        state   \n",
-       "560459513001                  38.90              3.199404        state   \n",
-       "560459513002                  38.90              3.199404        state   \n",
-       "560459513003                  38.90              3.199404        state   \n",
-       "\n",
-       "                    tract  Predictions  \\\n",
-       "geoid                                    \n",
-       "010139534001  01013953400    48.474262   \n",
-       "010139534002  01013953400    48.174011   \n",
-       "010730023034  01073002303    67.423523   \n",
-       "010730035002  01073003500    59.589863   \n",
-       "010730035003  01073003500    63.964989   \n",
-       "...                   ...          ...   \n",
-       "560459511001  56045951100    70.296913   \n",
-       "560459511002  56045951100    75.093887   \n",
-       "560459513001  56045951300    72.075195   \n",
-       "560459513002  56045951300    79.269608   \n",
-       "560459513003  56045951300    79.014572   \n",
-       "\n",
-       "              Population Density (per square mile), 2010  \n",
-       "geoid                                                     \n",
-       "010139534001                                        30.6  \n",
-       "010139534002                                        30.6  \n",
-       "010730023034                                      2370.0  \n",
-       "010730035002                                       978.9  \n",
-       "010730035003                                       978.9  \n",
-       "...                                                  ...  \n",
-       "560459511001                                         1.4  \n",
-       "560459511002                                         1.4  \n",
-       "560459513001                                        91.0  \n",
-       "560459513002                                        91.0  \n",
-       "560459513003                                        91.0  \n",
+       "              inc_pct_poverty  RPL_THEME1  RPL_THEME2  RPL_THEME3  RPL_THEME4\n",
+       "geos                                                                         \n",
+       "010010201001         0.191946      0.3913      0.5597      0.3735      0.0993\n",
+       "010010201002         0.044269      0.3913      0.5597      0.3735      0.0993\n",
+       "010010202001         0.382199      0.7065      0.3585      0.5821      0.7299\n",
+       "010010202002         0.111426      0.7065      0.3585      0.5821      0.7299\n",
+       "010010203001         0.042301      0.5659      0.8729      0.6429      0.3882\n",
+       "...                       ...         ...         ...         ...         ...\n",
+       "560459511001         0.094029      0.3925      0.6370      0.2331      0.8555\n",
+       "560459511002         0.062579      0.3925      0.6370      0.2331      0.8555\n",
+       "560459513001         0.261512      0.5093      0.6043      0.2862      0.6949\n",
+       "560459513002         0.098058      0.5093      0.6043      0.2862      0.6949\n",
+       "560459513003         0.227642      0.5093      0.6043      0.2862      0.6949\n",
        "\n",
-       "[217739 rows x 11 columns]"
+       "[216027 rows x 5 columns]"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "smoke_prediction"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Saving File"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "out = NFIRS.fires.copy()\n",
-    "out.columns =  'fires_per_1K_pop_' + out.columns\n",
-    "cols = out.columns"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "out = ACS.data.merge(out, how = 'left', left_index = True, right_index = True)\n",
-    "out = out[cols]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# Smoke Alarm model munging \n",
-    "\n",
-    "\n",
-    "# add number of surveys recorded at the block level\n",
-    "num_surveys_block = Smoke.models['Block_Group']['num_surveys'].copy()\n",
-    "num_surveys_block.index = num_surveys_block.index.str[2:]\n",
-    "\n",
-    "\n",
-    "out['recorded_home_visits'] = num_surveys_block\n",
-    "\n",
-    "\n",
-    "# add the statistical model outputs \n",
-    "Smoke_predicts = Smoke.models['MultiLevel'][\n",
-    "    [ 'detectors_working_prc','detectors_working_CI','geography']].copy()\n",
-    "Smoke_predicts.index = Smoke_predicts.index.str[2:]\n",
-    "out = out.merge(Smoke_predicts,how = 'left', left_index = True, right_index = True)\n",
-    "\n",
-    "## add DL model to outputs\n",
-    "DL = pd.DataFrame(smoke_prediction['Population Density (per square mile), 2010'])\n",
-    "DL['detectors_predicted'] = smoke_prediction['Predictions'].copy()\n",
-    "\n",
-    "out = out.merge(DL,how = 'left', left_index = True, right_index = True)"
+    "SVI =  DataLoaders.SVIData(ACS.data, ACS.tot_pop, 'block_group')\n",
+    "SVI.data"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 11,
    "metadata": {
     "tags": [
      "remove_cell"
     ]
    },
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "             tot_population  RPL_THEME1  RPL_THEME2  RPL_THEME3  RPL_THEME4\n",
+      "GEOID                                                                      \n",
+      "01001020100          2010.0      0.3913      0.5597      0.3735      0.0993\n",
+      "01001020200          2014.0      0.7065      0.3585      0.5821      0.7299\n",
+      "01001020300          3136.0      0.5659      0.8729      0.6429      0.3882\n",
+      "01001020400          4563.0      0.1825      0.7960      0.3661      0.0585\n",
+      "01001020500         10320.0      0.2801      0.6475      0.4176      0.6590\n",
+      "...                     ...         ...         ...         ...         ...\n",
+      "56043000200          3050.0      0.4619      0.6913      0.1022      0.8124\n",
+      "56043000301          2495.0      0.5088      0.7811      0.3546      0.5951\n",
+      "56043000302          2629.0      0.6885      0.8272      0.3455      0.5388\n",
+      "56045951100          3039.0      0.3925      0.6370      0.2331      0.8555\n",
+      "56045951300          3780.0      0.5093      0.6043      0.2862      0.6949\n",
+      "\n",
+      "[72142 rows x 5 columns]\n",
+      "58\n",
+      "             RPL_THEME1  RPL_THEME2  RPL_THEME3  RPL_THEME4\n",
+      "GEOID                                                      \n",
+      "01001020100    786.5130   1124.9970    750.7350    199.5930\n",
+      "01001020200   1422.8910    722.0190   1172.3494   1470.0186\n",
+      "01001020300   1774.6624   2737.4144   2016.1344   1217.3952\n",
+      "01001020400    832.7475   3632.1480   1670.5143    266.9355\n",
+      "01001020500   2890.6320   6682.2000   4309.6320   6800.8800\n",
+      "...                 ...         ...         ...         ...\n",
+      "56043000200   1408.7950   2108.4650    311.7100   2477.8200\n",
+      "56043000301   1269.4560   1948.8445    884.7270   1484.7745\n",
+      "56043000302   1810.0665   2174.7088    908.3195   1416.5052\n",
+      "56045951100   1192.8075   1935.8430    708.3909   2599.8645\n",
+      "56045951300   1925.1540   2284.2540   1081.8360   2626.7220\n",
+      "\n",
+      "[72142 rows x 4 columns]\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
@@ -1658,127 +1643,146 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>smoke_detector_risk_frac</th>\n",
-       "      <th>smoke_detector_risk_score</th>\n",
+       "      <th>RPL_THEME1</th>\n",
+       "      <th>RPL_THEME2</th>\n",
+       "      <th>RPL_THEME3</th>\n",
+       "      <th>RPL_THEME4</th>\n",
+       "      <th>inc_pct_poverty</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>GEOID</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>010010201001</th>\n",
-       "      <td>0.184218</td>\n",
-       "      <td>0.176500</td>\n",
+       "      <th>01001</th>\n",
+       "      <td>0.458660</td>\n",
+       "      <td>0.679522</td>\n",
+       "      <td>0.359982</td>\n",
+       "      <td>0.490418</td>\n",
+       "      <td>0.122660</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010201002</th>\n",
-       "      <td>0.198984</td>\n",
-       "      <td>0.214362</td>\n",
+       "      <th>01003</th>\n",
+       "      <td>0.405037</td>\n",
+       "      <td>0.524210</td>\n",
+       "      <td>0.258139</td>\n",
+       "      <td>0.504242</td>\n",
+       "      <td>0.129938</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202001</th>\n",
-       "      <td>0.349579</td>\n",
-       "      <td>0.668718</td>\n",
+       "      <th>01005</th>\n",
+       "      <td>0.880776</td>\n",
+       "      <td>0.833647</td>\n",
+       "      <td>0.630959</td>\n",
+       "      <td>0.591735</td>\n",
+       "      <td>0.263737</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202002</th>\n",
-       "      <td>0.352308</td>\n",
-       "      <td>0.676149</td>\n",
+       "      <th>01007</th>\n",
+       "      <td>0.673781</td>\n",
+       "      <td>0.516063</td>\n",
+       "      <td>0.221158</td>\n",
+       "      <td>0.627417</td>\n",
+       "      <td>0.164539</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010203001</th>\n",
-       "      <td>0.264615</td>\n",
-       "      <td>0.407736</td>\n",
+       "      <th>01009</th>\n",
+       "      <td>0.624344</td>\n",
+       "      <td>0.627232</td>\n",
+       "      <td>0.354505</td>\n",
+       "      <td>0.501772</td>\n",
+       "      <td>0.165344</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>560459511001</th>\n",
-       "      <td>0.297031</td>\n",
-       "      <td>0.510014</td>\n",
+       "      <th>56037</th>\n",
+       "      <td>0.424865</td>\n",
+       "      <td>0.521423</td>\n",
+       "      <td>0.403175</td>\n",
+       "      <td>0.545971</td>\n",
+       "      <td>0.110221</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511002</th>\n",
-       "      <td>0.249061</td>\n",
-       "      <td>0.358402</td>\n",
+       "      <th>56039</th>\n",
+       "      <td>0.109058</td>\n",
+       "      <td>0.116232</td>\n",
+       "      <td>0.540475</td>\n",
+       "      <td>0.730831</td>\n",
+       "      <td>0.073255</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513001</th>\n",
-       "      <td>0.279248</td>\n",
-       "      <td>0.453793</td>\n",
+       "      <th>56041</th>\n",
+       "      <td>0.499908</td>\n",
+       "      <td>0.694255</td>\n",
+       "      <td>0.263928</td>\n",
+       "      <td>0.741195</td>\n",
+       "      <td>0.167586</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513002</th>\n",
-       "      <td>0.207304</td>\n",
-       "      <td>0.236889</td>\n",
+       "      <th>56043</th>\n",
+       "      <td>0.549097</td>\n",
+       "      <td>0.762420</td>\n",
+       "      <td>0.257494</td>\n",
+       "      <td>0.658074</td>\n",
+       "      <td>0.146562</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513003</th>\n",
-       "      <td>0.209854</td>\n",
-       "      <td>0.244164</td>\n",
+       "      <th>56045</th>\n",
+       "      <td>0.457246</td>\n",
+       "      <td>0.618873</td>\n",
+       "      <td>0.262535</td>\n",
+       "      <td>0.766474</td>\n",
+       "      <td>0.146942</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>217739 rows × 2 columns</p>\n",
+       "<p>3142 rows × 5 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "              smoke_detector_risk_frac  smoke_detector_risk_score\n",
-       "GEOID                                                            \n",
-       "010010201001                  0.184218                   0.176500\n",
-       "010010201002                  0.198984                   0.214362\n",
-       "010010202001                  0.349579                   0.668718\n",
-       "010010202002                  0.352308                   0.676149\n",
-       "010010203001                  0.264615                   0.407736\n",
-       "...                                ...                        ...\n",
-       "560459511001                  0.297031                   0.510014\n",
-       "560459511002                  0.249061                   0.358402\n",
-       "560459513001                  0.279248                   0.453793\n",
-       "560459513002                  0.207304                   0.236889\n",
-       "560459513003                  0.209854                   0.244164\n",
+       "       RPL_THEME1  RPL_THEME2  RPL_THEME3  RPL_THEME4  inc_pct_poverty\n",
+       "GEOID                                                                 \n",
+       "01001    0.458660    0.679522    0.359982    0.490418         0.122660\n",
+       "01003    0.405037    0.524210    0.258139    0.504242         0.129938\n",
+       "01005    0.880776    0.833647    0.630959    0.591735         0.263737\n",
+       "01007    0.673781    0.516063    0.221158    0.627417         0.164539\n",
+       "01009    0.624344    0.627232    0.354505    0.501772         0.165344\n",
+       "...           ...         ...         ...         ...              ...\n",
+       "56037    0.424865    0.521423    0.403175    0.545971         0.110221\n",
+       "56039    0.109058    0.116232    0.540475    0.730831         0.073255\n",
+       "56041    0.499908    0.694255    0.263928    0.741195         0.167586\n",
+       "56043    0.549097    0.762420    0.257494    0.658074         0.146562\n",
+       "56045    0.457246    0.618873    0.262535    0.766474         0.146942\n",
        "\n",
-       "[217739 rows x 2 columns]"
+       "[3142 rows x 5 columns]"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "out['smoke_detector_risk_frac'] =  1 - out['detectors_predicted'] / 100\n",
-    "out['smoke_detector_risk_score'] =  out['smoke_detector_risk_frac'].rank(pct=True)\n",
-    "out[['smoke_detector_risk_frac','smoke_detector_risk_score']]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# add final invidual predictors \n",
-    "\n",
-    "out['SVI_Theme_1'] = SVI.data['RPL_THEME1'].replace(-999.0, np.NaN)\n",
-    "\n",
-    "out['fire_propensity_risk_score'] = FPM.test_prediction_probs[:,1]\n",
-    "out['fire_severity_risk_score'] = FSM.test_prediction_probs[:,1]\n",
-    "\n"
+    "SVI_county =  DataLoaders.SVIData(ACS_county.data, ACS.tot_pop, 'county')\n",
+    "SVI_county.data"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 12,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -1786,67 +1790,289 @@
    },
    "outputs": [],
    "source": [
-    "# Not weighting\n",
-    "#create and add final predictor \n",
-    "\n",
-    "out['CombinedRiskScore'] =  out.loc[:,['smoke_detector_risk_score',\n",
-    "                                       'SVI_Theme_1',\n",
-    "                                       'fire_propensity_risk_score',\n",
-    "                                       'fire_severity_risk_score'] ].mean(axis = 1,\n",
-    "                                                                          skipna = False )"
+    "Smoke = SmokeAlarmModels()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
+   "execution_count": 13,
+   "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training State smoke alarm stats model\n",
+      "Training County smoke alarm stats model\n",
+      "Training Tract smoke alarm stats model\n",
+      "Training Block_Group smoke alarm stats model\n",
+      "Training MultiLevel smoke alarm stats model\n",
+      "sm\n",
+      "(1644, 7)\n",
+      "(3142, 7)\n"
+     ]
+    },
     {
      "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>fires_per_1K_pop_2009</th>\n",
-       "      <th>fires_per_1K_pop_2010</th>\n",
-       "      <th>fires_per_1K_pop_2011</th>\n",
-       "      <th>fires_per_1K_pop_2012</th>\n",
-       "      <th>fires_per_1K_pop_2013</th>\n",
-       "      <th>fires_per_1K_pop_2014</th>\n",
-       "      <th>fires_per_1K_pop_2015</th>\n",
-       "      <th>fires_per_1K_pop_2016</th>\n",
-       "      <th>fires_per_1K_pop_2017</th>\n",
-       "      <th>recorded_home_visits</th>\n",
-       "      <th>...</th>\n",
-       "      <th>detectors_working_CI</th>\n",
-       "      <th>geography</th>\n",
-       "      <th>Population Density (per square mile), 2010</th>\n",
-       "      <th>detectors_predicted</th>\n",
-       "      <th>smoke_detector_risk_frac</th>\n",
-       "      <th>smoke_detector_risk_score</th>\n",
-       "      <th>SVI_Theme_1</th>\n",
-       "      <th>fire_propensity_risk_score</th>\n",
-       "      <th>fire_severity_risk_score</th>\n",
-       "      <th>CombinedRiskScore</th>\n",
+      "text/markdown": [
+       "**Training Performance**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1.918248522576297\n",
+      "Test RMSE: 1.385008491878767\n",
+      "Test MAE: 0.9815316831349422\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**Testing Performance**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test RMSE: 17.43807942261543\n",
+      "Test MAE: 13.710711395124534\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test Correlation: (0.30480256561260155, 1.6769545013572884e-08)\n",
+      "Test R-squared: -0.03231314164633203\n"
+     ]
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**Feature Ranking**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1. RPL_THEME1 (0.236634)\n",
+      "2. inc_pct_poverty_x (0.094384)\n",
+      "3. RPL_THEME2 (0.092675)\n",
+      "4. pct_alt_heat (0.086282)\n",
+      "5. house_yr_pct_before_1960 (0.083945)\n",
+      "6. race_pct_black_or_amind (0.083273)\n",
+      "7. RPL_THEME3 (0.081264)\n",
+      "8. RPL_THEME4 (0.066313)\n",
+      "9. house_pct_live_alone (0.063659)\n",
+      "10. did_not_work_past_12_mo (0.063023)\n",
+      "11. Population Density (per square mile), 2010 (0.048548)\n",
+      "12. inc_pct_poverty_y (0.000000)\n"
+     ]
+    }
+   ],
+   "source": [
+    "svi_use = True\n",
+    "smoke_prediction = Smoke.trainModels(ARC,ACS_county.data,ACS.tot_pop, SVI_county, ACS_cols_to_use,svi_use, utils.DATA['data'], 'county')\n",
+    "#smoke_prediction = Smoke.trainModels(ARC,ACS.data,ACS.tot_pop, SVI, ACS_cols_to_use,svi_use, utils.DATA['data'], 'block_group')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Saving File"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "level = 'county'\n",
+    "ACS = ACS_county\n",
+    "SVI = SVI_county\n",
+    "NFIRS = NFIRS_county\n",
+    "NFIRS_Sev = NFIRS_Sev_county"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "level = 'block_group'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "out = NFIRS.fires.copy()\n",
+    "out.columns =  'fires_per_1K_pop_' + out.columns\n",
+    "cols = out.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "out = ACS.data.merge(out, how = 'left', left_index = True, right_index = True)\n",
+    "out = out[cols]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "# Smoke Alarm model munging \n",
+    "\n",
+    "\n",
+    "# add number of surveys recorded at the block level\n",
+    "if level == 'block_group':\n",
+    "    num_surveys = Smoke.models['Block_Group']['num_surveys'].copy()\n",
+    "elif level == 'tract':\n",
+    "    num_surveys = Smoke.models['Tract']['num_surveys'].copy()\n",
+    "else:\n",
+    "    num_surveys = Smoke.models['County']['num_surveys'].copy()\n",
+    "num_surveys.index = num_surveys.index.str[2:]\n",
+    "\n",
+    "\n",
+    "out['recorded_home_visits'] = num_surveys\n",
+    "\n",
+    "\n",
+    "# add the statistical model outputs \n",
+    "if level == 'block_group':\n",
+    "    Smoke_predicts = Smoke.models['MultiLevel'][\n",
+    "    [ 'detectors_working_prc','detectors_working_CI','geography']].copy()\n",
+    "elif level == 'tract':\n",
+    "    Smoke_predicts = Smoke.models['Tract'][\n",
+    "    [ 'detectors_working_prc','detectors_working_CI']].copy()\n",
+    "    Smoke_predicts['geography'] =  'NA'\n",
+    "else:\n",
+    "    Smoke_predicts = Smoke.models['County'][\n",
+    "    [ 'detectors_working_prc','detectors_working_CI']].copy() \n",
+    "    Smoke_predicts['geography'] =  'NA'\n",
+    "    \n",
+    "Smoke_predicts.index = Smoke_predicts.index.str[2:]\n",
+    "out = out.merge(Smoke_predicts,how = 'left', left_index = True, right_index = True)\n",
+    "\n",
+    "## add DL model to outputs\n",
+    "DL = pd.DataFrame(smoke_prediction['Population Density (per square mile), 2010'])\n",
+    "#DL['detectors_predicted'] = smoke_prediction['Predictions'].copy()\n",
+    "\n",
+    "out = out.merge(DL,how = 'left', left_index = True, right_index = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "      <th></th>\n",
+       "      <th>fires_per_1K_pop_2009</th>\n",
+       "      <th>fires_per_1K_pop_2010</th>\n",
+       "      <th>fires_per_1K_pop_2011</th>\n",
+       "      <th>fires_per_1K_pop_2012</th>\n",
+       "      <th>fires_per_1K_pop_2013</th>\n",
+       "      <th>fires_per_1K_pop_2014</th>\n",
+       "      <th>fires_per_1K_pop_2015</th>\n",
+       "      <th>fires_per_1K_pop_2016</th>\n",
+       "      <th>fires_per_1K_pop_2017</th>\n",
+       "      <th>recorded_home_visits</th>\n",
+       "      <th>detectors_working_prc</th>\n",
+       "      <th>detectors_working_CI</th>\n",
+       "      <th>geography</th>\n",
+       "      <th>Population Density (per square mile), 2010</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>GEOID</th>\n",
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-      "text/plain": [
-       "              fires_per_1K_pop_2009  fires_per_1K_pop_2010  \\\n",
-       "GEOID                                                        \n",
-       "010010201001               1.342282               2.684564   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120                    NaN   \n",
-       "010010202002               2.832861               2.832861   \n",
-       "010010203001               0.846024               1.269036   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
-       "\n",
-       "              fires_per_1K_pop_2011  fires_per_1K_pop_2012  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002                    NaN               1.581028   \n",
-       "010010202001               3.141361                    NaN   \n",
-       "010010202002               2.832861               0.944287   \n",
-       "010010203001               0.846024               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002               0.970874                    NaN   \n",
-       "560459513003               0.625391               0.625391   \n",
-       "\n",
-       "              fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002               0.790514                    NaN   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               1.269036               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810               0.868810   \n",
-       "560459513002                    NaN               0.970874   \n",
-       "560459513003                    NaN               0.625391   \n",
-       "\n",
-       "              fires_per_1K_pop_2015  fires_per_1K_pop_2016  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN               1.342282   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               0.423012               0.846024   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN               1.372684   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001                    NaN                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
-       "\n",
-       "              fires_per_1K_pop_2017  recorded_home_visits  ...  \\\n",
-       "GEOID                                                      ...   \n",
-       "010010201001               1.342282                     0  ...   \n",
-       "010010201002                    NaN                     0  ...   \n",
-       "010010202001                    NaN                     0  ...   \n",
-       "010010202002               3.777148                     0  ...   \n",
-       "010010203001                    NaN                     0  ...   \n",
-       "...                             ...                   ...  ...   \n",
-       "560459511001                    NaN                     0  ...   \n",
-       "560459511002                    NaN                     0  ...   \n",
-       "560459513001               1.737619                     3  ...   \n",
-       "560459513002                    NaN                     3  ...   \n",
-       "560459513003                    NaN                     6  ...   \n",
-       "\n",
-       "              detectors_working_CI  geography  \\\n",
-       "GEOID                                           \n",
-       "010010201001              1.089020      state   \n",
-       "010010201002              1.089020      state   \n",
-       "010010202001              1.089020      state   \n",
-       "010010202002              1.089020      state   \n",
-       "010010203001              1.089020      state   \n",
-       "...                            ...        ...   \n",
-       "560459511001              3.199404      state   \n",
-       "560459511002              3.199404      state   \n",
-       "560459513001              3.199404      state   \n",
-       "560459513002              3.199404      state   \n",
-       "560459513003              3.199404      state   \n",
+       "<p>3142 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       fires_per_1K_pop_2009  fires_per_1K_pop_2010  fires_per_1K_pop_2011  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.750943               0.549471               0.567786   \n",
+       "01003               0.386493               0.533971               0.447518   \n",
+       "01005               0.719090               0.888287               0.169198   \n",
+       "01007               0.097073               0.145610               0.194146   \n",
+       "01009               0.420323               0.437836               0.647997   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.633972               0.611330               0.316986   \n",
+       "56039               0.310780                    NaN               0.133191   \n",
+       "56041               0.726111               0.871333               0.677704   \n",
+       "56043               0.978713               0.244678               0.367017   \n",
+       "56045               0.293298                    NaN               0.439947   \n",
        "\n",
-       "             Population Density (per square mile), 2010  detectors_predicted  \\\n",
-       "GEOID                                                                          \n",
-       "010010201001                                      504.8            81.578194   \n",
-       "010010201002                                      504.8            80.101570   \n",
-       "010010202001                                     1682.5            65.042084   \n",
-       "010010202002                                     1682.5            64.769157   \n",
-       "010010203001                                     1633.1            73.538513   \n",
-       "...                                                 ...                  ...   \n",
-       "560459511001                                        1.4            70.296913   \n",
-       "560459511002                                        1.4            75.093887   \n",
-       "560459513001                                       91.0            72.075195   \n",
-       "560459513002                                       91.0            79.269608   \n",
-       "560459513003                                       91.0            79.014572   \n",
+       "       fires_per_1K_pop_2012  fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.293051               0.457892               0.201473   \n",
+       "01003               0.523800               0.462775               0.671277   \n",
+       "01005               0.507593               0.211497               0.296096   \n",
+       "01007               0.242683                    NaN                    NaN   \n",
+       "01009               0.315242               0.245188               0.262702   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.520763                    NaN               0.475479   \n",
+       "56039               0.488368                    NaN                    NaN   \n",
+       "56041               0.338852                    NaN               0.290444   \n",
+       "56043               0.244678                    NaN               0.122339   \n",
+       "56045               0.146649               0.146649               0.439947   \n",
        "\n",
-       "              smoke_detector_risk_frac  smoke_detector_risk_score  \\\n",
-       "GEOID                                                               \n",
-       "010010201001                  0.184218                   0.176500   \n",
-       "010010201002                  0.198984                   0.214362   \n",
-       "010010202001                  0.349579                   0.668718   \n",
-       "010010202002                  0.352308                   0.676149   \n",
-       "010010203001                  0.264615                   0.407736   \n",
-       "...                                ...                        ...   \n",
-       "560459511001                  0.297031                   0.510014   \n",
-       "560459511002                  0.249061                   0.358402   \n",
-       "560459513001                  0.279248                   0.453793   \n",
-       "560459513002                  0.207304                   0.236889   \n",
-       "560459513003                  0.209854                   0.244164   \n",
+       "       fires_per_1K_pop_2015  fires_per_1K_pop_2016  fires_per_1K_pop_2017  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.531155               0.457892               0.567786   \n",
+       "01003               0.503458               0.508544               0.737388   \n",
+       "01005               0.126898               0.169198               0.761389   \n",
+       "01007               0.097073               0.194146               0.388293   \n",
+       "01009               0.367782               0.928212               0.875672   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.339628               0.543404               0.407553   \n",
+       "56039               0.887942               0.088794               0.621559   \n",
+       "56041               0.290444               0.096815               0.338852   \n",
+       "56043               0.367017               0.611696               0.367017   \n",
+       "56045               0.146649               0.293298               0.293298   \n",
        "\n",
-       "              SVI_Theme_1  fire_propensity_risk_score  \\\n",
-       "GEOID                                                   \n",
-       "010010201001       0.3913                    0.278164   \n",
-       "010010201002       0.3913                    0.079479   \n",
-       "010010202001       0.7065                    0.678772   \n",
-       "010010202002       0.7065                    0.134161   \n",
-       "010010203001       0.5659                    0.002346   \n",
-       "...                   ...                         ...   \n",
-       "560459511001       0.3925                    0.268031   \n",
-       "560459511002       0.3925                    0.262987   \n",
-       "560459513001       0.5093                    0.024417   \n",
-       "560459513002       0.5093                    0.755818   \n",
-       "560459513003       0.5093                    0.040824   \n",
+       "       recorded_home_visits  detectors_working_prc  detectors_working_CI  \\\n",
+       "GEOID                                                                      \n",
+       "01001                    12                   8.33             15.635132   \n",
+       "01003                    95                  52.63             10.040669   \n",
+       "01005                    15                  20.00             20.242793   \n",
+       "01007                    14                  42.86             25.923179   \n",
+       "01009                    47                  10.64              8.815553   \n",
+       "...                     ...                    ...                   ...   \n",
+       "56037                    31                  51.61             17.592192   \n",
+       "56039                     7                  71.43             33.465899   \n",
+       "56041                     0                   0.00              0.000000   \n",
+       "56043                     5                  60.00             42.941449   \n",
+       "56045                    12                  25.00             24.500000   \n",
        "\n",
-       "              fire_severity_risk_score  CombinedRiskScore  \n",
-       "GEOID                                                      \n",
-       "010010201001                  0.816859           0.415706  \n",
-       "010010201002                  0.037421           0.180641  \n",
-       "010010202001                  0.796419           0.712602  \n",
-       "010010202002                  0.301321           0.454533  \n",
-       "010010203001                  0.002481           0.244616  \n",
-       "...                                ...                ...  \n",
-       "560459511001                  0.294215           0.366190  \n",
-       "560459511002                  0.359560           0.343362  \n",
-       "560459513001                  0.661153           0.412166  \n",
-       "560459513002                  0.392522           0.473632  \n",
-       "560459513003                  0.202168           0.249114  \n",
+       "      geography  Population Density (per square mile), 2010  \n",
+       "GEOID                                                        \n",
+       "01001        NA                                   91.777666  \n",
+       "01003        NA                                  114.646496  \n",
+       "01005        NA                                   31.028365  \n",
+       "01007        NA                                   36.805332  \n",
+       "01009        NA                                   88.898883  \n",
+       "...         ...                                         ...  \n",
+       "56037        NA                                    4.201329  \n",
+       "56039        NA                                    5.329629  \n",
+       "56041        NA                                   10.146543  \n",
+       "56043        NA                                    3.811757  \n",
+       "56045        NA                                    3.005713  \n",
        "\n",
-       "[217739 rows x 21 columns]"
+       "[3142 rows x 14 columns]"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2298,49 +2370,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "**Combined Risk Score Summary:**"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "count    216824.000000\n",
-       "mean          0.404494\n",
-       "std           0.211338\n",
-       "min           0.001657\n",
-       "25%           0.241339\n",
-       "50%           0.386180\n",
-       "75%           0.543973\n",
-       "max           0.993570\n",
-       "Name: CombinedRiskScore, dtype: float64"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": 20,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
    "source": [
-    "display(Markdown('**Combined Risk Score Summary:**'))\n",
+    "## add DL model to outputs\n",
+    "DL = pd.DataFrame(smoke_prediction['Population Density (per square mile), 2010'])\n",
+    "DL['detectors_predicted'] = smoke_prediction['Predictions'].copy()\n",
     "\n",
-    "out['CombinedRiskScore'].describe()"
+    "out = out.merge(DL,how = 'left', left_index = True, right_index = True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 21,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -2368,479 +2415,191 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>fires_per_1K_pop_2009</th>\n",
-       "      <th>fires_per_1K_pop_2010</th>\n",
-       "      <th>fires_per_1K_pop_2011</th>\n",
-       "      <th>fires_per_1K_pop_2012</th>\n",
-       "      <th>fires_per_1K_pop_2013</th>\n",
-       "      <th>fires_per_1K_pop_2014</th>\n",
-       "      <th>fires_per_1K_pop_2015</th>\n",
-       "      <th>fires_per_1K_pop_2016</th>\n",
-       "      <th>fires_per_1K_pop_2017</th>\n",
-       "      <th>recorded_home_visits</th>\n",
-       "      <th>...</th>\n",
-       "      <th>detectors_working_CI</th>\n",
-       "      <th>geography</th>\n",
-       "      <th>Population Density (per square mile), 2010</th>\n",
-       "      <th>detectors_predicted</th>\n",
        "      <th>smoke_detector_risk_frac</th>\n",
        "      <th>smoke_detector_risk_score</th>\n",
-       "      <th>SVI_Theme_1</th>\n",
-       "      <th>fire_propensity_risk_score</th>\n",
-       "      <th>fire_severity_risk_score</th>\n",
-       "      <th>CombinedRiskScore</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>GEOID</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>010010201001</th>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>2.684564</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1.089020</td>\n",
-       "      <td>state</td>\n",
-       "      <td>504.8</td>\n",
-       "      <td>81.578194</td>\n",
-       "      <td>0.184218</td>\n",
-       "      <td>0.176500</td>\n",
-       "      <td>0.3913</td>\n",
-       "      <td>0.278164</td>\n",
-       "      <td>0.816859</td>\n",
-       "      <td>0.415706</td>\n",
+       "      <th>01001</th>\n",
+       "      <td>0.300455</td>\n",
+       "      <td>0.340547</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010201002</th>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1.089020</td>\n",
-       "      <td>state</td>\n",
-       "      <td>504.8</td>\n",
-       "      <td>80.101570</td>\n",
-       "      <td>0.198984</td>\n",
-       "      <td>0.214362</td>\n",
-       "      <td>0.3913</td>\n",
-       "      <td>0.079479</td>\n",
-       "      <td>0.037421</td>\n",
-       "      <td>0.180641</td>\n",
+       "      <th>01003</th>\n",
+       "      <td>0.225427</td>\n",
+       "      <td>0.159134</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202001</th>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3.141361</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1.089020</td>\n",
-       "      <td>state</td>\n",
-       "      <td>1682.5</td>\n",
-       "      <td>65.042084</td>\n",
-       "      <td>0.349579</td>\n",
-       "      <td>0.668718</td>\n",
-       "      <td>0.7065</td>\n",
-       "      <td>0.678772</td>\n",
-       "      <td>0.796419</td>\n",
-       "      <td>0.712602</td>\n",
+       "      <th>01005</th>\n",
+       "      <td>0.656577</td>\n",
+       "      <td>0.962444</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202002</th>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3.777148</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1.089020</td>\n",
-       "      <td>state</td>\n",
-       "      <td>1682.5</td>\n",
-       "      <td>64.769157</td>\n",
-       "      <td>0.352308</td>\n",
-       "      <td>0.676149</td>\n",
-       "      <td>0.7065</td>\n",
-       "      <td>0.134161</td>\n",
-       "      <td>0.301321</td>\n",
-       "      <td>0.454533</td>\n",
+       "      <th>01007</th>\n",
+       "      <td>0.492253</td>\n",
+       "      <td>0.799491</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010203001</th>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1.089020</td>\n",
-       "      <td>state</td>\n",
-       "      <td>1633.1</td>\n",
-       "      <td>73.538513</td>\n",
-       "      <td>0.264615</td>\n",
-       "      <td>0.407736</td>\n",
-       "      <td>0.5659</td>\n",
-       "      <td>0.002346</td>\n",
-       "      <td>0.002481</td>\n",
-       "      <td>0.244616</td>\n",
+       "      <th>01009</th>\n",
+       "      <td>0.667695</td>\n",
+       "      <td>0.969446</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",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\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>560459511001</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>1.4</td>\n",
-       "      <td>70.296913</td>\n",
-       "      <td>0.297031</td>\n",
-       "      <td>0.510014</td>\n",
-       "      <td>0.3925</td>\n",
-       "      <td>0.268031</td>\n",
-       "      <td>0.294215</td>\n",
-       "      <td>0.366190</td>\n",
+       "      <th>56037</th>\n",
+       "      <td>0.234741</td>\n",
+       "      <td>0.180140</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511002</th>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>1.4</td>\n",
-       "      <td>75.093887</td>\n",
-       "      <td>0.249061</td>\n",
-       "      <td>0.358402</td>\n",
-       "      <td>0.3925</td>\n",
-       "      <td>0.262987</td>\n",
-       "      <td>0.359560</td>\n",
-       "      <td>0.343362</td>\n",
+       "      <th>56039</th>\n",
+       "      <td>0.367555</td>\n",
+       "      <td>0.523552</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513001</th>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.737619</td>\n",
-       "      <td>3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>91.0</td>\n",
-       "      <td>72.075195</td>\n",
-       "      <td>0.279248</td>\n",
-       "      <td>0.453793</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.024417</td>\n",
-       "      <td>0.661153</td>\n",
-       "      <td>0.412166</td>\n",
+       "      <th>56041</th>\n",
+       "      <td>0.167282</td>\n",
+       "      <td>0.060153</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513002</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>91.0</td>\n",
-       "      <td>79.269608</td>\n",
-       "      <td>0.207304</td>\n",
-       "      <td>0.236889</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.755818</td>\n",
-       "      <td>0.392522</td>\n",
-       "      <td>0.473632</td>\n",
+       "      <th>56043</th>\n",
+       "      <td>0.448217</td>\n",
+       "      <td>0.713240</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513003</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>6</td>\n",
-       "      <td>...</td>\n",
-       "      <td>3.199404</td>\n",
-       "      <td>state</td>\n",
-       "      <td>91.0</td>\n",
-       "      <td>79.014572</td>\n",
-       "      <td>0.209854</td>\n",
-       "      <td>0.244164</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.040824</td>\n",
-       "      <td>0.202168</td>\n",
-       "      <td>0.249114</td>\n",
+       "      <th>56045</th>\n",
+       "      <td>0.337670</td>\n",
+       "      <td>0.443985</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>217739 rows × 21 columns</p>\n",
+       "<p>3142 rows × 2 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "              fires_per_1K_pop_2009  fires_per_1K_pop_2010  \\\n",
-       "GEOID                                                        \n",
-       "010010201001               1.342282               2.684564   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120                    NaN   \n",
-       "010010202002               2.832861               2.832861   \n",
-       "010010203001               0.846024               1.269036   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
-       "\n",
-       "              fires_per_1K_pop_2011  fires_per_1K_pop_2012  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002                    NaN               1.581028   \n",
-       "010010202001               3.141361                    NaN   \n",
-       "010010202002               2.832861               0.944287   \n",
-       "010010203001               0.846024               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002               0.970874                    NaN   \n",
-       "560459513003               0.625391               0.625391   \n",
-       "\n",
-       "              fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002               0.790514                    NaN   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               1.269036               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810               0.868810   \n",
-       "560459513002                    NaN               0.970874   \n",
-       "560459513003                    NaN               0.625391   \n",
-       "\n",
-       "              fires_per_1K_pop_2015  fires_per_1K_pop_2016  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN               1.342282   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               0.423012               0.846024   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN               1.372684   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001                    NaN                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
+       "       smoke_detector_risk_frac  smoke_detector_risk_score\n",
+       "GEOID                                                     \n",
+       "01001                  0.300455                   0.340547\n",
+       "01003                  0.225427                   0.159134\n",
+       "01005                  0.656577                   0.962444\n",
+       "01007                  0.492253                   0.799491\n",
+       "01009                  0.667695                   0.969446\n",
+       "...                         ...                        ...\n",
+       "56037                  0.234741                   0.180140\n",
+       "56039                  0.367555                   0.523552\n",
+       "56041                  0.167282                   0.060153\n",
+       "56043                  0.448217                   0.713240\n",
+       "56045                  0.337670                   0.443985\n",
        "\n",
-       "              fires_per_1K_pop_2017  recorded_home_visits  ...  \\\n",
-       "GEOID                                                      ...   \n",
-       "010010201001               1.342282                     0  ...   \n",
-       "010010201002                    NaN                     0  ...   \n",
-       "010010202001                    NaN                     0  ...   \n",
-       "010010202002               3.777148                     0  ...   \n",
-       "010010203001                    NaN                     0  ...   \n",
-       "...                             ...                   ...  ...   \n",
-       "560459511001                    NaN                     0  ...   \n",
-       "560459511002                    NaN                     0  ...   \n",
-       "560459513001               1.737619                     3  ...   \n",
-       "560459513002                    NaN                     3  ...   \n",
-       "560459513003                    NaN                     6  ...   \n",
-       "\n",
-       "              detectors_working_CI  geography  \\\n",
-       "GEOID                                           \n",
-       "010010201001              1.089020      state   \n",
-       "010010201002              1.089020      state   \n",
-       "010010202001              1.089020      state   \n",
-       "010010202002              1.089020      state   \n",
-       "010010203001              1.089020      state   \n",
-       "...                            ...        ...   \n",
-       "560459511001              3.199404      state   \n",
-       "560459511002              3.199404      state   \n",
-       "560459513001              3.199404      state   \n",
-       "560459513002              3.199404      state   \n",
-       "560459513003              3.199404      state   \n",
-       "\n",
-       "             Population Density (per square mile), 2010  detectors_predicted  \\\n",
-       "GEOID                                                                          \n",
-       "010010201001                                      504.8            81.578194   \n",
-       "010010201002                                      504.8            80.101570   \n",
-       "010010202001                                     1682.5            65.042084   \n",
-       "010010202002                                     1682.5            64.769157   \n",
-       "010010203001                                     1633.1            73.538513   \n",
-       "...                                                 ...                  ...   \n",
-       "560459511001                                        1.4            70.296913   \n",
-       "560459511002                                        1.4            75.093887   \n",
-       "560459513001                                       91.0            72.075195   \n",
-       "560459513002                                       91.0            79.269608   \n",
-       "560459513003                                       91.0            79.014572   \n",
-       "\n",
-       "              smoke_detector_risk_frac  smoke_detector_risk_score  \\\n",
-       "GEOID                                                               \n",
-       "010010201001                  0.184218                   0.176500   \n",
-       "010010201002                  0.198984                   0.214362   \n",
-       "010010202001                  0.349579                   0.668718   \n",
-       "010010202002                  0.352308                   0.676149   \n",
-       "010010203001                  0.264615                   0.407736   \n",
-       "...                                ...                        ...   \n",
-       "560459511001                  0.297031                   0.510014   \n",
-       "560459511002                  0.249061                   0.358402   \n",
-       "560459513001                  0.279248                   0.453793   \n",
-       "560459513002                  0.207304                   0.236889   \n",
-       "560459513003                  0.209854                   0.244164   \n",
-       "\n",
-       "              SVI_Theme_1  fire_propensity_risk_score  \\\n",
-       "GEOID                                                   \n",
-       "010010201001       0.3913                    0.278164   \n",
-       "010010201002       0.3913                    0.079479   \n",
-       "010010202001       0.7065                    0.678772   \n",
-       "010010202002       0.7065                    0.134161   \n",
-       "010010203001       0.5659                    0.002346   \n",
-       "...                   ...                         ...   \n",
-       "560459511001       0.3925                    0.268031   \n",
-       "560459511002       0.3925                    0.262987   \n",
-       "560459513001       0.5093                    0.024417   \n",
-       "560459513002       0.5093                    0.755818   \n",
-       "560459513003       0.5093                    0.040824   \n",
-       "\n",
-       "              fire_severity_risk_score  CombinedRiskScore  \n",
-       "GEOID                                                      \n",
-       "010010201001                  0.816859           0.415706  \n",
-       "010010201002                  0.037421           0.180641  \n",
-       "010010202001                  0.796419           0.712602  \n",
-       "010010202002                  0.301321           0.454533  \n",
-       "010010203001                  0.002481           0.244616  \n",
-       "...                                ...                ...  \n",
-       "560459511001                  0.294215           0.366190  \n",
-       "560459511002                  0.359560           0.343362  \n",
-       "560459513001                  0.661153           0.412166  \n",
-       "560459513002                  0.392522           0.473632  \n",
-       "560459513003                  0.202168           0.249114  \n",
-       "\n",
-       "[217739 rows x 21 columns]"
+       "[3142 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "out['smoke_detector_risk_frac'] =  1 - out['detectors_predicted'] / 100\n",
+    "out['smoke_detector_risk_score'] =  out['smoke_detector_risk_frac'].rank(pct=True)\n",
+    "out[['smoke_detector_risk_frac','smoke_detector_risk_score']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "# add final invidual predictors \n",
+    "\n",
+    "out['SVI_Theme_1'] = SVI.data['RPL_THEME1'].replace(-999.0, np.NaN)\n",
+    "\n",
+    "out['fire_propensity_risk_score'] = FPM.test_prediction_probs[:,1]\n",
+    "out['fire_severity_risk_score'] = FSM.test_prediction_probs[:,1]\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "# create and add final predictor \n",
+    "\n",
+    "#create fire_risk_score by weighing propensity and severity at a .8 to .2 ratio.\n",
+    "#We want the fire_risk_score to be half of the overall combinedRiskScore so multiple the fire_risk_score by 2.\n",
+    "out['fire_prop_weighted'] = out['fire_propensity_risk_score']*0.8\n",
+    "out['fire_sev_weighted'] = out['fire_severity_risk_score']*0.2\n",
+    "out['fire_risk_score'] = out['fire_prop_weighted']+out['fire_sev_weighted']\n",
+    "\n",
+    "out['CombinedRiskScore'] =  out.loc[:,['smoke_detector_risk_score',\n",
+    "                                       'fire_risk_score'] ].mean(axis = 1, skipna = True) #False )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "**Combined Risk Score Summary:**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
       ]
      },
-     "execution_count": 30,
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "count    3142.000000\n",
+       "mean        0.402014\n",
+       "std         0.232507\n",
+       "min         0.002664\n",
+       "25%         0.218870\n",
+       "50%         0.395830\n",
+       "75%         0.540223\n",
+       "max         0.992059\n",
+       "Name: CombinedRiskScore, dtype: float64"
+      ]
+     },
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "out"
+    "display(Markdown('**Combined Risk Score Summary:**'))\n",
+    "\n",
+    "out['CombinedRiskScore'].describe()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 26,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -2848,7 +2607,7 @@
    },
    "outputs": [],
    "source": [
-    "out_name = f\"CombinedModels-basic{date.today()}.csv\"\n",
+    "out_name = f\"CombinedModels-basic{level}-{date.today()}.csv\"\n",
     "out_save = out.copy()\n",
     "out_save.index = '#_' + out_save.index\n",
     "out_save.to_csv(utils.DATA['model-outputs'] / out_name)"
@@ -2856,7 +2615,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 27,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -2871,7 +2630,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -2901,6 +2660,7 @@
        " 'median_fires_1k_sev',\n",
        " 'fire_propensity_risk_score',\n",
        " 'fire_severity_risk_score',\n",
+       " 'fire_risk_score',\n",
        " 'recorded_home_visits',\n",
        " 'smoke_detector_risk_frac',\n",
        " 'smoke_detector_risk_score',\n",
@@ -2943,7 +2703,7 @@
        " 'county_rank']"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2951,7 +2711,7 @@
    "source": [
     "out_columns = ['state','NFIRS_start','NFIRS_end','years_fires_reported','total_fires_reported', 'max_fires_1k', \n",
     "               'median_fires_1k','total_fires_reported_sev', 'max_fires_1k_sev', 'median_fires_1k_sev',\n",
-    "               'fire_propensity_risk_score','fire_severity_risk_score', 'recorded_home_visits',\n",
+    "               'fire_propensity_risk_score','fire_severity_risk_score', 'fire_risk_score', 'recorded_home_visits',\n",
     "              'smoke_detector_risk_frac', 'smoke_detector_risk_score','geography', 'SVI_Theme_1','CombinedRiskScore',\n",
     "              'did_not_work_past_12_mo', 'house_pct_live_alone', 'pct_alt_heat', 'house_yr_pct_before_1960', \n",
     "               'inc_pct_poverty', 'race_pct_black_or_amind', 'tot_population', 'house_tot_occ_cnt', 'inc_pcincome', \n",
@@ -2965,7 +2725,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 28,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -2979,7 +2739,7 @@
        "      dtype=object)"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2991,7 +2751,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 29,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -3030,13 +2790,13 @@
        "      <th>fires_per_1K_pop_2017</th>\n",
        "      <th>recorded_home_visits</th>\n",
        "      <th>...</th>\n",
-       "      <th>Population Density (per square mile), 2010</th>\n",
-       "      <th>detectors_predicted</th>\n",
-       "      <th>smoke_detector_risk_frac</th>\n",
        "      <th>smoke_detector_risk_score</th>\n",
        "      <th>SVI_Theme_1</th>\n",
        "      <th>fire_propensity_risk_score</th>\n",
        "      <th>fire_severity_risk_score</th>\n",
+       "      <th>fire_prop_weighted</th>\n",
+       "      <th>fire_sev_weighted</th>\n",
+       "      <th>fire_risk_score</th>\n",
        "      <th>CombinedRiskScore</th>\n",
        "      <th>NFIRS_start</th>\n",
        "      <th>NFIRS_end</th>\n",
@@ -3068,122 +2828,122 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>010010201001</th>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>2.684564</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>504.8</td>\n",
-       "      <td>81.578194</td>\n",
-       "      <td>0.184218</td>\n",
-       "      <td>0.176500</td>\n",
-       "      <td>0.3913</td>\n",
-       "      <td>0.278164</td>\n",
-       "      <td>0.816859</td>\n",
-       "      <td>0.415706</td>\n",
+       "      <th>01001</th>\n",
+       "      <td>0.750943</td>\n",
+       "      <td>0.549471</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>0.293051</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>0.201473</td>\n",
+       "      <td>0.531155</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>12</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.340547</td>\n",
+       "      <td>0.458660</td>\n",
+       "      <td>0.003780</td>\n",
+       "      <td>0.004219</td>\n",
+       "      <td>0.003024</td>\n",
+       "      <td>0.000844</td>\n",
+       "      <td>0.003867</td>\n",
+       "      <td>0.172207</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010201002</th>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>504.8</td>\n",
-       "      <td>80.101570</td>\n",
-       "      <td>0.198984</td>\n",
-       "      <td>0.214362</td>\n",
-       "      <td>0.3913</td>\n",
-       "      <td>0.079479</td>\n",
-       "      <td>0.037421</td>\n",
-       "      <td>0.180641</td>\n",
+       "      <th>01003</th>\n",
+       "      <td>0.386493</td>\n",
+       "      <td>0.533971</td>\n",
+       "      <td>0.447518</td>\n",
+       "      <td>0.523800</td>\n",
+       "      <td>0.462775</td>\n",
+       "      <td>0.671277</td>\n",
+       "      <td>0.503458</td>\n",
+       "      <td>0.508544</td>\n",
+       "      <td>0.737388</td>\n",
+       "      <td>95</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.159134</td>\n",
+       "      <td>0.405037</td>\n",
+       "      <td>0.002344</td>\n",
+       "      <td>0.006465</td>\n",
+       "      <td>0.001875</td>\n",
+       "      <td>0.001293</td>\n",
+       "      <td>0.003168</td>\n",
+       "      <td>0.081151</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202001</th>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3.141361</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1682.5</td>\n",
-       "      <td>65.042084</td>\n",
-       "      <td>0.349579</td>\n",
-       "      <td>0.668718</td>\n",
-       "      <td>0.7065</td>\n",
-       "      <td>0.678772</td>\n",
-       "      <td>0.796419</td>\n",
-       "      <td>0.712602</td>\n",
+       "      <th>01005</th>\n",
+       "      <td>0.719090</td>\n",
+       "      <td>0.888287</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>0.507593</td>\n",
+       "      <td>0.211497</td>\n",
+       "      <td>0.296096</td>\n",
+       "      <td>0.126898</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>0.761389</td>\n",
+       "      <td>15</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.962444</td>\n",
+       "      <td>0.880776</td>\n",
+       "      <td>0.085835</td>\n",
+       "      <td>0.867506</td>\n",
+       "      <td>0.068668</td>\n",
+       "      <td>0.173501</td>\n",
+       "      <td>0.242169</td>\n",
+       "      <td>0.602307</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202002</th>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>0.944287</td>\n",
+       "      <th>01007</th>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.145610</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>0.242683</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.944287</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>3.777148</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>0.388293</td>\n",
+       "      <td>14</td>\n",
        "      <td>...</td>\n",
-       "      <td>1682.5</td>\n",
-       "      <td>64.769157</td>\n",
-       "      <td>0.352308</td>\n",
-       "      <td>0.676149</td>\n",
-       "      <td>0.7065</td>\n",
-       "      <td>0.134161</td>\n",
-       "      <td>0.301321</td>\n",
-       "      <td>0.454533</td>\n",
+       "      <td>0.799491</td>\n",
+       "      <td>0.673781</td>\n",
+       "      <td>0.021313</td>\n",
+       "      <td>0.002159</td>\n",
+       "      <td>0.017050</td>\n",
+       "      <td>0.000432</td>\n",
+       "      <td>0.017482</td>\n",
+       "      <td>0.408486</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010203001</th>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1633.1</td>\n",
-       "      <td>73.538513</td>\n",
-       "      <td>0.264615</td>\n",
-       "      <td>0.407736</td>\n",
-       "      <td>0.5659</td>\n",
-       "      <td>0.002346</td>\n",
-       "      <td>0.002481</td>\n",
-       "      <td>0.244616</td>\n",
+       "      <th>01009</th>\n",
+       "      <td>0.420323</td>\n",
+       "      <td>0.437836</td>\n",
+       "      <td>0.647997</td>\n",
+       "      <td>0.315242</td>\n",
+       "      <td>0.245188</td>\n",
+       "      <td>0.262702</td>\n",
+       "      <td>0.367782</td>\n",
+       "      <td>0.928212</td>\n",
+       "      <td>0.875672</td>\n",
+       "      <td>47</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.969446</td>\n",
+       "      <td>0.624344</td>\n",
+       "      <td>0.345075</td>\n",
+       "      <td>0.020231</td>\n",
+       "      <td>0.276060</td>\n",
+       "      <td>0.004046</td>\n",
+       "      <td>0.280107</td>\n",
+       "      <td>0.624776</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
@@ -3212,261 +2972,233 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511001</th>\n",
-       "      <td>NaN</td>\n",
+       "      <th>56037</th>\n",
+       "      <td>0.633972</td>\n",
+       "      <td>0.611330</td>\n",
+       "      <td>0.316986</td>\n",
+       "      <td>0.520763</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.475479</td>\n",
+       "      <td>0.339628</td>\n",
+       "      <td>0.543404</td>\n",
+       "      <td>0.407553</td>\n",
+       "      <td>31</td>\n",
        "      <td>...</td>\n",
-       "      <td>1.4</td>\n",
-       "      <td>70.296913</td>\n",
-       "      <td>0.297031</td>\n",
-       "      <td>0.510014</td>\n",
-       "      <td>0.3925</td>\n",
-       "      <td>0.268031</td>\n",
-       "      <td>0.294215</td>\n",
-       "      <td>0.366190</td>\n",
+       "      <td>0.180140</td>\n",
+       "      <td>0.424865</td>\n",
+       "      <td>0.000773</td>\n",
+       "      <td>0.008163</td>\n",
+       "      <td>0.000619</td>\n",
+       "      <td>0.001633</td>\n",
+       "      <td>0.002251</td>\n",
+       "      <td>0.091196</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511002</th>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>56039</th>\n",
+       "      <td>0.310780</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.133191</td>\n",
+       "      <td>0.488368</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.632111</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>0.088794</td>\n",
+       "      <td>0.621559</td>\n",
+       "      <td>7</td>\n",
        "      <td>...</td>\n",
-       "      <td>1.4</td>\n",
-       "      <td>75.093887</td>\n",
-       "      <td>0.249061</td>\n",
-       "      <td>0.358402</td>\n",
-       "      <td>0.3925</td>\n",
-       "      <td>0.262987</td>\n",
-       "      <td>0.359560</td>\n",
-       "      <td>0.343362</td>\n",
+       "      <td>0.523552</td>\n",
+       "      <td>0.109058</td>\n",
+       "      <td>0.015900</td>\n",
+       "      <td>0.010563</td>\n",
+       "      <td>0.012720</td>\n",
+       "      <td>0.002113</td>\n",
+       "      <td>0.014833</td>\n",
+       "      <td>0.269192</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513001</th>\n",
-       "      <td>0.868810</td>\n",
+       "      <th>56041</th>\n",
+       "      <td>0.726111</td>\n",
+       "      <td>0.871333</td>\n",
+       "      <td>0.677704</td>\n",
+       "      <td>0.338852</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.737619</td>\n",
-       "      <td>3</td>\n",
+       "      <td>0.290444</td>\n",
+       "      <td>0.290444</td>\n",
+       "      <td>0.096815</td>\n",
+       "      <td>0.338852</td>\n",
+       "      <td>0</td>\n",
        "      <td>...</td>\n",
-       "      <td>91.0</td>\n",
-       "      <td>72.075195</td>\n",
-       "      <td>0.279248</td>\n",
-       "      <td>0.453793</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.024417</td>\n",
-       "      <td>0.661153</td>\n",
-       "      <td>0.412166</td>\n",
+       "      <td>0.060153</td>\n",
+       "      <td>0.499908</td>\n",
+       "      <td>0.000971</td>\n",
+       "      <td>0.007969</td>\n",
+       "      <td>0.000777</td>\n",
+       "      <td>0.001594</td>\n",
+       "      <td>0.002371</td>\n",
+       "      <td>0.031262</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513002</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
+       "      <th>56043</th>\n",
+       "      <td>0.978713</td>\n",
+       "      <td>0.244678</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>0.244678</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3</td>\n",
+       "      <td>0.122339</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>0.611696</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>5</td>\n",
        "      <td>...</td>\n",
-       "      <td>91.0</td>\n",
-       "      <td>79.269608</td>\n",
-       "      <td>0.207304</td>\n",
-       "      <td>0.236889</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.755818</td>\n",
-       "      <td>0.392522</td>\n",
-       "      <td>0.473632</td>\n",
+       "      <td>0.713240</td>\n",
+       "      <td>0.549097</td>\n",
+       "      <td>0.001131</td>\n",
+       "      <td>0.006738</td>\n",
+       "      <td>0.000905</td>\n",
+       "      <td>0.001348</td>\n",
+       "      <td>0.002253</td>\n",
+       "      <td>0.357746</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513003</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>6</td>\n",
-       "      <td>...</td>\n",
-       "      <td>91.0</td>\n",
-       "      <td>79.014572</td>\n",
-       "      <td>0.209854</td>\n",
-       "      <td>0.244164</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.040824</td>\n",
-       "      <td>0.202168</td>\n",
-       "      <td>0.249114</td>\n",
+       "      <th>56045</th>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>12</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.443985</td>\n",
+       "      <td>0.457246</td>\n",
+       "      <td>0.020193</td>\n",
+       "      <td>0.373095</td>\n",
+       "      <td>0.016155</td>\n",
+       "      <td>0.074619</td>\n",
+       "      <td>0.090774</td>\n",
+       "      <td>0.267379</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>217739 rows × 23 columns</p>\n",
+       "<p>3142 rows × 27 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "              fires_per_1K_pop_2009  fires_per_1K_pop_2010  \\\n",
-       "GEOID                                                        \n",
-       "010010201001               1.342282               2.684564   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120                    NaN   \n",
-       "010010202002               2.832861               2.832861   \n",
-       "010010203001               0.846024               1.269036   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
-       "\n",
-       "              fires_per_1K_pop_2011  fires_per_1K_pop_2012  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002                    NaN               1.581028   \n",
-       "010010202001               3.141361                    NaN   \n",
-       "010010202002               2.832861               0.944287   \n",
-       "010010203001               0.846024               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002               0.970874                    NaN   \n",
-       "560459513003               0.625391               0.625391   \n",
-       "\n",
-       "              fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002               0.790514                    NaN   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               1.269036               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810               0.868810   \n",
-       "560459513002                    NaN               0.970874   \n",
-       "560459513003                    NaN               0.625391   \n",
+       "       fires_per_1K_pop_2009  fires_per_1K_pop_2010  fires_per_1K_pop_2011  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.750943               0.549471               0.567786   \n",
+       "01003               0.386493               0.533971               0.447518   \n",
+       "01005               0.719090               0.888287               0.169198   \n",
+       "01007               0.097073               0.145610               0.194146   \n",
+       "01009               0.420323               0.437836               0.647997   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.633972               0.611330               0.316986   \n",
+       "56039               0.310780                    NaN               0.133191   \n",
+       "56041               0.726111               0.871333               0.677704   \n",
+       "56043               0.978713               0.244678               0.367017   \n",
+       "56045               0.293298                    NaN               0.439947   \n",
        "\n",
-       "              fires_per_1K_pop_2015  fires_per_1K_pop_2016  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN               1.342282   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               0.423012               0.846024   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN               1.372684   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001                    NaN                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
+       "       fires_per_1K_pop_2012  fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.293051               0.457892               0.201473   \n",
+       "01003               0.523800               0.462775               0.671277   \n",
+       "01005               0.507593               0.211497               0.296096   \n",
+       "01007               0.242683                    NaN                    NaN   \n",
+       "01009               0.315242               0.245188               0.262702   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.520763                    NaN               0.475479   \n",
+       "56039               0.488368                    NaN                    NaN   \n",
+       "56041               0.338852                    NaN               0.290444   \n",
+       "56043               0.244678                    NaN               0.122339   \n",
+       "56045               0.146649               0.146649               0.439947   \n",
        "\n",
-       "              fires_per_1K_pop_2017  recorded_home_visits  ...  \\\n",
-       "GEOID                                                      ...   \n",
-       "010010201001               1.342282                     0  ...   \n",
-       "010010201002                    NaN                     0  ...   \n",
-       "010010202001                    NaN                     0  ...   \n",
-       "010010202002               3.777148                     0  ...   \n",
-       "010010203001                    NaN                     0  ...   \n",
-       "...                             ...                   ...  ...   \n",
-       "560459511001                    NaN                     0  ...   \n",
-       "560459511002                    NaN                     0  ...   \n",
-       "560459513001               1.737619                     3  ...   \n",
-       "560459513002                    NaN                     3  ...   \n",
-       "560459513003                    NaN                     6  ...   \n",
+       "       fires_per_1K_pop_2015  fires_per_1K_pop_2016  fires_per_1K_pop_2017  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.531155               0.457892               0.567786   \n",
+       "01003               0.503458               0.508544               0.737388   \n",
+       "01005               0.126898               0.169198               0.761389   \n",
+       "01007               0.097073               0.194146               0.388293   \n",
+       "01009               0.367782               0.928212               0.875672   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.339628               0.543404               0.407553   \n",
+       "56039               0.887942               0.088794               0.621559   \n",
+       "56041               0.290444               0.096815               0.338852   \n",
+       "56043               0.367017               0.611696               0.367017   \n",
+       "56045               0.146649               0.293298               0.293298   \n",
        "\n",
-       "              Population Density (per square mile), 2010  detectors_predicted  \\\n",
-       "GEOID                                                                           \n",
-       "010010201001                                       504.8            81.578194   \n",
-       "010010201002                                       504.8            80.101570   \n",
-       "010010202001                                      1682.5            65.042084   \n",
-       "010010202002                                      1682.5            64.769157   \n",
-       "010010203001                                      1633.1            73.538513   \n",
-       "...                                                  ...                  ...   \n",
-       "560459511001                                         1.4            70.296913   \n",
-       "560459511002                                         1.4            75.093887   \n",
-       "560459513001                                        91.0            72.075195   \n",
-       "560459513002                                        91.0            79.269608   \n",
-       "560459513003                                        91.0            79.014572   \n",
+       "       recorded_home_visits  ...  smoke_detector_risk_score  SVI_Theme_1  \\\n",
+       "GEOID                        ...                                           \n",
+       "01001                    12  ...                   0.340547     0.458660   \n",
+       "01003                    95  ...                   0.159134     0.405037   \n",
+       "01005                    15  ...                   0.962444     0.880776   \n",
+       "01007                    14  ...                   0.799491     0.673781   \n",
+       "01009                    47  ...                   0.969446     0.624344   \n",
+       "...                     ...  ...                        ...          ...   \n",
+       "56037                    31  ...                   0.180140     0.424865   \n",
+       "56039                     7  ...                   0.523552     0.109058   \n",
+       "56041                     0  ...                   0.060153     0.499908   \n",
+       "56043                     5  ...                   0.713240     0.549097   \n",
+       "56045                    12  ...                   0.443985     0.457246   \n",
        "\n",
-       "             smoke_detector_risk_frac  smoke_detector_risk_score  SVI_Theme_1  \\\n",
-       "GEOID                                                                           \n",
-       "010010201001                 0.184218                   0.176500       0.3913   \n",
-       "010010201002                 0.198984                   0.214362       0.3913   \n",
-       "010010202001                 0.349579                   0.668718       0.7065   \n",
-       "010010202002                 0.352308                   0.676149       0.7065   \n",
-       "010010203001                 0.264615                   0.407736       0.5659   \n",
-       "...                               ...                        ...          ...   \n",
-       "560459511001                 0.297031                   0.510014       0.3925   \n",
-       "560459511002                 0.249061                   0.358402       0.3925   \n",
-       "560459513001                 0.279248                   0.453793       0.5093   \n",
-       "560459513002                 0.207304                   0.236889       0.5093   \n",
-       "560459513003                 0.209854                   0.244164       0.5093   \n",
+       "      fire_propensity_risk_score  fire_severity_risk_score  \\\n",
+       "GEOID                                                        \n",
+       "01001                   0.003780                  0.004219   \n",
+       "01003                   0.002344                  0.006465   \n",
+       "01005                   0.085835                  0.867506   \n",
+       "01007                   0.021313                  0.002159   \n",
+       "01009                   0.345075                  0.020231   \n",
+       "...                          ...                       ...   \n",
+       "56037                   0.000773                  0.008163   \n",
+       "56039                   0.015900                  0.010563   \n",
+       "56041                   0.000971                  0.007969   \n",
+       "56043                   0.001131                  0.006738   \n",
+       "56045                   0.020193                  0.373095   \n",
        "\n",
-       "              fire_propensity_risk_score  fire_severity_risk_score  \\\n",
-       "GEOID                                                                \n",
-       "010010201001                    0.278164                  0.816859   \n",
-       "010010201002                    0.079479                  0.037421   \n",
-       "010010202001                    0.678772                  0.796419   \n",
-       "010010202002                    0.134161                  0.301321   \n",
-       "010010203001                    0.002346                  0.002481   \n",
-       "...                                  ...                       ...   \n",
-       "560459511001                    0.268031                  0.294215   \n",
-       "560459511002                    0.262987                  0.359560   \n",
-       "560459513001                    0.024417                  0.661153   \n",
-       "560459513002                    0.755818                  0.392522   \n",
-       "560459513003                    0.040824                  0.202168   \n",
+       "       fire_prop_weighted  fire_sev_weighted  fire_risk_score  \\\n",
+       "GEOID                                                           \n",
+       "01001            0.003024           0.000844         0.003867   \n",
+       "01003            0.001875           0.001293         0.003168   \n",
+       "01005            0.068668           0.173501         0.242169   \n",
+       "01007            0.017050           0.000432         0.017482   \n",
+       "01009            0.276060           0.004046         0.280107   \n",
+       "...                   ...                ...              ...   \n",
+       "56037            0.000619           0.001633         0.002251   \n",
+       "56039            0.012720           0.002113         0.014833   \n",
+       "56041            0.000777           0.001594         0.002371   \n",
+       "56043            0.000905           0.001348         0.002253   \n",
+       "56045            0.016155           0.074619         0.090774   \n",
        "\n",
-       "              CombinedRiskScore  NFIRS_start  NFIRS_end  \n",
-       "GEOID                                                    \n",
-       "010010201001           0.415706         2011       2017  \n",
-       "010010201002           0.180641         2011       2017  \n",
-       "010010202001           0.712602         2011       2017  \n",
-       "010010202002           0.454533         2011       2017  \n",
-       "010010203001           0.244616         2011       2017  \n",
-       "...                         ...          ...        ...  \n",
-       "560459511001           0.366190         2011       2017  \n",
-       "560459511002           0.343362         2011       2017  \n",
-       "560459513001           0.412166         2011       2017  \n",
-       "560459513002           0.473632         2011       2017  \n",
-       "560459513003           0.249114         2011       2017  \n",
+       "       CombinedRiskScore  NFIRS_start  NFIRS_end  \n",
+       "GEOID                                             \n",
+       "01001           0.172207         2011       2017  \n",
+       "01003           0.081151         2011       2017  \n",
+       "01005           0.602307         2011       2017  \n",
+       "01007           0.408486         2011       2017  \n",
+       "01009           0.624776         2011       2017  \n",
+       "...                  ...          ...        ...  \n",
+       "56037           0.091196         2011       2017  \n",
+       "56039           0.269192         2011       2017  \n",
+       "56041           0.031262         2011       2017  \n",
+       "56043           0.357746         2011       2017  \n",
+       "56045           0.267379         2011       2017  \n",
        "\n",
-       "[217739 rows x 23 columns]"
+       "[3142 rows x 27 columns]"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3481,7 +3213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 30,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -3520,9 +3252,9 @@
        "      <th>fires_per_1K_pop_2017</th>\n",
        "      <th>recorded_home_visits</th>\n",
        "      <th>...</th>\n",
-       "      <th>SVI_Theme_1</th>\n",
-       "      <th>fire_propensity_risk_score</th>\n",
-       "      <th>fire_severity_risk_score</th>\n",
+       "      <th>fire_prop_weighted</th>\n",
+       "      <th>fire_sev_weighted</th>\n",
+       "      <th>fire_risk_score</th>\n",
        "      <th>CombinedRiskScore</th>\n",
        "      <th>NFIRS_start</th>\n",
        "      <th>NFIRS_end</th>\n",
@@ -3558,124 +3290,124 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>010010201001</th>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>2.684564</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.3913</td>\n",
-       "      <td>0.278164</td>\n",
-       "      <td>0.816859</td>\n",
-       "      <td>0.415706</td>\n",
+       "      <th>01001</th>\n",
+       "      <td>0.750943</td>\n",
+       "      <td>0.549471</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>0.293051</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>0.201473</td>\n",
+       "      <td>0.531155</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>12</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.003024</td>\n",
+       "      <td>0.000844</td>\n",
+       "      <td>0.003867</td>\n",
+       "      <td>0.172207</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010201002</th>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.3913</td>\n",
-       "      <td>0.079479</td>\n",
-       "      <td>0.037421</td>\n",
-       "      <td>0.180641</td>\n",
+       "      <td>7</td>\n",
+       "      <td>168.0</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>0.457892</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01003</th>\n",
+       "      <td>0.386493</td>\n",
+       "      <td>0.533971</td>\n",
+       "      <td>0.447518</td>\n",
+       "      <td>0.523800</td>\n",
+       "      <td>0.462775</td>\n",
+       "      <td>0.671277</td>\n",
+       "      <td>0.503458</td>\n",
+       "      <td>0.508544</td>\n",
+       "      <td>0.737388</td>\n",
+       "      <td>95</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.001875</td>\n",
+       "      <td>0.001293</td>\n",
+       "      <td>0.003168</td>\n",
+       "      <td>0.081151</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>1.185771</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010202001</th>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3.141361</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.7065</td>\n",
-       "      <td>0.678772</td>\n",
-       "      <td>0.796419</td>\n",
-       "      <td>0.712602</td>\n",
+       "      <td>7</td>\n",
+       "      <td>758.0</td>\n",
+       "      <td>0.737388</td>\n",
+       "      <td>0.508544</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01005</th>\n",
+       "      <td>0.719090</td>\n",
+       "      <td>0.888287</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>0.507593</td>\n",
+       "      <td>0.211497</td>\n",
+       "      <td>0.296096</td>\n",
+       "      <td>0.126898</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>0.761389</td>\n",
+       "      <td>15</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.068668</td>\n",
+       "      <td>0.173501</td>\n",
+       "      <td>0.242169</td>\n",
+       "      <td>0.602307</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>3.141361</td>\n",
-       "      <td>1.047120</td>\n",
+       "      <td>7</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>0.761389</td>\n",
+       "      <td>0.211497</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202002</th>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>0.944287</td>\n",
+       "      <th>01007</th>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.145610</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>0.242683</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.944287</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>3.777148</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>0.388293</td>\n",
+       "      <td>14</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.7065</td>\n",
-       "      <td>0.134161</td>\n",
-       "      <td>0.301321</td>\n",
-       "      <td>0.454533</td>\n",
+       "      <td>0.017050</td>\n",
+       "      <td>0.000432</td>\n",
+       "      <td>0.017482</td>\n",
+       "      <td>0.408486</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>3.777148</td>\n",
-       "      <td>0.944287</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010203001</th>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.5659</td>\n",
-       "      <td>0.002346</td>\n",
-       "      <td>0.002481</td>\n",
-       "      <td>0.244616</td>\n",
+       "      <td>5</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>0.388293</td>\n",
+       "      <td>0.194146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01009</th>\n",
+       "      <td>0.420323</td>\n",
+       "      <td>0.437836</td>\n",
+       "      <td>0.647997</td>\n",
+       "      <td>0.315242</td>\n",
+       "      <td>0.245188</td>\n",
+       "      <td>0.262702</td>\n",
+       "      <td>0.367782</td>\n",
+       "      <td>0.928212</td>\n",
+       "      <td>0.875672</td>\n",
+       "      <td>47</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.276060</td>\n",
+       "      <td>0.004046</td>\n",
+       "      <td>0.280107</td>\n",
+       "      <td>0.624776</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.634518</td>\n",
+       "      <td>7</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>0.928212</td>\n",
+       "      <td>0.367782</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -3702,247 +3434,233 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511001</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>56037</th>\n",
+       "      <td>0.633972</td>\n",
+       "      <td>0.611330</td>\n",
+       "      <td>0.316986</td>\n",
+       "      <td>0.520763</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.475479</td>\n",
+       "      <td>0.339628</td>\n",
+       "      <td>0.543404</td>\n",
+       "      <td>0.407553</td>\n",
+       "      <td>31</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.3925</td>\n",
-       "      <td>0.268031</td>\n",
-       "      <td>0.294215</td>\n",
-       "      <td>0.366190</td>\n",
+       "      <td>0.000619</td>\n",
+       "      <td>0.001633</td>\n",
+       "      <td>0.002251</td>\n",
+       "      <td>0.091196</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>1.372684</td>\n",
+       "      <td>6</td>\n",
+       "      <td>115.0</td>\n",
+       "      <td>0.543404</td>\n",
+       "      <td>0.441516</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511002</th>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>56039</th>\n",
+       "      <td>0.310780</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.133191</td>\n",
+       "      <td>0.488368</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.632111</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>0.088794</td>\n",
+       "      <td>0.621559</td>\n",
+       "      <td>7</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.3925</td>\n",
-       "      <td>0.262987</td>\n",
-       "      <td>0.359560</td>\n",
-       "      <td>0.343362</td>\n",
+       "      <td>0.012720</td>\n",
+       "      <td>0.002113</td>\n",
+       "      <td>0.014833</td>\n",
+       "      <td>0.269192</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>0.632111</td>\n",
+       "      <td>5</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>0.488368</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513001</th>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
+       "      <th>56041</th>\n",
+       "      <td>0.726111</td>\n",
+       "      <td>0.871333</td>\n",
+       "      <td>0.677704</td>\n",
+       "      <td>0.338852</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.737619</td>\n",
-       "      <td>3</td>\n",
+       "      <td>0.290444</td>\n",
+       "      <td>0.290444</td>\n",
+       "      <td>0.096815</td>\n",
+       "      <td>0.338852</td>\n",
+       "      <td>0</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.024417</td>\n",
-       "      <td>0.661153</td>\n",
-       "      <td>0.412166</td>\n",
+       "      <td>0.000777</td>\n",
+       "      <td>0.001594</td>\n",
+       "      <td>0.002371</td>\n",
+       "      <td>0.031262</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.737619</td>\n",
-       "      <td>0.868810</td>\n",
+       "      <td>6</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>0.677704</td>\n",
+       "      <td>0.314648</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513002</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
+       "      <th>56043</th>\n",
+       "      <td>0.978713</td>\n",
+       "      <td>0.244678</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>0.244678</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3</td>\n",
+       "      <td>0.122339</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>0.611696</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>5</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.755818</td>\n",
-       "      <td>0.392522</td>\n",
-       "      <td>0.473632</td>\n",
+       "      <td>0.000905</td>\n",
+       "      <td>0.001348</td>\n",
+       "      <td>0.002253</td>\n",
+       "      <td>0.357746</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>0.970874</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>560459513003</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>6</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.5093</td>\n",
-       "      <td>0.040824</td>\n",
-       "      <td>0.202168</td>\n",
-       "      <td>0.249114</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0.611696</td>\n",
+       "      <td>0.367017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56045</th>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>12</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.016155</td>\n",
+       "      <td>0.074619</td>\n",
+       "      <td>0.090774</td>\n",
+       "      <td>0.267379</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.293298</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>217739 rows × 27 columns</p>\n",
+       "<p>3142 rows × 31 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "              fires_per_1K_pop_2009  fires_per_1K_pop_2010  \\\n",
-       "GEOID                                                        \n",
-       "010010201001               1.342282               2.684564   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120                    NaN   \n",
-       "010010202002               2.832861               2.832861   \n",
-       "010010203001               0.846024               1.269036   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
-       "\n",
-       "              fires_per_1K_pop_2011  fires_per_1K_pop_2012  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002                    NaN               1.581028   \n",
-       "010010202001               3.141361                    NaN   \n",
-       "010010202002               2.832861               0.944287   \n",
-       "010010203001               0.846024               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002               0.970874                    NaN   \n",
-       "560459513003               0.625391               0.625391   \n",
+       "       fires_per_1K_pop_2009  fires_per_1K_pop_2010  fires_per_1K_pop_2011  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.750943               0.549471               0.567786   \n",
+       "01003               0.386493               0.533971               0.447518   \n",
+       "01005               0.719090               0.888287               0.169198   \n",
+       "01007               0.097073               0.145610               0.194146   \n",
+       "01009               0.420323               0.437836               0.647997   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.633972               0.611330               0.316986   \n",
+       "56039               0.310780                    NaN               0.133191   \n",
+       "56041               0.726111               0.871333               0.677704   \n",
+       "56043               0.978713               0.244678               0.367017   \n",
+       "56045               0.293298                    NaN               0.439947   \n",
        "\n",
-       "              fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002               0.790514                    NaN   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               1.269036               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810               0.868810   \n",
-       "560459513002                    NaN               0.970874   \n",
-       "560459513003                    NaN               0.625391   \n",
+       "       fires_per_1K_pop_2012  fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.293051               0.457892               0.201473   \n",
+       "01003               0.523800               0.462775               0.671277   \n",
+       "01005               0.507593               0.211497               0.296096   \n",
+       "01007               0.242683                    NaN                    NaN   \n",
+       "01009               0.315242               0.245188               0.262702   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.520763                    NaN               0.475479   \n",
+       "56039               0.488368                    NaN                    NaN   \n",
+       "56041               0.338852                    NaN               0.290444   \n",
+       "56043               0.244678                    NaN               0.122339   \n",
+       "56045               0.146649               0.146649               0.439947   \n",
        "\n",
-       "              fires_per_1K_pop_2015  fires_per_1K_pop_2016  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN               1.342282   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               0.423012               0.846024   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN               1.372684   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001                    NaN                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
+       "       fires_per_1K_pop_2015  fires_per_1K_pop_2016  fires_per_1K_pop_2017  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.531155               0.457892               0.567786   \n",
+       "01003               0.503458               0.508544               0.737388   \n",
+       "01005               0.126898               0.169198               0.761389   \n",
+       "01007               0.097073               0.194146               0.388293   \n",
+       "01009               0.367782               0.928212               0.875672   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.339628               0.543404               0.407553   \n",
+       "56039               0.887942               0.088794               0.621559   \n",
+       "56041               0.290444               0.096815               0.338852   \n",
+       "56043               0.367017               0.611696               0.367017   \n",
+       "56045               0.146649               0.293298               0.293298   \n",
        "\n",
-       "              fires_per_1K_pop_2017  recorded_home_visits  ...  SVI_Theme_1  \\\n",
-       "GEOID                                                      ...                \n",
-       "010010201001               1.342282                     0  ...       0.3913   \n",
-       "010010201002                    NaN                     0  ...       0.3913   \n",
-       "010010202001                    NaN                     0  ...       0.7065   \n",
-       "010010202002               3.777148                     0  ...       0.7065   \n",
-       "010010203001                    NaN                     0  ...       0.5659   \n",
-       "...                             ...                   ...  ...          ...   \n",
-       "560459511001                    NaN                     0  ...       0.3925   \n",
-       "560459511002                    NaN                     0  ...       0.3925   \n",
-       "560459513001               1.737619                     3  ...       0.5093   \n",
-       "560459513002                    NaN                     3  ...       0.5093   \n",
-       "560459513003                    NaN                     6  ...       0.5093   \n",
+       "       recorded_home_visits  ...  fire_prop_weighted  fire_sev_weighted  \\\n",
+       "GEOID                        ...                                          \n",
+       "01001                    12  ...            0.003024           0.000844   \n",
+       "01003                    95  ...            0.001875           0.001293   \n",
+       "01005                    15  ...            0.068668           0.173501   \n",
+       "01007                    14  ...            0.017050           0.000432   \n",
+       "01009                    47  ...            0.276060           0.004046   \n",
+       "...                     ...  ...                 ...                ...   \n",
+       "56037                    31  ...            0.000619           0.001633   \n",
+       "56039                     7  ...            0.012720           0.002113   \n",
+       "56041                     0  ...            0.000777           0.001594   \n",
+       "56043                     5  ...            0.000905           0.001348   \n",
+       "56045                    12  ...            0.016155           0.074619   \n",
        "\n",
-       "              fire_propensity_risk_score fire_severity_risk_score  \\\n",
-       "GEOID                                                               \n",
-       "010010201001                    0.278164                 0.816859   \n",
-       "010010201002                    0.079479                 0.037421   \n",
-       "010010202001                    0.678772                 0.796419   \n",
-       "010010202002                    0.134161                 0.301321   \n",
-       "010010203001                    0.002346                 0.002481   \n",
-       "...                                  ...                      ...   \n",
-       "560459511001                    0.268031                 0.294215   \n",
-       "560459511002                    0.262987                 0.359560   \n",
-       "560459513001                    0.024417                 0.661153   \n",
-       "560459513002                    0.755818                 0.392522   \n",
-       "560459513003                    0.040824                 0.202168   \n",
+       "      fire_risk_score  CombinedRiskScore  NFIRS_start  NFIRS_end  \\\n",
+       "GEOID                                                              \n",
+       "01001        0.003867           0.172207         2011       2017   \n",
+       "01003        0.003168           0.081151         2011       2017   \n",
+       "01005        0.242169           0.602307         2011       2017   \n",
+       "01007        0.017482           0.408486         2011       2017   \n",
+       "01009        0.280107           0.624776         2011       2017   \n",
+       "...               ...                ...          ...        ...   \n",
+       "56037        0.002251           0.091196         2011       2017   \n",
+       "56039        0.014833           0.269192         2011       2017   \n",
+       "56041        0.002371           0.031262         2011       2017   \n",
+       "56043        0.002253           0.357746         2011       2017   \n",
+       "56045        0.090774           0.267379         2011       2017   \n",
        "\n",
-       "              CombinedRiskScore  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
-       "GEOID                                                                           \n",
-       "010010201001           0.415706         2011       2017                   2.0   \n",
-       "010010201002           0.180641         2011       2017                   4.0   \n",
-       "010010202001           0.712602         2011       2017                   5.0   \n",
-       "010010202002           0.454533         2011       2017                   5.0   \n",
-       "010010203001           0.244616         2011       2017                   6.0   \n",
-       "...                         ...          ...        ...                   ...   \n",
-       "560459511001           0.366190         2011       2017                   1.0   \n",
-       "560459511002           0.343362         2011       2017                   1.0   \n",
-       "560459513001           0.412166         2011       2017                   4.0   \n",
-       "560459513002           0.473632         2011       2017                   2.0   \n",
-       "560459513003           0.249114         2011       2017                   3.0   \n",
+       "       years_fires_reported  total_fires_reported  max_fires_1k  \\\n",
+       "GEOID                                                             \n",
+       "01001                     7                 168.0      0.567786   \n",
+       "01003                     7                 758.0      0.737388   \n",
+       "01005                     7                  53.0      0.761389   \n",
+       "01007                     5                  23.0      0.388293   \n",
+       "01009                     7                 208.0      0.928212   \n",
+       "...                     ...                   ...           ...   \n",
+       "56037                     6                 115.0      0.543404   \n",
+       "56039                     5                  50.0      0.887942   \n",
+       "56041                     6                  42.0      0.677704   \n",
+       "56043                     6                  17.0      0.611696   \n",
+       "56045                     7                  13.0      0.439947   \n",
        "\n",
-       "              total_fires_reported  max_fires_1k  median_fires_1k  \n",
-       "GEOID                                                              \n",
-       "010010201001                   2.0      1.342282         1.342282  \n",
-       "010010201002                   6.0      1.581028         1.185771  \n",
-       "010010202001                   7.0      3.141361         1.047120  \n",
-       "010010202002                  10.0      3.777148         0.944287  \n",
-       "010010203001                  10.0      1.269036         0.634518  \n",
-       "...                            ...           ...              ...  \n",
-       "560459511001                   2.0      1.372684         1.372684  \n",
-       "560459511002                   1.0      0.632111         0.632111  \n",
-       "560459513001                   5.0      1.737619         0.868810  \n",
-       "560459513002                   2.0      0.970874         0.970874  \n",
-       "560459513003                   3.0      0.625391         0.625391  \n",
+       "       median_fires_1k  \n",
+       "GEOID                   \n",
+       "01001         0.457892  \n",
+       "01003         0.508544  \n",
+       "01005         0.211497  \n",
+       "01007         0.194146  \n",
+       "01009         0.367782  \n",
+       "...                ...  \n",
+       "56037         0.441516  \n",
+       "56039         0.488368  \n",
+       "56041         0.314648  \n",
+       "56043         0.367017  \n",
+       "56045         0.293298  \n",
        "\n",
-       "[217739 rows x 27 columns]"
+       "[3142 rows x 31 columns]"
       ]
      },
-     "execution_count": 36,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3975,7 +3693,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 31,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -4052,124 +3770,124 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>010010201001</th>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>2.684564</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.415706</td>\n",
+       "      <th>01001</th>\n",
+       "      <td>0.750943</td>\n",
+       "      <td>0.549471</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>0.293051</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>0.201473</td>\n",
+       "      <td>0.531155</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>12</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.172207</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>2.684564</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010201002</th>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.180641</td>\n",
+       "      <td>7</td>\n",
+       "      <td>168.0</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>0.164841</td>\n",
+       "      <td>0.109894</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01003</th>\n",
+       "      <td>0.386493</td>\n",
+       "      <td>0.533971</td>\n",
+       "      <td>0.447518</td>\n",
+       "      <td>0.523800</td>\n",
+       "      <td>0.462775</td>\n",
+       "      <td>0.671277</td>\n",
+       "      <td>0.503458</td>\n",
+       "      <td>0.508544</td>\n",
+       "      <td>0.737388</td>\n",
+       "      <td>95</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.081151</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>1.185771</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>0.790514</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010202001</th>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3.141361</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.712602</td>\n",
+       "      <td>7</td>\n",
+       "      <td>758.0</td>\n",
+       "      <td>0.737388</td>\n",
+       "      <td>0.508544</td>\n",
+       "      <td>133.0</td>\n",
+       "      <td>0.122050</td>\n",
+       "      <td>0.091538</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01005</th>\n",
+       "      <td>0.719090</td>\n",
+       "      <td>0.888287</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>0.507593</td>\n",
+       "      <td>0.211497</td>\n",
+       "      <td>0.296096</td>\n",
+       "      <td>0.126898</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>0.761389</td>\n",
+       "      <td>15</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.602307</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>3.141361</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>2.094241</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
+       "      <td>7</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>0.761389</td>\n",
+       "      <td>0.211497</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0.338395</td>\n",
+       "      <td>0.169198</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202002</th>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>0.944287</td>\n",
+       "      <th>01007</th>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.145610</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>0.242683</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.944287</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>3.777148</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>0.388293</td>\n",
+       "      <td>14</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.454533</td>\n",
+       "      <td>0.408486</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>0.388293</td>\n",
+       "      <td>0.194146</td>\n",
        "      <td>5.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>3.777148</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>1.888574</td>\n",
-       "      <td>1.416431</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>010010203001</th>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.244616</td>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.048537</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01009</th>\n",
+       "      <td>0.420323</td>\n",
+       "      <td>0.437836</td>\n",
+       "      <td>0.647997</td>\n",
+       "      <td>0.315242</td>\n",
+       "      <td>0.245188</td>\n",
+       "      <td>0.262702</td>\n",
+       "      <td>0.367782</td>\n",
+       "      <td>0.928212</td>\n",
+       "      <td>0.875672</td>\n",
+       "      <td>47</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.624776</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.634518</td>\n",
-       "      <td>2.115059</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.423012</td>\n",
+       "      <td>7</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>0.928212</td>\n",
+       "      <td>0.367782</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.315242</td>\n",
+       "      <td>0.087567</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -4196,253 +3914,239 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511001</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>56037</th>\n",
+       "      <td>0.633972</td>\n",
+       "      <td>0.611330</td>\n",
+       "      <td>0.316986</td>\n",
+       "      <td>0.520763</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.475479</td>\n",
+       "      <td>0.339628</td>\n",
+       "      <td>0.543404</td>\n",
+       "      <td>0.407553</td>\n",
+       "      <td>31</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.366190</td>\n",
+       "      <td>0.091196</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>1.372684</td>\n",
+       "      <td>6</td>\n",
+       "      <td>115.0</td>\n",
+       "      <td>0.543404</td>\n",
+       "      <td>0.441516</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0.226419</td>\n",
+       "      <td>0.135851</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511002</th>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>56039</th>\n",
+       "      <td>0.310780</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.133191</td>\n",
+       "      <td>0.488368</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>0.088794</td>\n",
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        "      <td>...</td>\n",
-       "      <td>0.343362</td>\n",
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        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
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-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>5</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>0.488368</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>0.177588</td>\n",
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        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513001</th>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
+       "      <th>56041</th>\n",
+       "      <td>0.726111</td>\n",
+       "      <td>0.871333</td>\n",
+       "      <td>0.677704</td>\n",
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        "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.737619</td>\n",
-       "      <td>3</td>\n",
+       "      <td>0.290444</td>\n",
+       "      <td>0.290444</td>\n",
+       "      <td>0.096815</td>\n",
+       "      <td>0.338852</td>\n",
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        "      <td>...</td>\n",
-       "      <td>0.412166</td>\n",
+       "      <td>0.031262</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.737619</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>6</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>0.677704</td>\n",
+       "      <td>0.314648</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.048407</td>\n",
+       "      <td>0.048407</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513002</th>\n",
-       "      <td>NaN</td>\n",
+       "      <th>56043</th>\n",
+       "      <td>0.978713</td>\n",
+       "      <td>0.244678</td>\n",
+       "      <td>0.367017</td>\n",
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        "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3</td>\n",
+       "      <td>0.122339</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>0.611696</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>5</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.473632</td>\n",
+       "      <td>0.357746</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>6</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0.611696</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.244678</td>\n",
+       "      <td>0.122339</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513003</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
+       "      <th>56045</th>\n",
+       "      <td>0.293298</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>6</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>12</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.249114</td>\n",
+       "      <td>0.267379</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.293298</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>0.219974</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>217739 rows × 30 columns</p>\n",
+       "<p>3142 rows × 34 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "              fires_per_1K_pop_2009  fires_per_1K_pop_2010  \\\n",
-       "GEOID                                                        \n",
-       "010010201001               1.342282               2.684564   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120                    NaN   \n",
-       "010010202002               2.832861               2.832861   \n",
-       "010010203001               0.846024               1.269036   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
-       "\n",
-       "              fires_per_1K_pop_2011  fires_per_1K_pop_2012  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002                    NaN               1.581028   \n",
-       "010010202001               3.141361                    NaN   \n",
-       "010010202002               2.832861               0.944287   \n",
-       "010010203001               0.846024               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002               0.970874                    NaN   \n",
-       "560459513003               0.625391               0.625391   \n",
+       "       fires_per_1K_pop_2009  fires_per_1K_pop_2010  fires_per_1K_pop_2011  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.750943               0.549471               0.567786   \n",
+       "01003               0.386493               0.533971               0.447518   \n",
+       "01005               0.719090               0.888287               0.169198   \n",
+       "01007               0.097073               0.145610               0.194146   \n",
+       "01009               0.420323               0.437836               0.647997   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.633972               0.611330               0.316986   \n",
+       "56039               0.310780                    NaN               0.133191   \n",
+       "56041               0.726111               0.871333               0.677704   \n",
+       "56043               0.978713               0.244678               0.367017   \n",
+       "56045               0.293298                    NaN               0.439947   \n",
        "\n",
-       "              fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002               0.790514                    NaN   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               1.269036               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810               0.868810   \n",
-       "560459513002                    NaN               0.970874   \n",
-       "560459513003                    NaN               0.625391   \n",
+       "       fires_per_1K_pop_2012  fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.293051               0.457892               0.201473   \n",
+       "01003               0.523800               0.462775               0.671277   \n",
+       "01005               0.507593               0.211497               0.296096   \n",
+       "01007               0.242683                    NaN                    NaN   \n",
+       "01009               0.315242               0.245188               0.262702   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.520763                    NaN               0.475479   \n",
+       "56039               0.488368                    NaN                    NaN   \n",
+       "56041               0.338852                    NaN               0.290444   \n",
+       "56043               0.244678                    NaN               0.122339   \n",
+       "56045               0.146649               0.146649               0.439947   \n",
        "\n",
-       "              fires_per_1K_pop_2015  fires_per_1K_pop_2016  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN               1.342282   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               0.423012               0.846024   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN               1.372684   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001                    NaN                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
+       "       fires_per_1K_pop_2015  fires_per_1K_pop_2016  fires_per_1K_pop_2017  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.531155               0.457892               0.567786   \n",
+       "01003               0.503458               0.508544               0.737388   \n",
+       "01005               0.126898               0.169198               0.761389   \n",
+       "01007               0.097073               0.194146               0.388293   \n",
+       "01009               0.367782               0.928212               0.875672   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.339628               0.543404               0.407553   \n",
+       "56039               0.887942               0.088794               0.621559   \n",
+       "56041               0.290444               0.096815               0.338852   \n",
+       "56043               0.367017               0.611696               0.367017   \n",
+       "56045               0.146649               0.293298               0.293298   \n",
        "\n",
-       "              fires_per_1K_pop_2017  recorded_home_visits  ...  \\\n",
-       "GEOID                                                      ...   \n",
-       "010010201001               1.342282                     0  ...   \n",
-       "010010201002                    NaN                     0  ...   \n",
-       "010010202001                    NaN                     0  ...   \n",
-       "010010202002               3.777148                     0  ...   \n",
-       "010010203001                    NaN                     0  ...   \n",
-       "...                             ...                   ...  ...   \n",
-       "560459511001                    NaN                     0  ...   \n",
-       "560459511002                    NaN                     0  ...   \n",
-       "560459513001               1.737619                     3  ...   \n",
-       "560459513002                    NaN                     3  ...   \n",
-       "560459513003                    NaN                     6  ...   \n",
+       "       recorded_home_visits  ...  CombinedRiskScore  NFIRS_start NFIRS_end  \\\n",
+       "GEOID                        ...                                             \n",
+       "01001                    12  ...           0.172207         2011      2017   \n",
+       "01003                    95  ...           0.081151         2011      2017   \n",
+       "01005                    15  ...           0.602307         2011      2017   \n",
+       "01007                    14  ...           0.408486         2011      2017   \n",
+       "01009                    47  ...           0.624776         2011      2017   \n",
+       "...                     ...  ...                ...          ...       ...   \n",
+       "56037                    31  ...           0.091196         2011      2017   \n",
+       "56039                     7  ...           0.269192         2011      2017   \n",
+       "56041                     0  ...           0.031262         2011      2017   \n",
+       "56043                     5  ...           0.357746         2011      2017   \n",
+       "56045                    12  ...           0.267379         2011      2017   \n",
        "\n",
-       "              CombinedRiskScore  NFIRS_start NFIRS_end  years_fires_reported  \\\n",
-       "GEOID                                                                          \n",
-       "010010201001           0.415706         2011      2017                   2.0   \n",
-       "010010201002           0.180641         2011      2017                   4.0   \n",
-       "010010202001           0.712602         2011      2017                   5.0   \n",
-       "010010202002           0.454533         2011      2017                   5.0   \n",
-       "010010203001           0.244616         2011      2017                   6.0   \n",
-       "...                         ...          ...       ...                   ...   \n",
-       "560459511001           0.366190         2011      2017                   1.0   \n",
-       "560459511002           0.343362         2011      2017                   1.0   \n",
-       "560459513001           0.412166         2011      2017                   4.0   \n",
-       "560459513002           0.473632         2011      2017                   2.0   \n",
-       "560459513003           0.249114         2011      2017                   3.0   \n",
+       "       years_fires_reported  total_fires_reported  max_fires_1k  \\\n",
+       "GEOID                                                             \n",
+       "01001                     7                 168.0      0.567786   \n",
+       "01003                     7                 758.0      0.737388   \n",
+       "01005                     7                  53.0      0.761389   \n",
+       "01007                     5                  23.0      0.388293   \n",
+       "01009                     7                 208.0      0.928212   \n",
+       "...                     ...                   ...           ...   \n",
+       "56037                     6                 115.0      0.543404   \n",
+       "56039                     5                  50.0      0.887942   \n",
+       "56041                     6                  42.0      0.677704   \n",
+       "56043                     6                  17.0      0.611696   \n",
+       "56045                     7                  13.0      0.439947   \n",
        "\n",
-       "              total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
-       "GEOID                                                               \n",
-       "010010201001                   2.0      1.342282         1.342282   \n",
-       "010010201002                   6.0      1.581028         1.185771   \n",
-       "010010202001                   7.0      3.141361         1.047120   \n",
-       "010010202002                  10.0      3.777148         0.944287   \n",
-       "010010203001                  10.0      1.269036         0.634518   \n",
-       "...                            ...           ...              ...   \n",
-       "560459511001                   2.0      1.372684         1.372684   \n",
-       "560459511002                   1.0      0.632111         0.632111   \n",
-       "560459513001                   5.0      1.737619         0.868810   \n",
-       "560459513002                   2.0      0.970874         0.970874   \n",
-       "560459513003                   3.0      0.625391         0.625391   \n",
+       "       median_fires_1k  total_fires_reported_sev  max_fires_1k_sev  \\\n",
+       "GEOID                                                                \n",
+       "01001         0.457892                      38.0          0.164841   \n",
+       "01003         0.508544                     133.0          0.122050   \n",
+       "01005         0.211497                      15.0          0.338395   \n",
+       "01007         0.194146                       5.0          0.097073   \n",
+       "01009         0.367782                      51.0          0.315242   \n",
+       "...                ...                       ...               ...   \n",
+       "56037         0.441516                      32.0          0.226419   \n",
+       "56039         0.488368                      11.0          0.177588   \n",
+       "56041         0.314648                       3.0          0.048407   \n",
+       "56043         0.367017                       4.0          0.244678   \n",
+       "56045         0.293298                       3.0          0.293298   \n",
        "\n",
-       "              total_fires_reported_sev  max_fires_1k_sev  median_fires_1k_sev  \n",
-       "GEOID                                                                          \n",
-       "010010201001                  2.684564          1.342282             1.342282  \n",
-       "010010201002                  1.581028          0.790514             0.790514  \n",
-       "010010202001                  2.094241          1.047120             1.047120  \n",
-       "010010202002                  2.832861          1.888574             1.416431  \n",
-       "010010203001                  2.115059          0.423012             0.423012  \n",
-       "...                                ...               ...                  ...  \n",
-       "560459511001                  1.372684          1.372684             1.372684  \n",
-       "560459511002                  0.000000               NaN                  NaN  \n",
-       "560459513001                  0.000000               NaN                  NaN  \n",
-       "560459513002                  0.000000               NaN                  NaN  \n",
-       "560459513003                  0.625391          0.625391             0.625391  \n",
+       "       median_fires_1k_sev  \n",
+       "GEOID                       \n",
+       "01001             0.109894  \n",
+       "01003             0.091538  \n",
+       "01005             0.169198  \n",
+       "01007             0.048537  \n",
+       "01009             0.087567  \n",
+       "...                    ...  \n",
+       "56037             0.135851  \n",
+       "56039             0.133191  \n",
+       "56041             0.048407  \n",
+       "56043             0.122339  \n",
+       "56045             0.219974  \n",
        "\n",
-       "[217739 rows x 30 columns]"
+       "[3142 rows x 34 columns]"
       ]
      },
-     "execution_count": 37,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "fires_trained = NFIRS_Sev.fires[years]\n",
+    "fires_trained = NFIRS_Sev.fires_noAdjustment[years]\n",
     "fires_trained['total_fires_reported_sev'] = fires_trained.sum(axis = 1)\n",
     "fires_trained = fires_trained['total_fires_reported_sev']\n",
     "out = out.merge(fires_trained, how = 'left', left_index = True, right_index = True)\n",
@@ -4463,7 +4167,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 32,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -4494,7 +4198,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 33,
    "metadata": {
     "tags": [
      "remove_cell"
@@ -4571,124 +4275,587 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>010010201001</th>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>2.684564</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>01001</th>\n",
+       "      <td>0.750943</td>\n",
+       "      <td>0.549471</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>0.293051</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>0.201473</td>\n",
+       "      <td>0.531155</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>12</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.019504</td>\n",
+       "      <td>0.337628</td>\n",
+       "      <td>0.139963</td>\n",
+       "      <td>0.347003</td>\n",
+       "      <td>0.127977</td>\n",
+       "      <td>0.728978</td>\n",
+       "      <td>0.089284</td>\n",
+       "      <td>0.180285</td>\n",
+       "      <td>0.001453</td>\n",
+       "      <td>0.022453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01003</th>\n",
+       "      <td>0.386493</td>\n",
+       "      <td>0.533971</td>\n",
+       "      <td>0.447518</td>\n",
+       "      <td>0.523800</td>\n",
+       "      <td>0.462775</td>\n",
+       "      <td>0.671277</td>\n",
+       "      <td>0.503458</td>\n",
+       "      <td>0.508544</td>\n",
+       "      <td>0.737388</td>\n",
+       "      <td>95</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.020327</td>\n",
+       "      <td>0.298873</td>\n",
+       "      <td>0.187231</td>\n",
+       "      <td>0.263131</td>\n",
+       "      <td>0.089366</td>\n",
+       "      <td>0.630123</td>\n",
+       "      <td>0.249631</td>\n",
+       "      <td>0.119252</td>\n",
+       "      <td>0.000995</td>\n",
+       "      <td>0.044759</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01005</th>\n",
+       "      <td>0.719090</td>\n",
+       "      <td>0.888287</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>0.507593</td>\n",
+       "      <td>0.211497</td>\n",
+       "      <td>0.296096</td>\n",
+       "      <td>0.126898</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>0.761389</td>\n",
+       "      <td>15</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.005240</td>\n",
+       "      <td>0.328502</td>\n",
+       "      <td>0.173040</td>\n",
+       "      <td>0.401597</td>\n",
+       "      <td>0.257016</td>\n",
+       "      <td>0.576597</td>\n",
+       "      <td>0.121674</td>\n",
+       "      <td>0.299441</td>\n",
+       "      <td>0.002288</td>\n",
+       "      <td>0.050249</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01007</th>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.145610</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>0.242683</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>0.388293</td>\n",
+       "      <td>14</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.013765</td>\n",
+       "      <td>0.320549</td>\n",
+       "      <td>0.151724</td>\n",
+       "      <td>0.318074</td>\n",
+       "      <td>0.146243</td>\n",
+       "      <td>0.643781</td>\n",
+       "      <td>0.072113</td>\n",
+       "      <td>0.284106</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.014411</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01009</th>\n",
+       "      <td>0.420323</td>\n",
+       "      <td>0.437836</td>\n",
+       "      <td>0.647997</td>\n",
+       "      <td>0.315242</td>\n",
+       "      <td>0.245188</td>\n",
+       "      <td>0.262702</td>\n",
+       "      <td>0.367782</td>\n",
+       "      <td>0.928212</td>\n",
+       "      <td>0.875672</td>\n",
+       "      <td>47</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.016088</td>\n",
+       "      <td>0.315907</td>\n",
+       "      <td>0.172013</td>\n",
+       "      <td>0.300140</td>\n",
+       "      <td>0.116018</td>\n",
+       "      <td>0.731656</td>\n",
+       "      <td>0.038784</td>\n",
+       "      <td>0.229224</td>\n",
+       "      <td>0.000335</td>\n",
+       "      <td>0.057006</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\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>56037</th>\n",
+       "      <td>0.633972</td>\n",
+       "      <td>0.611330</td>\n",
+       "      <td>0.316986</td>\n",
+       "      <td>0.520763</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.475479</td>\n",
+       "      <td>0.339628</td>\n",
+       "      <td>0.543404</td>\n",
+       "      <td>0.407553</td>\n",
+       "      <td>31</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.363758</td>\n",
-       "      <td>0.036242</td>\n",
-       "      <td>0.239437</td>\n",
-       "      <td>0.183099</td>\n",
-       "      <td>0.820423</td>\n",
-       "      <td>0.024648</td>\n",
-       "      <td>0.154930</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.102113</td>\n",
+       "      <td>0.034314</td>\n",
+       "      <td>0.365076</td>\n",
+       "      <td>0.094774</td>\n",
+       "      <td>0.244424</td>\n",
+       "      <td>0.044100</td>\n",
+       "      <td>0.616271</td>\n",
+       "      <td>0.158779</td>\n",
+       "      <td>0.224322</td>\n",
+       "      <td>0.000628</td>\n",
+       "      <td>0.093154</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010201002</th>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
+       "      <th>56039</th>\n",
+       "      <td>0.310780</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
+       "      <td>0.133191</td>\n",
+       "      <td>0.488368</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>0.088794</td>\n",
+       "      <td>0.621559</td>\n",
+       "      <td>7</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.054545</td>\n",
-       "      <td>0.348617</td>\n",
-       "      <td>0.114625</td>\n",
-       "      <td>0.278509</td>\n",
-       "      <td>0.096491</td>\n",
-       "      <td>0.925054</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.074946</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.046053</td>\n",
+       "      <td>0.009976</td>\n",
+       "      <td>0.252004</td>\n",
+       "      <td>0.118485</td>\n",
+       "      <td>0.116231</td>\n",
+       "      <td>0.014235</td>\n",
+       "      <td>0.702453</td>\n",
+       "      <td>0.260909</td>\n",
+       "      <td>0.030319</td>\n",
+       "      <td>0.006320</td>\n",
+       "      <td>0.124490</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202001</th>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3.141361</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
+       "      <th>56041</th>\n",
+       "      <td>0.726111</td>\n",
+       "      <td>0.871333</td>\n",
+       "      <td>0.677704</td>\n",
+       "      <td>0.338852</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.290444</td>\n",
+       "      <td>0.290444</td>\n",
+       "      <td>0.096815</td>\n",
+       "      <td>0.338852</td>\n",
        "      <td>0</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.018750</td>\n",
-       "      <td>0.372917</td>\n",
-       "      <td>0.161458</td>\n",
-       "      <td>0.458549</td>\n",
-       "      <td>0.303109</td>\n",
-       "      <td>0.768844</td>\n",
-       "      <td>0.201005</td>\n",
-       "      <td>0.030151</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
+       "      <td>0.030348</td>\n",
+       "      <td>0.375898</td>\n",
+       "      <td>0.106618</td>\n",
+       "      <td>0.307708</td>\n",
+       "      <td>0.083410</td>\n",
+       "      <td>0.612454</td>\n",
+       "      <td>0.133782</td>\n",
+       "      <td>0.246122</td>\n",
+       "      <td>0.007641</td>\n",
+       "      <td>0.081690</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56043</th>\n",
+       "      <td>0.978713</td>\n",
+       "      <td>0.244678</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>0.244678</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.122339</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>0.611696</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.039509</td>\n",
+       "      <td>0.301766</td>\n",
+       "      <td>0.195733</td>\n",
+       "      <td>0.363713</td>\n",
+       "      <td>0.081943</td>\n",
+       "      <td>0.776961</td>\n",
+       "      <td>0.103910</td>\n",
+       "      <td>0.113356</td>\n",
+       "      <td>0.005773</td>\n",
+       "      <td>0.102321</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56045</th>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.146649</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>12</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014400</td>\n",
+       "      <td>0.281251</td>\n",
+       "      <td>0.180368</td>\n",
+       "      <td>0.261284</td>\n",
+       "      <td>0.072122</td>\n",
+       "      <td>0.707261</td>\n",
+       "      <td>0.053173</td>\n",
+       "      <td>0.237850</td>\n",
+       "      <td>0.001715</td>\n",
+       "      <td>0.002177</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3142 rows × 65 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       fires_per_1K_pop_2009  fires_per_1K_pop_2010  fires_per_1K_pop_2011  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.750943               0.549471               0.567786   \n",
+       "01003               0.386493               0.533971               0.447518   \n",
+       "01005               0.719090               0.888287               0.169198   \n",
+       "01007               0.097073               0.145610               0.194146   \n",
+       "01009               0.420323               0.437836               0.647997   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.633972               0.611330               0.316986   \n",
+       "56039               0.310780                    NaN               0.133191   \n",
+       "56041               0.726111               0.871333               0.677704   \n",
+       "56043               0.978713               0.244678               0.367017   \n",
+       "56045               0.293298                    NaN               0.439947   \n",
+       "\n",
+       "       fires_per_1K_pop_2012  fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.293051               0.457892               0.201473   \n",
+       "01003               0.523800               0.462775               0.671277   \n",
+       "01005               0.507593               0.211497               0.296096   \n",
+       "01007               0.242683                    NaN                    NaN   \n",
+       "01009               0.315242               0.245188               0.262702   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.520763                    NaN               0.475479   \n",
+       "56039               0.488368                    NaN                    NaN   \n",
+       "56041               0.338852                    NaN               0.290444   \n",
+       "56043               0.244678                    NaN               0.122339   \n",
+       "56045               0.146649               0.146649               0.439947   \n",
+       "\n",
+       "       fires_per_1K_pop_2015  fires_per_1K_pop_2016  fires_per_1K_pop_2017  \\\n",
+       "GEOID                                                                        \n",
+       "01001               0.531155               0.457892               0.567786   \n",
+       "01003               0.503458               0.508544               0.737388   \n",
+       "01005               0.126898               0.169198               0.761389   \n",
+       "01007               0.097073               0.194146               0.388293   \n",
+       "01009               0.367782               0.928212               0.875672   \n",
+       "...                      ...                    ...                    ...   \n",
+       "56037               0.339628               0.543404               0.407553   \n",
+       "56039               0.887942               0.088794               0.621559   \n",
+       "56041               0.290444               0.096815               0.338852   \n",
+       "56043               0.367017               0.611696               0.367017   \n",
+       "56045               0.146649               0.293298               0.293298   \n",
+       "\n",
+       "       recorded_home_visits  ...  race_pct_two+  age_pct_under25  \\\n",
+       "GEOID                        ...                                   \n",
+       "01001                    12  ...       0.019504         0.337628   \n",
+       "01003                    95  ...       0.020327         0.298873   \n",
+       "01005                    15  ...       0.005240         0.328502   \n",
+       "01007                    14  ...       0.013765         0.320549   \n",
+       "01009                    47  ...       0.016088         0.315907   \n",
+       "...                     ...  ...            ...              ...   \n",
+       "56037                    31  ...       0.034314         0.365076   \n",
+       "56039                     7  ...       0.009976         0.252004   \n",
+       "56041                     0  ...       0.030348         0.375898   \n",
+       "56043                     5  ...       0.039509         0.301766   \n",
+       "56045                    12  ...       0.014400         0.281251   \n",
+       "\n",
+       "      age_pct_over65  disability_pct  snap_past_12_mo  single_unit_home  \\\n",
+       "GEOID                                                                     \n",
+       "01001       0.139963        0.347003         0.127977          0.728978   \n",
+       "01003       0.187231        0.263131         0.089366          0.630123   \n",
+       "01005       0.173040        0.401597         0.257016          0.576597   \n",
+       "01007       0.151724        0.318074         0.146243          0.643781   \n",
+       "01009       0.172013        0.300140         0.116018          0.731656   \n",
+       "...              ...             ...              ...               ...   \n",
+       "56037       0.094774        0.244424         0.044100          0.616271   \n",
+       "56039       0.118485        0.116231         0.014235          0.702453   \n",
+       "56041       0.106618        0.307708         0.083410          0.612454   \n",
+       "56043       0.195733        0.363713         0.081943          0.776961   \n",
+       "56045       0.180368        0.261284         0.072122          0.707261   \n",
+       "\n",
+       "       multi_unit_home  mobile_home  boat_van_rv_home  spanish_speaking  \n",
+       "GEOID                                                                    \n",
+       "01001         0.089284     0.180285          0.001453          0.022453  \n",
+       "01003         0.249631     0.119252          0.000995          0.044759  \n",
+       "01005         0.121674     0.299441          0.002288          0.050249  \n",
+       "01007         0.072113     0.284106          0.000000          0.014411  \n",
+       "01009         0.038784     0.229224          0.000335          0.057006  \n",
+       "...                ...          ...               ...               ...  \n",
+       "56037         0.158779     0.224322          0.000628          0.093154  \n",
+       "56039         0.260909     0.030319          0.006320          0.124490  \n",
+       "56041         0.133782     0.246122          0.007641          0.081690  \n",
+       "56043         0.103910     0.113356          0.005773          0.102321  \n",
+       "56045         0.053173     0.237850          0.001715          0.002177  \n",
+       "\n",
+       "[3142 rows x 65 columns]"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "out = out.merge(ACS_keep, how = 'left', left_index = True, right_index = True)\n",
+    "out"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "out['state_id'] = '#_' + out.index\n",
+    "out['state_id'] = out['state_id'].str[:4]\n",
+    "out['state_rank'] = out.groupby('state_id')['CombinedRiskScore'].rank(ascending=False)\n",
+    "out['county_id'] = '#_' + out.index\n",
+    "out['county_id'] = out['county_id'].str[:7]\n",
+    "out['county_rank'] = out.groupby('county_id')['CombinedRiskScore'].rank(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "tags": [
+     "remove_cell"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>state</th>\n",
+       "      <th>NFIRS_start</th>\n",
+       "      <th>NFIRS_end</th>\n",
+       "      <th>years_fires_reported</th>\n",
+       "      <th>total_fires_reported</th>\n",
+       "      <th>max_fires_1k</th>\n",
+       "      <th>median_fires_1k</th>\n",
+       "      <th>total_fires_reported_sev</th>\n",
+       "      <th>max_fires_1k_sev</th>\n",
+       "      <th>median_fires_1k_sev</th>\n",
+       "      <th>...</th>\n",
+       "      <th>snap_past_12_mo</th>\n",
+       "      <th>single_unit_home</th>\n",
+       "      <th>multi_unit_home</th>\n",
+       "      <th>mobile_home</th>\n",
+       "      <th>boat_van_rv_home</th>\n",
+       "      <th>spanish_speaking</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>state_rank</th>\n",
+       "      <th>county_id</th>\n",
+       "      <th>county_rank</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GEOID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>01001</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>168.0</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>0.164841</td>\n",
+       "      <td>0.109894</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.127977</td>\n",
+       "      <td>0.728978</td>\n",
+       "      <td>0.089284</td>\n",
+       "      <td>0.180285</td>\n",
+       "      <td>0.001453</td>\n",
+       "      <td>0.022453</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01003</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>758.0</td>\n",
+       "      <td>0.737388</td>\n",
+       "      <td>0.508544</td>\n",
+       "      <td>133.0</td>\n",
+       "      <td>0.122050</td>\n",
+       "      <td>0.091538</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.089366</td>\n",
+       "      <td>0.630123</td>\n",
+       "      <td>0.249631</td>\n",
+       "      <td>0.119252</td>\n",
+       "      <td>0.000995</td>\n",
+       "      <td>0.044759</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>#_01003</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>01005</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>0.761389</td>\n",
+       "      <td>0.211497</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0.338395</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.257016</td>\n",
+       "      <td>0.576597</td>\n",
+       "      <td>0.121674</td>\n",
+       "      <td>0.299441</td>\n",
+       "      <td>0.002288</td>\n",
+       "      <td>0.050249</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>#_01005</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202002</th>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3.777148</td>\n",
-       "      <td>0</td>\n",
+       "      <th>01007</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>0.388293</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.048537</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.012945</td>\n",
-       "      <td>0.303398</td>\n",
-       "      <td>0.094660</td>\n",
-       "      <td>0.280973</td>\n",
-       "      <td>0.172566</td>\n",
-       "      <td>0.821138</td>\n",
-       "      <td>0.168699</td>\n",
-       "      <td>0.010163</td>\n",
+       "      <td>0.146243</td>\n",
+       "      <td>0.643781</td>\n",
+       "      <td>0.072113</td>\n",
+       "      <td>0.284106</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.011062</td>\n",
+       "      <td>0.014411</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>#_01007</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010203001</th>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.846024</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.035956</td>\n",
-       "      <td>0.302876</td>\n",
-       "      <td>0.134095</td>\n",
-       "      <td>0.379854</td>\n",
-       "      <td>0.082524</td>\n",
-       "      <td>0.995112</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.004888</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.037621</td>\n",
+       "      <th>01009</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>0.928212</td>\n",
+       "      <td>0.367782</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.315242</td>\n",
+       "      <td>0.087567</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.116018</td>\n",
+       "      <td>0.731656</td>\n",
+       "      <td>0.038784</td>\n",
+       "      <td>0.229224</td>\n",
+       "      <td>0.000335</td>\n",
+       "      <td>0.057006</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>#_01009</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -4715,282 +4882,275 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511001</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.049417</td>\n",
-       "      <td>0.234043</td>\n",
-       "      <td>0.175704</td>\n",
-       "      <td>0.219941</td>\n",
-       "      <td>0.054252</td>\n",
-       "      <td>0.711035</td>\n",
-       "      <td>0.053470</td>\n",
-       "      <td>0.228669</td>\n",
-       "      <td>0.006826</td>\n",
-       "      <td>0.000000</td>\n",
+       "      <th>56037</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>115.0</td>\n",
+       "      <td>0.543404</td>\n",
+       "      <td>0.441516</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0.226419</td>\n",
+       "      <td>0.135851</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.044100</td>\n",
+       "      <td>0.616271</td>\n",
+       "      <td>0.158779</td>\n",
+       "      <td>0.224322</td>\n",
+       "      <td>0.000628</td>\n",
+       "      <td>0.093154</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>#_56037</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511002</th>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.004849</td>\n",
-       "      <td>0.208513</td>\n",
-       "      <td>0.215517</td>\n",
-       "      <td>0.276139</td>\n",
-       "      <td>0.010724</td>\n",
-       "      <td>0.706250</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.293750</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.009383</td>\n",
+       "      <th>56039</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>0.488368</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>0.177588</td>\n",
+       "      <td>0.133191</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014235</td>\n",
+       "      <td>0.702453</td>\n",
+       "      <td>0.260909</td>\n",
+       "      <td>0.030319</td>\n",
+       "      <td>0.006320</td>\n",
+       "      <td>0.124490</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>#_56039</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513001</th>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.737619</td>\n",
-       "      <td>3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.325804</td>\n",
-       "      <td>0.076455</td>\n",
-       "      <td>0.210325</td>\n",
-       "      <td>0.172084</td>\n",
-       "      <td>0.709910</td>\n",
-       "      <td>0.054054</td>\n",
-       "      <td>0.236036</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
+       "      <th>56041</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>0.677704</td>\n",
+       "      <td>0.314648</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.048407</td>\n",
+       "      <td>0.048407</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.083410</td>\n",
+       "      <td>0.612454</td>\n",
+       "      <td>0.133782</td>\n",
+       "      <td>0.246122</td>\n",
+       "      <td>0.007641</td>\n",
+       "      <td>0.081690</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>#_56041</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513002</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.017986</td>\n",
-       "      <td>0.256295</td>\n",
-       "      <td>0.341727</td>\n",
-       "      <td>0.394973</td>\n",
-       "      <td>0.075404</td>\n",
-       "      <td>0.720325</td>\n",
-       "      <td>0.160976</td>\n",
-       "      <td>0.118699</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
+       "      <th>56043</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0.611696</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.244678</td>\n",
+       "      <td>0.122339</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.081943</td>\n",
+       "      <td>0.776961</td>\n",
+       "      <td>0.103910</td>\n",
+       "      <td>0.113356</td>\n",
+       "      <td>0.005773</td>\n",
+       "      <td>0.102321</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>#_56043</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513003</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>6</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.380238</td>\n",
-       "      <td>0.120700</td>\n",
-       "      <td>0.234824</td>\n",
-       "      <td>0.075080</td>\n",
-       "      <td>0.688752</td>\n",
-       "      <td>0.015408</td>\n",
-       "      <td>0.295840</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
+       "      <th>56045</th>\n",
+       "      <td>WY</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>0.219974</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.072122</td>\n",
+       "      <td>0.707261</td>\n",
+       "      <td>0.053173</td>\n",
+       "      <td>0.237850</td>\n",
+       "      <td>0.001715</td>\n",
+       "      <td>0.002177</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>217739 rows × 61 columns</p>\n",
+       "<p>3142 rows × 53 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "              fires_per_1K_pop_2009  fires_per_1K_pop_2010  \\\n",
-       "GEOID                                                        \n",
-       "010010201001               1.342282               2.684564   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120                    NaN   \n",
-       "010010202002               2.832861               2.832861   \n",
-       "010010203001               0.846024               1.269036   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
-       "\n",
-       "              fires_per_1K_pop_2011  fires_per_1K_pop_2012  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002                    NaN               1.581028   \n",
-       "010010202001               3.141361                    NaN   \n",
-       "010010202002               2.832861               0.944287   \n",
-       "010010203001               0.846024               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810                    NaN   \n",
-       "560459513002               0.970874                    NaN   \n",
-       "560459513003               0.625391               0.625391   \n",
-       "\n",
-       "              fires_per_1K_pop_2013  fires_per_1K_pop_2014  \\\n",
-       "GEOID                                                        \n",
-       "010010201001                    NaN                    NaN   \n",
-       "010010201002               0.790514                    NaN   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               1.269036               0.423012   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN                    NaN   \n",
-       "560459511002                    NaN                    NaN   \n",
-       "560459513001               0.868810               0.868810   \n",
-       "560459513002                    NaN               0.970874   \n",
-       "560459513003                    NaN               0.625391   \n",
+       "      state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
+       "GEOID                                                       \n",
+       "01001    AL         2011       2017                     7   \n",
+       "01003    AL         2011       2017                     7   \n",
+       "01005    AL         2011       2017                     7   \n",
+       "01007    AL         2011       2017                     5   \n",
+       "01009    AL         2011       2017                     7   \n",
+       "...     ...          ...        ...                   ...   \n",
+       "56037    WY         2011       2017                     6   \n",
+       "56039    WY         2011       2017                     5   \n",
+       "56041    WY         2011       2017                     6   \n",
+       "56043    WY         2011       2017                     6   \n",
+       "56045    WY         2011       2017                     7   \n",
        "\n",
-       "              fires_per_1K_pop_2015  fires_per_1K_pop_2016  \\\n",
+       "       total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
        "GEOID                                                        \n",
-       "010010201001                    NaN               1.342282   \n",
-       "010010201002               1.581028               0.790514   \n",
-       "010010202001               1.047120               1.047120   \n",
-       "010010202002               0.944287                    NaN   \n",
-       "010010203001               0.423012               0.846024   \n",
-       "...                             ...                    ...   \n",
-       "560459511001                    NaN               1.372684   \n",
-       "560459511002               0.632111                    NaN   \n",
-       "560459513001                    NaN                    NaN   \n",
-       "560459513002                    NaN                    NaN   \n",
-       "560459513003                    NaN                    NaN   \n",
+       "01001                 168.0      0.567786         0.457892   \n",
+       "01003                 758.0      0.737388         0.508544   \n",
+       "01005                  53.0      0.761389         0.211497   \n",
+       "01007                  23.0      0.388293         0.194146   \n",
+       "01009                 208.0      0.928212         0.367782   \n",
+       "...                     ...           ...              ...   \n",
+       "56037                 115.0      0.543404         0.441516   \n",
+       "56039                  50.0      0.887942         0.488368   \n",
+       "56041                  42.0      0.677704         0.314648   \n",
+       "56043                  17.0      0.611696         0.367017   \n",
+       "56045                  13.0      0.439947         0.293298   \n",
        "\n",
-       "              fires_per_1K_pop_2017  recorded_home_visits  ...  race_pct_two+  \\\n",
-       "GEOID                                                      ...                  \n",
-       "010010201001               1.342282                     0  ...       0.000000   \n",
-       "010010201002                    NaN                     0  ...       0.054545   \n",
-       "010010202001                    NaN                     0  ...       0.018750   \n",
-       "010010202002               3.777148                     0  ...       0.012945   \n",
-       "010010203001                    NaN                     0  ...       0.035956   \n",
-       "...                             ...                   ...  ...            ...   \n",
-       "560459511001                    NaN                     0  ...       0.049417   \n",
-       "560459511002                    NaN                     0  ...       0.004849   \n",
-       "560459513001               1.737619                     3  ...       0.000000   \n",
-       "560459513002                    NaN                     3  ...       0.017986   \n",
-       "560459513003                    NaN                     6  ...       0.000000   \n",
+       "       total_fires_reported_sev  max_fires_1k_sev  median_fires_1k_sev  ...  \\\n",
+       "GEOID                                                                   ...   \n",
+       "01001                      38.0          0.164841             0.109894  ...   \n",
+       "01003                     133.0          0.122050             0.091538  ...   \n",
+       "01005                      15.0          0.338395             0.169198  ...   \n",
+       "01007                       5.0          0.097073             0.048537  ...   \n",
+       "01009                      51.0          0.315242             0.087567  ...   \n",
+       "...                         ...               ...                  ...  ...   \n",
+       "56037                      32.0          0.226419             0.135851  ...   \n",
+       "56039                      11.0          0.177588             0.133191  ...   \n",
+       "56041                       3.0          0.048407             0.048407  ...   \n",
+       "56043                       4.0          0.244678             0.122339  ...   \n",
+       "56045                       3.0          0.293298             0.219974  ...   \n",
        "\n",
-       "              age_pct_under25 age_pct_over65  disability_pct  snap_past_12_mo  \\\n",
-       "GEOID                                                                           \n",
-       "010010201001         0.363758       0.036242        0.239437         0.183099   \n",
-       "010010201002         0.348617       0.114625        0.278509         0.096491   \n",
-       "010010202001         0.372917       0.161458        0.458549         0.303109   \n",
-       "010010202002         0.303398       0.094660        0.280973         0.172566   \n",
-       "010010203001         0.302876       0.134095        0.379854         0.082524   \n",
-       "...                       ...            ...             ...              ...   \n",
-       "560459511001         0.234043       0.175704        0.219941         0.054252   \n",
-       "560459511002         0.208513       0.215517        0.276139         0.010724   \n",
-       "560459513001         0.325804       0.076455        0.210325         0.172084   \n",
-       "560459513002         0.256295       0.341727        0.394973         0.075404   \n",
-       "560459513003         0.380238       0.120700        0.234824         0.075080   \n",
+       "       snap_past_12_mo  single_unit_home  multi_unit_home  mobile_home  \\\n",
+       "GEOID                                                                    \n",
+       "01001         0.127977          0.728978         0.089284     0.180285   \n",
+       "01003         0.089366          0.630123         0.249631     0.119252   \n",
+       "01005         0.257016          0.576597         0.121674     0.299441   \n",
+       "01007         0.146243          0.643781         0.072113     0.284106   \n",
+       "01009         0.116018          0.731656         0.038784     0.229224   \n",
+       "...                ...               ...              ...          ...   \n",
+       "56037         0.044100          0.616271         0.158779     0.224322   \n",
+       "56039         0.014235          0.702453         0.260909     0.030319   \n",
+       "56041         0.083410          0.612454         0.133782     0.246122   \n",
+       "56043         0.081943          0.776961         0.103910     0.113356   \n",
+       "56045         0.072122          0.707261         0.053173     0.237850   \n",
        "\n",
-       "              single_unit_home  multi_unit_home  mobile_home  \\\n",
-       "GEOID                                                          \n",
-       "010010201001          0.820423         0.024648     0.154930   \n",
-       "010010201002          0.925054         0.000000     0.074946   \n",
-       "010010202001          0.768844         0.201005     0.030151   \n",
-       "010010202002          0.821138         0.168699     0.010163   \n",
-       "010010203001          0.995112         0.000000     0.004888   \n",
-       "...                        ...              ...          ...   \n",
-       "560459511001          0.711035         0.053470     0.228669   \n",
-       "560459511002          0.706250         0.000000     0.293750   \n",
-       "560459513001          0.709910         0.054054     0.236036   \n",
-       "560459513002          0.720325         0.160976     0.118699   \n",
-       "560459513003          0.688752         0.015408     0.295840   \n",
+       "       boat_van_rv_home  spanish_speaking state_id  state_rank  county_id  \\\n",
+       "GEOID                                                                       \n",
+       "01001          0.001453          0.022453     #_01        63.0    #_01001   \n",
+       "01003          0.000995          0.044759     #_01        66.0    #_01003   \n",
+       "01005          0.002288          0.050249     #_01        13.0    #_01005   \n",
+       "01007          0.000000          0.014411     #_01        37.0    #_01007   \n",
+       "01009          0.000335          0.057006     #_01        11.0    #_01009   \n",
+       "...                 ...               ...      ...         ...        ...   \n",
+       "56037          0.000628          0.093154     #_56        19.0    #_56037   \n",
+       "56039          0.006320          0.124490     #_56         8.0    #_56039   \n",
+       "56041          0.007641          0.081690     #_56        22.0    #_56041   \n",
+       "56043          0.005773          0.102321     #_56         5.0    #_56043   \n",
+       "56045          0.001715          0.002177     #_56         9.0    #_56045   \n",
        "\n",
-       "              boat_van_rv_home  spanish_speaking  \n",
-       "GEOID                                             \n",
-       "010010201001          0.000000          0.102113  \n",
-       "010010201002          0.000000          0.046053  \n",
-       "010010202001          0.000000          0.000000  \n",
-       "010010202002          0.000000          0.011062  \n",
-       "010010203001          0.000000          0.037621  \n",
-       "...                        ...               ...  \n",
-       "560459511001          0.006826          0.000000  \n",
-       "560459511002          0.000000          0.009383  \n",
-       "560459513001          0.000000          0.000000  \n",
-       "560459513002          0.000000          0.000000  \n",
-       "560459513003          0.000000          0.000000  \n",
+       "       county_rank  \n",
+       "GEOID               \n",
+       "01001          1.0  \n",
+       "01003          1.0  \n",
+       "01005          1.0  \n",
+       "01007          1.0  \n",
+       "01009          1.0  \n",
+       "...            ...  \n",
+       "56037          1.0  \n",
+       "56039          1.0  \n",
+       "56041          1.0  \n",
+       "56043          1.0  \n",
+       "56045          1.0  \n",
        "\n",
-       "[217739 rows x 61 columns]"
+       "[3142 rows x 53 columns]"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "out = out.merge(ACS_keep, how = 'left', left_index = True, right_index = True)\n",
-    "out"
+    "out_final = out[out_columns]\n",
+    "if level is not 'block_group':\n",
+    "    print('removing geography column')\n",
+    "    out_final = out_final.drop(columns=['geography'])\n",
+    "out_final"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 36,
    "metadata": {
     "tags": [
      "remove_cell"
     ]
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "removing geography column\n"
+     ]
+    }
+   ],
    "source": [
-    "out['state_id'] = out.index\n",
-    "out['state_id'] = out['state_id'].str[:2]\n",
-    "out['state_rank'] = out.groupby('state_id')['CombinedRiskScore'].rank(ascending=False)\n",
-    "out['county_id'] = out.index\n",
-    "out['county_id'] = out['county_id'].str[:5]\n",
-    "out['county_rank'] = out.groupby('county_id')['CombinedRiskScore'].rank(ascending=False)"
+    "if level is not 'block_group':\n",
+    "    print('removing geography column')\n",
+    "    out = out.drop(columns=['geography'])\n",
+    "a = out.describe()\n",
+    "a.to_csv(utils.DATA['model-outputs']/f\"summary-pop50-{level}-{date.today()}.csv\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 37,
    "metadata": {
     "tags": [
      "remove_cell"
     ]
    },
+   "outputs": [],
+   "source": [
+    "out_name = f\"CombinedModels-FileStructureColumns-pop50-{level}-{date.today()}.csv\"\n",
+    "out_final.index = '#_' + out_final.index\n",
+    "out_final.to_csv(utils.DATA['model-outputs'] / out_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -5062,124 +5222,124 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>010010201001</th>\n",
+       "      <th>#_01001</th>\n",
        "      <td>AL</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>2.684564</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>1.342282</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.183099</td>\n",
-       "      <td>0.820423</td>\n",
-       "      <td>0.024648</td>\n",
-       "      <td>0.154930</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.102113</td>\n",
-       "      <td>01</td>\n",
-       "      <td>2189.0</td>\n",
-       "      <td>01001</td>\n",
-       "      <td>17.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>168.0</td>\n",
+       "      <td>0.567786</td>\n",
+       "      <td>0.457892</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>0.164841</td>\n",
+       "      <td>0.109894</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.127977</td>\n",
+       "      <td>0.728978</td>\n",
+       "      <td>0.089284</td>\n",
+       "      <td>0.180285</td>\n",
+       "      <td>0.001453</td>\n",
+       "      <td>0.022453</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>#_01001</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010201002</th>\n",
+       "      <th>#_01003</th>\n",
        "      <td>AL</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>1.185771</td>\n",
-       "      <td>1.581028</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>0.790514</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.096491</td>\n",
-       "      <td>0.925054</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.074946</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.046053</td>\n",
-       "      <td>01</td>\n",
-       "      <td>3155.0</td>\n",
-       "      <td>01001</td>\n",
-       "      <td>27.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>758.0</td>\n",
+       "      <td>0.737388</td>\n",
+       "      <td>0.508544</td>\n",
+       "      <td>133.0</td>\n",
+       "      <td>0.122050</td>\n",
+       "      <td>0.091538</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.089366</td>\n",
+       "      <td>0.630123</td>\n",
+       "      <td>0.249631</td>\n",
+       "      <td>0.119252</td>\n",
+       "      <td>0.000995</td>\n",
+       "      <td>0.044759</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>#_01003</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202001</th>\n",
+       "      <th>#_01005</th>\n",
        "      <td>AL</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>3.141361</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>2.094241</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>1.047120</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.303109</td>\n",
-       "      <td>0.768844</td>\n",
-       "      <td>0.201005</td>\n",
-       "      <td>0.030151</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>01</td>\n",
-       "      <td>633.0</td>\n",
-       "      <td>01001</td>\n",
-       "      <td>2.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>0.761389</td>\n",
+       "      <td>0.211497</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0.338395</td>\n",
+       "      <td>0.169198</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.257016</td>\n",
+       "      <td>0.576597</td>\n",
+       "      <td>0.121674</td>\n",
+       "      <td>0.299441</td>\n",
+       "      <td>0.002288</td>\n",
+       "      <td>0.050249</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>#_01005</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010202002</th>\n",
+       "      <th>#_01007</th>\n",
        "      <td>AL</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>0.388293</td>\n",
+       "      <td>0.194146</td>\n",
        "      <td>5.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>3.777148</td>\n",
-       "      <td>0.944287</td>\n",
-       "      <td>2.832861</td>\n",
-       "      <td>1.888574</td>\n",
-       "      <td>1.416431</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.172566</td>\n",
-       "      <td>0.821138</td>\n",
-       "      <td>0.168699</td>\n",
-       "      <td>0.010163</td>\n",
+       "      <td>0.097073</td>\n",
+       "      <td>0.048537</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.146243</td>\n",
+       "      <td>0.643781</td>\n",
+       "      <td>0.072113</td>\n",
+       "      <td>0.284106</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.011062</td>\n",
-       "      <td>01</td>\n",
-       "      <td>1948.0</td>\n",
-       "      <td>01001</td>\n",
-       "      <td>11.0</td>\n",
+       "      <td>0.014411</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>#_01007</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>010010203001</th>\n",
+       "      <th>#_01009</th>\n",
        "      <td>AL</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>1.269036</td>\n",
-       "      <td>0.634518</td>\n",
-       "      <td>2.115059</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>0.423012</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.082524</td>\n",
-       "      <td>0.995112</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.004888</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.037621</td>\n",
-       "      <td>01</td>\n",
-       "      <td>2972.0</td>\n",
-       "      <td>01001</td>\n",
-       "      <td>24.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>0.928212</td>\n",
+       "      <td>0.367782</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.315242</td>\n",
+       "      <td>0.087567</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.116018</td>\n",
+       "      <td>0.731656</td>\n",
+       "      <td>0.038784</td>\n",
+       "      <td>0.229224</td>\n",
+       "      <td>0.000335</td>\n",
+       "      <td>0.057006</td>\n",
+       "      <td>#_01</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>#_01009</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -5206,256 +5366,226 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511001</th>\n",
+       "      <th>#_56037</th>\n",
        "      <td>WY</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
+       "      <td>6</td>\n",
+       "      <td>115.0</td>\n",
+       "      <td>0.543404</td>\n",
+       "      <td>0.441516</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0.226419</td>\n",
+       "      <td>0.135851</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.044100</td>\n",
+       "      <td>0.616271</td>\n",
+       "      <td>0.158779</td>\n",
+       "      <td>0.224322</td>\n",
+       "      <td>0.000628</td>\n",
+       "      <td>0.093154</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>#_56037</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>1.372684</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.054252</td>\n",
-       "      <td>0.711035</td>\n",
-       "      <td>0.053470</td>\n",
-       "      <td>0.228669</td>\n",
-       "      <td>0.006826</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>56</td>\n",
-       "      <td>167.0</td>\n",
-       "      <td>56045</td>\n",
-       "      <td>3.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459511002</th>\n",
+       "      <th>#_56039</th>\n",
        "      <td>WY</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
+       "      <td>5</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>0.887942</td>\n",
+       "      <td>0.488368</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>0.177588</td>\n",
+       "      <td>0.133191</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014235</td>\n",
+       "      <td>0.702453</td>\n",
+       "      <td>0.260909</td>\n",
+       "      <td>0.030319</td>\n",
+       "      <td>0.006320</td>\n",
+       "      <td>0.124490</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>#_56039</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>0.632111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.010724</td>\n",
-       "      <td>0.706250</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.293750</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.009383</td>\n",
-       "      <td>56</td>\n",
-       "      <td>194.0</td>\n",
-       "      <td>56045</td>\n",
-       "      <td>4.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513001</th>\n",
+       "      <th>#_56041</th>\n",
        "      <td>WY</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.737619</td>\n",
-       "      <td>0.868810</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.172084</td>\n",
-       "      <td>0.709910</td>\n",
-       "      <td>0.054054</td>\n",
-       "      <td>0.236036</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>56</td>\n",
-       "      <td>114.0</td>\n",
-       "      <td>56045</td>\n",
-       "      <td>2.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>0.677704</td>\n",
+       "      <td>0.314648</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.048407</td>\n",
+       "      <td>0.048407</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.083410</td>\n",
+       "      <td>0.612454</td>\n",
+       "      <td>0.133782</td>\n",
+       "      <td>0.246122</td>\n",
+       "      <td>0.007641</td>\n",
+       "      <td>0.081690</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>#_56041</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513002</th>\n",
+       "      <th>#_56043</th>\n",
        "      <td>WY</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>0.970874</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.075404</td>\n",
-       "      <td>0.720325</td>\n",
-       "      <td>0.160976</td>\n",
-       "      <td>0.118699</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>56</td>\n",
-       "      <td>68.0</td>\n",
-       "      <td>56045</td>\n",
+       "      <td>6</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0.611696</td>\n",
+       "      <td>0.367017</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.244678</td>\n",
+       "      <td>0.122339</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.081943</td>\n",
+       "      <td>0.776961</td>\n",
+       "      <td>0.103910</td>\n",
+       "      <td>0.113356</td>\n",
+       "      <td>0.005773</td>\n",
+       "      <td>0.102321</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>#_56043</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>560459513003</th>\n",
+       "      <th>#_56045</th>\n",
        "      <td>WY</td>\n",
        "      <td>2011</td>\n",
        "      <td>2017</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>0.439947</td>\n",
+       "      <td>0.293298</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>0.625391</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.075080</td>\n",
-       "      <td>0.688752</td>\n",
-       "      <td>0.015408</td>\n",
-       "      <td>0.295840</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>56</td>\n",
-       "      <td>288.0</td>\n",
-       "      <td>56045</td>\n",
-       "      <td>5.0</td>\n",
+       "      <td>0.293298</td>\n",
+       "      <td>0.219974</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.072122</td>\n",
+       "      <td>0.707261</td>\n",
+       "      <td>0.053173</td>\n",
+       "      <td>0.237850</td>\n",
+       "      <td>0.001715</td>\n",
+       "      <td>0.002177</td>\n",
+       "      <td>#_56</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>#_56045</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>217739 rows × 52 columns</p>\n",
+       "<p>3142 rows × 53 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "             state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
-       "GEOID                                                              \n",
-       "010010201001    AL         2011       2017                   2.0   \n",
-       "010010201002    AL         2011       2017                   4.0   \n",
-       "010010202001    AL         2011       2017                   5.0   \n",
-       "010010202002    AL         2011       2017                   5.0   \n",
-       "010010203001    AL         2011       2017                   6.0   \n",
-       "...            ...          ...        ...                   ...   \n",
-       "560459511001    WY         2011       2017                   1.0   \n",
-       "560459511002    WY         2011       2017                   1.0   \n",
-       "560459513001    WY         2011       2017                   4.0   \n",
-       "560459513002    WY         2011       2017                   2.0   \n",
-       "560459513003    WY         2011       2017                   3.0   \n",
+       "        state  NFIRS_start  NFIRS_end  years_fires_reported  \\\n",
+       "GEOID                                                         \n",
+       "#_01001    AL         2011       2017                     7   \n",
+       "#_01003    AL         2011       2017                     7   \n",
+       "#_01005    AL         2011       2017                     7   \n",
+       "#_01007    AL         2011       2017                     5   \n",
+       "#_01009    AL         2011       2017                     7   \n",
+       "...       ...          ...        ...                   ...   \n",
+       "#_56037    WY         2011       2017                     6   \n",
+       "#_56039    WY         2011       2017                     5   \n",
+       "#_56041    WY         2011       2017                     6   \n",
+       "#_56043    WY         2011       2017                     6   \n",
+       "#_56045    WY         2011       2017                     7   \n",
        "\n",
-       "              total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
-       "GEOID                                                               \n",
-       "010010201001                   2.0      1.342282         1.342282   \n",
-       "010010201002                   6.0      1.581028         1.185771   \n",
-       "010010202001                   7.0      3.141361         1.047120   \n",
-       "010010202002                  10.0      3.777148         0.944287   \n",
-       "010010203001                  10.0      1.269036         0.634518   \n",
-       "...                            ...           ...              ...   \n",
-       "560459511001                   2.0      1.372684         1.372684   \n",
-       "560459511002                   1.0      0.632111         0.632111   \n",
-       "560459513001                   5.0      1.737619         0.868810   \n",
-       "560459513002                   2.0      0.970874         0.970874   \n",
-       "560459513003                   3.0      0.625391         0.625391   \n",
+       "         total_fires_reported  max_fires_1k  median_fires_1k  \\\n",
+       "GEOID                                                          \n",
+       "#_01001                 168.0      0.567786         0.457892   \n",
+       "#_01003                 758.0      0.737388         0.508544   \n",
+       "#_01005                  53.0      0.761389         0.211497   \n",
+       "#_01007                  23.0      0.388293         0.194146   \n",
+       "#_01009                 208.0      0.928212         0.367782   \n",
+       "...                       ...           ...              ...   \n",
+       "#_56037                 115.0      0.543404         0.441516   \n",
+       "#_56039                  50.0      0.887942         0.488368   \n",
+       "#_56041                  42.0      0.677704         0.314648   \n",
+       "#_56043                  17.0      0.611696         0.367017   \n",
+       "#_56045                  13.0      0.439947         0.293298   \n",
        "\n",
-       "              total_fires_reported_sev  max_fires_1k_sev  median_fires_1k_sev  \\\n",
-       "GEOID                                                                           \n",
-       "010010201001                  2.684564          1.342282             1.342282   \n",
-       "010010201002                  1.581028          0.790514             0.790514   \n",
-       "010010202001                  2.094241          1.047120             1.047120   \n",
-       "010010202002                  2.832861          1.888574             1.416431   \n",
-       "010010203001                  2.115059          0.423012             0.423012   \n",
-       "...                                ...               ...                  ...   \n",
-       "560459511001                  1.372684          1.372684             1.372684   \n",
-       "560459511002                  0.000000               NaN                  NaN   \n",
-       "560459513001                  0.000000               NaN                  NaN   \n",
-       "560459513002                  0.000000               NaN                  NaN   \n",
-       "560459513003                  0.625391          0.625391             0.625391   \n",
+       "         total_fires_reported_sev  max_fires_1k_sev  median_fires_1k_sev  ...  \\\n",
+       "GEOID                                                                     ...   \n",
+       "#_01001                      38.0          0.164841             0.109894  ...   \n",
+       "#_01003                     133.0          0.122050             0.091538  ...   \n",
+       "#_01005                      15.0          0.338395             0.169198  ...   \n",
+       "#_01007                       5.0          0.097073             0.048537  ...   \n",
+       "#_01009                      51.0          0.315242             0.087567  ...   \n",
+       "...                           ...               ...                  ...  ...   \n",
+       "#_56037                      32.0          0.226419             0.135851  ...   \n",
+       "#_56039                      11.0          0.177588             0.133191  ...   \n",
+       "#_56041                       3.0          0.048407             0.048407  ...   \n",
+       "#_56043                       4.0          0.244678             0.122339  ...   \n",
+       "#_56045                       3.0          0.293298             0.219974  ...   \n",
        "\n",
-       "              ...  snap_past_12_mo  single_unit_home  multi_unit_home  \\\n",
-       "GEOID         ...                                                       \n",
-       "010010201001  ...         0.183099          0.820423         0.024648   \n",
-       "010010201002  ...         0.096491          0.925054         0.000000   \n",
-       "010010202001  ...         0.303109          0.768844         0.201005   \n",
-       "010010202002  ...         0.172566          0.821138         0.168699   \n",
-       "010010203001  ...         0.082524          0.995112         0.000000   \n",
-       "...           ...              ...               ...              ...   \n",
-       "560459511001  ...         0.054252          0.711035         0.053470   \n",
-       "560459511002  ...         0.010724          0.706250         0.000000   \n",
-       "560459513001  ...         0.172084          0.709910         0.054054   \n",
-       "560459513002  ...         0.075404          0.720325         0.160976   \n",
-       "560459513003  ...         0.075080          0.688752         0.015408   \n",
+       "         snap_past_12_mo  single_unit_home  multi_unit_home  mobile_home  \\\n",
+       "GEOID                                                                      \n",
+       "#_01001         0.127977          0.728978         0.089284     0.180285   \n",
+       "#_01003         0.089366          0.630123         0.249631     0.119252   \n",
+       "#_01005         0.257016          0.576597         0.121674     0.299441   \n",
+       "#_01007         0.146243          0.643781         0.072113     0.284106   \n",
+       "#_01009         0.116018          0.731656         0.038784     0.229224   \n",
+       "...                  ...               ...              ...          ...   \n",
+       "#_56037         0.044100          0.616271         0.158779     0.224322   \n",
+       "#_56039         0.014235          0.702453         0.260909     0.030319   \n",
+       "#_56041         0.083410          0.612454         0.133782     0.246122   \n",
+       "#_56043         0.081943          0.776961         0.103910     0.113356   \n",
+       "#_56045         0.072122          0.707261         0.053173     0.237850   \n",
        "\n",
-       "              mobile_home  boat_van_rv_home spanish_speaking  state_id  \\\n",
-       "GEOID                                                                    \n",
-       "010010201001     0.154930          0.000000         0.102113        01   \n",
-       "010010201002     0.074946          0.000000         0.046053        01   \n",
-       "010010202001     0.030151          0.000000         0.000000        01   \n",
-       "010010202002     0.010163          0.000000         0.011062        01   \n",
-       "010010203001     0.004888          0.000000         0.037621        01   \n",
-       "...                   ...               ...              ...       ...   \n",
-       "560459511001     0.228669          0.006826         0.000000        56   \n",
-       "560459511002     0.293750          0.000000         0.009383        56   \n",
-       "560459513001     0.236036          0.000000         0.000000        56   \n",
-       "560459513002     0.118699          0.000000         0.000000        56   \n",
-       "560459513003     0.295840          0.000000         0.000000        56   \n",
+       "         boat_van_rv_home  spanish_speaking state_id  state_rank  county_id  \\\n",
+       "GEOID                                                                         \n",
+       "#_01001          0.001453          0.022453     #_01        63.0    #_01001   \n",
+       "#_01003          0.000995          0.044759     #_01        66.0    #_01003   \n",
+       "#_01005          0.002288          0.050249     #_01        13.0    #_01005   \n",
+       "#_01007          0.000000          0.014411     #_01        37.0    #_01007   \n",
+       "#_01009          0.000335          0.057006     #_01        11.0    #_01009   \n",
+       "...                   ...               ...      ...         ...        ...   \n",
+       "#_56037          0.000628          0.093154     #_56        19.0    #_56037   \n",
+       "#_56039          0.006320          0.124490     #_56         8.0    #_56039   \n",
+       "#_56041          0.007641          0.081690     #_56        22.0    #_56041   \n",
+       "#_56043          0.005773          0.102321     #_56         5.0    #_56043   \n",
+       "#_56045          0.001715          0.002177     #_56         9.0    #_56045   \n",
        "\n",
-       "              state_rank  county_id  county_rank  \n",
-       "GEOID                                             \n",
-       "010010201001      2189.0      01001         17.0  \n",
-       "010010201002      3155.0      01001         27.0  \n",
-       "010010202001       633.0      01001          2.0  \n",
-       "010010202002      1948.0      01001         11.0  \n",
-       "010010203001      2972.0      01001         24.0  \n",
-       "...                  ...        ...          ...  \n",
-       "560459511001       167.0      56045          3.0  \n",
-       "560459511002       194.0      56045          4.0  \n",
-       "560459513001       114.0      56045          2.0  \n",
-       "560459513002        68.0      56045          1.0  \n",
-       "560459513003       288.0      56045          5.0  \n",
+       "         county_rank  \n",
+       "GEOID                 \n",
+       "#_01001          1.0  \n",
+       "#_01003          1.0  \n",
+       "#_01005          1.0  \n",
+       "#_01007          1.0  \n",
+       "#_01009          1.0  \n",
+       "...              ...  \n",
+       "#_56037          1.0  \n",
+       "#_56039          1.0  \n",
+       "#_56041          1.0  \n",
+       "#_56043          1.0  \n",
+       "#_56045          1.0  \n",
        "\n",
-       "[217739 rows x 52 columns]"
+       "[3142 rows x 53 columns]"
       ]
      },
-     "execution_count": 41,
+     "execution_count": 38,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "out_final = out[out_columns]\n",
     "out_final"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "a = out.describe()\n",
-    "a.to_csv(utils.DATA['model-outputs']/f\"summary-pop0-{date.today()}.csv\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "tags": [
-     "remove_cell"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "out_name = f\"CombinedModels-FileStructureColumns-pop0-{date.today()}.csv\"\n",
-    "out_final.index = '#_' + out_final.index\n",
-    "out_final.to_csv(utils.DATA['model-outputs'] / out_name)"
-   ]
   }
  ],
  "metadata": {