LoadData.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The rpy2.ipython extension is already loaded. To reload it, use:\n",
      "  %reload_ext rpy2.ipython\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import socket\n",
    "from datetime import datetime\n",
    "import matplotlib as mpl\n",
    "import pandas as pd\n",
    "import imdb\n",
    "from tqdm import tqdm_notebook as tqdm\n",
    "import rpy2\n",
    "%load_ext rpy2.ipython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine data from imdb\n",
    "info_df = pd.read_csv('data/title.basics.tsv', sep='\\t', na_values='\\\\N')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings_df = pd.read_csv('data/title.ratings.tsv', sep='\\t', na_values='\\\\N')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_df = info_df.merge(ratings_df, on='tconst')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>tconst</th>\n",
       "      <th>titleType</th>\n",
       "      <th>primaryTitle</th>\n",
       "      <th>originalTitle</th>\n",
       "      <th>startYear</th>\n",
       "      <th>runtimeMinutes</th>\n",
       "      <th>genres</th>\n",
       "      <th>averageRating</th>\n",
       "      <th>numVotes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>tt0000009</td>\n",
       "      <td>movie</td>\n",
       "      <td>Miss Jerry</td>\n",
       "      <td>Miss Jerry</td>\n",
       "      <td>1894.0</td>\n",
       "      <td>45</td>\n",
       "      <td>Romance</td>\n",
       "      <td>5.4</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140073</th>\n",
       "      <td>tt0230366</td>\n",
       "      <td>movie</td>\n",
       "      <td>Jeffries-Sharkey Contest</td>\n",
       "      <td>Jeffries-Sharkey Contest</td>\n",
       "      <td>1899.0</td>\n",
       "      <td>135</td>\n",
       "      <td>Documentary,News,Sport</td>\n",
       "      <td>3.9</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167863</th>\n",
       "      <td>tt0291338</td>\n",
       "      <td>movie</td>\n",
       "      <td>May Day Parade</td>\n",
       "      <td>May Day Parade</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>66</td>\n",
       "      <td>News</td>\n",
       "      <td>7.1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116517</th>\n",
       "      <td>tt0178983</td>\n",
       "      <td>movie</td>\n",
       "      <td>Westinghouse Works</td>\n",
       "      <td>Westinghouse Works</td>\n",
       "      <td>1904.0</td>\n",
       "      <td>68</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>5.3</td>\n",
       "      <td>263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>tt0000574</td>\n",
       "      <td>movie</td>\n",
       "      <td>The Story of the Kelly Gang</td>\n",
       "      <td>The Story of the Kelly Gang</td>\n",
       "      <td>1906.0</td>\n",
       "      <td>70</td>\n",
       "      <td>Biography,Crime,Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           tconst titleType                 primaryTitle  \\\n",
       "8       tt0000009     movie                   Miss Jerry   \n",
       "140073  tt0230366     movie     Jeffries-Sharkey Contest   \n",
       "167863  tt0291338     movie               May Day Parade   \n",
       "116517  tt0178983     movie           Westinghouse Works   \n",
       "357     tt0000574     movie  The Story of the Kelly Gang   \n",
       "\n",
       "                      originalTitle  startYear runtimeMinutes  \\\n",
       "8                        Miss Jerry     1894.0             45   \n",
       "140073     Jeffries-Sharkey Contest     1899.0            135   \n",
       "167863               May Day Parade     1900.0             66   \n",
       "116517           Westinghouse Works     1904.0             68   \n",
       "357     The Story of the Kelly Gang     1906.0             70   \n",
       "\n",
       "                        genres  averageRating  numVotes  \n",
       "8                      Romance            5.4        81  \n",
       "140073  Documentary,News,Sport            3.9        33  \n",
       "167863                    News            7.1         7  \n",
       "116517             Documentary            5.3       263  \n",
       "357      Biography,Crime,Drama            6.1       537  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select our films for the game\n",
    "clean_df = all_df[all_df['titleType'] == 'movie'] # Movies only\n",
    "clean_df = clean_df[clean_df['isAdult'] == 0] # No porn\n",
    "clean_df = clean_df.drop(['endYear', 'isAdult'], axis=1) #Drop unused columns\n",
    "clean_df.dropna(subset=list(set(clean_df.columns) - set(['genres'])), \n",
    "                inplace=True) # Has a release year\n",
    "clean_df = clean_df[pd.to_numeric(clean_df['runtimeMinutes'])>39] # Feature length = 40 mins\n",
    "clean_df.sort_values(by='startYear', inplace=True)\n",
    "clean_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "this_year = datetime.today().year+3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "yrs = [0] + \\\n",
    "    [x for x in list(range(1950,2000)) if x % 10 == 0] + \\\n",
    "    [x for x in list(range(2001,this_year))  if x % 2 == 0] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "for idx, yr in enumerate(yrs):\n",
    "    if idx == len(yrs)-1:\n",
    "        break\n",
    "    dec_df = clean_df[(clean_df['startYear'] >= yr) & (clean_df['startYear'] < yrs[idx+1])]\n",
    "    dec_df.to_csv(path_or_buf='data/packets/movies_'+str(yr)+'s.tsv', sep='\\t')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "votes_90percentile = clean_movie_df[['startYear','numVotes']].groupby('startYear').\\\n",
    "    quantile(0.90).reset_index().rename(columns={'numVotes':'percentile90'})\n",
    "votes_925percentile = clean_movie_df[['startYear','numVotes']].groupby('startYear').\\\n",
    "    quantile(0.925).reset_index().rename(columns={'numVotes':'percentile925'})\n",
    "votes_95percentile = clean_movie_df[['startYear','numVotes']].groupby('startYear').\\\n",
    "    quantile(0.95).reset_index().rename(columns={'numVotes':'percentile95'})\n",
    "votes_df = votes_90percentile.merge(votes_925percentile, on='startYear').\\\n",
    "    merge(votes_95percentile, on='startYear')\n",
    "long_df = votes_df.melt(id_vars='startYear')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAJYCAYAAACadoJwAAAEGWlDQ1BrQ0dDb2xvclNwYWNlR2VuZXJpY1JHQgAAOI2NVV1oHFUUPrtzZyMkzlNsNIV0qD8NJQ2TVjShtLp/3d02bpZJNtoi6GT27s6Yyc44M7v9oU9FUHwx6psUxL+3gCAo9Q/bPrQvlQol2tQgKD60+INQ6Ium65k7M5lpurHeZe58853vnnvuuWfvBei5qliWkRQBFpquLRcy4nOHj4g9K5CEh6AXBqFXUR0rXalMAjZPC3e1W99Dwntf2dXd/p+tt0YdFSBxH2Kz5qgLiI8B8KdVy3YBevqRHz/qWh72Yui3MUDEL3q44WPXw3M+fo1pZuQs4tOIBVVTaoiXEI/MxfhGDPsxsNZfoE1q66ro5aJim3XdoLFw72H+n23BaIXzbcOnz5mfPoTvYVz7KzUl5+FRxEuqkp9G/Ajia219thzg25abkRE/BpDc3pqvphHvRFys2weqvp+krbWKIX7nhDbzLOItiM8358pTwdirqpPFnMF2xLc1WvLyOwTAibpbmvHHcvttU57y5+XqNZrLe3lE/Pq8eUj2fXKfOe3pfOjzhJYtB/yll5SDFcSDiH+hRkH25+L+sdxKEAMZahrlSX8ukqMOWy/jXW2m6M9LDBc31B9LFuv6gVKg/0Szi3KAr1kGq1GMjU/aLbnq6/lRxc4XfJ98hTargX++DbMJBSiYMIe9Ck1YAxFkKEAG3xbYaKmDDgYyFK0UGYpfoWYXG+fAPPI6tJnNwb7ClP7IyF+D+bjOtCpkhz6CFrIa/I6sFtNl8auFXGMTP34sNwI/JhkgEtmDz14ySfaRcTIBInmKPE32kxyyE2Tv+thKbEVePDfW/byMM1Kmm0XdObS7oGD/MypMXFPXrCwOtoYjyyn7BV29/MZfsVzpLDdRtuIZnbpXzvlf+ev8MvYr/Gqk4H/kV/G3csdazLuyTMPsbFhzd1UabQbjFvDRmcWJxR3zcfHkVw9GfpbJmeev9F08WW8uDkaslwX6avlWGU6NRKz0g/SHtCy9J30o/ca9zX3Kfc19zn3BXQKRO8ud477hLnAfc1/G9mrzGlrfexZ5GLdn6ZZrrEohI2wVHhZywjbhUWEy8icMCGNCUdiBlq3r+xafL549HQ5jH+an+1y+LlYBifuxAvRN/lVVVOlwlCkdVm9NOL5BE4wkQ2SMlDZU97hX86EilU/lUmkQUztTE6mx1EEPh7OmdqBtAvv8HdWpbrJS6tJj3n0CWdM6busNzRV3S9KTYhqvNiqWmuroiKgYhshMjmhTh9ptWhsF7970j/SbMrsPE1suR5z7DMC+P/Hs+y7ijrQAlhyAgccjbhjPygfeBTjzhNqy28EdkUh8C+DU9+z2v/oyeH791OncxHOs5y2AtTc7nb/f73TWPkD/qwBnjX8BoJ98VQNcC+8AAEAASURBVHgB7J0HeJRV1sdPekIavVfpRWmKNEEUAUFUUBeBtSPuZ1nUVURB17VhBRFFRV1c+7KKogjSBAQUEFF6b9JLGun9e/833MnMZCaZmkz5n+eZvO3W30xm3vPeU0KKDREKCZAACZAACZAACZAACZAACVQCgdBK6INdkAAJkAAJkAAJkAAJkAAJkIAiQAWEHwQSIAESIAESIAESIAESIIFKI0AFpNJQsyMSIAESIAESIAESIAESIAEqIPwMkAAJkAAJkAAJkAAJkAAJVBoBKiCVhpodkQAJkAAJkAAJkAAJkAAJUAHhZ4AESIAESIAESIAESIAESKDSCFABqTTU7IgESIAESIAESIAESIAESIAKCD8DJEACJEACJEACJEACJEAClUaACkiloWZHJEACJEACJEACJEACJEACVED4GSABEiABEiABEiABEiABEqg0AlRAKg01OyIBEiABEiABEiABEiABEqACws8ACZAACZAACZAACZAACZBApRGgAlJpqNkRCZAACZAACZAACZAACZAAFRB+BkiABEiABEiABEiABEiABCqNQHil9cSO/IbA2bNnXR5reHi4REdHq/r5+fmSm5vrcluVUTEqKkrCwsIkKyurMrpzuY+IiAjBWCF5eXnq5XJjlVARn4GQkBDJzs6uhN5c7yIyMlLwguCzis+sr4v+LGRkZPj6UNX4YmJi1P8YDjIzM6W4uNhnx43PbGxsrOTk5EhBQYHPjhMDq1atmoSGljxDdOezgDZq1qzp03Pl4EiABAKPABWQwHtP3Z6ROzdhuJnXCkhRUZHP39DhZgNKkztzdhu4Aw3gplNzxY2Rr483Pj5ezcrXxwmlTnOFYufr4wVU/VlITU316Zt5/bFOTExUY8bxuXPnpLCwUF/yua3+/oIC4uufBf3wBBDd+SxoJcbn3gwOiARIIKAJ0AQroN9eTo4ESIAESIAESIAESIAEfIsAFRDfej84GhIgARIgARIgARIgARIIaAJUQAL67eXkSIAESIAESIAESIAESMC3CFAB8a33g6MhARIgARIgARIgARIggYAmQAUkoN9eTo4ESIAESIAESIAESIAEfIsAFRDfej84GhIgARIgARIgARIgARIIaAJUQAL67eXkSIAESIAESIAESIAESMC3CFAB8a33g6MhARIgARIgARIgARIggYAmQAUkoN9eTo4ESIAESIAESIAESIAEfIsAFRDfej84GhIgARIgARIgARIgARIIaAJUQAL67eXkSIAESIAESIAESIAESMC3CFAB8a33g6MhARIgARIgARIgARIggYAmQAUkoN9eTo4ESIAESIAESIAESIAEfIsAFRDfej84GhIgARIgARIgARIgARIIaALhAT07To4ESIAESIAErAgUFYvsOxkp+05FSmZuqMTHFErr+nnSpkGRVUkekgAJkAAJeIMAFRBvUGWbJEACJEACPkng0JkI+WRtohxPjSgzvua18+XB60USy14qU5YnSIAESIAEXCdAEyzX2bEmCZAACZCAHxHYdTxSpi2qZVP5wDQOnY2QSf8ROXg6zI9mxaGSAAmQgP8RoALif+8ZR0wCJEACJOAkgazcEHl/VQ0pKAopt2ZOvsibi2Mlv6DcYrxIAiRAAiTgBgEqIG7AY1USIAESIAH/ILByZ6xkGf4ejkhyRqj8sq+aI0VZhgRIgARIwAUCjn0bu9Awq5AACZAACZCArxDYeiTKqaFscbK8U42zMAmQAAkEOQEqIEH+AeD0SYAESCAYCCRlOOfXkZTBGC3B8LngHEmABKqGABWQquHOXkmABEiABCqRQIRz+odEhBmxeikkQAIkQAJeIUAFxCtY2SgJkAAJkIAvEWhU0/Aud0Ia1XCuvBNNsygJkAAJBD0BKiBB/xEgABIgARIIfAI9WmY7NclLnSzvVOMsTAIkQAJBToAKSJB/ADh9EiABEggGAt2b50irerkVTLXE7Kpr8zxp1zCvgrK8TAIkQAIk4CoBKiCukmM9EiABEiABvyEQYqT/uHtAqjStVZ5pVYh0bGKUuzLLb+bFgZIACZCAPxKgAuKP7xrHTAIkQAIk4DSB+Ogi+cfVZ2V413RJjCm0qF8ztkBuujRdnh4tEhNpcYkHJEACJEACHibAOIMeBsrmSIAESIAEfJdAhPGrd3XnDBlyUYacTQ+TTCM5IRSTWvGFEhYWJuFh8b47eI6MBEiABAKEABWQAHkjOQ0SIAESIAHHCcAkq05CodQRy5UQx1tgSRIgARIgAVcJUAFxlRzrkQAJkAAJ+B2B1MxQSckKk+iIYqmbUCBhNET2u/eQAyYBEvB/AlRA/P895AxIgARIgAQqILB+f4ws2RorJ1IjTCVjIork0lbZMrRzusRFM/GgCQx3SIAESMDLBKiAeBkwmycBEiABEqg6AkVFIh+uri4bD8aUGUR2fois3BkrW/6MkvuvSpZGtcoU4QkSIAESIAEvEODisxegskkSIAESIAHfIDB/U/x55cPWCofhCGJIcma4vLWspuTklRz7xsg5ChIgARIIXAJUQAL3veXMSIAESCCoCSDK1fLtsQYDKB/lKxdJGeGybHvZVZKgBsjJkwAJkICXCFAB8RJYNksCJEACJFC1BDYejJaiYige5SsfepTr9kbrXW5JgARIgAS8SIAKiBfhsmkSIAESIIGqI3AsudTh3JFRnEkPl9zyEqU70gjLkAAJkAAJVEiACkiFiFiABEiABEjAHwnkFzq28mE+t/wC8yPukwAJkAAJeIMAFRBvUGWbJEACJEACVU4A2c0dl2IjN0iRxNENxHFkLEkCJEACLhKgAuIiOFYjARIgARLwbQIXNck5P0BbEbCsxx4inZvmWZ/kMQmQAAmQgBcIUAHxAlQ2SQIkQAIkUPUE2jbIk1b1co2BVGSKVSyhIcVydZfMqh80R0ACJEACQUCACkgQvMmcIgmQAAkEK4E7+qVK9WraFMv+SsiY3mnSoLouF6y0OG8SIAESqBwCVEAqhzN7IQESIAESqAICNWKL5LFrzkqnxjDHKrsSUiO2UP7vyhTp3Tq7CkbHLkmABEggOAmEB+e0OWsSIAESIIFgIZBYrUjuHZgix1PCZcfxKEnLDJWoiGJpXidf2jXIlfCwYCHBeZIACZCAbxCgAuIb7wNHQQIkQAIk4GUCDWsUCF4UEiABEiCBqiVAE6yq5c/eSYAESIAESIAESIAESCCoCFABCaq3m5MlARIgARIgARIgARIggaolQAWkavmzdxIgARIgARIgARIgARIIKgJB4wPyyy+/yIYNG+Suu+6SuLg4m2/y6dOn5ciRIzav6ZOtWrWSxMREfWjanj17VtatWyfHjx+Xhg0bSqdOnaRZs2YSElI26oqpkrHz66+/yp49eyQvL086duyoXrGxseZFbO67Ws9mYzxJAiRAAiRAAiRAAiRAApVEICgUkL1798qTTz4pubm5MmbMGLsKyNy5c+W///1vuehffvll6dWrl0WZL7/8Ut555x3VvvmF3r17yzPPPCNRUVHmp9U+FJbJkyfLjh07LK5FR0fL888/Lz169LA4rw9crafrc0sCJEACJEACJEACJEACVUkg4BUQ3LBPmjSpjHJgCzoUFUjjxo3F3iqE9fnFixfLjBkz1EoHlJtu3brJsWPHlCLz888/yyOPPCKvv/66hIWVxnmEIoTz+/fvl9atW8tNN92kVlVWr14tCxYskMcee0ymTp0qPXv2tBimq/UsGuEBCZAACZAACZAACZAACVQhgYBWQBYtWiQzZ86U9PR0hxBrBeSFF16QFi1aVFgHZlOzZs1S5aBQXHvttaY6/fr1k7/97W/yxx9/CMy/+vbta7r27bffKuWjSZMm8uabb0q1atXUNayYNGjQQN577z2ZPXt2GQXE1XqmjrlDAiRAAiRAAiRAAiRAAlVMICCd0JOSkuQf//iHQJGA8tG/f/8KMZ86dUqVhQlU06ZNKyyPAitXrpTk5GSJj4+Xq6++2qJO7dq1Zfjw4ercvHnzLK599dVX6hjXtfKhC4waNUpiYmIEytC2bdv0abV1tZ5FIzwgARIgARIgARIgARIggSokEJAKyObNm5XDOZzN4WcxZcqUChHr1Q+YRJmbS5VXccuWLerygAEDJCIiokzRgQMHqnNwGD937pzah8ICEy3IVVddpbbmf+Avctlll6lTy5cvN11ytZ6pAe6QAAmQAAmQAAmQAAmQgA8QCEgTLCge48aNkxtuuEE5nOfk5FSIWisgbdu2FUTDWrt2rVIUsJKBc127di3Txq5du9Q5eysmjRo1UspMYWGhHDx4UDp37iy6DlY+0LYt0e0dOHDAdNnVeqYGuEMCJEACJEACJEACJEACPkAgIBUQRJCyF0XKHnOtgPz+++8yf/58yc/Ptyh66aWXKufwOnXqmM6npKSofVtheXUhmGelpqbKmTNn1Cldp3r16rpImS3qQHQd7LtaD3WtZcWKFWpM1udxjHHZUrZslbV1znwlCCtJMCfzZcEYESrZ18dpzjU8PNznxxsaWrK46k9cwdjXx4v/Jf1ZgLmoP4j+LGCsGHNRUZHPDluPVTP22YEaAzMP8e7OZ6G4uNiXp8mxkQAJBCiBgFRAXHmvtAKCyFRQNi6++GJ1M44wud99952sX79eJkyYIHPmzDGF1c3KylJdOaKA6FUYXSchIcHuMPU1XQcFXa1nq5M33nijTPhfXa59+/byzTff6EO3tjAnsxWC2K1GvVS5PIXQS1263CxuNty54XC5Yxcq+hNXKB/+oIDot8Gf2Oox6+82feyrW+toh746Tj0udz4L1g/bdJvckgAJkIA3CVABMegimhV+GDMzM+W2224TOIJrGTJkiAwbNkzuvfdelaTwo48+krvvvltd1l/c1o7kui62+oZGl0VfEGfqoLyr9VCXQgIkQAIkQAIkQAIkQAK+QoAKiPFOREZGygcffGD3PYEPyF/+8hf55JNPBOZLWgGpWbOmnDhxQjIyMuzW1de0wlGrVi1VVp+3VVFf03VQxtV6ttqHUgV/FFuCMMBQxFwVmDTpp/NQurTi5Gp73q6HFRqYMpivNnm7T1fah9mVXk0CU63QutJWZdTRnwFf5wpTG/z/Q5Bnp6CgoDLwuNWH/ixgVdQfzGfwEEabNvn6mPFdgO9df/gsmHN15zsbJnH+YHLm1j8NK5MACfgcASogDr4luGGHAoIIVvhxws0gnMihgOgIV7aa0jlI4BgP0Y7n5dXR13Qdd+qpTq3+3HPPPVZnLA8xJ1fF3DwIN8l6Lq625+16MF3ADZ2vjxM3ReYKiP5ceZuPq+2DKcTXueJ/zFwBcedGzlVWztbTnwWw9QcFBHy1AoKHKwjK4auCByjgm52drV6+Ok6MSyv52Mf3gaufBbw32u8QbVFIgARIoDIIBGQYXm+A07bLeFqkf0ArUiZQVt8o1q1bVw1Lr2SUd2NmXQcVXa3nDRZskwRIgARIgARIgARIgARcJUAFxCCHyFdPPfWU/POf/7TLUefugNKBJ2QQmCtBtm/frrbWf/R5PLnWmdXr1aunQvPCFAGheW3J1q1b1ekOHTqYLrtaz9QAd0iABEiABEiABEiABEjABwhQATHeBEQ8gW/Hjz/+KIcOHbL5tixcuFCd7969u+n60KFD1T5yhugoVaaLxs7SpUvVIepokxQoL0hcCFm2bJnamv9BwsFNmzapU5dcconpkqv1TA1whwRIgARIgARIgARIgAR8gAAVEONNQPbz5s2bq7fjxRdftFAmYFcL34+NGzcqR7277rrL9LY1a9ZMevfurRytp02bZjLNQoHffvtNFi1apMrefPPNpjrY0cfz5s2zWD2Bz8Qrr7yi4uR36dJF2rVr55F6Fo3wgARIgARIgARIgARIgASqkACd0A34iHzy7LPPyvjx45VCMGbMGOnXr59y+v3jjz9U9nI4Uk6aNMlkdqXfszvvvFM2b94sixcvln379glWLeDE/csvvyjFZOTIkWUS+yGq1qBBg2TJkiXy4IMPKiUGCQ7XrVsnhw8fViGBH330Ud2FaetqPVMD3CEBEiABEiABEiABEiCBKiZABeT8G4AVECQZnDlzpsCk6uuvv1ZXEBUFN/5QCLC1Fpx777335JlnnlGKChIZQmAydeutt8ott9xiXUUdT5kyRbCCgtUVmH5pQbQtKCVNmzbVpyy2rtazaIQHJEACJEACJEACJEACJFBFBEIME6PiKurbZ7uFP8eRI0dUToBWrVqZwp9WNGCEmIQCAp+SJk2aOFQP+NFXUlKSNGrUSHS0rIr6crVeRe3iurtheGvUqKG6Ace0tDRHuqyyMjoM79mzZ6tsDI50DIU2MTFRFcXnTEdKc6RuVZRBjhwIfJp8WRCGV4cgRWQ6fwnDi8/CyZMnXQ69WpnvCQJ36DwTp0+ftjBVrcxxONIXHjjhOzg1NdXnw/BinBgvxJ3PAsLwIsgJhQRIgAQqk0CVr4AgUZl5PPPKnLy9vnCzZ2u1w155fR43M/YS/Oky1luYf2G1w96Kh3V5fexqPV2fWxIgARIgARIgARIgARKoCgJed0KHX4N1ZCk8XbrvvvsEqwt4+njllVfKm2++qZyvqwIC+yQBEiABEiABEiABEiABEqgcAl5TQFatWqWiOPXq1UuFuNXTQXK+sWPHyqxZs5S5UkFBgfKBeOCBB+Txxx/XxbglARIgARIgARIgARIgARIIQAJeUUBSUlKUkrF7926FTDtm42D27Nmic2rguEePHspfAvsvv/yyfP7559ilkAAJkAAJkAAJkAAJkAAJBCABryggWMnQmcMHDx4so0ePNqH78MMPTfvIg7F+/XrZs2eP6KR+yMNBIQESIAESIAESIAESIAESCEwCXlFA1qxZo2ghR8YPP/wgHTt2VMeIrgSFAwLTrBEjRqh9OKFPnz5d7e/YsUNyc3PVPv+QAAmQAAmQAAmQAAmQAAkEFgGPR8GCT8fevXsVpeHDh1vQ0pnBcXLYsGEW19q0aaMS8CEU5tatW+Xiiy+2uM4DEiABEiABEvAmgYNnwmXhNpHDJ2OloDBa6iUWSLfmOdKiTr43u2XbJEACJBB0BDyugBw4cEBlAAfJAQMGWADFaoiWIUOG6F3TNiEhQaCAIC8GFRATFu6QAAmQAAl4kUB2Xoh8vDZR/jgcc76XCGMbIduOiizfboRXb5ojt/ZNlZhIps3y4tvApkmABIKIgMdNsJALQwtyfGgpLCyUZcuWqcM6depIt27d9CW1zc/PNyXAa9iwocU1HpAACZAACZCANwjkFYjMWFzzvPJhS8Eols1/RsvrP9QSlKWQAAmQAAm4T8DjCkiDBg0Eifwg2t8D+ytWrBBEx4IMGjRIkEjPXObOnWvKkNusWTPzS9wnARIgARIgAa8QWPBHvPyZFHm+bcvfpZKTJeeOJEfId5vivTIGNkoCJEACwUbA4woIFAskFoQ8/PDDAr+Pffv2CfJ8aBkzZozeFaySzJgxQyZMmKDOde/eXerXr2+6zh0SIAESIAES8AaB3PwQWbUz1mja1sqHdY/FstIom5FjS0mxLstjEiABEiCB8gh43AcEnT322GOyYMEClWhQh9fVg+jZs6cgNC8EGdE7depkCtmLc1OmTMGGQgIkQAIkQAJeJbD/dITkFzqqUIRIoaGnTPyinjSrnS/922VJj5bZEupoda/OhI2TAAmQgH8R8PgKCKbfp08flVAwKirKgkbLli3l22+/lbCwMHUeTudJSUlqHysnU6dOleuvv96iDg9IgARIgASCh0CxcZO/92SkLPwjTuauT5Dvje3uE5FS5MgihZOYUrNKfoucrCaHz0bKR2uqy6xlNSTHWEWhkAAJkAAJOEfAKysgGMKoUaNUlvOlS5cqE6x+/fqpqFixsVjuLpHQ0FCByRV8PsaNG1cmapYuxy0JkAAJkEDgEziSFG5Eo6ouRw1/C2tpWD1f/to3TZobqw+ekpgIV7QarXAUy45j0fKf1dXlnitK/Bs9NS62QwIkQAKBTsBrCgjAtWjRQsaPH18uw9WrV5dxSC+3Ai+SAAmQAAkEHAGYQ72xuJZdk6jjqREybWEtuf+qZGnTIM8j829WR7cDRUQrFo42jfIlEbK2HY2STo2ZQNdRcixHAiRAAl4xwXIGq3U0LGfqsiwJkAAJkID/E4Az+PsrathVPvQMC4qMciurC/J2eEJqxhZJh0YIF+9qeyX1ft6j84d4YlRsgwRIgAQCn0CVKyDmiHfu3EkndHMg3CcBEiCBICCw1riBT8t2zB8jIzdMftpVEurdE2hu6nFOoiKK3GrqsCmMr1vNsDIJkAAJBA0Br5lgIfHgl19+KR9++KFKMJiXlydFRaVf8sWGpyHK4JWbmyvJyclqC/LPPfdc0LwBnCgJkAAJBDuBrUejnUKw9Ui0DL4o06k69grXSyyU+wYmy7s/1pTMXNeeyWEFh0ICJEACJOA4Aa8oIFAuBg4cKCtXrnR8JCxJAiRAAiQQlASSMhxb/dBwnC2v69nbNq5ZIHdcliLr9sfKgbPRkpxur6Tt89WrFdq+wLMkQAIkQAI2CXhFAXn33XctlA9Evqpbt64cPHhQDaJp06aCFRGsemCr5f7775cbb7xRH3JLAiRAAiQQBAQiwpyLRhUR7lx5ewihyMz/LV5+PxwthYZ/iZa46CIj4aDjqyEdGtEBXbPjlgRIgAQcIeD4N6wjrZ0v8/7776u9GjVqCMLwZmRkyIEDB6Rhw4bq/KeffqrMsjIzM9V188zn/fv3d6InFiUBEiABEvB3AliBcEYa13A/FC+ibk39trZsPBhjKB+WvTujfEB5uqKDZ8zBLEfBIxIgARIIXAJeUUD27t2riE2aNEmZYml8AwYMULvIkg4JDw9X13/66Sdp0qSJzJo1SzZs2KCu8Q8JkAAJkEBwELi0Zdb5iVa0slFyHRnI3ZG0rFB5Z3lNycrTP4Glqx+l7VY0FpQslrG9U6W6EU2LQgIkQAIk4DgB/e3reI0KSp4+fVrOnTunSg0bNsyidJcuXdSxtZLRunVref3115WT+kMPPWRRhwckQAIkQAKBTaBDozy5sLEj4XBDpF2DXOnSzD2Tp4Wb4xxwOIdSAiXEtiISH10o4wekSI+WGDeFBEiABEjAGQIe9wGBX4cWrGqYS5s2bdThli1bzE+rfWRKR04QKCfwC4mMjCxThidIgARIgAQCk8Dt/VLl7eU1ZN+pKLsTbG4kDrzrcveyjiMY42+G2VWJYmFr5cO8+5LrvVplSVhosaTnhElsVJG0qpdnKEE5Eu1SJnXz9rlPAiRAAsFJwOMKyAUXXCBhYWEqvC58PxISEkxk27Ztq/aTkpLk2LFj0qhRI9O12rVrS/v27WXHjh2CfCCdO3c2XeMOCZAACZBAYBOIiSyWCYOTZeXOWFmxs5okZ5T+PNWILZT+7TJlgOFrEeFcwKwy0FIN86tS06syl22egJ/Hzb1KVvZtFuBJEiABEiABpwiUfsM7Vc1+YaxctGjRQvbt2ydbt241OZ6jBs5r5WTz5s0WCgjygZw4cUI1DId1KiD2GfMKCZAACQQigTDDKPjKjpnqhQhVcAaPM1YcasV7Lswtsqk7K67UcbYPlicBEiCBYCLgcR8QwMNKBuT555+XrCztXCjKrAr+HpB58+aprf6zdu1aSUkpWVrX0bL0NW5JgARIgASCi0CtuEJpVjvfo8oHCNYwcnbAnMqeb4ctyrXjnYvSZasNniMBEiABEigl4BUFZOLEiRIaGiqrV6+WHj16yHvvvSdITggZOXKk2n7wwQcyY8YMSUtLU6slTzzxhDoPP5BWrVqpff4hARIgARIgAU8SiDDW/ds3hBO7IyshJb9bFzVxz+ndk+NnWyRAAiQQCAS8ooD07dtXJkyYoPhs375dHn30UeVgjhMPPPCAREWVOBk++OCDglwhWBXBCghk7NixUqtWLbXPPyRAAiRAAiTgaQLDumQYv0mOrIKESPfm2dKwBldAPP0esD0SIIHgJuAVBQRIX3jhBXnmmWekQYMG0rJlSxNlJB2cO3euxMQgComxCH5+ZQT7KDd16lTsUkiABEiABEjAKwRg2vWXHuU5lZesfDSsni9jeqd5ZQxslARIgASCmYDHndA1zOjoaHnyyScFyQjhcG4u1157raxZs0Y++ugjQRLC2NhY6dOnj0yePFni4+PNi3KfBEiABEiABDxOoH/7LEk0/EH+tyFRUjItQ2vBOKunEXr3pkvPMdSux8mzQRIgARIwkpF7G0JERIRcfPHFZbrp1q2b4EUhARIgARIggaoggISGFzY5LbtPRMqRpAgpKAqTZg1ipWXtcxITVhpApSrGxj5JgARIIJAJeF0BCWR4nBsJkAAJkEDlEUjNDJWTaeFSZFhI1U0olNoeCM+L0L/IxI4XwsTXrRsrqanFkp1defNiTyRAAiQQbASogATbO875kgAJkICfEThwOkK+3pgg+09HWoy8cc18ubZbunRqXBKlCorJ2fQwyc4LlcSYQqkea6Q9p5AACZAACfgcAbcUEITOPXv2rMcnNXv2bI+3yQZJgARIgAT8j8DPe2Pks58TjVUPeGbAObw0fO7R5AiZtaymDLkw3bgSImuNshk5pf4c9RILZGDHDOndOtuIeuV/c+eISYAESCBQCbilgHz++edy6NAhj7OhAuJxpGyQBEiABPyOwP5TEfKpoXyUBku0pUUUyw9bbQcvOWWYa336c3XZdjRa7uqfIuGluonfseCASYAESCCQCHgtDG8gQeJcSIAESIAEKp/AV4bZVbFa+bCleOjxlHcNZYpl85/RRrSrBF2BWxIgARIggSom4NYKyJw5cyQrq/xIIbfeeqskJSVJz549VVjeKp4vuycBEiABEvADAkmGL8ehM/D5sDS7cn7oUFCKZfXuanJZ2yxpXJNJBZ1nyBokQAIk4FkCbikgl19+eYWj0QkH69WrJ0OHDq2wPAuQAAmQAAmQwPFU/fNU0QqHI6xK2vj1QIyhgKQ7UoFlSIAESIAEvEiAJlhehMumSYAESIAEXCOAiFaeFjitU0iABEiABKqeABWQqn8POAISIAESIAErAnU8kOPDqknJL7Q+w2MSIAESIIGqIEAFpCqos08SIAESIIFyCTSsUSB14j3rr1ErjhpIudB5kQRIgAQqiQAVkEoCzW5IgARIgAScIzDcSDJYIp6xx7qwSUnCQudGwdIkQAIkQAKeJqC9/DzdLtsjARIgARIgAbcIXNwix4iElSE/7oiz047jEbIa1ciXLs1y7LTj+OmUzFA5fDZCcvJDpXq1Qrmgbp5E8pfUcYAsSQIkQAIGAX5t8mNAAiRAAiTgswRu7JEuDaoXyPzf4iUj1zKTYFR4sXRqki2bDsWczxdiPY0SBSU2qkjGXZ4ioW4E1DqZGmbkEkmUncejLDqJDC+SAe2zZGjndIngL6oFGx6QAAmQgD0C/Lq0R4bnSYAESIAEfIJAnzbZ0uOCbNlzMkpOGOF5ESGrbkKBtGuYJ9ERxdKndbZ89kuinE23/kkLkdb1c+WWPmlS2w2n9j0nI+XtZTUktwBWy5arLnkFIbJ4a5zsPhEpfx+crMbjE9A4CBIgARLwYQLW39Y+PFQOjQRIgARIIFgJYHWhY+Nc9bJmAEXknyPOyC5jdeLgmQjJyguVxJhCpaA0q51vXdyp4/TsUJn9o1Y+UNV6GaXk+NDZSPn050S5q3+qU+2zMAmQAAkEIwEqIMH4rnPOJEACJBBgBMKMxQl7Coo7U128NVYpNBW3USy/HYyRqzplSNNano3eVXHfLEECJEAC/kXALQVkwYIFkpmZWe6Ms7Ky1PVjx47Jf//733LL6oujRo3Su9ySAAmQAAmQQJURgH+JY1KyEoLyTWvp6F2O1WQpEiABEgg2Am4pIA888IAcOnTIIWYbN26Um2++2aGyVEAcwsRCJEACJEACXiSQmx8iqVmWju8VdXcqza2f1Yqa53USIAESCAgCzAMSEG8jJ0ECJEACJEACJEACJEAC/kHArUc148aNk+TkZP+YKUdJAiRAAiRAAk4QiDIibCUauT7SnFgFqWdE56KQAAmQAAmUT8AtBWTy5Mnlt86rJEACJEACJODHBLoZyQtX7Ix1YAYl4Xm7Nnc/2aEDnbEICZAACfg1AZpg+fXbx8GTAAmQAAl4k8CgCzMkJrLIgS5CpGuzbHE37K8DHbEICZAACfg9ASogfv8WcgIkQAIkEFwECgpFJf77eW+M/HogWo6nuLWYXy68xGpFMn5AikSGaSUEKx3mUnLctFa+/NVIeEghARIgARKomID3vrUr7pslSIAESIAESMBhAsiAvnx7rPywJU6yjWSD5tK4Zr7c2OOctKmfZ37aI/ttG+TJxGuSZO76BJWN3bzRcGMY/dtnyPCu6RLJX1RzNNwnARIgAbsE+HVpFw0vkAAJkAAJ+AqBImMB4r2VNWTzn9E2h3Q0OUJmLK4pf+2dJr1aZ9ss487JhjUK5MEhyXI2PUwOnY2QnLwQqR5bJK3q5Um04axOIQESIAEScJwAFRDHWbEkCZAACZBAFRFY8EfceeUDN/slSf+sh1JsXPr050RpZKyGeCsbee34QsGLQgIkQAIk4DoBKiCuswvYmqGhlqYNzkzUvG5ISIiYHzvTTmWW9YdxYoxa/GG8GKs/jNNfuYIv/reKccftR+LqmNOzQ2TZtjhjpvaVjxIMIQIzrW83JcjfB6c6TUZ/Hvzhs2s+OVe5og09Z/P2uE8CJEAC3iYQYvyA+dcvmLeJsH0SIAESIAGfIrB8s8ibCx0fUqihr3/0oChlJN9YrEisJhLm+nMVxzv2w5L5+fkSERHhhyPnkEmABPyZAFdA/Pnd89LYU1Odf3Koh4IfstjYkpj5ubm5kp3teVts3ZcnttWqVZOwsDBJT0/3RHNeayMyMlIwVkhOTo56ea0zDzSsPwOZmZkeaM17TURHRwteEHxW8Zn1ddGfBXf+TytzjvHx8ep/DH2eO3dOiuDM4aQcOIH3yLbvh62msAryf28XSXpOidYRGV4snZvly/DuOdKklv3+sRqQmJgo+NzixtyXJSEhwbTC7O5noXr16r48VY6NBEggAAlQAQnAN9XdKbmjNGBBTd98FhYW+rwCEhUVpUwQ3Jmzu7wdqW9uJlFQUODzXGNiYtS0fJ0rlE+tgOCG09fHC6j6swBF1B8WsPF9AM4QjBnfC47KnhOR8vO+GNl2NNLRKqZyWvnAiTwjOfmv+yPltwMRcnPPNOnb1vaDET1Of/gsQLHT4s5nwR/MZPU8uSUBEggcAlRAAue95ExIgARIICAIQGH4ZG112XiwRJF1f1IlPlRYGfnsl0RJMHJ7XNTE91e73J83WyABEiAB3yRAq1jffF84KhIgARIISgLwSpzzU43zyoenXRShiITI3HUJUmjfEisouXPSJEACJFCZBCplBWT37t2yceNG2bt3r3o1aNBAXn31VTXPOXPmyKBBg6RRo0aVOW/2RQIkQAIk4IMENh6MrjDcrv1hQ2EpjRhnr1xyZrjKpN6hkeeTFtrrk+dJgARIgARKCXhVATlz5oxMnjxZPvjgAwvHw759+5pGgOvjx4+Xe++9V6ZNm2ayFTYV4A4JkAAJkEDQEFixsySIhSOKRFkoFSsfus7hs5FCBUTT4JYESIAEKpeA1xQQrHgMHDhQ0tLS7M4IEWdOnjypHCnfeOMNOX78uHzxxRdUQuwS4wUSIAESCFwCCJl76AxCwjq2kuEOidwC+8rKuawQWfR7nOH8Hi3JGWGCKFpNjOSGPVtlS9fmOe50y7okQAIkQAIGAa/4gGRlZcnYsWOV8oGoIrfffrvMmzdPJk6caAEd16ZPny7169dX57/88kv57LPPLMrwgARIgARIIDgIZOXiJ6nET8PRGTerlSd/H3TW0eKmcuGhtv1Lft0r8thnCfLDlng5mhwhWXmhkpoVJlsNZeS9lTXkjcU1JSvXvvJi6oA7JEACJEACdgl4RQF58sknZc+ePSpG+ffffy/w8xgxYoRJ0dCjCQ8PlwkTJij/kNatW6vTzz33nF+EltRz4JYESIAESMAzBKpFFRnqBxQD28qBrV6a1MqXdg3zpV6iETrLISlpe+m2WGOFI8qixu7jEfLiV0a44Hx7Ckax7DoRJbOW16QTuwU5HpAACZCAcwS8ooAsXrxYjeLxxx+XwYMHVzgiOKA//PDDqhwUl6NHj1ZYhwVIgARIgAQCi0CEkS6keR0kALSnAJSdr5E7UP6zOtFYztdKi96WLVtypqTt/MJQeW9FDTmeUmKJjKhYH61JUNnT7dXU4zpwOlJW7SxJDGq/LK+QAAmQAAnYI+BxBQQJkXbt2qX6u/766+31W+b88OHDTQm2Dhw4UOY6T5AACZAACQQ+gQHtM89PsiJFwlAHQopl9e5YWb+/mpxIg+8IBApGxXVRMr8wROZtLEnot/1YlJxNL0mYiGsVyapd2lm+opK8TgIkQAIkYE3A4wrI4cOHTZlu27Zta92f3WOsgtStW1ddT01NtVuOF0iABEiABAKXQPcWOdKlKTKVV6RIFBvmuiWrGWVp2DtvXbJYdhqKR3p2qOw75Vy29TPp4XLOqEchARIgARJwnoDHvz2bN28u8O2AIO+Ho5KUlCSnTp1SxZ1RXBxtn+VIgARIgAR8nwBMqu7olyo9WmYZg7WnSGCFw941Z+YIj5MQOWaYYZU4wDtTVyRTOc07V4elSYAESIAEvBAFKyoqSrQC4UxEKziqQ1BfO6TzDSIBEiABEgg+AhHGM6zbL0uTh68+a4S+zZIG1fOlZmyBXFA3Ty5sgjC4nlA+SrnCFCs+2vnU6PHRRtxgCgmQAAmQgNMESpYqnK5WfoUrr7xStm/fLq+//roMGDBAhg0bVm6F1atXy5QpU1QZJClEeF4KCZAACZBAcBNoVS9fWtWzzCU1+8fqHodSK65QwsNyZfHWOIfbhlIUF+2Yr4nDjbIgCZAACQQJAY+bYIEbQum2aNFC+YLAuXzcuHGCyFjmSQkzMzPl559/lnvuuUf69+8vSEoYExMjb731VpCg5zRJgARIgAScJYCcHJ6UmnEF0rBGgbRtkCeNjG3FUqJ0XNFBO8tXXIMlSIAESIAELAl4ZQUkPj5ePv74Y8FKCBSLDz74QL101+vXr5eEBCPcYZHlkvfUqVNN5lu6LLckQAIkQAIkoAnERHpq1QHthMjQzhmq6VDDquu2fufkle9rSr5dPaSkTqfGOdKrNRzlKSRAAiRAAq4Q8MoKCAbSp08fZYZ13XXXlRlXfn6+hfLRrl07WbJkiUpKWKYwT5AACZAACZDAeQLN6+Q5ycKWwlKiSMC/pLeZItGsdoE8M1qkeqzlw7HSDkOkxwVZMu7yFIHCQiEBEiABEnCNgFdWQPRQWrZsKd98842sWrVK4OeBqFh4nTt3Tlq1aiVt2rSRCy+8UG6++WaJiNAx3HVtbkmABEiABEjAkkDPltmyeEvc+YSB5WkBJUoGSlirIJFhxTKkc7oMvrCsGVW7xiIvjj4nK7aGyFYjU3pyRphEhhdLk1oF0tOIzNXS8EuhkAAJkAAJuEfAqwqIHhp8PPCikAAJkAAJkIA7BOokFMrVhtnU938ggWCJklG2vZLzMJW6uWeabD0SLaeNvB1hRuLC+tUL5CIjklZ5DuRRxvOw/u2z1Kts2zxDAiRAAiTgLoFKUUDcHSTrkwAJkAAJkIAmAL+NnLwQWb5DR63SiojehkiHRjlyZ/9UiY4opiKhwXFLAiRAAj5CwC0F5I477jAlD5w+fbrJgXz8+PFy9OhRl6e4cOFCl+uyIgmQAAmQQGATQLLCG3qky0VNc2XZ9ljZcyJScgtClF/GBXVz5bK2WXKxkVEd5SgkQAIkQAK+R8AtBWTlypVy6NAhNat//vOfptn99NNPsnv3btMxd0iABEiABEjA0wRa188TvCA5+SESZfhqUOnwNGW2RwIkQAKeJ+CWAoKs5XhBQkNLA2qZn/f8kNkiCZAACZAACVgSgKkVhQRIgARIwD8IuKWA7Nq1y+YsN2/ebPM8T5IACZAACZAACZAACZAACQQ3gdJli+DmwNmTAAmQAAmQAAmQAAmQAAlUAgEqIJUAmV2QAAmQAAmQAAmQAAmQAAmUEPCKAvLXv/5V3n77bUlNTSVnEiABEiABEiABEiABEiABEjAR8IoCsnHjRrn33nulQYMGMnr0aFmyZIkUFRWZOuUOCZAACZAACZAACZAACZBAcBLwigISExOjaObk5MgXX3whgwcPlubNm8uUKVNk3759wUmasyYBEiABEiABEiABEiABEhCvKCDr1q2T//3vf3LttddKRESEwnzkyBF5/vnnpXXr1tKvXz+ZM2eOZGRk8C0gARIgARIgARIgARIgARIIIgJeUUCQB+TGG2+U+fPny/Hjx2XmzJnSo0cPE9bVq1fLnXfeKfXr15fbb79dVq1aJcXFjOFuAsQdEiABEiABEiCBgCLQrl07adGihdxxxx0en9eMGTNU22h/586dLrU/depUUxuHDx92qQ1WIgFHCXhFATHvvHbt2nL//ffL+vXrBXlDYIYFcyxIZmam/Oc//5HLL79cWrVqJc8++6z8+eef6hr/kAAJkAAJkAAJkECgEDh06JDgderUKY9PKSUlRbWN9vPy8lxqPzk52dRGQUGBS22wEgk4SsDrCoj5QNq2bauUjAMHDqhVDziq16tXTxXBuaeeekpp3+Z1uE8CJEACJEACJEACJEACJBA4BNzKhO4qhpCQEOUHctlllwlC9j7yyCPy888/q+YYLctVqqxHAiRAAiRAAiTgqwRgfo57nOrVq/vqEDkuEqg0AlWigGzYsEE+/fRT+eqrr+TYsWMWk+3Vq5fFMQ9IgARIgARIgARIwN8JXHLJJf4+BY6fBDxGoNIUEITfhdKB1969ey0mgHwht956q3JIh5MWhQRIgARIgARIgASqggB8NJBIGf6qCKrjrMB/AmblzZo1c6m+7s/dcaAdjOXgwYNqLJGRkbppj23xEBlBhBo3buyxNtlQcBDwqg/I2bNn5a233hKsaiD87tNPP21SPhCed+TIkbJgwQJBiN4XX3xRqHwEx4eOsyQBEiABEiABdwjgxvrSSy9V9w0DBw6ssCnci+AeAy8ExTGX7OxseeKJJ9S9So0aNVSETpSrVq2a8kv9y1/+om7izevofUSfQlmkF4DgPge+rfB5TUhIkHHjxklhYaG61rlzZ1V2/Pjx6tj6jzvjsG5r06ZNMmDAAElMTJQ2bdqosfTs2VPeeOMN66JOHyO5NJjXqVNHKR5NmjQRBBzCuZUrVzrdHisEJwGvrIB888038v7778vixYuV9m2O9qKLLlIheMeOHas+sObXuE8CJEACJEACJEACFREIDw+XLl26yOzZs2X37t2yceNGufjii+1We/vtt1W5hg0bWpSD/ynSAVhbZqAh+GsgqhRe33//vXz++ecqv5l5J3jQiv7PnTunHrj+61//Ml1GNKpt27ZJWFiYOodyubm5csEFF5jK6B13x6HbwRZ52KZPny5ZWVmm0+gXihdeUBI+/PBDpZSYCjiwg+TSjz32mEqtYJ06ISkpSZYvXy4rVqyQf/zjH/Lcc8+JN1ZcHBgmi/gJAa+sgEyaNEn9s+owbjVr1pT77rtPfvvtN9m8ebNMmDCByoeffEA4TBIgARIgARLwRQLm+TQ++eQTu0P8/fffZfv27er6LbfcYlIIkAz56quvVspHdHS0SpaMHBppaWly9OhRWbp0qVx11VWqHm7mcW9jfeOtO01PT5fHH39cHXbt2lVuuOEGtfpw22236SJ2t54cBzpB0mespiDAD+YO5WDRokWCFRjI119/7VIuEqRUwAoKGGDVB+3ABAv53vDg+cILL1RK2yuvvKJWglRn/EMCdgh4ZQUEfYWGhqp/XCQcvO6669yyg7Qzdp4mARIgARIgARIIUgIwKWrfvr1KvPfFF1/Ia6+9ZlIuzJF89NFHpkNzpQWrAFi5gLz77rvKF1UXhPlUo0aN5Morr1TmVWvWrFH9IIgOTL+sBUoEBIoQLDwgeAjrSGRPT45DdWz8wZwRZVTLkCFDBJFHBw8eLGvXrlXKA5QTKEuOCB4gz5kzRxVFOzDDgtKmBfd5UNZGjBihrk2bNk2Zn9la7dF1uA1uAl5ZAcESHbJo/vDDDwLbSVecuIL7beHsSYAESIAESIAEKiKgFQo4bC9btqxMcfhfwHQKAn9U+GZowaoIHM3xMr9Z19exRdoA3FxrOXHihN4ts8VNvlY+cBFmYo6YIXl6HEjubGs+sbGxyt8WY8MqBsykHBWspkCZwnygMJkrH7oN+MzMmjVLKYEw+UJuNwoJ2CPgFQUEXwiMiGAPOc+TAAmQAAmQAAl4ggBMqnCjD7FlhoUn9TrzuFZWdL/wC0GEKESsgtWGPYGztZbysoz36dNHF3Nq6+lxPPzww3b779u3rzKVQgFrZ3x7laDE6Vxt3bp1s+nDouu2bNlSOnbsqA4dbV/X5Ta4CHjNBMscI2wPsWwJByy8oHnXrVtXLW8OHTpU2WBCc6aQAAmQAAmQAAmQgKME6tevr+4hvvvuO2VWlJmZKXjSr+Xjjz9Wu7jHGDVqlD5tscUqh5YzZ84onxDcq+zatUuZK+H+RUt5JlWI9umOeGocMEsrT1q1aiVbt25V/hvWvGzVg0WLueIFB/fyRM8DzvswQ9MKYnl1eC34CHhVAcE/MJzPERnBnvz73/9WWUFhfwlzLQoJkAAJkAAJkAAJOEoAKxtQQHAzPX/+fBkzZoyqCsdwOEdDEPYffh3WggeiCxcuVBGsfvnlF5X/w7qMo8d4+u+qeGocWMlp2rRpucNA2FwtyNGmndP1OeuteYSwdevWCV6OCJQPrDC5q5g50hfL+B8BrykgP/74o3oqYa41A49e6TAPD4eEP3gygXwgCN9GIQESIAESIAESIAFHCFxzzTUqJwVWL2CGpRWQL7/8UkWDQhvW5lc4h7CysMJA6FhzQdhc+IrgxhxO6MnJyTJx4kTzIjb3Y2JibJ6v6KSnx6HD/trr1/y6viezVxbnochpgZKF5NGOSn5+vqNFWS7ICHhFAcGHFdGvtPKBqAtwTO/QoYNK0APG+KKA5o3kQHAQw7ImQtzBhhKRLSgkQAIkQAIkQAIkUBEBJDaG0zVMgxA6F/cX8NvQ5ldwMkdSPmtB/g+tfODG+qGHHlKO6rhXMXeyhoWGFqxUeFo8OQ7cS0FhMvdbsR4vTKogUETApiKByZYWhBd+6aWX9CG3JOAyAa8oIE8++aSKgoVRIRQcnMSsBf8ceCEqBcy08OWAqAlTp05VS6jW5XlMAiRAAiRAAiRAArYIYIUDCgjMfmB2NXz4cFm1apUqeuutt6poVub1cJM+d+5cdQqhYuHngZxltuT06dOm0zqruemEmzveGAd8L8pTQPbv369GDVMtKG8VibkJFUL3ViSwcHFkZaWidng9sAnYD/vgxrzxBAJyzz332FQ+rJuGEvLqq6+q08g2isyiFBIgARIgARIgARJwhACS4OlM6EiQN2/ePGVZAYdorDBYC/J66NUMhNm1p3ygHiJpaYGC40nxxji++uoru0OE/wYSQkM0L7uFz1+AU7/O57F69WoVNcxeHZiTYcUEdS655BKhCZY9UjzvcQUEqxh79uxRZM3jYVeEWtts4umCrl9RHV4nARIgARIgARIgARDQfh4IfIMAN5D+/ftLixYt1L75H/NIWeYrHOZlsI/8F1AStGjTcn3s7tYb40BYXyQOtBaMHabuEESm+te//mVdxO7x008/ra5BwYDVij1FDFnYkSsFqyBQcBxZYbHbKS8ENAGPKyCIeKA/mDoWtCME8fRBOzadPHnSkSosQwIkQAIkQAIkQAKKwOjRo1XiY9xo6xtwrZRYI0I+C+3nAT/UGTNmqBtnlIMfxaZNm+SBBx5Q2dXN68JkypPijXEguzt8b2GKpjO0I9khTN21Wdr48eNVFnlH5wJTep3nBEmmkU9k48aNgofGuOeDL83f/vY3U3LDGjVqyKOPPupo8ywXhAQ8roA0atTIhBFO5o4KHNd1siC91OdoXZYjARIgARIgARIIbgK46R0xYoQJQnx8vNx4442mY/MdlH3ttdfUKSgcDz74oMpNBlMuPBDt3r27vPnmm8qcCDfyOqO5Iz4Q5v1UtO/pcSAM77PPPitJSUmKBeaCV6dOnUzJBBGSGP62zgoijPXu3VtVQ5JBmFjFxcVJ7dq15YorrhDtrA//D5jT817OWcLBVd7jCgj+4XUW9G+//dZhmgsWLFBPHbAsWFESHYcbZUESIAESIAESIIGgIWC+4oHcYuU5Q997770qbK/OiwGfkG3btklaWpq6qZ4yZYpK2AcfEX3jjXwj5mFpPQHW0+PAuGGGhYTP8MFISUlRw6xXr568/vrrAh8RWzlRKpoLImbBBwQ+u9piBSZZ4AXB/RsioCLJIXx7KSRQHoEQ4x/O4zHlxo0bJx988IEK8QZbTNhglicHDhxQTxuQD6RHjx4CzZpSdQRgv+mqYEkbT3QgsAHVX0yutuftetWrV1dfmr4e+AA/oomJiQoHltQ9/QPoac544gbxtLmCp8eJp3d4aAKB2QISmfm66M8CTFW98PXt8enj6ai2A4etvaejCHlywAhLips2/BZlZ2d7smmPt4Vx6nwO7nwW8MQcN6bBLDAhgvk4rDZwE41VEGRYr2zxxjjgU4uk0BdddJE0a9bMo1PC9zsUNig48LPBige+Uykk4AgBrygguIFFEh/cJOGH56677lJJfKA9IyKFFphczZo1S4XOQ1l8mSITKZb1KFVHgApI1bG317O+6cR1KiD2KDl/ngqI88ycrRGoCsjek5Gy8WC0HE+JkCLjMV6dhALp3DRXujTNMX7nnKXkfHkqIM4zYw0SIAHfIeCVPCBYmkM8bjgkYfnvnXfeUS88HYcGjicMSISjnaM0DkRnoPKhaXBLAiRAAiTgawSy80LkozXVZfOf0RZDO3gmUjbsryZNa+XL3ZenSK34QovrPCABEiABEigl4HEfEN00Vj0QbxoZRbXAVhBLgYjGYK58QGFBxlI4TlFIgARIgARIwBcJ5Bs6xcylNc8rH7atl/9MipBXF9WStCyv/bz6IhqOiQRIgAScIuCVFRA9AkSRQCg7ZEOHU9LOnTvVC4oIMmviBVtLrJRoO2xdl1sSIAESIAES8CUCS7bGySFjpaNE7NtZpWWFyX/XJcj4K1J9afgcCwmQAAn4DAGvKiCYZVRUlNx9990+M2EOhARIgARIgAScJVBYJLJiR6yD1Yrljz9jJMnwbaQploPIWIwESCCoCHCNOKjebk6WBEiABEjAFQJHkyMkK8/Rn8yS1ZHdhqM6hQRIgARIoCwBt1ZA4Eius56Xbdr1My1btnS9sp2aiK61YcMGFZGrojBxv/76qyB0HbKpIps7XrGx5T/5QhhX+LwcP35cGjZsqJL+wOHePOqXraG50hfacbWerTHwHAmQAAmQQPkEzmU7qnyUtuNKndLa3CMBEiCBwCXglgJy+eWXy6FDhzxOx9Ox7ffu3StPPvmk5ObmypgxY+zGqYYSMXnyZNmxY4fFnBC96/nnn1c5SiwunD/48ssvVZQvtG8uSFz0zDPPKDM08/PYd7UvV+tZ989jEiABEiABxwlUizRssJyUapG2HdWdbIbFSYAESCDgCDj/SMfPEOCGHeF9rZUD62ng+iOPPKKUDzjHP/HEE/LSSy/JNddcI3Caf+yxx9QKh3W9xYsXy4wZM9RqCZQbZAh96KGH1CrIzz//rNq0Trzlal+u1rMeM49JgARIgAT1cKqzAABAAElEQVScI9DECK8bEQaFwnGl4oK6ec51wtIkQAIkECQE3FoBMWeE3B7IeI7kSL4iixYtkpkzZzqUNfrbb7+V/fv3S5MmTeTNN98UJH6DYBUDYYLfe+89mT17tvTs2dM0PZhoIZEiBMrLtddea7rWr18/Fd3rjz/+UMkV+/bta7rmSl+o7Go9U8fcIQESIAEScIlApPFreWnLLFmzp3xzXN148zp50rhmgT7klgRIgARIwIyAWwpIvXr1TCZY8AVZuXKlXHnllTJ69GgZMWKEJCYmmnVVebtJSUnywgsvKJ8P9ArFaNWqVeUO4KuvvlLXhw8fblI+dIVRo0bJJ598IjDl2rZtm/LvwDXMNzk5WYUQvvrqq3VxtUX2X7T1/vvvy7x588RcAXGlLzTqaj2LgfGABEiABEjAJQLDu2XIjmNRkpxZ/k8nVkrG9EpzqQ9WIgESIIFgIOCWCRYcu2Fm9Pe//13q168vMDVasmSJ3HHHHQLlZOTIkfK///1PsrOzK5Xl5s2blfIBZ3P4dEyZMqXc/qFEHDt2TJW56qqrypRFKOHLLrtMnV++fLnp+pYtW9T+gAEDJCIiwnRe7wwcOFDtwmH83Llzat/Vvlytp8fCLQmQAAmQgHsE4qOL5O+Dk6VugvnKhqVZVrWoIrlvYDJXP9xDzdokQAIBTsAtBQQRnnr16qV8IHADj5tz5PyoWbOm8rn4+uuv5S9/+Ysyy7rlllvk+++/l/z8fK8jheIxbtw4pfwMGTKkwv527dqlysDsCisXtqRp06bq9IEDB0yXdT19zXTh/E6jRo0kLCxMHR08eFBtdR1X+3K2nvWYeEwCJEACJOA6gboJhTL5ujNyY480aV47T6LCiyXc+CVtUD1fhlyULv8aeVraNKDvh+uEWZMESCAYCJS/juwEgdDQULniiivU66233pKlS5fKF198Id98843ywYAJE161atWSG264QZlpwU8C9TwtPXr0sBuxylZfKSkp6nT16tVtXVbndKb2M2fOmMroeuWZmqFeamqq6Hq6jqt9OVvPNFiznd9++00yMjLMzpTuQnlr0aJF6Qkn98xXgqB8YfXIlwWfPyjSvj5O+Fhp8ReuGK8/cQVjXx8vmOrPQmSkf+SYMA9FjjEXFTkfTQrzrgzRv0cVfRbwrXZ110LjZet7tHLeF3Ou+Nx6OnpkZfBmHyRAAsFLoPSuxoMMcBM6dOhQ9UIEqYULFyplZMGCBQL/DDhz44V8GfCvgM/IJZdc4sERONdUVlaWqpCQkGC3or6G+WjR9RxRQHQ9XUe3p9sy3+prug6uuVrPvF29/9xzz5UJNayvtW/fXimN+tidLX4U/eGGDnPEqp2/SExMjODlD+JPXLG6iJe/iD+x1UzLe4Ciy/jCtqJcUb4wRvMx1KhRw/zQqf3KsEpwakAsTAIkEBQEPL/8YIUNOTTgCzJ37lw5ffq0fPrppyq0LZ6EIWnf9OnT1WpFq1atVK6O7du3W7Xg/UNEs4KUd/Ohb/jMv6z1vjP1XO3L1Xrep8ceSIAESIAESIAESIAESMBxAl5ZAbHXPZ4qIVcGXjBLgo8InNSXLVumQuDiyTxelb2UDLMwiD2zJPNr5soGnkCeOHHCqXqu9uVqPTUxqz/w22ncuLHV2ZJDhCF2J2gAzIO0aQgio2klzWZnPnASY4UpQ0V5Yqp6qOZcwRRsfVn0Z0Arzr46VpjaaLNBf+AKjnrMWCGt7O9KV95HrIJq0yZfHzO+C/DQDJ9b6/xNrszdm3UwTm2G5c53Nkzi9P+AN8fLtkmABEjAnEClKiDmHWMpHg7i+OJEskBEiqoq0Y7nOlKVrXHoa+ZL86gHBURfs1UvPT1dndb13OkLDZXXl76m+7I1HpybOHGivUvqPObkquBH0fzmMy3Nt0NR4nOIGzooxL4sUHw1VyhL+nPlq2PW5kG+zhX/K/rmC99FmZmZvorUNC58FmD2Cbb+oIDgO08rIPiO8uUbeyj6+A6Dyas7N/WmN8uLO8i5hfFC8D3r6mcB701srGO5Tbw4HTZNAiQQZAQqXQGB2RXyWcAka+3atWW+NOFAXtmiVxf0Dbyt/vUNn3mixYqUCTxZsq7nal+u1rM1F54jARIgARIggUAggN9tV5Wvqpo/gtNopbyqxsB+SaCqCVSKAoIn6l9++aUyt4LSYR0FpWvXrsoZHSF73YnA5CpM5CzBkyQ89UK4XFtj2Lp1q2q+Q4cOpm6QIR1iz29Fn4cJgm7T1b5crWcaLHdIgARIgARIIMAIWN9PBNj0OB0SCFgCXnNCh9Lx5ptvqizk8DdAssLVq1eblI9OnTrJs88+K3v27JFNmzbJY489ZrpJr2zaMGlAMkEI/FGsBUkAMUaIebQuRPqCQKnSUarUifN/EIoY0r17d1PoTFf7crXe+aFwQwIkQAIkQAIkQAIkQAI+QcCjCsjJkycFOUD69++vnJwfeOAB+emnn0xKR7t27eSpp55SKwZYUUCG8tatW/sEiJtvvlmNY968eRYrGnBMfeWVV9QcunTpIpiDlmbNmknv3r2Vw+K0adMsbJuRa2PRokWqqG5b19PHzvSFuq7W0/1ySwIkQAIkQAIkQAIkQAJVTcBtE6xTp06ZfDrMVzj0xFq2bGkyr+rcubM+7XPbtm3byqBBg2TJkiXy4IMPKsWiTp06sm7dOjl8+LAgN8ejjz5aZtx33nmnbN68WRYvXiz79u1TKyRY/fnll1+UYoIQxDAxMxdX+3K1nnnf3CcBEiABEiABEiABEiCBqiTglgJy0003CZ7iW9tgYmUA/hxIMgjzI38RrMhg7MjY/uOPP5qGDcUJSknTpk1N5/QOlIL33ntPnnnmGdm1a5cKJ4xrMJm69dZb5ZZbbtFFLbau9IUGXK1n0TkPSIAESIAESIAESIAESKCKCIQY0SOKXe0bjtWHDh1S1RHOdMSIEUrp6Nmzpyk+uStt60zgrtT1RB0gOXLkiMra3qhRIzGPfFVe+8gjsn//fhXSEPk0HMkC7mpfrtYrb/z6mrtheHVWXvjF+EsYXoSC9mWBQovQqxB8znR0NV8dsw7DC/8pXxaE4UVEGgii6fhTGF6YvLrx9V1pbwuiBepQx0hG6+thePF9jxDH/hSG153PAqIxIciJv4qvh/q2xRX3OIyCZYsMzwUTAbdWQMxB4Utgzpw56mV+3pX9qv5RRXInrHbYWvEobz64mXHWzMzVvlytV974eY0ESIAESIAESIAESIAEvE3Ao07o3h4s2ycBEiABEiABEiABEiABEvBvAm6tgPTt21datWrl3wQ4ehIgARIgARIgARIgARIggUoj4JYC8vHHH1faQNkRCZAACZAACZAACZAACZCA/xOgCZb/v4ecAQmQAAmQAAmQAAmQAAn4DQEqIH7zVnGgJEACJEACJEACJEACJOD/BKiA+P97yBmQAAmQAAmQAAmQAAmQgN8QcMsHxG9myYGSAAmQAAmQAAmQAAkENQEkzjbPwfLHH3/I/PnzBbnb7rzzThObl156SXJycmTcuHGCfHCeEOSZWr16taBPtN2+fXu57rrrJDo6utzmkZtt4cKFcuDAAbngggukd+/e0q5dO7fy7ZXbYSVdpAJSSaDZDQmQAAmQAAmQAAmQQOUTgOLxzjvvyM6dO2XmzJmmAUAZePrpp9VNvbkC8uKLL6qEpFdffbVHFBAoHrfddpscPHjQ1Dd2kPj0008/lYEDB1qc1wcY66RJkwSJnc1l+PDhMnfu3AqVF/M6vrZPEyxfe0c4HhIgARIgARIggconYDyVDlmzWkLnvC9hb0yX0A9mS8iK5SLp6ZU/FvboUQKvvPKK3HfffZKSkmLRblhYmERGRkpERITFeU8ebNy4UQYMGKCUj65du8q///1vWbJkiUyePFkpOTfddJPs3bu3TJeffPKJ/P3vf1erJRMnTpQffvhB3nrrLbUK8t133wmUo8LCwjL1/OUEV0D85Z3iOEmABEiABEiABLxCIGTbVgn97BMJycwwtR+CvS2bpXjhAikaeaMU9+pjusYd/yKQm5trc8C33HKL4OUtgYIwfvx4pShglWPBggUSFRWlurvqqqvk8ssvF2yvvfZaWbdunSQmJqprGO+jjz6q9rFyc/fdd5uGOGLECOnVq5esXLlSvv/+e1XXdNGPdrgC4kdvFodKAiRAAiRAAiTgWQIhWzdL6PvvWigfFj3k5UnYF59JyE8rLU7zgAQqIrBt2zb5/fffld/JrFmzTMqHrgelBMrHrl275KOPPtKn5csvv5STJ09KzZo1lemW6YKx06BBA+WbgnNYEfFXoQLir+8cx00CJEACJEACJOAeAcO2PvTTjyWkuNhuO1gJwdXQr78SOX3abrnKvnDPPffIDTfcIHBu/uabb9R+48aNpXXr1nLrrbfK9u3b7Q4JTtDPP/+8MuOBk3XHjh1l7NixsmzZMpt17rrrLtV+nqGMPfnkk9KqVSv15H727NkW5c+cOSPvv/++jBkzRjl2t2nTRvDEfs2aNRbl9IGz49BzxgoBVgywMoCxN2/eXPXz7bff6qbVNiMjQ437iy++UMc//fSTOoZJE2TFihXqGOZQjoozY96xY4dqFuPD+2JLevbsqU6bs9e8YJ4FEzFrGT16tDq1dOlSSU5Otr7sF8c+Z4KFD5R+M/yCIAdJAiRAAiRAAiTglwRCflkrIdnZFY5dmWMhgtKqH6XoppsrLF8ZBRAZ6ejRo3LRRRfJv/71L4mJiZELL7xQdu/eLR9//LFSStavX6+iLZmPB0/lR40aJbg5DgkJkWbNmsnx48fV8eeffy4TJkyQ1157zSJaFEyHThvKF/p54YUXVHP79++X2NhYZWKEE7gR7tevn3qaj2O0e/jwYeXfAAUJkaX0jT+uuzIOPed58+apqFVQBuLi4gSKBvpCP88++6xMmTIFXUh+fr58/fXXUnxewTxy5Ihi1q1bN3UdddAWIks5Is6O+dSpU6rZhg0b2m2+evXq6hra1gK/EUjbtm31KYtty5YtJTw8XAoKCpSiedlll1lc94cDn1gBwQcHWjScc2DXRiEBEiABEiABEiABbxMI2b3LqS5CjJt7XxNEccJKCFYf8BAX2/vvv9/wnU9XqwLnzp0zDRk35HiqDuUDTsy4IUdkJigPixYtUiY/r7/+unKUNlUy23n55Zdl6NCh8tlnn8lTTz2lnKRxOdtQ4q655hqlfAwePFgpNIcOHVJmRFAIIIjmhPFB3B3HX//6Vxk5cqRSOjBPzAGmTBAoSNrZvEaNGoIIWFCcIFjlwbG+wVcnHfzjypixUgTZt2+f3V70NT1mFISyB6ldu7ba2vqDuUGOHTtm67LPn6tSBQTaHqISQDPEshrCoVFIgARIgARIgARIoDIIhJjdnDvUX1qaQ8UqsxDMnGBiVK1aNdUtnowjfOsll1yiVkOgNGh58803lZKAPBJ48q9zXGAlZMiQIYLrEJgkmSsuun6HDh3UKgNMgHBTf8UVV6hL7733nvzyyy/StGlTgRkU/BQguEnGagRWGLAK8eGHH6rz7o4Dqz7wmUB/EJg4YfUGq0BQhpYvN6KXeVhcGTPGCbbw50DYXGsBY4ThhaQZny29UqPZ16pVy7qK6Rj+IRCY4PmjVLoCArs9wMZyEZYK4ZQD7VWLN0Oh6T64JQESIAES8D0CqZmhcvB0hBxLCZd8/40u6XtgOSL7BIwbVqfE2fJONe5aYURLQjhZa4EpFeTXX381Xfrf//6n9hGZyVYCPOSXwE08nsDDfMta4M9h6z5t06ZNqugDDzxg02fhP//5j4ra9Mwzz6hy7o4DKyDWc4YCBkUEYr6aoE544I8rY4aCBNYQPGiHoogVGAjMv5CIMDU1VR0jQSKUFQh8bSDx8fFqa+sPzN8guqytMr58rtJ8QJDB8d1331XLemfPni3DBFo1ksB4MxxamU55ggRIgARIoMoJ/HYwWn7YEmcoHhGmsUSGF8klF+TINV3SJbFayQ+26SJ3SMBDBIqbt5CQA/sdbg3lfU06d+5sc0jaf8DcukTnm0BiPJhf2RKsWmAVAWURItZc7DlS6z6Q3duWwBRJmyPhurvjgH+JLcHKC5INwjfC0+LqmJHUcMOGDSoaFlaO4NAPxjCdQiJCKGc333yzKQQvxl2vXj1lVqaVE1tzwYoJpDwlxVY9XznnVQUE8Y/huIQYxosXLzYtLenJAxqgQ/Gg47mmwi0JkAAJBAcB+IV+9kuirN1TYjpiPuu8ghB1fsufUXLfVcnStJbnbyjM++N+cBIo6tmrJNmg8WEsefZsmwOiYOF6cW/fywXSpEkTm4OuX7++Oo/VDKwIYMVAPwCGY3ZFggfH1mKrL9zr6WhP5Tlb67ZgXuTuOLT5kW5Tb/UKgj721NadMcPJHL4v8IWB2RuCBGC15m9/+5s8/PDDStHAOLUzOvbBUfvm4NiW6OhXOneIrTK+fM4rCsiJEydUGDbYBNrTsLE0iBBwegnJlyFxbCRAAiRAAp4ngFWPEuVD396Z91FyO5ieEyZvL6spk687I3HRKEchAQ8SqFdfigcOktClxkNSo1lbSog+X9T9YiluZ/sJvwdH5HRTMGPXyoZ5ZX2Tj5t1PHHHqgDMp+BMjShZ8B0pT2y1CTMha4Fig3s5PK0v74m9roebb3fHoduqrK27Y0YoXSggeIG/uRnbjz/+qKYBSyAtWpHTSoY+r7cw49KsbSmFupwvbz2mgMBxBhCx2oEwaNbLX7CDQ1zqqVOnqoyQXbp0ofLhy58Mjo0ESIAEvEggLStUFm2OM3rQt3f2O0vLDpPFhrJyQ49Sf0H7pXmFBJwjUDT0GhjSGyF2V1hU1J9MKCVFXbpJ0ei/Wlz3lYM///zTZo4JRKGC6JCzcE5v0aKF7NmzR53v0aOH2lr/ga+uztZtfc3eMcyrEFkKY7EleJo/Y8YMgfM7nvx7axy2+vbEOVfZQVHAQ3lEJsN9L8Rc+cDxd999h4307dtXbfEHfCBw7H/ooYfUvvkfrKjgvhuKUadOncwv+c1+WVXWyaFjWW/69OnqQ4WMjsjeqJUPODIh5BkSpeDDB83PW8tjTg6bxUmABEiABKqQwO+Ho6WgCLd2tp45lx3YhgMxxg9u2fM8QwJuEzCe6heNvFEK/v6QFF3UWYq1o3lklBQZKx6F4+6Rojvuwp2j2115o4FPPvnEZrMffPCBOt+9e3fT9Ysvvljtz5kzx3TOfAchYbFighfC8joqWslBJCpbMn/+fKWA4AE1xFvjsNU3zmmHdX1/aq9ceeddGTPylEA5Q5qJlStXlmkeeVx++OEHlXNFhxFGoTvuuEPdL8ONwTxQk24AYZAhiEIG5cgfxS0FBGZUCOEGGzatUQNCnz59VF4PaH34x4BiYmvZzh+BccwkQAIkQALuEzB3OHekNZhipee49ZPlSDcsE8wEWraSorvGS+GLr0rBazOk8JVpUvR/90vxhRf5NBXcZ33//fcWY4RjM25e69Spo6Iv6YsInYvVDVisPPfccxa+uTANgk9ulpEdHk/pdYhdXbe8LcL2IqoW/H0//PBDi6JwCkdfEESvgnhrHKpxG3+wUgDBvaqOQmWjWLmnXBkz+h0wYIBqF24H8JfRAvMqKB04h8zxWB3Sgv1hw4apYABIV2FeD++dZvzII4/oKn63dUttQqxnREqAYGkJiXAA8YILLvA7EBwwCZAACZBA5REoKP0ddrjT/ELHVkscbpAFScAeAT96qgz/C9zI4oYVUah+++03lQcDigaczbU5D6aKp/FI1IfQvU8++aR89dVX0r9/fxV2F1nGEVkJ9RAu1hkzLJjZo91//OMf6uk9cnRg5WXt2rXKjAh9I+iQVkC8NQ70Y0t0RLDff/9d+csgkzjMm5wRV8eMxI5r1qyRZcuWqYf2uFeG9RCOYZqF1ZE33nijzFCefvppQbQy+Ots3rxZBg0apKyJoGxiZQXJJvHe+au4pYDoSSPsGVY5kGimcePG+jS3JEACJEACJGCTQK04ZzSQYgk3Fj8SY5ypY7NbniSBgCOA1Q7kV4Oyof0JEC73tddeUxYp1hOG1Qr8P/BkHTe2OoQuymHVA0/qXYlMCl8FhAT+v//7P1mxYoV6oc24uDh54oknlHKCYy3eGodu33yL7O2w2nn//ffVTT8c9LHS46y4MmY4+yMxInKkILcK8t9BsGKEc1A0ECTAWqDAIYcLXBngX7NlyxZVJCEhQSV3fPzxx62r+NVxiOHE4rJVLbRtaMzmAk0cygiAQSO31qCxrAcbPNgf3n777eZVue8jBGA656rgH0r/I+GfW8epdrU9b9dD2DvYT+poId7uz9X2sYyrQ+1lZGTYtAl1tW1v1NMhEu1F8PBGn660iR9GHUMdYRb9IaOs/iwgs64bX9+u4HKpTu3atU1OlwgHqk0J/jwbIS8uqG20iZ+gilc2LmqSI3+7MsWlMThaCXbiiMuP6DJ6dd/RupVdDuPUdu3ufBZgHo2cA/4qOhKQP40fN5CeMEtH9CP4EODmFooDvr+gTOB/DgqII32gjg6hC+uV8jJvO8MYT/jRLn4LsHJg7Xht3Za3xmHdD8yv4CgPRvj+d0dcGTNyfyCfCO498B45GgkW91JQQHAfgHrwsfZ3cWsFBMtA27ZtU8kFYYOIpSS8IXA2wgs3oki6AkXjkksu8XdWHD8JkAAJkICHCDStnS8XNs6RrUejK2jRyM9g6CdDO2dUUI6XSSC4CeBmFj64zgjqeOP+DPd/zozFW+OwZgGlrHnz5tanXTp2Zczwm8bLWYHicdlllzlbzafLu+3Rh/Bf06ZNUxkdYUuIZS79VAYaMJaasNTXsWNHeeWVV/ziiZ1Pv2McHAmQAAkECIFb+qZKnfiC87OxtxgfIjdeck6gsFBIgARIgAQCg4DbCojGgOW1kSNHqkgMWN6CMxKW3bRgKW7ixImm5fdNmzYJTB4oJEACJEACwUkAiQUnXnNWujVHMJOyZliJ1Qpl3OUpMqCD87bawUmUsyYBEiAB/yDgMQXEfLrI4AjnGNi5rVq1Sm677TaVLMW8zMyZM5Xd6ahRo1SoOHdiM5u3y30SIAESIAH/IRAbVWwoGany9MjTclOPNBnYMUOGdUk3/D2S5ZkbThvKSY7/TIYjJYFKJABTIjzoDQR/gErExq58hIBbPiCOzKFfv36CFxQOhHX797//LcjgCEEYsblz56oXYlUjRNstt9ziFXtER8bKMiRAAiRAAlVDoG5CodTlSkfVwGevfkkAIVopJOCvBLyyAmILBiLN3H333Sru8vbt21U4NkTx0AIHdigp8BehkAAJkAAJkAAJkAAJkAAJBCaBSlNAzPF16NBBXn31VRU+bt68eXLNNdeYHNfNy3GfBEiABEiABEiABEiABEggsAhUiQKiEcJxfcSIESpxzpEjR2Tq1KmChC0UEiABEiABEiABEiABEiCBwCRQpQqIOVJkU580aZLs3r3b/DT3SYAESIAESIAESIAESIAEAoiAzyggAcSUUyEBEiABEiABEiABEiABErBDgAqIHTA8TQIkQAIkQAIkQAIkQAIk4HkCVEA8z5QtkgAJkAAJkAAJkAAJkAAJ2CHg9TwgdvrlaRIgARIgARIgARJwi0BiYqJb9VmZBEigaghQAaka7uyVBEiABAKeQGGRyN7jIZJmJDOPjRKJDwuRaP7qBPz7XpkTDAkJqczu2BcJkICHCPCnwEMg2QwJkAAJkEAJASgeS7bGyfLtsZKVV2rpGxpSW7o2z5ER3c9JzTijEIUESIAESCAoCVABCcq3nZMmARIgAe8QyCsQeXNpTdl3yljysJKiYpHfDsbI7uORcv+gZGlayyhMIQE3CJw7d06Ki40Plh9JfHy8hIaWKuZ+NHQOlQQ8RoD/AR5DyYZIgARIgAQ++znRpvJRQqbEXCYjN0zeXlZTsnJpPsNPjHsEioqKlAICJcRfXu7NmLVJIDAIVLkCkpNjGAdTSIAESIAE/J7An0nhsuFANWMeFT+RTssOk+U7Yv1+znoCxn2wpGWFSkYOlSrNhFsSIAESsEfA6yZY69atk/r160vz5s1NY0hNTZXJkyfL4sWL5fDhw9KvXz8ZMWKE3HvvvVyWNFHiDgmQAAn4F4FNhnlViTh2E77xQIwM75rhX5O0Gu3xlHBZuDlOth2NkryCkmd6iTGFcskF2TLowgyJi65YGbNqkockQAIkEPAEvLYCsmrVKmnXrp306tVLVqxYYQKJ5dKxY8fKrFmzZP/+/VJQUCA//vijPPDAA/L444+bynGHBEiABEjAvwicSHXumdaZ9DCBw7q/yto9MfLCt7Vl06EYQ/koVbqwurNse5w8P7+OYFWIQgIkQAIkYEnAKwpISkqKUjJ2796teoOioWX27NmycOFCfSg9evSQJk2aqOOXX35ZPv/8c9M17pAACZAACfgPATiZOychAtMlf5StR6LkU8PfpXTOpQqIng8UkbcMh/xUwzSLQgIkQAIkUErAK9+KWMk4duyY6mXw4MEyevRoU48ffvihaX/evHmyfv162bNnjwwdOlSdf/HFF03XuUMCJEACJOA/BOokFDo12BrVCiXCDxcIsGozd32CMVcoHWUVD3MI6Tlh8t2mePNT3CcBEiCBoCfgFQVkzZo1Cuydd94pP/zwg3Ts2FEdnzhxQikcOIBpFvw+INHR0TJ9+nS1v2PHDsnNzVX7/EMCJEACJOA/BLo000FFHFsKKS3vP3PESPecjJSkDEc1p2LZaPjGIDwxhQRIgARIoISAxxUQ+HTs3btXtT58+HALzosWLTIdDxs2zLSPnTZt2khCQoLyCdm6davFNR6QAAmQAAn4PoE29fOkfUM8QCp/VQAziYooUk7avj+rsiM8fDai7Em7Z0IkvzBETqY5qrDYbYgXSIAESCBgCHhcATlw4IDk5eUpQAMGDLAAhdUQLUOGDNG7pi0UEMiRI0dM57hDAiRAAiTgPwRu75cqdRP0437bKyHhocUyrn+qJFbzTweQ3HznfzpzXKjjP+86R0oCJEACzhFw/lu0gvbj4uJMJcxzfBQWFsqyZcvUtTp16ki3bt1M5bCTn58vMNGCNGzYUG35hwRIgARIwL8IxEcXycRhZ6VXqywJsbEQ0rx2njwyNEk6NvZfU9sasc75uuAdrOlCHf965zlaEiABEnCcgMfXhBs0aCDVqlWTrKws5e9x7bXXqtEgFC+iY0EGDRpk/DBZ/jLNnTtXoKRAmjVrprb8QwIkQAIk4H8EqkUVyy190+T67ulyLKOWnMsOl2pRIrWjk6R+YskKuf/NqnTEHRpBedKrO5a/ZaWlSvewIlQ73nmlpbQF7pEACZBAYBHwuAICxeLKK6+U7777Th5++GGJiIiQ1q1bqzwfGt2YMWP0rmCV5N1335Vnn31WnevevbtKXGgqwB0SIAESIAG/JBAfUyR9mxQbvwMlwz99ulAOng6X9furydHkcJU7o1ZcoXQyVkOQuC/M42vy3sEGZeLiFjnKubz8HqCkhMhgIyEhhQRIgARIoJSAxxUQNP3YY4/JggULVKJBHV5Xd9mzZ09BaF4IMqJ36tTJFLIX56ZMmYINhQRIgARIIIAI5BtuIR+vjpc1e6KNWZWuGhw+KyqR3yIjm/jdA1KkcU3tP+Lbkx/VM81IMhghp8/hZ7RE0bAcccm5i1tkS6/W2ZaXeEQCJEACQU7AKwpInz59VELB2267zSKkbsuWLeXbb7+VsLAwhR1O50lJSWofKycvvPCCXH/99UH+lnD6JEACJBBYBIqNe/FXvxHZsDfGmBhuzMvKmfRwmbaoljw6LEkaVPd9JSTWMDN7ZOhZ+WhNddl2FEqVpWA1Z2DHDBneNd3yAo9IgASqjECRkfk0NLR0qfWPP/6Q+fPnq4TYSB2h5aWXXlIWOuPGjZNGjRrp025tMzMzZfXq1YI+Yf3Tvn17ue6661QqivIaRnqKDRs2yL59+yQ+Pl7atWsnl19+uSQmJtqsdvToUZVfz+bF8yc7d+4stWrVKq+I1695RQHBqEeNGqWynC9dulRB69evnyAqVmxsrGlS+BDA5Ao+H3iTraNmmQpyhwRIgARIwG8JLN8C5QPDt7VSUDotRIr6aE2iPHZNyYOp0iu+uRcXXSz3DkyRQ2ciZIuRGf2soUSFGRG+GtUokG7Ns6VmnH9G+fJN2hwVCbhOAIrHO++8Izt37pSZM2eaGoIy8PTTT0vv3r3FXAFBUmxY6Vx99dUeUUCgeOCh/MGDB019Y6du3bry6aefysCBAy3O4yA5OVkmTJigrhfjKY6Z1KtXT6ZNmybmLg36MvLq4Vp58v3335sSgJdXzpvXvKaAYNAtWrSQ8ePHlzt+vCnWDunlVuBFEiABEiABvyIwf70ebqnplT5jvT18NlL2nYqQVvXyrS/57HHzOvmCF8W/CWQUZMl3p5fI+tTfJCk/RRLDE6R74kVybd3BUiuyhn9PLshH/8orr8ikSZNk7NixFiRgkRMZGfn/7F0HmFNF1z7be1/K0nsH6aAgiAiigoLYsKJi76J+9s/628uHYkPsggWwIYqCgCIgHQSpi3RYlu29//NOmOxN9mZzb8puspzDE+69U8+8ySZz5jTpr2xT4cGHtWvXygN2BFrq06eP9Ilu0aIFLVu2jMDXxRdfLDUc8JdWBIHjyiuvJOTPg6YCrg2IHguhaPbs2TR37ly5lvj4+BqCBIQqEMZzpCVxVK7mr4urVwSQW2+9lXr16iVVS4iKVRux8FEbOlzHCDACjIB/I5BdQHTQpEJjx5EwvxJA/PsdYu6BwJKMP+nhnf9HWWU5NoAsyvidpu19nx5ufxddnGKbXNmmIT/4NAIlJfphv6+66irCy1sEoQMH8bhCywH/6LAwERJQ0KhRo6QpFa6IGLtq1SqrwDBnzhwpfCC1BQSYNm3ayD74b+LEiTR16lSp5cDYMLnSkhJAvvnmG+revbu2yqfuvSKA/Pbbb/T2228TBJGBAwdKvw74dsBujcn3EXAmNBpdAcIx4+UP5Kk118Va8YWkzbdTF3O6Ooc/4QqfNJUM1dX11mW/pk2b1uV0Ls/1b5r5ruUBMZSSEmO+o4d64FQRL38hdz4LyMF1stPi43/Q7f88LAwEbc1cFC5FlcX02C7hE1BZQlc1v0gV85URcIrAli1baMOGDdLv5K233rIKH6ojhBIIH/CP/uSTT6wRY3/55RfZBGZhWuFD9XvkkUekAHLo0CFp1gWLI9D+/ful6RbcHXx9z+0VAQSJBnfs2EFQIf3111/y9dBDD1Hnzp2twsigQYPY9Ep9knzsmpub6zJHwcEi3v8JoaO0tFQ6Wrk8WB10jIiIkF8McA7zZYKKODzc4uiKkxxHpzm+sgb1GUA+IF8mnESp0yg4BeIz6+uE0Ob43Lrzd1qXa4wIhd+fJfCI0XlDAkrE+vRPLI2O4Uo7aOTh5FlUVCST47oyRl31wSGEcqZ157OA32lfMMeoK9zs58kpy6WHdj7rUPjQtn8+dRqdnjiI2kS01BbX2/1NN91Ex4+LQAhi4wp/208//VTut/D9cOqpp0qzHUcn4Pi+e+WVV2j58uW0efNmKXD37t2brr32Wl1/hOuvv95q/oO0CTADwqYX5kNaU/v09HTp1I2DaJjYgxfwgBP7oUOH1sDKLB9qzbNmzZIb+5kzZ9KKFSsIv+EwbwL/Kv8cJsvPz5e+F/D9AP3+++9Sg4CgSC+++CIhR92bb74pN+vPPvusbOPsPzM8w4EcBCFCa2KlnQPRYSGAIFn3HXfcIatgRXT11Vdbo8Zq2+Mef7PYF+A3Ky0tTb4XKFfaD7yXKuATyn2RvCKA4EOHDzRUTXhBCIEDEIQSRBbACyej8P6HZgTO5wCSyTcQcGczjk2y2nyWl5fLLwXfWJU+F9jMQWhyZ836I3u2FJsEJYDgxNLX+VWbel/nExtOxSu+yH2dX3yq8PeFH3UId/hc+DolJ0dQUkwQZZgIBtUyoUC8F3UvgOAHGwIIBHwIIb5M2oAu7nwWIMSczALI10fnU265sTwtFVRJHx/8iv7bcapPfDQWLFggzW+wWX3yySfl90LPnj3lXgvCyLfffiv3X4i2pCWcyiNQEDbH+A5EIKDDhw/LZwgWcHyGcKIEXPTFXu7YsWNyHkQsBaWmpsrAQkoAgdM0Ag5t375d1mPcffv20a5duyQv2Ps98MADsg7/ucKHWvO8efOk0ziEAQjjEDQwF9YMAUmldMDvJUyR1HflgQMHJGbwpwChD8aCE7oRMsszhANQs2bNHA6vtK0YW5ESRNSz/RVRsfCbhe8svOeKlACCAE8wzUJOPkTPQiQvlA0fPlw1rfdrdSwyD7OCP4iHH35YSqZ4Az7++GO65JJLrF90R44ckREJxowZQ9CYTJo0ib788ku/OdXzMFw8HCPACDACDRaB0X2MLy05upwsmcaN9+GWjICrCKzMXmOq68rstaba10VjRHGCXwC0D/AjwPX222+nvLw8mjBhgs2+ChtyaC0gfCDCEzbkiMwE4QEOz4mJifT666/TBx98oMs6tAbI7wYNxOOPP0533nmnbAeBfezYsVL4QK43CDR79+6lo0ePWhNNwwkc/IHc5QMO2hdeeKEUILBOrEFpPiAgZWVlyXkSEhLkATgENBCc0HEgDr8Ks+QKzx06dJDTQAhwRKpO8eyonSqHMIX9NQiJv7WHEUoAgYM75oYrBCJiQQN1hgjdi/ccZlu+QF4TQLSLS05OlqokCBj4w4BqDlnSO3XqJJtBffzFF1/QZZddJoURbV++ZwQYAUaAEfBvBC4YKEwQGjtfQ0BAFV1+Wo7fZER3viJu4esIpJdkmGLxWInInOljhL0U9lDK+gBafYSaHTBggNSGQGhQBHMjaCjgH4CTf5XjApoQHAijHgQfAz3Tvm7dukktAw6Nsak/88wzZfsZM2bQypUrqVWrVtKcSPn/QQCANgIaBmycP/roI9neXT5wyA3TM8wHaiNMnKC9gXYYwtDixYtluSf/c4Vn8AlsIYh99dVXNdgBxgjDC8rJybFqamo01BRAi7R06VIpeCC0sJbgbwLatGmTtC6CJgsKgNtuu01aGv38889SaIHmqL6pTgQQ7SJh8gKTK4AC27vHHnvM+keDdv5gg61dD98zAowAI8AI1I5AWAjR45cSta0RqrbahCw0qJKmDM+mLs183w+n9tVyrT8hEB0cbYrdGJPtTQ3uYuP7779f194fplSgNWuqtTxff/21LIPZlDLrlQUn/hs3bpzcxMPcCubz9gSNCvZx9rR+/XpZBNMhPZN6bIKxaX7qqadkO3f5gAbE3scBAhgEEZBRbYJsbPA/V3iGgKRM1OC/AkERGhgQzL/gioDQuiCYvEFYqY1gXvbyyy/LJhAylfM5CmA6Cg0WhD5oPaDRwmE/fEkgPEFAxHsOd4hnnnmmtmnqpM4rPiCOOIeKDx9AaEAgnSo7QW17+w+Uto7vGQFGgBFgBPwTgQSxz3tgbBb9uTOU/kqNoIOZIVRaHkBJwuSqR4tikTW8gOKjOHGff767/st1n9jutD5XZMo0SL1Fe18jZLXWIwT+ASmzHNzDHwMEX12YX+kRNrDQIqAtQsRqyZEjtZrD3t9E9YU5kDJHQpm7fMC/RI+geYHDOXxQPU2u8oykhvDZgHYCmiM49ANjmEIhESGEM1gA1eaLhTC+0GK8++67UkiB8AGHey3Bn3HdunXaIpt7+L3cc8899NxzzxHC/Na3EOJVAQR2efiQQ+DACx9Q5QikRQV/JAhFhhdnQ9ciw/eMACPACDQcBMQBH53WsUi+Gs6qeCX+jMDEpmPpw4NfCvdyY8LvJSnn+9xyW7bUj8qlwjNDmwGNAA54ETULBMdsZ7Rnz54aTfTmwuZYRXuqzdlaDQazI3f5wEm/HjnTIOj1MVLmDs9wMofvC7QXMHuDBgLamptvvllqKFR2dOWMbs8PgqMgaACyl0O79OGHH+pmQLfvp/eMIAEQQOB3AjMsPS2YXj9vlHlFAIF6CCBD7acnheKPAo4zSuhARkgmRoARYAQYAUbA3xHYmx5C24+EUnZhEEWGVkqzs67NSijYXCRif4fBb/hvF9mabmx5Jb1z4BOnPI9tNIqGJAiHJh8jHPYqYUPLmtrkK7Mc7MdgPgVnakTJUn642j7ae70xtZGxVFsINnCEhimRMidSdXpXbL7d5UNvXG+WucszBAcIIHgBf60ZGw7oQfCvsSf4jsC5H5oNCCjYW7tzUK8ENwiNevtz+/m9+ewVAeT999+XEp5iHE5OcEAaMmSIFDx69OihqvjKCDACjAAjwAj4PQLH84Lok+VxtDvNkuVYu6BEYWY2aXAudW9R96GFtXzwvT4Cd7aZQoUi2eAnh2o6CaseY5LPpGc7P6gefeqK5HN6plGIQgVSIWfhnA6fgZ07d8pyJIrWI/gSqPDkevV6ZTCvQmQp8KJHOOX/3//+J53fcfLvLT705vZEmavYwd8DUV8RgAm5OUBa4QPPCJULss+TggiyCJuL9wt4QQPiyMQN/RH5avr06dKXBL4meqQibmFfXt8JjYVC3LsEaRm2egANSWKcSdze5YZHZwQYAUaAEWAEPItAWk4QPf9D8gnho9qxXs2SmR9M0xcl0BerYqmsQpXy1VcQCAwIpIfb30mfnTKdRiUNp5gg4bAkKDIwgoYKjcf07s/T692eorDAmsKlL6zhs88+02UDSfpAyP+gqH///vIWZjx6hA0qTsnxghOzUVJCDiJR6dF3330nBRDk6QB5iw+9uVGm/IvdOfV3hWeYOUE4w/4XPtD2hFwdiEyFvbIKI4w2cFeAwz+EDyRyRLLF2oQP9ImNjSU4yiPirEq8iHItqShkKnqZtq6u770igCDWMyIpIKETpD8Ah8gHkOTwoUYcYphpOfIJqWsQeD5GgBFgBBgBRsAVBCqFvPH+0gQqLFU/p46i2ATQ79uj6PG5jWnX0VBXpuI+Xkagf9wp9Eb3Z2nNkJ9p89AltH7or/R+z1dpZFLNDN5eZsXU8BBAcDquJTg2I3kg8qwh+pIihM6FdgNmP3BC1vrlwjTouuuuk0lOcUpvZpOKsL3wJ1i4cCGpTa6aE5th5fCM6FUgb/Gh5rS/woQKhA29ikJl38bZsys8Y15lMoVM6zB9UoTATBA6UHb55ZdL7ZCqgyURolZBS4Fww8BWmbjZX/G+gaBhgbACgqM7TPMU4X2GM/yvv/4q338VjUzV18fVKyZYkydPJrwAChxvfvnlF7loqOfgTANpDy8QcoTgzYE/CPxC2rdvXx848JyMACPACDACjIBpBDbtD6dDWTXDkjoaKEf4hvxvYSLdMTqTOqdwyGFHONV3eWig8fe0vnmF/wU2suedd548JYe/ACKNQtCAs7k2VCtO45GoD6F7kQZh7ty58nAYjurIMo5cFOgHEx4zZlgIN4txkfAO0ZmwaYbm5c8//5QbaWCESE9KAPEWH47eCxURDJGo4NuCvSY2+GbIVZ6R2HH58uW0aNEimXcFSSMRFADPMM2CdmTatGlWVpCOAgf5IGR412qwrI00N9Au4f2HAz40IDCtw9qQ6wVaFORGgXkW/LJxD82YClesGabOb70igKhVQII+/fTT5QuONwAcUrcSSGATCCcpAKbiKwMUFRFAjcNXRoARYAQYAUbAFxHYcsC8WU5lVQB9+Hs8PXlhOoWF1DTZ8sV1Mk++iwC0HUhmB2FD+RPAJwT51uB7a0/IDYFNKsK6ImGdCqGLdtB64KR+8ODB9t2cPiPEK0IC33LLLTLPG3K9gXCKj8zdEE605C0+tHOoe2RvR14UaBaw6cfes7CwUFUbvrrCM1wPIBAiRwpyq7z11ltyPmg1UIZM9gjLqwhRsqAdcYVgpoX3E3x+//330icE48CHBSZkCOOrzOVcGd+TfQKEWqbevv2QhAWakBdeeMFG6KhHljyJrd+OBYcpVwl/UOoPCX/cOE3xZUJUCfxhqmghvsor1LgqRjhORLSqVV/kWUXacPVLtK7WhB9GmIqCEGYRGlpfJ/VZQHQUf/iuhJZbOV3ilFVrguBrWMNOHHH5YeKAPAhG6PWfE2nnUfNCCMaOj6ygDk1KqX/bIurVypyDOvhUdu3ufBZge96kSRMjS/XJNkaiLvka47DV14smZZZPhMSFDwE2txAc8P2FzSf+5iCAGJkDfVQI3Xbt2lFSUpJZNnTb48AZ4+K3AJoD9R2g21gUeosP+/lgfgVHeWDkrhO2Kzwj9wfyiWDvgfcI2itvEfYKEGZgjQTBENoPXyKvakAcLRQfSmhBYCsItZDRL3pH43E5I8AIMAKMACNQHwiEBLl+hodQvWv/jZCvjk1KaMoZ2RQTYSwfRX2slef0bQSwmdXTeNTGNfoMGDCgtiYu1eEg0gwv3uLDnnkIZZ4yP3KFZ0SfwqsuCAKWM/OtuuDD0Rx1IoDgFBS2bhA4IHhAYrcnhOaFDRvS0jMxAowAI8AIMAL+gECLxHLaesh9TneJ8L2vC9+Q+8/LoHA2y3IfUB6BEWAEfBoBrwggCHOmnM8hdMD53D7qAMxe4B8CoQMvqP6YGAFGgBFgBBgBf0JgQLsi+uXvKLLoQRxFwDK2oiPZITR/QzRdNLA6eo2xntyKEWAEGAH/QsArAgjUeVqnJgUJ7B7HjBkjBQ44BClfAVXPV0aAEWAEGAFGwJ8QaJZQTsO6FNIyEWJXRO8XL3eEkCr6Y4eIaNQ3j0K98uvsT8gyr84QgCkR/C59zbbfGd9czwgAAa98xWl9OuAkpbQcZ5xxBiEdPRMjwAgwAoxAw0TgcFYwITQtMoMHidQYHVsE0pBuREkWX/8GueiLBuZSblEgbdjnrpNngExUuDc9lDpxiN4G+Vnx5KL++OMPTw7HYzECdYqAVwQQJEOZNGmSFDwQ35iJEWAEGAFGoGEjUFQaQLNWxNG6vbab8OU7iT5dRjRhkAjx2aVhYgBBCw7kf6WW0Jci23lJuShwg/KK3evvxtTclRFgBBiBOkHAKwIIEtgwMQKMACPACJwcCBSXBdCrPyWdSMhX0wypXCT//XoF0b60WJp8elaDBCVAWF4N7lBEvVsX09uLEghO5RaqiYczAKLCOBKWM4y4nhFgBPwbAa8IIPaQIA4xHNER+xivlJQUevnll2WzDz/8kEaPHl1nYcnseeNnRoARYAQYAfcQmLM6VpMN3LEPxOrUcOrUNIJO62gsx4Z7XNVPb0SwumtMJq1JjaDfd0TSv+kqo7YRQaSKAgV8rZPL6od5npURYAQYgTpCwKsCCLJNPvLIIzLtuzYK1tChQ63LQ/2NN95It956K7366qvWxErWBnzDCDACjAAj4LMIZBcG0srdMLsyssEm+nlTdIMWQPBGQYgYJLQheIm8Z/TGr4m044jSiNT2VgZQpcgNvEBgNKFfnkgkV1tbrmMEGAFGwH8R8NrXGzQeyPI4Y8aMGiF4FVwlJSWEDK4I2ztt2jS67LLLfDpLruKbr4wAI8AIMAIWBLYdChMZ2aH1cKz50GJ1PD+Y0nKCtEUN+h5CxOWn5lBkqHGzqsVbo+lz4U/DxAgwAoxAQ0XAKwJIYWEhXXHFFZSTkyM1GpMnT6Z58+bRAw88YINjUFAQvfbaa9S0aVNZPmfOHJo1a5ZNG35gBBgBRoAR8F0EMgvMCxOu9PFdBJxz1ii2gu48O4PiIoQzjFOCIFcltEqRtHm/Ea2J0wG5ASPACDACPoeAVwSQxx57jHbu3CnUx4H0448/Evw8JkyYYBU0FApIRnjXXXdJ/xBoS0DPPPOMOE2DKp+JEWAEGAFGwNcRCAs2/30d6kIfX8fBGX+tkspp4oBcZ81O1Fu0SYu2IrcIEyPACDACDQ8Br/iAIPs56KGHHqKzzz7bKWrNmzene++9l2655RYpuBw8eJCQP4SJEWAEGAFGwLcRaJlkxmG6SuYGaRZf7tuL8hJ3e0R+D+NURanHQmVekBDzSibj0/h5y7g4NlXz87eQ2T9JEfC4BqS4uJi2b98u4Rw/frxhWMeNG0cBiGMoaM+ePYb7cUNGgBFgBBiB+kOgQ5NSSo42KlAEyDC1EaHmtSb1t0LPzYxkhcYpQPrWFHBOkFohw77BH1+1LoorGYGTAAGPa0D27dtndSTv3LmzYQihBWncuDGlpaVRdna24X7ckBFgBBgBRqD+EEASvksG59JbIveFhRw7o0cIR+zxffOszB4SWdM37A2nY7mWn6IUoRlBHg1cGyJFmhK8LFHFTlZhrSG+/7wmRoARqEbA4wJImzZtCL4diGyFnB99+/atnq2Wu4yMDCl8oIkZwaWWIbmKEWAEGAFGwEsIHMsNopW7LHkukIiweUI5HRYChUW3Ydk8a6eOEZF6bx6ZQ0kxFYT2s1fG0Zo9tlnT0X7+hmg6VeQJuXRQDoV4/BdKy1Hd37drXErLd0YanBiYllGYyCvC5BiB3Nxcv/MbjYmJkT6yjlfFNYxAw0fA41/vYWFhUoDYunWrjGhlVACBozoI/ZVDesOHn1fICDACjIB/IYAYIT9ujKafN0eLnBU1tR1BgZYNc8WJqLPR4VU0tFsAXTyEqLywjIpLiKYtTKS9x+EPgba2Y6BkhRBs0vOC6M7RmdJnxFsIHS5Jo5zyXEoMiacmoY28NY11XGh35q2poPwSY04dp3cutPblG30EtDnG9FtwKSPACPgiAh4XQLDIkSNHEgSQ119/nUaMGEHnnXderWv/448/6NFHH5VtkKQQ4XmZGAFGgBFgBHwPgTlrYmnJP4jOZBE07DmsqBQ2+aJu8ulZIut5KbVrlUhhoZZs4MfEfvqHDTEnhA/0tBU+LGOhrIp2HQ2jhULIObd3vqXYQ/+XVpbS52nz6Mtj31Naabp11BZhKXRVykV0W/L11jJP3yBL+mWn5tL7S2GuVlP4ssxnKe/QpISGdGIBxNPvAY/HCDACvoGAGY84wxwjlG7btm2lLwicy6dMmUKIjIW8IIoKCgpoxYoVdNNNN9Hw4cMJSQkjIiJo+vTpqglfGQFGgBFgBHwIgV1HQzXCh57wYGG2SggW36yNpciwSpkVXC2huDSAlm5zLLyodhbBpIoQhrZcJ3UGQrVvL9hNizP/oD+y/6KjJcequ9Zyly20Hddtv5emHZxpI3ygy8GSI/Tc3jfoslU3UkGF9zb+fdsU0xWnZdtpdrTCXAB1Timhm8/MsmtTy8K4ihFgBBgBP0PAKxoQ2Dd++umnUhMCwWLmzJnypbD566+/KDY2tkaG9Oeee479PxRIfGUEGAFGwMcQWGzNS+FY+FAs5xQF0dp/I+h8S55ZWbzzaAiVCw2JMQqQviIIXQtNiqJ56Qvo3UOf0rGy46pIXvvF9KJ7W95E3aI62ZSrBwgt9+9+irYW7FBFutflx1fTQ/QsvdDWopXXbeRm4ZBORULIKKVft0TRPyKTfJZI5hgeUkmtREjjUzsWUv+2xSKyk5uTcHdGgBFgBHwYAa8IIFjvkCFDpBnW1KlT6bvvvrOBoKzMNm58ly5daNq0aTRq1CibdvzACDACjAAj4DsI7Dii77fhiMOdsn11LTbaZim7wKKohwDx+L8v0vyMRbpDrMvbTJO33UXPtnuIRiUOq9FmUdbvtDZvU41yvYJfji+ji5LG0oDY3nrVHilLFs74k4Q5FhMjwAgwAicjAl4TQABm+/bt6dtvv6Vly5YR/DwQFQsvRK3o0KEDderUiXr27EmXXXYZhYRYbIRPxjeB18wIMAKMgK8jUCIiV5WUm7PazRVaEC2FiVN+s6SiQH1w5AuHwocas6yqnB7d8zy1i2hF7SPaqGJ5dSS42DTSPPxw/FevCiCaqfiWEWAEGIGTDgGvCiAKTfh44MXECDACjAAj4J8IjJi/+wAAQABJREFUhAZXUbCIcFUuZQhj9kHHRCSr4tIqccBkWXObZDP5PSx+ETBLQqSq9498bgi40qoyevPgB/Rax6ds2u8oTLV5dvaws8hce2fjcT0jwAgwAoxANQLmjrOq+/EdI8AIMAKMwEmEAHwS2oo8FvqRq/SByMwPpie+DKaSE1a3TeMrqG2jan8O/V6qNIC6NiulhKhK6WheXCni9xqkP7JX13AkR/QrM1Risn1tYyMkMczXftsaKSJ7RdHaPeFUUGJMiKttXK5jBBgBRsBfEXBLA3Lttddakwe+9tprVgfyG2+8kQ4ePOgyJgsWLHC5L3dkBBgBRoAR8A4CyEuB8LiOQ8jWnHdPWgB9tJjopjGWuksH5dLLC5KcOqOHBlfSRQNzCYLA2lxjvhtq9gqqEFGtDlPnyA6qiJqFNaGs8upIjNYKBzfNQps4qDFXvHFfGM1ZHUuZBbY/t8iXckbXAjpfZIYPsbVUMzcBt2YEGAFGwA8RsP1GNLmApUuX0t69e2Wv//73v9bev//+O+3YUXukEWtjvmEEGAFGgBHwCwT6iRCya1KL6e+D4YJfmEgZOcWvol82BtAlQy1LbJVcRjeMyKKZy+Kp1IFPSYTwFblk2H6akTWdfkr9jcxoPxSQFVW2/ib9Y3qLCFg7VbXT67D4wU7bOGsAjcecNXG6zaAVWbw1mvaKKF93js5ocFnfdRfNhYwAI8AInEDALQEEWcvxAgUGVltzactPzMMXRoARYAQYAT9HAGZY1w3Ppnd/S6DtRyzf/c6XFCAyphNt2EPUQ4TkLRN5PXq2LKHHxh+nnzZF08Z94VRYavn9iA6rIOTJ6NhxC/3nwH2UUZ7lfHidFoEUSHFBMbQxbyuVCZ+Q1KJ99GWabTRGnW7WoqahjemCRidUNtZSczepaSE0VyRtdCyoWYS31GOhNFfkTLlsMEfEMocwt2YEGAF/RsAtAWT79u26a9+0yZy6XHcQLmQEGAFGgBHwOQQQlWp0z3wTAohlCV/9SfRuXiMqrQiQOS+QB2Nk93yRlC+H8ksChS6liqLDqyi3PI8u3vIfl4UPzBYbFE0X/D1ZGGLZakGMgBkRFE7/6/Y0hQcaFbD0R0XGdyRkdE5VtHxHJJ0tMIW/CxMjwAgwAicDAtVqi5NhtbxGRoARYAQYAbcRCBERscxSWjYJ4cPSq7gskDbtD6dXf0oWJkqxFC0ypkP4AH105KsaSQYtvYz/n12R65Lw0TysKf049HM6Jba78cl0WhYKB3NkjbdoP3Qa2BRBQxRAfx+AWRsTI8AIMAInBwJuaUBODoh4lYwAI8AIMAJaBJrFl1NgQJU0rTLmB6J622sEqmjJP1EUJhzOz++bLxstyBQe6/VEjYKTZPSsOcfmU1lpGbUJb0E9o7tSUIA5L/GM/CCD2o/qhaaLkMVMjAAj4F0EKisrbVwGNm7cKJNlt2zZkq677jrr5C+88AIVFxfTlClTqHnz5tZyd24KCgpkTjzMibG7du1KF1xwAYWHOz58QA49++TdWh5iY2Opf//+2iK/ufeKAHLllVfKTOiTJk2i+Ph4vwGDGWUEGAFGgBFwjkBEaBWd0qqYNuyLcN641hYQSKpo4d/RNLBdEUVF51JaaXqtPRxVRgSGU1FlsaNqQ+UbC7bSuOVX2bRtHJJMd7S4jsYmj5LlyCeytWA75VcUEuoGxvahxBDb3zmNS6TNWLU9BNnLZrU15jpGgBEwhQAEj3feeYe2bdtGb7zxhrUvhIEnnniCTjvtNBsB5Pnnn6fs7Gw655xzPCKAQJC45ppr6N9//7XOjZvGjRvT559/TmeddZZNOR6QtBs59KqqHGucBwwYQKtXr67R1x8KvCKArF27VgJ677330vjx4wnhegGu1lHdH8BhHhkBRoARYAT0ERjfL4/+ORwmcny4a8krvD/E7+vK3ZE0/JTj+pPVUto1siPd1WIK3bbz4VpauV51rOw4Pfbvi/TuoU8Jpl35FQU2g8Hh/YLkMXRvqxspOihK1jWKKTedtDFFaJWY6heBIpEqZtWuUNp2KJhyCwMpKrySOqZU0GkdSyk20vEmsH655tmNIPDSSy/Rgw8+SFdccYVN86CgIAoNDRXJUk9kS7Wp9cwD9sQjRoygiooK6tOnD91xxx3UokULWrZsGYGviy++WAoRHTt2tJkQ/tQQPqKioqS2xKbyxAO0KP5KXhFAIiIsp2JQMX3xxRfyBfXW1VdfTZMnT6YOHTr4K17MNyPACDACjIBAoFFsBd18Zha9JyJiFUkhBBs0dYyvvTcG1x4RDWp8cDxFBkZQYWWRsU6i1QARXjet9Ljw+TjhYGK4p7mGB0uP6HaoFI7u3xxfQJvyt9DMrq9RfHAshYpf1l5CQ7R+rxENUZUwQasSkcHc097oMseFhhHYuDeYZi6JpPxiW4F6/b9E364Op0lDimh4N3PJLA1Pzg29jkBJiX4i06uuuorw8hZB6EBuPFxxED9//nxr9NhRo0bRGWecQbief/75tGrVKoqLqw7bDe0MCFqYr7/+2lss1tu4tn9pHmIDIAIsAKqkygMHDtCzzz4rwit2pGHDhtGHH35I+fkWm18PTcvDMAKMACPACNQhAohk9cgF6XRqh0K5iVZTBwo5JED4iJih4rIA0SeAzObfmJv+I/1370tmpvJK2z3F++mxPS9ax0aCwdAgZ1GtLILaub3zKTLMHF7WifjGbQTW/xtM036KqiF8qIFLhHLqo2WRtOhvBBZgYgSMI7BlyxbasGGDtAB66623rMKHGgFCCfbKiCr7ySefqGJ5RT+Qv/p4SOZr+c8rAgjygFx00UXSsefw4cPS3m7gwIFWNmALB2efpk2bSo0I1FC12bhZO/INI8AIMAKMgE8hkBhdSVcNzaGXJqXRExceE/k90unly9MoOdqcRiIu0tJ+SrMrKEj8M0oFlYVGm3q93fKcv2TuEUzUWGiIpozIFlnOlWChrlo2AmhIp0Ia1cPWrEvbgu+9i0CBiFg287dIJ0EDLL5Ks/+MoKPZXtk2ubTIm266iSZOnEhwbv7222/lPUx7cNALi5OtW7c6HBcWKjgUVj4O3bt3l+ZJixYt0u1z/fXXy/FLS0vpsccek5YsOLl/7733bNqnp6fT+++/T5dffjnB8qVTp040YcIEWr58uU079WCWD7VmaDRw2H3DDTcQeG/Tpo2c5/vvv1dDyysOuoERrHFASJSN5wceeEA+L1myRD4/8sgj8tnIf2Z4/ueff+SQ4M/exErNNXjwYHlrj73SgPTr1081bVDXALHx1/tW9MoikR39s88+k6+9e/fazNGuXTspjMBJp1WrVjZ1/FC3CBw5om9qYIQLRHNISEiQTQsLCyknJ8dIt3prgyAJwcHBdPy4edvzumQ6MjLSqprFF2peXl5dTm96rsTERNknMzPTdN+67BAdHU0xMTFySjj84Yfc10l9Fo4ePerTBzezV8bSHzssPhFGML2wfy6ddWIj/l36z/Tk3lfFprDOfp6MsGiozdVNL6Z7Wt5obXs4K5i+WRtD/xwKs9nkwk8Emo9B7Y2bm1kHFTdwXoX9OsidzwJ8M5s0aSLH8cf/4CjsDv20IYy+WmXEVM4yy5ndS+iqYa69Z4pPRC7yhE8sNvgHDx6UTtRPPvkkwfy9Z8+ehL0WcMF3219//VXDfwCn8pdeeilhcwytY+vWrWV79MHzXXfdRa+88ooNj/iMHDt2jB5++GH6v//7P7UUGcUJwg8I3/dDhgyRp/l4xrjYT0BoASGylNr449kVPtSaZ82aJQ+yIQzge1xrUfP000/To48+iikoKyuLkpKSbL4rsca+ffsSfDM++ugj6acMJ/Q///xT9sF/2McAD+CnPUA3y/Prr79O99xzDw0dOlRGwLJOoLl5++236dZbbyXsg1NTU2UNIl9hXcAO+xPwAX6xr+rVqxedeeaZ8hBfM4zf3dapKN+5c2fCB2PPnj3S+QaAqy8+lD3++OPUtm1bvwORGWYEGAFGgBGwReDMbgUyVK+RXBiRoZXC0bdak4Es5NM6PkPIy+FvtL/4oA3LzRLK6bZRWfTCZWl099kZdNtZmfT4+GP05MR0l4UPmwn4wS0Eth4UDjsmyGx7E0O73PSJJ56Qp/jQPkArgOvtt98uD6qgfcDhiiJsbOH0DOED2g+YxyMyE4SHn376iXB4hE3zBx98oLrYXF988UU699xzCQIA9mx33nmnrC8qKqKxY8dK4ePss88mWL/goBnCMfZ9IDiBgz+Qu3wg2uqFF15I+/btk+vEGmDKBIKABMEDBEECEbAgoIHghI5nbObNkis8K5/n3bt3O5xO1Sme0RDRuiB8QKiEsHHeeefRf//7XynEYQ3YT8OVwZ+pTgUQBZS08xV+IG+++SZ98803MvyZqsMHg4kRYAQYAUbAvxFoEldBEwdg4xNQ60KQAf3q07Nr+EAMjR9I3/T4kN7q9Dzd3vw6mtR4PJ2TeCa1CWtZ63jOKqMCIykltDF1jGhLZ8Sf6qy56fpABzlDkGixk/CZ6d6ihJrGmzNPM80EdzCMQI6IdmWGsgvMtTcztqttYeYEEyNoR0HQ6iPULEK0QhsCoUER9l3wN+jSpQvNmzfPGmIW+7IxY8bIfRnawiRJK7io/t26dZPmXkizgE09NsegGTNm0MqVK6UFC8ygUlJSZDkEAGgjoGGAwQ00DiB3+YAWAD4TymKmjTBxmj17ttywQxhavHixnMeT/7nCM/gEthDEvvrqqxrsAGOE4QXBYkQZJSn/D6wFGhBEzoIFEaJmIZIW+sGVQeFZY2A/KKiXvyTELIaKD6o0fChXrFhhherUUz3/g2AdnG8YAUaAEWAE6gyBEd0K6abR5RQeoj9ldHgF3XJWFvVqqR+hJiQwmAaJPBtlVWU0N30B/ZT5G+0tOaA/mIHSK5pcSL/1+ZoWnPI5fdXjPXq1w5PUIsyyUTLQ3VCTduFsQmwIKB9phJw2ZsgXgwXcf//9VnM87VqwzwKtWbPGWqyiKSEyk14CvHHjxslNPMytYPZjT9CoqOBC2rr169fLR2yUEdbWnj7++GNaunQpPfXUU7LKXT6gAVEmiGouCGAQREBabYIs8MB/rvAMAQlYg+C/AkFRHbRDe4NEhMqMEGZ5EFZAMLXCWiDAYM88bdo0qb2577775DN8bEBIdwGNlz+SOd2jGyuEiglSHl67du2yGQmSsgrRC6mciRFgBBgBRqBhIDCyVxUNFl/ry7YQbUotpnzh9Bsr8itAGzBAJB8MD3G8AcRp4CN7nqefM5d4BIx+MadQaGD15gg/9ne1uIHuT7VsijwxyejEMzwxDI9RRwi0b1pOu44a3wq1byJCYvkYnXLKKbocwUwHpJyZca/2XwgGBPMrPYLWAifvaAtHcy05cqRWczjKSwFTJGWOhPHc5QP+JXqE/STMl8rLPf8+ucozkhpCiIBWA5ojOPQD40OHDklfLghnl112mdXPE+u65ZZb5EtvjUrD9d1330lBC9oe9Pc3Mv5X58LKoDb68ssvpdpI2f2pYSBBQ9KGCglqP3tJVrXjKyPACDACjIB/IxAvfNEvGER0attcGQ/f6GrmpM/3mPCBOZdmr6ARCafZTH9W4ul0U9FV9O7hT23KXXk4P/ls6hjZ1pWu3KeeEBjWpZQWbhIBAqQcbDl91mcFDQJ8MhcIrEn0CJFGQdBmQCOAfZYKuALzd2cE31x70psLOS5UtKdmzZrZd6nxDPMhd/lQgU7sB1caBPtyd5/d4RnBbrAHhi8MzN5gFgdtzc033yw1GCo7OtoZJay/R48eUksFx3h/JK8IIIiIgDBsCxcurCGFQp0EoQNONMnJyf6IGfPMCDACjAAj4GUEoP2YcdhiG+2pqVbnrqcfjy+i0+MHUWywJfoZxr65+dXULqIVPZz6vMsJDZEQ8aHWd3iKVR6njhBISaik8/qU0Pz14WJGi5BRc2pL+WCREb1HS8+frNecz1wJoiIqYUPbU23ysVnFiTu0Ajj8hTP1p59+KkPkatvb3+uNqRe9C4INsnXDlEiZE9mPpX3G5ttdPrTj1cW9uzzDLA0CCF7AH+tX9Ntvv8lb+NeYISWEIRKYP5JXBBBEOoCEpwggQe0EwQOhz5gYAUaAEWAEGIHaENheuJvSyzJqa2K67mhpOj367wsy2/qNza4khMxVJ6YhASEuCR+xQTFynGtSLqFgBw7ophnlDnWKwISBxYRkg79uhhCiJSWQBNCA9qV03RnVkdq0rer7fv/+/bo5JlS6A7XvgukOIo3u3LlTsqwNL6tdA3JsIJ+bGYJ5FSJLgRc9win///73P+n8jpN/b/GhN7cnylzFDv4eCEUMP43evXtLVrTCBwp++OEHWY5QvYrgvwPXhdtuu01GHVPl2quKnuWvrgtec0KHlIxQbDDBQjg2RA9QfwRaAPmeEWAEGAFGgBGwR+BIaZp9kceeCyuL6PWDM+jpva9Zx9yY7zhpm7WR3Q1CBS8WTu3XN5vEwocdNv70GCgsry4fUkwPXpBH/dqK0KciLDQoTBzR9mhZRneOyadbRxdSiFeObN1HCtGR9GjmzJmyWJvITmXVdhTCFZtaHBrjhbC8Rknt7xCJSo/grwABROUM8RYfenOjTJn5u+Mb4grP0E5AOEPkKjjh2xPyuPz8888y54oKI4w2EB4XLFhA8A/RI+QsgU8K1jVMRJX1R/KKAPKf//xHxmYGqJdccolpSdofgWSeGQFGgBFgBDyHQFiguRNYV2b+5vhP9MPxX2XX3HLzyT2biTwlrPVwBXnf7NO5WQXdPqaQ3ro+l2bcmE3v3JBDU8cWUJ+2vmd2pUUQAsiPP/6oLZIb1/nz51OjRo1k9CVVidC50G7A7OeZZ56xhn1FPUyDYKmCCEw4pVchdlXf2q4I24uoWjC9/+ijj2yawikcc4EQvQrkLT7k4Dr/wYQKBO2PikKl06zWIld4xrwjRoyQ4yLzPPxlFCH3CoQOlCGqlVaToXBC6N45c+aoLvIK35wpU6bIezi0IwyzP5JX5Plrr73WH7FgnhkBRoARYAR8BAHk6agLevfwJzQueRQlhSSani45JMF0H0cdkDF9V1oo5RcHUrSIEtaxSSkhiSFT/SAQHFQ/87oyK/wvsJFFsjpEoVq3bp3MgwFBA87mMHdShNN4JOpD6N7HHnuM5s6dS8OHD5eO6jhxRy4K9EO4WDNmWAg3i3GnTp0qM4sjRwc0LzipR34QECI1qY21t/hQ67S/qohgiEQF35b27dtb+bJv6+jZVZ6R2HH58uW0aNEimXdl4sSJMigAnmGaBe0IwuxqCckiIVxAi4V7JH9Eu71CMwKTLTjFQ7BBhC1/Ja8IIPZgwB8EtoFQF+GFMGkvv/yybAY14OjRo63JcOz78jMjwAgwAozAyYdA49BkGhzbl1YJx3Fv0qGSo5RatJcGxvammUdmGZ6qU0Q7iguONdzeUcO0nCCatTJOhIKtqfGJCBGCSNNSYRZURH3bFFOQV2wWHHHG5f6CAMx0kOIAwobyJ0C43FdeeYWGDBlSYxnIHQH/D/gXbNq0ySZML7QeOKkfPHhwjX7OCu655x5CSGCEkF2yZIl8oU90dDQ9/PDDUjjRjuEtPrRzqHts4OFXgQBJ2PTDQR+aHrPkCs/QUCBULnKkILfKW2+9JaeFxghlTzzxhAwSYM/Le++9J5NJQlCEcIgXCFotCJAQ+OCb4q8UICKNwMvKK4Q3GWo5SHBalRccbRCDGoSQbWh366230quvvmq10/MKQ04GRag6R3GxVVdIwHFxcerResWHGWHW4O+CNSE8GuJUKwdHa0O7GyQIgkqwtFRkyO3eXb5wmuGMXO3nbFzUw2HKVcIfFKJtgPDHjdMUXyaEvcMfsIoW4qu8Qo2rPnf5+fmEqCe+TCo6B1TMvkz4YYyJsURDwolSQUGBL7MreVOfBWTW9eLXt8dwQLRD5XSJ71itCYKzSXYW7qGr/rmDSqtKnTUVWc1PozW5G6mg0vymAr4cQ+MG0uX/3EpwfjdCT7d9gMYKzYk7tD8jmP73cxIVlUGyUA7P+iM2iimnKWdkUcski1akcePG1t9Ldz4L8Nds0qSJ/qR+UGok6pKvLSM2Nlba/LvLF0LiwocAm1sIDvj+Qj4O/M1BANGLWGU/J/qoELrt2rWjpKQk+yYuPSPsL8bFbwH2Teo7wNFg3uLDfj7sReEoD4zw/e8OucIzcn/gIB57D7xHRvZ7+J4Hz3DkhzbLUQ4Ud9ZSH329JjpB43HWWWfVugFFpAX1xQn1EzbvUPspZ6G6BgS2dnCar41efPFFss/WDvu8d955h7AeLSHLO7J+6qkxseGFcKb+8FU/bOBx+uAoOoWr/dT4fGUEGAFGwF8Q6BTZjl7q8Bj9J/UZKq60/X5VawikQHqkzV10YaNzqayyjN469BF9dPQrVW3oGhoYIg+LnunwIF299Q4qrCiqtd/IhKF0XtJZtbZxVlkq5Ih3f0s8IXygdUCtXdLzgumVn5LovnMzqEUim2bVCtZJWonNrJ7GozY40GfAgAG1NXGpDgeRZnjxFh/2zEMoQ4ZxT5ArPDdv3ty0xQ8OsiF0NBTBQ2HvFYUuTr6R5wOn3xAmJk+eLJOvPPDAA2peeUXda6+9Zo1fjY38rFnGVeA2g3ngAVIpqEWLFgR7Qb0XPnBagsMVIjtAgwEnIpiWQQ0JLciKFSvovvvuq3HiB0EF5RA+IAFDNfnCCy/Q2LFjCRET4MRvn7gRc7raT8sv3zMCjAAj4E8IDIsfTF90f4fOFhnGwwJCrawHUZDQWgyiz7q9KYUPVIQIQWKI0GSYoQCx8e9wwt8EAs83Qz6iFuGOk6lB0Hmu3cNOtdvOePhzZyRlFZhzNCgtD6SP/4inSq/ZLTjjmusZAUaAEfAMAl7RgMBeDWZFkDQRmQHheEFwntESTF9gk3fRRRdJZxoIAIiUACclZ6ZL2nE8da8EENjVaZ22HI0PoUPZ8kGg0IZQQ1g0xLqGOhQOWNr4zt9//z2lpqYS1KcIT6yiM0BjAv+YGTNmEGz/7G0wXe3niH8uZwQYAUbAHxBoHd6Cnm//CJVUltJh4bNRKf6lhDahyKCIGuz3ielBzUKb0uHSozXq9AoGx/YTDujVzuSnxHenBf0/p3kH59MfOX/RkZJjFBEUTp0jO9C4pFHUJaqD3jCmyzbtt885YWyIQ1khtO1QGDX1X6spYwvlVowAI9CgEfCKBgRaAdBDDz1kFT5qQxEqKTj2gCC4wKaxriktLU3a1cMECtEcjBBiOsPGHTbk55xzjk0X2BeOGzdOls2bN8+mDlEnQKhXwodqcOmll1JERIS0EdyyZYsqlldX+9kMwg+MACPACPgpAmGBodRWZCxvH9FGV/jAsoJEMsD7Wt1iaIWhQqNyT8sba7SFSdYFjcbQyx3+S593n07vd3mF7hdjekr4wIQwqXKVth+u1gS5Ogb3838EYEoE/wrsGZgYAX9DwOMCCEyItm/fLnEYP368YTywGVdaD8Q4rmtS2g+YRBn1Qdm8ebNkE6HQ9Bys4AMDgsM4HFxBEFjghAQaNaqmAyP8RU4//XRZD8cyRa72U/35yggwAoyAvyCAqFRfpn1P7xz6RFy/o12F/5pifUTCaXRfy1uEcZVjvwqYc70gtCodI9uaGttTjYMCXbejyikyZ7rlKZ55HN9CAMF8sHex90v1LS6ZG0ZAHwHXj2D0x5MJCFWUExV32UFTm2JoQRDVA5qI+ohqoQQQ8IxILYhdDUEBmgyUIf6yPSlBy5HGBGuCMAM8EL0A4elUH2g+MLYeqfG0gpir/fTGR6ZTR+HnwBeiM7hK2pBwMMHTE8xcHdsb/SD04uXrfGqFYn/BFe+XP+EKjH2dX2CqPgvavzWU+yqpgyXwB57x+XVE+4sO0pN7XqW/cmqG3u0X24v+224qtYts7ai7TfnklpdSr7hu9Ob+mSI61iYRY8qy4Q8JCKEzEk6lO1pdX2MsxVtdfBZaJFbQcRe1IFHCekuLKz63/hARzeYN4gdGgBE4qRHwuAAClSB+ZJDuHpv6vn37GgI4IyNDCh9obEZwMTS4gUZKAEGSmu+++05mBNV2GzRokHQOR/xlRQgzB1LhUVW59grzLAhUCDUMUn1q2+SrsKCqjzv95KR2/yF+tH30LdUESYy+/fZb9ejWFeZsePkDORIGfZF3CIn2pnu+yCd48idcEWDCPsiEr+Lqb9gqHFV4ZvWsvW7N2U6T1txCOWX6IabX5W6mK7bcRl+dOoP6JPTUdnV4Pzp5BI1uN4KyS3NoX+FBmbW8TVQrigq2ZEV21BHfwep72FEbd8tH9ibauM+1UU5pHyEEueq+7oRORfZrJkaAEWAE6hoBzVeYZ6aGCZESIMxEtEJCQhD6wwyqrkkJIHAOh9CEBD0IkzthwgQpUCF5DBzmtaF2lRbBmQCCtcA0DaT6IA64I1J1qo87/RzNweWMACPACPgKAiUVpXTtmrsdCh+Kz7zyfLpOtCssrz1MrmqvrvGhcQTn8u5xXRwKH7lC8DlafIzKK+smxO2QruKwrbni0Pg1Vpj7D+5kvD23ZAQYAUbAFxHwuAYEixw5ciRt3bqVkH4e/hHnnXderWuHHeOjjz4q2yBalDIxqLWTBysRzQqbfiSVueaaawiO4IrGjBkj+UeiRCQp/OSTT+iGG26Q1erkqLbTaOUcptpiLpCZPmjvaj/0tSckPHQ0P6J/aYUs+77OnrXmQTA9gybMlwnaOpgyqPfHV3nF34QyuQGmyszRV/lVpkyMq+ffIfVZwHeCP5jd4LOgTJscfbd8dmAO7RcaCiN0pDiNPkydTVPaXGGkea1tCsoLacbez2jO4R/oQNFh2RaO7sOST6Xb2l5LfeKNaVpqnaSWynvGEj0zJ4QOZuAsECZijn1WVP3kEWUi80mleO9DrWZYjnCtZWprFRKzqb9XayHfMAKMACPgZQS8IoAglO4PP/wg/R7gXH7dddfRxRdfbJOUEJv9TZs20ccffyzDzuKHFJv16dOne3nJNYcPDQ2V2dpr1lhKoNG55JJL6LPPPqMlS5ZYBRCYEyBrODJTOyJVpzb8SlWuyvX6qTrVB21c7ac3Pt6f2shTmdDxo+gvmdB9PWM3PgtK0wbNGGdCr+0TbLxOmwkd2kl8L/k6qc8CPrP+IIDADE8JIPg+0BOe5x/81RTsPx76lS6MPcdUH/vG+4sP0R07H6H9JZagIKoeoX5/PbZMvu5ocT1dl3KZqvLK9d4xAfTzpmhatj2SSsq1AoitQBIoqi4ZlENdGheKYCYkfSbVYR1Me139LOC9UQdlXlkgD8oIMAKMgA4CXhFAYDv76aefSk0INqEzZ8602eDDnAkaB5y8aOm5556zmm9py33hHg7kEEDgmI41wVQMP6zYrKsIV3p8qo0iNjogZRNfWx9Vp/q4009Oyv8xAowAI+DDCBwssWgfjLJ4wGR7+3HzKwro9p0Pk7Nx3jg4k5KC42VIXvsxPPUcHlJF4/vn0bi+ebQ/I4TW7gmnnUfDKC1H+FKKjIOxEZXUvXkJjeqRT03jKzw1LY/DCDACjEC9IuAVAQQrGjJkiDTDmjp1qnTq1q7S3iyjS5cuNG3aNN2wtNp+9Xmv/DIgNKkTPGfCBNoqAQQRvkBKk6GEDL012fdxp5/e+FzGCDACjIAvIRASYO6nCJGs3KGPjnzlVPhQ47964F0amXg6RQdFqSKvXIOEFVbbRmXyRWRxxK8QZ3QoZ2IEGAFGoKEhYO5b3+Tq27dvLyMqLVu2jFS8ajh7Y/ON5DmdOnWinj170mWXXVavNqiIfPXNN99Ie9onn3xSd5UqdweEDmUahazlIPi76JEqh7ZEZVZv0qSJ9HGBuQdC86pybf+///5bPnbr1s1a7Go/6wB8wwgwAoyABxDIyAuiHUdDKbcokKLCqqh941JqluCerxcSC+4p3m+Yu/YRrQ23tW8IU6Xvj1uS5drX6T3nVuTT0qwVNDZ5lF61V8tY+HAOr7ejlTnnwHwLbQhl8725ByPQMBDwqgCiIBo+fDjh5auE0Jvw7QBde+21hFDC9rRgwQJZ1K9fP2vVueeeS4j0hZwhECiUYKIa/Pqrxa4ZfZQDMdrAMX/RokXypRzaVR/Yda9fb4mBP2DAAFUsx3aln3UAvmEEGAFGwA0EsgsD6ctVcbRpf83Q2hBCJp2a47Igck7SmfRr1u+GuUN7Vym9LIPwMkP/FOysFwHEDI8na1vlB3Oyrp/XzQj4KwI+p9z9/PPP6xxLhP1VQsfzzz9vDZULRnBaBt+PtWvXSi3N9ddfb+WvdevWdNppp8kIVa+++qrVNAsN1q1bRz/99JNsCw2PltTzvHnzbLQnME176aWXpG9M7969CaZpWnK1n3YMvmcEGAFGwCwCx4XW44Ufkk8IH3CO1lIVpR4LpZd+TKLUNNdMo0YkDKF+Mb20gzq87xXVlc5OPMNhvbOKokpLSHRn7bT1BZXmwv5q+/I9I8AIMAKMQE0E6kQDUnPamiV79+6lW265hX7++We64gr3wyvWnMFxCdShTz/9NN14441SILj88stp2LBh0tF848aNMns5ImU9+OCDpMyu1GiI8IVoXgsXLiRkGIfWAo7pK1eulILJhRdeWCOLOqJqjR49mn755Re6++67pRCDBIerVq2SmeThb4Jkgfbkaj/7cfiZEWAEGAGjCAg/aHr3twTKKQo60UUbqQlFlueS8kB6b0kCPXFhOkWE2gspzmd7sf1jdMuOB2lnUarDxu3CW9PLHf5LgQGun501CkkSHAdYM6M7nExT0TS0keaJbxkBRoARYATcRSBAnPCb/6WwmxVDYAP+0Ucf0Y4dO6TWoEePHnTBBRfI8Lt2zW0e4agNB3TkAVEhMD3Aks0cRh/g5/HGG29IkyrVB+pd+KtAIFAJFlWduiI/yFNPPSUFFVUGUysIMldddZU1BKWqwxVrRKQwaFeKiqpP1xBtC0IJ5tQjV/vpjeWozFNheGGW5i9heI8fP+4IDp8ox+dJheFFmGYVqMAnmNNhQmW89vXwxtowvPBNU99BOkvymSL1WTh69KjLoVfNLGbtv+H0wbIEw13G9cmjc06pDk0OvzmVZ+LYsWM2mmL7QYsqimnmkdn01bHvKU/4XiiKDoqkiY3G0g3NrqAoce8uXb/tXlqfb/G1MzLWR13/R6dEV/vkGenj7TYIbKLMj9z5LCAML3wMmRgBRoARqEsE3BZA8KMN0yBlbmTPPPwkZs+eLcPu2tdt3ryZpkyZQmvWrLGpqi8BRDGBjTOECiR8gyAAJ3IjhI0hMqnDp6Rly5aG+mGtmCsjI4OaN28uY7sbmcvVfkbGZgHECEp120ZtOjErCyCew54FEOdYzlwaT+v2ivTbBqllYhk9dH61QG9GAFFTlFdV0K7CPZRVnk3xwXHUMaIdhQR6TmH/Z84aGYZXzVfbFaZh73d5pUaTdXmb6eeMJZRatJcqBL8tw5vTiPjT6MyEodYEgTU6ebCABRAPgslDMQKMQJ0j4PY3em3CB1YD522c6H/wwQc2i0PCQZRrM2XDD+Ptt9+2aVcfD9jsOdJ21MYPNjPQYJghmH+1atVKvuqin5k5uC0jwAgwAul55n4m0oW/iLsUHBBEXaM6ujuMw/5D4gbQFU0upM/T5jlsg4qk4AR6uu1/bNogh8hje16kpdkrbMo3F2yjHzMWUdfIjsJM7HFqFtbUpp4fGAFGgBFgBKoRcN2QVoyByFFK8wE1LsyUkGQQvgwwqVImIx9++KE1yhQcrW+++Wa6/fbbrcIH1Mj33nsvbdmyhcaMGVPNHd8xAowAI8AI1CsCgQHmrHSRsdsf6L5Wt9DdLW6gsIBQXXZ7R/egT7q9QSlhlhxOaFQqsqTfuuOhGsKHdoBthbto8ra7Kb3UXKQt7Rh8zwgwAoxAQ0fA3NGWHRpwolYEP47bbrtNPdKgQYOof//+NH78eFk2d+5cGjp0KJ199tlWYQQViPb0/vvvkza8rXUQvmEEGAFGgBGoVwRS4stp73H9TboeY2jvL3RNyiUyvO6vmctoW+FuKq4soQ4JbWlQVB/qFda1xjI+PPIl/S00Hc4IYX6f3/8mvSIc5pkYAUaAEWAEaiLglgCi8lXA3wERpOwJTuhXXnmldLRG3guEqlX5NhBVClqShx56yJojw74/PzMCjAAjwAjUDQKZ+YGUXxJI0eGVlBglUnCfoP7timjlbjh+QxPiXL2B9v5ESSEJdFkTy0EZtPHwrcjOzrYJDoL1wC9lVto3hpf2W9ZyOlxylE2xDCPGDRkBRuBkQsAtASQrK0tiBS2GinJiD97IkSOlAILoWE888YSsRgb0L774okZ4Wvu+/MwIMAKMACPgPQTKK4iWbouipdsjKTO/+ucgLLiSkqIrqEOTUurRsoS6NS+mfw7VTEBoz1nTuDIa0rHQvrhBPO8QGpLcijxTa1mdu5HGN2KzYlOgcWNGgBE4KRCo/sVxYbkqxCqcqB1Rs2bNrFXFxcXS5Grx4sWkwnRaK/mGEWAEGAFGoM4QKCwJoLcWJdKe9JrmVcjpcTgbrxD6fUcUNY8voxTxOiKea2pCLJqRxKhyumVkFgW774NeZxiYmSizLNtMc9n2eFmm6T6OOiBg/oHMYMoQgmJoUBUFi8BkjeIdteZyRoARYAR8GwG3BJDS0lK5uogIxyEaY2JirAgg1jhMsVj4sELCN4wAI8AI1AsCM0VuDz3hQ4+ZQ0LwiAippGGdC2jNnggqKqs2xQoRAsfgDgWE/B/R4RBGGibFBEWbXlhscPXvn+nOooNIkyXeoxBaviOS/j4YTkWlmrgxi6qoVxuiyWcSOf4FdmVW7sMIMAKMgPcRcEsAMcIewswqgp9IUlKSeuQrI8AIMAKMQD0gsHl/GG07jPxGxvw6wGJRWSDtywihFyel0QFxzS0OpMjQSmqVVEahXv8lqQeQ7KbsHNleRswqqbIcvNlV6z66k7xwzZ5wmrcmVpOBvuYUm/cS/edjouvPCKNeLYtrNuASRoARYAR8FAHNcYr3Oezevbv3J+EZGAFGgBFgBGpFYFWqOjOvPiCqtcOJyn0iGtbutFBq06hMbHhFxKgmJ4fwgeVHBIXLiFlGcEKbnlFdCUKLK/Tduhj68PeEWoUPFRCgTPjxIFlkWk4DtX1zBUDuwwgwAj6PQJ0KIFpzLJ9HhhlkBBgBRqCBInAoE74crtE/h6A5OTnptubXUkpodV4QRyggt8gjbe5yVF1r+fq94bTwb5h7GTdnK6sIoB82uGfuVStTXMkIMAKMgIcRqFMBRGuO5eF18HCMACPACDACBhEoFRtWVym78OQ9aU8IiaO3O79ArcNbOIQvLiiG3uz0f25pPyyDm3mPqmjz/nAq9Z8ULA7x4wpGgBE4ORA4CSx3T443klfJCDACjIBRBBBiN8dFQSJcOKOfzATh46vu79LXx+bTz5lLKLVoL1WIHCEtwprRmQlD6MqmEykuONYliA6KKFfpea78LAdQuXhbECHLnxJBugQSd2IEGIEGgYAr33Q1Fr5nzx768ccfa5SjYPv27dby1atXi6gezn+8zjvvPGsfvmEEGAFGgBHwLAI9WxTTnmM1w+8amaV1cpmRZg26TWhgKF3R9EL58uRCj+W695Ncadxqy5Ns81iMACPACJhGwL1vuxPTzZs3j/ByRioRobN2VQh4zsQIMAKMACPgFQSGdSmkxVujROZzs+ZUVfT9+hjaIPwUBnUoon5tikkT6NArvJ5Mg5oxurLFpYoCRWdotpgYAUaAEfAHBOrUB8QfAGEeGQFGgBFo6AhEhFaJ0K3ZFBxo9rAngHKLgmiryIr+gcgj8vrCRMovdn3b3NBxNru+pvGuOnEEUJdmJRQeYvb9NMsht2cEGAFGwDMIuKUBufzyy+n48eOe4YRHYQQYAUaAEagzBDqnlNK952TQp3/Gnchwrjc1NrSOBIwq2nU0jKaLbOoYBwkJmdxDAP4b1RnnjY8VGFAlEkHmG+/ALRkBRoARqGcE3BJAnn322Xpmn6dnBBgBRoARcBUB5PN45ILjQpAIpe2HQ2mnECjSc4M0plmOhA/MaKlDbpAl/0TR6J4FrrJh0y+vPJ/CA8MoJND1UME2A/rZw4X984RQl3CC69rwtzRBi0mn5hL75vjZG83sMgInOQJuCSAnOXa8fEaAEWAE/B4B+A5AG4IXkeUUffP+UHrntyTDa1u23T0BZHvBbvrgyBf0Z85qKqwskvN2iGhLFySfTZc0Hkdw+j5ZqHuLEprQL4++EckInVGzRKIpo4hSIouIXSedocX1jAAj4EsIsADiS+8G88IIMAKMgA8gsFdoNcxQVkEQZeYHUmK08yiH9uN+enQOvXbgPZF2z9Z/YXfRv/TKgXfoh+O/0LROz1CT0Eb2XRvs8yihTUpJKKdv1sbUMI+LCqug3q2L6byB4dSlRZAMAnD0aIOFghfGCDACDRQBFkAa6BvLy2IEGAFGwFUECkrMxydBH7MCyPdCuHj1wLu1srmzaA/dvvMR+qTrNIoICq+1bUOq7CE0IXgdzgqmtJxgKZ41ji2nFokWR/XGjcM5AllDesN5LYzASYaA+V+ZkwwgXi4jwAgwAicbAjHh5jUZMRHm+uSVF9Ar+982BC20IZ+nOQ/1bmgwP2vUTGhC+ohwx33FSwkffrYEZpcRYAQYgRoIsABSAxIuYAQYAUbg5Eagk/QHMY4BTubjI80JIEuyl1NuhfHITd8e/8k4Q9ySEWAEGAFGwKcRYAHEp98eZo4RYAQYgbpHoGOTUmqZaCTjucVv48xu5iNgbcnfYWphh0qOUnZ5rqk+3JgRYAQYAUbANxFgHxDffF+YK0aAEWAE6g0BZDe/amg2vfxjEpVWODqnsuQI6SoS4A3tVFiD18KKIulAvm7f33Ss5DjFhERRl9AONDZpFLUOb0EFlTX71BjErqCgooDig2PtSvmREWAEGAFGwN8QYAHE394x5pcRYAQYgTpAAP4Gd4/JpBlLEwhRrmpSAPVrW0RXDcmmQDsZZWXOOnpkz3OUVZ5j0205raYPD39B16VMosYhxsP8YpBA8S8pRMSdZWIEGAFGgBHwewRcFkCqRNDxl156ibp3705Dhgyh+Ph4vweDF8AIMAKMACNQjQASFT4x4Rit3B1JWw6GUUZ+kMh4XiWdoQd3KKQOTWqaaa3O3SCiVj1MleKfHlWI8hlHPqfTYgfoVTss6xPTQyYodNiAKxgBRoARYAT8BgGXBZD09HT6z3/+Ixf63Xff0fnnn29d9OzZsykrK4smTJhAKSkp1nK+YQQYAUaAEfAvBELEr8SwLoXy5Yzz4soSenTPCw6FD23/FblrtI9O769NucxpG27ACDACjAAj4B8IuCyAHDx40LrC8HDb2OxPPvkk7dixg3r06MECiBUlvmEEGAFGoGEj8EvmUkovy/D4Iic1Hk9D4sxpTNxiolD4pxQXE0VEuDUMd2YEGAFGgBHQR8BlAaRRo+qstIsXL6bRo0frz8CljAAjwAgwAicFAqtzN3p0nQEUQLc2v4auT7nco+PqDRaQm0MhS5dQwZbNFJybSzGiUWVUNJX37EWlI0ZSVVycXjfTZTsKU2lJ1p+0r/ggBQYEUtvwVjQqcZh0zDc9GHdgBBgBRsBPEXBZAGnZsiW1atWK9u/fT++99x5FRkZSx44dKSwsjPLy8iQcy5YtI5hqmaWJEyea7cLtGQFGgBFgBDyIQKlIuL39cBgdRRZuEfCqcVwFIeJVeIgl9K7eVBllmXrFLpdVifzf5yefLTJ+i7BcXqSg3bso4rOPKUBoPbSrCyzIp9BVKyhkwzoquvIaqujYyWUuCioK6em9r9FCoSWyp7cOfUQXNRpL97W6mUIDQ+2r+ZkRYAQYgQaHgMsCCJA455xz6N1336Xs7Gx64oknaoDz+OOP1ygzUgAHdyZGgBFgBBiB+kFgyT+RNH9jDBWV2oa3CguupHNOyadRPQqEUFCTt5gg6A08S1sLdlLj0GTPDqoZLfDoEYr4+AMKKKvpUK+aBZSUUMQnH1LhbXdSZVPzfo1FFcV0w/b7aFvhLjWkzRWC1tfpP9CBksP0ZqdnKShAL+qYTRd+YAQYAUbArxFwSwB58803KTg4mKZPn+7XIDDzjAAjwAgwAhYEZq2IpeU7o3ThKCkPoG/XxdLBzBC6dlh2DSGkd0x3+jVrmW5fVwuLKotc7WqoX9gP39UqfKhBIKCEff8tFd14iyqS1/KqCoLvy9KsFXSw5IgQJSpFtK4IahGWQh0j21KvqG6y3pHwoR1sVe46+vToHJqccqm2mO8ZAUaAEWhwCLglgED4gBBy11130c6dO6mgoIAqKytp6tSpdPjwYYIGpGvXrg0ONF4QI8AIMAL+iMBWEUp3w75wSs8NksJD0/hy6i9yeahwuit2RZwQPqCF1lFxyLIqWvtvBLVJLqUzu9smEzwn8Ux66+CHIsmg54SGxiEOtB/ityYgP5+qxO+QsAF26e0IyMqk4NTd0uxKb7XaQYFI8J5UCsjIoKokSw6Tf4v20327n6Q9xfu1TeX9xvwtRC7443905Eu6sulFFMxakBqYcgEjwAg0HATcEkAUDPD9wEuRMscaOXIkDRs2TBXzlRFgBBgBRqAeEMgpDKT3RULB1GO2/gU7j4bR79ujqFfLYrpaZD7/cYMyoaptO26pW7ApRobmDdZYCyWExNHUVrfQU3tf9cgqo4Ii6ZTobkSlJQQzqCrhFB549CiF/raIgndss2ouKoWDeFmfflQ6fISpyFVBBw9IPmtbrVqIahN06ACVCwHkkNB2XLv9Hsopz1VNPHLNqcijfwp2UC+sm4kRYAQYgQaKgEcEEHtsIHS0bduWEhM5a609NvzMCDACjEBdIpBfHECv/JREx/Mcfd1X0eYD4fTygiTKKtRIE06YLBT+IbvTQqlLs1KblhManUOFFUX06oF3DeUDsels9zC5uD/FvfYaBaUfkzVVcDwRPoIQBrSegoE5ORS29DeLs/i1U4z7aQihxixBEALBodzTwofiJa3UfPAW1ZevjAAjwAj4AwKOfpHc4h1RsZgYAUaAEWAE6h+BuWtiaxE+wJ/lbP9oTohpZtOFUNOFbAUQDHJF0wvptLj+wp9hLq0p2EBHi9MpOjiSyirLCdGgjNDAnES6fXE2BVUp3YPodUL4QH9NqXU4CCIRH8ygwjvvoapopc2xVlfflJdT8PZtFLxtW3WZwbvgTRtpZ9VR+itgg8Ee5ptFCs0PEyPACDACDRkBrwggAAy+IAjRe+jQIekPUi6+8Js3by5fCN8bEmL+x64hvxG8NkaAEWAEPI1AblEgrU5FMj1HPh3aGY200bYnCgrU6iFs69pGtKLH295DycnJVBpQRuf+MYl25KXaNnLwdFFac3piRSKFaIUP0VZP6LAfIlDk8Ahd9CuVjL/Qvko+I+Ru+NyvKDArS7feWWGw6L+eVhCd4qyla/XIfdIlsoNrnbkXI8AIMAJ+goDHBZA1a9bQrFmz6KuvvpKChx4O8fHxdNFFF9GVV14pfUS8HeNdjwcuYwQYAUagoSOw40ioED2MbNuBhNF21ag1E07sRmj67g8MCx/JlVH0pBA+wiptQwAbmQdtIBIhb0fJ2POF17jtT1zw1i0UjnwfboZ6Px5mbN1Geda2Gxo3kJJCErRFfM8IMAKMQINDwLVveB0YcoTqe/LkyTRw4EB6/fXXHQof6Iq8Ie+//z6dccYZdPbZZ9faVmcqLmIEGAFGgBEwgEBukXGfDgPD2TRpFFNOrZMd585QjZHX6fN9c9Wj0+vxwAL6o4klma3TxjoNIEbBTyMw47hNbUB+HoV/Ndtt4QODxpV6B9eIgHDhxH+zDd/8wAgwAoxAQ0TA9njIxRVu3bqVxowZQwcPHrQZoX379tIZvUmTJtIka/fu3YRXlkb1/euvv1LPnj3pyy+/pLPOOsumPz8wAowAI+BvCGTkB9H6f8PpUHYwlVcEUHJMhYwy1a6x8826p9caEVrpwpDKrMqRRsRiqjVxYG6NPCB6kx0qPkJpJeacqjckFtJZR+L0hjNeJg66qElTS/uKCgpdvEgKJsYHcNyyX4Z+nhTHPYzVFFeVSOf9e1veRK3DWxjrxK0YAUaAEfBDBNwWQCBMXHDBBVbhIzo6mu6//3669NJLqXPnzrqQHD9+nN544w166aWXqKioiDIzM+niiy+m9evXS4FFtxMXMgKMACPgwwgItzf6fn0MLdoaRZV2vgu//B1N3ZoX0zVDcygmwhWhwPzCwU9MuJrLIjTUPkoVBQqZ48L+uTR3bSz8vQVp+1Xfo02vlvoRpDLLsmlFzhqZlC84IFgIYOajIeaFVNTOqoHaiLlfU/GFEylk3VrpcF5bpnMDw9k06ZMZSV2zw2lbfLFNubsPyIj+e/YqWpu7iaZ1eob6xfRyd0juzwgwAoyATyIgTGHdM4Y977zzaMGCBXJxCL/72WefUcuWLQ0t9sCBA3TnnXfSt99+K9v369ePVq1aJbOrGxqAG3kFgSNHjrg8bnh4OCUkWOyXCwsLCaZ5vkzwR0JCTQjFvkyRItFanMh1AMoXydfy8lw3UamLdaoQ3Dhc8GXCgUlMjCVaUq5wXkYyVVfpg2XxMkGf7aZdjWbZvMdFlNM5p+RTfFQltU4qo7hIJSCods6v6rNwVOTD0Pv6LioNoIWbo+nPXZFUUGLOynZAuyKZ4Tw1LURmPE89hmAh1ZqQ1iL54AV982qE3gXXZZVl9OahD2l22jdUVuWej8RdW5vQHdtPaC+cQ+KwhRKZ1NVhQxcqNicU0mXDd1NpEEb3PMUGRdOcHu9To1BL0kP7GRo3bkxBQRZTMEefBfs+es+BgYEEKwUmRoARYATqEgG3NCDQWCjho1evXjR//nzrj7mRRUBQgenVqaeeKrUf69atox9++IEmTJhgpDu3YQQYAUbAJxBYKTKIIzu4vvABFi2b+JyiYPpiVfwJnquoR4sSmjggl5rEuX/ij0Ez8wPpjV+TKC3H/Fd7THgFTehnSarXvkkZTT03g7JFAkOMhWOqxnHllCgEJz1CeN3bdz5Cq/M26FWbLhtyrJYQuiZGU6KTupro6rRpr6xImrGiLd0xaB/lhnrm/dNOmluRTzOPzKYHW9+uLeZ7RoARYAQaBALmjsfsljx9+nRrCSJfqZNEa6GBm9DQUBk1KyrKYlM7Y8YMA724CSPACDAC5hHARnrv8RBaviOClvwTSev3BFFRzTQWpgdeKEysLGRuq7vlYDi9MD9ZJPRzPyx5hZAN3l6caFD4wKl99cl9YlQ53Xl2ptTMaBcfLzQ0nVNKpcbDkfCB9tOF5sNTwkdvak19M6M03Gk58q17CEqLF3ahW7c1po654R5n7pfMZbpaLo9PxAMyAowAI1DHCJg/JtMwOG/ePPkEB/Tu3btraszdwlfk8ssvJwgfCxcuJJhCxMbGmhuEWzMCjAAjUAsC2w+H0ld/xZJ9wr3QX4jOH0h0jovm9sfzguhYritfpRZhpbgskN79LZEen5Cu8dmoZSEOqv7cGUmHsowIMhA8AmQOj5T4MurXpojO6FpIYSHVAomDKXSLs8tzaVaa5bdAt4GJwthKkZH9F2iSlM7IROd6appQGkz3/pMiX10nbKayWnKjmGUxqzybgG9CiJsO+WYn5vaMACPACHgZAVd+NSVLCKWLFwgCiLvUt29fOQQSGO7du5dg0sXECDACDRsBnPwv2xZFu9JCKb84UG7AOzYtpRHdCqhtI89FjfpzZwTNWhEnTtVraihKhbvCHJFXbuu+SLr5zAIKMRlhNavAZAedtxS+Gr9sjqKJA1337bEkHNQZvEaRBYOuzUro1rOyaiPv+dUAAEAASURBVNSaLViRs9Ztnw/M2aEimaYvTqLWBWFmWfCZ9i0KQunfGH3nfFeZrCR9szdXx+N+jAAjwAj4AgIum2BBSFDUrl07devytU+fPta++/bts97zDSPACDQ8BBCh6YtVsfTqT8m0bm8EIV9FpTiAzxFX+FK89GMyzV0TI8vcXf3+jGCavRLCR+207VAwfSOiP5ml8BDPbBCBgzt0KAvnSc5WWT0DzL/mCYzdpUMl5oNWjIg/jYbEDZBRnsYljaaXGt1J879rQe3ywnVERHc5rLv+I4+Y//zUxl10UBQlBLP2ozaMuI4RYAT8EwGXBRAVfQPLLi93L+IJxkD0JEWeGE+NxVdGgBHwPQTmrIml37fD70u7YdZqJ6po8dZo+kGEtXWX5m+AIIOxtePrjSpCoG6PpMwCc1+LTYVzdmgwhBDtWvTGr70suzCISsqc8eh4jPJKs32rRMjgaPq/75Pp4z/iaOm2SMorMrf2gyLHR2rRPsdMOahZkr2CjpSk0blJI+mJtlPpvC1VFCwcdMyuwMHw9VZ8/c5GFFnhsmFBDb5HxA8RoZHNvSc1BuECRoARYAR8EAGXv9m6dOlCcCAHbdq0ye2lIaKWorZt26pbvjICjEADQwBO4NjsWjbsjracKK+iX/6OosPyZN81EIrFhv6fQzDpMSIcBEhB5e/91YchRmYNEfvN/m2RD8LRWoyMYmljhEtHoyVFIxKTGR4sbQ9mhtBfqZHCPyaOHpvbSDrnO5pDlUPouHH7/TTu76tpYeYSVWzquqd4Pz299zW6e9fjVL53l6m+vtq4UUkIvZR2OgWJf+5SCAXT9SmT3B2G+zMCjAAj4JMIuCyAhISEULdu3eSiNm7c6PbiNmyoDt/IAojbcPIAjIDPIrB8B4QPbH6dbZYDhNgQQMuFc7WrlCmykhvTflTP4IpD+bg+ecJ/xb1QrLERFRTuoiM4uO/V0v2keKXlAfT16jiRUFFF9arGRd0hSd5V/9xOa/Lc/97HmH/k/EWPt6r+/lfz+Ot1eMJp9G6XF93OZF5G5fRA6tO0raBhCGf++n4y34wAI+AdBFwWQMDOKaecIrlCLpC///7bZQ6R+G727Nmy/+DBg60J11wekDsyAoyAzyKQesyiOTXKYKpwUHeVApzJODoDBwSY10MgoeDtozJFYkE9IcTYeH1auydAjOxeQGHSFExnUYaLAFgV/bw5Rjc0MLKc37f7SSqqdI9Xe3a+TUmjjQmuJ4G0H68+nvEuV4mkpuWn9JG+LXNFEsG3O71ANze7mobHn0odI9pS09DGlCJefaJ7UG/xChT/aqOdRXto8ra7aUPeltqacR0jwAgwAn6HgFvGqhMnTqSPP/6YysrK6Prrr6eVK1daM7MaRQKZfCdPnmzNRI3M6EyMACPQcBEoLDEnFRSKzN6uUlJ0uYhqVUVlUi4wNk5KfE2ftn8OhUrn+KPZwdIxvnFsBUFg6C1eSshpmVROj12QLszGomn1ngiRxE+Z4TifF47sZ/fKd3WZsh+EoOuGZ4uQvgkntD6uDmfhF9nUO4zKshnk46NfUU6F65G6bAaze/imdRb1zrLkg7Kr8vlHCB9AreSs0VQVFyf5DQoIosFxfeVLbwH5FQU0bvPVMsyuXr0qK60qpft3P0Xf9/qYIoPcC1SgxuQrI8AIMAL1jUDtxy9OuBs3bhxdc801stWaNWukEJKZmemkV3V1YWEh3X333fTLLyIQv6D27dvTRRddVN2A7xgBRqDBIRAbYS5qlH17hM3NEKZVRQYEk1BxxNJTmiY5FwJw8h8scjj0alkdRjW/OICmLUykN0V28VW7I0USw1Dan2ERRmYsTRBJBJMkL+pNigyrovH98+j/LjlGL086Sk9MOEYtElU4YXtNiOU5WAhIU87IIiT9c5d6Ct5vOhPfwfZzmR25irYfCSMkN9TSr5m/ax89er81odgp11gVXpUxMVTevgNVBQU57aNl0gwqRtqqNvh0lZ4+nErPOFM7Xa33c47Ndyp8qAEyyrNoTvp89chXRoARYAT8HgG3NCBY/bRp02jJkiW0f/9+qQ2ZP38+Pfvss3TDDTdQYKBj+WbOnDk0depU2Q/jREdH07fffkvwLWFiBBiBhotA55QSgwnzLBg0ji2j79bF0K6joXRMJP1DvhDlP9JMJNIb1qWQhnQqFIn19DGDf8bfB8KFFsSZEBJAo3sKX44TAhIiUv1vYdIJXrHVrNkfwsirPyXRg2OPW/spLiCMRIZV0NRzMoRPRQz9LnxfbDf0AdS+cSldMiiHoD1xhxDCuEDgAmGmZ8tSaidyqOxJd910DWsFr8AamhVQWWUZHSlNc4fNWvsWxUdLhPWRtggeeAdKxpxr2eiLWM7RDz+g8644nqaieQsqGzGSAnJyxCuLQleuoAChwdebE3OVt2hJFd16UFVYKFU2bkKBhw9RyNrVFJSebplE/MaVt2sv+ano0NHxxDo1y7JX6ZQ6Lvrs6Fy6uNFYimAtiGOQuIYRYAT8BgG3BRBkLP/ss89o/PjxBO1HRkYG3XzzzVKz0bZtW8ILeUKSk5Pp33//pZ07d9KOHTtkW4VSWFgYzZo1i3r06KGK+MoIMAINFAFk3V4mQvBaNuM1N/W2y64SEZocmeVU0eHsEJFPJE7kEgmnm0ZkiQ0/tpK21CSugq4fnkXvC42FJVSt3naTaGCHMjq3d7UZFPKUVGcWd8wnEhF+vTpWmj/Zzmx5Qobx8f1z6ZxT8gj+LzDNgrN5m+RSAm9GCSFy1/4bTgezI6hCLCE8KJaaCuEsVQgaWw6EUUm5RQJLEH4o7f6fve+Ab6u83n60vffKcqazA5mQQUgCBCgQRthhz68DKKOMlkJLW1oo/RcolL3L3nsEEkYIWWRB9o4zvPfQlr5zrnxtSZZkSbZlOTknvxvd++773Cv5fd73jHwboMyRA99ruH36RkcPjkG47YUq1ydrCCzz5sL0Ka30OwPgQpN9y0m/gH3WHE8zdO1OTYOmoT5Usz557txcOMaOa01zTD4Kpk8+go7+JnnvGrnp75p19nGwT5tBXKztvp1Fwz39W0n1zmKFmxbOSO+4tb1ITiIlcxX2Kly55WY8PfJf4PggIoKAICAI9GYEOk1A+OZnzpypEIs//OEPeOaZZ8DRzC0WCzZv3qwcoQCaMmUKXnjhhVaPWqHKSp4gIAj0fgRyUp04e0q94va1bV072H21Tf7al1Dz3LQ7YsKz32bi+hMDq4AeUWjFradWUnDDNGyjst6SSXO5c48Bpg81g7RCFWL0JpGPFTvD1bd3K8Tg7CltuwXcfm0zRTcne5D1exNQQ6SDfXrlEeGYPNiMo4c2heXxqop2fHjnhImHJ+K6es/cg7d3sDbixX2tpmCObFdisQfZFuLqHUhemsNnjAatHv1NfbA/isCDHXSlZM/MOBr2oplwjBoDw8pl0O/aBU1TI9xJRFYHD4Ht6KlwZ+f4NOUcMQLaH1f5pIW6cAwf4ZPNuxrmK64mEtMAbclB6CimVQapAjekpcNubVPF86nEF6YEepoa6DdthLaslHTCKF45jc05YqSHlLSr0D7BpIl8h2pL8w78bc9DuG/one0blBRBQBAQBHoRAl1CQPh+s7Oz8eSTT+Lqq6/GHXfcgR9//BH19YFXplg167jjjsPFF1+sHN5BDXsRdjJUQUAQiAKBtTQhX75Dndx7T6ijaEypwm24sfmgCWtpJ2TCoMAemljN6caTq2kir1V2NuzkcrZfrhHDC5MV9S0LkQ+W/32fTkbk3pN7T3rw/z338NoyWjWnXQizTauQDd498Q4OyBPWsjo9PlmXiqXkWviCqXXkutelqG4xKfOXrzcl4V2KzO4MK8BgexyZfDAJYdW0JmvkRGRD8pO4aOMiJWL5BflnIsuQgROzZuG5ktf9h9rp6z7GfJyWPVdpx52VBdvJp4L2cDoUK+2G6FevpsfvInRDi4vadRwxPmAhN9mUOFOJnNBuhi4vj9hjbcByaqLhh6UwLfycdkHMapLyyTYpthkzYaOdmo52RkYkDUWx9YBP/XAuvqj+huKDLEAe/RMRBAQBQaC3ItBlBEQFgHc0Fi1apFyWlpa2qlzxeZ8+fdC/f3+MHz8eBQUFahX5FAQEgcMAAXJ4h9eWpXvF9eicepAvZJ7p5zIiNsEIiFo+M9lF0aXtyu7E26sSiZB4cnJSU9Av04D1xUyOIh/bT/tUUqX2FPyT1bCeWJzVWiAz2YnjRjdh9qgmhTBwoEaOx+EZR2uxiE+YhOSmOjCfVMCqSVWMXRqzcXlH99dk2opdGc/C3WzDpuZteKXsXfxtyB24tOBcvFfxGWocdRGPJViFRG0CHhh2F4zayHcE3Ll5sJ5xJhLefzdY80q6m2wLzQsuAchNbmfF9OH7MP7wfeBmSHXM9N030JGtCO+shCIhp2afgC9rvgvcTgepi2u+x4xBR3dQSrIFAUFAEIhfBDTkBrdt7z5+xykjiyECrELXGVGdD/CrFe+vl6ZFvzvex8nPo7fj+gbN2d5cyivxkU/uw30fM5LdePa60D9p6/cA/3pfg0jdAYc7hs6UGz2A3JLPceOOlykqu/I17Ghdv6PePFgzLn86343CXOCN7zX0HNR22z8LJh9bBv4aNkOZT+Mcs+KVox9Hsj4J5y+7pktigYxLG4WHxv8Vo9KG+/QV6YVj+TLYXnmJrObbbHjUNjR9+8F07S+hHThITQr5yd+zYL+BjpUrYHv80ZD11Uz9afNgPPs89TLg54IVv8I3FUsD5oVKPLvfaXh04j/IPMXzHIONN1Qbap6D1M6MxsjJn1pfPgUBQUAQiAYBISDRoHaI12kM8Ec83FvW0wpjQkKCUpzjw1hD6VGH22g3lmMHCDzhMJt9VSm6scuommbvcDxWFpvNphxRNRSjSuo7wLZgLNWNGtzyYhKpJPGVOvnl864VNpp+5pfBA9oVV2pxz1uJ4IjfXSftJ/HRte1pR0uBED3R26NrJVitnFQX/nFRM6llAdsOavHRajJeL9a1qomZjbtQnvkeSrJegVsbWAGqjykf/x5zD1478B4+LPsiWFcB0xcUzkeaJhW19jrkGLMwNXMSjs6Y2DqJDlgpkkT+Dq9bC+zeBZibAbLjwMhRwBhybkLf8XCEJ/TJycmKDSNPzNvJPXcD5b7ErF0ZNYG+s/j7P8lUJ7g6X729AZetuwE/N2xWa4X1eXaf0/DIpL+3Lkp05jebF19SSQVNRBAQBASBWCKgj2Vn0lfvQKCBDDKjFZ54qpNPJiCdaSvaMURSj+2PmDTF+ziTaBLjTUDifbyqO211nN9uTG6d6EbyfCItm5nkUJ6lg0wq2NaE7ULqSN0p0ejCIHJNu2a3sYvJB4+wq8gMt9M95INHWdlApGOlCycf0YQ+NN+8drZiO40F62/HdttmuLQdk/ASaxkuXPNLbi5iuWDAmRjk7E8OrtrsXdpNnMkLgLauFm6jCe7MzLCJQ+tg2MOVl5crJb0pOCFtrddywr8HKgHxX5TQkOvdlHDJB7dHv3/mtWvI7uRI/25ar/mJP1P0L8xaNx8WVwij99YanpMBuj4+u8uMY7S7uLwAIwTED2C5FAQEgW5HQAhIt0MsHQgCgsD+6tj81IzpZ8XuCgOe/zYDlY2+fa7Zo9podNWORXc8164iM4HHxt6xmICo0uxuwlbHGproqynd8zk8ZQgmZ41HZUVlwA50mzfBtPgraPcVt9I5N5Fu+4RJsB53AogVBKwXy0RtdVXE3YVTx6gz4vScE/Fm+Udhta+jh3VC1sywykohQUAQEATiFYFu/rMTr7ct4xIEBIFYIsAep7pbDBSEb1iBDQ9SYEB/8uHbd/ePxbe/eLlyo6RWTyvlnvG4yHPUv4uf6vbB6TRa3H/k3WT4H/jPjemj95H04nPQEfnwFg3thhiXLkHyf/4NbWmJd1bPnNPuSKTiDtPonb1apekopkgYMj/3FPQjd8gigoAgIAj0ZgQC/0XozXckYxcEBIEeQ6CBImfzbkcleeBWJ7o8mKyUNrWb7hgcx9i4cFot3qaAgN6ub7ujr97cJnMP9bk8sv85vFf5abfeDse6eGz8/ZiWPbldPxxAMPGJ/xLJ+L41LxA11FLU8sTnn4USpKW1ZOxPXPkF9Jbxmxa+uArCIwp5xhz8u+geJOuC24uovX5U9SWeOvgy2QkpBlVqsnwKAoKAINCrEPDVUehVQ5fBCgKCQE8jYCM73W3k1nU1BcrbSgH+2L2sKpkpbkwfloK5Yxsxrr8VizbyCm/Xqz+lJzpx4fQ6WGwaVPmpXaljkU9GQIOcFIdij72VAtq9UPpGt8GSpc/A7MzpFK/iQhxRQEbgfqLbsR2J/3sRGoooHo6wXYjx269h+8Wp4RTvljJKrJBhw6CnsYcjLorSzgEUw5VJqUfg1dGP4cF9T+Gb2h+CVmNbkccPvIi9zgN4ZgrtDgXZWQragGQIAoKAIBAHCAgBiYOHIEMQBHobAuwiduGGZHy+PgU2Z+CN1BryfMVB9zg44HVzqzEs34odZR5PXp25X/YSxVG6h+bZMLyPDUcWWmCkX7IXl3DcDJFQCBw50DPhf6v841DFOpWXoDFh0YS3grbB6lSJpHKlISPtSMSwZjUFKDyFeFSgfZJIWoq+rPWU06D77yPQOAN4yPJrVkMe4Awrl8M+bYZfTvDLwoR+mJUxLSQBUWt/WvoVHt/5An4z7Eo1ST4FAUFAEOg1CASeOfSa4ctABQFBINYIOIl8PLk4Ex+uSSPy0fFk8GCtAfd+kIskoxsmvao2EkqRJXQeu6idNNiCvpkO/LwvAc98k4lXf0jHvmpyeyoSFIFEioo+d4zHAH1tw4ag5TqbkaALTTJNH7wXMfngMWlJZUvT1NjZ4XWqvotiilguXADVtiPUm6qx25BA92r6JDzjch4Ye7Li3Y1w5eFtT8HqDOwyOdw2pJwgIAgIAj2BQLfsgNx9990oKSnBFVdcgenTp/vc1969e/G3v/1NSXvyySdb/Zj7FJILQUAQiFsEPlmXgp/3c6yX8NWpmmxa/ERkoU3aExfWrmcd+9BubT31eAyhy7X11LNnbgwm978JFJ/ETCpixVWGLonxMTCXYqs0ONFgUVXe1GehfvretZ4M9K+ZU4PURA8BrHOQkU43yfDEoUFb1lRWQE9xOgKPMmi1tgxbZLsmbRW77swx9gg0X5eLxBeeg7a2JmTDfJ/GJd/COWgwHByPpAPhqPPl9soOSrVl1zsasaxqFUYiOOZtpeVMEBAEBIH4QSBqAlJdXa2QjJEjR4J9p3vLm2++ia1bt2LGjBntCEgF+VJ/5plnlOKPP/64EBBv4ORcEIhzBBotGny1gSf/UU8hW+smGZ2kPmVFaoJLidPxAe2ohC/tCUz4dWNXktXEbjmlurXDPeQi+OmvM1DTHM1PrwfzogIH/n6pHhXlFWgkjSqnS0NaSW4ywE/Hj2SL4y8Dc2xkoF+Hwuw2taFsQyaqHKEnz/7thHt9as7xQYtqi/cqeZE+Pb5z+kMDd1ok70jQYXQ6g10Ea8g4vqNvgXqfxq8WhkVADlgj9/a1smotRmYKAen0Q5UGBAFBIKYIRPNXUBnghg0bMGvWLCVo0/jx4zF58uTWI9qASDG9c+lMEBAEIkZgA+18dN7LlGda1mzTwWzX4JJjGrBqV/uJc8SDi6sKnqnp8S0qT+rQOBhikslNBERNieRTg1F9rbjuZCv0ujTFFCIlgftRpue4clYtzpqsxVZyClDXrCVS58YQIkD9s9qIh9rb5LTx2GbepV522efY5JE4NfuEoO1pLOEH2/NuhN8Yx7AiUNRQ7+QeO9fTApsmAi9UupKDRFgowGJ6RsgxGzSRqxE+suNZDC0qxPT0KSHblkxBQBAQBOIJgah/zdVdjyaKMrt06VLl8L+xd999V4mKPWXKFAwdKis0/vjItSDQ2xAor/fd7ezc+N1YtzcRZXUN0PcKa7SO1rtVNDzlxg2wYPxA3wl3s1WDAzU8yQy3rbY2z5zUgBPHNSEpIbir1sxkF6YO6zii+fl5p+ONsg/gpH9dJYMTCvHvYX+GTtPyjpCnAj0FGLRTfA9HfR00iYlkvB15fx56BViPn9tVQ+10O5qatl2tcBvTktaAs4WA8O6JtopUrcig3pWbC3cKhaYnGZo4SPmM5D+7245bd/wVr495AgMS+kZSVcoKAoKAINBjCERNQFi9qry8HKtXr8aPP/7Yehw4cKD1Zj766CPwwZKVlaXskOTn57fmy4kgIAj0LgS61gGRZydk4wETOIJ5fItKGNTPUKPVYGx/C644trZdoTqzSuBU5Zx2RYIkaLC+OEEhIEEKRJTM3pZ+O+Bq/HvfkxHVC1X4T4NvRq4xWymiPXgACa+9Al1FOVS3A5yhUi8+DxcBLmcl71euwoFcLT4kip0YNlxn98OmLz7zCbrIdk9OWqDjeywcUIgxySOwsWlrRPfZ7DIrxut/H/r7iOpJYUFAEBAEegqBqAkIDziXVm5OPvlk5VBvoLS0FFOnTgUbm48aNQpsK1JWVqZ8Lly4UC2mfPbr108hJbxDoqpwFRQU+JSRC0FAEIgfBArS26vzdHZ0NU065Kc7MSDL3kOerMIjFZlJTlKdUglEoLt2g/E55chGxUtXILKWZPSejgdqI3ja7gojeAdqUPANkOCVA+RcUnCOslvxEMWdsLs7/1zzDWQZT6Lbvo0MtJ8NutsRLvHgttwGAyxnng3HpPaBDDm/p8QZZoBBHh+/XRx8RbdtK0xffqEQL983zg39zh3QPfYILOecj1uG/xJXb7mFiFtk78ri2qWwumwwaY3co4ggIAgIAnGNQKcISKA7YwKRkODR577ttttw+eWXY9++fVi1apVyfPfdd/jhB0+QJd5B+fTTT5VDbYtJybPPPouTTjpJTZJPQUAQiBMExlJAQXala3XwNDKSqWTwGzDplSkazp5Sj4cXZrVE6g7Wtu/ULXirHedYDMVoStiK7AZVtSdQ224MzLHjpHGNisH8N5uT8BnFPmm0+hKRQjL0Po/GPyQ/tJem9CSXEgywMsqAifvIi9agKNdozE4L3qn4BF/VLEGx5QCRDy2GJAzEr/pdikZHM9Y1bkStow7p+jRU2Kqw3xa+QXQfYx4KdFkwffQBDEuXdOrNUJ+CKzsbTb++AWRo2PHDjHEJZ9FwuFJSoG3s2C2w8iaTOloCkQ/Pm+77zVHfdA254E1463VMnTQFfzrmevxp/8NB78pkG4D0xqNgcObAoa1DQ9JaNCduBRuxD0kcGLSeZAgCgoAgEC8IdDkBCXRjAwYMAB/z589XVLV4x4PllVdewbp165S0NWvWoI70YlmFi3dRRAQBQSD+EGDD5l/QCv/7q9kbkTpV7Nw4C2mC3+hswkLn8yjrb0DuvptoAqun1lk5RZ2eqX2p15H3qbZXnv4BatK+QU3q13BrHMisn4P+FdcixTKutdEEipkxabAZ8yY0IC1RnTYCc0Y3Y9bIZuyuNKCqQQcD8ZB+tHOTlxa+bcPMEc14T8GvtbuwTzzEL+zirQW3NO3ATTvuRqmtojWNTyrt1VjZsFaxPXho2F+Qb8zFr7bdHhH54HbOz5mHxOeehn7XTr7slPATth9xJCxnnweYQscU6VRHnalMOzMclDDxzdcj+hZ09PZyvnH1Kly4NwdLT5mGhU3LfEZptOdhcMldyGqY45POFw2J61DaD0RA2mVJgiAgCAgCcYdA1ASE3enu3LkT7AFL3fGI9O7OO+88LFiwQKnGnrN27NihkJExY8ZE2pSUFwQEgRghMHdsE0rr9Fi+oyt0gdzYWtWIO2t+hf3sgpR4TdngdSgsuxFpzd5qN5pO7RwwNCqZqch8H/XJq1rRqkn7mgjJ19A7MjDBeCz+VnQjslOc0AUxjCdtGorCbleO1ka8TlY3/IRPqxZhR/NuRbWpn6kAszOm46TsOdCTgfbs0U1YQ9Hh91ZFrirD4yJXUF69dXy6z3IQ/2/rrah3Bl+t32neg2upzElZs8Hjj0TGJY/C5etMXUI+1H7tU46OX/LRMkjHxMmw1tQoalXquLvqU1tZiaPXWbCwqK1F3vUYu+t/MNKuh0qm23KBVPN4vLHIhdy5NSgqsHlnybkgIAgIAnGHQGR/ybyGv3nzZsUNr54M65gwqDYc/OmMwtOJhhSmi4qKlMOrGzkVBASBOEOAbRsuPaYOQ3Jt+GR9Krl89VVHimy4Gny9rhCGzKuAvn9TqjYmrcemwVfA4MhGgnWQQhzMxj24eciFOLDmCuwsj3zi7j0mNwLbOzj0tVjl+hAVuhORpx3hXSWs82anGX/a/YCi4uRdYXPzdiXt2ZLX8K9hdysqMr+mSeKTizKxi+w6whNSz6FghuxWN1ICct/eR0KSD7X/ElsZXi57R70M63NS6hH4d99bkfzKgxHtBHTUuI6CFbKaU7yLjTxzuTIyFdUpHivvYHSVnLBDi3uHkZcsivFCW3UYUfygQj64fZVM+/dld2qVODN/nl+huHv2z5drQUAQEATiBYGoCYiJtsaZfDgcDqxfv1452HbDW1599VXY7XaFnIwdOxYG2rYWEQQEgUMDgWNGmDFjuFmJ7l1J6kgcnby0LvLvOK/mFtRcQHrs61CZ8XErOHZ9FfhQ5dEDz+CNY4/Ha98VYlcrCVFVs9RSwT+5H1YbM5v2BC9EOcvqViueiEIW8su0uxy4YfsfQ+4e7LYU48rNN+Hl0f9F/4Q+uPmUKjxDQQnXFbPOTKj78OTNHduoqHz5dR3ycr+lBD/U/xiyjHemI0Jj9Ivy5iNrJ8W4iGLRybtf/3MNuXfvLaIll7xdSTzU++7XbMR5+/Px+oBSZNefhGTrSDUr5CfbJy3elIzTJgTf8QrZgGQKAoKAIBADBKImIEcffTTq6+sV4uHthnfLli2tOyBffvkl+GBhNa0jjzwSffv2bb0t3ilhEiMiCAgC0SNgtmkonkYCdlOUbbNNi3Ty1jSyrw2jybWtNsDMiGNR8Mp7k1VLUcidtKpuV1bXoxkB74awkTYfw/vY8NhXmdhb6b+qH2py3baaO6D8Oh8C4j+eJnI1usL8DW46+VT8sD0Jn/+UgpqmIHpS/pXpmleNa5OXwaEPHQG8wk7xGSKUV8veDUk+1ObqnA34654H8eTIfyrP5qrZtYSZFpsPsq1DIJw8aRyA8EQyhI9U1jT+HGmViMqX26ugre56owN3HBqeBwNGt39fsKxOp//xx1xsyXGiqf64iNpil81CQCKCTAoLAoJAjBHo1Ow/kQJLsctdPlThwITjxo3D7t27MWnSJPD1Vooaa7FYsGLFCrWY8smxQdiGxNsN7/Dhw8ljYfiTCp8G5UIQOMwQ4Ajib6xIRzORCW9ZvIk0mjLsuJxiUaiRsDk69ns/puLH3YlwkUqHKjqtGzOKmnH6xIZOqW2kJrhwyy+q8M2WZCzbnoKSWnVMbX2pfQb6TLD3R5KlCM0J2wNlK2mbyZh6Pnl7ZUNuPjYdMOKl7zNQ3xpfI2hVcmpqR3H+g8ELtOSk6CLzusT2a68QAQlX2Oh7/s9XgdWXzsg5Gb86fgTe/TEN321Joufi2woTyKnDa9B3+Df4sKoGGeShapp+MtLpXzhS56gPp1jUZZJ1RD66YRHJOWRo1GOKeUVb99lbJLi0eOXzAvxm7AiEHynHDd6RFBEEBAFBIJ4R6BQBCXRjybRyZTR6VkCvu+46XH755WhoaAB7uWJXvIsXL8Znn32mVG1ublZc8qpueTkxNTVV8Y41b968QM1LmiAgCLQg8C25hGXyEUwO1hrwr0+zFVLQYNHi2W8yYbYzKfCd5Top3MB3W5OxpcREuwtVtIMSWfwB7/71NO85YUwTzptpwrvLdXjzh8h+YtjQNhQBMbss3t3RLo8N951fjhe+S8fKXYGM4j07CEw+dvT7A5oSN/vUD3QxNrm9qgsbZi+s/ga7zMVEElzgQH7HZR6DmRlHY49lHypoJyASYXUsPt6u+Bjn5J6G26b8BscTbuv3mlBW78EsLaUJK/RP46HGN+Dc1fZMNDs0OL3vSfh13uXIM3gC/wXrO0ufESyrS9I5aJ6zoGvVpTjGRm8iIO704N/BrgDZSCRkQJ0LO8LeaNKQAwXf73hXjEPaEAQEAUGgKxGIbHYQZc9MKmbNmqUcs2fPbiUgn3/+easbXiYnHLyQyQoHLxQRBASB4AiU1Orx1sqOXeHaHFqFhLBxapv470h4rstp4vs0kRTexQgURK+tfnhnKV7ua8OrQdRIE3o1uYDiTQSSy4+tw9gBVny8NpWC9Xn/rGmQmLEXK7JuJ/KxIVBVn7Q8Qw6mp09pTWtwNOGu3ffj21pfd6is2vR+5ecYnzyGAr+x+lT0wiSEidXfhtyO48Y0Kw2VWsuVYHQHGkvbNcy2LB8c/BxLK1biyRH/DBn3YXLake3qh0rQQks7RW1kJ1TZI1NGY3BiIUXxdsBFv/Fa+u3urHC0cA7Gx4H7eos4ho+EYe2abhsufzv7WfcTAfFyidVBb30yAjta6KCaZAsCgoAgEDMEvP9Sx6xTtaPjjz/eJ+BgJbkeZHuSQYMGqUXkUxA4rBFotGgo6J8WBr857pcbkn3UqEKB5Es+QpWEYty9vtiE8QOtaDBrsXR7IraXmsA7KCkmF4bm2zCd1LUykzuepA7IDn8VVnUr2pywI+QA3y7/GO9SMD2258ih1f8JqWNpB+FUDEsajMmDLcrB5IxVUHgVuC9NxHQmOy7eVEM2LyGbVjLvGHh9ayRpi8uKX269DZuatwWtuK5pY9C8SDI+qfoKA039cU2/i5Qdlt/tvAcHbO3Jh3ebHMPjpu1/wltjn4KRol83OMhIXWtAAhEih9uJVfVrsb5xEwaY+mKf9aB31aDnp2Qfj8U136OZ7G1CiVFjwO2F13mKEFt1jBwF46qVAa1YQrXjncckxnLRpXD17++dHPfnDopZ4qIgg9rqyHbBIrmx6fU/4NuMOVTFs6PXUd3JQ0I/v47qS74gIAgIAt2NQLcQkBNOOAGjRo1CYWFhu/FnZGTgzDPPVNLZ9a635OTk4OSTT/ZOknNB4LBDwGrXYNHGZPxAOhfVLRGzeTI9lr5O50wHBpHWzcb9foykC1FavScRFlLVen15GngHxVtYTesLMv6eT1G/Z4/yrNZ753ufj+jrRlaKo/UevPP8z5lQ1Ceths0QetJd52yzaah21GKbeSfeLP8QV/a5AL/pdwXt3GjAq7++K8DJ+O/wf+D67Xcq6lL+ffM1x+e4Z/htmJNGALfIMwdfCUk+1HJd9fnYwRdQ6ajChJRx2NgUnPR491dsPYCrttyCvZb9aGiJ85FjyILNZSfXu5HtSAxJKMQdA68ju5STcMuOPwd13ZukTcR9Q+/EaHcf6BcthOl7inxu9kx4fX/RvUca+tyZmYnmG38X97E/At6FTgfzgouR9ORj0JDXx+6Q0c2bML5hDdalTuyw+T5k+8U2XSKCgCAgCMQzAhoyoAx/mTKe70TG1mUIlJSURN0WezvLpMkEC9v4cHT7eBYmxOyJjXff4kF45f6/X2WhjAL9+UrbyuepEyn+xhp/T1O+pTtzlZnsIO9S/v17t+gZC5MQtvcIJOxggmXx2iY89TWft41fyfD7z0WxOTYOvhiNSR2rSflVbb28rOA83DjgmtZr/xPe0Xi97H18VPkldln2KtmpuhRMyByHs/ufiomJ45Di8NiR2GkCf+zas8B1Yi2FtBNSTCo3sZQJKWPxAMUoyXYnQb9lM6oObsXTpuX4PHkXqjSeySwbwB+fORNX9VmAwrU7YPrkoy6dcDdfegWco3s2CK2OyEReXh5qa2thbiFV4T4H7YH9SHj9VegqysOtElG5ZiJ+9w+4A7sShwWo5/l+ZRPh/+1J1chJ5YCV4Qk7fcnPzw+vsJQSBAQBQaCLEBAC0kVAHkrNCAHpmafJOx/3f5wdViwNLQUn83hMinbNOdQ9hiYLnppuxY3s3WdVIC+t/WRHJSBsz/Xlz8l4b3UqVdMQDXHT/54xq+eqgXhVxmehBhVW3sujHw0rhsfS2lV49MBz2NLsq/I1nibi1/W7HK+Xf9AuoGBYA+hlhfhZMLHIJduXsZYsnLfMjMkHfD0o1RucsA0vQsKZl8BNalLGrxfB9MVnHVDKyIGwT5gIy/kLIq/YhTU6Q0CUYbhc0G/eBN2O7dCUl0O/eyc0lNZVYiPVt0+yTsMXeaehyZ3Q2qxR78LUYWbMm9CAZBN/f8MXISDhYyUlBQFBoOsQEALSdVgeMi0JAemZR/nZ+hR8REbUHYs6wegO8tFx794lZo1swvlT29Si1DxvAsJp/9u6EQvX5SDVPF4tQhNYJ+ooLsfe/IfQnLilNb0zJ/Oy5+IvQ27zaYJ3M9g2QpUXS97EQ/ufVi/l0w+Bs/dk4i9r+8NE3pdYVDrqIm9PjhGjYFi5vIVC+lXs5KWzX380X39jJ1vpXPVOExC/7rUHDiDxhWfJQN/3O6Jiqn76Vevw0klPoOTMX6Fp3AykkHesJHcp9Dr1d6HD6j4FhID4wCEXgoAgECMEQulZxGgI0o0gIAgwAsvC9rPZ88RDfWJbS8JTBdtjWogNQz6FwZ6DBFshebtywWLcTUEBu1ZF70dyl8uyuWk7Xix9E8spqjkH/2Oj6XEpozAqqQgvl72jDl8+/RGgOew7g8hgn1bUH1kxkKa56n4VOaYidUojkQ+R8BFw9etHti23wLj4K+jXrYFWjfBOql6OoUVwDCyE6cuFERM6LdHC/u8/hoQhydAPG49SMp0SZerwn4uUFAQEgZ5HQAhIzz8DGYEgQBHMNeS5qfd9HRssbeo65bZK8ry0DuydKb8pD5MyjkAu2P4DqLF7iIbdUAk+uktqHHV4mozHHzvwgk8XNrddiVTO8TxEQiDA3JZIyOf96/Dp/jqceqB744h4j8SVm+t9ecicc1R367wzYD11HjSN5BiADNXdaRQ7xODZlXPn5iPh1f9FRELUJQjrK/+DjrxwiQgCgoAg0NsQ6H0znt6GsIxXEAgDAbb/6DrxVuzwPu+6HtSWkowu1FK07X/u/S8+q16sJrd+cqyI3w+8gewMujdYm9qhleJp+JMPNU8+w0Sg5VV8sagipgTEMe4Qn0iTsbdCPPweA7vxddDuiGFT5C6d3WWlcO3eRTpYyX6tyqUgIAgIAvGNgK+Pzfgeq4xOEDhkEUhNJONVJXoxE4bOimcGmZLAxuF83hVtBh5TVkYN5v98ZUDywTU4DsXFG39DButdSbACj4VTu+9Og/d5SOYQkGuzmmHVdp0BdSicnIUD4ehhD1ihxtfdeba5J5FaIitWRS7O4r2RV5IagoAgIAj0MAJCQHr4AUj3ggAjoKNv4si+7PK16ybqLpcGRxZaurRNHqu3bDyQCHdN6JVrBxmbv0PBA/VoU9fybkPO4xABeg3ddNQa23s466rRqpNtV1Y2zBSAkIK4dFXTva4dV5++sJ41P6px2z98H5r6rrWlimogUkkQEAQEgQgQEAISAVhSVBDoTgROGtdIzfO0TJ2adaY3NwUT1ODaOTVYMK0OORQfoDtE70rByOJHkN44rcPmmYiI9BIEWl7DDFsXkMakJOjGjGt/46SSZJt8FJqu+y3c6bFR0Ws/iPhJsR81VbETiXRE7qoqJDz7FGCzRVpVygsCgoAg0GMIiA1Ij0EvHQsCvggMzbfj1PGN+GRdOK54feu2v6L4DhRQkBeVJwyrRHHGK1h6sASu9X+molraZ+m61WYN7WwMPfBXrCs6FS5t7AP3tb93Sek0AvR6HFGd2OqKN9r2nLl5SLjhRphIxcpVU4Oa1avgbmyCOyUFjsFDyHbBE/gx2vYPtXr2GTNhXPIttPX1Ed2ajtxgGb/7BrYTToyonhQWBAQBQaCnEBAC0lPIS7+CQAAEmICkJriUwH1We+c2KEf3tWEZuaG9c9c/wN6hWEamnIjMxpkBeu5ckslRgKz6uajM+Djyhmi1vajehO3pQl4iB68bavDuBxGQS3bmRN24MzsHtuNOgGP8BCS1RNnWZmbCecR4OJ2yExYUWN4VIhKR8O7byj5oJMsEhhXLYTt+7mGtyhYUV8kQBASBuENACEjcPRIZ0OGOwLEjmzFpsBlr9ySguMpAqlRa5GVoMXGYCY98AtQ1d4SQJ0p57sBVuG7bH+Cif6rsz/0vMhpn0KV3hAc1t3OfaU1ToiMg1O3OVCtSbVo0kFctkR5EoIV8zClJw5nFmREPxE0TaPPFl8F5GBuURwyaXwVWxdLt3QPD6h/9ckJfcrBDTU013GRTIyIICAKCQLwj0Lkl1ni/OxmfIBAnCDhpXt1o0cDFE7wwJNnkxjEjzFgwvR5XzqrFedMsmDQMuOl0UqDSdNSIBvMm1uDfZf/wIR/cbWPSBuwpuL9LVbDU20ltnuCxXFYTwv2kZV4Oup2u2ht0dHvhttuT5egeOKJ4nrn9Go+uhzjW5KpUrN95CR4umY1EZxDbDnoWv9ifjv+0BCGMBEI36fuZL79KyEckoAUpaznnfApSODBIbvBkjdkcPFNyBAFBQBCIIwTa/3WMo8HJUASB3owAk42VOxPx3dYk7K0wkEqFRiEPwwtsOH5ME8b0D0/liIMU/nzAgGqaW7ho8nrKRDuWbNKhztx+Eqkjt6lMXj5YnYnB+Bz99JWoSf0aB3KehtV4UIGzNPsV2PRlGL7//2hE7duIFvMk2xAM3/cgtg24iTZYImQRVHx/ih2zSlLxbR8K1sbV/fVPAqVFO9jurEfjfJgm8BzEz0U3so7c2e5NsUJPXsmK6hPw7sAaPDe8IqoRsFOqvs1G7EkNYXCs4qR+Uk+TKpPx+LJCJNt+wql0fbRpBF4aWonvChpQkmhHikOLsTVJOHdPFo4pj84GyXwJ7XwMHxHVfUklPwSIzDmHj4R+716/jNCX7tS00AUkVxAQBASBOEFACEicPAgZRvwjUFqrw9ZSExrMWprkuzA034bC7MDepdgD1dNfZ2LzQVPLjfFskAgEfWwpMSnHjOHNuHBqHUhrJaC4qeyijcn4ZH0KfO1BjNDRBH/cADMSDW5wNHINTXT3VhnRZNWi3msR1OjIQX7NucitnYcd/f6AqvSFSl82ikbeleSDG3XTv+yGE9Cv8mocyH064D0FTWwhGxftysY4mgg/NaIcNp0HM7UOX6bQLkmdKc5tCOheRhDRYGFz/4nVycqh3sevthrwaf9alCbZ1aSwP59YNhgzylLxQWENPh5Qi+1pFjjoXRjYZMKwOpNCTH7MaaQ0apKOUbUJuGB3Ns6nQ89+dVskx2rAzZv6KIea1plPF3mxco4e25kmpK4fAo5hRTB9+QV9q9pzcb+iyiUb/LvThIAEwkbSBAFBIP4QEAISf89ERhQnCNhpnrtiRyLW7EnEbtrBsNIqsb8MyrGRmlQd+mf5EpHnvs1oIR/q9EGd/KmfbizdlkQEwoX5U2jFP4C8vDQdy3awlyDfiTgXdVLSz/sSMba/BZceU4v7P85RyEeAZpQkrTsBRfv/hWTziyjOfwiJ1sJgRaNOZ6sSJiFMQEqyXoZL58WEwmzVSfDcuLlAMYBe3KdOsQ3hifSgBhOOJ7uEZr0LVx6zi3YUQuwAhNmXd7GBDUZlgr6Hdiqc7R+zd9GwznmcwSTTpsezSwfjyhm7URYBCRlbk4hjyzwTzPnFWeAjkDAhqTU6kGrXddqLVaD2A6XZp7FdkUhXIuAaOAgcoFEXZqBB+7GzurJ7aUsQEAQEgW5FQAhIt8IrjfdWBPZWGmgHIwPVTaG/InsqjfjXJ9m47sRqDCM3uizr9pqwYT+vgKvkQ0n2+4+JiFvZ4ZhWZEafDA+B4R2S0lo9lhPxaSMfKmnxbsJTn/t5YrEWtc0dq1KRAhj6VV1BRujTUZ7xvndjXXbOJETnSkZ601TUpH0dcbsDm4xKnWyapJ+7N4AxLWmtvb9oOP47sgxvDK7qMqP1y3bm4lLy+sQEalVOE1bkNqKG9J0yacelwuTAq0OrIrqXArMhZPkR9Yn4mO7jz0cewCe0k8EkK5Sw3chd6/qFKtKaxzsdvMMRrYR6awO16ew/ADZyHyvS9QiYz70Ayf99GBoLBxQNLo5RY2CfNCV4AckRBAQBQSDOEAg9u4qzwcpwBIFYILC/Wo8HP8+CLcCOR6D+bbRk/hSpW90zvwKJRjd+2K7GNuhgVkmzTp7sPftNBiYPMZPqlA6rdiX67WSEasNDQvYQWWIyE25sj2TrCPSpuizQrXRZWoIt8h2WwkYjhtPEvCNJdehwx4a+uHVDH6wn+4rbJxVjd1r0OyLZFr1iMM79MoZHVaYohzqO7akWDwEJc2Y+ktSe8iwdEwDeCXl41UAcV5qK2yfvg/K6effRcm6gbaH7Vw/AJFLlioWEeuP8++dYHhbyegVDx/frX1euO0bAnZuL5l/+BokvvwRtZXu7ISbMhllz0HjiL0jfrwu27joekpQQBAQBQaBLEBAC0iUwSiOHCgJsd/HS9xlhkw/1vhvJDuObzcn4xZGN8BACNafjz4O1Bny4JtoJXLi0w3ccCRS3w6FtIMPo6AyOfVtrf6V1R2Cn0TLRvnFTQfuGQqSw5QvbV3z61UhcNWMXfsinSPItbYWo5pPFOwsPrSTj7GBeoah0UUMCTjiYhq/6dhAcrqXvX23J9+mjo4sz9mVhZF0iHhxTim/IKJxVqFh4J2M2GeXftLGAbEo6JmYd9RNufjgQchkrxauwS9yJcGGNupyroA+abvod9D+th37zJmyw7cSLffZgeUY1KrXNyDDswRG7VuDc3Hk4JuOoqPuRioKAICAIxBIBISCxRFv6insEtpUasb86OjKwvjhBISActyPimXCMkeGVU43Lo+6knNNkPpB453mfByrrnfbQGieW9SvAs0XlZDROs/xQQl1fuiMHp++LPO4EN2ugifqzS4fQBL4Ez1PUd7uf8TrP573sr1tH0q/JgAd+LPTZ7WjN9Du5d01/bE7fjgPJpGYXaIbeknbu7izF+5Vf9Q4vmWCwgXmzzon9yZ7dnP6kjpYUghh12GiUBbzfBO9bVc/dej0s510IxxFHRtmDVIsYAZ0OjgkT8VDuOjxb8r1P9Vp7Pb6rXa4cv8g6Dn8efAuMWs9326egXAgCgoAgEEcICAGJo4chQ+l5BJiARCsVDR47jMwkJyoa4vurpdhqwISyjLeRX3tO0FvmcsV5/1GCF6Y1Twpazjsjw16DcY1bMWFrPq7elouleQ14vqgSK8muwl+rjWN/3Ewr/Bftij7qNvfNJOQ2Usu6ZlsevstvwL5kcntLacPrEnBEdRIW0e7F6uwm1JFdR45Vj2nlKTjxQDqM7vDUVrLJpuLtr4vwuynFWMo7LX5iIBe7v9qah+s3R7b74deMQjjCUUPzr9fV10w2FJUeVq2ytriLpnM72RpY554IN3lcEoktAs8cfIXIx2shO/2serGS//ehvw9ZTjIFAUFAEOhpBOJ7ltTT6Ej/hx0CDQFia4QLgk6rTNswqq8FFVtTwq3Wo+Wq0xZTnJBvMbDsJiRSHA9vaTbuRHHBg5T/DeqSl2Ps7pcomxWfvNfIvWqw/hrFL7ig4jXo4VHB4gn+nLJ05ag3OLGEyMgeinrOmxTDyFXtDIo5kejldsqDYIc22V6d+p6yXcUZAXZSzt9Drmjp6IzkEgl58fuhWJ3VhMV96pWdChPZZ7D61Cn7M1AQht1HZ/qPZV3lCVPQmcabbyPf0fQs6cG4ydUuaCVeJPYI7LMcxBMH/hdWx0xC5uXMxbT0yWGVl0KCgCAgCPQEAkJAegJ16TNuEUjqSF0oxMj7tniyQsFiuLdyuDeOAhFksh6inWizIlGRUvuw66vRlLhB8ViVaBlGJGSwkmU27oI5YadajCKo/4Sdfe/G0IN/oTQ9zUcDGL0T+Tim/i3MqF/aWs/7JI3cwnJwvlDCaFlOOQ2w25Dw5cKA2k6h6scij43BY2UQHov7CdWH20g7gomxsz8JNZbDOe+Dys+J0odvV/V2xSdCQA7nF0buXRDoBQgIAekFD0mGGDsEhuZF701pCnmy2llmwLfLphPtiP1KcSRkhwmEk4zQmxI2t4JrTthBpGNH67X/SUXmhzCbdtNuyS1I9VPHajJtwz5S1dpsWoJTa4ejP0XrjkasxxwL+7GzPVVNCTB9/KFyzjsjsaNynu676//eci8cXFDIR3e9BZG1u75xU0QV1jdsjKi8FBYEBAFBINYICAGJNeLSX1wjMLqfFTmpDlRGaMORQtG5N+wz4dVl6dAEsniOs7tmslKa9SrN6sNfVeVbaEz6GRsHXw6DPRdJ1qF0rzoiJcWwGve13uGfxu/Hsz/4qnO1ZnZwYp9+TGsJO5ERJ7l5NS5eBP1WIkoOT6yU1gK94MTNxsPDRyjkya3VwZWfD+2+Yhi2b4v70dvJ6FkkPhCod7S3Owo1sgZnZOVDtSV5goAgIAh0BwJCQLoDVWmz1yKg0wIXUWTz/yzMgrtDItG2lt1o1WE9RSaPB3FqzGRjEXgsquqUxbgZB3KfDuzRKYybsBsqUEdHOyFIvu1Ddh5kBD6oydQuO1SCc0Ah3Fm+0b1d/frDcsllZIfggqa+DokvPAddaUmoZro8z0UqSFqzOeJ2XWnpaLr+RiDV19WxpqoK+of/Dxpb5Ltt6htnOHM+LCuWQVtS0i07Qzx227FzIr5nqdA9COQas7DN3KYS2VEvOYbO2Tt11L7kCwKCgCDQWQRouiUiCAgC3giYMnZid+FtpKLU5J0c4JyVgnhKGD/SZNqKn4aeg2ZTYFUq3vmoTV6KnwdfhWwr7X50tV5TS3vs8SpcYQTdZD9iZduPYEJB1twZmTBfeTWcffoGK9Ul6d5P1EkEyDF2XMTturKy0XzdDe3IBzfkzs6GecEl4N2RSIXhdZ18CkxnnQ3zjb9D829ugGPI0A7fQu97YqwDiVrGRYTJfPlVQJIaUDNQaUmLJQJHpU2IqLujIywfUeNSWBAQBASBLkBAdkC6AERp4tBC4K7d/0RJyhZUDluJPtWXIrPhWJjsfeGCBWZjMRz6WmQ1zqFJXwBD7B6CQh3LgZxnYDHtxfqhZyOn7hRk1R8HjkruJlUrM5GSyvRPUZv6vcKbamgemuDQwKJXp55dN/gacncbiVhpQs3qVh2Jm1bmm399PYxLl8CwcgW01VVKFb6DwNPqwC2q5d1JyUi85lo4qC37+nXQNDdTQxo4+/aDfdIU2I+eCuM3HtemgVsKnNp8yeXgsQYT58hRCnlIeuxRaBwUWyQMUUga7XwY5hzfWtpFu0bma38FTVUlEt55C/pd7VfJnXn5sM4/B878AqUvd3IK9GtXw/T1Yt/o2uRm1zZ+ImwnngR3alprH3LS8wicmXMynt3zPOp1Hbwr9GLzquJFOWf0/KBlBIKAICAIhEBACEgIcCTr8ENgbcMGbGjaoty43VCF4vwHlcMbifHbP1UuIzH69q4f6XljwiYY7XkwOnMCkh6VfJRnfICqjM88zRPhqMz4SDkC9kezdQctwN+xrgD/GV2O+ggJQ8A2vRIzKb5HOMJEwHzxpXCOPSKc4p4yPFGefZxyoKkJGqsFGlKRSnj9VegqysNqh8mKY+gw6Igo6AcPhn7iZNjq69FYU0NOvuhnkXZcVHHSDkMkwupL7j59OqziIpJjueBCJL78krKDEYxAqWTJcu4FcEychEBhMt3ZOQoR0ZaXQ7djGzQN9XAnJMJVOBDOgYNa78cNj2qeg8gVH5rqamhJtY29Xbk4tgfH/RCJOwQy95TivpX98Oupe4Iz7ZYX5Zaf+2CkoxT26ZG9t3F30zIgQUAQOKQREAJySD9eublIEVhRvyYYRadQAAAzEElEQVRklQTrIHJVWxiyTHSZ6jSTNyc8OysO8lK1q+89qEr/nAhIPor234+05va+/cmfFQ7kPEdeqB6JuOuBTQn4YuEIPDi6FG8Pqoarbd4dcVtKhZbbOKoyvDgo9mnTIyMf/qNKToabD0pvvvEW6NethX7TRtoZqaSYFXoy+i6A/cjxcJtM0O3ZTUSlGe6UNDiHDYOroA9SUvzGyW5n/cQ5aLCi9qUrOeiXE/jSPn1G4IwAqQ4iXtYTToTpq4UBcj1JTEysc09SyEfQQi0Zrrw88BGusM2N08/uJty6Ui52COjXr8WJB9Px+LJB+P2kfaglpxf+YqJgmLcR+bhsZy4c1rVEQMJ/D/3bkmtBQBAQBLobASEg3Y2wtN+KQDMFVP54UzU27rPBbDci2WTDhEEJ+MXIDBji5E2ssHtUerTORCTYB9DYSUXJsA8uHanmUFC9wrLftt5PV52ohENtz6ltpJ2Lj7Ev9zFS96IVeRKboUzxPpXWdBSphM2CydaPyIIVzQlbUZn2GWzG6Ayz88x6cIC9v68dgFs29sEdk4vxNRmRRy00W55ZmopBjcEN0FWq5aCVeesp86Luql1FHXmcmjRZOdrlUYKLdwKiEVLJspxzHpIeZ3WpwJ641HtiQ3rbMcdG1IuNCIiL7FpMn33iqxJFrbhycmH9xalwjBkbUZtS+NBCQFdWptzQ3JJ0TP08Be8OrMayPPqdMDmQTruNk6qSMX9vVmswTF1Z6aEFgNyNICAIHHIIxMm075DDVW7ID4GPfirDJ+sGQ+tqU01ppHnu57RQ/dnaCiyYVo6Zw3w9IPk1EZNLk3koRhT/BxkNM0mX2qOO4oIDdSlL4dLYkN0wt8vHwapcNUlLsS//USI6TbCQnYlbE3iiW5+8Enx0hWRZdBhFUbxVyaYo4k+T+9ytaWZ8U9CAg0nkpYlm1kvzOXp5eB6beDL053X91CaVnQeNlZint5B6k23aDFjJmLq3qPywNy7zVdci4ZWXoG1sb2CvqHQNK1KMyxUVLu/7DeOcCQYfWvLwpW1RI2OVKN6lEREE4Gzb8Ugl3Une5eAjkDAZZq9xIoKAICAIxDMCQkDi+ekcImN7bUUxlmw+WjGODHRLGmcuXv0+C1b7TzhhVEGgIgHTGi0abD5oUmJ26HVu9Mu0Y3iBDfrwzA/atfnjrgQUr7oaWS6dogalFuCggpmNs5RL/90KtUy0nw5tPbnDfQYHs5+nzRZl6hBtU5563EQwYwK15ZYyV28nVR0ywgYbXnvJiPpE8KGKg8b1Nq24vjqkEpsyLEHb799kIBWRwRjY4n5XM3QoGi65Arq9ezyuc+12uFjlZ/hIUoPyU31SO4vjTzaSb7r1DhiWL4N+8yZS86omAqVX1LMcEyZ1yS4FEw4hHXH8EvTQ0Fxk46M7sD+s3vnr76TyIoKAICAIxDMCQkDi+ekcAmMrrmrEt5snBCUf6i3yJP/tVYNx1OBGpCWEZhB2Wgz8cE0qvt6UBBepRXlLssmOonwHLHYtzDYN0hJdGNnXiqnDzEg0Bp/g7y434IUlGdSeZ/bubWAe7Ny733DPm4zbUZLzEhV3U/C+g2hIXEOaXYF3O8Jtk8sNaTCSKoYea7N9yUS7NlrIx9TyZFy5PReWSy+AYe0a6H8iD1DtCnsS9ITJBXuylcNBvsDeG1iDhf3qsSPVAofWjYGkbsX66efvzoJJNSKhHQPd9TcBFgucI0YqR5Dme1cyRWe3z5qjHL1r4DLa3oyAY+xYGOg7Gq6Iyl64SEk5QUAQ6CkEhID0FPKHSb/Pfb+fyEdRWHerdWUQCViFG+YG13dn8vHgF+nYU56k7FL4T5qbyJ5hXbGvJ5+f9yfgk/WpuOyYWowb4KcO1DKyl39IayUfYQ02ykI7+92NJoom3iVCZGJogwkX7M7Ggl3ZyuR/Yd86vDmwCstJPzyge10C7Ky9mfjL2v5gYmEjj0+WBRfDmJsL06IvWeMqKBHhMevpaZ67N1s5At2DWl///8g1LMeRIAIiIggIAp1DgJ0VcPybcBwhuMgpg23GzM51KLUFAUFAEOhmBISAdDPAh1vzDjLS3bhjJ+1A2NA/NwcljYNobyN82VYV2g7k9ZUJCvngFr13JjrqodmqxROLMvHL42t8SIiDCM3Dn7pRUtve+1FHbUaSz6pbLg3FEUnYFkm1dmVpwwFHVaTghINpRDyykEDqYt7COxF8sHyf1wAmJMUpVujIQ05RfQJO25+BsbVM3jyiuF6lUxt5WeL4F6o3JpVItBQL+4MJIbu3NYjtQtiYSUFBoEMEyG7KfPFlSHriv9Cyi2Wq4L34ol6zO2XLJZcDiW0qlB22LQUEAUFAEOgBBISA9ADoXdHlqlWrsG3bNthsNowZM0Y5kmnlq6dkD7koffyHStQ0HQ29a6gyDDba1rozIxqSzZlJOxFACQWYSyP7hNTEhNb61Q0aLNuaRn98owsAyLVe+j4Dfzm7XFHHclM/933owqa93f/HmskSBwFkz1WdkdG1iXh5iQffjto5pjwVfAQSnrw4KUaEOyOjNZu9MXHMC+PXi6DbSZHUWwxZeVJDL5rPhKe1kt+JOyEBljPPbok24Zcpl4KAIBA1Au7sbDRf/1uYPngPho0bfNpRiD95eeOAnmJD5AONXAgCgkCcIiAEJE4fTLBhVVZW4s4778SmTZt8iiTQxO/ee+/FUUcd5ZMei4uv1qzHmxuYeEwiFZ020bgNNGn1Xqdrywt2prMPwm9eZKrg8f7j0NSSjUQzXRuhc2bRpzbCFn17aqKdkNveskOjq4aD43m4YkPabPoKitPxH9/BRHE1oywwoVBXQJ0ZmdDVelz3Bmuey7IoXqg8p63/MwExc+A9MhjnYHYg8uFOSYWGPDMZli6Bcc1qaIiMBBIOwGe+9HK4SZ1LRBAQBLoeATd9x3iHw0oLNJn0ndTUN0CTkoyazGw4C8J34NH1I5MWBQFBQBCIDAHv+WJkNaV0zBGwkjvT3/3ud9i5cyeKiopw7rnnIj09HUuWLMHHH3+M22+/Hf/4xz8wderUmI1ta3ExkY+pRD7aVtLVziMlH1yPCYa36N3UrrN9295lIj13cnwPJcZHpDWjK2/Vl2LLwF+DI6t3RkxODS7ZGdi7DdM827GzKa7GaTC99TqMq38M2ZX1jLOU3Y6ghSgitjsruzXbTS5hbbSzYZt3JgxEQjgwmra8TNklYQ89bPRqnzqNCEvw+B+tjcmJICAIdAoB/m7qR46CTudRwXSVUtwP3tIVEQQEAUGglyAgBKSXPCge5ocffqiQjwEDBuDRRx9FEhv5kkyfPh19+vTB008/jaeeeiqmBOSJ5eaA5EMZ2CH6XzAVMP90i2E/qV19jIM5L8Cpax87IlJ42HC8wOJrYM9tuMkzk/Wkkyny8TFKk9ZzLwC7jDUt/ALa+jqfbpxkm2E9dR6cRcN90sO+oAmPfcpRyhF2HSkoCAgCgoAgIAgIAoKAFwJCQLzAiPfTd955RxnivHnzWsmHOubzzz8fL7/8MrZv344NGzZgLLlt7G6pJRUds3ka7VpEZ5PR3ePr6vZVghFsZ8etsWNXn3tRlbaQAglSzAttAA9Qqq5UoMEFyUshl8JMPk7f12ZP40pNVUiGg1ZBHaPGtDM6dUw+Co6Jk6Gl2AHaKtp5ISNWV34+HaKmEQh6SRMEBAFBQBAQBASB2CEgBCR2WHeqp2oKenbgwAGljblz57Zry2QyYebMmVi4cCEWLVoUEwKydtdeMjIf0W4sh2oCE4+alG9RkvUa8mvnI6V5HHmXSoHNUI665B9Qkv0/JbZHyPsPZRJDeUPrTRjQZESjwYVMqw5HVabgzOJMZFKMDxYDqVjZZ85CE3ms6lCYdAwoVI4Oy0oBQUAQEAQEAUFAEBAEYoSAEJAYAd3ZbrZs2aI0wWpXOTmB7QAKC8mommTXrl3KZ7D/KioqFO9ZgfINpPuv6hUHyvdOa7aRD9vDSKpTF2Fr/5tpN8GJutTvo7rzSRVJuPOnvkrAwHVZzTiQxN6lNBhG8TxO3ZeB6RWBjcy5Mw3FATCefS4cZAuka2qKqv9YVwr3XYr1uNT+tETSVNEQqYv38fJYeZws3mNXEuL0P3W8PLx4x1fFtLe8C+ojZ1zdUdqAeD8ftT35FAQEAUGguxEQAtLdCHdR+zU1Hs9GGV5uU/2bTiW1HBYmGKHk2muvbedFSy0/atQovP/+++plyM/xQwfik40hixwymVZdOalX3aqQj2hv6qiKZPzvu6EUF0WDI2qTcdnO8FvS0HNPvPFmaChwYDIfPehyOfxRA3l5eZEU79Gy/P1Rv0M9OpAwO+9N2Kq3lE2uZHuDsHOP3iS5nfA8ZyePdyKCgCAgCMQaASEgsUY8yv6am5uVmmlpaUFbUPMsMYo+PXnMaDg+2wu9fWDQMakZqv2Eet2bPimEICpz/4JFXw7F8txG3HvkQdQZI9v9yTfr8ciKgQr54Hs3zDuDworr4SbVOg4AqMmk+Cd7dsO5bq2vNxvK0085GsaLLoaWXOyKCAKCgCAgCAgCgoAg0NsREALSS54gBxxkUT1fBRp2Ykv0245WtPr3749gJIU9bHVU37vv6f03YOXugR0GB2Q1I6e2nmwmghMo73bj5dwFGw7m/xEvlpkw8Jd/QN9HHsIJJen4om8t1pMKVQPZaph1LizJb4BdF9gNZr8mA55eOgTZVo8HK+3kKdCSG1x/YWUgXX09XNu3Ag3kNSs1Bdphw6Gh1Vi3l6qQ0+mkGIEu/+pxda2q2vBY41lY5cZ7rPGOK2OpjtnhcEStdhPLZ6Inoq2q+UTy2xLLMap98Th5vL3hO9ZVuPK9suqtiCAgCAgCsURACEgs0e5EX6rqQmNjcHeual4oksJDeOSRR0KOpKSkJGS+d+blsybip/LFsDQdF5CEqDsfDsNODEpdgf3VCwKW824zXs5tuio051yK57bmI+uq21Gdmgbtr65H8gfv4ty9e+loUyfZR7YcT44ow1d961GZ4KBdDGAI2XWcTnYdV2zPRbLT46/fPmEiLGfMByigZFAZOLgti9UjqCw/U1UtxGw2o6Ghoa1MHJ5lZWUpo2LnCfEsKSkprWpXTWRXw0e8i/oucFDSaPX+Y3mPbLOmTnBZlTSeSSmTUVZt4+8Xf8/iWXicKnmuIk930b4LTGg5kK2IICAICAKxREAISCzR7kRfquF5Pa2QBxM1jydVsZR/nlWEv3/yIQ7WngSN2zcQHe986JOW4M8nZCItYQpu+PAH6C3T45aEqITJYjiAsa6b8YfSo2G96ny4iXywuPr1Q/Ovr1eC8GkpCKPGaoGb1OIyyb3tXRT8755Vm2CtLafYKBqQOb9Sx52aDHvhQNiPmgrnsCIlTf4TBAQBQUAQEAQEAUHgcEVACEgvefLqDohKMgINW10Vj7VxKqsC3H3GFOw+uAEf/rQfB5uT4XRpkZXQhOOGJGPq6FGtw733uGrc9fVCaM0ntqZ15kQlDMHa6Ci/fT0XatI+wsXmzzFvzi2w9B/QvgiluPIopgYd3mL7xangg4UVj6zKmfwnCAgCgoAgIAgIAoKAIOCNgBAQbzTi+Dyfgsjxdjsbo+/evRuDB3up6bSM++eff1bORo8e3SN3MrhvX9w+ZAgyyaCahcdaV1fnM5bcvEI8Pt+ON757GkuqCtDsGAydM4f3SUhtiewaKIAfQCpMdK11p5HNSJtbWidIJULjovREKt/mPtVu/BkG3S40gzwuuXLI1qQBFuMOajcXGU0UKNHtUS8IRkacRBWsCRuQZPgY0/QHcdbI05E64k9kei4iCAgCgoAgIAgIAoKAINDVCAgB6WpEu6k91vueM2cOvvrqK+W45pprfHpiXfs1a9YoaVOmTPHJi7cLDRk8XnD8abiAB8bG1E4ysDeoBtxMLIwtQ25Ecek2lFTXIo8MsQeT+hNLWeVObCjeD4fLjRF98zCob39KpdgoRHg0FJ0dSclwJxLxIG9gVeZN+IlUpSx2JwpTdNCSVpReSwEFrVqUNjmRm56KY44YC4c5l8ZwrdK+/CcICAKCgCAgCAgCgoAg0H0ICAHpPmy7vOULLrhAIR/vvvsupk+fjjFjxih9sGeZBx54QPGMNH78eIwcObLL++62Btm7k5eHJ/9+Cgv6gg9vyc/JBR/thEiamw5V3GQLk0XH7Nw+alK7T46rwipklY4QRuHtakmCICAICAKCgCAgCAgCgkC0CAgBiRa5Hqg3YsQInHjiiVi4cCFuvPFGhYRwAKrly5djL3ll4jggt956aw+MTLoUBAQBQUAQEAQEAUFAEBAEwkNACEh4OMVNqT/+8Y8YOHAgXn75ZSxevLh1XEceeaRCSgoLC1vT5EQQEAQEAUFAEBAEBAFBQBCINwSEgMTbE+lgPBwo69JLL8Ull1yCffv2gf2/9yPbiFh7vupgmJItCAgCgoAgIAgIAoKAICAIBERACEhAWOI/kYkI73bIjkf8PysZoSAgCAgCgoAgIAgIAoJAGwJtvkzb0uRMEBAEBAFBQBAQBAQBQUAQEAQEgW5BQAhIt8AqjQoCgoAgIAgIAoKAICAICAKCQCAEhIAEQkXSBAFBQBAQBAQBQUAQEAQEAUGgWxAQAtItsEqjgoAgIAgIAoKAICAICAKCgCAQCAEhIIFQkTRBQBAQBAQBQUAQEAQEAUFAEOgWBISAdAus0qggIAgIAoKAICAICAKCgCAgCARCQAhIIFQkTRAQBAQBQUAQEAQEAUFAEBAEugUBISDdAqs0KggIAoKAICAICAKCgCAgCAgCgRAQAhIIFUkTBAQBQUAQEAQEAUFAEBAEBIFuQUAISLfAKo0KAoKAICAICAKCgCAgCAgCgkAgBDRukkAZknb4IlBfXx/1ze/evRvfffedUr+oqAjTp0+Puq1YVNRqtdBoNHA6nbHoLuo+Nm/ejJUrVyr1x40bh4kTJ0bdViwqMq4sLpcrFt1F3cfatWvx008/KfUnT56MMWPGRN1WrCry+8r4xvs7q+Lx0Ucfobq6Wrk866yzkJaWpmbF5adOp1Pe23j/0/jmm2/CbDYrGF544YUwGo1R4cnvUkpKSlR1pZIgIAgIAtEioI+2otQ7dBHozAShuLgYjz76qALOOeecg5NPPvnQBSqGd7Z169ZWXK+99lrMnj07hr0ful0xAXn88ceVG7z99tsxbdq0Q/dme+jOXn/9dWzbtk3p/fTTT497AtJDMEXc7fPPP4/Kykql3uWXX47U1NSI25AKgoAgIAj0FAKigtVTyEu/goAgIAgIAoKAICAICAKCwGGIgBCQw/Chyy0LAoKAICAICAKCgCAgCAgCPYWAEJCeQl76FQQEAUFAEBAEBAFBQBAQBA5DBISAHIYPXW5ZEBAEBAFBQBAQBAQBQUAQ6CkEhID0FPLSryAgCAgCgoAgIAgIAoKAIHAYIiAE5DB86HLLgoAgIAgIAoKAICAICAKCQE8hIHFAegr5Q7TfpqamVp//ycnJyMrKOkTvNLa31djYiJqaGqVTdreZkZER2wEcor3V1dVBjXvDmIor065/0KWlpbDb7UrDffr0gV4v3t+7AuWDBw+2xoLp16+fEhumK9qVNgQBQUAQiAUCQkBigbL0IQgIAoKAICAICAKCgCAgCAgCCgKigiUvgiAgCAgCgoAgIAgIAoKAICAIxAwBISAxg1o6EgQEAUFAEBAEBAFBQBAQBAQBISDyDggCgoAgIAgIAoKAICAICAKCQMwQEAISM6ilI0FAEBAEBAFBQBAQBAQBQUAQEHck8g7AarXi2WefxfDhw3HCCSeERMThcGDVqlXYs2cP2DPTgAEDMGHCBOTn54est3v3bmzevBn79u1TPGNNnDgRQ4cODVnHP3P79u1YsmQJxo4di6OOOso/O+6uI8E1WnzUegcOHEBSUhIKCwuV55GSkhIQj/LycuUZBMxsSRw2bBjS09NDFenRvO7EtbP4lJWVKe85v6vsUYu/U/yu9zZZtmwZVq5ciauuugrB3iX1ntR3MJLvdrS/I/yer1+/Hvv371fe0SFDhmDSpElx7QFKxSfc76iKK//Obtu2DTabDWPGjFEO9iwYrnTn9yTcMUg5QUAQEASCISAEJBgyh1H6fffdh6+++gqnnXZaSAKydetW/P3vf8euXbt80DEajbj00kuVQ6PR+ORZLBY8/vjjePfdd33S+WLOnDm4++67w3LL2dzcjD/+8Y9g15Pnn39+ryAg4eAaLT7sOvbhhx/GwoUL2+GamZmJ66+/HnPnzm2X9+abb+KNN95ol+6d8M9//hPTpk3zToqr8+7ENVp8XC4XnnvuObz44ovtsGKCzu95Tk5Ou7x4TGDydNdddykLEwsWLAhKQKJ9d6P5HWF8n3rqKbz++uutrmdV7EaNGoXf//73GDx4sJoUF5/RfkcrKytx5513YtOmTT73kZCQgHvvvTfs377u/J74DEwuBAFBQBCIAgEhIFGAdihV4QkTk4+OhOMl3H777aiqqkLfvn1xyimnKDsRq1evxmuvvYZnnnlGWYE/99xzfZr685//jKVLl0Kn0+G8885TVitra2vxzjvv4Ouvv1biWdx8880+dQJd/Oc//1HIR6C8eEwLF9do8HG73fjLX/6CFStWIC0tDRdddJGy0s47Uvwsv/32WyWfV679iQRPLln69++PYKupwdLjAefuxJXvL1p8+Dmq7zN/N6ZMmaK8r88//zzWrl2LP/3pTwphjPcYGDz5veOOOxTy0dHzjubdjfZ35OWXX8Yrr7yi/I4ce+yxOPnkk5XYIpzGO6u33XYbXnjhhaDvdEf30tX50X5Hedfid7/7HXbu3ImioiLw7ynvRvLO78cff6z8Bv/jH//A1KlTQw65u78nITuXTEFAEBAEwkBACEgYIB2KRSoqKvCvf/0LP/zwQ1i3xyvDTD5Yberpp5+GwWBQ6rH6AwfB4tW2J554AmeccQZ4R4Tlu+++U8gHnz/wwAPKpIzPWY4//ngw8XjvvffAKj+nn366JyPA/9zOJ598EiAn/pIiwTVafL755huFfCQmJirEj4O7qTJ79mw8+uijyi4H72Qwvt6iTrB5JyveVoy9x+l/Hgtcuc9o8OEJMJMPrVarrFAfccQRrcOfPHkyLrzwQvz000+K6qI/IWwtGAcnn332GR555BE0NDR0OJpo391ofkd4Us67Syy8C+qtJjpjxgxcccUViloht83n8SDRfkc//PBDhXywait/j1mtkmX69Ong7zn/9vJOUDACEqvvSTxgLGMQBASB3o2AGKH37ucX1eg//fRTXHLJJQr54OjP3hOmYA2y2gQL//FXyYda9qSTTlLUqFhX2Vs96/PPP1eKcD6vCHsLrwRfd911ShL/QeUVw0DCK7L333+/stLPf4TjWSLFNVp8WDef5dRTT1UmJf6YsDocC2PHKmuqsH0CTy5ZlYNtRXqLxArXaPHhVXiWK6+8st13iXcLmWyzjdTevXvjEnJeWLjlllsU9Up+P2bNmtXhOKN9d6P5HdmxY4eidmUymXDcccf5jI3TVFVDJoLxItF+R3lnmGXevHmt5EO9J1Y95UUHJskbNmxQk1s/Y/U9ae1QTgQBQUAQ6AQCQkA6AV5vrfrqq6+iqakJRx99tKK2wAaOHYlqlMwGlf7Cq25Op1NJVlfs+IIN1Vl4FTiQ8M4H75awWoa68uxdjkkJqxuwLvWtt94a9zr0keIaLT68C8WkLpghPqtQqao+NTU1rZCqGLNqB6vE9RaJFa7R4MOTd94NYLx5ghhI2P7j7bffxgUXXBAou8fT2KibJ8yssse2B7zL0JFE++5G8zvCiyQsvBPiTajVMZaWliqn3r89al5PfUbzHa2urgYbqrOopMp7/Ey2Zs6cqSQtWrTIO0s5j9X3pF3HkiAICAKCQBQIiApWFKD19irslYf1jMePHx/2rfDuAxs8s2oBGzirkwJu4P3331d2MNiuwHtlnf+gsgQzvmWVFZ40qDsn7DHIW3g1kCdGPNlm1SL2ChPPEimu0eJzzjnnhISBV4LZyxDjy16CVFEn2CNGjAB7e2LbHJ7w8PPhNDaWjkeJFa7R4MMTYibKI0eOVHaWGD92mMAGxPxu80SUJ47xLEw8rr76apx99tkKCWHj8o4k2nc3mt8RVvHk35Xi4mJ88MEH+M1vftM6PF68UG3YWB0rXiSa7+iWLVuU4fN7E+w3U/199d5pVu85Vt8TtT/5FAQEAUGgMwgIAekMer20bjhG3/63xitvZ511lmJTwCu9rFbCk1smJTzhzc3NVYxXvesxIWGVC57kBtoF4V0YNkhn8dc7550W9p7Fqis33XSTd7Nxex4prp3BJxgIPBl+8sknlWy2z2GVDVXUCTYbRfNEzm63q1nKJ++IsaMBfpbxJLHCNRp8WM2NJS8vT3mH2TCbHTOoO4KsrnjNNdcoux/+HuLiBWPeSQu2mxZsjNG+u9H8jvAY+L1kxwvsBYvfX16UYJU2Jh+8gME2ZGyc3hsk2HdU3a30Xtzxvx927czCu87+EqvviX+/ci0ICAKCQDQIiApWNKgdhnVYVYr/wDH54BXejz76SPHqw+SDJ7lsMHnkkUf6IMMqVixsCM0r8v7COyeqsAcnVXhizJMN/mSVkHj2yqSOOZrPaPEJ1ddjjz2GdevWKavxvMvlLeoEmz3s8GopryQzvkwsWYWIvWr99re/DcsDkne78XYeLa7R4KNOBHkSzHgy+WCyzRNidg/L7zA/E7ZjOpQkWoyj+R1h3NhOjX9jeALOixrsFY9JNC9i8PvLKprxvtOkPv9g31H+XWVhz3bBRM0LZ5cqWBtqerTPUK0vn4KAICAIdAYBISCdQe8wqsurc/fcc4/iXamgoACsYsAeZ9irj9lsVgzKf/zxRx9E2BiaJxw84WW9cnW1mFeHmcCwZxvVoJ3VhVRhTy9seMpue+NVLUgda2c+o8UnWJ/shpRXiFluvPFGxV2yWpYnyDx54QkcG/+zBzS2SWB3pkws2YMZPysOJvfSSy+p1XrlZzS4RouPSkC+//57xZaJd58YW54Qs3MFXrlnYS9uTE4OFYkGY773aH5HuB57Gft//+//KbtMvIvCBv9MPHi3jhc4mOCpE3guH6/S0XeUxx3KlkXd0fTfvYzmfqN9htH0JXUEAUFAEPBHQFSw/BGR63YIcBAwnrSyDjbrcLOaifqHkAsvX75cUb9iVSk2Gj/mmGOUNtgDEE+E/+///k+xN2CbA54wsN42T/jOPPNM5ZwnF2q0ZVav4Ek0u4i99tpr243lUEqIBp9A98+E7t///jfYhScLPwf2kOUtTC442n0wYRsQJnwcb4GfB6sN9VaJBtdo8WGPYqrccMMNii2Nes2fHNyT7ZgYU97xY7W4Q0GiwTja35Evv/xS2RFlxwkPPvigjzrnL3/5SyXII8fI4B0sXryIR1W3cL6j2dnZyqvhvRvs/66oeaFIin+dYNfRPMNgbUm6ICAICAKRItC27BxpTSl/2CDAEygmH6ziwBGHvckHg8A+6XnyysKeWLyF3Uny6jq74eXVd/Zoxapa7PaTDzaGZmECwuoUf/vb3xSjXl6dKykpUfS8WdebD9VOhNvga16t7+0SCT6B7pV3n/iZMPlgNSr2uDR//vxARTtMU1Xo2GaHPQ71ZuksroHuPRA+qr0MT3pV4u1fV3UfHciDnH/Z3nQdKcbR/o689dZbCiz8G+NvS8YTcVYjZCLIqlnxuMsU7ndUNTzn37dgouapCzbByoWbHukzDLddKScICAKCQEcIyA5IRwhJPva0uNNljz7BDCSZYHBEdFad8hf2EMQr9CxsC6K6iOVrJhksgwYNUlxsqoSE1b2CCQdM44PHwqpcvV3Cxcf/PtkFLKv48MSLJyT33nuvYtvhXy7ca1W/nFeqVSPqcOvGY7locQ12L4HwYeNzFiblwWwQVJLCO3+HmkSCcbS/I2q9YLtHmZmZSjBTjo3Bvz/+JKUnMY/kO6rugKgkI9C41UUY9b0LVCbStEieYaRtS3lBQBAQBIIhIAQkGDKS3oqAuuMRSsdateFQbTq4Mpdnuw9vt5Le5IPdTrI7T26fDSJ55V01jGzt3OuEyQn/cWbiwauF6oTQq0ivOo0UH++bY9zYHTLvAnGEZI56ziQumLBqG+vK80p9MHLH+LMwtl2h4hFsLN2dHg2u0eLD9lAs3CfvEqpuUr3vkQMcsowePdo7uVefR4NxtL8jXI93EbjPYBLo9ydY2VilR/odZY9/rGbG98m7ZayG6i8///yzktQV71I0z9B/PHItCAgCgkC0CIgKVrTIHUb1VFLAK5Gq0a3/7asG6N6xPFgd66KLLgo64VV3L9h/P//h5cnb888/H/TgWCAs7IKTyz388MPKdW/9L1J81PtkN55/+MMfFPLBpIPdFYciH1yPPYmxHcLixYuhriir7amfHEmZJdhKs1ou3j+jwTVafBj3sWPHKpAsWbIkIDRs+8TCnpwOFYkG42h/RzhwJkuwOEDegUzVsj2NczTfUSb9c+bMUYauxjbxvg8mNGvWrFGSeMe5sxLNM+xsn1JfEBAEBAEVASEgKhLyGRQB3qJXV9zYu4+/igCTD9X7EnumUUXVfWe3sHx4C3sFYgLCK5fsTetwlGjxYdw2btyo7ByxdzE2oGbVjECH6v6YJ2YqSbnvvvt8VpN5ssTG5/wceQfrqquu6tWPIxpcO4PPZZddpuDFBtD+k+QvvvhCiZTOq/hqFOteDW7L4KPBONrfEdWmid97Njb3Fl7FZ8cXvEPCjhTU3ynvMj1xHs13lMfJnulY3n33XeU7rlzQf+z16oEHHgCrR3IAWcaysxLNM+xsn1JfEBAEBAEVAVHBUpGQz6AI8O4ET3TZDSa71L3wwguVVXKOUMzXy5YtU+r6BwPjyQCnsYE0ewjiP5y8Q8JqBBwpmoVtGAKprSiZh/h/0eDDExE26mfhSRdHsA4lqlcyVr3661//qngWY/KyYMECJXAb2y0wOWR1OCYyd9xxh6LSFarNeM+LBtfO4MNOGNjbFU+OOfbKuHHjlF0Rtkfg2Cr8/WHnCofSex4NxtH+jvBEmRc2VHe77E2Mf0v4/WcPfKyayTtYd911l499WU+9p9F+R3m8TKJOPPFEJcArexDke2cbIr5PdrzBaqe8CNQVEs0z7Ip+pQ1BQBAQBBgBISDyHoSFwIABA5RVcg4Axqo8fKjCNgO//vWvMXfuXDWp9ZMD27Fx5SuvvKJEMGZdexY2aGc3u+oqXGuFw+wkUnzYzkA1RI0UKt4BYdW1Rx55RHGLzBM6Fp4Y8sSHJzb8eShIpLjyPXcGHybSrIr1zDPPYP3/b+9OY2P63gCOP1Vq3xuiSGNv7RJKiJTUvlOE0MQaa1KJCFFe8EZRqSWlEREkRUQkeIFErLXT2GsNEWu1Ygm1FH/P4d5Mbzvzn3Z+Qzv9nqSde+4998ycz6U8Pdu1a+ZLXTUY0d9qF3Wn8dLwDIpjXNyfI7pXja5ClpKSYhZd0IUXNGkPqg5b0l9wWKtI/Ws7X/6O6mfXX/aEh4ebn7c6ZNJK2n4NSv7LQLY4z9D6PLwigAACvggE/Rp+8dOXCri37Anob/h08rOOvdZ/DK3VWzxJ6LKueo/+51nXn9dVXPS3zqTfAn/bR4eu6PPQIVo6Nt/dCk6l/fkU19UXH1356OnTp6LDukrzZH5vn31xjYvzc0Q/k86FsHoDNKDRnrtATPpPs/4d1T9P2tv8X6585fQq7jN01kMeAQQQ8FaAAMRbKcohgAACCCCAAAIIIICAzwJMQveZkAoQQAABBBBAAAEEEEDAWwECEG+lKIcAAggggAACCCCAAAI+CxCA+ExIBQgggAACCCCAAAIIIOCtAAGIt1KUQwABBBBAAAEEEEAAAZ8FCEB8JqQCBBBAAAEEEEAAAQQQ8FaAAMRbKcohgAACCCCAAAIIIICAzwIEID4TUgECCCCAAAIIIIAAAgh4K0AA4q0U5RBAAAEEEEAAAQQQQMBnAQIQnwmpAAEEEEAAAQQQQAABBLwVIADxVopyCCCAAAIIIIAAAggg4LMAAYjPhFSAAAIIIIAAAggggAAC3goQgHgrRTkEEPCrwMKFC6VJkybmKzo6Wr5+/Vqk91uzZo19/8CBA+X79+9Fup/CCCCAAAIIIPB3BIJ+/kp/5614FwQQQMC9QHZ2trRp00aysrJMoaVLl8ry5cvd3+ByJTMzUzp16iRfvnyR8uXLy9mzZ6VLly4uJThEAAEEEEAAgZIiQA9ISXkSfA4EyrhAaGiobNy40VZITEyU69ev23l3Bz9+/JDJkyeb4EPLLFmyhODDHRbnEUAAAQQQKAECBCAl4CHwERBA4LdAbGysjBs3zmS+ffsmU6ZMkby8PI88ycnJcuHCBVMmKipKEhISPJbnIgIIIIAAAgj8WwGGYP1bf94dAQQcAjk5OWYo1qtXr8yVFStWyKJFixylfmfv378vHTp0kNzcXKlSpYpkZGRIq1atCi3LSQQQQAABBBAoGQL0gJSM58CnQACBPwJ169aVTZs22R7Lli2Tu3fv2nnrQKevaQ+JBh+aVq5c6XXwoXNF7ty5I58/f7aqK/KrTpLXOqw5K0Wu4NcNL1++NF/FuZd7EEAAAQQQKK0CBCCl9cnxuREIYIGRI0fK+PHjTQs1SJg6dao418tISUmR9PR0U6Zfv34yZ84cjyIfPnyQ+Ph4adu2rVSrVk0iIyPNq+bnz58vnz598ni/XtT3Gzp0qLRo0cL0uGgd9evXl5o1a0rnzp0lNTW1wOfU+3RFroiICPO1Z88eE1B169ZNwsLCpEGDBtK6dWs5duyYFiUhgAACCCAQ8AIMwQr4R0wDESidAs6hWFu2bDGBiLbm+fPn5j/zGlTUrl1bbty4IQ0bNnTb0DNnzkhcXJw8evTIbZmWLVtKWlqaCSSchTQIWrx4saxbt0500run1KtXLzl69KgEBwfbxTQA0dW5NOlywRs2bJDHjx+bvPXt0KFDMmDAACvLKwIIIIAAAgErQA9IwD5aGoZA6RbQoVjao2AlnQfy5s0bk503b55o8KFJV87yFHw8fPhQYmJiTPChQYH2dly5ckXev38vly5dMpPWy5UrJ/fu3ZM+ffrI69evTb2u31avXi062V2Dj549e8rhw4fl2bNn8u7dO7l586asWrXKBEJ6z4kTJ2Tv3r2ut+c7TkpKMsFHjRo1ZMyYMdKxY0fTE9K3b9985cgggAACCCAQqAL0gATqk6VdCASIwIQJE2Tnzp2mNTNnzpRhw4bJoEGDTF5XzNq1a5fHlo4YMUL2798vQUFBcvDgQRk8eHCB8keOHDHntadi+vTpsnnzZruMrsYVHh4uL168MJPjL168aIZf2QX+HGivhxVEaE+G9mhYybUHRM+1a9fOrNxVuXJlU+Tjx49StWpVqzivCCCAAAIIBLQAAUhAP14ah0DpF9BeD92gUCdsa0+FzrnQYEB7PXTolQ7BcpdOnjwpOiRKk84j0WFc7pLuJbJt2zbzHrdv37YntF++fFlmzJgh2pOiPSEaoLhLOrdEgwldmevq1at2MWcAcv78eenatat9nQMEEEAAAQTKkgBDsMrS06atCJRCgTp16thDsXQIlAYf2puxdetWj8GHNvX06dN2i3W4k6ekPSua9D006LCSTi7XIVtv376VadOmWacLfa1Xr545rytkuUshISFslOgOh/MIIIAAAmVC4PesyDLRVBqJAAKlVWD48OEyduxY0RWkNGkvhK589f+Szuuw0rlz50R7Ntwl7WGxku4vUljSwEeTBhg6oV2XB9b30N6O48ePm8nxet3TRPWmTZuaXhYtR0IAAQQQQKAsChCAlMWnTpsRKIUC7du3twMQnbjtTXINJHQ/EW+T633WPRqg6OpV+/btE72uw6qKk5o1a1ac27gHAQQQQACBgBEgAAmYR0lDEEDAKWCtlFWhQoUizbnQvTlc04EDB0wPjG5g6Jp0pS4NjKKiomTIkCGiE+afPHniWqTAsTXxvMAFTiCAAAIIIFBGBAhAysiDppkIlEWB5s2by61bt0xvhS6dW5yVpjIyMkRX27KCD53MPmrUKDPR3Ln8rzX3w7lpYlm0p80IIIAAAgi4EyAAcSfDeQQQKPUCurmgJp2Tce3aNenevbvbNuXl5ZlApWLFivnKbN++XXJzc825tWvXmt3U8xX4k9H7rX1Kijs8q7B6OYcAAggggECgCbAKVqA9UdqDAAK2gO63YSVdYtdTSklJER0eFRYWZlbYsspaK2npBPRJkyZZpwu86gaEVg+IBiMkBBBAAAEEEChcgACkcBfOIoBAAAjo0KmIiAjTEt0DxAomnE3TXc0TExNFh07pTuj9+/e3i1jDtqxr9gWXA52UHhcXZ5+xAhH7BAcIIIAAAgggYAsQgNgUHCCAQKAJ6OTz9evXm2ZpAKE7lSclJUlOTo45p4FHamqq9O7d22x0qCdnz55tNjk0BX5969Gjh3UoulnhqVOn7BWwsrOzzapYMTEx9v1a2BqKZd/IAQIIIIAAAgjYAgQgNgUHCCAQiAIadOjcjUqVKpmJ5AsWLJDQ0FCzo3rjxo1l1qxZZlldbfvo0aMlOTk5H0NCQoJYS+emp6dLdHS06IaDuju7vsbGxooGMnPnzjVferNOWM/MzMxXDxkEEEAAAQQQ+C1AAMKfBAQQCHiB+Ph4s1mg9lRYk8yzsrLMkCttvE5W37Fjh+zevbvAJoHVq1cXnd8xceJEswO7ltceDt3UMDg42Exs100OdY8QDWCslJaWZh3yigACCCCAAAIuAkG/hiX8dMlziAACCAS0gK5QpXM2dBfzWrVqie5M3qhRIzu48NR4Hbr14MEDs+O53hcZGSkhISGebuEaAggggAACCDgECEAcIGQRQAABBBBAAAEEEEDAfwIMwfKfLTUjgAACCCCAAAIIIICAQ4AAxAFCFgEEEEAAAQQQQAABBPwnQADiP1tqRgABBBBAAAEEEEAAAYcAAYgDhCwCCCCAAAIIIIAAAgj4T4AAxH+21IwAAggggAACCCCAAAIOAQIQBwhZBBBAAAEEEEAAAQQQ8J8AAYj/bKkZAQQQQAABBBBAAAEEHAIEIA4QsggggAACCCCAAAIIIOA/AQIQ/9lSMwIIIIAAAggggAACCDgECEAcIGQRQAABBBBAAAEEEEDAfwIEIP6zpWYEEEAAAQQQQAABBBBwCBCAOEDIIoAAAggggAACCCCAgP8ECED8Z0vNCCCAAAIIIIAAAggg4BAgAHGAkEUAAQQQQAABBBBAAAH/CRCA+M+WmhFAAAEEEEAAAQQQQMAhQADiACGLAAIIIIAAAggggAAC/hMgAPGfLTUjgAACCCCAAAIIIICAQ4AAxAFCFgEEEEAAAQQQQAABBPwnQADiP1tqRgABBBBAAAEEEEAAAYfA/wCB9BbEy/bAUQAAAABJRU5ErkJggg==\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -i long_df -w 4 -h 3 --units in -r 200\n",
    "# import df from global environment\n",
    "# make default figure size 5 by 5 inches with 200 dpi resolution\n",
    "\n",
    "install.packages(\"ggplot2\", repos='http://cran.us.r-project.org', quiet=TRUE)\n",
    "library(ggplot2)\n",
    "ggplot(long_df, aes(x=startYear, y=value, col=variable)) +\n",
    "    geom_point() +\n",
    "    scale_x_continuous(breaks=round(seq(1894,2019, length=5))) +\n",
    "    labs(y='# Of Reviews A Movie Has', x='Year')\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "difficulty_dict = {'easy':'percentile90', 'medium': 'percentile925', 'hard':'percentile95'}\n",
    "difficulty = 'easy'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_difficulty_df(difficulty, clean_movie_df, votes_df, \n",
    "                        difficulty_dict =  {'easy':'percentile95', \n",
    "                                            'medium': 'percentile925', \n",
    "                                            'hard':'percentile90',\n",
    "                                            'impossible':'none'}):\n",
    "    if difficulty != 'impossible':\n",
    "        diff_df = clean_movie_df[clean_movie_df['startYear'] < 0]\n",
    "        for idx, row in votes_df.iterrows():\n",
    "            min_votes = row[difficulty_dict[difficulty]]\n",
    "            year_df = clean_movie_df[clean_movie_df['startYear'] == row['startYear']]\n",
    "            to_add = year_df[year_df['numVotes'] >= min_votes]\n",
    "            diff_df = diff_df.append(to_add)\n",
    "    else:\n",
    "        diff_df = clean_movie_df\n",
    "    return diff_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "easy_df = build_difficulty_df('easy', clean_movie_df, votes_df)\n",
    "easy_df.to_csv('data/easy.tsv', sep='\\t')\n",
    "med_df = build_difficulty_df('medium', clean_movie_df, votes_df)\n",
    "med_df.to_csv('data/med.tsv', sep='\\t')\n",
    "hard_df = build_difficulty_df('hard', clean_movie_df, votes_df)\n",
    "hard_df.to_csv('data/hard.tsv', sep='\\t')\n",
    "imp_df = build_difficulty_df('impossible', clean_movie_df, votes_df)\n",
    "imp_df.to_csv('data/imp.tsv', sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pull in specific release dates & poster URLS\n",
    "def add_addtl_data(file_name_in, file_name_out=None, rowrange=None, overwrite=False):\n",
    "    ia = imdb.IMDb()\n",
    "    selected_films_df = pd.read_csv(file_name_in, sep='\\t')\n",
    "    if rowrange is not None:\n",
    "        selected_films_df = selected_films_df.iloc[rowrange[0]:rowrange[1]+1]\n",
    "    releaseDate = []\n",
    "    posterURL = []\n",
    "    for idx, mv in tqdm(selected_films_df.iterrows(), total=selected_films_df.shape[0]):\n",
    "        try:\n",
    "            movie = ia.get_movie(mv['tconst'][2:]);\n",
    "            mv_list = movie.keys()\n",
    "            if 'original air date' in mv_list:\n",
    "                releaseDate.append(movie['original air date'])\n",
    "            else: \n",
    "                releaseDate.append(mv['startYear'])\n",
    "            if 'cover url' in mv_list:\n",
    "                posterURL.append(movie['cover url'])\n",
    "            else:\n",
    "                posterURL.append('')\n",
    "        except socket.timeout as e:\n",
    "            print(e)\n",
    "            print('Failed to retreive '+mv['primaryTitle']+', '+str(mv['startYear']))\n",
    "            releaseDate.append('')\n",
    "            posterURL.append('')\n",
    "    print('after loop')\n",
    "    selected_films_df['releaseDate'] = releaseDate\n",
    "    selected_films_df['posterURL'] = posterURL\n",
    "    relDate = selected_films_df['releaseDate'].str.replace(repl='',pat=')').\\\n",
    "        str.split(pat='(', expand=True)\n",
    "\n",
    "    selected_films_df['releaseDate'] = pd.to_datetime(relDate[0])\n",
    "    selected_films_df['releaseCountry']= relDate[1]\n",
    "    \n",
    "    if file_name_out:\n",
    "        if not os.path.isfile(file_name_out) or overwrite:\n",
    "            selected_films_df.to_csv(file_name_out, header='column_names', sep='\\t')\n",
    "        else: # else it exists so append without writing the header\n",
    "            selected_films_df.to_csv(file_name_out, mode='a', header=False, sep='\\t')\n",
    "    return selected_films_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'data/packets/movies_2004s.tsv'"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_list=list(set(os.listdir('data/packets')) - set(['.ipynb_checkpoints']))\n",
    "\n",
    "'data/packets/'+file_list[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d869eae1eb0548a28416ffc39d3f0af3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=7596), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "add_addtl_data('data/packets/'+file_list[0], file_name_out='data/packets/complete_'+file_list[0], overwrite=False)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "951"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('data/imp_complete.tsv', sep='\\t')['releaseDate'].isna().sum()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "mcenv",
   "language": "python",
   "name": "mcenv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}